the after-school period: a critical window for children’s...

The after-school period: a critical window for children’s health

behaviours by

Lauren Arundell Bachelor of Applied Science (Exercise and Sport Science) (Honours)

Submitted in fulfilment of the requirements for the degree of

Doctor of Philosophy

Deakin University, May 2016

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Redacted stamp

Publications and Conference Presentations from this

Thesis

Publications

No. Chapter Publication

1 Two Arundell L, Fletcher E, Salmon J, Veitch J, Hinkley T.

(2016) The correlates of after-school sedentary behavior

among children aged 5-18 years: a systematic review.

BMC Public Health. 2016; 16(1):1-10.

doi:10.1186/s12889-015-2659-4. Impact factor: 2.264

2 Two Arundell L, Fletcher E, Salmon J, Veitch J, Hinkley T.

A systematic review of the prevalence of sedentary

behavior during the after-school period among children

aged 5-18 years. International Journal of Behavioral

Nutrition and Physical Activity. 2016; 13 (1): p. 1-9.

Impact Factor: 4.111

3 Four Arundell, L, Salmon, J, Veitch, J, O'Connell, E,

Hinkley, T and Hume, C. (2013) 'Standardising the

'after-school' period for children's physical activity and

sedentary behaviour', Health Promotion Journal of

Australia, vol. 24, no. 1, pp. 65-7. Impact Factor 0.945

4 Five Arundell L, Hinkley T, Veitch J, Salmon J. (2015)

Contribution of the After-School Period to Children's

Daily Participation in Physical Activity and Sedentary

Behaviours. PLoS One 10(10):e0140132. Impact factor:

3.23

5 Six Arundell, L, Ridgers, ND, Veitch, J, Salmon, J,

Hinkley, T & Timperio, A. (2013) 5-year changes in

afterschool physical activity and sedentary behavior,

American Journal of Preventive Medicine, vol. 44, no.

6, pp. 605-11. Impact factor: 4.527

6 Seven Arundell L, Salmon J. Hinkley T, Veitch J. The

correlates of after-school physical activity and sedentary

behaviour, under review in BMC Public Health. Impact

factor: 2.264

Conference Presentations

Oral presentations

1. Arundell L*, Hinkley T, Veitch J, Salmon J. Contribution of the after-school

period to children’s health behaviour participation. 11th School of Exercise and

Nutrition Sciences Research Degree Symposium, Deakin University, Melbourne,

Australia. September 2015.

2. Arundell L*, Salmon J, Hume C, Veitch J Hinkley T. Children’s after-school

behaviours: intensity and type. Australasian Society for Behavioural Health and

Medicine (ASBHM), Auckland, New Zealand. February 2014.

3. Arundell L, Ridgers N*, Veitch J, Salmon J, Hinkley T, Timperio A. Changes in

after-school physical activity and sedentary behaviour over five years.

International Society for Behavioral Nutrition and Physical Activity (ISBNPA),

Gent, Netherlands. May 2013.

4. Arundell L*, Salmon J, Veitch J, Hume C. Associations between children’s

after-school activity preference and after-school physical activity and sedentary

behaviour. Australasian Society for Behavioural Health and Medicine (ASBHM),

Melbourne, Australia. February 2012.

5. Arundell L*, Salmon J, Veitch J, Hume C. Children’s health behaviours during

the after-school period. 8th Exercise and Nutrition Sciences, Higher Degree by

Research Student Symposium, Deakin University, Melbourne, Australia. October

2011.

6. Arundell L*, Salmon J, Veitch J, Hume C. Children’s sedentary behaviour

during the after-school period. Australian Conference of Science and Medicine in

Sport, Fremantle, Australia. October 2011.

7. Arundell L*, Salmon J, Veitch J and Hume C. Children’s health behaviours

during the after-school period. International Society for Behavioural Nutrition

and Physical Activity (ISBNPA) conference, Melbourne. June 2011.

8. Arundell L*. Reliability and validity of measures to assess children’s after-

school behaviours. 7th Exercise and Nutrition Sciences, Higher Degree by

Research Student Symposium, Deakin University, Melbourne, Australia.

November 2010.

9. Arundell L*. Children’s Physical Activity and sedentary behaviours during the

after-school period: a review. 6th Exercise and Nutrition Sciences, Higher

Degree by Research Student Symposium, Deakin University, Melbourne,

Australia. November 2009.

* denotes presenter

Poster presentations

1. Arundell L, Fletcher E, Salmon J, Veitch J, Hinkley T. The correlates of after-

school sedentary behavior among children aged 5-18 years: a systematic review.

International Society for Behavioural Nutrition and Physical Activity (ISBNPA)

conference, Edinburgh, Scotland. June 2015.

2. Arundell L, Salmon J, Veitch J, Hume C and O’Connell E. Defining the ‘after-

school’ period for children’s health behaviours. International Society for

Behavioural Nutrition and Physical Activity (ISBNPA) conference, Melbourne.

June 2011.

i

Abstract

Physical activity during childhood has many immediate and future physical,

social and mental health benefits. An emerging pool of evidence also suggests

that sedentary behaviours (i.e. behaviours that require little energy expenditure

and are performed in a seated/lying position) have detrimental health outcomes,

independent of physical activity. Accordingly, in 2014 the Australian Government

endorsed guidelines recommending every day children (5-12years) perform at

least an hour of moderate- to vigorous-intensity physical activity, limit electronic

media use to less than two hours, and interrupt prolong periods of sitting as often

as possible. Despite the associated health risks, the majority of Australian children

fail to meet these guidelines. The need to identify key periods of the day for

interventions targeting behaviour change is therefore evident.

The after-school period is an important, yet understudied time of the day where

children are able to perform both active and sedentary past time options without

the restriction of school timetabling. Interventions targeting after-school physical

activity and sedentary behaviours require an understanding of the correlates

associated with these behaviours to effectively target change. The exploration of

the prevalence and correlates of children’s after-school behaviours has been

limited to date by inconsistencies in the definition of ‘after-school period’ used,

cross-sectional samples, and studies that assess the correlates of behaviour from

only one of the domains within the ecological model. By addressing many of

these limitations, this thesis has made a novel contribution to the literature

examining children’s after-school physical activity and sedentary behaviour.

Abstract

ii

Firstly, to identify the current prevalence rates of children’s after-school physical

activity and sedentary behaviour, this thesis reviewed the literature to date

including systematically reviewing the prevalence of children’s after-school

sedentary time and sedentary behaviours from 29 papers. Despite a variety of

definitions of ‘after-school period’ used, children perform little physical activity

after-school and spend approximately half of the period sedentary. Importantly,

this time is comprised of a variety of screen- and non-screen based sedentary

behaviours (e.g. homework and social sedentary behaviours), providing a wealth

of potential intervention targets. As such interventions require an understanding

of the factors influencing participation, the correlates of after-school physical

activity and sedentary behaviour were also reviewed. Few and inconsistent

correlates of after-school physical activity, predominantly from the intrapersonal

and social domains of the ecological model have been identified in the literature

to date. Of 58 potential correlates of after-school sedentary behaviour identified

by the systematic review, only two non-modifiable correlates (sex and age) were

measured frequently enough to produce an overall association and the direction

varied according to the behaviour. No consistent modifiable correlates were

identified. The prevalence and correlate literature is currently limited by cross-

sectional data, samples predominantly from the US, and studies that examined the

correlates within only one of the domains of the ecological framework at a time.

To facilitate future research of after-school physical activity and sedentary

behaviour, and enable direct and accurate comparisons between studies, a

standardised definition of ‘after-school period’ is required. Using accelerometer

and activPAL inclinometer data from 308 children, the time spent sitting,

sedentary, in light-, moderate-, and moderate- to vigorous-intensity physical

Abstract

iii

activity were compared across three potential after-school periods: end-of school

to: 1) sunset; 2) 6pm; and 3) dinner time. No differences in the percentage of time

spent in any of the behaviours across the three definitions were identified.

Therefore the end-of school to 6pm is an appropriate definition and is used

throughout this thesis.

To address the gaps within the literature of children’s after-school physical

activity and sedentary behaviour, this thesis examined children’s after-school

behaviours cross-sectionally and longitudinally. After-school accelerometer

measured sedentary behaviour, light-, and moderate- to vigorous-intensity

physical activity and proxy-reported screen-based sedentary behaviour among

406 children (mean age 8.1 years) were examined. Children spent over half of the

after-school period sedentary (objectively measured), which accounted for only a

fifth of their daily sedentary behaviour. In contrast, children spent only 14% of

the after-school period in moderate- to-vigorous intensity physical activity, but

this contributed to almost a third of their daily moderate- to-vigorous intensity

physical activity levels. Of concern, children performed over 80% of their daily

screen-based sedentary behaviours during the after-school period, highlighting the

importance of the period for the accumulation of physical activity and sedentary

behaviours. This study also found that the behaviours children perform after

school also significantly impacts the likelihood of them achieving the physical

activity and sedentary behaviour guidelines.

To build upon these cross-sectional findings, children’s after-school physical

activity and sedentary behaviours over 5 years were examined. Two cohorts of

children were followed: younger children (aged 5-6 years) and older children

(aged 10-12 years) at baseline. Over a five year period, children’s after-school

Abstract

iv

sedentary behaviour increased; however, the contribution this period made to

daily behaviours remained relatively stable. Conversely, children’s after-school

moderate- to-vigorous intensity physical activity significantly declined,

particularly among girls and the older cohort as they transitioned from primary

(elementary) school to secondary school. Importantly, despite the decline in

actual minutes of moderate- to-vigorous intensity physical activity performed

after school, this period made a larger contribution to children’s daily moderate-

to-vigorous intensity physical activity levels over time. The after-school period

appears to become more important for the accumulation of moderate- to-vigorous

intensity physical activity as children progress through primary and into

secondary school and among girls, suggesting interventions should begin when

children are young to reduce these age-related changes and develop strategies to

target girls’ after-school physical activity.

Adding to the limited literature examining the correlates of children’s after-school

moderate- to-vigorous intensity physical activity and sedentary behaviour, this

thesis comprehensively examined correlates across three domains of the

ecological model among 354 children from the cross-sectional behaviour analysis

(mean age 8.2 years). Although 59 correlates were assessed, only five correlates

were significantly associated with either outcome behaviour after adjusting for

age, sex and clustering by school. Variables positively associated with moderate-

to-vigorous intensity physical activity included: sibling physical activity co-

participation, frequency of non-organised physical activity and the number of

days at a sporting club after school. Parents being concerned about their child’s

health behaviours was negatively associated with moderate- to-vigorous intensity

physical activity. Variables associated with sedentary behaviour included non-

Abstract

v

organised physical activity frequency (negatively associated) and the facilities to

be active not available (positively associated).

Only one variable, the frequency of non-organised physical activity, was

associated with both after-school physical activity (positive association) and

sedentary behaviour (negative association). This suggests that different

intervention strategies may be required when targeting physical activity and

sedentary behaviour performed during the after-school period. While few

correlates were significantly associated with after-school physical activity and

sedentary behaviour, these findings provide novel and valuable information that

can be used for intervention development.

Promoting non-organised physical activity participation may be a simple, feasible

and low cost intervention strategy to increase after-school physical activity and

reduce sedentary behaviour. In addition, sibling physical activity co-participation

and attending sporting clubs are also potential intervention strategies to increase

physical activity after school. To target after-school sedentary behaviour,

interventions should also target parental awareness of local physical activity

facilities or provide examples of how they can use the facilities they have in an

active way.

The findings from this thesis have highlighted that the after-school period holds

potential for children to perform active, screen- and non-screen based sedentary

behaviours. The period is also important for the accumulation of children’s daily

physical activity and sedentary behaviour and becomes increasingly so as they go

through primary school and into secondary school and among girls. Further,

changes in after-school behaviour may have significant impact on their likelihood

Abstract

vi

of achieving the associated physical activity or sedentary behaviour guidelines.

Although additional longitudinal research using purpose-developed and context-

specific survey items is warranted, this thesis provides information about the

influences on these behaviours that could be used to inform the development of

interventions to target children’s suboptimal physical activity and sedentary

behaviours during the after-school period.

vii

Acknowledgements

There are a great number of people who have made this thesis possible. Firstly to

my supervisors who really are a team of ‘supers’: Jo Salmon, Jenny Veitch and

Trina Hinkley. Jo, it has been a privilege to have had you as my PhD supervisor

for seven years. Your love of research is contagious. Thank you for the time you

have devoted to me, despite your unbelievable schedule. The opportunities and

support you’ve given me are beyond anything I could have imagined. Thank you.

Jenny, thank you for your advice, not only about all things PhD related, but also

about the young family-work-study juggle. You have shown me that it can be

done! Trina, thank you for your calming presence throughout my PhD journey.

Your advice and guidance has been invaluable. So too has your ability to remind

me about life outside of the PhD bubble. Thank you for your friendship. I would

also like to thank Clare Hume for fostering my research interest in the early days.

To the entire Behavioural Epidemiology Group for your support along the way, I

am very grateful to have worked alongside such a wonderful team. To my fellow

PhD students with whom I have shared this experience (and there have been many

of you over the past seven years), thank you for your support, advice and for

showing me that I too will complete this and come out on the other side!

I would particularly like to thank my work family, the J4.16 girls – Julie, Jacqui,

Kate, Jen, Eloise, Maria and everyone who has sat with us in between. You have

been with me along the entire journey - before and after every PhD meeting, for

each paper rejection and acceptance and you have listened to countless

presentation practises. Thank you for your support, advice, endless supply of

snacks and laughs, you have helped me get through this more than you know.

viii

Finally to my family who grew along the way. Mum and Dad, Louise and Phil,

Robert and Lauren, your endless support, never wavering belief in me and

countless babysitting hours has made this possible, and I am forever grateful.

Thank you. To my parents-in-law Michele and Graham, thank you for your

constant support and willingness to watch over my children so that I could write.

To my husband Dave, I could not have done this without you and I can’t thank

you enough for helping me get to the finishing line after seven years. Although

this has taken longer than anticipated, I wouldn’t change the reasons for anything.

To my beautiful children Charlotte and William, you weren’t here when I started

this but you were the motivation to finish and I dedicate this thesis to you. I hope

that it shows you both that you can achieve anything you set your mind to -

always remember “Whether you think you can or you think you can’t, you’re

right” [Henry Ford].

ix

List of Figures................................................................................................................... xi

List of Tables .................................................................................................................. xiii

List of Appendices .......................................................................................................... xvi

CHAPTER ONE Introduction ........................................................................................ 1

1.1 Structure of this thesis ................................................................................. 3

CHAPTER TWO Literature Review .............................................................................. 6

2.1 Defining physical activity and sedentary behaviour .................................... 6

2.2 Physical activity and health ......................................................................... 7

2.3 Sedentary behaviour and health ................................................................... 8

2.4 Physical activity and sedentary recommendations .................................... 10

2.5 Physical activity and sedentary behaviour assessment .............................. 11

2.5.1 Subjective measurement techniques ................................................ 11

2.5.2 Objective measurement techniques ................................................. 13

2.6 Prevalence of children’s physical activity and sedentary behaviour ......... 18

2.6.1 Prevalence of physical activity ........................................................ 18

2.6.2 Prevalence of sedentary behaviour ................................................. 21

2.7 The after-school period for children’s physical activity and sedentary

behaviour ................................................................................................... 22

2.8 Prevalence of children’s physical activity during the after school period . 24

2.9 Prevalence of children’s sedentary behaviour during the after-school

period (Paper One) ..................................................................................... 26

2.10 Contribution of the after-school period to children’s daily physical activity

and sedentary behaviour ............................................................................ 27

2.11 Theories and correlates of children’s behaviour ........................................ 29

2.12 Correlates of children’s after-school physical activity .............................. 33

2.13 Correlates of children’s after-school sedentary behaviour (Paper Two) ... 36

2.14 Summary of literature review .................................................................... 38

2.15 Thesis aims ................................................................................................ 39

Literature review Appendix One: Paper One: A systematic review of the

prevalence of sedentary behavior during the after-school period among

children aged 5-18 years. ........................................................................... 41

Literature review Appendix Two: Paper Two. The correlates of after-school

sedentary behaviour among children aged 5-18: a systematic review. ...... 57

CHAPTER THREE Context and methods overview .................................................. 72

3.1 Context of the studies within this thesis .................................................... 72

x

3.2 The Transform-Us! Study .......................................................................... 74

3.2.1 Aim of Transform-Us! ..................................................................... 74

3.2.2 Ethical approval for Transform-Us! ............................................... 75

3.2.3 Recruitment of Transform-Us! participants .................................... 75

3.2.4 My role in Transform-Us! ............................................................... 76

3.3 The Children’s Living in Active Neighbourhoods Study (CLAN) and the

Health Eating and Play Study (HEAPS) .................................................... 77

3.3.1 Aim of CLAN and HEAPS ............................................................... 78

3.3.2 My role in CLAN and HEAPS ......................................................... 78

3.3.3 Ethical approval for CLAN and HEAPS ......................................... 79

3.3.4 Recruitment of CLAN and HEAPS participants .............................. 79

CHAPTER FOUR Paper Three: Standardising the ‘after-school’ period for

children’s physical activity and sedentary behaviour .................................. 81

CHAPTER FIVE Paper Four: Contribution of the after-school period to children’s

daily participation in physical activity and sedentary behaviours .............. 85

CHAPTER SIX Paper Five: 5-Year Changes in Afterschool Physical Activity and

Sedentary Behavior ......................................................................................... 97

CHAPTER SEVEN Paper Six: The correlates of children’s after-school physical

activity and sedentary behaviour ................................................................. 107

CHAPTER EIGHT Thesis Discussion and Conclusion ............................................ 138

8.1 Overview and discussion of findings ....................................................... 139

8.1.1 Previous state of the literature ...................................................... 139

8.1.2 Prevalence of physical activity and sedentary behaviour during the

after-school period ........................................................................ 140

8.1.3 Contribution of the after-school period to daily physical activity and

sedentary behaviour levels ............................................................ 144

8.1.4 Correlates of physical activity and sedentary behaviour during the

after-school period ........................................................................ 147

8.2 Strengths and limitations of this thesis ........................................................... 152

8.3 Future research recommendations and directions ........................................... 156

8.4 Practical implications from this thesis ............................................................ 159

8.5 Conclusions .................................................................................................... 161

Thesis references ........................................................................................................... 164

Appendices ................................................................................................................. 177

xi

List of Figures

Chapter Two

Appendix One

Figure 1: Flow chart of results from systematic search conducted in 2015 .......... 4

Figure 2: Percentage of time children (5-12 years) and adolescents (13-18 years)

spend sedentary during the after-school period ....................................

Figure 3: Percentage of time children and adolescents spend in specific sedentary

behaviors during the after-school .........................................................

Appendix Two

Figure 1: Flow chart of search results ...................................................................

Chapter Four

Figure 1. Example of one child’s accelerometer measured after-school behaviours

during the three periods examined (end of school to 6 pm (18:00

hours), end of school to dinner time and end of school to sunset). SED,

sedentary time; LPA, light physical activity; MVPA, moderate-to-

vigorous physical activity) ....................................................................

Chapter Six

Figure 1: Children’s physical activity and sedentary time during the after-school

period .................................................................................................. 1

List of Figures

xii

Figure 2: Contribution of the after-school period to children’s daily physical

activity and sedentary time ................................................................

xiii

List of Tables

Chapter Two

Appendix One

Additional Table 1: Search strategy ......................................................................

Additional Table 2: Study characteristics .............................................................

Additional Table 3: PRISMA 2009 checklist ........................................................

Appendix Two

Table 1: Correlates of children’s after-school sedentary behavior reported in 4

findings .................................................................................................

Table 2: Correlates of children’s sedentary behavior that were reported in <4

findings (insufficient evidence) ............................................................

Table 3: Correlates of adolescents’ sedentary behavior that were reported in <4

findings (insufficient evidence) ............................................................

Additional File 1: Table S1: Study characteristics .

Chapter Three

Table 3.1: Characteristics of studies incorporated into this thesis ........................

List of Tables

xiv

Chapter Four

Table 1: Proportion of time spent in accelerometer-derived sedentary, light,

moderate and moderate-to-vigorous physical activity, as well as

inclinometer-derived sitting during three after-school periods .............

Chapter Five

Table 1: The mean minutes and percentage of the after-school period spent in

sedentary time (SED), light- (LPA) and moderate- to vigorous-intensity

physical activity (MVPA), and the contribution to daily behaviour and

achieving the physical activity (PA) guidelines .................................

Table 2: Parental proxy-reported screen-based sedentary behaviours during the

after-school period (mean minutes ±SD), and the contribution to daily

screen-based sedentary behaviours (±SD) and achieving the sedentary

behaviour (SB) guidelines (±SD) .......................................................

Chapter Six

Table 1: Children’s physical activity and sedentary time at baseline (T1),

M(SD) ................................................................................................. 1

Table 2: Mean changes in percentage of time spent in physical activity and

sedentary time after school over 3 and 5 years, b (95% CI) ............... 1

Table 3: Mean change in the contribution of the afterschool period to daily

physical activity and sedentary time, b (95% CI) ............................... 1

List of Tables

xv

Chapter Seven

Table 1: Generalised linear model analysis of the correlates of children’s after-

school moderate- to vigorous-intensity physical activity ...................


school sedentary behaviour, according to the domains of the ecological

model ..................................................................................................

Additional Table 1: Child self-reported and parent proxy-reported survey items

examining the intrapersonal, social environmental and physical

environmental correlates of children’s after-school physical activity and

sedentary behaviour ............................................................................

Chapter Eight

Table 8.1: The percentage of the after-school period spent in sedentary behaviour

(SED), light- (LPA) and moderate- to vigorous-intensity (MVPA)

physical from cross-sectional and longitudinal prevalence studies in this

thesis ................................................................................................... 1

xvi

List of Appendices

Appendix 2.1: Authorship Statement: Paper One

Appendix 2.2: Authorship Statement: Paper Two

Appendix 3.1: Transform-Us! Methods paper

Appendix 3.2: Transform-Us! Deakin University Human Research Ethics

Committee Approva1

Appendix 3.3: Transform-Us! Child Survey

Appendix 3.4: Transform-Us! Parent Survey

Appendix 3.5: CLAN Deakin University Human Research Ethics Committee

Approval

Appendix 3.6: HEAPS Deakin University Human Research Ethics Committee

Approval

Appendix 4.1: Authorship Statement: Paper Three

Appendix 5.1: Authorship Statement: Paper Four

Appendix 6.1: Authorship Statement: Paper Five

Appendix 6.2: Copywrite Permission: Paper Five

Appendix 7.1: Authorship Statement: Paper Six

1

CHAPTER ONE

Introduction

The physical, social and mental health benefits of childhood physical activity are

well established (Janssen and LeBlanc, 2010; Andersen et al., 2006; Strong et al.,

2005; Larun et al., 2006), while the evidence of negative health outcomes

associated with elevated childhood sedentary behaviour is mounting (Tremblay et

al., 2011b; Rey-Lopez et al., 2008; Russ et al., 2009). In response to these health

benefits and risks, Australia has created recommendations relating to the

minimum time children should be active and the maximum amount of time they

should spend sedentary each day. The Australian guidelines recommend children

(5-12 years) perform at least 60 minutes of moderate- to vigorous-intensity

physical activity each day (higher levels associated with additional health

benefits) and include activities that strengthen muscle and bone on at least three

days per week (Australian Government Department of Health, 2014). Many other

developed countries have similar guidelines for children’s physical activity

(Tremblay et al., 2011a; Department of Health (Scotland), 2011). In addition,

Australia is one of the first countries to endorse sedentary behaviour guidelines

for children. These state that children should minimise the time spent sedentary

by limiting electronic media use for entertainment to no more than two hours per

day (lower levels are associated with reduced health risks) and break up sitting as

often as possible (Australian Government Department of Health, 2014).

Despite the associated health risks, population data suggest that children are not

achieving these guidelines. In 2011-12, only 28% of Australian 5-11 year olds

Chapter One: Introduction

2

met the physical activity guidelines and only 36% achieved the sedentary

behaviour guidelines (Australian Bureau of Statistics, 2013). These rates are

similar to those in many other developed countries (Healthy Active Kids New

Zealand, 2014; Active Healthy Kids Canada, 2014; Active Healthy Kids England,

2014; National Physical Activity Plan Alliance, 2014) and highlight the need to

implement interventions targeting increases in physical activity and reductions in

sedentary behaviour. However, as there are considerable within-day differences in

children’s physical activity patterns (Trost et al., 2000), it is necessary to examine

different periods of the day to determine the appropriateness of targeting

children’s health behaviours during those time periods (Welk et al., 2000).

The after-school period, often termed the ‘critical window’, is a promising yet

understudied time period that may provide an opportune time to promote physical

activity and reduce sedentary behaviour. During after-school hours, children are

no longer restricted by the school time table and this period affords children more

discretion to choose engagement in active and/or sedentary pastimes. They may

also have more autonomy over these choices than at other times of the day.

Further, the context of the after-school period (i.e. where they are, who they are

with etc.) may differ to other times of the day (e.g. during school hours).

While there is an emerging literature on the after-school period in relation to

children’s physical activity (Hager, 2006; Fairclough et al., 2007; Cox et al.,

2006; Nilsson et al., 2009a), few studies have cross-sectionally or longitudinally

examined participation in both physical activity and sedentary behaviour during

this period or determined the contribution this period makes to daily physical

activity and sedentary behaviour levels. For effective intervention development

targeting this period, an understanding of the correlates specific to after-school


3

physical activity and sedentary behaviour is also needed. The aim of this thesis

was to examine children’s participation in, and the correlates of, physical activity

and sedentary behaviour performed during the after-school period.

1.1 Structure of this thesis

This thesis by publication begins with a literature review (Chapter Two) to

critique and synthesise the existing literature relevant to children’s physical

activity and sedentary behaviour during the after-school period. Contained in the

literature review are two systematic reviews: Paper One - A systematic review of

the prevalence of sedentary behavior during the after-school period among

children aged 5-18 years (under review in International Journal of Behavioral

Nutrition and Physical Activity); and Paper Two - The correlates of after-school

sedentary behaviour among children aged 5-18 years: a systematic review

(published in BMC Public Health). These reviews, in combination with other

sections of the literature review, highlight the lack of evidence regarding the

prevalence and correlates of after-school physical activity and sedentary

behaviours. Further, they provide a background and rationale for the additional

studies and papers included within Chapters Four through Seven of this thesis.

Chapter Three contains a detailed description of the studies incorporated within

this thesis including details of the study aims and recruitment process which is

often excluded within published manuscripts. Chapter Three also contains details

of my role within each study.

Three cross-sectional and one longitudinal study examining children’s after-

school physical activity and sedentary behaviour are presented in Chapters Four

through Seven. Chapter Four contains Paper Three (published in the Health


4

Promotion Journal of Australia) which developed a standardised definition of

‘after-school’, a need identified from the current literature. That paper examined

children’s physical activity and sedentary behaviours measured objectively via the

Actigraph GT3X accelerometer and PAL Technologies activPALTM inclinometer

using a variety of definitions of ‘after-school’. By comparing the findings, a

conclusion regarding a standardised definition of the ‘after-school’ period was

devised. This definition was used in the remaining studies within this thesis.

Chapter Five contains Paper Four (published in PLoS One) which cross-

sectionally examined children’s objectively measured after-school physical

activity and sedentary behaviour (via Actigraph GT3X accelerometer), and their

proxy-reported screen-based sedentary behaviours. That paper examined the

contribution that behaviours performed during the after-school period make to

daily physical activity and sedentary behaviour levels and to children achieving

the current physical activity and screen-based sedentary behaviour guidelines.

Chapter Six contains Paper Five (published in the American Journal of Preventive

Medicine) which builds on the findings from Chapter Five by examining after-

school behaviours longitudinally. That paper examined children’s after-school

physical activity and sedentary behaviours (measured by Actigraph accelerometer

GT1M), the contribution these make to daily behaviour levels and how this

changed over five years.

The cross-sectional and longitudinal exploration of children’s after-school

physical activity and sedentary behaviours presented in Chapter Five and Chapter

Six highlight how sedentary children and adolescents are after school. It also

shows that although only a small proportion of the after-school period is spent in

moderate- to vigorous-intensity physical activity, this period makes an important


5

contribution to children’s and adolescents’ daily physical activity levels.

Interventions targeting increases in children’s physical activity and reductions in

sedentary behaviours are therefore warranted. However, to be effective they

require an understanding of the period-specific correlates of these behaviours

which were examined in Chapter Seven.

Chapter Seven contains Paper Six (in preparation) which used an ecological

framework (Davison and Birch, 2001) to explore the intrapersonal (e.g.

enjoyment of physical activity, screen-based, social or academic sedentary

behaviours and sports competence etc.), social (e.g. after-school social norms, co-

participation with siblings, parents and peers, rules promoting or restricting

physical activity and sedentary behaviours etc.) and physical environment (e.g.

the child’s location, access to physical activity and sedentary behaviour

equipment in the home etc.) correlates of children’s objectively measured after-

school physical activity and sedentary behaviour.

Chapter Eight provides an overview and synthesis of the findings from all

chapters and discusses the strengths and limitations of this body of research.

Drawing on findings from this thesis and previously published literature, this

chapter provides suggestions for future research recommendations and directions,

and practical implications for targeting children’s after-school physical activity

and sedentary behaviour.

6

CHAPTER TWO

Literature Review

2.1 Defining physical activity and sedentary behaviour

Physical activity is defined as bodily movement produced by skeletal muscle that

increases energy expenditure above basal level (US Department of Health and

Human Services, 1996; Caspersen et al., 1985). Physical activity is characterised

by four components: frequency (how often it occurs), duration (how long it lasts),

intensity (how strenuous it is) and type (the type of activity) (Sallis and Patrick,

1994). Physical activity intensity is determined using the metabolic equivalent of

task (METS), where 1.6-3.9 METS is considered light intensity, 4-5.9 METS is

considered moderate intensity and ≥6 METS is considered vigorous intensity

(Trost et al., 2002a; Trost et al., 2011). Children’s physical activity is performed

in the domains of organised and non-organised activity during and outside of

school hours, active transport, domestic chores and active free play (Pangrazi,

2000). Children’s physical activity is sporadic, spontaneous and intermittent in

nature (Pangrazi, 2000; Bailey et al., 1995), with bouts of higher intensity

activities typically lasting 3 to 22 seconds (Bailey et al., 1995; Baquet et al.,

2007). Physical inactivity refers to the absence of, or inadequate participation in

physical activity; however, this terminology has occasionally been inappropriately

substituted with the term sedentary behaviour (Owen et al., 2000).

Sedentary behaviour refers to a distinct set of behaviours (Ainsworth et al., 1993)

requiring less than 1.5 METs and are performed during waking hours while sitting

or lying (Sedentary Behaviour Research, 2012). Examples include television (TV)

Chapter Two: Literature Review

7

viewing, computer, internet or electronic games use (screen time), school work

and reading (Lobstein et al., 2004). It is important to examine physical activity

and sedentary behaviours as groups of separate behaviours as evidence suggests

they have independent health outcomes, unique correlates, and are often only

weakly related (Tremblay et al., 2010; de Rezende et al., 2014; Stierlin et al.,

2015; Gorely et al., 2004; Melkevik et al., 2010).

2.2 Physical activity and health

Childhood physical activity has numerous physical, social and mental health

benefits (Janssen and LeBlanc, 2010; Andersen et al., 2006; Strong et al., 2005;

Larun et al., 2006). A systematic review of the health benefits of childhood

physical activity revealed that active children have a lower risk of overweight and

obesity, more favourable cholesterol and blood lipid profiles, lower blood

pressure levels, lower risk of metabolic syndrome, and higher bone mineral

density (Janssen and LeBlanc, 2010). Data from European (Andersen et al., 2006)

and American (Strong et al., 2005) children and adolescents have shown that

active children have fewer risk factors for cardiovascular disease and type 2

diabetes, including lower waist circumference (Andersen et al., 2006; Strong et

al., 2005), blood pressure (Andersen et al., 2006; Strong et al., 2005), glucose

levels (Andersen et al., 2006; Strong et al., 2005), cholesterol levels (Andersen et

al., 2006; Strong et al., 2005), elevated triglycerides (Andersen et al., 2006;

Strong et al., 2005) and insulin resistance (Andersen et al., 2006).

Children who participate in physical activity also have fewer depressive

symptoms (Janssen and LeBlanc, 2010; Larun et al., 2006), higher self-esteem,

better quality of sleep, greater social skills, better awareness of fair play and


8

teamwork and an increased sense of community belonging (Biddle et al., 2004;

Shilton and Naughton, 2001). Active children also have fewer emotional

problems such as hyperactivity and problems with their peers (Wiles et al., 2008).

In summary, there is strong evidence to suggest that childhood physical activity is

beneficial to children’s physical, mental and social health. However, evidence

also suggests that other behaviours children commonly perform, such as sedentary

pastimes, may also impact their health.

2.3 Sedentary behaviour and health

The evidence showing negative physical, social and mental health outcomes

associated with elevated sedentary behaviour during childhood is mounting

(Tremblay et al., 2011b; Rey-Lopez et al., 2008; Russ et al., 2009). TV viewing is

the most common sedentary behaviour measured; therefore associations with

health are often based on relationships with TV viewing time. Consistently,

childhood TV viewing has been positively associated with obesity both cross-

sectionally and longitudinally (Tremblay et al., 2011b; Rey-Lopez et al., 2008;

Chinapaw et al., 2011; Marshall et al., 2004). High levels of TV viewing are also

associated with elevated blood pressure (Pardee et al., 2007), and cardiometabolic

biomarkers of inflammation and endothelial function (Sardinha et al., 2008; Gabel

et al., 2015; Martinez-Gomez et al., 2012). Poor social and mental health is also

observed among children with high levels of TV viewing (Tremblay et al.,

2011b). A systematic review showed that children who watch more than two

hours of TV per day have poor self-esteem and pro-social behaviour (Tremblay et

al., 2011b). Each additional hour of TV viewing is also associated with increased

social-emotional problems and lower social competence (Russ et al., 2009).


9

Further, emerging evidence shows children who watch more than two hours of

TV per day have lower academic achievement (Tremblay et al., 2011b).

In addition to the immediate health implications, elevated levels of TV viewing in

childhood and adolescence have been associated with long-term health

consequences. These include risk of obesity (Hancox, Milne et al. 2004), poor

fitness (Tucker, 1986; Armstrong et al., 1998) and raised cholesterol in adulthood

(Hancox, Milne et al. 2004).

Evidence of associations between health and other sedentary behaviours is less

clear. A 2008 review of the association between computer and video game use

with overweight/obesity risk (Rey-Lopez et al., 2008) found a null association.

However the authors noted the lack of a clear definition of these sedentary

behaviours within the literature which required them to generate their own

behaviour groupings and draw conclusions based on these (TV viewing, video

game use including games consoles and computer use including playing computer

games and browsing the internet). Consequently, any significant findings may

have been lost when summarising the findings according to these groupings.

Elevated levels of total sedentary behaviours have also been shown to be

associated with increased cardiovascular disease and diabetes risk factors among

children (Pardee et al., 2007; Sardinha et al., 2008). In addition, evening screen

time of an hour or more is associated with higher risk of sleep problems

(Kubiszewski et al., 2014).

Given the positive physical, social and mental health outcomes associated with

childhood physical activity and the negative health outcomes associated with

sedentary behaviours, Australia and many other developed countries have


10

developed recommendations relating to how much of these behaviours children

should perform.

2.4 Physical activity and sedentary recommendations

In response to the evidence of health outcomes associated with performing

physical activity and sedentary behaviours, the Australian Government endorsed

physical activity and sedentary behaviour recommendations in 2014 for youth

aged 5-18 years (Australian Government Department of Health, 2014). These

recommendations are consistent with those from other developed countries

(Australian Government Department of Health, 2014; Tremblay et al., 2011a;

Department of Health (Scotland), 2011). They were developed according to

evidence supporting the minimum amount of physical activity required to obtain

health benefits during childhood and for setting limits on the maximum amount of

sedentary behaviours to prevent adverse health outcomes (Australian Government

Department of Health, 2014).

The recommendations state that every day children aged 5-12 years should

perform at least 60 minutes of moderate- to vigorous-intensity physical activity

that includes aerobic, muscle and bone strengthening activities (Australian

Government Department of Health, 2014). In addition, children should limit

sedentary behaviours, specifically their electronic media use for entertainment, to

less than two hours per day and break up long periods of sitting (Australian

Government Department of Health, 2014).

It is therefore important that children are as active as often as possible and limit

their sedentary behaviour. To examine the time that children spend being active

and sedentary, and to determine the proportion of children meeting the


11

recommendations, valid, reliable and appropriate instruments are required to

measure behaviour (Melanson and Freedson, 1996).

2.5 Physical activity and sedentary behaviour assessment

Measuring children’s physical activity and sedentary behaviour provides valuable

information on the prevalence and patterning of behaviour. When determining the

most appropriate measurement technique to use among a child population,

considerations must be given to participant burden, age and the data sought. The

techniques suitable for measuring children’s physical activity and sedentary

behaviour can be categorised as objective or subjective and are described briefly

below.

2.5.1 Subjective measurement techniques

Surveys, logs and diaries are commonly used subjective methods of behaviour

measurement. Surveys are frequently used for large studies of children due to

their practicality and participant acceptance (Melanson and Freedson, 1996).

Surveys provide extensive information on the frequency, intensity, type, duration

and domain of the physical activity or sedentary behaviour (Melanson and

Freedson, 1996). Surveys are an inexpensive and time effective method. Self-

report surveys have shown to have acceptable reliability among children as young

as 10 years (Telford et al., 2004) and acceptable validity when compared to direct

observation (Sirard and Pate, 2001). A limitation of self-report is social

desirability bias where participants report outcomes they believe are desirable or

pleasing to the researchers (Warnecke et al., 1997). Further, recall difficulties

(Melanson and Freedson, 1996) and poor time perception skills (Welk et al.,


12

2000) among children under 10 years may impact their ability to provide

information about time spent in specific behaviours. Proxy-report surveys, where

another person (usually a parent) completes the survey items about the child, are

often used to overcome a number of these limitations (Baranowski, 1988).

However, proxy-report relies on the reporters’ observation of the behaviours

being assessed, (Baranowski, 1988) which excludes data collection during the

times they are not with the child whose behaviour is being assessed (e.g. at school

or after-school care).

Diaries and logs require participants to record their physical activity and

sedentary behaviours during a pre-determined time frame (e.g. two days, one

week, etc.). A child-specific example is the Multimedia Activity Recall for

Children and Adolescents (MARCA) which uses child determined periods of

interest (i.e. asks child to identify when lunch, end of school, dinner etc. occurred)

(Ridley, 2005). The MARCA has high test-retest reliability (ICC ranging from

0.88 to 0.94) and moderate criterion validity (Spearman coefficients ranging from

0.36 to 0.45) (Ridley, 2005). The Bouchard Diary, an activity log often used in

adolescent populations, asks for the main behaviour performed at 15-minute

intervals (Bouchard et al., 1983). Total energy expenditure obtained from the

Bouchard Diary has been correlated with the Tritrac-R3D activity monitor in

young adults aged 18-23 years (r=0.74) (Wickel et al., 2006). Diaries and log

books are limited to the degree to which participants follow instructions (Sallis

and Saelens, 2000) and although comprehensive, they may be burdensome and

reactive (Melanson and Freedson, 1996).

In summary, subjective measures are suitable and cost-effective for examining

physical activity and sedentary behaviours in children (Melanson and Freedson,


13

1996), large or geographically diverse populations and for obtaining information

on non-time-dependant or descriptive measures among younger populations

(Welk et al., 2000; Adamo et al., 2009). However, a 2009 review of subjective

(e.g. surveys, diaries and logs) and objective measures (e.g. accelerometry, heart

rate monitoring or direct observation) of children’s physical activity concluded

that data collected from subjective measures overestimated participation in

comparison to objective measures (Adamo et al., 2009). Therefore the use of

objective measures should also be considered.

2.5.2 Objective measurement techniques

Various objective physical activity measurement methods have been established,

although not all are suitable for use among children (Melanson and Freedson,

1996). The doubly labelled water technique is a highly accurate objective measure

of energy expenditure but is unable to differentiate between the type, duration,

frequency or intensity of physical activity or sedentary behaviour (Melanson and

Freedson, 1996). Although also objective, heart-rate monitoring can produce large

individual differences (Melanson and Freedson, 1996) and be influenced by

genetic factors, temperature (heat), and stress (Montoye and Taylor, 1984; Epstein

et al., 2001). This limits the appropriateness of these two techniques for use when

examining children’s physical activity or sedentary behaviours. Direct

observation is considered the criterion measure of physical activity and it enables

period specific (e.g. school recess, after-school) behaviour to be examined (Sirard

and Pate, 2001). However, it is costly and has a high researcher burden in both the

data collection and analysis phases. Motion detectors such as accelerometers and

pedometers are often used when objectively examining children’s physical


14

activity due to their small size, durability (Melanson and Freedson, 1996) and

comfort for the participant (Janz, 1994). Pedometers can be used to estimate the

number of steps taken but do not measure type or intensity of physical activity

(Melanson and Freedson, 1996). Accelerometers and inclinomers are popular

devices for objective measurement among children and will now be described in

more detail.

Accelerometers

Accelerometers are sensitive to amount and intensity of movement and are a

practical and useful tool for child populations (Melanson and Freedson, 1996).

They are small, durable (Melanson and Freedson, 1996) and comfortable for the

participant (Janz, 1994). Accelerometers measure the acceleration and

deceleration of the body between 0.25 to 2.5 Hz, therefore capturing only human

movement (i.e. not recording movement from travelling in a vehicle) (Welk et al.,

2003; ActiGraph, 2009). Accelerometers are sensitive to the amount and intensity

of movement and provide information regarding the frequency and duration of

behaviours in real time (Melanson and Freedson, 1996). This enables data from

specific periods of interest, such as the after-school period, to be extracted. The

Computer Science Application (CSA) accelerometer has been validated for

assessing physical activity and sedentary behaviour among children in laboratory

(Trost et al., 1998) and field settings (Janz, 1994; Ott et al., 2000; Eston et al.,

1998; Puyau et al., 2002). The CSA has been developed into the Actigraph

accelerometer which is widely used in research examining the behaviours of

children.

Accelerometers collect movement counts in predetermined periods of time known

as epochs (ActiGraph, 2009). Previously, one-minute epochs have been typically


15

used in studies assessing child, adolescent and adult behaviours, in part, to

accommodate data storage capabilities of early accelerometer models (Trost et al.,

2000). However, due to the intermittent and sporadic nature of children’s

behaviour, shorter epochs (e.g. 5 seconds, 15 seconds) are recommended

(Edwardson and Gorely, 2010) to minimize any smoothing of intensity levels

observed over a 60 second period (Trost et al., 2005). Therefore, studies that have

used 5 second epochs should not be compared to studies that have used 60

seconds epochs (Edwardson and Gorely, 2010), particularly as estimates of

vigorous intensity physical activity differ when using 5 and 60 second epoch

lengths (Nilsson et al., 2002).

Accelerometer movement counts are typically interpreted according to previously

defined cut points which represent physical activity intensity levels (i.e. the lower

the movement counts the lower the intensity of the behaviour) (Puyau et al., 2002;

Sirard et al., 2005; Pate et al., 2006; Reilly et al., 2003; Freedson et al., 1998;

Trost et al., 2002a). These cut points have been calculated using algorithms

obtained from studies using direct comparisons of accelerometer counts and

oxygen consumption during nominated activities of varying intensity (e.g.

watching TV, running) (Puyau et al., 2002; Sirard et al., 2005; Pate et al., 2006;

Freedson et al., 1998; Trost et al., 2002a; Masse et al., 2005). The most

appropriate cut points to use among children remains a contentious issue despite

reviews (Cain et al., 2012), comparisons with direct observation (McClain et al.,

2008) and validation studies contrasting the most commonly applied cut points

across the physical activity spectrum (Trost et al., 2011).

Individual calibration producing person-or study-specific cut points may limit

some of the measurement error associated with accelerometry cut points.


16

However this is very time and resource intensive, reducing its suitability for large

population studies. New approaches to accelerometer-based physical activity

research propose using raw acceleration signals to which pattern recognition

techniques can be applied. (Troiano et al., 2014; John et al., 2013) This enables

the behaviours being performed to be identified (Troiano et al., 2014; Fairclough

et al., 2016). Such techniques are still in their infancy and require additional

evaluation, followed by unanimous use among researchers to facilitate study

comparisons.

A number of makes of accelerometers have been used within the literature, for

example Caltrac® (Computer Science and Applications, Hemokinetics Inc.),

Actigraphtm (CSA, Inc. Shalimar, FL), Actiwatch® (MiniMitter Company, Inc.,

Sunriver, OR) and the newly developed GENEActiv (Activinsights, Cambs,

United Kingdom). In addition, multiple models of accelerometers have been used

to assess children’s physical activity (e.g. Actigraph 7164, GT1M, GT3X,

GT3X+). Comparison studies have found agreement (via ICC) between models of

Actigraph in vertical axis counts (ICC:0.99, 95% CI:0.99-0.99), vector magnitude

counts (ICC: 0.98, 95% CI: 0.97-0.99), and moderate- to vigorous-intensity

physical activity duration (ICC: 0.99, 95%CI: 0.99-0.99), enabling direct

comparisons between the GT1M, GT3X and GT3X to be made (Robusto and

Trost, 2012). However, caution should be used when comparing the earlier model

(7164) and the GT1M, as the earlier model may underestimate time spent

sedentary and overestimate light-intensity physical activity (Corder et al., 2007).

Accelerometers are limited in that they may underestimate the energy cost of

common childhood movements such as water-based activities and cycling

(Pedišić and Bauman, 2015) and are unable to provide information on the specific


17

behaviours being performed which may be important for intervention

development (Welk et al., 2000). It is therefore suggested that they be used in

conjunction with a measurement technique that can capture the description of the

behaviour, such as surveys (Melanson and Freedson, 1996). Further, hip mounted

accelerometers are unable to assess postural changes (Hart et al., 2011); however

inclinometers can provide such information.

Inclinometers

Inclinometers, such as the activPALTM (Brockman et al., 2010), enable a

participant’s free-living time to be classified into periods of sitting, standing (not

walking) and walking (Brockman et al., 2010). Data obtained from the

activPALTM also includes information on transitions from sitting to standing and

standing to sitting. The device has been found to have acceptable validity among

children (Aminian and Hinckson, 2012; Ridgers et al., 2012b) and adults (Ryan

CG et al., 2008; Grant PM et al., 2006). As the device collects data in real time, it

can be condensed into periods of interest, for example the after-school period, to

allow analysis and comparison of specific periods. The limitations of

inclinometers are that their accuracy can be affected by unusual sitting postures,

for example partly kneeling (Aminian and Hinckson, 2012). As with

accelerometers, they are unable to provide information about participation in

specific behaviours (e.g. sitting watching TV viewing, or sitting completing

homework) (Aminian and Hinckson, 2012), or contexts in which behaviours

occur, which may be useful for interventions.

In summary, subjective measures provide behaviour-specific participation data,

while objective measures provide time-specific data. As such, a combination of

subjective and objective measures may be used to combat their respective


18

limitations (Melanson and Freedson, 1996). Data produced from these subjective

and objective measures provide valuable information on the prevalence of

children’s physical activity and sedentary behaviours.

2.6 Prevalence of children’s physical activity and sedentary behaviour

Population-level physical activity and sedentary behaviour data provide

information on the prevalence of children’s behaviours (Commonwealth

Scientific Industrial Research Organisation (CSIRO), 2008; Colley et al., 2012;

Matthews et al., 2008; Steele et al., 2010; Ruiz et al., 2011). International

prevalence data also enables comparisons of these behaviours between countries.

2.6.1 Prevalence of physical activity

The 2011-12 Australian Health Survey reported different prevalence rates for

children and adolescents meeting physical activity guidelines depending on the

criteria used (Australian Bureau of Statistics, 2013). When physical activity was

summed across the week and averaged per day, Australian children (aged 5-17

years) performed 91 minutes of physical activity per day and approximately 60%

met the physical activity guidelines of one hour per day (Australian Bureau of

Statistics, 2013). Lower rates of compliance were observed when the criterion

was 60 minutes on every day (28.4% of 5-11 year olds and 8.2% of 12-17 year

olds (Australian Bureau of Statistics, 2013)). Among both age groups, a greater

proportion of boys meet the physical activity guidelines than girls (5-11 year olds:

boys 29.2%, girls 27% and 12-17 year olds: boys 9%, girls 7.4%) although

statistically significant differences were not assessed (Australian Bureau of

Statistics, 2013).


19

The Active Healthy Kids Australia Report card (2014) combined data from five

large studies of Australian children’s (2-17 years) physical activity (Active

Healthy Kids Australia, 2014). This report provided valuable information on the

types of physical activities children are performing. Active play (non-organised

sport) provides the greatest contribution to children’s physical activity (42%),

followed by playing sport (34%), walking/bike riding (15%) and other activities,

predominantly chores (9%) (Active Healthy Kids Australia, 2014).

In relation to the duration of time that Australian children spend in specific types

of physical activities, parent-proxy report surveys show that children aged 5-17

years spend 19 minutes per day in active travel, which predominantly consists of

walking (Australian Bureau of Statistics, 2013). This duration increases cross-

sectionally from 13 minutes per day among 5-8 year olds to 18 minutes per day

among 9-11 year olds, 20 minutes per day among 12-14 year olds and 24 minutes

per day among 15-17 year olds (Australian Bureau of Statistics, 2013). Children

(5-17 years) also participate in 56 minutes of organised and non-organised

moderate- to vigorous-intensity physical activity per day. However, it is clear that

older children participate in less total organised and non-organised physical

activity than their younger counterparts. This is driven by the large age-related

reduction in non-organised moderate- to vigorous-intensity physical activity from

91 minutes per day among 5-8 year olds to 53 minutes per day among 9-11 year

olds, 33 minutes per day among 12-14 year olds and 20 minutes per day among

15-17 year olds (Australian Bureau of Statistics, 2013).

International Active Healthy Kids report cards facilitate international

comparisons. Achievement rates of 60 minutes per day of moderate- to vigorous-

intensity physical activity is poor among Canadian children (5-11 year olds: 7%,


20

and 12-17 year olds: 4%) (Active Healthy Kids Canada, 2014), higher among

English children (7-8 year olds: 51%) (Active Healthy Kids England, 2014) and

even higher among New Zealand children (10-14 year olds: 78%) (Healthy Active

Kids New Zealand, 2014). Only 42% of 6-11 year olds from the United States of

America performed at least 60 minutes of moderate- to vigorous-intensity

physical activity on at least five days per week (National Physical Activity Plan

Alliance, 2014).

Fifty-seven percent of English children (Active Healthy Kids England, 2014),

60% of New Zealand children (Healthy Active Kids New Zealand, 2014) and

75% percent of Canadian children (Active Healthy Kids Canada, 2014)

participate in organised physical activities and sports. Interestingly, Canadian

children show similar patterns to Australian children in that participation in

organised physical activities and sports declines with age and this is particularly

evident during the after-school period (Australian Bureau of Statistics, 2013),

(Active Healthy Kids Canada, 2014). However, among New Zealand children,

participation in organised sport increases with age during childhood (5-9 to 10-14

years) and then declines during adolescence (15-19 years) (Healthy Active Kids

New Zealand, 2014). These differences in participation rates may be due to

cultural influences and different measures which make direct comparisons

difficult.

Canadian parents reported that 69% of 5-19 year olds participated in outdoor play

(considered active play), however, data on duration is limited (Active Healthy

Kids Canada, 2014). Duration data from New Zealand parallels Australian data

showing age-related declines in active play from 140 minutes per day (5-9 year

olds) to 87 minutes per day (10- 14 year olds) (Healthy Active Kids New Zealand,


21

2014). This may also be due to cultural differences, however, different measures

and terminology in survey items (e.g. replacing active play for younger children

with organised sport for older children) may also impact the prevalence reported.

2.6.2 Prevalence of sedentary behaviour

The 2011-12 Australian Health Survey found that fewer than a third of Australian

children aged 5-17 years met the screen-based sedentary behaviour guideline of

less than two hours every day and the proportion declines steeply with age (36%

of 5-11 year olds down to 21% of 12-17 year olds) (Australian Bureau of

Statistics, 2013). A higher proportion of girls than boys in both age groups met

the recommendations (5-11 years: girls 40%, boys 31% and 12-17 years: girls

27%, boys 16%).

The proportion of Australian children watching any TV is fairly consistent among

children aged 5-8 years, 9-11 years, 12-14 years and 15-17 years(98%, 98%, 95%

and 90% respectively) (Australian Bureau of Statistics, 2013). The duration of TV

viewing averages 7.7 hours per week during the outside of school hours

(Australian Bureau of Statistics, 2013). However, among the four age groups,

there were large differences in the use of the internet for homework (10% of 5-8

year olds used it compared to 27% of 9-11 year olds, 35% of 12-14 year olds and

47% of 15-17 year olds) and non-homework/entertainment purposes (26% of 5-8

year olds used it compared to 48% of 9-11 year olds, 64% of 12-14 year olds

and84% of 15-17 year olds) (Australian Bureau of Statistics, 2013). Further, non-

screen based sedentary behaviours are also performed outside of school hours.

Over two-thirds of children 5-17 years read for pleasure (71.2%) and this is for an

average of 3.3 hours per week (Australian Bureau of Statistics, 2013). Eighty-two


22

percent of children 5-17 years complete homework or other study and on average,

this occurs for 3.5 hours per week (Australian Bureau of Statistics, 2013).

Internationally, 69% of Canadian children (aged 5-11 years) (Active Healthy Kids

Canada, 2014) and 60% of New Zealand children (5-9 years) (Healthy Active

Kids New Zealand, 2014) meet the sedentary behaviour guidelines with

compliance rates declining with age (Healthy Active Kids New Zealand, 2014;

Active Healthy Kids Canada, 2014). This is also evident among children from the

United States with 59% of 6-8year old children spending less than two hours per

day in screen-based sedentary behaviours and this declines to 48% among 9-11

year olds (National Physical Activity Plan Alliance, 2014).

In summary, children in Australia and many developed countries perform a

variety of physical activities, screen- and non-screen based sedentary behaviours.

However, few are meeting the physical activity and sedentary behaviour

guidelines (Australian Bureau of Statistics, 2013). Many of the behaviours

children participate in, such as sport club participation, active transport and TV

viewing, are likely to be performed outside of school hours, particularly during

the after-school period. Yet to date, the majority of interventions targeting these

behaviours have been implemented within the school setting (Van Kann et al.,

2015; Hayes and Van Camp, 2015; Kipping et al., 2014; Goh et al., 2014;

Dobbins et al., 2009; Kriemler et al., 2011). The after-school period, often termed

the ‘critical window’, may present an important and unique opportunity for

intervention.

2.7 The after-school period for children’s physical activity and sedentary

behaviour


23

With the majority of interventions targeting increases in children’s physical

activity during school hours (Van Kann et al., 2015; Hayes and Van Camp, 2015;

Kipping et al., 2014; Goh et al., 2014; Dobbins et al., 2009; Kriemler et al., 2011),

the after-school period is a surprisingly under-studied period of the day that could

provide a key target for intervention. This is especially the case given children are

not restricted by school timetabling during this time. After school, children are

often presented with opportunities to engage in both active and sedentary

pastimes (Australian Bureau of Statistics, 2012) and by 10 years of age, are

developing autonomy over their active or sedentary choices (Norman et al.,

2005).

To be able to synthesise this literature, a consistent definition of the after-school

period is required. Studies have examined physical activity and sedentary

behaviours during a variety of periods including 2pm-midnight (Nilsson et al.,

2009b), 3-5pm (Fairclough et al., 2007), 3-6pm (McGall et al., 2011; Wickel et

al., 2013) 3-7.30pm (Dengel et al., 2009), 3-11.30pm (Dzewaltowski et al., 2008),

3.30-8.30pm (Cooper et al., 2010), 4-6pm (Hesketh et al., 2008), 1.05pm until

bedtime (Loucaides et al., 2009), three hours immediately after school (Ramirez-

Rico et al., 2014), and from the school bell until bedtime (Rushovich et al., 2006).

This creates challenges when aiming to draw comparisons between studies as, for

example, the influences on a child’s behaviour when dismissed from school at

3.30pm may differ from the factors influencing behavioural choice at 6.30pm.

Further research on a consistent definition of the after-school period is needed.

To determine the potential of this period for intervention, it is important to first

establish how active and sedentary children are after school, and then determine

whether these levels of engagement make a substantial contribution to meeting


24

public health guidelines. Following this, an understanding of the correlates of

children’s after-school physical activity and sedentary behaviour is required. As

the correlates of children’s after school physical activity and sedentary behaviour

are likely to differ to the correlates of these behaviours performed during school

hours, it is important to identify factors specific to the after-school period. This

will provide valuable information for the development of interventions targeting

the after-school period. The remainder of this literature review will synthesise the

evidence in relation to the prevalence of children’s physical activity and sedentary

behaviour after school and the correlates of these behaviours during this period.

The abstracts from two systematic reviews (one published in BMC Public Health

and the other under review in the International Journal of Nutrition and Physical

Activity) written as part of this PhD are included in section 2.9 and section 2.13

and appended in full to the end of this literature review.

2.8 Prevalence of children’s physical activity during the after school period

Although, the definition of after-school period varies considerably between

studies, the literature to date provides an overview of the physical activity levels

of children and adolescents during this important period. Data from the Australian

2007 National Children’s Nutrition and Physical Activity Survey shows that

Australian children (n=794, 10-13.9 years) perform on average 20.9 minutes of

moderate- to vigorous-intensity physical activity during the 90 minutes directly

after school (Stanley et al., 2011). Internationally, a small study of English

children (n=58, 7-11 years) measured physical activity levels during two after-

school periods (3-5pm and 5-7pm) via four-day accelerometry. Boys and girls

spent more time in moderate- to vigorous-intensity physical activity during the


25

post-school period (3-5pm: 13.2 and 10.6 mins respectively) compared with the

early evening period (5-7pm: 8.8 and 7.9 mins respectively) (Fairclough et al.,

2007). Using a self-report four-day time use diary, adolescents from the UK

(n=1484, aged 15 years) reported their after school activities between 3.30-

6.30pm at 15-minute intervals (Atkin et al., 2008). Boys and girls participated in

21 and 19 minutes of physical activity respectively after school (Atkin et al.,

2008).

Nilsson and colleagues (Nilsson et al., 2009b) used an after-school period of 2pm

or 3pm to midnight when examining accelerometer data from the European Youth

Heart Study (EYHS). Nine-year old boys and girls from Denmark, Portugal,

Estonia and Norway performed between 34-52 minutes and 24-39 minutes of

moderate- to vigorous-intensity physical activity respectively during this period

(Nilsson et al., 2009b). Among 15-year olds, the participation levels were lower

with boys performing 18-45 minutes and girls performing 20-31 minutes per day

(Nilsson et al., 2009b). Decelis and colleagues (Decelis et al., 2014) used 2pm to

6.59pm as their after-school period and found that Maltese boys and girls (10-11

years) performed moderate- to vigorous-intensity physical activity for 24.3 and

17.2 minutes of the period respectively.

The after-school period used by Nilsson and colleagues (Nilsson et al., 2009b)

was approximately twice the length of the period used by Decelis and colleagues

(Decelis et al., 2014), four times the length of the period used by Atkin and

colleagues (Atkin et al., 2008), five times the length of the period used by

Fairclough and colleagues (Fairclough et al., 2007) and six times the length of

Stanley and colleagues (Stanley et al., 2011). Therefore, direct comparisons are

difficult as behaviours performed at 6pm are likely to differ from behaviours


26

performed at 9pm. However, evidence suggests that the after-school period

provides opportunities for physical activity among youth and subsequently, it

holds potential for intervention implementation. As children’s overall physical

activity levels change over time (Australian Bureau of Statistics, 2013), children’s

after-school physical activity levels are also likely to change. However, to date

little is known about the longitudinal changes of children’s after-school physical

activity.

The after-school period also provides opportunities for children to perform

sedentary behaviours. The following section contains a systematic review of the

prevalence of child and adolescent sedentary behaviour during the after-school

period which is currently under review in the International Journal of Behavioral

Nutrition and Physical Activity.

2.9 Prevalence of children’s sedentary behaviour during the after-school

period (Paper One)

This section of the literature review is a systematic review titled A systematic

review of the prevalence of sedentary behavior during the after-school period

among children aged 5-18 years. It is currently under review (first revision

completed) in the International Journal of Behavioral Nutrition and Physical

Activity and presented as an Appendix at the end of this literature review. The

abstract presented below provides a summary of the findings.

Background: Independent of physical activity levels, youth sedentary behaviors

(SB) have negative health outcomes. SB prevalence estimates during

discretionary periods of the day (e.g. after-school), inform the need for targeted


27

period-specific interventions. This systematic review aimed to determine

children’s and adolescents’ SB prevalence during the after-school period.

Methods: A computerized search was conducted in October 2015 (analysed

November 2015). Inclusion criteria were: published in a peer-reviewed English

journal; participants aged 5-18 years; measured overall after-school sedentary

time (ST) objectively, and/or specific after-school SBs (e.g. TV viewing)

objectively or subjectively; and provided the percentage of the after-school period

spent in ST/SB or duration of behavior and period to calculate this. Where

possible, findings were analyzed by location (e.g. after-school care/‘other’

locations). The PRISMA guidelines were followed.

Results: Twenty-nine studies were included: 24 included children (≤12years),

four assessed adolescents (>12years) and one included both; 20 assessed ST and

nine assessed SB. On average, children spent 41% and 51% of the after-school

period in ST when at after-school care and other locations respectively.

Adolescents spent 57% of the after-school period in ST. SBs that children and

adolescents perform include: TV viewing (20% of the period), non-screen based

SB (including homework; 20%), screen-based SB (including TV viewing; 18%),

homework/academics (13%), motorised transport (12%), social SB (9%), and

screen-based SB (excluding TV viewing; 6%).

Conclusion: Children spent up to half of the after-school period in ST and this is

higher among adolescents. A variety of screen- and non-screen based SBs are

performed after school, providing key targets for interventions.

2.10 Contribution of the after-school period to children’s daily physical

activity and sedentary behaviour


28

Recognising the suboptimal physical activity levels among children (Australian

Bureau of Statistics, 2013; Active Healthy Kids Canada, 2014; Healthy Active

Kids New Zealand, 2014; Active Healthy Kids England, 2014), the after-school

period may provide a valuable contribution to children’s daily physical activity

levels. Evidence among Australian children is limited, while international studies

suggests that children perform 46% of their daily physical activity levels

(accelerometry measured) between 3pm-9pm (Hager, 2006) and take over half of

their daily pedometer steps after school (Flohr et al., 2006). Four-day activity log

data (completed at 15-minute intervals) from UK adolescents (n=1484, aged 15

years) showed that boys and girls performed 41% and 44% of their non-school

based physical activity respectively between 3.30pm-6.30pm (Atkin et al., 2008).

There is less evidence relating to the contribution of the after-school period to

overall sedentary behaviours. However, it has been shown in an American sample

(n=80, 9-12 years) that boys and girls watched 72% and 66% respectively of their

daily TV between 3-9pm (Hager, 2006).

Overall very few studies have examined the contribution of the after-school

period to daily physical activity and sedentary behaviour levels and the majority

of these are cross-sectional and the literature regarding longitudinal behaviors is

limited. Additional research to determine the contribution of the after-school

period to overall physical activity and sedentary behaviour, particularly among

Australian samples is warranted. However, as with determining prevalence rates,

an accurate and consistent definition of the after-school period is required.

To develop effective interventions that target increases in physical activity and

reductions in sedentary behaviours during the after-school period, a better

understanding of the correlates of these behaviours is required. Theoretical


29

models of behaviour may assist in understanding the potential correlates of

children’s activity choices during the after-school period and how they may be

maintained.

2.11 Theories and correlates of children’s behaviour

Section 2.6 of this thesis identified that many children fail to meet the physical

activity and sedentary behaviour guidelines, and sections 2.8 and 2.9 highlighted

that there is an opportunity to target increases in children’s physical activity and

reductions in their sedentary behaviours during the after-school period.

Behavioural theories can help guide our understanding of the factors influencing

behaviour and identify strategies for interventions. Numerous theoretical models

have been developed, adapted and used to facilitate the exploration of children’s

physical activity and sedentary behaviour and identify the potential correlates of

these behaviours (Glanz et al., 2002; Bandura, 1986; Stokols, 1996; Becker et al.,

1977; Prochaska and DiClemente, 1982; Ajzen and Driver, 1992). Health

promotion programs and interventions with a theoretical foundation are more

likely to produce successful outcomes (Salmon et al., 2007). The theoretical

models frequently used in physical activity and sedentary behaviour epidemiology

explore behaviour change through individual, social and physical environmental

pathways. Commonly used theories targeting individual characteristics include

the Health Belief Model, the Theory of Reasoned Action, the Transtheoretical

Model of Behaviour Change and the Social Cognitive Theory.

The Health Belief Model is generally applied to health outcomes, risks and

benefits. It involves linear pathways to generate an individual’s perceived threat

of the problem (i.e. their susceptibility to the problem combined with their


30

perceived seriousness of the problem), and their outcome expectations (i.e.

perceived benefits and perceived barriers). The perceived threat and outcome

expectations act directly on their self-efficacy or perceived ability to carry out the

desired behaviour (i.e. increase physical activity or decrease sedentary behaviour)

(Nutbeam and Harris, 2004). Given that children are not likely to be motivated to

be active for health reasons, this model has limited application to youth

populations.

The Theory of Reasoned Action (TRA) posits that there are relationships between

influences, intentions and behaviour and assumes a linear progression from these

factors and relationships to behavioural change (Glanz et al., 2002). The

influences, which are based on individuals’ attitudes towards behaviour (i.e.

behavioural beliefs and evaluation of behavioural outcomes) and subjective norms

(i.e. normative beliefs and motivation to comply), determine behavioural intention

which is considered the most direct determinant of behaviour (Glanz et al., 2002;

Nutbeam and Harris, 1998). The TRA considers only a limited number of social

influences, potentially underestimating the social situation’s impact on behaviour

(Glanz et al., 2002; Nutbeam and Harris, 1998). It has, however, been used

prolifically in child and adolescent physical activity research (Trost et al., 2002b;

Saunders et al., 1997).

The Transtheoretical Model of Behaviour Change is founded on the principle that

at any time an individual is at one of five levels of motivation or readiness to

change (i.e. precontemplation, contemplation, preparation, action, maintenance or

relapse) (Nutbeam and Harris, 2004). The circular model permits movement

between the stages and allows for entry or exit at any stage (Nutbeam and Harris,

2004). Public health programs must therefore develop intervention strategies for


31

individuals in each stage of change to either progress to the next stage (e.g. move

from contemplation to preparation) or to remain in the stage (remain in

maintenance). This model has been applied more sparingly in physical activity

studies with children and youth, and has been found to be an inconclusive

correlate in recent years (Bauman et al., 2012).

Social cognitive theory (SCT) attempts to explain behaviour based on a process of

reciprocal determinism of the behaviour itself, personal factors and the

environment or situation in which the behaviour is performed (Bandura, 1986).

The behaviour can be influenced by the individual’s cognitive factors including

self-efficacy, outcome expectations and behavioural capability (Nutbeam and

Harris, 2004; Bandura, 1986; Nutbeam and Harris, 1998). The environment can

modify the behaviour through social influences (e.g. observational learning,

reinforcement, participatory learning and role modelling) and structures within

the environment (e.g. physical surroundings, access to and availability of

facilities) (Nutbeam and Harris, 2004; Bandura, 1986; Nutbeam and Harris,

1998). This theory has been applied frequently to studies that aim to understand

and influence child and adolescent physical activity (Salmon et al., 2009).

Theories targeting behaviour change through the individual do not incorporate the

environment as an independent predictor of behaviour (Glanz et al., 2002;

Nutbeam and Harris, 1998) despite evidence that the physical environment is an

important predictor (Sallis et al., 1997; Biddle et al., 2004; Veitch et al., 2005;

Burdette et al., 2004; Epstein and Roemmich, 2001; Norman et al., 2005).

Although the social cognitive theory includes an environmental construct, the

theory posits that individuals interpret their environment which may result in

diverse responses from different people, or from the same person at different


32

times (Nutbeam and Harris, 2004; Bandura, 1986; Nutbeam and Harris, 1998).

Behavioural changes beyond the individual level are therefore limited when using

psychosocial theories.

As a consequence of this limitation, and growing recognition of the importance of

the role of environment in influencing behaviour, ecological models have been

increasingly applied to health behaviour research. Such models propose that

behaviour change is influenced by the social and physical environments in

addition to intrapersonal attributes (Bronfenbrenner, 1989). Ecological models are

comprised of three universal domains: intrapersonal (relating to the individual

person), social (relating to the social environment) and physical [relating to the

physical environment), each containing influences that differ according to the

target behaviour and population (Bronfenbrenner, 1989; Stokols, 1996; Stokols et

al., 1996). Ecological models enable the complex nature of one’s environment to

be analysed, whereby actual and perceived characteristics are equally noted

(Stokols, 1992). The influences in each domain of the ecological model may be

drawn from other theories, for example self-efficacy from Bandura’s SCT

(Bandura, 1986) and behavioural beliefs from the TRA (Glanz et al., 2002).

Reviews have highlighted the effectiveness of ecological models to frame

interventions among adolescents and the need to target all domains of the model

(Perry et al., 2012). Further, interventions targeting specific topics (e.g. physical

activity) and implemented in specific settings (e.g. schools) have commonly used

an ecological approach. (Golden and Earp, 2012) The use of an ecological

framework would therefore enable the understudied correlates of children’s

physical activity and sedentary behaviour during the after-school period to be

explored and grouped according to their position within the ecological model.


33

2.12 Correlates of children’s after-school physical activity

The correlates of children’s (8-14 years) after-school physical activity have

recently been evaluated in a review by Stanley and colleagues in 2012 (Stanley et

al., 2012). This paragraph presents a brief summary of the findings of that review

which examined literature published between 1990 and January 2011 (n=10

papers included). All papers were cross-sectional, were predominantly among

samples from the United States (n=7 studies) and assessed physical activity via

objective measures (accelerometer n=5 studies), self-report survey (n=4 studies)

or a combination of objective and self-report (n=1 study) (Stanley et al., 2012).

The authors found being a boy and having access to physical activity facilities in

the neighbourhood such as playgrounds, dance studios etc. were positively

associated with after-school physical activity. Age and TV viewing/playing video

games were negatively associated with children’s after-school physical activity

while peer support had an inconsistent association. There was a null association

between ethnicity, family support, number of facilities (in the home or

neighbourhood environment not specified), access to equipment (in the home or

neighbourhood environment not specified) and neighbourhood safety and after-

school physical activity.

Since this review was published, four additional papers have examined correlates

of children’s after-school physical activity: two examining Australian samples

(Stanley et al., 2014; Engelen et al., 2015), one from the United States (Chaoqun

et al., 2012) and one from the United Kingdom (McMinn et al., 2013). The

majority of the correlates identified within these papers are within the

intrapersonal and social domains of the ecological framework. Self-efficacy was


34

found to be positively associated with children’s after-school physical activity

(Chaoqun et al., 2012) while parental education was negatively associated

(McMinn et al., 2013).

Stanley and colleagues (Stanley et al., 2014) examined the correlates by sex and

found more intrapersonal correlates were significantly related to after-school

physical activity among boys than girls. Among boys (n=200, aged 11.7 years,

47% of the sample in that study), positive associations with objectively measured

after-school physical activity and behavioural attributes/beliefs, self-efficacy,

perceived competence, perceived barriers, perceiving sufficient time to be active

after school, social support, weather and access to facilities/equipment were

observed (Stanley et al., 2014). Stanley and colleagues also examined associations

between the reasons boys chose to be active after school and their after-school

physical activity. Positive associations between after-school physical activity and

their decision to perform an organised sport after school because they want to

improve their skills, meet new people, they have no one to play with and are

seeking social support were observed. The only reason positively associated with

after-school physical activity among girls (n=223, aged 11.7 years, 53% of the

sample in that study) was because it gets you fit (association also seen among

boys) (Stanley et al., 2014).

Aspects of the social environment were also associated with children’s after-

school physical activity levels. Children with social support (combined parental,

peer and teacher support, and parental encouragement) (Chaoqun et al., 2012),

family social support (McMinn et al., 2013) and those who are allowed to play

anywhere in the neighbourhood (McMinn et al., 2013) are more active than peers

without these factors. In contrast, children whose parents restrict walking/cycling


35

to a friend’s house and sedentary behaviours are less active after school (McMinn

et al., 2013). The unexpected positive relationship between parent’s restriction of

sedentary behaviours and their child being less active is likely due to the cross-

sectional nature of the data as causation cannot be established. For example, the

child may have been less active and consequently the parent restricted their

sedentary behaviour, however this cannot be determined from the available data.

As these studies were among samples from the United States (Chaoqun et al.,

2012) and United Kingdom (McMinn et al., 2013), additional research examining

the impact of the social environment on children’s after-school physical activity

levels among Australian children is required.

There is less evidence regarding the physical environment and children’s after-

school physical activity. However, Engelen’s 2015 study (Engelen et al., 2015)

found that children are more active when outdoors after school compared to when

they are inside. This study was among a small sample of young children (n=20

children aged 5-7 years), highlighting the need for further research among larger

samples including older children (e.g. 5-12 years).

As after-school care is a frequently attended location during the after-school

period (Mullan, 2012), an emerging literature has examined children’s behaviours

at this location. It appears that the physical environment is particularly important

when the correlates of children’s after-school physical activity performed while at

after-school care are examined. Evidence shows that children are more active

when after-school care active recreation sessions are conducted outside compared

to inside, and for shorter duration (Rosenkranz et al., 2011a). Research has further

explored the correlates of children’s structured and unstructured physical activity

sessions while at after-school care (Rosenkranz et al., 2011b). Gender (being


36

male), enjoyment of physical activity and self-efficacy for physical activity were

positively associated with physical activity during structured physical activity

sessions, whereas only gender (being male) was positively associated with

physical activity during unstructured sessions (Rosenkranz et al., 2011b). The

lack of correlates associated with physical activity during unstructured sessions

may be due to the variety of physical activities performed during unstructured

sessions, whereas children would have been performing similar behaviours during

the structured sessions.

Evidence of the correlates of children’s after-school physical activity is emerging,

however additional studies examining correlates across the intrapersonal, social

and physical environment domains among large Australian samples is required to

inform intervention development. While there is a previous review of the

correlates of children’s after-school physical activity (Stanley et al., 2012), there

is no review of the correlates of children’s after-school sedentary behaviour.

Given the health outcomes associated with sedentary time and sedentary

behaviours and the prevalence rates of these during the after-school period,

identifying of the correlates associated with these behaviours is warranted.

2.13 Correlates of children’s after-school sedentary behaviour (Paper Two)

This section of the literature review is a systematic review titled The correlates of

after-school sedentary behavior among children aged 5-18 years: a systematic

review published in BMC Public Health. The manuscript is appended to the end

of this literature review and below is the abstract as a summary of the findings.


37

Background: Children and adolescents spend a large proportion of the after-

school period in sedentary behaviors (SB). Identifying context-specific correlates

is important for informing strategies to reduce these behaviors. This paper

systematically reviews the correlates of children’s and adolescents’ after-school

SB.

Methods: A computerized literature search was performed in October 2015 for

peer-reviewed original research journal articles published in English before

October 2015. Eligibility criteria included: 1) sample aged 5-18 years; 2)

quantified the amount of SB or component of this that the children/adolescents

were performing after school; 3) a measure of SB as the dependent outcome; and

4) the association between potential correlates and after-school SB.

Results: Data were synthesized in October 2015. Thirty-one studies met the

eligibility criteria: 22 studies among children (≤12 years), six among adolescents

(>12 years), two had a combined sample of children and adolescents and one

cohort followed children from childhood to adolescence. Findings were separated

by after-school location i.e. after-school programs (n=4 studies) and unidentified

locations (n=27). There was insufficient evidence to draw conclusions on all but

two of the 58 potential correlates: sex and age. Among children at unidentified

locations there was a null association between sex (male) and overall after-school

SB, a null association between sex (male) and after-school TV viewing, a positive

association between age and overall after-school SB and an inconsistent

association between age and after-school TV viewing. No correlates of after-

school sedentary behaviour while at after-school programs were identified.

Conclusions: Only two correlates have been investigated frequently enough to

determine an overall association; neither correlate is modifiable. Due to the lack


38

of consistent investigation of potential correlates, further evidence is required to

accurately identify potential intervention targets

2.14 Summary of literature review

In reviewing the literature, it is evident that despite public health

recommendations, children in many developed countries perform suboptimal

levels of physical activity and sedentary behaviour. These behaviours performed

during childhood can result in immediate and future health implications; therefore

intervention strategies must target increases in physical activity and reductions in

sedentary behaviour from a young age. To increase the effectiveness, such

strategies require an understanding of key periods throughout the day where

children are able to engage in active and sedentary past times. The after-school

period provides a potentially important opportunity for the promotion of

children’s physical activity and a reduction in sedentary behaviours. However, a

clear definition of the after school period is lacking and required for future

studies. Little is known about the cross-sectional and longitudinal prevalence of

children’s after-school behaviours or the contribution the behaviours performed

during the after-school period make to overall daily physical activity and

sedentary behaviours levels.

The ecological model provides a useful framework for understanding various

levels of influence on children’s behaviours during the after-school period.

However, few studies have examined the correlates of children’s physical activity

and sedentary behaviour during the after-school period, particularly among large

Australian samples, and across all three domains of the ecological model

(Bronfenbrenner, 1989). As the after-school period provides children with the


39

opportunity to be active and sedentary, a greater understanding of the influences

on these behaviours is required for tailoring intervention strategies targeting the

after-school period.

2.15 Thesis aims

The overall aim of this thesis is to examine children’s and adolescents’

participation in, and the correlates of, physical activity and sedentary behaviour

performed during the after-school period. Specifically, the aims of each chapter

are:

Chapter 2: Review the current literature examining children’s physical activity

and sedentary behaviour with a focus on the after-school period. This

includes reviewing the prevalence of children’s and adolescents’ after-

school physical activity and sedentary behaviour; and reviewing the

correlates of children’s and adolescents’ after-school physical activity

and sedentary behaviour.

Chapter 3: Provide an overview of the studies from which data are used in this

thesis. This chapter explains the methodology of these studies and the

candidate’s involvement in them.

Chapter 4: Develop a standardised definition of the ‘after-school period’ for

future research examining children’s physical activity and sedentary

behaviour.

Chapter 5: Describe children’s after-school physical activity and sedentary

behaviours cross-sectionally, establish the contribution this makes to

daily participation in those behaviours and examine the association


40

between participation in after-school physical activity and sedentary

behaviours and achieving the physical activity and sedentary behaviour

guidelines.

Chapter 6: Examine the prevalence of children’s after-school behaviours

longitudinally and the contribution this period makes to daily physical

activity and sedentary behaviour levels over five-years.

Chapter 7: Examine the intrapersonal, social and physical environment correlates

of children’s after-school physical activity and sedentary behaviour

using an ecological framework.

Chapter 8: Discuss and synthesise the findings from this thesis with consideration

of previous literature and provide recommendations for future research.

Chapter Two: Literature Review. Appendix One: Paper One: A systematic review of the prevalence of sedentary behavior during

the after-school period among children aged 5-18 years.

41

Literature review Appendix One: Paper One: A systematic review of the

prevalence of sedentary behavior during the after-school period among

children aged 5-18 years.

This appendix contains the full manuscript of the abstract contained in Section

2.9. Below is a systematic review of children and adolescents’ after-school

sedentary behaviour prevalence which is published in the International Journal of

Behavioral Nutrition and Physical Activity (Impact Factor: 4.111) as:

Arundell L, Fletcher E, Salmon J, Veitch J, Hinkley T. 2016 A systematic review

of the prevalence of sedentary behavior during the after-school period among

children aged 5-18 years. International Journal of Behavioral Nutrition and

Physical Activity, 13(1): p. 1-9.

The Authorship Statement for this manuscript is contained in Appendix 2.1

REVIEW Open Access

A systematic review of the prevalence ofsedentary behavior during the after-schoolperiod among children aged 5-18 yearsLauren Arundell*, Elly Fletcher, Jo Salmon, Jenny Veitch and Trina Hinkley

Abstract

Background: Independent of physical activity levels, youth sedentary behaviors (SB) have negative healthoutcomes. SB prevalence estimates during discretionary periods of the day (e.g., after-school), inform the need fortargeted period-specific interventions. This systematic review aimed to determine children’s and adolescents’ SBprevalence during the after-school period.

Methods: A computerized search was conducted in October 2015 (analysed November 2015). Inclusion criteriawere: published in a peer-reviewed English journal; participants aged 5-18 years; measured overall after-schoolsedentary time (ST) objectively, and/or specific after-school SBs (e.g., TV viewing) objectively or subjectively; andprovided the percentage of the after-school period spent in ST/SB or duration of behavior and period to calculatethis. Where possible, findings were analyzed by location (e.g., after-school care/‘other’ locations). The PRISMAguidelines were followed.

Results: Twenty-nine studies were included: 24 included children (≤12 years), four assessed adolescents (>12 years) andone included both; 20 assessed ST and nine assessed SB. On average, children spent 41 % and 51 % of the after-schoolperiod in ST when at after-school care and other locations respectively. Adolescents spent 57 % of the after-school periodin ST. SBs that children and adolescents perform include: TV viewing (20 % of the period), non-screen based SB (includinghomework; 20 %), screen-based SB (including TV viewing; 18 %), homework/academics (13 %), motorised transport (12 %),social SB (9 %), and screen-based SB (excluding TV viewing; 6 %).

Conclusion: Children spent up to half of the after-school period in ST and this is higher among adolescents. A variety ofscreen- and non-screen based SBs are performed after school, providing key targets for interventions.

Trial registration: PROSPERO registration number CRD42015010437

Keywords: Children, Adolescents, Sedentary behavior, After-school hours, Prevalence

Abbreviations: METS, Metabolic equivalents; Cpm, Counts per minute; BEACHES, Behaviours of eating and activity forchild health; SOFIT, System for observing fitness instruction time

BackgroundSedentary behaviors are typically performed in a sit-ting/lying position and result in minimal energy ex-penditure (≤1.5 metabolic equivalents [METS]) [1].Evidence highlighting the negative health outcomes ofsedentary behavior during childhood independent ofphysical activity levels is mounting [2]. For example,extensive TV viewing is positively associated with

body composition and decreased academic achieve-ment among children [2]. Many developed countrieshave endorsed recommendations that either place alimit on the time children should spend engaged inspecific sedentary behaviors (e.g., Australia andCanada recommend less than 2 h of screen time perday [3, 4]) or recommend minimising time spent sed-entary (e.g., UK guidelines recommend minimisingthe time spent sedentary for extended periods [5, 6]).Despite these guidelines, the majority of children ex-ceed sedentary behavior recommendations [7–10].

* Correspondence: [email protected] for Physical Activity and Nutrition Research, Deakin University, 221Burwood Highway, Burwood, VIC, Australia

© 2016 The Author(s). Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, andreproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link tothe Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Arundell et al. International Journal of Behavioral Nutrition and Physical Activity (2016) 13:93 DOI 10.1186/s12966-016-0419-1

42

One period of the day that has the potential to make asubstantial contribution to children’s daily sedentary be-havior levels is the after-school period. During thisperiod, children may have more choice over the behav-iors they perform compared to other times of the day,such as during school hours. Further, children performthe majority of their recreational sedentary behavior dur-ing this period [11]. For example, children perform 84 %of their daily screen-based sedentary behaviors andaccrue 80 % of the daily sedentary behavior guidelines(no more than two hours per day in front of screens)during the after-school period [11]. Although defined as‘the end-of-school to 6 pm’ [12], many studies use a var-iety of definitions of after-school [13–15] which makescomparing the raw minutes engaged in sedentary behav-ior after school difficult as longer periods provide agreater opportunity to be sedentary. Therefore, identify-ing the percentage of time that children and adolescentsengage in sedentary behavior after school is importantfor informing whether this period represents a potentialintervention target.Given public health guidelines focus on limiting

screen-based sedentary behaviors as well as total seden-tary time, both the prevalence of engagement in specificbehaviors such as TV viewing and screen-time, as wellas the total time spent sedentary during this periodshould be examined. This literature is yet to be synthe-sized and reviewed systematically. Therefore, the aim ofthis paper was to systematically review the percentage oftime children and adolescents spend during the after-school period in 1) ‘sedentary time’ defined as overallaccumulated sedentary behavior measured objectively,and 2) distinct ‘sedentary behaviors’ particularly thosepertinent to the guidelines (e.g., TV viewing), measuredobjectively or subjectively

MethodsThis review is registered with PROSPERO (registrationnumber: CRD42015010437).

Search procedureA computerized search using the EBSCOhost search en-gine was conducted for peer-reviewed original researchjournal articles published in English before October2015. The following databases were searched: AcademicSearch Complete, CINAHL Complete, Education Re-search Complete, MEDLINE, MEDLINE Complete,PsycARTICLES, Psychology and Behavioral SciencesCollection, PsycINFO and SPORTDiscus with Full Text.The key words in the search were age (“school age” ORyouth OR young OR child* OR adolescen*), AND seden-tary behavior (sedentar* OR television OR TV OR screenOR “electronic games” OR inactiv*), AND after-schoolperiod (after-school OR “after school” OR afternoon OR

evening OR “critical window” OR “critical hours”). Refer-ence lists of retrieved articles were also examined for po-tential papers. See Additional file 1: Table S1 for anexample search strategy.

Inclusion criteriaStudies were eligible for inclusion if they incorporatedchildren aged 5-18 years and used an objective meas-ure to assess overall after-school ‘sedentary time’ and/or used an objective or subjective measure to assessone or more individual after-school ‘sedentary behav-iors’ (e.g., TV viewing, computer use). In addition, be-cause of study variability in the duration of the after-school period, the percentage of the after-schoolperiod spent in sedentary behavior or enough infor-mation for this to be calculated also needed to be re-ported. That is, the paper needed to report both theduration of sedentary behavior and the length of theafter-school period whereby the proportion of theafter-school period spent sedentary could be calcu-lated as follows: (duration of sedentary behavior/length of after-school period)*100. Studies were in-cluded if they examined behaviors in the afternoononce school had finished, regardless of the periodstart and finish times.

Exclusion criteriaStudies examining ‘outside of school’ sedentary be-havior were excluded as this often included behav-iors performed before school or on weekends.Studies of special populations (e.g., overweight/obeseparticipants or children with a disability) were ex-cluded to allow for generalizability to the broaderpopulation. Papers examining subjective measures ofoverall sedentary time (i.e., the total time childrenwere sedentary) were excluded due to the variabilityin survey items and sedentary behaviors examinedbetween studies (for example, studies included a var-iety of combinations of TV viewing, computer use,DVD use, homework etc.). This variance in the com-bination of individual behaviors as contributors tooverall sedentary time would have prevented accur-ate comparisons with the objective measures of sed-entary time or with other studies using a differentcombination of subjectively measured sedentary be-haviors to constitute overall sedentary time.Eligibility was initially determined through a review

of the title and abstract by two authors (LA and EF,inter-rater reliability of initial screening was deter-mined by percent agreement and found to be 83 %agreement). The full-text of eligible studies were thenlocated and reviewed.

Arundell et al. International Journal of Behavioral Nutrition and Physical Activity (2016) 13:93 Page 2 of 9

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Data extraction and synthesisData for children (sample aged ≤12 years) and adoles-cents (sample aged > 12-18 years) were analyzed separ-ately. Results for boys and girls are reported separatelyin this review if there were significant differences. Allsedentary behaviors (e.g., TV viewing, motorised trans-port etc.) were examined to enable an exploration of thetime spent in each behavior during the after-schoolperiod. The average proportion of the after-schoolperiod spent in sedentary time and each sedentary be-havior was then calculated. Where accelerometry wasused to assess overall sedentary time, results were sepa-rated and examined according to the accelerometer cutpoint used to provide a cut point-specific estimate ofsedentary time. This was calculated by summing theproportion of the after-school period spent sedentaryfrom all studies that used the cut point and dividing thisby the number of those studies.As the durations of the ‘after-school’ period varied

greatly between studies (see Additional file 2: Table S2),comparisons were made via t-tests of the estimated per-centage of sedentary time among studies using an after-school period of ≤ 180 min and >180 min (based on thedefinition of end-of-school bell time to 6 pm beingapproximately 180 min). No differences were observed(p = 0.143), therefore all studies were analysed together.This also aligns with previous findings that comparedthe percentage of time spent sedentary during threeafter-school period lengths (end-of-school to 6 pm, end-of-school to sunset and end-of-school to dinner time)and found no differences [12].The PRISMA guidelines [16] were followed in report-

ing this review with the exception of conducting a meth-odological quality or risk of bias assessment. Nomethodological quality or risk of bias assessment wasperformed as the existing tools identified [17, 18] con-tained components specific to intervention or longitu-dinal studies. Therefore, those tools are not appropriatefor prevalence reviews as previously noted in a system-atic review of the prevalence of young children’s(<2 years) sedentary behavior [19]. Similarly, a previoussystematic review of children’s sedentary behavior preva-lence [20] did not include assessment of risk of bias.

ResultsFive-hundred and seventy papers were identified,screened and assessed for their eligibility (Fig. 1) and 29studies met the inclusion criteria. Of these, 20 assessedoverall after-school sedentary time and nine assessedafter-school sedentary behaviors. Among the studiesassessing overall sedentary time, 16 included children(sample aged ≤12 years) [11–13, 21–33], three includedadolescents (sample >12-18 years) [34–36], and one in-cluded both age groups [37]. Among the nine studies

assessing sedentary behaviors, eight included children[38–45], and one included adolescents [46]. The eligiblepapers were published between 1996 and October 2015and were analysed in November 2015. Study samplesranged from 20 to 2053 (mean 578) and over half of thestudies (n = 15) had a sample of fewer than 500 partici-pants. Study characteristics can be found in Additionalfile 2: Table S2.

Country of studyThirteen of the included studies were from the UnitedStates [22–24, 27, 29, 33, 35, 38, 39, 41, 42, 44, 45], withAustralia [11, 12, 25, 43], Canada [30, 31] and theUnited Kingdom [13, 21, 28, 32, 37, 46] also having mul-tiple studies. One study was identified from each of NewZealand [26], Ireland [34] and Portugal [36] and onestudy had a combined sample from Bulgaria, Taiwan andthe United States [40].

Child’s after school locationAmong the 20 studies assessing after-school sedentarytime, three assessed behavior while the children were atafter-school care [22, 23, 29]. No studies examined ado-lescents’ behaviors while at after-school care. Theremaining 17 studies either did not report where thechildren were after school or noted that they were at avariety of places. These studies were grouped together asat ‘other locations’ [11–13, 21, 24–28, 30–37]. No stud-ies investigating sedentary behaviors assessed behaviorswhen children were at after-school care, therefore allwere considered ‘other locations’ (n = 9) [26, 38–46].

Scr

eeni

ngIn

clud

edE

ligib

ility

Iden

tific

atio

n Records identified through database

searching (n = 570)

Records after duplicates removed (n = 568)

Records screened (n = 568)

Records excluded (n = 517)

Full-text articles assessed for eligibility

(n = 51)

Full-text articlesexcluded as not able to calculate percentage of

after-school SB (n = 22)

Studies included in qualitative synthesis

(n = 29)

Duplicates removed (n = 2)

Fig. 1 Flow chart of results from systematic search conductedin 2015


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After-school sedentary timeMeasurement toolsThe majority of studies measured sedentary time using theActiGraph accelerometer (n = 15); however, a variety of cutpoints were used to indicate sedentary time including <50counts per minute (cpm) [36], <100 cpm [11–13, 23, 26,28, 29, 32, 33, 37], < 300 cpm [30, 31], < 800 cpm [35], and<1.5METS [24]. Of the remaining five studies, one used theActical accelerometer with a sedentary cut point of<100 cpm [25], two used direct observation (modified ver-sion of BEACHES [Behaviours of Eating and Activity forChild Health] [27], and SOFIT [System for Observing Fit-ness Instruction Time] [22]), one used the RT3 tri-axial ac-celerometer with a cutpoint of <288 cpm [21] and one usedthe activPAL where sedentary was defined as sitting/lyingdown [34].

Percentage of after-school sedentary time by sexFigure 2 shows the percentage of time children andadolescents spend sedentary during the after-schoolperiod by location, measure and cut point. On aver-age, children spent 49.5 % (range 16.1 - 88.9 %) andadolescents spent 56.6 % (range 27.7 - 88.9 %) of theafter-school period sedentary.

Percentage of after-school sedentary time by locationAs shown in Fig. 2, results varied depending on the child’slocation. Children attending after-school care spent onaverage 41.1 % (range 16.1-56.1 %) [22, 23, 29, 33], andchildren at other locations spent on average 50.6 % (range

27.8 %-73.5 %) [11–13, 21, 24–28, 30–33, 37] of the after-school period sedentary.

Percentage of after-school sedentary time by cut pointResults also varied when different cut points wereused. Findings from accelerometer studies that exam-ined sedentary time using 100 cpm showed that chil-dren spent on average 42.3 % of the after-schoolperiod sedentary [11–13, 23, 25, 26, 28, 29, 32, 33,37], whereas the average time children spent seden-tary after school when using <300 cpm as the cutpoint [30, 31] was 71.2 % of the period. Among ado-lescents, the studies that used <50 cpm [36] showedthat on average adolescents spent 26.9 % of theperiod sedentary and in comparison the studies thatused <800 cpm [35] showed adolescents spent onaverage 82 % of the after-school period sedentary.

After-school sedentary behaviorsMeasurement toolsA variety of subjective measurement tools were used toassess a range of after-school sedentary behaviors. Fivestudies assessed after-school TV viewing [38, 40, 43, 45,46]. Seven studies reported screen-based sedentary be-haviors and these were separated into two groups de-pending on whether or not their measure included TVviewing: four studies measured screen-based sedentarybehaviors including TV viewing [39, 41, 42, 44] andthree studies measured screen-based sedentary behaviorsexcluding TV viewing [40, 43, 46]. One study measured

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social sedentary behaviors [46], three measured home-work/academics [43, 45, 46], three measured non-screenbased sedentary behavior including homework/aca-demics [41, 42, 44], one measured non-screen based sed-entary behavior excuding homework/academics [43],and two measured motorised transport. [43, 46] The ma-jority of studies used child self-report surveys askingchildren to report their after-school “free time” behav-iors; [46] or previous day recall in 30-min blocks [41],one-hour blocks [40], in child-specific blocks (e.g., be-fore/after child specified meal/snack) [43], or in 15 minintervals (via telephone interview) [42, 44, 45]. Onestudy used parental proxy-report of behaviors in 15-minintervals [39] and another used observation to capturethe time children spent watching TV [38].

Percentage of time spent in specific after-school sedentarybehaviorsFigure 3 shows the percentage of the after-school periodspent in specific sedentary behaviors. As only one studyreported adolescents’ after-school sedentary behaviors[46], these findings are presented alongside the children’safter-school sedentary behavior studies [38–45]. Sevenfindings from five studies [38, 40, 43, 45, 46] reportedthe percentage of the after-school period spent watchingTV. TV viewing averaged 20.4 % (range 12.6 - 31 %) ofthe after-school period which was the highest percentagefor any sedentary behavior (Fig. 3). The second largestpercentage of the after-school period was spent perform-ing non-screen based sedentary behaviors includinghomework (mean 20.3 %, range 10 - 29.2 %) [41, 42, 44].This was followed by screen-based sedentary behaviors

(including TV viewing;18.2 %, range 8.5 - 25.3 %) [39,41, 42, 44], homework/academics (12.9 %, range 6 -15.5 %) [43, 45, 46], motorised transport (12.1 %, range9.4 - 16.6 %) [43, 46], social sedentary behaviors (adoles-cent boys 7.9 %, girls 10.1 %) [46], screen-based seden-tary behaviors (excluding TV viewing; 5.5 %, range 1.4 -8.3 %) [40, 43, 46], and non-screen based sedentary be-haviors excluding homework/academics, such as reading,sitting quietly, writing, playing cards/puzzles/boardgames (3.7 %) [43].

DiscussionThis systematic review examined the prevalence of chil-dren’s and adolescents’ sedentary time and sedentary be-haviors during the after-school period. The findingshighlight that children spent between 41-51 % of theafter-school period sedentary and that adolescents aremore sedentary than children (57 %). TV viewing andother screen-based behaviors make up just 26 % or lessof this period. Other non-screen based sedentary behav-iors (e.g., social sedentary behaviors, motorized trans-port, homework, and reading) comprise 54 % of theafter-school period; however, it is possible several ofthese behaviors occur concurrently [47, 48]. The per-centage of time spent sedentary after school is greaterthan other periods of the day, such as recess and lunch-time, where children also have discretion over their be-havior choices. For example, children aged 5-6 years and10-12 years spend approximately 15 % and 14 % of re-cess sedentary respectively, and 22 % and 21 % of lunch-time sedentary respectively [49]. Further, recess andlunchtime contribute 1.8 % and 6 % of children’s daily

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Fig. 3 Percentage of time children and adolescents spend in specific sedentary behaviors during the after-school period. Abbreviations: m =male,f-female, *adolescent sample


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sedentary behavior time compared to the after-schoolperiod which contributes 26 % of daily sedentary behav-iors [21]. Subsequently, it would appear that the after-school period is a key period that holds great potentialfor interventions to target reductions in sedentary time.Further, findings suggest that interventions may need totarget other specific behaviors, such as motorised trans-port and social sedentary behaviors, in addition toscreen-based sedentary behaviors which have tradition-ally been targeted for change.This review also suggests that children spent less time

sedentary when in after-school care compared with‘other locations’. This may be due to fewer sedentarypastime options (such as TV viewing and computer use)being available at after-school care. Further, after-schoolcare may have more active structured and unstructuredpastime options and facilities (e.g., active free play andorganised sporting activities that use the school oval andsports equipment), and children may have more friendsto be active with at after-school care compared to otherlocations. However, further research is needed to sup-port this suggestion.Findings from the included studies were highly vari-

able. Children at after-school care are sedentary for16.1 % to 56.1 % of the after-school period, children atother locations are sedentary for 27.8 % to 73.5 % of theperiod and adolescents are sedentary for 27.7 % to88.9 % of the period. The substantial variability in esti-mates may be due to differences in sample sizes and ac-celerometer cut points. Although cut points <100 cpmmay be capturing standing and light-intensity physicalactivity and incorrectly categorizing this as sedentarytime, this threshold has been shown to most accuratelyrepresent sitting time when compared to inclinometersamong 8-12 year-olds [50]. Based on findings using thecut point of 100 cpm, children spent approximately25 min per hour of the after-school period sedentaryand adolescents spent 42 min per hour of the after-school period sedentary (although this was obtainedfrom only one study among adolescents). However, ahigher sedentary cut point can greatly elevate prevalencerates. For instance, Reilly and colleagues [51] found a321 min (5 h, 21 min) per day difference in sedentarytime depending on the cut point used. This is also evi-dent in the current review, as the prevalence of adoles-cents’ after-school sedentary time ranged from 27 %when using <50 cpm to 82 % when using <800 cpm. It isalso important to note that there were large variations inestimates within thresholds. For example among thestudies using 100 cpm, the percentage of time spent sed-entary ranged from 16.1 % [29] to 56.1 % [32], highlight-ing the variability within the literature. This alsohighlights that there may be other important contextualfactors impacting after-school behavior such as location

(e.g., at home or after-school care) and who the childrenare with (e.g., alone or with friends) which require fur-ther investigation. Future research should also examinethe intrapersonal, social and physical environment corre-lates which may further explain the variance in after-school sedentary behaviors. Such investigation would en-able identification of the characteristics of children andadolescents who display high levels of sedentary timeand behaviors which can subsequently be used as inter-vention targets. Other factors, such as sample size andcharacteristics, may also explain part of the variance inprevalence rates.The most frequently measured after-school sedentary

behavior was TV viewing, with children and adolescentsspending approximately one fifth of the after-schoolperiod watching TV. The percentage of the after-schoolperiod spent watching TV by children and adolescentswas similar (children: 21 % and adolescents 19 %) sug-gesting the age-related increases in after-school seden-tary time observed in this review and previouslyobserved [11] may be due to increases in participation inother sedentary behaviors (e.g., computer use or home-work) [52]. However, it is hard to draw conclusions asonly one study examined adolescents’ sedentary behav-iors. Further, the prevalence of after-school screen-basedsedentary behaviors was more than three times higherwhen it included TV viewing compared to when thescreen-based sedentary behavior measure did not in-clude TV. This suggests that TV viewing is the mainscreen-based sedentary behavior after school and a po-tentially important intervention target if targetingscreen-based sedentary behaviors.The prevalence of screen-based sedentary behaviors

that included TV viewing was lower than the prevalencereported by studies that just reported TV viewing. Thismay be due to the differences between measures used asdifferences in recall period and question response format(e.g., behaviors during previous day, previous week etc.)and the mode of administration (e.g., phone interview orwritten survey) may impact on the sedentary behaviorsreported [53]. The studies examining screen-based sed-entary behavior including TV viewing requested partici-pants to report their present or previous day behaviors[39, 41, 42, 44] and asked for the main behavior beingperformed which does not allow for reporting of concur-rent sedentary behaviors. In contrast, the studies exam-ining TV viewing used a variety of recall periods fromthe present day [45] to recall of behaviors on three days[40]. There may be differences in daily TV viewing be-haviors that are not able to be captured via a one day re-call. Alternatively, higher prevalence rates may be due toTV viewing alone being an easier behavior to recall orparticipants may think broadly about all screens whenasked about TV viewing without realising, whereas they


47

may be more discriminatory when asked about individ-ual screen use. Further, participants may have been per-forming sedentary behaviors concurrently, however thiswas not assessed. Additional exploration using consist-ent measures would facilitate direct comparisons.It is also important to note that approximately one-

fifth of the after-school period was spent in non-screenbased sedentary behaviors. Although only measured inthree studies, it is possible that most of the non-screenbased sedentary behaviors were homework or academicpursuits as when the measure did not include these be-haviors, the prevalence was much lower (3.6 %). Thesimilar percentage of time spent watching TV and innon-screen based sedentary behaviors suggests theremay be opportunities for interventions to target seden-tary behaviors other than TV viewing (e.g., throughstanding homework tasks [54]).

Limitations of the current literatureThe objectively-measured sedentary time findings shouldbe interpreted with some caution as there were numer-ous cut points used to represent sedentary time whichmay influence estimations of sedentary time. Also, whilefew studies reported children’s behaviours while at after-school care, the majority of studies did not report wherethe children or adolescents were after school resulting inthese studies being combined into ‘other locations’. The‘other locations’ could include for example, a child/ado-lescent’s home, a friend’s or relative’s home, or the localneighbourhood and there may be important differencesin sedentary time/sedentary behaviors when childrenand adolescents are at such locations. However, this can-not be determined from the data available. Additionalstudies taking into account the child’s/adolescent’s actuallocation after school are important for informing the de-velopment of interventions targeting those settingswhere children are most likely to be sedentary duringthe after-school period. The variability of subjectivemeasures of sedentary behaviors also limited the abilityto directly compare findings. The use of uniform surveyitems in future studies would assist in gaining a greaterunderstanding of the sedentary behaviors that childrenand adolescents perform after school. The varying periodlengths makes direct comparisons of raw minutes of sed-entary behavior after school difficult. While the use ofproportion of time overcomes this, the use of the stan-dardised definition of the after-school period (end-of-school to 6 pm [12]) would further facilitate the directcomparison of future studies examining after-school be-haviors. As there were no studies that examined the in-dividual sedentary behaviors children perform duringafter-school care and only one that examined the indi-vidual sedentary behaviors among adolescents, the evi-dence in these areas is limited. Sedentary behaviors

performed during after-school care (e.g., seated crafts,board games) may differ to those at ‘other’ locations;therefore, this information may assist the developmentof interventions targeting the after-school care setting.Lastly, a limitation is that any bias due to study method-ology quality within the current review is unknown asno methodological quality or risk of bias assessment wasperformed; therefore, higher quality studies may show ahigher or lower prevalence rate than studies of poorquality. More appropriate measures of study quality forliterature reviews of prevalence studies are needed toprovide estimates based on the highest quality evidence.

ConclusionChildren and adolescents spent almost half of the after-school period sedentary with adolescents spending agreater percentage of the period sedentary than children.Few studies measured behaviors performed while atafter-school care; however, the limited evidence suggeststhat children spent less time sedentary at after-schoolcare than at ‘other’ locations. Children and adolescentsspent the greatest percentage of the after-school periodwatching TV and engaged in non-screen based sedentarybehaviors; however, additional research is needed thatmeasures other sedentary behaviors (e.g., mobile phoneand digital tablet use, etc.), that uses standardized surveyitems to enable study comparisons, and that includes theadolescent population. This review highlights children’sand adolescents’ sedentary behaviors that can be targetedfor reduction though interventions in the after-schoolperiod.

Additional files

Additional file 1: Table S1. Search strategy. Example of search strategy.(DOCX 15 kb)

Additional file 2: Table S2. Study characteristics. Details of thecharacteristics of the studies included in this review. (DOCX 23 kb)

AcknowledgementsNot applicable.

FundingLA is supported by a National Health and Medical Research Council (NHMRC)PhD Scholarship (APP1074484).EF is supported by a National Health and Medical Research Council (NHMRC)Centre of Research Excellence Grant (APP10576080)JS is supported by a National Health and Medical Research Council (NHMRC)Principal Research Fellowship (APP1026216).JV is supported by a National Health and Medical Research Council (NHMRC)Early Career Research Fellowship (APP1053426).TH is supported by a National Health and Medical Research Council(NHMRC) Early Career Fellowship (APP1070571).National Health and Medical Research Council (NHMRC) had no part in studydevelopment, design or analysis.

Availability of data and materialsThe dataset supporting the conclusions of this article is included within thearticle (and its Additional files 1 and 2).


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Authors’ contributionLA, EF, JS, JV and TH were involved in the conception and design of thepaper. LA and EF were involved in the data collection and synthesis. Allauthors contributed to the writing of the paper, read and approved the finalmanuscript.

Competing interestsThe authors declare that they have no competing interests.

Consent for publicationNot applicable.

Ethics approval and consent to participateNot applicable.

Received: 2 March 2016 Accepted: 3 August 2016

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50

Additional Table 1: Search strategy.

1. school age OR youth OR young OR child* OR adolescen*2. sedentar* OR television OR TV OR screen OR “electronic games” OR inactiv*3. after-school OR “after school” OR afternoon OR evening OR “critical window” OR

“critical hours”4. 1 and 2 and 35. limit 4 to published prior to October 2015 AND peer reviewed AND English language

AND age groups: child (5-12 years) and adolescents (12-18 years)

51

Add

ition

alT

able

2: S

tudy

cha

ract

eris

tics

Aut

hor

Yea

rSa

mpl

e si

zeA

ge in

yea

rs (r

ange

or

M (S

D))

, gen

der

(%m

ale)

Cou

ntry

Aft

er-s

choo

l pe

riod

def

initi

onSt

udy

desi

gnL

ocat

ion

ofch

ildre

nSB

mea

sure

Aru

ndel

l et a

l.20

13n=

2053

Gro

up 1

: n=

608,

5-6

year

s, 52

% m

ale

Gro

up 2

: n=

1445

, 10-

12 y

ears

, 45%

mal

e

Aus

tralia

End

of sc

hool

be

ll-6p

mC

ohor

tN

ot re

porte

dA

ctig

raph

716

4, 6

0 se

c ep

och,

SED

<100

cpm

Ove

rall

ST:

5-6y

r, m

: 27.

8%; f

: 27.

9%10

-12y

r, m

:37.

6%; f

: 37.

9%

Aru

ndel

l et a

l.20

13n=

308

acce

lero

met

er

data

; n=1

08

activ

PAl d

ata

8, 4

2% b

oys

Aus

tralia

End

of sc

hool

be

ll-6p

mC

ross

-se

ctio

nal

Not

repo

rted

Act

igra

ph G

T3X

, 15

sec

epoc

h. S

B:

Ove

rall

ST: 4

7.5%

Atk

in e

t al.

2013

n=84

5,10

.2 (±

0.3)

, 41%

boy

sU

K3-

11pm

Long

itudi

nal

Not

repo

rted

Act

igra

ph a

ccel

erom

eter

G

T1M

, SB

:<10

0 cp

mO

vera

ll ST

: 40.

3%

Atk

in e

t al.

2008

n=1,

484

13-1

6 ye

ars,

38%

mal

eU

K3.

30-6

.30p

mC

ross

-se

ctio

nal

Not

repo

rted

Self-

repo

rt di

ary

of

beha

viou

rs d

urin

g“f

ree

time"

TV v

iew

ing:

20.

2%

Scre

en b

ased

EX

C T

V: m

: 7.8

%; f

:1.4

%

So

cial

Sed

enta

ry: m

: 7.9

%; f

: 10.

1%

Hom

ewor

k/ac

adem

ics:

m: 1

3.2%

; f: 1

4.5%

M

otor

ised

tran

spor

t: m

: 3.4

%; f

: 10.

4%

Bai

ley

et a

l.20

12n=

135

11.7

(±1.

4), 4

2% m

ale

UK

End

of sc

hool

bel

l -6

.30p

mB

asel

ine

data

fro

m P

A

(inte

rven

tion)

Not

repo

rted

RT3

tria

xial

acce

lero

met

ers,

60 se

c ep

och,

SED

: <28

8 cp

m

Ove

rall

ST: 5

6.1%

Bat

tista

et a

l.20

05n=

533

grad

e 4-

6, 5

0% m

ale

US

2-6p

mC

ohor

tA

fter-

scho

ol

care

SOFI

T (S

yste

m fo

r O

bser

ving

Fitn

ess

Inst

ruct

ion

Tim

e)

Ove

rall

ST: 3

6.7%

Bee

ts e

t al.

2013

n=78

5K

inde

r to

year

5, 5

0%

mal

eU

SAA

vera

ge o

f 208

m

inut

es/d

ay

(ran

ge 6

0-24

0)

Obs

erva

tiona

lA

fter-

scho

ol

care

Act

igra

ph G

T1M

, 5se

c ep

och,

SED

<10

0cpm

Ove

rall

ST: m

: 50.

1%; f

: 56.

1%

DuR

ant e

t al.

1996

n=13

85-

6 ye

ars %

mal

e no

tre

porte

dU

SA>1

50m

ins a

fter

3pm

Cro

ss-

sect

iona

ldat

a fro

m

long

itudi

nal

stud

y

Not

repo

rted

Obs

erva

tiona

l: C

hild

ren'

s ac

tivity

ratin

g Sc

ale

(CA

RS)

TV v

iew

ing:

31%

Fuem

mel

er e

t al

.20

11n=

45 p

aren

t-ch

ild tr

iads

(m

ums,

dads

and

child

ren)

Chi

ld a

ge: 1

0.6

(±0.

7)

51%

mal

e. M

othe

r age

40

.6 (±

5.6)

, fat

her a

ge:

42.8

(±6.

2)

USA

3-7p

mC

ross

-se

ctio

nal

Not

repo

rted

Act

igra

ph 7

164,

60s

ec

epoc

h, S

ED<1

.5M

ETs

Ove

rall

ST: 5

2.3%

Har

ding

et a

l.20

15n=

363

12.0

(±0.

4), 3

9% m

ale,

follo

wed

to 1

5.4

yrs

(±0.

5), 3

9% m

ale,

UK

End

of sc

hool

bel

l -9

pmC

ohor

tN

ot re

porte

dA

ctig

raph

acc

eler

omet

er

GT1

M, S

ED<1

00cp

mO

vera

ll ST

: 12y

r: 63

.2%

; 15y

r: 70

.1%

Har

ringt

on e

t al

.20

11n=

102

15-1

8 ye

ars (

0% m

ale

(fem

ale

sam

ple)

Irel

and

4-10

pmC

ross

-se

ctio

nal

Not

repo

rted

activ

PAL

incl

inom

eter

sO

vera

ll ST

: 65%

52

Hag

er20

06n=

8010

(±1.

0), 5

0% m

ale

USA

5.30

-6pm

Cro

ss-

sect

iona

lN

ot re

porte

dPa

rent

repo

rt TV

and

co

mpu

ter/

vide

o ga

me

use

Scre

en b

ased

INC

L TV

:m: 1

5%; f

: 8.5

%

Jago

et a

l.20

05n=

81

13.3

(±0.

5), 5

4% m

ale

USA

3pm

-6.5

9pm

Cro

ss-

sect

iona

lN

ot re

porte

dA

ctig

raph

MTI

SE

D<8

00cp

m, a

nd se

lf-re

port

prev

ious

day

el

ectro

nic

recr

eatio

n us

e

Ove

rall

ST: m

: 75.

3%; f

: 88.

9%

Lau

2013

n=20

par

ent-

child

dia

ds,

6.25

(±0.

64),

55%

mal

eA

ustra

lia3.

30-7

pmC

ross

-se

ctio

nalf

rom

co

hort

stud

y

Not

repo

rted

Act

ical

acc

eler

omte

r, 15

sec

epoc

h,SE

D<1

00cp

m

Ove

rall

ST: 5

0.5%

McG

all e

t al.

2011

n=60

,8.

3yea

rs (±

0.7)

, 54%

m

ale

New

Zea

land

3-5p

mC

ross

-se

ctio

nal

Not

repo

rted

actig

raph

GT1

M, 6

0-se

c ep

och,

sed

<100

cpm

, va

lid d

ata

4+ d

ays.

Treu

th

et a

l (M

ed S

ci C

ports

Ex

erc

2004

: 36:

125

9-66

)

Ove

rall

ST: 3

9%

McK

enzi

e et

al

.20

08n=

139

6.5

(±0.

98),

50%

mal

eU

SA2

x 30

min

ute

perio

ds b

etw

een

end

of sc

hool

and

di

nner

Cro

ss-

sect

iona

lH

ome

Obs

erva

tiona

l: m

odifi

ed

vers

ion

of B

EAC

HES

(B

ehav

iour

s of E

atin

g an

d A

ctiv

ity fo

r Chi

ld H

ealth

: Ev

alua

tion

Syst

em).

Ove

rall

ST: 5

4.6%

New

man

et a

l.20

07n=

742

10.1

3, 4

8% m

ale

Bul

garia

, Ta

iwan

and

th

e U

SA

End

of sc

hool

un

til 1

0pm

Cro

ss-

sect

iona

lN

ot re

porte

dSe

lf-re

port

Scre

en b

ased

EX

C T

V: 4

.48%

Pate

et a

l.19

99n=

181

10.7

(±0.

7), 4

6.3%

m

ale.

n=82

at f

ollo

w-u

p

USA

3pm

-11.

30pm

Long

itudi

nal

Not

repo

rted

Self-

repo

rt Pr

evio

us D

ay

PA re

call

(PD

PAR

).Sc

reen

bas

ed IN

CL

TV:

m

: 21.

2%; f

: 17.

1%

Non

-scr

een

SB IN

CL

hom

ewor

k/ac

adem

ics:

m: 1

0%; f

: 12.

4%

Posn

er e

t al.

1999

n=19

4 (a

t 2-

year

follo

w-

up)

9.1

(±0.

5), 5

4% b

oys

USA

2.45

-6pm

or 3

.35-

6.35

pm

(dep

enda

nt o

n di

smis

sal t

ime)

Coh

ort

Var

iety

Self-

repo

rtH

omew

ork/

acad

emic

s:

15.

5%

Puls

ford

et a

l.20

13n=

629

10.9

5 (±

0.4)

, 51%

mal

eU

nite

d K

ingd

om3-

11pm

Cro

ss-

sect

iona

lN

ot re

porte

dA

ctig

raph

GT1

M (W

rist

wor

n), 1

0sec

epo

ch,

SED

<100

cpm

Ove

rall

ST: 4

0.4%

Ros

enkr

anz

et

al.

2011

n=24

09.

3 (±

0.7)

, 51%

mal

eU

SAN

ot re

porte

dC

ross

-se

ctio

nal

Afte

r-sc

hool

ca

reA

ctig

raph

GT1

M, 3

0sec

ep

och,

SED

<100

cpm

Ove

rall

ST: 1

6.1%

Silv

a et

al.

2011

n=24

11.0

4 (±

1.45

), 50

%

mal

ePo

rtuga

l6.

01pm

-8pm

Cro

ss-

sect

iona

lN

ot re

porte

dA

ctig

raph

, 716

4, 6

0sec

ep

och,

SED

<50c

pmO

vera

ll ST

: m

: 26.

1%; f

: 27.

7%

Stan

ley

et a

l.20

11n=

794

11.9

(±1.

6), 4

8% m

ale

Aus

tralia

90 m

inut

es a

fter

end

of sc

hool

bel

lC

ross

-se

ctio

nal

Not

repo

rted

Self-

repo

rt 1

day

reca

ll us

ing

Mul

timed

ia A

ctiv

ity

Rec

all f

or C

hild

ren

and

Adu

lts (M

AR

CA

).

Scre

en b

ased

EX

C T

V: 8

.3%

H

omew

ork/

acad

emic

s: 6

%

N

on-s

cree

n SB

EX

C h

omew

ork/

acad

emic

s:

3.7%

Mot

oris

ed T

rans

port:

16.

6%53

Ston

e et

al.

2014

n=85

611

(±0.

6), 4

5% m

ales

Can

ada

2hrs

afte

r sch

ool

bell

Coh

ort

Not

repo

rted

Act

igra

phG

T1M

, 5se

c ep

och,

SED

<300

cpm

Ove

rall

ST: m

: 70.

1%; f

: 73.

5%

Ston

e an

d Fa

ulkn

er20

14n=

856

11 (±

0.6)

, 45%

mal

esC

anad

a2h

rs a

fter s

choo

l be

llC

ohor

t N

ot re

porte

dA

ctig

raph

GT1

M, 5

sec

epoc

h, S

ED<3

00cp

mO

vera

ll ST

: m: 6

8.3%

; f: 7

2.9%

Tave

rno

Ros

s et

al.

2012

n=66

210

.6 (±

0.5)

, 45%

mal

eU

SAaf

ter s

choo

l bel

l -6p

mC

ross

-se

ctio

nal

Hom

e or

A

fter-

scho

ol

Car

e

Act

igra

ph G

T1M

and

G

T3X

m, 6

0sec

epo

ch,

SED

<100

cpm

Ove

rall

ST (h

ome)

: m: 4

3.6%

; f: 4

8.4%

O

vera

ll ST

(afte

r-sc

hool

car

e): m

: 43.

6%; f

: 44

.1%

Vis

sers

et a

l.20

11n=

1697

10.3

(±0.

3), 4

4% m

ales

Engl

and

12no

on -

9pm

Cro

ss-

sect

iona

lN

ot re

porte

dA

ctig

raph

GT1

M, 5

sec

epoc

h, S

ED<1

00cp

mO

vera

ll ST

: m: 5

3.9%

; f: 5

5.8%

Wic

kel.

2013

n=86

2 ye

ar 3

st

uden

ts a

nd

954

year

4

stud

ents

10, 5

0% m

ale

USA

3-6p

mC

ohor

tV

arie

tySe

lf-re

port

pres

ent d

ay

scre

en-a

nd n

on-s

cree

n ba

sed

SBre

call

Scre

en b

ased

INC

L TV

: 21.

7%

N

on-s

cree

n SB

INC

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, scr

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in s

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of c

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or e

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met

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Add

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21

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resu

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don

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clud

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terv

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mea

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con

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. -

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22

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resu

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ass

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fris

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Item

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page

7

Add

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al a

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if d

one

(e.g

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ubgr

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a-re

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[see

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25D

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, ris

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-leve

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, rep

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as).

14

Con

clus

ions

26

Pro

vide

a g

ener

al in

terp

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of th

e re

sults

in th

e co

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atio

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. 15

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sys

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sup

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of d

ata)

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emat

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view

. 15

From

: M

oher

D,

Libe

rati

A, T

etzl

aff

J, A

ltman

DG

, Th

e P

RIS

MA

Gro

up (

2009

). P

refe

rred

Rep

ortin

g Ite

ms

for

Sys

tem

atic

Rev

iew

s an

d M

eta-

Ana

lyse

s: T

he P

RIS

MA

Sta

tem

ent.

PLo

S M

ed 6

(6):

e100

0097

. do

i:10.

1371

/jour

nal.p

med

1000

097

For m

ore

info

rmat

ion,

vis

it:w

ww

.pris

ma-

stat

emen

t.org

.Pag

e 2

of 2

56

Chapter Two: Literature Review. Appendix Two: Paper Two: The correlates of after-school sedentary behavior among children

aged 5–18 years: a systematic review.

57

Literature review Appendix Two: Paper Two. The correlates of after-school

sedentary behaviour among children aged 5-18: a systematic review.

This appendix contains the full manuscript of the abstract contained in Section

2.13. Below is a systematic review of the correlates of children and adolescents’

after-school sedentary behaviour which is published in BMC Public Health

(Impact factor: 2.264) as: Arundell L, Fletcher E, Salmon J, Veitch J, Hinkley T.

2016. The correlates of after-school sedentary behavior among children aged 5–

18 years: a systematic review. BMC Public Health, 16(1):1-10.


RESEARCH ARTICLE Open Access

The correlates of after-school sedentarybehavior among children aged 5–18 years:a systematic reviewLauren Arundell*, Elly Fletcher, Jo Salmon, Jenny Veitch and Trina Hinkley

Abstract

Background: Children and adolescents spend a large proportion of the after-school period in sedentary behaviors(SB). Identifying context-specific correlates is important for informing strategies to reduce these behaviors. Thispaper systematically reviews the correlates of children’s and adolescents’ after-school SB.

Methods: A computerized literature search was performed in October 2015 for peer-reviewed original researchjournal articles published in English before October 2015. Eligibility criteria included: 1) sample aged 5–18 years;2) quantified the amount of SB or component of this that the children/adolescents were performing after school;3) a measure of SB as the dependent outcome; and 4) the association between potential correlates and after-school SB.

Results: Data were synthesized in October 2015. Thirty-one studies met the eligibility criteria: 22 studies amongchildren (≤12 years), six among adolescents (>12 years), two had a combined sample of children and adolescentsand one cohort followed children from childhood to adolescence. Findings were separated by after-school locationi.e. after-school programs (n = 4 studies) and unidentified locations (n = 27). There was insufficient evidence to drawconclusions on all but two of the 58 potential correlates: sex and age. Among children at unidentified locations therewas a null association between sex (male) and overall after-school SB, a null association between sex (male) andafter-school TV viewing, a positive association between age and overall after-school SB and an inconsistent associationbetween age and after-school TV viewing. No correlates of after-school sedentary behaviour while at after-schoolprograms were identified.

Conclusions: Only two correlates have been investigated frequently enough to determine an overall association;neither correlate is modifiable. Due to the lack of consistent investigation of potential correlates, further evidence isrequired to accurately identify potential intervention targets.

PROSPERO registration number: CRD42014009180

BackgroundSedentary behaviors are defined as behaviors expending≤1.5 metabolic equivalents (METS) in a sitting or reclin-ing posture (e.g. TV viewing, computer use, reading) [1].The total time spent engaged in sedentary behaviors iscalled sedentary time. Emerging evidence shows thehealth and other risks of engaging in elevated amountsof sedentary behavior among youth, such as increasedadiposity, decreased fitness, poor self-esteem and pooracademic achievement [2–4]; however, this evidence is

at times equivocal [5]. Despite this, approximately 75 %of youth in many developed countries exceed Govern-ment recommended levels of no more than two hours ofrecreational screen time per day [6–8].The after-school period, from the conclusion of school

until 6 pm [9], is typically characterized by children en-gaging in sedentary behaviors. Up to 38 % of this periodis spent sedentary [10] and children watch over 70 % oftheir daily TV between 3–9 pm [11]. Interventions tar-geting after-school sedentary behaviors may thereforebe effective. Children are not restricted by the schooltimetable during this period, and may have some dis-cretionary choices between active or sedentary options.

* Correspondence: [email protected] for Physical Activity and Nutrition Research, Deakin University, 221Burwood Highway, Burwood, Australia

© 2016 Arundell et al. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, andreproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link tothe Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Arundell et al. BMC Public Health (2016) 16:58 DOI 10.1186/s12889-015-2659-4

58

Although warranted, such interventions require an under-standing of context-specific correlates of participation inthese behaviors during the after-school period prior todevelopment.Previous reviews exploring the correlates of children’s

individual sedentary behaviors such as total screen-viewing [12] and TV viewing [13], and overall sedentarytime (objectively and subjectively measured) [14], haveexamined children’s daily behaviors without specificattention to the after-school period. As there are healthoutcomes specific to screen-viewing [3, 4, 15], and thesebehaviors are often intervention targets [16, 17], investiga-tion into the correlates of after-school screen-viewingbehaviors as well as total sedentary time during this periodis important. In addition, the context of the after-schoolperiod (i.e. location of the child and who the child is with)is likely to be different to what children experience duringthe whole school day. Therefore, it is likely that the corre-lates of sedentary behaviors performed after school varyfrom the correlates of daily sedentary behaviors.Many theories have been used to facilitate the study of

behaviors and their corresponding correlates. Ecologicalmodels posit that behavior is influenced by intraper-sonal/demographic factors as well as their social/culturaland physical/policy environments [18], all of which arelikely to impact a child’s after-school sedentary behavior.The aim of this paper is to systematically review thecorrelates of children’s and adolescents’ after-schoolsedentary behavior organised according to an ecologicalframework.

MethodsThis review is registered with PROSPERO (registrationnumber: CRD42014009180).

Search procedureUsing the EBSCOhost search engine, a computerizedsearch for literature was performed in October 2015within the following databases: Academic Search Complete,CINAHL Complete, Education Research Complete, MED-LINE, MEDLINE Complete, PsycARTICLES, Psychologyand Behavioral Sciences Collection, PsycINFO and SPORT-Discus with Full Text. Peer-reviewed original research jour-nal articles published in English until October 2015 weresought. The following keyword combinations were used forage (school age, youth, young, child*, adolescen*), behavior(sedentar*, television, TV, screen, electronic games, inactiv*)and time-of-day (after-school, after school, afternoon, even-ing, critical window, critical hours).Articles were analysed in October 2015 and were

included if they met the following criteria: 1) includedchildren aged 5–18 years; 2) quantified the amount ofsedentary time/behavior the children were performingafter school (in minutes or proportion of the period);

3) included a measure of sedentary behavior (objectivelyor subjectively measured) as the dependent outcome; and4) assessed the association between potential correlatesand after-school sedentary behavior. Studies that includedspecial populations (e.g. children with a disability or over-weight/obese populations) were excluded due to the in-ability to generalise the findings to the broader population.No restriction was placed on the definition of ‘after-school’ to allow for the greatest inclusion of studies. Arti-cles that examined sedentary behaviors ‘outside of school’were excluded as that definition typically includes behav-iors before school and on weekends which was beyond thescope of the current review. All sedentary behaviors werereported (e.g. TV viewing, Computer/ DVD/video gameuse) to enable an exploration of the potential correlatesspecific to each behavior. Articles were included regardlessof where the children were located during the after-schoolperiod (e.g. at after-school program, at home) to allowcomparisons of behaviors and potential correlates.Initially, each title and abstract was reviewed to deter-

mine eligibility. The full-text of studies deemed eligiblewere retrieved and assessed. Relevant papers from othersources (e.g. reference lists) were also added if eligible.All articles were reviewed by two authors (LA and EF)and any differences were discussed until agreement wasachieved (83 % agreement in initial screening). Wheneligibility was unclear contact was attempted with the cor-responding author for further clarification (n = 4 authors).

Methodological quality and risk of bias assessmentStudy quality and risk of bias was determined using amodified published rating scale from McMaster Univer-sity [19]. Six methodological components were assessedincluding selection bias (e.g. sample representativeness),study design (e.g., RCT), confounders (e.g., were between-group differences controlled for?), blinding (e.g. wasthe outcome assessor aware of group allocation), datacollection methods (e.g. are they valid and reliable),and withdrawals and dropouts (e.g. percent of participantscompleting/providing full data). Intervention-specific cri-teria within any component was not assessed for observa-tional studies (e.g. intervention integrity, blinding). Asrecommended in the quality assessment tool’s dictionary,each study was given a score of weak, moderate or strongfor each component. Two reviewers (LA and EF) inde-pendently assessed the quality of each study, comparedresults and discussed any differences until agreement wasachieved (93 % agreement in initial study quality assess-ment). The PRISMA guidelines were followed [20].

ResultsFigure 1 shows that 569 articles were identified, screenedand assessed for eligibility. Of these, 31 met the in-clusion criteria. Studies were analysed for children and

Arundell et al. BMC Public Health (2016) 16:58 Page 2 of 10

59

adolescents separately. Studies were included in the childdata when the mean age was ≤12 years [10, 11, 21–39] (n =22) and in the adolescents’ data when the mean age was>12 years [40–45] (n = 6). One cohort studied examinedcorrelates when the sample was children (9–10 and 10–11years) and adolescents (13–14 years) [46]. For this study,data for the 9–10 and 10–11 year olds were included inthe children’s findings and data for the 13–14 year oldwere included in the adolescents’ findings. Two additionalstudies had a sample that included both children andadolescents (grades 3 and 9 [47] and 9–15 years [48]).These two studies combined the age groups, thereforetheir findings were duplicated to be included in both thechild and adolescent data for this review as the potentialcorrelates related to both age groups. Therefore, a total of25 studies were included for children and nine for adoles-cents. Study characteristics can be found in (Additionalfile 1: Table S1).

After-school period definitionsA variety of definitions for the ‘after-school’ period wasprovided and many studies did not define the period.Among the four studies examining potential correlatesof sedentary behavior while children were at after-schoolprograms, only one study [21] provided information todefine ‘after-school’. However, that study defined theperiod as the average number of minutes (208, range60–240) after school and did not provide a start and/orfinish time, and it is assumed that this would havevaried widely by child. The other three studies did notreport the actual time period [26, 29, 31]. Among the27 studies examining correlates of children’s/adolescents’

after-school behaviors while at unidentified locations, fourdid not provide a definition [33, 45, 47, 48]. Twenty differ-ent definitions of the after-school period were used amongthe remaining 23 studies ranging from two hours immedi-ately after school [36, 37] through to 12noon–9 pm [32].

Child’s locationOnly four studies that met the inclusion criteria assessedthe potential correlates of children’s sedentary behaviorwhile attending an after-school program. All four studieswere among children [21, 26, 29, 31]. Of the remainingstudies, 22 did not report where the children/adolescentswere located after school [10, 11, 22–25, 28, 32, 33, 36–41,43–49] and five reported that the children/adolescents wereat a variety of locations after school [27, 30, 34, 35, 42]. Forsynthesis of the results, these 27 studies were combined torepresent children/adolescents at ‘unidentified locations’.

Country of studyAll four studies investigating the potential correlates ofchildren’s/adolescents’ sedentary behavior during after-school programs were conducted in the United States[21, 26, 29, 31]. The majority of the studies investigatingafter-school behaviors while at unidentified locationswere conducted in the United States (n = 12) [11, 22, 23,27, 30, 34, 35, 41–43, 45, 48]. The only other countriesfrom which multiple studies were identified were theUnited Kingdom [28, 32, 39, 40, 46, 49], Australia[10, 24, 33] and Canada [36, 37]. One study was identi-fied from each of the following: Portugal [44]; a combinedsample from Bulgaria, Taiwan and the United States [25];a combined sample from England and Spain [38]; and a

Fig. 1 Flow chart of search results


60

combined sample from Denmark, Portugal, Estonia andNorway [47].

Measurement toolsData collection methods for the studies examining thepotential correlates of children’s/adolescents’ sedentarybehavior while at after-school programs were predomin-antly objectively measured by an ActiGraph GT1M ac-celerometer with a sedentary behavior cut point of <100counts per minute (cpm) [21, 29, 46, 49] or <1.5METS[31]. One study used self-report physical activity/sittingactivities recall [26].Among the 27 studies examining after-school seden-

tary behavior while at unidentified locations, 16 usedobjective measures including Actical accelerometer(<1.5METS [23]), ActiGraph accelerometer with sev-eral sedentary cutpoints (<50 cpm [44], <100 cpm[10, 24, 28, 30, 32, 38, 43, 46, 49], <288 cpm [39],<300 cpm [36, 37], and <800 cpm [41]), and directobservation (Children’s activity rating Scale [CARS])[22]. Eleven studies used subjective measures, only one ofwhich used a parent proxy-report child sedentary behaviorlog (watching TV and computer/video games includinghandheld devices in 15-min intervals) [11]. The remaining10 studies used child self-report: behaviors at 15 minintervals [40], TV viewing (60 min blocks) [47], self-reportsurvey of behaviors in 60 min intervals [25], screen timerecall (30 min blocks) [33], increasing intervals of a varietyof sedentary behaviors (i.e. 15, 30 then 60 min) [45], asedentary behavior diary (every 20 min) [42], the Self-Administered Physical Activity Checklist (SAPAC) [48],and behavior recall via telephone interview (15 min inter-vals) [27, 34, 35]. Studies were classified as measuringoverall sedentary behavior, TV viewing, computer/DVD/video games, a composite measure of screen-based seden-tary behaviors (when TV viewing and computer/DVD/video games may have been included in the measure butwere unable to be extracted for separate analysis) or non-screen-based sedentary behaviors.

Determining an associationA previously published coding model [50, 51] was usedto determine the overall association between a correlateand outcome behavior (‘+’ positive, ‘-’ negative or ‘0’ no/non-significant association). When there were four ormore findings that investigated a correlate and sedentarybehavior or a component of sedentary behavior, theassociation was assigned ‘0’ (null: 0–33 % of findingssupported an association), ‘?’ (inconsistent: 34–59 %of findings supported an association) or ‘+’ or ‘–’(positive or negative: 60–100 % of findings supportedan association).

Correlates of children’s and adolescents’ after-schoolsedentary behaviorCorrelates of children’s after-school sedentary behaviorIn total, 58 potential correlates of children’s after-schoolsedentary behavior were identified from the literature[10, 11, 21–39, 42, 47, 48]. Of these, only sex and agewere assessed frequently enough to provide an overallassociation. Table 1 shows a null association between sexand overall sedentary behaviors after school [10, 11, 24,31, 32, 35, 39]. There was also a null association betweensex (being male) and after-school TV viewing [25, 27, 47].Age was positively associated with overall sedentary be-haviors [10, 35, 46, 48, 49], and inconsistently associatedwith after-school TV viewing [27, 47]. No overall associa-tions were found with any potential correlates of children’ssedentary behavior while at after-school programs.Table 2 shows the potential correlates of children’s

after-school sedentary behavior that were measured tooinfrequently to determine an association. Overall seden-tary behavior was the mostly commonly assessed outcomewith 36 potential correlates assessed for their association.This was followed by TV viewing (15 potential correlates),non-screen-based sedentary behaviors (8 potential corre-lates), screen-based sedentary behaviors (6 potentialcorrelates and computer/DVD/video games (4 potentialcorrelates). Five potential correlates (age, sex, BMI, raceand family structure) were assessed across multiple behav-ior outcomes.Of the potential correlates assessed for their association

with overall sedentary behavior, 12 were intrapersonal (e.g.age, race), two related to the social environment (e.g.mum’s/dad’s sedentary behavior) and 22 related to thephysical/policy environment (e.g. number of TV sets athome). However, 16 of these physical/policy environmentcorrelates were assessed among children attending after-school programs and are specific to that program. Amongthe correlates of after-school TV viewing, eight wereintrapersonal, one was social and six were related to thephysical environment. Computer/DVD/video games hadfive potential correlates, two intrapersonal, one socialand two from the physical environment. The socialand physical environment correlates of children’s after-school screen-based and non-screen-based sedentary be-haviors examined who they were with (i.e., mum, dad,unrelated adult) and where they were located (i.e., publicplace, outside at home, outside at other home).

Correlates of adolescents’ after-school sedentary behaviorNo correlates of adolescents’ after-school sedentary be-havior were measured often enough to determine anoverall association. The 15 potential correlates of adoles-cents’ after-school sedentary behavior are shown in Table 3.Among adolescents, TV viewing was the behavioral out-come most frequently assessed with 11 potential correlates


61

assessed for their association. Seven potential correlateswere assessed for their association with overall sedentarybehavior, two were assessed with computer/DVD/videogames, and one with non-screen based sedentary behavior.Only sex, race and BMI were assessed across multiple be-havior outcomes. Among all behaviors, the majority of thepotential correlates were intrapersonal (n = 9) and TVviewing was the only behavioral outcome with which phys-ical/policy environment correlates were assessed.

Methodological quality and risk of bias assessmentThe majority (67 %) of the studies were cross-sectional[11, 23–26, 28–33, 38, 40–44, 47, 48] with 11 cohortstudies identified [10, 21, 22, 27, 34–37, 45, 49] and onestudy used baseline data from three interventions target-ing overall physical activity [39]. Reliability and validityof measurement tools was poorly reported with onlyeight studies reportedly using valid and reliable tools[22–24, 26, 30, 31, 42, 44]. Only six studies had a low se-lection bias with a “very/somewhat likely” representativesample and ≥80 % selected individuals agreeing to par-ticipate [24, 27, 31, 33, 41, 43]. Completion rates weregenerally high with over 80 % completion in ten studies[24, 25, 31, 32, 36, 37, 41–43, 48] and 60–79 % comple-tion in a further eleven studies [10, 23, 27, 30, 33–35,38, 44, 45].

DiscussionFifty-eight potential correlates of children’s and adoles-cents’ after-school sedentary behavior were identified inthis systematic review. As found in previous reviews ofdaily sedentary behavior among children and adolescents[52, 53], there was insufficient evidence to draw conclu-sions about the majority of these. Only two variables

(sex and age) were assessed frequently enough (four ormore times) to produce an overall association. Both ofthese variables were non-modifiable, were identifiedfrom studies among children, and were within the intra-personal domain of the ecological model.The complex nature of after-school sedentary behav-

iors is highlighted within these findings due to the nullassociations between sex (male) and overall sedentarybehavior and a null association with TV viewing. Thesefindings are in contrast to a previous review that foundan inconsistent association between sex and overall sed-entary behavior among preschool-aged children [14], butconcur with reviews among preschool children [14] and2–18 year olds [13] that found no association betweensex and daily TV viewing. Another review of the corre-lates of adolescents’ (13–18 years) daily sedentary behav-iors found a positive association with sex (male) [52].However, the authors grouped their studies so that theassociation was reported for combined TV/video/com-puter use or TV viewing without being able to determineif the association existed for each specific sedentary be-havior. This behavior grouping may have been to alignwith public health recommendations, so future researchmay benefit from identifying discretionary sedentary be-haviors (e.g. computer use for recreation) over non-discretionary sedentary behaviors (e.g. computer use forhomework) for targeted interventions.This review also found a positive association between

age and children’s after-school overall sedentary behav-ior, an association previously seen with young children’s(≤7 years) daily screen-viewing [12]. In contrast to thiswas the inconsistent association between age and chil-dren’s after-school TV viewing. This also contradicts aprevious cohort studies that found TV viewing declines

Table 1 Correlates of children’s after-school sedentary behavior reported in ≥4 findings

Overall sedentary behavior TV viewing

Correlate variables Ass. Studies Ass. Studies

Sex (male) + + [27]a

- [32] -

0 [10, 11, 24, 35, 39] [31]h 0 [25], [27]b, [47]

Overall association (≥4 findings) 0 0

Age + [10, 35, 46, 48, 49] + [27]a, [47]cd

0 [27]b, [47]efg

Overall association (≥4 findings) + ?

Children aged 5–12 yearsAbbreviations: ‘0’ null association, ‘+’ positive association, ‘-’ negative associationaAfrican American samplebWhite samplecAll sample, includes children from Denmark, Portugal, Estonia and NorwaydEstonia sampleeDenmark samplefNorway samplegPortugal samplehSample at after-school programs


62

Table

2Correlatesof

children’ssede

ntarybe

havior

that

wererepo

rted

in<4finding

s(insufficien

teviden

ce)

Overallsede

ntarybe

havior

TVview

ing

Com

puter/DVD

/video

games

Screen

basedSB

Non

-screenbasedSB

Intrapersonal

Intrapersonal

Intrapersonal

Intrapersonal

Intrapersonal

At‘unide

ntified

locatio

ns’

At‘unide

ntified

locatio

ns’

At‘unide

ntified

locatio

ns’

At‘unide

ntified

locatio

ns’

At‘unide

ntified

locatio

ns’

+[48]

Race

(non

-Caucasian)

+[47]ceg/0[22],[47]dfBM

I+[25,27]b/0[27]a Sex

(male)

+[33–35]Sex(m

ale)

-[27],[34,35]Sex(m

ale)

+[11]h/0[11]iASMVPA

+[48]Race

(non

-Caucasian)

+34/0[27]

Age

+34/0

33Age

+[34,35]/0[27]Age

+[28]

Parentaled

ucation

+[47]cef /0

[47]gdChild

behavior

autono

my

Social

+[34]

Race

(non

-Caucasian)

0[34]Race

(non

-Caucasian)

+[32]

Sometim

eseatsbreakfast

(refalwayseat)

-[47]ce/0[47]dfgFather’sincomehigh

(reflow)

0[27]Family

structure(1

parent

house)

Social

Social

-[37]

Child

IM:high(re

flow)

0[22]Sum

ofskinfolds

Physical/Policy

At‘unide

ntified

locatio

ns’

At‘unide

ntified

locatio

ns’

-[28]

Dep

rivation(re

fleastde

prived

)0[22]Waist:Hip

ratio

−0[25]Cou

ntry

(Bulgaria,Taiwan,

USA

)-[3

4]With

peer

grou

pAS

+[34]

With

mum

/dad

AS

0[28]No.of

carsat

home

0[47]Father’sincomemed

(reflow)

0[27]Atten

dsASProg

ram

(refothe

rcare)

Physical/Policy

+[34]

With

unrelatedadultAS

0[28]Hou

seho

ldincome

0[47]Mothe

r’sincomehigh

/med

(reflow)

At‘unide

ntified

locatio

ns’

0[27]Family

structure(1

parent

house)

0[32]Po

or/Goo

dqu

ality

breakfasteaten

(refno

neeaten)

Social

-[34]

Timein

publicplace

AS

Physical/Policy

Atafter-scho

olprog

ram

0[27]Family

structure(1

parent

house)

-[34]

Timeou

tsideat

home

AS

At‘unide

ntified

locatio

ns’

-[29]

ASMVPA

-[34]Timeou

tsideat

othe

rho

use

(not

own)

0[26,31]jBM

IPh

ysical/Policy

+[27]Atten

dsASProg

ram

(refothe

rcare)

Social

At‘unide

ntified

locatio

ns’

At‘unide

ntified

locatio

ns’

0[23]Mothe

r’sSB

+[47]

Cou

ntry:Portugal,Estonia,Norway

(eachrefD

enmark)

0[23]Father’sSB

0[25]Cou

ntry

(Bulgaria,Taiwan,U

SA)

Physical/Policy

+[47]

TVen

vironm

ent

At‘unide

ntified

locatio

ns’

+[47]d/0[47]cefgNo.TV

setsin

theho

me

-[28]

Hom

ehasprivategarden

0[47]TV

inbe

droo

m

-[36]h/0[36]iOutdo

orplay

-[27]Atten

dsASProg

ram

(refothe

rcare)

-[30]i /0[30]hAtten

dsASProg

ram

(refho

me)

-[44]h/0[44]iSeason

(winter)

0[38]Cou

ntry:Eng

land

(refSpain)

+[46]

Rainfall


63

Table

2Correlatesof

children’ssede

ntarybe

havior

that

wererepo

rted

in<4finding

s(insufficien

teviden

ce)(Con

tinued)

Atafter-scho

olprog

ram

+[21]h/0[21]iASProg

ram

hasPA

policy

+[21]

ASProg

ram

collectsfeed

back

onactivities

childrenwant

+[21]hASProg

ram

staffprovided

with

1-4h

ofPA

training

+[21]h/0[21]iASProg

ram

unde

rgon

e≥1year

ofevaluatio

n

+[29]

Durationof

ASProg

ram

session

+[29]

ASProg

ram

cond

uctedinside

-[21]i /0[21]hASProg

ram

provides

activities

forbo

thsexes

-[29]

≥25

%of

ASProg

ram

allocatedto

PA

0[21]ASProg

ram

provides

ageandskill

approp

riate

activities

0[29]ASProg

ram

provides

organised/fre

eplay

activities

0[29]ASProg

ram

provides

non-fixed

equipm

ent

0[29]No.of

children

0[29]ASProg

ram

boys:girlsratio

0[29]ASProg

ram

staff:childrenratio

0[21]Presen

ceof

parent

worksho

pprom

otingim

portance

ofPA

0[21]ASProg

ram

curriculum

unde

rgon

eform

alevaluatio

n

Abb

reviations:‘0’nu

llassociation,

‘+’p

ositive

association,

‘-’ne

gativ

eassociation,

ASafterscho

ol,M

VPAmod

erate-

tovigo

rous-in

tensity

physical

activ

ity,SBsede

ntarybe

havior,IM

inde

pend

entmob

ility

a African

American

sample

bCau

casian

sample

c Allsample,

includ

eschild

renfrom

Den

mark,Po

rtug

al,Eston

iaan

dNorway

dEstoniasample

e Den

marksample

f Norway

sample

gPo

rtug

alsample

hMale

i Fem

ale

j sam

pleat

after-scho

olprog

rams


64

with age while computer use increases [54]. The positiveassociation with age and overall sedentary behaviourbut inconsistency between age and TV viewing maybe due to increase homework requiring computer useor increased participation in organised activities after-school. However, the mixed findings from this reviewhighlight the need for further research to better under-stand how the use of individual components of sedentarybehavior (i.e. TV viewing, electronic game use) varies aschildren age.Despite evidence that sedentary time increases with age

[55], a smaller number of potential correlates of after-school sedentary behavior were identified among adoles-cents than children in all three domains of the ecologicalmodel. This is a reflection of the lower number of studiesamong adolescents. Further it highlights the need for fur-ther investigation into the correlates of other componentsof sedentary behaviors such as homework/academics andrecent technologies such as iPads and Kindles, particularlyas the amount of suggested homework time increases asstudents progress through school [56].The majority of the potential correlates of children’s

overall sedentary behavior and the components of sed-entary behavior while at unidentified locations were intra-personal. Conversely, all of the potential correlates ofchildren’s after-school sedentary behavior while at after-school programs were within the physical/policy domainof the ecological model. This suggests that correlates ofsedentary behaviors performed during the after-schoolperiod may be dependent on the setting, the policies inplace and features of the physical environment. Future

research should identify the setting and context of chil-dren’s sedentary behavior in the after-school period.

LimitationsThere are a number of limitations within the literatureincluded in this review that need to be acknowledged.Firstly, the majority of studies did not report where thechild was located after school and these studies mayhave included children attending after-school programs.The correlates of children’s and adolescents’ after-schoolsedentary behavior may be specific to particular contextsor locations and therefore identifying differences betweencontexts is important for the development of interventionstrategies. Secondly, international comparisons are diffi-cult as the majority of the studies that met the eligibilitycriteria were among samples from the United States andthe United Kingdom. Countries and cultures have differ-ent environments which may influence children’s andadolescents’ after-school sedentary behavior and so needto be further explored. Thirdly, consideration must betaken of the definitions of the after-school period usedwhen examining the correlates of after-school sedentarybehavior. The potential correlates of a child’s/adolescents’behavior at 2 pm may vary considerably to those influen-cing the behavior at 8 pm. However, such differences werenot able to be determined from the literature as all timeframes were considered ‘after-school’. Fourthly, the varietyof measurement tools and data management used mayhave impacted on the findings. For example, among theobjective measures, a variety of sedentary cut pointswere used. This may influence the reported time children/

Table 3 Correlates of adolescents’ sedentary behavior that were reported in <4 findings (insufficient evidence)

Overall sedentary behavior TV viewing Computer/DVD/video games Non-screen based SB

Intrapersonal Intrapersonal Intrapersonal Intrapersonal

-[41]Sex (male) 0[40] Sex (male) +[40] Sex (male) 0[40] Sex (male)

+[48] Age +[47]ace/0[47]bd BMI +[45](comp/int)/-[48]/0[45](vid games)

Race (non-Caucasian)+[43]/-[42]BMI +[48]/0[45] Race (non-Caucasian)

+[48] Race (non-Caucasian) +[47]acd/0[47]be Child behavior autonomy

+[43] Body Fat % -[47]ac /0[47]bde Father’s income high (ref low)

Social 0[47] Father’s income med (ref low)

+[42] Time supervised AS 0[47] Mother’s income high/med (ref low)

+[42] Time alone AS Physical/Policy

Physical/Policy +[47] TV environment

0[46] Rainfall +[47]b/0[47]acdeNo. TV sets in the home

0[47] TV in bedroom\

+[47] Country: Portugal, Estonia, Norway (each ref Denmark)

Abbreviations: ‘0’ null association, ‘+’ positive association, ‘-’ negative association, AS after-school, BMI Body Mass IndexaAll sample, includes children from Denmark, Portugal, Estonia and NorwaybEstonia samplecDenmark sampledNorway sampleePortugal sample


65

adolescents spent in sedentary behavior [57] and subse-quently may impact the correlates identified with thisbehavior. Further, objective techniques do not providebehavior-specific information, while subjective measuresmay be at risk of recall bias, particularly among children[58]. However, despite the limitations associated with eachmeasurement tool, it is important to use both objectiveand subjective measures to identify associations betweenoverall sedentary behaviors with individual health com-ponents. This information is vital given the emergingevidence of health outcomes associated with individualsedentary behaviors [3, 4, 15]. Finally, due to the diversityof samples, measures and variables used, we are unable toperform a meta-analysis.Future research should focus on increasing the literature

assessing correlates of children’s and adolescents’ after-school sedentary behavior from all domains of the eco-logical model using valid and reliable measurement tools,consistent terminology and a standardized after-schoolperiod definition. Additional attention on the correlatesfor adolescents would assist with intervention develop-ment among this understudied age group. Longitudinalstudies among children and adolescents would also pro-vide valuable information about the determinants of afterschool sedentary behaviors and sedentary time. Futurestudies comparing associations by sub-groups, such assex, location and ethnicity would further assist tailoringintervention strategies targeting after-school sedentary be-haviors and sedentary time.

ConclusionsThis review highlights the need for further researchexamining the intrapersonal, social/cultural and physicalenvironmental/policy correlates of children’s and adoles-cents’ after-school sedentary behavior. There was insuffi-cient evidence to draw conclusions about the majority ofpotential correlates with overall associations only observedfor two non-modifiable variables among children: sex(male) and age. This lack of evidence makes the identifica-tion of potential strategies to decrease children’s andadolescents’ after-school sedentary behaviors challenging.Further investigation and identification of country-, con-text- and behavior-specific correlates of sedentary behav-iors in both children and adolescents is required todevelop effective interventions that target healthy levels ofafter-school sedentary behavior in these populations.

Additional file

Additional file 1: Table S1. Study characteristics. (DOCX 19 kb)


Authors’ contributionsLA, EF, JS, JV and TH were involved in the conception and design of thepaper. LA and EF were involved in the data collection and synthesis. Allauthors contributed to the writing of the paper and approved the finalmanuscript.

AcknowledgmentsLA is supported by a NHMRC PhD Scholarship (APP1074484).EF is supported by a NHMRC Centre of Research Excellence Grant(APP10576080).JS is supported by a NHMRC Principal Research Fellowship (APP1026216).JV is supported by a NHMRC Early Career Research Fellowship (APP1053426).TH is supported by a NHMRC Early Career Fellowship (APP1070571).

Received: 7 September 2015 Accepted: 21 December 2015

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38. Ramirez-Rico E, Hilland TA, Foweather L, Fernández-Garcia E, Fairclough SJ.Weekday and weekend patterns of physical activity and sedentary timeamong Liverpool and Madrid youth. Eur J Sport Sci. 2014;14(3):287–93.

39. Bailey D, Fairclough S, Savory L, Denton S, Pang D, Deane C, et al.Accelerometry-assessed sedentary behaviour and physical activity levelsduring the segmented school day in 10-14-year-old children: the HAPPYstudy. Eur J Pediatr. 2012;171(12):1805–13.

40. Atkin AJ, Gorely T, Biddle SJH, Marshall SJ, Cameron N. Critical hours:physical activity and sedentary behavior of adolescents after school. PediatrExerc Sci. 2008;20(4):446–56.

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43. Pratt C, Webber LS, Baggett CD, Ward D, Pate RR, Murray D, et al. Sedentaryactivity and body composition of middle school girls: the trial of activity foradolescent girls. Res Q Exerc Sport. 2008;79(4):458–67.

44. Silva P, Santos R, Welk G, Mota J. Seasonal differences in physical activityand sedentary patterns: the relevance of the PA context. J Sports Sci Med.2011;10(1):66–72.

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67

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tiona

l stu

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) in

the

sear

ch a

nd d

ate

last

sea

rche

d.

5-6

Sear

ch

8P

rese

nt fu

ll el

ectro

nic

sear

ch s

trate

gy fo

r at l

east

one

dat

abas

e, in

clud

ing

any

limits

use

d, s

uch

that

it

coul

d be

repe

ated

. 5-

6

Stud

y se

lect

ion

9S

tate

the

proc

ess

for s

elec

ting

stud

ies

(i.e.

, scr

eeni

ng, e

ligib

ility,

incl

uded

in s

yste

mat

ic re

view

, and

, if

appl

icab

le, i

nclu

ded

in th

e m

eta -

anal

ysis

). 6

Dat

a co

llect

ion

proc

ess

10D

escr

ibe

met

hod

of d

ata

extra

ctio

n fro

m re

ports

(e.g

., pi

lote

d fo

rms,

inde

pend

ently

, in

dupl

icat

e) a

nd a

ny

proc

esse

s fo

r obt

aini

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nd c

onfir

min

g da

ta fr

om in

vest

igat

ors.

6

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a ite

ms

11Li

st a

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efin

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l var

iabl

es fo

r whi

ch d

ata

wer

e so

ught

(e.g

., P

ICO

S, f

undi

ng s

ourc

es) a

nd a

ny

assu

mpt

ions

and

sim

plifi

catio

ns m

ade.

6

Ris

k of

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s in

indi

vidu

al

stud

ies

12D

escr

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met

hods

use

d fo

r ass

essi

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sk o

f bia

s of

indi

vidu

al s

tudi

es (i

nclu

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spe

cific

atio

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whe

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th

is w

as d

one

at th

e st

udy

or o

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me

leve

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nd h

ow th

is in

for m

atio

n is

to b

e us

ed in

any

dat

a sy

nthe

sis.

6-7

Sum

mar

y m

easu

res

13S

tate

the

prin

cipa

l sum

mar

y m

easu

res

(e.g

., ris

k ra

tio, d

iffer

ence

in m

eans

). -

Syn

thes

is o

f res

ults

14

Des

crib

e th

e m

etho

ds o

f han

dlin

g da

ta a

nd c

ombi

ning

resu

lts o

f stu

dies

, if d

one,

incl

udin

g m

easu

res

of

cons

iste

ncy

(e.g

., I2 )f

or e

ach

met

a-an

alys

is.

-

Pag

e 1

of 2

70

Sect

ion/

topi

c #

Che

cklis

t ite

m

Rep

orte

d on

pag

e #

Ris

k of

bia

s ac

ross

stu

dies

15

Spe

cify

any

ass

essm

ent o

f ris

k of

bia

s th

at m

ay a

ffect

the

cum

ulat

ive

evid

ence

(e.g

., pu

blic

atio

n bi

as,

sele

ctiv

e re

porti

ng w

ithin

stu

dies

). -

Add

ition

al a

naly

ses

16D

escr

ibe

met

hods

of a

dditi

onal

ana

lyse

s (e

.g.,

sens

itivi

ty o

r sub

grou

p an

alys

es, m

eta-

regr

essi

on),

if do

ne, i

ndic

atin

g w

hich

wer

e pr

e-sp

ecifi

ed.

-

RES

ULT

S St

udy

sele

ctio

n 17

Giv

e nu

mbe

rs o

f stu

dies

scr

eene

d, a

sses

sed

for e

ligib

ility

, and

incl

uded

in th

e re

view

, with

reas

ons

for

excl

usio

ns a

t eac

h st

age,

idea

lly w

ith a

flow

dia

gram

. 7

and

Figu

re 1

Stud

y ch

arac

teris

tics

18Fo

r eac

h st

udy,

pre

sent

cha

ract

eris

tics

for w

hich

dat

a w

ere

extra

cted

(e.g

., st

udy

size

, PIC

OS

, fol

low

-up

perio

d) a

nd p

rovi

de th

e ci

tatio

ns.

7-10

and

Addi

tiona

lTa

ble

1

Ris

k of

bia

s w

ithin

stu

dies

19

Pre

sent

dat

a on

risk

of b

ias

of e

ach

stud

y an

d, if

ava

ilabl

e, a

ny o

utco

me

leve

l ass

essm

ent (

see

item

12

). 12

-13

and

Addi

tiona

lTa

ble

1R

esul

ts o

f ind

ivid

ual s

tudi

es

20Fo

r all

outc

omes

con

side

red

(ben

efits

or h

arm

s),p

rese

nt, f

or e

ach

stud

y: (a

) sim

ple

sum

mar

y da

ta fo

r ea

ch in

terv

entio

n gr

oup

(b) e

ffect

est

imat

es a

nd c

onfid

ence

inte

rval

s, id

eally

with

a fo

rest

plo

t. A

dditi

onal

Tabl

e 1

Syn

thes

is o

f res

ults

21

Pre

sent

the

mai

n re

sults

of t

he re

view

. If m

eta-

anal

yses

are

don

e, in

clud

e fo

r eac

h, c

onfid

ence

inte

rval

s an

d m

easu

res

of c

onsi

sten

cy7-

13

Ris

k of

bia

s ac

ross

stu

dies

22

Pre

sent

resu

ltsof

any

ass

essm

ent o

f ris

k of

bia

s ac

ross

stu

dies

(see

Item

15)

. 13

and

Addi

tiona

lTab

le

1A

dditi

onal

ana

lysi

s 23

Giv

e re

sults

of a

dditi

onal

ana

lyse

s, if

don

e (e

.g.,

sens

itivi

ty o

r sub

grou

p an

alys

es, m

eta-

regr

essi

on [s

ee

Item

16]

). N

/A

DIS

CU

SSIO

N

Sum

mar

y of

evi

denc

e 24

Sum

mar

ize

the

mai

n fin

ding

s in

clud

ing

the

stre

ngth

of e

vide

nce

for e

ach

mai

n ou

tcom

e; c

onsi

der t

heir

rele

vanc

e to

key

gro

ups

(e.g

., he

alth

care

pro

vide

rs, u

sers

, and

pol

icy

mak

ers)

. 7-

13

Lim

itatio

ns

25D

iscu

ss li

mita

tions

at s

tudy

and

out

com

ele

vel (

e.g.

, ris

k of

bia

s), a

nd a

t rev

iew

-leve

l (e.

g., i

ncom

plet

e re

triev

al o

f ide

ntifi

ed re

sear

ch, r

epor

ting

bias

). 15

Con

clus

ions

26

Pro

vide

a g

ener

al in

terp

reta

tion

of th

e re

sults

in th

e co

ntex

t of o

ther

evi

denc

e, a

nd im

plic

atio

ns fo

r fu

ture

rese

arch

. 16

FUN

DIN

G

Fund

ing

27D

escr

ibe

sour

ces

of fu

ndin

g fo

r the

sys

tem

atic

revi

ew a

nd o

ther

sup

port

(e.g

., su

pply

of d

ata)

; rol

e of

fu

nder

s fo

r the

sys

tem

atic

revi

ew.

18

From

: M

oher

D,

Libe

rati

A, T

etzl

aff

J, A

ltman

DG

, Th

e P

RIS

MA

Gro

up (

2009

). P

refe

rred

Rep

ortin

g Ite

ms

for

Sys

tem

atic

Rev

iew

s an

d M

eta-

Ana

lyse

s: T

he P

RIS

MA

Sta

tem

ent.

PLo

S M

ed 6

(6):

e100

0097

. do

i:10.

1371

/jour

nal.p

med

1000

097

For m

ore

info

rmat

ion,

vis

it:w

ww

.pris

ma-

stat

emen

t.org

.

Pag

e 2

of 2

71

72

CHAPTER THREE

Context and methods overview

3.1 Context of the studies within this thesis

This thesis draws on original data from three studies. Chapter Four (Paper Three),

Chapter Five (Paper Four) and Chapter Seven (Paper Six) utilised baseline data

from the Transform-Us! randomised controlled trial, and Chapter Six (Paper Five)

utilised combined data from two large cohort studies: the Children’s Living in

Active Neighbourhoods Study (CLAN) and the Health Eating and Play Study

(HEAPS). This chapter describes the methodology of Transform-Us! and

CLAN/HEAPS, and my role within each study. An overview of the study

characteristics is provided in Table 3.1.

C

hapt

er T

hree

: Con

text

and

met

hods

ove

rvie

w

73

Tabl

e 3.

1 C

hara

cter

istic

s of s

tudi

es in

corp

orat

ed in

to th

is th

esis

Stud

y na

me

Tran

sfor

m-U

s!

CLA

N

HEA

PS

Stud

y ty

pe

Ran

dom

ised

con

trolle

d tri

al

Coh

ort s

tudy

C

ohor

t stu

dy

Stud

y du

ratio

n 30

mon

ths

5 ye

ars

5 ye

ars

Sam

ple

size

(bas

elin

e)

595

child

ren

1220

chi

ldre

n 15

62 c

hild

ren

Dat

a co

llect

ion

T1: (

Feb-

June

201

0)

T2: (

Nov

/Dec

201

0)

T3: (

Nov

/Dec

201

1)

T4: (

Nov

/Dec

201

2)

T1: 2

001

T2: 2

004

T3

: 200

6

T1: 2

002-

2003

T2

: 200

6

T3: 2

008

Mea

sure

s (us

ed in

this

thes

is)

Obj

ectiv

e m

easu

res o

f PA/

SB

Ant

hrop

omet

ry

Sur

vey

Tim

e-us

e lo

g

Act

iGra

ph a

ccel

erom

etry

, Act

ivPA

L in

clin

omet

er

Mea

sure

d he

ight

and

wei

ght

Chi

ld se

lf- a

nd p

aren

t pro

xy-r

epor

t P

aren

t pro

xy-r

epor

t

C

ompu

ter S

cien

ce A

pplic

atio

ns

(bec

ame

Act

iGra

ph) a

ccel

erom

etry

- P

aren

t sel

f-re

port

A

ccel

erom

eter

mod

el

Epo

ch u

sed

Cut

poi

nts u

sed

GT3

X

15-

sec

Fre

edso

n (T

rost

et a

l., 2

002a

)

716

4 6

0-se

c F

reed

son

(Tro

st e

t al.,

200

2a)

The

sis C

hapt

er/P

aper

Cha

pter

Fou

r, P

aper

Thr

ee: S

tand

ardi

sing

the

'afte

r-sc

hool

' per

iod

for c

hild

ren'

s phy

sica

l act

ivity

an

d se

dent

ary

beha

viou

r C

hapt

er F

ive,

Pap

er F

our:

Con

tribu

tion

of th

e af

ter-

scho

ol p

erio

d to

chi

ldre

n's d

aily

par

ticip

atio

n in

phy

sica

l act

ivity

and

sede

ntar

y be

havi

ours

. C

hapt

er S

even

, Pap

er S

ix: C

orre

late

s of a

fter

scho

ol p

hysi

cal a

ctiv

ity a

nd se

dent

ary

beha

viou

r

Cha

pter

Six

, Pap

er F

ive:

5-y

ear

chan

ges i

n af

ters

choo

l phy

sica

l act

ivity

an

d se

dent

ary

beha

vior

Chapter Three: Context and methods overview

74

3.2 The Transform-Us! Study

The Transform-Us! study was a National Health and Medical Research Council

(NHMRC) funded randomised controlled trial involving 595 grade 3 children

(children invited to participate n=1606; response rate 37%) from 20 randomly

selected primary (elementary) schools in metropolitan Melbourne, Australia. The

18-month Transform-Us! intervention was delivered by class teachers to all year 3

students in year one (2010) and grade 4 students the following year (2011). A 12-

month follow-up period occurred while the children were in grade 5 (2012). The

schools were randomised to one of three intervention groups which aimed to 1)

target physical activity in the home and school settings; 2) target sedentary

behaviour in the home and school settings; 3) target physical activity and

sedentary behaviour in the home and school settings; or 4) current practice control

group. Baseline data collection occurred prior to commencement of the

intervention. Details of the Transform-Us! recruitment methods and intervention

are described in the published methods paper in which the candidate is a co-

author (Salmon et al., 2011) (Appendix 3.1). A brief explanation of these are

provided below.

3.2.1 Aim of Transform-Us!

The primary aim of Transform-Us! was to determine whether an 18-month, multi-

setting behavioural intervention targeting sedentary behaviour (SB-I) and physical

activity (PA-I) alone or in combination (SB+PA-I) results in lower rates of

sedentary behaviour and higher levels of physical activity among 8-9 year old

children compared with current practice.


75

The secondary aims were to: determine the independent and combined effects of

SB-I, PA-I and SB+PA-I on children’s metabolic and cardiovascular risk factors

for health; identify the mediators and moderators of the intervention; determine

whether changes in behavioural and health outcomes are maintained 12-months

post-intervention; and determine whether SB-I, PA-I and SB+PA-I are cost-

effective.

3.2.2 Ethical approval for Transform-Us!

Ethical approval was obtained from the Deakin University Human Research

Ethics Committee (EC 141-2009). Approval was obtained from the Victorian

Department of Education and Training (2009_000344) and the Catholic

Education Office (Project Number 1545). Parental consent was required for

parent’s participation and children’s participation in any data collection prior to

their involvement. Child assent was required from children on the assessment

days. See Appendix 3.2 for ethical approval.

3.2.3 Recruitment of Transform-Us! participants

The participating schools were required to have an enrolment of at least 300

students and be located within a 50km (31 miles) radius of the City of Melbourne.

Using the schools’ suburb socioeconomic index for areas (SEIFA) score (suburb

disadvantage score) (Australian Bureau of Statistics, 2006b), schools were

stratified into the first (n=74), third (n=74) and fifth (n=71) quintile to represent

low-, mid- and high- socioeconomic status (SES) areas. Schools in each stratum

were randomly ordered with probabilistic weighting according to enrolment

number. The principals were then sequentially contacted via email or phone to


76

arrange a face-to-face meeting and invitation to participate. Recruitment of

schools in the high-SES areas proved difficult as they were apprehensive to meet

and discuss Transform-Us! and many believed their students were already active

enough so this was not relevant to them. Therefore, the mid- and high-SES groups

were combined. In total 8 of the 41 schools in the low SES areas who were

approached consented to participate (19.5% response rate) and 12 of the 96

schools in mid- to high-SES areas who were approached consented to participate

(12.5% response rate). Schools within each SES group were then randomised into

an intervention group using computer-generated blocks of four.

3.2.4 My role in Transform-Us!

Throughout my candidature I was the project manager of Transform-Us!. In this

role I was directly involved in the initial pilot study that trialled the proposed

intervention strategies among teachers, parents and children from one primary

school in Melbourne. The process evaluation data from teachers, parents and

children involved in this pilot study informed the final intervention. I also

managed the Transform-Us! reliability and validity study to assess the reliability

of survey measures used in the intervention and in Chapter Five (Paper Four) and

Chapter Seven (Paper Six). In addition, as project manager I oversaw the

recruitment of and liaison with schools, teachers and participants involved in

Transform-Us!. I was responsible for the recruitment, training and management of

a team of over 80 field staff employed to conduct research visits and assessments

with participating children; co-ordination of administration staff to assist with the

day-to-day running of Transform-Us!; and an equipment manager who initialised

and downloaded the accelerometers and activPALs used in Transform-Us!. I


77

assisted with writing the initial National Ethics Application Form (NEAF) for the

Deakin University Human Research Ethics Committee and the applications for

approval from the Department of Education and Training and the Catholic

Education Office as well as all modification requests. I participated in the

research visits to schools to conduct the evaluation assessments with participating

children. I was involved in developing coding manuals for surveys and data

cleaning protocols. Furthermore, I was involved in the development of

intervention materials including class lessons, standing lesson strategies, active

breaks strategies, active and standing homework suggestions and newsletters sent

to families.

I managed the budget for the funding obtained from the NHMRC as well as

additional funds obtained from the MAZDA foundation, a Diabetes Australia

Research Trust (DART) grant and Deakin University funds. Further, I actively

contributed to journal articles, and conference abstracts and presentations on

Transform-Us!. For my PhD, I developed unique survey measures that were

included in the baseline child and parent surveys (see Appendix 3.3 for the

Transform-Us! Child survey and Appendix 3.4 for the Transform-Us! Parent

surveys) and a two-day after-school log which were incorporated in the data

collection of the RCT. I then extracted the behaviour outcomes using objective

and survey measures (i.e. children’s physical activity and sedentary behaviour

after-school) that were specific to this thesis.

3.3 The Children’s Living in Active Neighbourhoods Study (CLAN) and the

Health Eating and Play Study (HEAPS)


78

The Children’s Living in Active Neighbourhoods Study (CLAN) and the Health

Eating and Play Study (HEAPS) are two cohort studies. Both collected survey

data from parents and objective physical activity and sedentary time data from

children and adolescents over a five year period. Data presented in Chapter

Five (Paper Four) was obtained by combining outcome measures from both

datasets. Data collection for CLAN and HEAPS occurred on three occasions (see

Table 3.1).

3.3.1 Aim of CLAN and HEAPS

The aim of CLAN was to enhance the knowledge and understanding of

physical activity and sedentary behaviour patterns of Australian children and

how the family environment influences physical activity and sedentary

behaviour among children. The aim of HEAPS was to examine how the

family environment influences the eating and physical activity behaviours of

Australian children. The common aims and subsequently the type of data

collected from these two studies meant that it was possible for the data to be

merged.

3.3.2 My role in CLAN and HEAPS

Prior to my PhD candidature, I was the field manager for the final HEAPS data

collection (2008) under the guidance of the project manager. During this time I

was involved in maintaining communication with participants and scheduling

assessment visits. I was involved in the recruitment, training and management of

casual field staff to conduct the field visits to collect the child data. Further, I was


79

actively involved in the field visits and data collection. I had no active role in the

CLAN study prior to my candidature.

3.3.3 Ethical approval for CLAN and HEAPS

Ethical approval was obtained for CLAN and HEAPS from the Deakin University

Human Research Ethics Committee (CLAN: EC40-2003; HEAPS: EC289-2005).

Approval was also obtained from the Department of Education and Early

Childhood Development Victoria (CLAN: SOS00141; HEAPS: SOS002174) and

the Catholic Education Office (CLAN: GE00/0010; HEAPS: GE02/2009).

Parental consent was required for parents’ and children’s participation in any data

collection prior to their involvement. Child assent was required from children on

the assessment days. See Appendices 3.5 and 3.6 for CLAN and HEAPS ethical

approval respectively.

3.3.4 Recruitment of CLAN and HEAPS participants

Children and their parents were recruited into CLAN through 19 state primary

schools in high- and low-SES areas of metropolitan Melbourne, Australia. Ten

high-SES (determined via Socioeconomic Index for Areas, SEIFA (Australian

Bureau of Statistics, 1998)) and nine low-SES schools from the eastern and

western regions of Melbourne were selected via stratified random sampling

proportionate to school size (enrolment >200 students). Five schools declined and

were replaced with randomly selected schools. Two cohorts of children

participated in CLAN at baseline: cohort 1 consisted of 295 children from grade

Prep (5-6 years, 27% response rate) and cohort 2 consisted of 919 children from

grades 5-6 (10-12 years, 44% response rate). All participants were invited to be


80

contacted in the future and provide consent for further follow-up participation.

Follow-up data occurred in 2004 and again in 2006.

HEAPS also utilised the Australian Bureau of Statistics’ Socioeconomic Index for

Areas (Australian Bureau of Statistics, 1998) to classify Melbourne State and

Catholic primary schools with student enrolments greater than 200 into SES

quintiles. To provide a sample representative of high-, middle- and low-SES

areas, 13 schools from the 1st, 3rd and 5th quintiles were selected and invited to

participate. Twenty-four schools (9 high-, 7 middle- and 8 low-SES) agreed to

participate. Initially HEAPS was to study grade prep children only and therefore

all prep children attending HEAPS schools were invited to participate in

2002/2003 (Cohort 1). In 2003, the study was extended and grade 5-6 children at

15 of the 24 HEAPS schools were invited to participate (Cohort 2). These 15

schools were representative of the high-, middle- and low-SES areas. At baseline

parental consent was received for 1562 children, 615 from cohort 1 (38%

response rate) and 947 from cohort 2 (45% response rate). All participants were

invited to be contacted in the future and provide consent for further follow-up

participation. Follow-up data collection occurred in 2006 and again in 2008.

The following four chapters contain the original research components of this

thesis. Each chapter contains a paper either published, or under review in a peer-

review journal or in preparation for publication. The papers are prepared in

accordance to the structure, formatting and referencing guidelines specified by the

journal in which it is published.

81

CHAPTER FOUR

Paper Three: Standardising the ‘after-school’

period for children’s physical activity and sedentary

behaviour

As discussed in Sections 2.7-2.10 and Sections 2.12-2.13, there is currently no

standardised definition of the “after-school period”. The definition of this period

varies greatly between studies (e.g. 2pm-midnight (Nilsson et al., 2009b), 3-5pm

(Fairclough et al., 2007) and from the school bell until bedtime (Rushovich et al.,

2006)), making it difficult to compare findings. Therefore, it is essential for the

future study of children’s after-school physical activity and sedentary behaviours

to develop a standard definition of the ‘after-school period’. Once adopted, this

will enable direct comparisons of studies examining children’s after-school

behaviours. A standardised definition will allow for comparable prevalence rates

of children’s after-school physical activity and sedentary behaviour to be

established. Further, the correlates of these behaviours will be able to be

examined and compared across different subgroups such as nationalities. The

following paper provides a standardised definition of the ‘after-school period’.

This paper is published in the Health Promotion Journal of Australia (Impact

Factor: 0.945) as: Arundell L, Salmon J, Veitch J, O'Connell E, Hinkley T, Hume

C. 2013. Standardising the 'after-school' period for children's physical activity

and sedentary behaviour. Health Promotion Journal of Australia, 24(1):65-7.


Standardising the ‘after-school’ period for children’sphysical activity and sedentary behaviour

Lauren ArundellA,B, Jo SalmonA, Jenny VeitchA, Eoin O’ConnellA, Trina HinkleyA

and Clare HumeA

ACentre for Physical Activity and Nutrition Research, School of Exercise and Nutrition Sciences,Deakin University, 221 Burwood Highway, Burwood, Vic. 3125, Australia.

BCorresponding author. Email: [email protected]

AbstractIssue addressed: Studies examining children’s after-school physical activity (PA) and sedentary behaviours (SB) often use arbitrarytimes to signify the period start and end. A standardised time is required for future research examining this period. The aim of thepresent studywas to compare children’s after-school behaviour using three definitions of the after-school period, namely (1) end ofschool to 6 pm; (2) end of school to dinner time; and (3) end of school to sunset, to determine the extent of variability in PA and SBduring the after-school period depending on the definition used.Methods:Children (n= 308; aged 8 years) from theMelbourne Transform-Us! interventionwore an accelerometer and a subsample(n= 112) wore an activPAL inclinometer in 2010. The end of school bell time was obtained from the child’s school, parentscompleted a 2-day log reporting their child’s dinner time and sunset times were obtained from Geoscience Australia. ActiGraphaccelerometers assessed the proportion of time spent sedentary (SED) and that spent in light (LPA),moderate (MPA) andmoderate-to-vigorous (MVPA) PA during the three time periods; activPAL inclinometers assessed the proportion of time spent sitting (SIT).Results: Apart from the end of school time (3:30 pm), dinner (range 3:30 pm–8:40 pm) and sunset (range 5:07 pm–7:34 pm) timesvaried. Despite this, there were no significant differences in estimates of the proportions of time children spent in SED, LPA, MPA,MVPA or SIT between the three after-school periods examined.Conclusion:Given the small differences inSED, PAandSITduring theafter-schoolperiod regardless of thedefinition (6pm, sunsetordinner time), it appears that applying a standardised definition of end of school to 6 pm is acceptable for defining children’s PA andSB during the after-school period.

So what? The use of a standardised after-school definition (end of school to 6 pm), will enable future studies exploring children’safter-school PA and SB to be more comparable.

Key words: physical activity, sedentary behaviour, children, measurement development.

Received 27 July 2012, accepted 11 January 2013, published online 21 March 2013

Introduction

The after-school period offers an opportunity to promote children’sphysical activity (PA) and reduce sedentary behaviours (SB).1 Afterschool, primary school children are not restricted by schooltimetabling and may have the opportunity to engage in active andsedentary pastimes,2 particularly during daylight hours. However,studies have examined after-school PA and SB during a variety ofperiods, including 1:05 pm–bedtime,3 3 pm–5pm,1 3 pm–7:30 pm,4 3pm–11:30 pm,5 3:30 pm–8:30 pm,6 4 pm–6 pm7 and from the schoolbell until 6 pm.8 The variation in these definitions potentiallyexcludes important PA of varying intensities (e.g. light PA (LPA), suchas walking home from school; or moderate-to-vigorous PA (MVPA),

such as sports training) or SBs (e.g. TV viewing after dinner), orcould provide behavioural information that is not conducive todiscretionary PA and SB intervention development and delivery(e.g. being dark outside).

It is unknown whether a standardised definition may result in anunder- or overestimation of children’s PA or SB during this period;however, a standardised after-school period definitionwould enablepopulation comparisons of children’s PA and SB prevalence andpatterning. This will assist in establishing the contribution theafter-school period makes to the achievement of PA and SBrecommendations, and after-school intervention development andimplementation. A standardised definition does not diminish the

Journal compilation � Australian Health Promotion Association 2013 CSIRO Publishing www.publish.csiro.au/journals/hpja

Health Promotion Journal of Australia, 2013, 24, 65–67 Research and Methodshttp://dx.doi.org/10.1071/HE12910

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potential for children to accumulate PA and SB outside of this period,although it has been identified as a ‘critical window’9 when PA and/or SB interventions are likely to be highly amenable. The aim of thepresent study was to compare children’s after-school behaviourusing three definitions of the after-school period, namely (1) end ofschool to 6 pm; (2) end of school to dinner time; and (3) end of schoolto sunset, to determine the extent of variability in PA and SB duringthe after-school period depending on the definition used.

Methods

ParticipantsThe present study was nested within the baseline data collectionof the randomised controlled trial Transform-Us! (ACTRN12609000715279; ISRCTN83725066). Grade 3 children (n= 1606) at 20 primaryschools in Victoria (Australia) received information explaining theassessments and consent forms. Of these children, 551 consented towear accelerometers and inclinometers (34% response rate).Assessments were conducted in February–June 2010.

Approval was obtained from Deakin University Human ResearchEthics Committee, the Victorian Department of Education and EarlyChildhood Development and the Catholic Education Office.

Measures

Period time pointsSchools provided the end of school bell times. Parents of consentingchildren were asked to complete a 2-day after-school log, markingwhen their child ate dinner. Sunset times for these days wereobtainedusing theNationalMappingDivision’s Sunrisenset Program(version 2.2; Australian Government Geoscience, Symonston, ACT,Australia). From this the three after-school periods were created thatwere specific to each child: (1) endof school to 6pm; (2) endof schoolto dinner time; and (3) end of school to sunset.

After-school PA, SB and sitting timeChildrenwerefittedwith aGT3XActigraphaccelerometer (Actigraph,Pensacola, FL, USA), which provides objective estimates of PA andsedentary time and has acceptable validity among children.10

Accelerometers were worn on a belt at the child’s right hip andcollected data in 15-s epochs.11 Tomeasure sitting time, a subsampleof children also wore an activPAL inclinometer (PAL Technologies,Glasgow, UK). The inclinometer classifies activity into periods ofsitting and/or lying down, standing and stepping12 and hasacceptable validity in adults13,14 and pre-school children.15 TheactivPAL was worn on an elastic garter positioned at themidanterioraspect of the right thigh. Both units were worn during waking hours(excluding water-based activities) for 8 consecutive days.

Data management and analysisAccelerometer data were downloaded using Actilife LifestyleMonitoring System (v5.1; Actigraph), whereas activPAL data weredownloaded using activPAL Professional (v8.3.5; PAL Technologies).The PAL data files were transformed into Excel files reporting time

spent sitting/lying (SIT), standing and stepping in 15-s epochs. Rawaccelerometer data files and transformed PAL files were run throughspecifically developed Excel macros to determine non-wear time(�10 consecutiveminutes of zero counts).Wear time criteriawere setat �70% of the period for inclusion in analysis. Using age-specificaccelerometer cut-off points,16 children’s accelerometer-derivedsedentary time (SED; �1.5 metabolic equivalents (METs), defined as<100 counts min–1), LPA (1.6–3.9 METs), moderate PA (MPA; 4.0–5.9METs) and MVPA (�4.0 METs) were calculated. The PA, SED and SITdata were matched to the 2 days that the after-school log wascompleted andwere extracted for the three after-school periods thatwere calculated for that child. The proportion of each of the threeperiods spent engaged in SED, LPA, MPA, MVPA and SIT was thencalculated. Figure 1 shows an example of the accelerometer data forone participant.

Meanvalues and95%confidence intervals (CI)were calculated for theproportion of time children spent in SED, LPA, MPA, MVPA and SITduring the three after-school periods. Significant differences weredetermined by examining whether the 95% CIs overlapped. Themedian and range for the end of school, sunset and dinner timeswere calculated for descriptive purposes.

Results

Three hundred and eight children (aged 8 years; 42% boys) hadActiGraph and after-school log data and 112 children had activPALand after-school log data. The median end of school, dinner andsunset times were 3:30 pm (no variation), 6:20 pm (range 3:30pm–8:40 pm; however, only four children reported dinner at 3:30 pm)and 5:53 pm (range 5:07 pm–7:34 pm), respectively.

10011.0%

25.0%

64.0% 59.0%

25.4%

15.6%

%MVPA %LPA %SED

17.7%

25.8%

56.5%

Prop

ortio

n of

tim

e du

ring

the

peri

od 90

80

70

60

50

40

30

20

10

End-of-school to 6pm(18:00 hours)

End-of-school to Dinner(19:00 hours)

End-of-school to Sunset(18:31 hours)

0

Fig. 1. Example of one child’s accelerometer measured after-schoolbehaviours during the three periods examined (end of school to 6 pm(18:00 hours), end of school to dinner time and end of school to sunset). SED,sedentary time; LPA, light physical activity; MVPA, moderate-to-vigorousphysical activity.

66 Health Promotion Journal of Australia L. Arundell et al.

83

The proportion of time spent in SED, LPA, MPA, MVPA and SIT fromend of school to 6 pm (Period 1), end of school to dinner time (Period2) and end of school to sunset (Period 3) is given in Table 1. Themaximum difference in the proportion of time spent in these fivebehaviours during these three periods was 2%. There were nosignificant differences between the three after-school periods foreach of the behaviours assessed because all 95% CIs overlapped.

Discussion

The present study is the first to determine the extent of variability inchildren’s PA and SB during the after-school period depending onthe definition used. The results of the present study showed nosignificant differences in the proportion of time children spent inaccelerometer-determined SED time, LPA,MPAorMVPA, or activPAL-determined SIT between end of school bell time to children’s dinnertime, endof school bell time to sunset time and the endof school belltime to 6 pm. Therefore, in relation to Australian primary schoolchildren’s PA andSB in the after-school period, a standardised timeofend of school bell time to 6:00 pm may be used to signify thebeginning and end of the after-school period, respectively. Further,given the variability of children’s dinner times and the changes insunset times across seasons, end of school bell time to 6:00 pm is afeasible time period to use in large population studies because itwould eliminate methodological issues that may arise when usingdifferent times for different children or seasons.

Limitations of the present study include the generalisability of thefindings to other countries, where children’s school days mayconclude at different times. In addition, objective measures do notprovide behavioural information, which may be important for thedevelopment of interventions. Nevertheless, the use of objectivemeasures of PA, SB and sitting time is a study strength, as is the use oftime markers (i.e. end of school, dinner and sunset times) specific toeach child.

Conclusion

There were no significant differences in the proportion of timeAustralian children spent in SED, LPA, MPA, MVPA or SIT between thethree after-school periods. Therefore, the use of a standardised timeperiod (end of school bell time to 6:00 pm) adequately representschildren’s after-school PA and SB behaviours and may be used infuture studies.

Acknowledgements

JS was supported by a National Health andMedical Research CouncilofAustralia (NHMRC)Principal ResearchFellowship (APP1026216). CHand JV were supported by a National Heart Foundation of AustraliaPostdoctoral Fellowship Award. This project was funded by theNHMRC (533815).

References1. Fairclough SJ, Butcher ZH, Stratton G. Whole-day and segmented-day physical

activity variability of northwest England school children. Prev Med 2007; 44(5):421–5. doi:10.1016/j.ypmed.2007.01.002

2. Australian Bureau of Statistics. Children’s participation in cultural and leisureactivities. Canberra: Commonwealth of Australia; 2004.

3. Loucaides CA, Jago R, Charalambous I. Promoting physical activity during schoolbreak times: piloting a simple, low cost intervention. Prev Med 2009; 48(4): 332–4.doi:10.1016/j.ypmed.2009.02.005

4. Dengel DR, Hearst MO, Harmon JH, Forsyth A, Lytle LA. Does the built environmentrelate to the metabolic syndrome in adolescents? Health Place 2009; 15(4): 946–51.doi:10.1016/j.healthplace.2009.03.001

5. Dzewaltowski DA, Ryan GJ, Rosenkranz RR. Parental bonding may moderatethe relationship between parent physical activity and youth physical activityafter school. Psychol Sport Exerc 2008; 9(6): 848–54. doi:10.1016/j.psychsport.2007.10.004

6. Cooper AR, Page A, Wheeler B, Hillsdon M, Griew P, Jago R. Patterns of GPSmeasured time outdoors after school and objective physical activity in Englishchildren: the PEACH project. Int J Behav Nutr Phys Act 2010; 7(1): 31–9. doi:10.1186/1479-5868-7-31

7. Hesketh K, Graham M, Waters E. Children’s after-school activity: associations withweight status and family circumstance. Pediatr Exerc Sci 2008; 20(1): 84–94.

8. Rushovich BR, Voorhees CC, Davis CE, Neumark-Sztainer D. Pfeiffer KA, Elder JP,Going S, Marino VG. The relationship between unsupervised time after school andphysical activity in adolescent girls. Int J Behav Nutr Phys Act 2006; 3: 20–8.doi:10.1186/1479-5868-3-20

9. Welk GJ, Corbin CB, Dale D. Measurement issues in the assessment of physicalactivity in children. Res Q Exerc Sport 2000; 71(Suppl): S59–73.

10. Trost SG,WardD,Moorehead S,Watson P, Riner PW, Burke J. Validity of the computerscience and applications (CSA) activitymonitor in children.Med Sci Sports Exerc 1998;30: 629–33. doi:10.1097/00005768-199804000-00023

11. Bailey RC,Olson J, Pepper SL, Porszasz J, BarstowTJ, CooperDM. The level and tempoof children’s physical activities: an observational study.Med Sci Sports Exerc 1995; 27(7): 1033–41. doi:10.1249/00005768-199507000-00012

12. Brockman R, Jago R, Fox KR. The contribution of active play to the physical activity ofprimary school children. Prev Med 2010; 51(2): 144–7. doi:10.1016/j.ypmed.2010.05.012

13. Ryan CG, Gray H, Newton M, Granat MH. The convergent validity of free-living physical activity monitoring as an outcome measure of functional abilityin people with chronic low back pain. J Back Musculoskelet Rehabil 2008; 21:137–42.

14. Grant PM, Ryan CG, TigbeWW, GranatMH. The validation of a novel activitymonitorin the measurement of posture and motion during everyday activities. Br J SportsMed 2006; 40: 992–7. doi:10.1136/bjsm.2006.030262

15. Davies G, Reilly JJ, McGowan AJ, Dall PM, Granat MH, Paton JY. Validity, practicalutility, and reliability of the activPAL(TM) in preschool children.Med Sci Sports Exerc2012; 44(4): 761–8. doi:10.1249/MSS.0b013e31823b1dc7

16. Trost SG, Pate RR, Sallis JF, Freedson P, Taylor W, Dowda M, Sirard J. Age and genderdifferences in objectively measured physical activity in youth. Med Sci Sports Exerc2002; 34(2): 350–5. doi:10.1097/00005768-200202000-00025

Table1. Proportionof timespent inaccelerometer-derivedsedentary,light, moderate and moderate-to-vigorous physical activity, as well as

inclinometer-derived sitting during three after-school periodsData show mean values with 95% confidence intervals in parentheses. SED,sedentary time; LPA, light physical activity; MPA, moderate physical activity;

MVPA, moderate-to-vigorous physical activity; SIT, sitting time

Period 1(end of schoolto 6:00 pm)

Period 2(end of school todinner timeA)

Period 3(end of school

to sunset timeB)

AccelerometerSED 47.5% (46, 49) 47.3% (45, 49) 47.0% (46, 48)LPA 24.7% (24, 25) 24.6% (24, 25) 24.6% (24, 25)MPA 21.7% (21, 23) 22.0% (21, 23) 22.0% (21, 23)MVPA 27.9% (27, 29) 28.2% (27, 30) 28.3% (27, 30)

ActivPALSIT 48.9% (46, 52) 47.7% (45, 52) 47.3% (45, 52)

AObtained from the after-school log.BObtained from the National Mapping Division’s Sunrisenset Program(version 2.2; Australian Government Geoscience, Symonston, ACT, Australia).

Standardising the ‘after-school’ period Health Promotion Journal of Australia 67

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CHAPTER FIVE

Paper Four: Contribution of the after-school period

to children’s daily participation in physical activity

and sedentary behaviours

The standardised definition of the after-school period produced in Chapter Four

will be used for the remaining studies included in this thesis. Using this definition,

a precise and comparable examination of the cross-sectional prevalence rates of

children’s after-school physical activity and sedentary behaviour can be

performed. Further, calculation of the contribution the after-school period makes

to children’s daily behaviour levels can be conducted. The following paper

provides a cross-sectional examination of children’s after-school physical activity

and sedentary behaviour and the contribution the behaviours accrued during this

period make to children’s daily behaviours. This paper is published in PLoS One

(Impact factor: 3.23) as:

Arundell L, Hinkley T, Veitch J, Salmon J. 2015. Contribution of the After-School

Period to Children's Daily Participation in Physical Activity and Sedentary

Behaviours. PLoS One, 10: e0140132.


RESEARCH ARTICLE

Contribution of the After-School Period toChildren’s Daily Participation in PhysicalActivity and Sedentary BehavioursLauren Arundell*, Trina Hinkley, Jenny Veitch, Jo Salmon

Centre for Physical Activity and Nutrition Research, School of Exercise and Nutrition Sciences, Faculty ofHealth, Deakin University, Burwood, Australia

* [email protected]

Abstract

Objectives

Children’s after-school physical activity (PA) and sedentary behaviours (SB) are not well

understood, despite the potential this period holds for intervention. This study aimed to

describe children’s after-school physical activity and sedentary behaviours; establish the

contribution this makes to daily participation and to achieving physical activity and seden-

tary behaviours guidelines; and to determine the association between after-school moder-

ate- to vigorous-intensity physical activity (MVPA), screen-based sedentary behaviours and

achieving the physical activity and sedentary behaviour guidelines.

Methods

Children (n = 406, mean age 8.1 years, 58% girls) wore an ActiGraph GT3X accelerometer.

The percentage of time and minutes spent sedentary (SED), in light- physical activity (LPA)

and MVPA between the end-of-school and 6pm (weekdays) was calculated. Parents (n =

318, 40 years, 89% female) proxy-reported their child’s after-school participation in screen-

based sedentary behaviours. The contribution that after-school SED, LPA, MVPA, and

screen-based sedentary behaviours made to daily levels, and that after-school MVPA and

screen-based sedentary behaviours made to achieving the physical activity/sedentary

behaviour guidelines was calculated. Regression analysis determined the association

between after-school MVPA and screen-based sedentary behaviours and achieving the

physical activity/sedentary behaviours guidelines.

Results

Children spent 54% of the after-school period SED, and this accounted for 21% of children’s

daily SED levels. Boys spent a greater percentage of time in MVPA than girls (14.9% vs.

13.6%; p<0.05), but this made a smaller contribution to their daily levels (27.6% vs 29.8%;

p<0.05). After school, boys and girls respectively performed 18.8 minutes and 16.7 minutes

of MVPA, which is 31.4% and 27.8% of the MVPA (p<0.05) required to achieve the physical

activity guidelines. Children spent 96 minutes in screen-based sedentary behaviours,

PLOS ONE | DOI:10.1371/journal.pone.0140132 October 30, 2015 1 / 11

OPEN ACCESS

Citation: Arundell L, Hinkley T, Veitch J, Salmon J(2015) Contribution of the After-School Period toChildren’s Daily Participation in Physical Activity andSedentary Behaviours. PLoS ONE 10(10): e0140132.doi:10.1371/journal.pone.0140132

Editor: Andrea S. Wiley, Indiana University, UNITEDSTATES

Received: April 7, 2014

Accepted: September 10, 2015

Published: October 30, 2015

Copyright: © 2015 Arundell et al. This is an openaccess article distributed under the terms of theCreative Commons Attribution License, which permitsunrestricted use, distribution, and reproduction in anymedium, provided the original author and source arecredited.

Data Availability Statement: Data used in this papercan be accessed through Deakin University’sresearch repository, DRO, at http://dro.deakin.edu.au/, by searching the manuscript title and authors.

Funding: Transform-Us! was funded by the NationalHealth and Medical Research Council (NHMRC)(533815), www.nhmrc.gov.au. Lauren Arundell issupported by a National Health and MedicalResearch Council (NHMRC) Postgraduate ResearchScholarship (APP1074484), www.nhmrc.gov.au.Jenny Veitch is supported by a National Health andMedical Research Council (NHMRC) Early CareerResearch Fellowship (APP1053426), www.nhmrc.

86

contributing to 84% of their daily screen-based sedentary behaviours and 80% of the sed-

entary behaviour guidelines. After-school MVPA was positively associated with achieving

the physical activity guidelines (OR: 1.31, 95%CI 1.18, 1.44, p<0.05), and after-school

screen-based sedentary behaviours were negatively associated with achieving the seden-

tary behaviours guidelines (OR: 0.97, 95%CI: 0.96, 0.97, p<0.05).

Conclusions

The after-school period plays a critical role in the accumulation of children’s physical activity

and sedentary behaviours. Small changes to after-school behaviours can have large

impacts on children’s daily behaviours levels and likelihood of meeting the recommended

levels of physical activity and sedentary behaviour. Therefore interventions should target

reducing after-school sedentary behaviours and increasing physical activity.

IntroductionIn spite of the evidence of detrimental health outcomes [1,2], children in developed countriesperform suboptimal levels of physical activity (PA) and excessive amounts of sedentary behav-iour (SB) [3–5]. Sedentary behaviours has been defined as “any waking activity characterizedby an energy expenditure�1.5 metabolic equivalents and in a sitting or reclining posture” [6].Current sedentary behaviours guidelines recommend children in many countries limit theirelectronic media use/screen-based sedentary behaviours to less than two hours (�120 minutes)per day [7,8]. In addition, physical activity guidelines state that for health and other benefitschildren should perform at least 60 minutes of moderate- to vigorous-intensity physical activity(MVPA) every day [7,9,10]. However, in 2011–2012 only 7.8% and 7.1% of Australian 5–17year old boys and girls, respectively, achieved both of these guidelines (i.e.�60 minutes ofMVPA/day and�120 minutes of recreational screen-based sedentary behaviour/day) [11].

The after-school period, recently defined as the end-of-school to 6pm [12], has been identi-fied as a key period for the accumulation of children’s physical activity and sedentary behav-iours [13] and for potential intervention implementation. The varying timeframes previouslyused to define the after-school period (e.g. 3.30–8.30pm [14] and 4-6pm [15]) and the differentlocations and contexts of previous research (e.g. attending after-school programs [16]) makedirect comparisons between studies of after school behaviours difficult. However, behavioursperformed after-school can make a significant contribution to daily activities with up to half ofchildren’s daily steps performed after school [17] and up to 72% of daily TV viewing occurringbetween 3pm-9pm [18]. Further, evidence shows that the period becomes more important forthe accumulation of physical activity as children progress through primary (elementary) andinto secondary school [19]. Behaviours performed after school may also contribute to dailyphysical activity and sedentary behaviour levels, and impact the likelihood of children achiev-ing guidelines for health. Although this is currently unknown, an understanding of how theafter-school period contributes to daily physical activity and sedentary behaviour levels andimpacts the possibility of achieving guidelines would provide further rationale for interventionsto target this period.

Subsequently, the aims of this study were to: 1) identify the percentage of the after-schoolperiod boys and girls spend in objectively measured sedentary behaviour (SED), light-intensityphysical activity (LPA), MVPA and proxy-reported screen-based sedentary behaviours; 2)

Children’s After-School Behaviours


gov.au. Trina Hinkley is supported by a NationalHealth and Medical Research Council (NHMRC)Early Career Fellowship (APP1070571), www.nhmrc.gov.au. Jo Salmon is supported by a National Healthand Medical Research Council (NHMRC) PrincipalResearch Fellowship (APP1026216), www.nhmrc.gov.au. The funders had no role in study design, datacollection and analysis, decision to publish, orpreparation of the manuscript.

Competing Interests: The authors have declaredthat no competing interests exist.

87

identify how the after-school period contributes to daily levels of SED, LPA MVPA and screen-based sedentary behaviour; 3) identify how the after-school period contributes to achieving thephysical activity and sedentary behaviours guidelines among boys and girls (i.e.�60 minutesof MVPA/day and�120 minutes of screen-based sedentary behaviour/day); and 4) examinethe association between after-school MVPA and sedentary behaviours and the odds of achiev-ing the physical activity/sedentary behaviours guidelines during weekdays.

MethodsThis study used baseline data from the Transform-Us! intervention (ACTRN 12609000715279;ISRCTN 83725066). Transform-Us! targeted children’s physical activity and sedentary behav-iours and the methods for that intervention have been described in detail elsewhere [20]. Inbrief, 595 grade 3 children (total n = 1606; response rate 37%) were recruited from 20 randomlyselected primary (elementary) schools. The schools were within a 50km (31 miles) radius of thecity of Melbourne, Australia, had an enrolment of over 300 students, and were stratified bysocioeconomic status (SES; 8 of 41 schools in low SES areas and 12 of 96 schools in mid- tohigh-SES areas). For the current study, the children’s baseline accelerometer data and parentproxy-report data (collected Feb—Jun 2010) were used. Details of each of these measures areprovided below.

Ethics StatementEthical approval was obtained from the Deakin University Human Research Ethics Committee,the Victorian Department of Education and Early Childhood Development and the CatholicEducation Office. Written parental consent and child assent to complete the assessments wereobtained prior to participation.

DemographicsChildren reported their age and sex and parent’s self-reported their highest level of education.

Accelerometer-assessed physical activity and sedentary timeChildren were fitted with a GT3X Actigraph accelerometer (Pensacola, FL) by trained research-ers during class time and were informed that the monitors assess how active they are. Acceler-ometers have been shown to have acceptable validity among children [21]. Children wereasked to wear the unit for eight consecutive days (excluding water-based activities and sleeptime) on their right hip using an elastic belt. Data were collected in 15-second epochs [22] anddownloaded using Actilife Lifestyle Monitoring System, Version 5.1. To determine whetherthere may be some bias in physical activity levels, children who achieved 3 valid weekdays ofaccelerometer data were compared with those who achieved 4 or 5+ days; we examined afterschool and daily MVPA and found no differences in MVPA levels (data not shown).

Proxy-report after-school screen-based sedentary behavioursParents’ proxy reported their child’s behaviour as evidence suggests that children younger than10 years cannot reliably report the duration of their activities [23]. Parents reported the dura-tion that their child spent during a typical school week (Monday-Friday) after school and dur-ing the entire day in the following screen-based sedentary behaviours: 1) watching TV/videos/DVDs; 2) playing Play Station/Nintendo/computer games; and 3) using the computer/internet(excluding games). These survey times were based on reliable survey items from the Children'sLeisure Activities Study Survey (CLASS) [23]. The reliability of the modified survey items was



assessed through a 7-day test re-test reliability study, with participants from a convenience-sampled Melbourne primary school in 2009 (n = 49, mean age 41.9 ±4.8 years; 75% female).The reliability of the proxy-report screen time behaviours was determined using intraclass cor-relation coefficients (ICC) which were considered fair (<0.5), moderate (0.5–0.74) or high(�0.75) [24]. Two of the after-school screen-based sedentary behaviours items showed moder-ate reliability (ICC:>0.6) and the remaining item (after-school computer/internet) showedfair reliability (ICC: 0.4). Two of the daily screen-based sedentary behaviours items showed fair(ICC>0.4) reliability and the remaining item (playing Play Station/Nintendo/computergames) showed moderate reliability (ICC:>0.6).

Data management and analysisSpecifically developed excel macros and Stata code (State 12) were used to analyse the rawaccelerometer data files. Data from the end-of-school (end-of-school time data collected fromthe school, mode = 15:30) to 6pm were extracted for analysis. Non-wear time was considered�20 consecutive minutes of zero counts in line with the most commonly used definition asidentified in a recent review of children’s accelerometer studies [25] and because it provides themost accurate estimate of children’s sitting time [26]. Children were required to have 8+ hoursof valid data on at least three weekdays [27] and to have data for at least 50% of the after-schoolperiod on each of those days [19] to be included in the analysis of daily behaviours and theafter-school period respectively.

Previously established age-specific cut-points [28] were used to calculate children’s LPA(1.6–3.9 METs) and MVPA (�4 METs) during the after-school period. MVPA was defined as�4 METs as calibration studies have shown that the energy expenditure of brisk walking isapproximately 4 METs among children and adolescents [29]. SED was defined as<100 counts.min-1 which is the cut point that most closely represents sitting time among children [30]. Thisalso corresponds with the Sedentary Behaviour Research Network’s sedentary behavioursdefinition as sitting has a MET value of up to 1.5 among children [31]. The percentage of theafter-school period in which children participated in SED, LPA and MVPA was calculated.The contribution of each of these to daily SED, LPA and MVPA was calculated as: (minutes inintensity during the after-school period/minutes in intensity during the entire day)�100. Thecontribution that MVPA performed during the after-school period made to achieving thephysical activity guidelines on weekdays was calculated as: (minutes in MVPA during theafter-school period/60)�100. MVPA data were positively skewed so were log transformed priorto all analyses. To aid in interpretability, the untransformed data were also analysed and resultsreported.

Mean daily time in after-school screen-based sedentary behaviours was calculated by sum-ming the durations spent in each screen-based sedentary behaviours and dividing by five. Thecontribution of after-school screen-based sedentary behaviours to total daily screen-based sed-entary behaviours was calculated as: (minutes in screen-based sedentary behaviours time dur-ing the after-school period/minutes in screen-based sedentary behaviours during the entireday)�100. The contribution that screen-based sedentary behaviours performed during theafter-school period made to achieving the sedentary behaviours guidelines (on weekdays wascalculated as: (minutes in screen-based sedentary behaviours after-school/120)�100. T-testswere used to assess sex differences between the behaviour intensities. Logistic regression wasperformed to determine the likelihood of achieving the physical activity guidelines based onthe percentage of the after-school period spent in MVPA. Logistic regression was also per-formed to determine the likelihood of achieving the sedentary behaviour guidelines based onthe time spent in screen-based sedentary behaviours during the after-school period. Both



models were adjusted for clustering by school and the covariates of age, sex and maternal edu-cation. There was no interaction between sex and achieving the physical activity guidelines,therefore all children were analysed together.

ResultsThe final sample consisted of 406 children who had valid survey and accelerometer data for theafter-school period (68% of sample). Of these, 359 also had valid accelerometer data for theentire day (mean age 8.1 years ±0.47; 58% girls). Three-hundred and eighteen parents (meanage 39.5 years ±5.09; 89% female) completed a survey. There were no differences in age or sexamong the children with and without parent proxy-report data. Table 1 shows that both boysand girls spent over half of the after-school period SED (53.7%), almost a third in LPA (32.2%)and 14.1% in MVPA. On average, children spent over an hour SED during the after-schoolperiod and approximately 41 minutes in LPA (no sex differences). Boys performed signifi-cantly more MVPA after school than girls (18.8 [±9.75] minutes vs 16.7 [±8.03] minutes).

During the entire day children spent 60.3% of their time SED, 29.2% in LPA and only 10.6%in MVPA. Girls spent a significantly greater percentage of time in LPA than boys, whereasboys spent a greater percentage of time in MVPA than girls during both the after-school periodand the entire day. The after-school period accounted for more than one-fifth of children’sdaily SED (20.8%) and 27.6% and 29.8% of daily MVPA for boys and girls respectively. The

Table 1. The meanminutes and percentage of the after-school period spent in sedentary time (SED), light- (LPA) andmoderate- to vigorous-inten-sity physical activity (MVPA), and the contribution to daily behaviour and achieving the physical activity (PA) guidelines.

All children(n = 406)

Boys (n = 172) Girls(n = 234)

Mean percentage of time spent SED and in PA during the after-school period % (±SD)

SED 53.7 (±9.96) 54.8 (±10.09) 52.9 (±9.80)

LPA 32.2 (±6.96) 30.4 (±6.67)* 33.5 (±6.86)

MVPA 14.1 (±6.08) 14.9 (±6.26)* 13.6 (±5.89)

Mean time (mins) spent SED and in PA during the after-school period (±SD)

SED 62.3 (±16.82) 62.9 (±16.89) 61.8 (±16.79)

LPA 40.9 (±13.64) 38.6 (±13.25) 42.6 (±13.70)

MVPA 17.6 (±8.85) 18.8 (9.75)* 16.7 (8.03)

Mean percentage of time spent SED and in PA during the whole day % (±SD) All children(n = 359)

Boys (n = 153) Girls(n = 206)

SED 60.3 (±6.25) 59.9 (±6.33) 60.5 (±6.20)

LPA 29.2 (±4.62) 28.5 (±4.56)* 29.6 (±4.62)

MVPA 10.6 (±3.04) 11.5 (±3.01)* 9.9 (±2.87)

Mean contribution of SED and PA time during the after-school period to daily behaviour% (±SD)


Boys (n = 153) Girls(n = 206)

SED 20.8 (±4.67) 21.4 (±4.97)* 20.4 (±4.38)

LPA 25.0 (±6.08) 24.1 (±6.23)* 25.7 (±5.87)

MVPA 28.8 (±9.35) 27.6 (±9.52)* 29.8 (±9.14)

Mean contribution of after-school MVPA to achieving PA guidelines§ % (±SD) 29.3 (±14.75) 31.4 (±16.25)* 27.8 (±13.38)

Weekday wear time (mean mins/day) 705.6 (±76.7) 717.0 (±78.48)* 697.4(±74.45)

Sex differences

*p<0.05§physical activity guidelines: �60 minutes of MVPA per day.

doi:10.1371/journal.pone.0140132.t001



after-school period made a significantly larger contribution to boys’ daily SED than girls’(21.4% vs 20.4%, p<0.05). Conversely, the period made a significantly larger contribution togirls’ LPA and MVPA than boys’ (LPA: 24.1% vs 25.7%, p<0.05; MVPA: 27.6% vs 29.8%,p<0.05). After school, boys and girls performed 31% and 28% of the MVPA needed to reachthe guidelines of�60 minutes of MVPA per day.

Significantly more boys than girls achieved the physical activity guidelines (�60 minutes ofMVPA) on weekdays (69.5% vs 47.7% respectively, p<0.01); however, there were no differ-ences in the percentage of boys and girls who achieved the sedentary behaviour guidelines(�120 minutes screen-based sedentary behaviours) on weekdays (58.7% and 59% respectively).When comparing the percentage of children who achieved both the physical activity and sed-entary behaviour guidelines (i.e.�60 minutes of MVPA and�120 minutes screen-based sed-entary behaviours), more boys than girls achieved both guidelines on weekdays (42.7% vs27.3% respectively, p<0.05).

Data from the parent proxy-report of after-school and daily screen-based sedentary behav-iours is shown in Table 2. Boys and girls spent 94.8 (±59.01) and 97.2 (±61.67) minutes, respec-tively, during the entire day in screen-based sedentary behaviours. After-school boys and girlsperformed 113.4 (±89.90) and 109.3 (±80.32) minutes respectively of screen-based sedentarybehaviours. The after-school period contributed to 84% of children’s daily screen-based seden-tary behaviours and 80% of the maximum screen-based sedentary behaviours recommendedfor children (�120 minutes/day). There were no sex differences in daily or after-school screen-based sedentary behaviours.

Results of the logistic regression showed that the odds ratio of achieving the physical activityguidelines was 1.31 (95%CI: 1.18, 1.44, p<0.01). Therefore, for each 1% increase in percentageof the after-school period spent in MVPA, children have a 31% increased likelihood of achiev-ing the physical activity guidelines of�60 minutes of MVPA per day. Logistic regression alsoshowed the odds ratio of achieving the sedentary behaviour guidelines was 0.97 (95% CI: 0.96,0.97, p<0.01). For each 1% increase in screen-based sedentary behaviours during the after-school period, children were 3% less likely to achieve the sedentary behaviour guidelines of�120 minutes in screen-based sedentary behaviours per day.

DiscussionThis study highlights the importance of the after-school period for children’s physical activityand sedentary behaviours participation and achieving the associated guidelines. Results showeda 31% increase in likelihood of achieving the physical activity guidelines for every 1% increase

Table 2. Parental proxy-reported screen-based sedentary behaviours during the after-school period (meanminutes ±SD), and the contribution todaily screen-based sedentary behaviours (±SD) and achieving the sedentary behaviour (SB) guidelines (±SD).


Boys(n = 136)

Girls(n = 182)

After-school screen-based sedentary behaviours minutes (±SD) 96.16 (±60.45) 94.8 (±59.01) 97.19(±61.66)

Daily screen-based sedentary behaviours minutes (±SD) 111.0 (±84.32) 113.4(±89.80)

109.3(±80.32)

Contribution of after-school screen-based sedentary behaviours to daily screen-basedsedentary behaviours % (±SD)

83.6 (±22.92) 83.2 (±20.93) 83.9 (±24.35)

Contribution of after-school screen-based sedentary behaviours to achieving the sedentarybehaviours guidelines§ % (±SD)

80.1 (±50.38) 78.9 (±49.17) 80.9 (±51.34)

§sedentary behaviour guidelines: �120 minutes of screen-based sedentary behaviour per day

doi:10.1371/journal.pone.0140132.t002



in the after-school period spent in MVPA. If this finding was extrapolated for an average childin the current study, a 1% shift (for instance, from 14% to 15% of the after-school period inMVPA) would increase MVPA from 21 minutes to 22.5 minutes during an after-school periodof 150 minutes (e.g. 3.30-6pm). We also conducted the analysis with minutes of after-schoolMVPA as the predictor. Results were very similar and therefore are not presented. After-schoolscreen-based sedentary behaviours participation was associated with a reduced likelihood ofachieving the sedentary behaviours guidelines. For every additional 10 minutes of screen-basedsedentary behaviours, children are 30% less likely to meet the sedentary behaviours guidelinesfurther highlighting the need to reduce after-school screen-based sedentary behaviours.

Children perform the majority of their daily screen-based sedentary behaviours during theafter-school period and almost reach the maximum recommended amount of daily screen-based sedentary behaviours during this period alone. Previous research has investigated if chil-dren meet or exceed the sedentary behaviour guidelines on a daily basis [7,11]. However, thecurrent study produces additional data on when the screen-based sedentary behaviours areactually occurring, providing valuable information regarding the time of day that interventionsshould be implemented.

Although less than 15% of children’s time after school is spent in MVPA, this contributedalmost a third of children’s daily MVPA, highlighting the crucial role the after-school periodplays in the accumulation of children’s daily physical activity. Although girls spent a lower per-centage of the after-school period in MVPA, that percentage made a larger contribution togirls’ total daily physical activity (both LPA and MVPA) than boys’ after-school physical activ-ity. This suggests that the after-school period is a key time of the day to target these behavioursamong girls as they perform MVPA at lower levels than boys during other times of the day(e.g. recess and lunchtime [32]). In contrast, although the majority of children’s time was spentsedentary in the after-school period, the contribution of this period to daily sedentary levelswas the smallest across the activity intensities measured. Children must therefore also bespending large volumes of time sedentary during other periods of the day, such as school classtime [30]. However, there is a great opportunity to reduce sedentary behaviour by targeting theafter-school period.

Previous studies have shown boys participate in more physical activity [33,34] and specifi-cally more MVPA after school than girls [35]. This was also found in the current study as boysengaged in MVPA for a greater percentage of the day and the after-school period than theirfemale counterparts. The sex differences was also seen when examining the duration (minutes)of MVPA performed after school. However, girls performed more LPA after school than boys,which may be attributed to active transport or active free play after school. Investigation intothe actual behaviours that children perform after school may help us further understand thesedifferences and provide targets for interventions in the after-school period.

In comparison to children in other studies and countries, the current sample spent a smallerpercentage of the after-school period in SED, and a greater percentage of time in LPA andMVPA than Canadian 11 year olds [36]. Compared to a sample of children from Sydney (5–7years), the current sample spent less time sedentary (106 minutes), more time in LPA (90.6minutes) and more time in MVPA (14.5 minutes) after school [37]; however, the after-schoolperiod used among the Sydney sample was longer than the period examined in the currentstudy (3:30-7pm compared to end-of-school to 6pm). The current sample performed similarlevels of daily MVPA to 6–19 year old Canadian children (57 minutes/day) [38] but less thanNew Zealand 10–14 year old children (102 minutes/day) [39]. Further, a greater proportion ofthe current sample achieved the physical activity guidelines than 7–8 year olds from England(51%) [40], yet fewer achieved them than New Zealand 10–14 year olds [39]. In regards toachieving the sedentary behaviours guidelines, a smaller proportion of the current sample



achieved the guidelines than Canadian 5–11 year olds (69%) [41], but a greater proportionachieved them than 11–15 year old Scottish youth (76%) [42]. These variations may be due tosampling and age differences, and could also be due to sociocultural, policy and/or environ-mental differences between countries. However, purpose-designed representative samples thatuse a consistent methodology (e.g., the Health Behavior in School-Aged Children survey [43])are needed to better examine these differences in physical activity and sedentary behavioursestimates during the after-school period between studies (and countries).

This is the first study to determine how important the after-school period is for children’slikelihood of achieving the physical activity and sedentary behaviour guidelines. In particular,findings highlight the large impact that very small changes in after-school physical activity canhave on the probability of children meeting the physical activity guidelines (31% more likely tomeet the guidelines for every 1% increase in time spent in MVPA during the after-schoolperiod). It is therefore important to develop interventions that target increases in children’sphysical activity and reductions in sedentary behaviour and screen-based sedentary behavioursduring the after-school period. For example, active homework strategies [20] may target bothphysical activity and sedentary behaviour levels. Introducing after-school dance classes to Afri-can-American girls has also been shown to successfully increase physical activity levels andreduce TV/video viewing and video game use [44]; these strategies may be adapted to differenttarget populations. Further, time spent outdoors [45] is consistently shown to be associatedwith physical activity and the after-school period provides a feasible opportunity to promoteoutdoor play and subsequently physical activity.

Strengths and limitationsThe response rate was 37% and as such it is not known if these children were representative ofthe broader sample. As parents are not with their child during some parts of the day (e.g. schoolhours), they may not be able to recall their screen-based sedentary behaviours during this timewhich may impact their reporting of daily screen-based sedentary behaviours duration. Fur-ther, the objective measure of sedentary time may include time when children are standing andnot moving as it is not a direct measure of sitting. Also, the proxy-report measure did not askspecifically for the time engaged in specific sedentary behaviours while sitting. However, thecollection of objective measures of physical activity and overall SED and proxy-report screen-based sedentary behaviours duration during the after-school period (when parents are oftenwith their child) is a strength of this study as this provided the intensity and duration of after-school behaviours performed by young children. This information may be used to enhance theeffectiveness of interventions which target after-school physical activity and sedentary behav-iour. Future research should also examine other contextual factors that may be related to chil-dren’s after-school behaviours (e.g. who the child is with, where they are and SES) and collectdetailed information on the type of physical activity (e.g. basketball, running) and sedentarybehaviours (reading, sitting in a car) they are performing to further tailor after-schoolinterventions.

ConclusionAfter school, children perform 80% of the maximum daily recommendation for screen-basedsedentary behaviour but less than 30% of the daily MVPA recommended for health. After-school MVPA is positively associated with achieving the physical activity guidelines and after-school screen-based sedentary behaviours are negatively associated with achieving the seden-tary behaviour guidelines. However, more than half of the after-school period is spent inscreen-based sedentary behaviours and little time is spent in MVPA. Interventions should



target reductions in sedentary behaviour and increases in physical activity during the after-school period as the behaviours performed during this period make a large contribution todaily levels and to achieving the associated guidelines.

AcknowledgmentsThe authors would like to thank Jacqui Reid and the Transform-Us! project staff for their assis-tance with data collection; the Transform-Us! participants, and Eoin O’Connell for the excelmacros used to analyse the raw accelerometer data.

Author ContributionsConceived and designed the experiments: LA TH JV JS. Performed the experiments: LA. Ana-lyzed the data: LA. Contributed reagents/materials/analysis tools: LA TH JV JS. Wrote thepaper: LA TH JV JS.

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97

CHAPTER SIX

Paper Five: 5-Year Changes in Afterschool Physical

Activity and Sedentary Behavior

The cross-sectional examination of children’s after-school physical activity and

sedentary behaviour levels and the contribution this makes to daily levels detailed

in Chapter Five provides an overview of these behaviours. However, how these

behaviours change over time is not well known. The following paper provides a

longitudinal examination of children’s after-school physical activity and

sedentary behaviour and the contribution the behaviours accrued during this

period makes to children’s daily behaviours, describing how these change over

five-years. This paper is published in the American Journal of Preventive

Medicine (Impact factor: 4.527) as:

Arundell L, Ridgers ND, Veitch J, Salmon J, Hinkley T, Timperio A. 2013. 5-year

changes in afterschool physical activity and sedentary behavior. American

Journal of Preventive Medicine 44(6):605-11.

The Authorship Statement for this manuscript is contained in Appendix 6.1 and

the Copyright Permission is contained in Appendix 6.2

5-Year Changes in Afterschool Physical Activityand Sedentary Behavior

Lauren Arundell, BAppSc, Nicola D. Ridgers, PhD, Jenny Veitch, PhD, Jo Salmon, PhD,Trina Hinkley, PhD, Anna Timperio, PhD

Background: The afterschool period holds promise for the promotion of physical activity, yet littleis known about the importance of this period as children age.

Purpose: To examine changes in physical activity of children aged 5–6 years and 10–12 years andtheir sedentary time in the afterschool period over 3 and 5 years, and to determine the contributionof this period to daily physical activity and sedentary behavior over time.

Methods: Data from two longitudinal studies conducted in Melbourne, Australia, were used.Accelerometer data were provided for 2053 children at baseline (Children Living in ActiveNeighbourhoods Study [CLAN]: 2001; Health, Eating and Play Study [HEAPS]: 2002/2003); 756at 3-year follow-up (time point 2 [T2]); and 622 at 5-year follow-up (T3). Light (LPA), moderate(MPA) and vigorous (VPA) physical activity were determined using age-adjusted cut-points.Sedentary time was defined as r100 counts/minute. Multilevel analyses, conducted in April 2012,assessed change in physical activity and sedentary time and the contributions of the afterschoolperiod to overall levels.

Results: Afterschool MPA and VPA decreased among both cohorts, particularly in the youngercohort, who performed less than half of their baseline levels at T3 (MPA: T1¼24 minutes;T3¼11 minutes; VPA: T1¼12 minutes; T3¼4 minutes). LPA also declined in the older cohort.Afterschool sedentary time increased among the younger (T1¼42 minutes; T3¼64 minutes) and oldercohorts (T1¼57 minutes; T3¼84 minutes). The contribution of the afterschool period to overall MPAand VPA increased in the older cohort from 23% to 33% over 5 years. In the younger cohort, thecontribution of the afterschool period to daily MPA and VPA decreased by 3% over 5 years.

Conclusions: The importance of the afterschool period for children’s physical activity increaseswith age, particularly as children enter adolescence.(Am J Prev Med 2013;44(6):605–611) & 2013 American Journal of Preventive Medicine

Introduction

The health benefits of physical activity throughoutyouth are well established,1,2 and an emergingbody of evidence suggests that participation in

sedentary behaviors may have independent negativehealth impacts,3,4 although prospective evidence is notstrong.5 Levels of children’s physical activity and seden-tary behavior are, however, not optimal.6 Identifying themost promising time periods in which to change

children’s health behaviors will assist future interventiondevelopment.The afterschool period increasingly is recognized as an

important and feasible time period in which to promoteincreases in physical activity and reductions in sedentarytime among children.7–9 After school, children are notrestricted by school schedules and have the opportunity toengage in discretionary active and sedentary pastimes,10

particularly during daylight hours. Inconsistent defini-tions of the afterschool period (e.g., 4PM–6PM,11 3:30PM–8:30PM)12 make direct comparisons between studiesdifficult; however, it appears that children are engagingin between 11 minutes of accelerometer-defined moder-ate-to-vigorous physical activity7 and 77 minutes ofpedometer-defined physical activity13 after school. More-over, the afterschool period can contribute up to 46% ofchildren’s daily activity levels14 and 52% of their daily

From the Centre for Physical Activity and Nutrition Research (C-PAN),Deakin University, Melbourne, Australia

Address correspondence to: Nicola D. Ridgers, PhD, Centre for PhysicalActivity and Nutrition Research, Deakin University, 221 Burwood Hwy,Burwood, 3125, Australia. E-mail: [email protected].

0749-3797/$36.00http://dx.doi.org/10.1016/j.amepre.2013.01.029

& 2013 American Journal of Preventive Medicine � Published by Elsevier Inc. Am J Prev Med 2013;44(6):605–611 60598

steps.15 Boys consistently engage in more physical activityafter school than girls,11,15–17 and it appears that this timeperiod makes a larger contribution to daily physicalactivity levels among boys than among girls.14

The prevalence of afterschool sedentary behaviors andthe contribution this periodmakes to daily sedentary time isdifficult to ascertain as studies have used a range of methodsto assess behavior (e.g., TV log,14 self-report surveys ofscreen-based sedentary behaviors, and social sedentarybehaviors17). Previous studies12,18,19 have used objectivemeasures of afterschool physical activity and sedentarybehavior; however, none have used objective measures toexamine changes in the afterschool period over time.In the only longitudinal study to examine changes in

afterschool behavior over time, Wickel and colleagues20

found declines in total activity and increases in sedentarybehavior. However, their sample was followed over only a 2-year period (from ages 9–11 years) and used self-reportmeasures.Substantial changes may occur from early childhood to

late adolescence, particularly as children transition fromelementary to middle school. It is plausible that theimportance of the afterschool period to children’s andadolescents’ overall physical activity levels may change aschildren age. Identifying the contribution the afterschoolperiod makes to overall activity levels at various stages ofchildhood is essential for informing the development ofinterventions that target periods of the day when youngpeople are potentially most receptive to behavior changestrategies. The aim of this study was to investigatechanges in children’s afterschool physical activity andsedentary time over 3 and 5 years, and to determine thecontribution of this period to children’s overall physicalactivity and sedentary time as they age.

MethodsData from the Children Living in Active Neighbourhoods Study(CLAN)21 and the Health, Eating and Play Study (HEAPS)22 werepooled for the current analysis. In brief, CLAN aimed to examinethe influence of the family environment on elementary school–aged children’s physical activity and sedentary behavior overtime21; HEAPS examined family influences on children’s eatingbehaviors and physical activity over 5 years.22 Ethical approval forboth studies was granted by the Deakin University HumanResearch Ethics Committee, the Department of Education andTraining Victoria, and the Victorian Catholic Education Office.Parents provided informed written consent for their child’sparticipation at each time point and adolescents also providedinformed written consent subsequent to baseline.

Sample

Elementary schools in metropolitan Melbourne, Australia, with anenrollment 4200 students were selected randomly and invited toparticipate in CLAN and HEAPS. Forty-three schools (18 in low-,seven inmiddle-, and 18 in high-SES areas) participated. At baseline

(T1), all children in Grade Prep (younger cohort, aged 5–6 years)and Grades 5–6 (older cohort, aged 10–12 years) were invited toparticipate. Consent was provided from 2782 children (CLAN:n¼1220, 38% response rate; HEAPS: n¼1562, 42% response rate).At baseline, parents in CLAN (T1¼2001) and HEAPS (T1¼2002/3)were asked if they would be willing to be contacted about futureresearch. Those willing were invited to participate in two follow-upmeasures conducted at 3 and 5 years post-baseline (CLAN:T2¼2004, T3¼2006; HEAPS: T2¼2006, T3¼2008).

Measures

Demographic data. At each time point, parents reported theirmarital status; highest level of education and employment status,including those of their partner (if applicable); as well as theirchild’s gender and date of birth. Maternal education was used as aproxy of SES and was classified as low (some high schoolattendance or less); medium (high school or trade certificatecompletion); or high (tertiary education), consistent with previousresearch.23 Across both studies, data were provided by 2689parents at baseline, 822 parents at T2, and 695 parents at T3.

Physical activity and sedentary time. Physical activity andsedentary time were measured objectively using a uni-axial Acti-Graph 7164 accelerometer. Accelerometers have been validated forassessing children’s physical activity and sedentary time inlaboratory and field settings.24,25 The unit was worn on the righthip for up to 8 consecutive days and measured movement in1-minute epochs. Children were instructed to wear the monitorduring all waking hours, excluding water-based activities. For thecurrent study, the afterschool period was defined as the end of theschool day, as determined by the school bell times (usually 3:30PM),until 6PM on weekdays. This is consistent with a previouslongitudinal examination of children’s physical activity duringthe afterschool period.20

Accelerometry Data Management

Accelerometer data were downloaded and initially checked forcompliance using ActiLife software. Data were then analyzed usingspecifically developed Excel macros. Nonwear time was definedas Z20 consecutive minutes of zero counts, which commonly hasbeen used to define nonwear in children and adolescents.26

Children who provided valid afterschool and whole-day data onat least 3 weekdays were included in analyses. A valid weekday wasdefined as a day on which the monitor was worn for Z610 minutes(T1); Z647 minutes (T2); or Z635 minutes (T3). This representsnonmissing counts for at least 80% of a standard measurement day,which is defined as the length of time that at least 70% of the samplewore the monitor.27 In addition, children were required to haveworn the monitor for 50% of the afterschool period.28 At baseline,2053 children were included in the analyses. At T2 and T3, 756children (87.1% of sample monitored) and 622 children (87.7% ofsample monitored), respectively, met the inclusion criteria.

Data were analyzed using age-specific cut-points29 to determinetime spent in light physical activity (LPA: 1.5–3.99METs); moderatephysical activity (MPA: 4–5.99 METs); and vigorous physicalactivity (VPA: Z6 METs). A 4-MET threshold was used torepresent MPA as brisk walking, which is often used to identifyMPA in calibration studies and has been associated with this level ofenergy expenditure.30 Sedentary time (SED) was defined as r100

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counts per minute.31 The average time spent in SED, LPA, MPA,and VPA was computed for each valid day and each validafterschool period. The contribution of the afterschool period wascomputed as a percentage for each valid day (duration of eachactivity intensity in the afterschool period/total duration of theactivity intensity for that day � 100) and averaged across valid days.

Data Analysis

Data were analyzed in April 2012. Descriptive statistics werecalculated for all measured variables. Independent t tests revealedsignificant differences between boys and girls in physical activitylevels in the afterschool period and for the whole weekday. Allsubsequent statistical analyses were stratified by gender. Inaddition, at each time point, children who provided 5 days ofdata engaged in more SED and LPA and less MPA and VPAcompared to children with 3 or 4 days of data. Therefore, analyseswere adjusted for number of valid days.Multilevel analyses (using MLwiN 1.10) were used to examine

changes in children’s physical activity levels and sedentary timeduring the afterschool period. The contribution of the afterschoolperiod to daily physical activity and sedentary time also wasevaluated. As multilevel models are robust regarding missing datapoints and can estimate effects over time using incomplete datasets,32 all valid data points collected were used in the analyses.A three-level multilevel model was used. Level 1: measurement

time point (T1, T2, T3); Level 2: children; and Level 3: baselineschool. The percentage of time spent in SED, LPA, MPA, and VPAafter school, and the contribution of the afterschool period to dailySED, LPA, MPA, and VPA were the outcome variables. SES(maternal education); maternal employment; study (i.e., CLAN orHEAPS); number of valid days; season of measurement; and dailywear time were identified as potential confounding variables apriori and included in the final analyses. Analyses were alsostratified by age cohort.To examine changes in the outcome variables, two dummy

variables were generated. These were for physical activity levels atT2 (3-year change) and T3 (5-year change) compared to T1. Therandom structure considered random intercepts and randomslopes on T2 and T3. Separate analyses were conducted for theoutcome variables. The regression coefficients were assessed forsignificance using the Wald statistic,33 which was set at po0.05.

ResultsAt baseline, the level of maternal education was low for33% of participants, medium for 35%, and high for 32%.The percentage of the afterschool period and of the wholeday children spent in physical activity and sedentary time(by gender and cohort) at baseline is shown in Table 1.Among both the younger and older cohorts, boys engagedin significantly less LPA and significantly more MPA andVPA than girls during the afterschool period.Appendix A (available online at www.ajpmonline.org)

illustrates the 3- and 5-year changes in the younger andolder cohorts’ afterschool behaviors using raw scores.Afterschool SED time increased from 42 minutes at T1to 64 minutes at T3 for the younger cohort, and from57 minutes at T1 to 84 minutes at T3 for the older cohort.

Both cohorts decreased their MPA (younger cohort:T1¼24 minutes, T3¼11 minutes; older cohort: T1¼13minutes, T3¼9 minutes) and VPA (younger cohort:T1¼12 minutes, T3¼4 minutes; older cohort: T1¼6minutes, T3¼2 minutes), whereas declines wereobserved for LPA among the older cohort only (T1¼76minutes, T3¼65 minutes).Table 2 shows percentage changes in afterschool PA

and SED over 3 and 5 years according to gender, usingmultilevel analyses. Significant decreases were observedfor MPA and VPA for girls and boys in both cohorts;however, the magnitude of change was greater among theyounger cohort. Among the older cohort, there werelarge significant decreases in LPA over 3 and 5 years, withgreater declines observed among girls. In both cohorts,children’s afterschool sedentary time significantlyincreased over 3 and 5 years in both girls and boys.The change in the proportion of time that both cohortsengaged in physical activity after school using raw scoresis presented in Appendix A (available online at www.ajpmonline.org).Among both cohorts, the contribution of the

afterschool period to daily LPA and SED remainedrelatively stable at approximately 17% and 20%, respec-tively, for the younger cohort and 16% and 21%,respectively, for the older cohort. The greatest changeswere seen in the contribution to daily MPA and VPA,with the period making a greater contribution to dailylevels over time in the older cohort (23% at baseline and33% at T3 for both MPA and VPA). Changes in thecontribution of the afterschool period to daily physicalactivity and sedentary time over 3 and 5 years accordingto gender, using multilevel analyses, are shown inTable 3.Overall, there were few consistent changes in the

contribution the afterschool period made to the youngerboys’ and girls’ daily PA or SED. In the older cohort, thecontribution of the afterschool period to each intensity ofphysical activity and sedentary time increased over 3 and5 years, with the exception of boys’ sedentary time (signi-ficant at 3 years only) and LPA (significant at 5 years only).The relative contribution of the afterschool period to dailyphysical activity using raw scores is presented in AppendixB (available online at www.ajpmonline.org).

DiscussionConsistent with previous research, both MPA and VPAdeclined during the afterschool period in bothcohorts.20,34 However, larger decreases were observed inLPA in the older cohort compared to MPA and VPA.These data indicate that all physical activity intensitiesdecreased over time. Further research is needed to identifywhat behaviors youth engage in that correspond to these

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intensities to inform future intervention efforts.35 Inter-estingly, the contribution of the afterschool period to dailyMPA and VPA was greater for the older cohort over time(from less than one quarter of the daily physical activitylevels to more than one third) compared to the youngercohort (stable at �25%), highlighting the increasingimportance of this time period to young people’s overalldaily physical activity levels.The relative decline in MPA and VPA was greater

among younger children compared to the older children.Although age-related physical activity declines areobserved consistently when examining daily behavior,36

the findings regarding the afterschool period are mixed.Declines in physical activity have been found in Euro-pean samples,34 whereas among British youth (n¼1307,aged 10–12 years)37 afterschool physical activity increa-sed with age. Few studies have examined the afterschoolbehaviors of children during the early elementary schoolyears, as the main focus has been on the behaviors ofolder children and adolescents.38–40

The current study suggests that children’s afterschoolbehaviors undergo major changes between the ages of 5/6and 10/11 years, which may be explained in part byincreases in screen-time usage such as TV viewing andelectronic media use.41 Further, the results highlight theneed for interventions to target children’s afterschoolMPA and VPA from early elementary school, because,although declines in afterschool activity levels are seen, it

is a period where children may be able to participate ingreater amounts of discretionary physical activity com-pared to other periods throughout the day.At baseline, the older cohort in this Australian sample

spent a similar proportion of the afterschool periodengaged in MPA and VPA compared with theaccelerometer-measured MVPA levels of children aged 9years in the European Youth Heart Study.34 Notably, therewere large declines seen in afterschool LPA among theolder cohort, particularly for girls. Interestingly, the greatestincrease in the contribution the afterschool period makesto daily activity levels was observed in the first 3 yearsamong boys (i.e., during their transition from elementaryschool to secondary school); among girls, there wereconsistent increases in the contribution over 3 and 5 years.Previous research has found that as youth progress

through secondary school, they perform less physicalactivity throughout other periods of the day (e.g., recessand lunchtime),28 possibly suggesting that the in-schooltime contribution to physical activity levels decreasesover time. This highlights the importance of theafterschool period for youth to engage in physical activityand to promote activity levels through interventionsduring this time. Afterschool programs hold promise asone setting for increasing physical activity levels inyouth,41–43 although further research is needed to iden-tify which specific strategies are most effective in thesesettings over time.44

Table 1. Children’s physical activity and sedentary time at baseline (T1), M (SD)

Younger cohorta Older cohortb

Girls (n¼295) Boys (n¼313) Girls (n¼789) Boys (n¼656)

Afterschool activity (150-minute period), %

SED 27.87 (9.26) 27.80 (9.67) 37.93 (10.67) 37.60 (11.73)

LPA 49.40 (7.86)* 47.20 (8.40)* 52.07 (9.13)* 48.67 (9.47)*

MPA 15.73 (5.20)* 16.73 (5.53)* 7.60 (3.93)* 9.67 (5.13)*

VPA 6.80 (4.53)* 8.80 (5.60)* 3.06 (3.26)* 4.53 (4.40)*

Daily activity, %

SED 33.63 (9.3) 31.96 (9.04) 44.91 (10.57)* 42.70 (10.49)*

LPA 48.15 (6.05) 46.90 (5.94) 46.74 (7.06) 46.19 (6.99)

MPA 13.04 (2.97) 14.12 (2.93) 6.03 (2.04) 7.60 (2.17)

VPA 5.18 (2.17)* 7.00 (2.96)* 2.33 (1.58)* 3.51 (2.14)*

Daily wear time (minutes) 750.6 (70.5)* 755.6 (66.7)* 807.8 (80.6)* 814.0 (81.6)*

Note: Boldface indicates significance.aAged 5–6 years at baselinebAged 10–12 years at baselinenpo0.05LPA, light-intensity physical activity; MPA, moderate-intensity physical activity; SED, sedentary time (o100 counts per minute)28; VPA, vigorous-intensity physical activity using age-adjusted thresholds30



Boys and girls in both cohorts showed increases inafterschool sedentary time of a similar magnitude(approximately 25 minutes) over 3 and 5 years. Increasesin the contribution to daily sedentary levels wereminimal, suggesting that this increase is consistent acrossthe entire day. The observed increase may in part be dueto school schedules and homework expectations, as 54%of children (aged 5–12 years) previously have reportedhomework to be a barrier to participation in physicalactivity after school.45

However, Atkin and colleagues found that amongstudents aged 15 years in the Project STIL (SedentaryTeenagers and Inactive Lifestyles), physical activity did notdisplace time spent doing homework between 3:30PM and6:30PM, suggesting that other factors (e.g., TV viewing) maycontribute to these changes.38 The afterschool period maybe a key time to target reductions in children’s andadolescents’ sedentary time as it may be more challengingto change children’s sedentary time during structuredschool time, particularly as children progress throughsecondary school, or later in the evenings (after 6PM). Onepromising approach may be the modification of homeworktasks that target both physical activity engagement andsedentary time during this time,46,47 although furtherresearch is needed to identify the effectiveness of suchstrategies in children and adolescents.

Strengths and LimitationsStrengths of this study include the large sample size, theuse of objective measures of sedentary time and physicalactivity, and the 5-year follow-up period. Limitationsinclude the use of a 60-second epoch for the acceler-ometry, as this may not be sensitive enough to capturesporadic VPA among children.48 However, this epochlength was unavoidable when using the 7164 accelerom-eter model over extended periods of time. Second,defining nonwear as 20 minutes of consecutive zerosmay be considered to be a limitation, as this may haveresulted in an underestimation of sedentary time.26

Third, as accelerometers do not capture behavioralinformation, it is not known what types of behaviorschanged during the afterschool period as children aged.

ConclusionThis study suggests that the afterschool period may be animportant time period for interventions targeting physicalactivity and sedentary time throughout childhood andadolescence. Children’s and adolescents’ afterschoolphysical activity declines over time, with changes in bothMPA and VPA occurring during elementary school yearsand changes in LPA occurring during secondary school.Large increases in sedentary time also were observed,particularly over the 5-year period. The increasing

Table 2. Mean changes in percentage of time spent in physical activity and sedentary time after school over 3 and 5 years,b (95% CI)


T1 to T2 T1 to T3 T1 to T2 T1 to T3

Boys, %

SED 8.37 (6.32, 10.41)*** 13.37 (11.30, 15.44)*** 9.34 (6.57, 12.12)*** 15.40 (12.88, 17.92)***

LPA �0.31 (�2.02, 1.40) 0.09 (�1.65, 1.83) �6.35 (�7.92, �4.78)*** �9.18 (�10.97, �7.39)***

MPA �5.14 (�6.22, �4.06)*** �7.99 (�9.09, �6.89)*** �1.98 (�2.83, �1.14)*** �3.62 (�4.53, �2.71)***

VPA �2.85 (�3.98, �1.69)*** �5.41 (�6.55, �4.27)*** �0.90 (�1.58, �0.22)** �2.47 (�3.21, �1.74)***

Girls, %

SED 5.36 (3.37, 7.34)*** 14.54 (12.18, 16.90)*** 10.73 (9.04, 12.42)*** 15.61 (13.98, 17.24)***

LPA 1.09 (�0.77, 2.95) �2.01 (�4.03, 0.02) �8.44 (�9.98, �6.91)*** �11.55 (�13.12, �9.99)***

MPA �5.16 (�6.15, �4.17)*** �8.30 (�9.29, �7.30)*** �1.06 (�1.82, �0.30)** �2.03 (2.93, �1.13)***

VPA �1.96 (�2.74, �1.17)*** �4.37 (�5.24, �3.50)*** �1.16 (�1.58, �0.73)*** �1.99 (�2.47, �1.52)***

Note: Boldface indicates significance. The b value reflects the percentage change in children’s afterschool activity levels between Year 1 (T1) and Year3 (T2), and between Year 1 (T1) and Year 5 (T3). A positive b value reflects an increase in children’s sedentary time and physical activity after school ateither T2 or T3 compared to T1; a negative b value reflects a decrease in sedentary time and physical activity. All models are adjusted for study, seasonof measurement, maternal education, maternal employment, number of valid days, and daily wear time.aAged 5–6 years at T1; aged 8–9 years at T2; aged 10–11 years at T3bAged 10–12 years at T1; aged 13–15 years at T2; aged 15–17 years at T3npo0.05, nnpo0.01, nnnpo0.001LPA, light-intensity physical activity; MPA, moderate-intensity physical activity; SED, sedentary time (o100 counts per minute)28; VPA, vigorous-intensity physical activity using age-adjusted thresholds30


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contribution that the afterschool period makes to overallphysical activity, particularly during adolescence, suggeststhat afterschool initiatives may be particularly importantin this age group. However, interventions targeting bothphysical activity and sedentary behavior should beginduring the early elementary school years to minimize thechanges observed in the younger years.

The authors gratefully acknowledge the contribution of allproject staff, especially Dr. Michelle Jackson, Dr. AmandaTelford, Sophie Thal-Janssen, and Anna Stzendur for thecollection of data in both studies, and Eoin O’Connell for theanalysis of the raw data. Data collection for HEAPS was fundedby the Victorian Health Promotion Foundation (baseline) andAustralian Research Council (follow-ups; ID DP 0664206) andfor CLAN by the Financial Markets Foundation for Children(baseline) and the National Health and Medical ResearchCouncil (follow-ups; ID 274309). Nicola Ridgers is supportedby an Australian Research Council Discovery Early CareerResearcher Award (DE120101173). Jenny Veitch is supportedby a National Heart Foundation of Australia PostdoctoralFellowship Award. Jo Salmon is supported National Health &Medical Research Council Principal Research Fellowship(APP1026216). Anna Timperio is supported by a VictorianHealth Promotion Foundation Public Health Fellowship.

No financial disclosures were reported by the authors ofthis paper.

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Table 3. Mean change in the contribution of the afterschool period to daily physical activity and sedentary time, b (95% CI)


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Note: Boldface indicates significance. Models adjusted for study, season of measurement, maternal education, maternal employment, number of validdays, and daily wear time. The b value reflects the percentage change in the contribution of the afterschool period to children’s daily sedentary timeand physical activity levels between Year 1 (T1) and Year 3 (T2), and between Year 1 (T1) and Year 5 (T3).aAged 5–6 years at T1; aged 8–9 years at T2; aged 10–11 years at T3bAged 10–12 years at T1; aged 13–15 years at T2; aged 15–17 years at T3npo0.05, nnpo0.01, nnnpo0.001LPA, light-intensity physical activity; MPA, moderate-intensity physical activity; SED, sedentary time (o100 counts per minute)28; VPA, vigorous-intensity physical activity using age-adjusted thresholds30



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Appendix

Supplementary data

Supplementary data associated with this article can be found in theonline version at http://dx.doi.org/10.1016/j.amepre.2013.01.029.


June 2013 104

FFive-Year Changes in After-School Physical Activity and Sedentary Behavior

Lauren Arundell BAppSc, Nicola D. Ridgers, PhD, Jenny Veitch, PhD, Jo Salmon, PhD, Trina Hinkley, PhD, Anna Timperio, PhD

Appendix A

Children’s physical activity and sedentary time during the after-school period

Key: T1 = Baseline; T2 = 3-year follow-up; T3 = 5-year follow-up

Note: Data are shown according to cohort and are unadjusted Ms. ¥ Aged 5–6 years at T1; aged 8–9 years at T2; aged 10–11 years at T3 ‡ Aged10–12 years at T1; aged 13–15 years at T2; aged 15–17 years at T3

LPA, light physical activity; MPA, moderate physical activity; SED, sedentary time; T, time point; VPA, vigorous physical activity

Am J Prev Med 2013; 44(6) A-1 105

AAppendix B

Contribution of the after-school period to children’s daily physical activity and sedentary time

Note: Data are shown according to cohort and are unadjusted Ms.

Key: T1 = Baseline; T2 = 3-year follow-up; T3 = 5-year follow-up ¥ Aged 5–6 years at T1; aged 8–9 years at T2; aged 10–11 years at T3‡ Aged10–12 years at T1; aged 13–15 years at T2; aged 15–17 years at T3

LPA, light physical activity; MPA, moderate physical activity; SED, sedentary time; T, time point; VPA, vigorous physical activity

Am J Prev Med 2013; 44(6) A-2 106

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CHAPTER SEVEN

Paper Six: The correlates of children’s after-school

physical activity and sedentary behaviour

Chapters Five (Paper Four) and Six (Paper Five) highlight children’s low levels of

after-school physical activity and how these decline over time. Further, these

chapters show the suboptimal levels of sedentary behaviours children perform

after school. To develop interventions targeting increases in after-school physical

activity and reductions in sedentary behaviours, an investigation of the correlates

associated with these behaviours is required. Section 2.12 and Section 2.13 (Paper

Two) show that the literature examining the correlates of after-school physical

activity and sedentary behaviour is still in its infancy. Therefore, the following

paper aimed to add to this literature by examining the correlates of after-school

physical activity and sedentary behaviour using an ecological framework. This

paper is under review in BMC Public Health (Impact factor: 2.264).

Arundel, L, Salmon J, Hinkley T, Veitch J. The correlates of children’s after-



Chapter Seven, Paper Six: The correlates of children’s after-school physical activity and sedentary behavior

108

Abstract

Introduction: Understanding correlates of children’s after-school moderate- to

vigorous-intensity physical activity (MVPA) and sedentary behaviour (SB) is

important for informing intervention development. This study used an ecological

framework to examine the intrapersonal, social and physical environmental

correlates of children’s after-school MVPA and SB.

Methods: Child and proxy-report survey data from the Transform-Us!

intervention at baseline were used. Children (n=354, age 8.2 years, 43% boys)

also wore an ActiGraph GT3X accelerometer from which the percentage of the

after-school period (end of school-6pm) spent in MVPA (%MVPA) and SB

(%SB) were calculated. Generalised linear models assessed the association

between 26 intrapersonal, 22 social, and 11 physical environment variables and

%MVPA and %SB. Initial analyses (model 1) determined the association with

%MVPA and %SB for each variable separately with adjustment for age, sex and

clustering by school. All variables showing significant associations were entered

into model 2 for which also adjusted for age, sex and clustering by school.

Results: Children spent 14.2% and 53.3% of the after-school period engaged in

MVPA and SB respectively. Variables positively associated with %MVPA

included: sibling PA co-participation (Odds Ratio [OR] 1.04, 95% CI 1.02, 1.06),

non-organised PA frequency (OR 1.01, 95% CI 1.00, 1.02), and days at a sporting

club after school (OR 1.07, 95% CI 1.01, 1.14). Parents being concerned about

their child’s health behaviours was negatively associated with %MVPA (OR 0.97,

95% CI 0.96, 0.99). Non-organised PA frequency (OR 0.99, 95% CI 0.98, 0.99)


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and the facilities to be active not available (OR 1.18, 95% CI 1.06, 1.33) were

significantly associated with %SB:

Conclusion: Only four of the 59 variables examined were significantly related to

MVPA and only two variables were associated with SB in the fully adjusted

models. Associations were predominantly with context specific variables

suggesting the child’s location and who they are with may be important

influences on after-school behaviour. Specifically, encouraging participation in

sports clubs, having someone to be active with, and ensuring availability of

physical activity facilities for children are potential targets to consider in the

development of future interventions to promote after school MVPA and minimise

SB.


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Introduction

Evidence highlighting the health benefits of childhood physical activity (PA) is

well established [1, 2]. More recently, research has shown the negative physical,

mental and social health impact of spending extended time in sedentary

behaviours (SB) [3, 4]. Accordingly, many developed countries recommend

children perform at least 60 minutes of moderate- to vigorous-intensity physical

activity (MVPA) every day, limit their recreational screen time, a key sedentary

behaviour, to less than two hours per day and break up long periods of sitting as

often as possible [5, 6]. Achievement of these recommendations is poor among

children in many countries [7-9]. For example, only 8% of Australian children

aged 5-17 years achieve the PA guidelines and 29% achieve the SB guidelines

[7]. Further, as PA and SB habits begin in youth and tracks into young adulthood

[10, 11], it is imperative to develop interventions to target behaviour change at a

young age when these behaviours are being established.

The after-school period, defined as from the end-of-school until 6pm [12], is a

period where children have more discretion over their behaviours and the

opportunity to be active and sedentary. However, after school, children often

spend as little as 8-9 minutes per hour being active [13] and spend large amounts

of time sedentary [14-18]. Children can spend up to 74% of the period sedentary

[18] and perform 80% of their daily screen-based sedentary behaviours during

this time [15]. Interventions targeting increases in physical activity and reductions

in sedentary behaviour are therefore required. However, identification of the

factors that promote physical activity and limit sedentary behaviours after school

is needed for effective intervention development.


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Stanley and colleagues [19] conducted a review of the correlates of children’s

after-school physical activity. Only ten studies had been conducted between 1990

and January 2011 and only ten of the 36 potential correlates identified were

reported by three or more of these studies, thereby making it difficult to draw

overall conclusions of associations [20]. The main focus of the research to date

has been on the demographic correlates of after-school physical activity (e.g. sex,

age and ethnicity) and on the physical environment (i.e. access to facilities and

number of facilities), with less consideration of the social environment or

correlates across the intrapersonal, social and physical environments

simultaneously.

More recently, a systematic review conducted in 2015 identified the correlates of

children’s after-school sedentary behaviours [21]. Only two non-modifiable

correlates (age and sex) were identified and the association varied depending on

the behaviour of interest. For example, age was positively associated with overall

after-school sedentary behaviour but there was an inconsistent association

between age and after-school TV viewing. These reviews highlight that this

literature is still in its infancy and there is a need for further research examining

the correlates of children’s after-school physical activity and sedentary behaviour.

As the correlates of children’s after-school physical activity and sedentary

behaviour may be within the intrapersonal, social or physical environments,

potential correlates should be assessed across multiple levels of the ecological

model simultaneously. This would enable the relative associations of correlates of

physical activity or sedentary behaviour within each domain to be examined [22].

Therefore, this study aimed to use an ecological framework to examine the


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intrapersonal, social and physical environmental correlates of children’s after-


Methods

Sample

Baseline data from the Transform-Us! intervention collected between February

and June 2010 were used (ACTRN 12609000715279; ISRCTN 83725066). The

methods for Tranform-Us! have been described in detail elsewhere [23]. In brief,

Transform-Us! was a four arm randomised controlled trial that targeted reductions

in sedentary behaviour and increases in physical activity in the home and school

settings. Participants were grade 3 students recruited from 20 randomly selected

primary (elementary) schools within 50km (31 miles) of the city of Melbourne

and with an enrolment of 300 or more students. Schools were stratified by

socioeconomic status (SES; 8 schools in low-SES areas and 12 schools in mid- to

high-SES areas). The current study utilised children’s baseline accelerometer

data, children’s self-report survey data and parent proxy-report survey data.

Ethics statement

Transform-Us! received ethics approval from the Deakin University Human

Research Ethics Committee (141-2009), and approval from the Victorian

Department of Education and Training (2009_000344) and the Catholic

Education Office (Project Number 1545). Prior to participation, written parental

consent and child verbal assent to complete the assessments were obtained.

Data management and analysis


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Outcome variables

Trained researchers fitted the children with a GT3X Actigraph accelerometer

(Pensacola, FL) on an elastic waist belt during class time. Accelerometers have

acceptable validity among children [24]. Children were asked to wear the

accelerometer during waking hours (except for water-based activities) for eight

consecutive days. Data were collected in 15-second epochs to best capture

children’s intermittent behaviours [25]. Accelerometer data were downloaded

using Actilife Lifestyle Monitoring System, Version 5.1. Specifically developed

excel macros were used to analyse the raw data and extract data from the end-of-

school (time data collected from schools, mode = 15:30) to 6pm.

Non-wear time was considered ≥20 consecutive minutes of zero counts as its use

provides the most accurate estimate of children’s sitting time compared to ≥10 or

≥60 consecutive minutes of zero counts [26]. Children were required to have data

recorded for at least 50% of the after-school period on at least three weekdays

[14] to be included in the analysis. Using previously established age-specific cut-

points [27], children’s MVPA during the after-school period was calculated.

MVPA was defined as ≥4 METs as this is the energy expenditure of brisk

walking among children and adolescents [28]. Sedentary time (SED) was defined

as <100 counts.min-1 which is the cut point that most closely represents sitting

time among children [29]. This also corresponds with the Sedentary Behaviour

Research Network’s definition of sedentary behaviours being those behaviours

performed in a sitting or reclining posture [30] with a MET value of up to 1.5

among children. To account for differences in wear time, the proportion of the

after-school period in which children participated in MVPA and SED on an


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average weekday was calculated (possible range 0-1). For ease of understanding,

this is reported as a percentage and therefore the outcome variables were

percentage of the after-school period spent in MVPA (%MVPA) and sedentary

behaviour (%SB) [31].

Explanatory variables

Height was measured by trained researcher to the nearest 0.1cm twice using

SECA portable stadiometers (SECA 220, Los Angeles, California, USA). The

average of the two measurements was taken. Weight was also measured by

trained researchers to the nearest 0.1kg using portable electronic Wedderburn

Tanita scales (Melbourne, Victoria, Australia). The average of the two

measurements was taken. Where a discrepancy of over 1cm or 1kg was noted, a

third measurement was taken, and the mean of the closest two measures was used.

Body Mass Index (BMI) was calculated and used to categorise participants via

age- and sex specific International Obesity Task Force classification [23] as

healthy weight, overweight or obese.

Survey data

Children were asked multiple questions from the intrapersonal, social and

physical environment levels of the social ecological model [22]. Full details of the

variables included, data management and reliability is included in Additional

Table 1, and therefore a summary is provided below.

Intrapersonal variables

Children self-reported their age, sex and enjoyment of 14 physical activity options

and nine sedentary behaviour options. Factor analysis (with varimax rotation)


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identified two distinct enjoyment factors: Factor 1: enjoyment of “boy PAs” and

Factor 2: enjoyment of “girl PAs”, as they included physical activities that were

more commonly performed by boys or girls respectively within the Australian

population [32]. Three factors were identified via factor analysis (with varimax

rotation) regarding sedentary behaviour enjoyment: enjoyment of academic

sedentary behaviours, enjoyment of screen-based sedentary behaviours, and

enjoyment of social sedentary behaviours. Children also reported their physical

activity competence, healthy TV viewing behaviours and unhealthy TV viewing

behaviours.

Parents were asked to report demographics including age, sex, highest level of

education, employment status, family living situation, height, weight and country

of birth. Parents also reported their child’s nature (active or not) and the existence

of barriers intrinsic to their child (e.g. my child doesn’t enjoy being active).

Parents reported the weekly (Monday-Friday) frequency that their child

participated in non-organised physical activity (e.g. ride a bike for fun), organised

sports or activities, active transport and sedentary transport. Parents also reported

the weekly (Monday-Friday) duration of time that their child spent in after school

in outdoor play during summer and winter

Social environment

Children were asked about their physical activity and sedentary behaviour after-

school social norms, the presence of rules that promoted/restricted physical

activity and sedentary behaviour within their house and about neighbourhood

connectedness.


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Parents were asked to report the time they spent in MVPA, sitting, watching TV

and using the computer. When data were collected for week and weekend days

separately, only the weekday data were used as the after-school period only

occurs on weekdays (for example, parents reported their duration sitting and

watching TV and computer on weekdays and weekend days, therefore only the

weekday data were used). Parents reported the frequency that their child

performed physical activity and watched TV with siblings, parents/guardians and

peers, the frequency that they provided emotional (e.g. praise) support for their

child to be active or sedentary and the frequency that they provided

practical/financial support for their child to be active.

Parents reported how many hours per day they spent in paid employment and who

their child was with during the after-school period on each day of the week.

Parents responded to items regarding how restrictive of sedentary behaviour they

are, if they thought their child doesn’t have anyone to be active with, if they use

sedentary behaviour as a ‘babysitter’, and if they had concerns about their child’s

health behaviours

Physical environment

Children were asked if they had access to physical activity equipment at home, if

they had sedentary behaviour items in their bedroom, a dog at home and a yard to

play in.

Parents reported characteristics of their home environment (e.g. live in a cul-de-

sac) and availability of electronic media in the home. Parents also reported their


117

child’s location on each day of the week and if the right facilities available for

their child to be active.

Survey reliability

The reliability of the modified survey items was assessed through a 7-day test re-

test reliability study in 2009. Participants were recruited from a convenience-

sampled Melbourne primary school (n=30 children mean age 11 years; 62%

female) and n=49 parents, mean age 41.9 ±4.8 years; 75% female). The reliability

of continuous items was determined using intraclass correlation coefficients (ICC)

which were considered fair (<0.5), moderate (0.5-0.74) or high (≥0.75) [33]. The

reliability of categorical items was determined using Kappa and percent

agreement. The kappa value was considered poor to fair (0.00-0.40), moderate

(0.41-0.60), substantial (0.61-0.80) or almost perfect (0.81-1.00) [33]. Percent

agreement values were considered fair when greater than 66% [34]. See

Additional Table 1 for reliability data.

Data analysis

All analyses were performed in STATA 12. Descriptive statistics were used to

report sample characteristics. Generalised linear models (GLM; with binomial

family and logit transformation) were used to examine the association between

the outcome variables and explanatory variables as the outcome variables were

proportion data (but reported as a percentage for ease of understanding). All

models were adjusted for age, sex and clustering by school. Each explanatory

variable was entered individually into a GLM model (model 1) with each of the

outcome variables separately (%MVPA or %SB). All explanatory variables


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associated at p<0.05 were then entered into multivariable models (model 2). The

GLM models used produce an odds ratio which is interpreted as a percentage

increase or decrease in the outcome variable associated with a one point increase

in the explanatory variable or compared to the referent group [35]. Collinearity of

explanatory variables was assessed. When the variance inflation factor (VIF) of

an explanatory variable was >10 and tolerance was <0.01 [35], the variable was

removed. For the MVPA multivariable model, only one variable (number of

locations visited per week after school) was removed; no variables were removed

from the SB model.

Results

The final sample consisted of 354 children who had complete child survey, parent

survey and valid accelerometer data (age 8.2 ± 0.45 years; 42.9% boys). Children

spent on average 14.2% (±6.07) or 18.7 minutes (±8.5) and 53.3% (±9.75) or 65.3

minutes (±14.36) of the after-school period engaged in MVPA and sedentary

behaviour, respectively.

The explanatory variables associated with MVPA in model 1 and model 2 are

shown in Table 1. Sixteen variables were associated in the model 1 analysis: four

were negatively associated with MVPA and 12 were positively associated with

MVPA. However, only four explanatory variables (all proxy-reported) remained

significantly associated with after-school MVPA in model 2; one from the

intrapersonal domain, two from the social and one from the physical environment.

The frequency that the child performed non-organised physical activity after-

school (OR 1.01, 95% CI 1.00, 1.02), the frequency that a sibling was active with

the child (OR 1.04, 95% CI 1.02, 1.06), and the frequency that they attended a


119

sporting club after-school (OR 1.07, 95% CI 1.01, 1.14) were positively

associated with after-school MVPA. Having parents who were concerned about

health behaviours (PA and SB) was negatively associated with after-school

physical activity (OR 0.97, 95% CI 0.96, 0.99).


school moderate- to vigorous-intensity physical activity.

MVPA % Model 1 OR (95% CI)

Model 2 OR (95% CI)

Intrapersonal-individual Parental country of birthad

Australia (ref) Other

1.00 0.84 (0.75, 0.95)§

1.00 0.94 (0.83, 1.07)

Child’s nature (active)bd 1.03 (1.01, 1.05)§ 0.99 (0.97, 1.01) PA competencebd 1.05 (1.01, 1.09)* 1.04 (1.00, 1.08)

Intrapersonal – behavioural

Frequency of non-organised physical activitybd 1.01 (1.00, 1.02)§ 1.01 (1.00, 1.02)* Frequency of organised sport or activitiesbd 1.06 (1.01, 1.12)* 1.02 (0.96, 1.08) Frequency of active travelbd 1.03 (1.01, 1.05)§ 1.02 (1.00, 1.03 Minutes of outdoor play per day (summer) bd 1.00 (1.00, 1.00)§ 1.00 (1.00, 1.00) Minutes of outdoor play per day (winter) bd 1.00 (1.00, 1.00)§ 1.00 (1.00, 1.00)

Social environment

Frequency of PA co-participation with siblingbd 1.02 (1.02, 1.06)§ 1.04 (1.02, 1.06)§ Frequency of SB co-participation with peersbd 1.06 (1.01, 1.11)* 1.02 (0.97, 1.08) No. days with other child (friend) bd 1.09 (1.03, 1.15)§ 1.00 (0.93, 1.07) Parental concern about health behaviours (PA and SB) bd 0.97 (0.96, 0.99)§

0.97 (0.96, 0.99)§

Rules restricting sedentary behaviourbc 0.95 (0.91, 0.99)* 0.99 (0.94, 1.04)


Own a dogac No (ref) Yes

1.00 1.14 (1.04, 1.25)§

1.00 0.99 (0.87, 1.13)

TV in bedroomac No (ref) Yes

1.00 0.91 (0.83, 0.99)*

1.00 1.00 (0.87, 1.15)

Number of days at a sporting clubbd 1.06 (1.01, 1.12)* 1.07 (1.01, 1.14)*


120

Model 1: Examined association of each explanatory variable separately, adjusting for sex, age and clustering by school, with the outcome variable Model 2: Examined association of all explanatory variables simultaneously, adjusting for age, sex and clustering by school *p<0.05, §p<0.01, Notes: aOdds ratio relates to an X% increase or decrease of the after-school period spent in MVPA for the comparison group/s compared with the referent group, bOdds ratio relates to an X% increase or decrease of the after-school period spent in MVPA for every one unit increase in the correlate; c=child self-report, d=proxy-report Abbreviations: MVPA = moderate- to vigorous-intensity physical activity, PA = physical activity, SB = sedentary behaviour As shown in Table 2, 17 explanatory variables were significantly associated with

after-school sedentary behaviour in the model 1 analysis: eight intrapersonal

variables, four social environment variables and five physical environment

variables. Six variables were positively associated with sedentary behaviour and

11 variables were negatively associated with sedentary behaviour. In model 2

only two variables remained significant, one intrapersonal and one social

environment variable. Each additional occurrence of proxy-report non-organised

physical activity was associated with a 1% decrease in after-school sedentary

behaviour per day. Each one unit increase in parent’s belief that the right facilities

for their child to be active were not available was associated with an 18% increase

in after-school sedentary behaviour.


school sedentary behaviour, according to the domains of the ecological model

SB% Model 1 OR (95% CI)

Model 2 OR (95% CI)

Intrapersonal Parental country of birthad

Australia (ref) Other

1.00 1.13 (1.04, 1.23)§

1.00 1.05 (0.97, 1.14)

Child’s nature (active) bd 0.98 (0.97, 1.00)* 1.00 (0.98, 1.01) Enjoyment of “girls PA’s”bc 1.01 (1.00, 1.02)§ 1.00 (0.99, 1.01) Healthy TV viewing behavioursbc 1.04 (1.01, 1.07)§ 1.03 (0.99, 1.07) No-one to be active with childbd 1.13 (1.01, 1.26)* 0.96 (0.84, 1.11)


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Intrapersonal – behavioural

Frequency of non-organised physical activitybd 0.98 (0.97, 0.99)§ 0.99 (0.98, 0.99)§ Frequency of active travelbd 0.98 (0.96, 0.99)§ 0.99 (0.97, 1.00) Minutes of outdoor play per day (summer) bd 0.99 (0.99, 0.99)§ 1.00 (1.00, 1.00)

Social environment

Frequency of PA co-participation with siblingbd 0.97 (0.96, 0.99)§ 0.99 (0.97, 1.01) Frequency of SB co-participation with peersbd 0.94 (0.90, 0.98)§ 0.97 (0.93, 1.01 Number of days with other child (friend) bd 0.91 (0.88, 0.95)§ 0.98 (0.93, 1.03) Parental concern about health behaviours (PA and SB) bd 1.01 (1.00, 1.02)§

1.00 (0.99, 1.02)


Own a dogac No (ref) Yes

1.00 0.90 (0.84, 0.96)§

1.00 0.96 (0.88, 1.05)

Facilities to be active not availablebd 1.15 (1.02, 1.30)* 1.18 (1.06, 1.33)* Number of days at friend's placebd 0.91 (0.84, 0.98)* 0.99 (0.92 1.08) Number of days at after-school carebd 0.97 (0.94, 1.00)* 0.97 (0.90, 1.03) Number of different locations per daybd 0.89 (0.76, 1.00)* 0.90 (0.80, 1.03)

*p<0.05, §p<0.01, c=child self-report, p=proxy-report Model 1: Examined association of each explanatory variable separately, adjusting for sex, age and clustering by school, with the outcome variable; Model 2: Examined association of all explanatory variables simultaneously, adjusting for age, sex and clustering by school Notes: aodds ratio relates to an X% increase or decrease of the after-school period spent in MVPA for the comparison group/s compared with the referent group, bodds ratio relates to an X% increase or decrease of the after-school period spent in MVPA for every one unit increase in the correlate; c=child self-report, d=proxy-report Abbreviations: MVPA = moderate- to vigorous-intensity physical activity, PA = physical activity, SB = sedentary behaviour

Discussion

This study identified a small number of significant correlates of children’s after-

school physical activity and sedentary behaviour across the three domains of the

ecological model. Despite assessing 59 explanatory variables, only four were

associated with after-school MVPA and only two with after-school sedentary

behaviour in the fully-adjusted models. Interestingly, only one variable was

associated with both physical activity and sedentary behaviour. While there may

be other variables not assessed within the current analysis that impact after-school


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behaviour, these findings suggests that interventions targeting physical activity

and sedentary behaviour may require different strategies depending on the

behaviour.

Parent reported frequency that their child performed non-organised physical

activity after-school (e.g. walked, cycled, walked the dog) was associated with

both after-school MVPA and sedentary behaviour. If the findings were

extrapolated for an average child within this study during an after-school period

of 150 minutes (e.g. 3.30-6pm), each additional performance of non-organised

physical activity after-school would result in a 1% increase in MVPA (i.e. a shift

from 14% to 15% of the after-school period engaged in MVPA or an increase

from 21 to 22.5 minutes of MVPA), and a 2% decrease in sedentary behaviour

(i.e. a shift from 53% to 51% or a decrease from 80 to 77 minutes of sedentary

behaviour). Previous studies examining the relationship between after-school

physical activity and sedentary behaviour have reported conflicting relationships

between the behaviours [36, 37], potential due to different measurement tools and

different definitions of the behaviour outcomes. Although the current study asked

for proxy report of non-organised physical activities that would typically be of

moderate- to vigorous-intensity, the intensity was not specified to participants and

the examples provided (ride bike for fun, walk for exercise, walk dog and play

with dog) may, in some instances, be performed at light-intensity [30].

Encouraging participation in non-organised physical activity of any intensity may

be a simple strategy to promote after-school MVPA and reduce sedentary

behaviours.


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This study also showed that children with parents who are concerned about their

child’s health behaviours perform less MVPA after school than their peers. This is

in contrast to previous research that has shown a positive association between

parents who believe it is important for their child to be active and their child’s

physical activity levels [38]. The current findings may be a consequence of

parents accurately identifying that their child is performing unhealthy behaviours

after school and then becoming concerned about the health behaviours. However,

due to the cross-sectional nature of this study, this cannot be confirmed and

longitudinal data are needed to further investigate this.

Findings from this study build on previous research that has shown the context of

the after-school period (i.e. where the child is and who they are with) is related to

children’s after-school behaviours [39, 40]. For example, time spent outside with

a sibling has previously been associated with more after-school MVPA among

girls [39]. This concurs with the current study that found physical activity co-

participation with a sibling and the number of days a child attends a sporting club

were positively associated with after-school MVPA. If these finding were

extrapolated for an average child in this sample during an after-school period of

150 minutes, each additional occurrence of physical activity co-participation with

a sibling would result in a 4% increase in MVPA after-school (i.e. a shift from

14% to 18%, or an increase from 21 to 27 minutes of MVPA); and each

additional day at a sporting club results in a 7% increase in after-school MVPA

(i.e. a shift from 14% to 21%, or an increase from 21 to 31.5 minutes of MVPA).

These findings may have important implications for future intervention

development. Intervention strategies that provide examples of activities siblings

could do together and encourage parents to promote co-participation may increase


124

children’s after-school physical activity. Physical activity co-participation with a

sibling may be a more feasible intervention target than promotion of sporting club

attendance due to availability, logistical and financial requirements. However,

collaborations with or subsidies from sporting clubs may increase their

accessibility which may have additional benefits for children’s after-school

sedentary behaviour given the relationship between them found in the current

study.

The availability of facilities and equipment has previously been positively

associated with after-school physical activity [41]. However, in this study there

was no association between availability of facilities and after-school physical

activity but interestingly, a lack of available facilities to be active was associated

with more sedentary behaviour after-school. Each unit increase in parents

agreement that such facilities were not available for their child was associated

with an 18% increase in sedentary behaviour (i.e. a shift from 53% to 71%, or an

increase from 80 to 107 minutes of sedentary behaviour during an after-school

period of 150 minutes). While physical activity equipment in the home is

associated with less sedentary behaviour [42] and has been acknowledged as

important among children who perform less sedentary behaviours than their peers

[43], few studies have examined the association between physical activity

facilities and sedentary behaviour and therefore the findings are mixed.

Availability of good sports options was associated with less TV viewing in

children (aged 9.1 years) but not adolescents (14.1 years) [44], yet availability of

local playgrounds was not associated with meeting the sedentary behaviour

guidelines among pre-school aged girls (aged 4.5 years) [45]. This may be

because parents are not aware of the physical activity facilities in their area and


125

when physical activity facilities are not available, parents may feel there is no

alternative to their child being sedentary. Therefore, informing parents of the

physical activity facilities in their neighbourhood or providing examples of how

to use the facilities they have (e.g. yard at home) in an active way may result in

reductions in sedentary behaviours.

It is important to note that many of the correlates assessed in this study were not

significant in the final model which may be due to a number of reasons. Firstly,

many of the survey items were global measures and did not specifically assess the

correlate during the after-school period. Secondly, a 2016 review has shown that

among the limited research to date, the correlates of children’s after-school

sedentary behaviour differ according to location [21]. It could be assumed that the

correlates of physical activity levels would also differ depending on where they

are; however, this study did not stratify by location. In addition, correlates

previously noted in the literature, for example rules which are consistently

inversely related to screen time [46, 47], may not be as relevant during the after-

school period as during other times, for example during the early evenings or on

weekends, and were therefore not significant in the current analysis. This may be

because parents are less likely to be home after-school compared with the evening

time to supervise their children, or because children are at other locations, such as

after-school care or sports clubs, and therefore, home-based rules regarding

sedentary behaviours would not impact behaviour at this location. Lastly, there

may be other factors, particularly within the policy environment within the

physical environment domain of the ecological model, not assessed that are

associated with children’s after-school behaviours require investigating.


126

Limitations of this study include the cross-sectional design which does not allow

for causal pathways to be established. Also, accelerometers measure overall

movement, or a lack of movement as an estimate of sedentary behaviour, and do

not directly measure posture (sitting). Future studies using inclinometers would

add to the literature examining correlates of after-school sedentary behaviours.

This study also had many strengths including the sample, the use of objective

measures of MVPA and SB and the combination of child and parent report of

explanatory variables. Further, unlike previous research which has examined

correlates within a single domain of the ecological model, this study explored a

large range of potential correlates over three domains. This allows the correlates

to be placed within the wider context of the child’s life.

Future research should examine different correlates that may impact behaviour

that were not included in the current study. To do this, purpose designed survey

measures for examining the correlates of after-school behaviours should be used.

Further, as specific sedentary behaviours are frequently related to health outcomes

(e.g. TV viewing and risk of overweight [3, 48, 49]), future research should

examine the correlates of specific behaviours performed after school (e.g. after

school screen-based sedentary behaviours or social sedentary behaviours).

Conclusion

Of the 59 correlates of after-school PA or SB examined, only five were

significantly related and the correlates of PA and SB were predominantly

different suggesting the need for behaviour specific intervention strategies. The

frequency that the child performed non-organised physical activity, such as

walking and cycling, was the only variable associated with both more MVPA and


127

less sedentary behaviour and this may be an important, simple and feasible

intervention focus. Intervention strategies targeting increases in after-school

physical activity may also benefit from promoting sibling co-participation in

physical activity and engagement with sports clubs. Intervention strategies

targeting reductions in sedentary behaviour should also ensure that facilities for

children to be active are available. This study highlights that the context of the

after-school period warrants further investigation as where the child is located and

who they are with is important for the behaviours they are performing after

school.

Cha

pter

Sev

en, P

aper

Six

: The

cor

rela

tes o

f chi

ldre

n’s a

fter-

scho

ol p

hysi

cal a

ctiv

ity a

nd se

dent

ary

beha

vior

128

Add

ition

al T

able

1: C

hild

self-

repo

rted

and

par

ent p

roxy

-rep

orte

d su

rvey

item

s exa

min

ing

the

intr

aper

sona

l, so

cial

env

iron

men

tal a

nd

phys

ical

env

iron

men

tal c

orre

late

s of c

hild

ren’

s aft

er-s

choo

l phy

sical

act

ivity

and

sede

ntar

y be

havi

our.

C

onst

ruct

(s

ourc

e*)

Var

iabl

e de

scri

ptio

n V

aria

ble

codi

ng

Var

iabl

e us

ed in

an

alys

is

Rel

iabi

lity

Sc

ale

Cro

nbac

hs

alph

a In

trap

erso

nal -

indi

vidu

al

Enjo

ymen

t - “

boy

PA’s

” (C

h)

How

muc

h do

you

enj

oy: B

aseb

all,

Foot

ball,

Cric

ket,

Socc

er, B

all p

layi

ng,

Skat

eboa

rd, W

eigh

t lift

ing,

Mar

tial a

rts

1 =

real

ly d

islik

e, 2

=

disl

ike,

3 =

neu

tral,

4=lik

e, 5

= re

ally

like

Enjo

ymen

t of “

boy

Pa’s

”.

(ran

ge 0

-40)

0.74

83

Enjo

ymen

t - “

girl

PA’s

” (C

h)

How

muc

h do

you

enj

oy: V

olle

ybal

l, R

acke

t spo

rts, W

ater

pla

y, S

wim

min

g la

ps, J

ump

rope

, Dan

ce

1 =

real

ly d

islik

e,

2=di

slik

e, 3

=neu

tral,

4=lik

e, 5

=rea

lly li

ke

Enjo

ymen

t of “

girl

PA’s

”. (r

ange

0-3

0)

0.

7183

Enjo

ymen

t - A

cade

mic

SB

(C

h)

How

muc

h do

you

enj

oy:R

eadi

ng fo

r fun

, Rea

ding

for h

omew

ork,

H

omew

ork/

wor

kshe

et

1 =

real

ly d

islik

e,

2=di

slik

e, 3

=neu

tral,

4=lik

e, 5

=rea

lly li

ke

Enjo

ymen

t of a

cade

mic

SB

(ran

ge 0

-15)

0.73

96

Enjo

ymen

t - S

cree

n SB

(C

h)

How

muc

h do

you

enj

oy: P

layi

ng c

ompu

ter/v

ideo

gam

es (e

xclu

ding

Wii)

, N

inte

ndo

Wii

(act

ive)

and

wat

chin

g TV

1

= re

ally

dis

like,

2=

disl

ike,

3=n

eutra

l, 4=

like,

5=r

eally

like

Enjo

ymen

t of s

cree

n-ba

sed

SB (r

ange

0-1

5)

0.

637

Enjo

ymen

t - S

ocia

l SB

(C

h)

How

muc

h do

you

enj

oy: S

ittin

g/ta

lkin

g, T

alki

ng o

n th

e ph

one,

Lis

teni

ng to

m

usic

1

= re

ally

dis

like,

2=

disl

ike,

3=n

eutra

l, 4=

like,

5=r

eally

like

Enjo

ymen

t of s

ocia

l SB

(r

ange

0-1

5)

0.

5069

PA c

ompe

tenc

e (C

h)

Whi

ch se

nten

ce d

o yo

u ag

ree

with

mor

e: 1

) I d

o w

ell a

t all

kind

s of s

ports

OR

I d

on’t'

feel

I am

ver

y go

od w

hen

it co

mes

to g

ames

and

spor

ts; 2

) I w

ish

I co

uld

be a

lot b

ette

r at g

ames

and

spor

ts O

R I

feel

I am

goo

d en

ough

at g

ames

an

d sp

orts

(rev

. cod

ed);

3) I

thin

k I c

ould

do

wel

l at g

ames

and

spor

ts I

have

no

t trie

d be

fore

OR

I am

afr

aid

I mig

ht n

ot d

o w

ell a

t gam

es a

nd sp

orts

I ha

ven’

t trie

d; 4

) I fe

el I

am b

ette

r or a

s goo

d as

oth

ers m

y ag

e at

gam

es a

nd

spor

ts O

R I

don’

t fee

l I c

an p

lay

gam

es a

nd sp

orts

as w

ell a

s oth

ers m

y ag

e; 5

) D

urin

g re

cess

and

lunc

h br

eaks

, I u

sual

ly w

atch

oth

er c

hild

ren

play

gam

es a

nd

spor

ts O

R D

urin

g re

cess

and

lunc

h br

eaks

, I u

sual

ly p

lay

gam

es a

nd sp

orts

(r

ev. c

oded

); 6)

I do

n’t d

o w

ell a

t new

out

door

gam

es a

nd sp

orts

OR

I am

go

od a

t new

out

door

gam

es a

nd sp

orts

(rev

. cod

ed)

PA

com

pete

nce

scal

e (r

ange

0-6

)

0.62

Hea

lthy

TV v

iew

ing

beha

viou

rs

(Ch)

1)

Whe

n th

e sh

ow I

wan

ted

to w

atch

is fi

nish

ed I

turn

the

TV o

ff an

d go

and

do

som

ethi

ng e

lse;

2) B

efor

e I s

witc

h th

e TV

on

I fin

d ou

t wha

t's o

n by

lo

okin

g in

the

TV g

uide

1 =

Nev

er/ra

rely

, 2 =

So

met

imes

, 3 =

Alw

ays

Hea

lthy

TV v

iew

ing

beha

viou

rs sc

ale

(ran

ge

0-4)

Unh

ealth

y TV

vie

win

g be

havi

ours

(C

h)

1) T

he fi

rst t

hing

I do

whe

n I g

et h

ome

is tu

rn th

e TV

on;

2) I

sit a

nd w

atch

TV

no

mat

ter w

hat i

s on;

3) I

con

tinue

to w

atch

TV

eve

n af

ter t

he p

rogr

am I

wan

ted

to w

atch

is fi

nish

ed; 4

) I si

t and

wat

ch T

V/V

ids/

DV

Ds f

or so

long

that

m

um/d

ad te

lls m

e to

turn

it o

ff; 5

) I si

t in

front

of t

he T

V a

nd "c

hann

el su

rf";

6) I

find

out w

hat's

on

TV b

y sw

itchi

ng o

n th

e TV

and

"cha

nnel

surfi

ng".

1 =

neve

r/rar

ely,

2 =

so

met

imes

, 3 =

alw

ays

Unh

ealth

y TV

vie

win

g be

havi

ours

scal

e (r

ange

0-

12)

Cha

pter

Sev

en, P

aper

Six

: The

cor

rela

tes o

f chi

ldre

n’s a

fter-

scho

ol p

hysi

cal a

ctiv

ity a

nd se

dent

ary

beha

vior

129

Con

stru

ct

(sou

rce*

) V

aria

ble

desc

ript

ion

Var

iabl

e co

ding

V

aria

ble

used

in

anal

ysis

R

elia

bilit

y

Sc

ale

Cro

nbac

hs

alph

a Pa

rent

age

(P

) Pa

rent

age

Pa

rent

sex

(P)

Pare

nt se

x

Pa

rent

al e

duca

tion

(P)

Wha

t is y

our h

ighe

st le

vel o

f sch

oolin

g: 1

= N

ever

atte

nded

scho

ol, 2

=

Prim

ary

scho

ol, 3

= S

ome

high

scho

ol, 4

=C

ompl

eted

hig

h sc

hool

, 5

=Tec

hnic

al o

r tra

de sc

hool

, 6 =

Uni

vers

ity o

r ter

tiary

qua

lific

atio

n

U

nive

rsity

/Ter

tiary

D

egre

e H

igh

scho

ol/T

echn

ical

tra

de

Not

com

plet

ed h

igh

scho

ol

Pare

ntal

BM

I (P

) H

ow ta

ll ar

e yo

u w

ithou

t you

r sho

es (c

m)

How

muc

h do

you

wei

gh w

ithou

t clo

thes

or s

hoes

(kg)

BM

I

Pare

ntal

em

ploy

men

t sta

tus

(P)

Empl

oym

ent s

tatu

s Em

ploy

ed fu

ll tim

e in

pa

id/u

npai

d em

ploy

men

t, Em

ploy

ed p

art t

ime

in

paid

/unp

aid

empl

oym

ent,

Hom

e-du

ties f

ull t

ime,

U

nem

ploy

ed

Full

time

Part

time

H

ome

dutie

s ful

l tim

e

Oth

er

Pare

nt w

orkl

oad

(P

) N

umbe

r of h

ours

wor

ked

durin

g a

typi

cal w

eek

Pa

rent

wor

kloa

d

Fa

mily

situ

atio

n (P

) W

hat i

s the

chi

ld's

fam

ily si

tuat

ion

1 =

both

par

ents

live

to

geth

er, 2

= th

e pa

rent

s liv

e ap

art,

3= o

ther

Bot

h pa

rent

s liv

e to

geth

er

The

pare

nts l

ive

apar

t O

ther

Pare

ntal

mar

ital s

tatu

s (P

) Pa

rent

mar

ital s

tatu

s 1

= M

arrie

d, 2

= D

e fa

cto/

livin

g to

geth

er, 3

=

Sepa

rate

d, 4

= D

ivor

ced

5 =

Wid

owed

, 6 =

Nev

er

mar

ried

Mar

ried/

de fa

cto

N

ot m

arrie

d

Pare

ntal

cou

ntry

of b

irth

(P)

Pare

nt c

ount

ry o

f birt

h

Aus

tralia

O

ther

Chi

ld’s

nat

ure

(act

ive)

(P

) 1)

My

child

nee

ds to

be

enco

urag

ed to

be

phys

ical

ly a

ctiv

e (r

ev.c

oded

); 2)

My

child

is n

atur

ally

act

ive;

3) M

y ch

ild is

usu

ally

too

activ

e an

d m

ust b

e 'sl

owed

do

wn'

; 4) P

A is

som

ethi

ng m

y ch

ild d

oes a

utom

atic

ally

1 =

stro

ngly

dis

agre

e, 2

=

disa

gree

, 3 =

nei

ther

ag

ree/

disa

gree

, 4 =

agr

ee,

5 =

Stro

ngly

agr

ee

Chi

ld’s

nat

ure

(act

ive)

sc

ore

(ran

ge 4

-20)

0.76

88

Pare

ntal

per

cept

ions

of

barr

iers

intri

nsic

to th

e ch

ild

(P)

1) M

y ch

ild ju

st d

oesn

't en

joy

bein

g ph

ysic

ally

act

ive;

2) M

y ch

ild is

too

over

wei

ght t

o pa

rtici

pate

in P

A; 3

) My

child

doe

sn't

have

goo

d en

ough

skill

s to

do

mor

e PA

1 =

stro

ngly

dis

agre

e, 2

= di

sagr

ee, 3

=nei

ther

ag

ree/

disa

gree

, 4=a

gree

, 5=

Stro

ngly

agr

ee

Intri

nsic

PA

bar

riers

sc

ore

(ran

ge 0

-3)

0.

662

Cha

pter

Sev

en, P

aper

Six

: The

cor

rela

tes o

f chi

ldre

n’s a

fter-

scho

ol p

hysi

cal a

ctiv

ity a

nd se

dent

ary

beha

vior

130

Con

stru

ct

(sou

rce*

) V

aria

ble

desc

ript

ion

Var

iabl

e co

ding

V

aria

ble

used

in

anal

ysis

R

elia

bilit

y

Sc

ale

Cro

nbac

hs

alph

a N

o on

e to

be

activ

e w

ith

child

My

child

doe

sn't

have

any

one

to b

e ph

ysic

ally

act

ive

with

1

= st

rong

ly d

isag

ree,

2=

disa

gree

, 3=n

eith

er

agre

e/di

sagr

ee, 4

=agr

ee,

5=St

rong

ly a

gree

No

one

to b

e ac

tive

with

ch

ild

Intr

aper

sona

l - b

ehav

iour

al

Out

door

pla

y du

ring

Sum

mer

(P

) H

ow m

any

hour

s/m

inut

es d

oes y

our c

hild

usu

ally

spen

d ou

tsid

e du

ring

a ty

pica

l wee

k af

ter s

choo

l dur

ing

the

war

mer

mon

ths (

Mon

-Fri)

Min

utes

per

day

Out

door

pla

y du

ring

Win

ter

(P)

How

man

y ho

urs/

min

utes

doe

s you

r chi

ld u

sual

ly sp

end

outs

ide

durin

g a

typi

cal w

eek

afte

r sch

ool d

urin

g th

e co

oler

mon

ths (

Mon

-Fri)

Min

utes

per

day

Freq

uenc

y of

non

-or

gani

sed

phys

ical

act

ivity

(P

) H

ow o

ften

(Mon

-Fri)

does

you

r chi

ld:

Rid

e bi

ke fo

r fun

, wal

k fo

r exe

rcis

e, w

alk

dog

and

play

with

dog

PA b

ehav

iour

freq

.

Freq

uenc

y of

org

anis

ed

spor

t or a

ctiv

ities

(P

) H

ow o

ften

(Mon

-Fri)

does

you

r chi

ld:

Parti

cipa

te in

org

anis

ed sp

ort o

r act

iviti

es

O

rgan

ised

spor

t fre

q.

Freq

uenc

y of

act

ive

trave

l (P

) H

ow o

ften

(Mon

-Fri)

doe

s you

r chi

ld:

Wal

k to

des

tinat

ions

not

scho

ol, c

ycle

to d

estin

atio

ns n

ot sc

hool

, wal

k to

sc

hool

and

cyc

le to

scho

ol

A

ctiv

e tra

vel f

req.

Freq

uenc

y of

sede

ntar

y tra

vel

(P)

How

ofte

n (M

on-F

ri) d

oes y

our c

hild

: Tr

avel

by

car/b

us to

/from

des

tinat

ions

oth

er th

an sc

hool

and

trav

el b

y ca

r/bus

to

/from

scho

ol.

Se

dent

ary

trave

l fre

q.

Soci

al E

nvir

onm

ent

Soci

al n

orm

s - a

fter-

scho

ol

PA

(Ch)

1)

Mos

t of m

y fri

ends

pla

y ou

tsid

e af

ter s

choo

l OR

Not

man

y of

my

frien

ds

play

out

side

afte

r sch

ool;

2) M

ost o

f my

frien

ds d

o PA

or s

port

afte

r sch

ool

OR

Not

man

y of

my

frien

ds d

o PA

or s

port

afte

r sch

ool

PA

soci

al n

orm

s sco

re

(ran

ge 0

-2)

Soci

al n

orm

s - a

fter-

scho

ol

SB

(Ch)

1)

Mos

t of m

y fri

ends

wat

ch T

V a

fter s

choo

l OR

Not

man

y of

my

frien

ds

wat

ch T

V a

fter s

choo

l; 2)

Mos

t of m

y fri

ends

pla

y on

the

com

pute

r afte

r sc

hool

OR

Not

man

y of

my

frien

ds p

lay

on th

e co

mpu

ter a

fter s

choo

l

SB

soci

al n

orm

s sco

re

(ran

ge 0

-2)

Rul

es -

prom

otin

g PA

(C

h)

1) I

am a

llow

ed to

pla

y ac

tive

gam

es in

side

the

hous

e; 2

) I a

m a

llow

ed to

th

row

bal

ls o

r pla

y ba

ll-ga

mes

insi

de th

e ho

use;

3) I

am

allo

wed

to w

alk/

ride

a bi

ke in

the

stre

et w

ithou

t an

adul

t; 4)

I am

allo

wed

to g

o to

the

park

with

out a

n ad

ult;

5) I

am a

llow

ed to

go

to th

e lo

cal s

hops

with

out a

n ad

ult

1 =

neve

r/rar

ely,

2=

som

etim

es, 3

=alw

ays

Rul

es p

rom

otin

g PA

sc

ore

(ran

ge 0

-5)

Rul

es -

rest

rictin

g P

A

(Ch)

I h

ave

to fi

nish

my

hom

ewor

k be

fore

I ca

n pl

ay o

utsi

de

1 =

neve

r/rar

ely,

2=

som

etim

es, 3

=alw

ays

Rul

es re

stric

ting

PA

scor

e (r

ange

0-1

)

Cha

pter

Sev

en, P

aper

Six

: The

cor

rela

tes o

f chi

ldre

n’s a

fter-

scho

ol p

hysi

cal a

ctiv

ity a

nd se

dent

ary

beha

vior

131

Con

stru

ct

(sou

rce*

) V

aria

ble

desc

ript

ion

Var

iabl

e co

ding

V

aria

ble

used

in

anal

ysis

R

elia

bilit

y

Sc

ale

Cro

nbac

hs

alph

a R

ules

- pr

omot

ing

SB

(Ch)

1)

I am

allo

wed

to w

atch

any

tele

visi

on sh

ow(s

) I c

hoos

e; 2

) Dur

ing

mea

l tim

es, t

he T

V is

allo

wed

to b

e on

; 3) I

am

allo

wed

to w

atch

TV

in m

y ro

om;

4) I

am a

llow

ed to

pla

y on

the

com

pute

r whe

neve

r I c

hoos

e; 5

) I a

m a

llow

ed

to u

se th

e co

mpu

ter/p

lay

elec

troni

c ga

mes

in m

y ro

om (e

.g. P

SP);

6) I

am to

ld

to si

t stil

l and

pla

y qu

ietly

.

1 =

neve

r/rar

ely,

2=

som

etim

es, 3

=alw

ays

Rul

es p

rom

otin

g SB

sc

ore

(ran

ge 0

-6)

Rul

es -

rest

rictin

g S

B

(Ch)

1)

My

pare

nts r

estri

ct h

ow m

uch

time

I spe

nd w

atch

ing

TV; 2

) My

pare

nts

rest

rict h

ow m

uch

time

I spe

nd u

sing

the

com

pute

r and

pla

ying

ele

ctro

nic

gam

es; 3

) I a

m to

ld o

ff fo

r wat

chin

g to

o m

uch

TV; 4

) I m

ust f

inis

h m

y ho

mew

ork

befo

re I

can

wat

ch T

V; 5

) Afte

r sch

ool,

my

Mum

or D

ad c

hoos

e w

hat I

wat

ch o

n TV

/vid

eo/D

VD

; 6) I

n th

e ev

enin

gs, m

y M

um o

r Dad

cho

ose

wha

t I w

atch

on

TV/v

ideo

/DV

D

1 =

neve

r/rar

ely,

2=

som

etim

es, 3

=alw

ays

Rul

es re

stric

ting

SB

(ran

ge 0

-6)

Pare

ntal

rest

rictio

n of

SB

(P

) 1)

I le

t my

child

wat

ch a

ny te

levi

sion

show

s he/

she

choo

ses (

rev.

cod

ed);

2) I

rest

rict h

ow m

uch

time

my

child

spen

ds w

atch

ing

TV; 3

) I re

stric

t how

muc

h tim

e m

y ch

ild sp

ends

usin

g th

e co

mpu

ter a

nd p

layi

ng e

lect

roni

c ga

mes

; 4) M

y ch

ild is

allo

wed

to p

lay

on th

e co

mpu

ter w

hen

he/s

he c

hoos

es (r

ev. c

oded

)

1 =

stro

ngly

dis

agre

e, 2

= di

sagr

ee, 3

=nei

ther

ag

ree/

disa

gree

, 4=a

gree

, 5=

Stro

ngly

agr

ee

Pare

ntal

rest

rictio

n of

SB

(r

ange

0-2

0)

0.

7175

Nei

ghbo

urho

od

conn

ecte

dnes

s (C

h)

1) T

here

are

lots

of c

hild

ren

arou

nd m

y ar

ea to

pla

y w

ith; 2

) I o

ften

play

in th

e st

reet

with

oth

er k

ids i

n m

y ar

ea; 3

) I o

ften

visi

t oth

er k

ids a

nd fa

mili

es in

my

area

; 4) I

kno

w m

y ne

ighb

ours

qui

te w

ell

1 =

yes,

2 =

no

Soci

al c

onne

cted

ness

sc

ale

(ran

ge 0

-4)

0.

6332

Pare

ntal

PA

(P

) A

ctiv

e A

ustra

lia su

rvey

item

s[7]

: D

urat

ion

of v

igor

ous g

arde

ning

and

vig

orou

s PA

and

mod

erat

e PA

Pare

nt w

eekd

ay P

A

Pare

ntal

SB

(wee

kday

) (P

) A

ctiv

e A

ustra

lia su

rvey

item

s[7]

: D

urat

ion

of si

tting

and

wat

chin

g TV

and

com

pute

r dur

ing

wee

kday

s/5

(WEE

KD

AY

S O

NLY

)

Pa

rent

SB

per

day

PA c

o-pa

rtici

patio

n:

Sibl

ing

(P)

In a

typi

cal w

eek,

freq

uenc

y th

at c

hild

doe

s PA

/pla

ys sp

ort w

ith si

blin

gs

0=ne

ver,

1.5=

1-2

days

/wk ,

3.5

=3-4

da

ys/w

k, 5

.5=5

-6

days

/wk,

7=E

very

day,

‘.’

=N/A

Sibl

ing

PA c

o-pa

rtici

patio

n

PA c

o-pa

rtici

patio

n:

Pare

nt/g

uard

ian

(P

) In

a ty

pica

l wee

k, fr

eque

ncy

that

chi

ld d

oes P

A/p

lays

spor

t with

pa

rent

/gua

rdia

n/ca

regi

ver

0=ne

ver,

1.5=

1-2

days

/wk,

3.5

=3-4

da

ys/w

k, 5

.5=5

-6

days

/wk,

7=E

very

day,

‘.’

=N/A

Pare

nt/g

uard

ian

PA c

o-pa

rtici

patio

n

Cha

pter

Sev

en, P

aper

Six

: The

cor

rela

tes o

f chi

ldre

n’s a

fter-

scho

ol p

hysi

cal a

ctiv

ity a

nd se

dent

ary

beha

vior

132

Con

stru

ct

(sou

rce*

) V

aria

ble

desc

ript

ion

Var

iabl

e co

ding

V

aria

ble

used

in

anal

ysis

R

elia

bilit

y

Sc

ale

Cro

nbac

hs

alph

a PA

co-

parti

cipa

tion:

Pee

rs

(P)

In a

typi

cal w

eek,

freq

uenc

y th

at c

hild

doe

s PA

/pla

ys sp

ort w

ith p

eers

0=

neve

r, 1.

5=1-

2 da

ys/w

k, 3

.5=3

-4

days

/wk,

5.5

=5-6

da

ys/w

k, 7

=Eve

ryda

y,

‘.’=N

/A

Peer

s PA

co-

parti

cipa

tion

SB c

o-pa

rtici

patio

n:

Sibl

ing

(P

) In

a ty

pica

l wee

k, fr

eque

ncy

that

chi

ld si

ts a

nd w

atch

TV

, pla

y vi

deo/

elec

troni

c ga

mes

, on

the

com

pute

r, or

with

oth

er e

lect

roni

c de

vice

s with

si

blin

gs

0=ne

ver,

1.5=

1-2

days

/wk,

3.5

=3-4

da

ys/w

k, 5

.5=5

-6

days

/wk,

7=E

very

day,

‘.’

=N/A

Sibl

ing

SB c

o-pa

rtici

patio

n

SB c

o-pa

rtici

patio

n:

Pare

nt/g

uard

ian

(P)

In a

typi

cal w

eek,

freq

uenc

y th

at c

hild

sits

and

wat

ch T

V, p

lay

vide

o/el

ectro

nic

gam

es, o

n th

e co

mpu

ter,

or w

ith o

ther

ele

ctro

nic

devi

ces w

ith

pare

nt/g

uard

ian/

care

give

r

0=ne

ver,

1.5=

1-2

days

/wk,

3.5

=3-4

da

ys/w

k, 5

.5=5

-6

days

/wk,

7=E

very

day,

‘.’

=N/A

Pare

nt/g

uard

ian

SB c

o-pa

rtici

patio

n

SB c

o-pa

rtici

patio

n: P

eers

(P

) In

a ty

pica

l wee

k, fr

eque

ncy

that

chi

ld s

its a

nd w

atch

TV

, pla

y vi

deo/

elec

troni

c ga

mes

, on

the

com

pute

r, or

with

oth

er e

lect

roni

c de

vice

s with

pe

ers

0=ne

ver,

1.5=

1-2

days

/wk,

3.5

=3-4

da

ys/w

k, 5

.5=5

-6

days

/wk,

7=E

very

day,

‘.’

=N/A

Peer

s SB

co-

parti

cipa

tion

Emot

iona

l sup

port

for P

A

(P)

How

ofte

n pe

r wee

k do

you

: 1) W

atch

you

r chi

ld p

artic

ipat

e in

PA

or s

ports

; 2)

Pra

ise

your

chi

ld fo

r par

ticip

atin

g in

PA

or s

ports

; 3) E

ncou

rage

you

r chi

ld

to d

o PA

or s

ports

; 4) R

ewar

d yo

ur c

hild

for b

eing

act

ive

0=ne

ver,

1.5=

1-2

days

/wk ,

3.5

=3-4

da

ys/w

k, 5

.5=5

-6

days

/wk,

7=E

very

day,

‘.’

=N/A

PA e

mot

iona

l sup

port

freq.

(ran

ge 0

-28)

Prac

tical

supp

ort f

or P

A

(P)

How

ofte

n pe

r wee

k do

you

: 1) P

rovi

de tr

ansp

ort t

o a

plac

e w

here

you

r chi

ld

coul

d do

PA

or p

lay

spor

ts; 2

) Pro

vide

pra

ctic

al su

ppor

t (e.

g. c

lub

fees

) chi

ld

to d

o PA

or s

port

0=ne

ver,

1.5=

1-2

days

/wk,

3.5

=3-4

da

ys/w

k, 5

.5=5

-6

days

/wk,

7=E

very

day,

‘.’

=N/A

PA lo

gist

ical

/fina

ncia

l su

ppor

t fre

q. (r

ange

0-1

4)

Emot

iona

l sup

port

for S

B

(P)

How

ofte

n pe

r wee

k do

you

: 1) W

atch

you

r chi

ld p

lay

on th

e co

mpu

ter/e

lect

roni

c ga

mes

; 2) P

rais

e yo

ur c

hild

for p

layi

ng o

n th

e co

mpu

ter/e

lect

roni

c ga

mes

; 3) E

ncou

rage

you

r chi

ld to

sit q

uiet

ly a

nd w

atch

TV

0=ne

ver,

1.5=

1-2

days

/wk,

3.5

=3-4

da

ys/w

k, 5

.5=5

-6

days

/wk,

7=E

very

day,

‘.’

=N/A

SB e

mot

iona

l sup

port

freq.

(ran

ge 0

-21)

Cha

pter

Sev

en, P

aper

Six

: The

cor

rela

tes o

f chi

ldre

n’s a

fter-

scho

ol p

hysi

cal a

ctiv

ity a

nd se

dent

ary

beha

vior

133

Con

stru

ct

(sou

rce*

) V

aria

ble

desc

ript

ion

Var

iabl

e co

ding

V

aria

ble

used

in

anal

ysis

R

elia

bilit

y

Sc

ale

Cro

nbac

hs

alph

a C

onte

xt (w

ith w

hom

) (P

) W

ho w

as th

e ch

ild w

ith e

ach

day

durin

g th

e pr

evio

us w

eek:

M

um/s

tep-

mum

, Dad

/ste

p-da

d, S

tep/

Bro

ther

, Ste

p/Si

ster

, Frie

nd, R

elat

ive,

G

rand

pare

nt/s

, Nan

ny/M

inde

r

For e

ach

wee

kday

1=

yes,

0=no

#

days

mum

(ran

ge 0

-5)

# da

ys d

ad (r

ange

0-5

) #

days

sibl

ing

(ran

ge 0

-5)

# da

ys o

ther

chi

ld (f

riend

, ra

nge

0-5)

#

days

oth

er a

dult

(rel

ativ

e, g

rand

pare

nt,

nann

y/m

inde

r, ra

nge

0-15

)

m

um=0

.884

da

d=0.

950

sibl

ing=

0.92

5 othe

r chi

ld =

0.

699

othe

r adu

lt =

0.74

8

Use

of T

V a

s a b

abys

itter

(P

) 1)

If m

y ch

ild w

atch

ed le

ss T

V a

nd u

sed

the

com

pute

r les

s, th

ere

wou

ld b

e no

thin

g fo

r my

child

to d

o; 2

) The

TV

/com

pute

r is u

sefu

l for

kee

ping

my

child

oc

cupi

ed; 3

) I d

on’t

have

to w

orry

abo

ut w

here

my

child

is w

hen

he/s

he is

w

atch

ing

TV/u

sing

the

com

pute

r; 4)

My

child

mig

ht g

et u

p to

mis

chie

f if

he/s

he w

asn’

t allo

wed

to w

atch

TV

/use

the

com

pute

r; 5)

My

child

’s si

blin

gs

or fr

iend

s enc

oura

ge h

im/h

er to

wat

ch T

V/u

se th

e co

mpu

ter w

ith th

em; 6

) My

child

is ‘a

ddic

ted’

to th

e co

mpu

ter;

7) T

V v

iew

ing

is so

met

hing

my

child

doe

s au

tom

atic

ally

1 =

stro

ngly

dis

agre

e, 2

= di

sagr

ee, 3

=nei

ther

ag

ree/

disa

gree

, 4=a

gree

, 5=

Stro

ngly

agr

ee

TV u

sed

as b

abys

itter

sc

ore

(ran

ge 7

-35)

Pare

ntal

con

cern

s abo

ut

heal

th b

ehav

iour

s (PA

and

SB

)

(P)

1) I

am sa

tisfie

d w

ith th

e am

ount

of P

A m

y ch

ild d

oes (

reve

rse

code

d); 2

) I

wou

ld li

ke m

y ch

ild to

do

mor

e PA

; 3) M

y ch

ild d

oes e

noug

h PA

to k

eep

him

/her

hea

lthy

(rev

erse

cod

ed);

4) T

he a

mou

nt o

f TV

my

child

wat

ches

w

ould

adv

erse

ly a

ffect

his

/her

hea

lth; 5

) The

am

ount

of t

ime

my

child

spen

ds

on th

e co

mpu

ter/p

layi

ng e

-gam

es w

ould

adv

erse

ly a

ffect

his

/her

hea

lth

1 =

stro

ngly

dis

agre

e, 2

= di

sagr

ee, 3

=nei

ther

ag

ree/

disa

gree

, 4=a

gree

, 5=

Stro

ngly

agr

ee

Pare

nts c

onsc

ious

of P

A

and

SB h

ealth

im

plic

atio

ns (

rang

e 5-

25)

Phys

ical

Env

iron

men

t

Acc

ess t

o PA

equ

ipm

ent

(Ch)

A

vaila

bilit

y in

the

hom

e of

: Bal

ls (f

ootb

alls

, bas

ketb

alls

, ten

nis b

alls

, ba

seba

lls),

Bas

ketb

all r

ing,

Bat

s, ra

cque

ts, g

olf c

lubs

, Bill

y ca

rt, B

owls

(ten

pi

n, sk

ittle

s), C

limbi

ng e

quip

men

t/tre

es th

at y

ou c

an c

limb,

Cub

by h

ouse

, Fr

isbe

e, S

afet

y eq

uipm

ent f

or a

ctiv

ities

(e.g

. bik

e he

lmet

), Sc

oote

r/ Sk

ateb

oard

, Ski

ppin

g ro

pe, S

lide/

swin

gs, S

wim

min

g/w

adin

g po

ol, T

able

te

nnis

tabl

e, b

ats a

nd b

alls

, Tra

mpo

line,

Tric

ycle

/bic

ycle

, V

olle

ybal

l/bad

min

ton

net

1=ye

s, 0=

no

Hom

e PA

equ

ipm

ent

acce

ss sc

ore

(ran

ge 0

-17)

Faci

litie

s to

be a

ctiv

e no

t av

aila

ble

(P)

The

right

faci

litie

s are

not

ava

ilabl

e fo

r my

child

to d

o m

ore

phys

ical

act

ive

1 =

stro

ngly

dis

agre

e, 2

= di

sagr

ee, 3

=nei

ther

ag

ree/

disa

gree

, 4=a

gree

5=

Stro

ngly

agr

ee

Faci

litie

s to

be a

ctiv

e no

t av

aila

ble

Chi

ld b

edro

om S

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134

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ncy

Chapter Seven, Paper Six: The correlates of after-school physical activity and sedentary behaviour

135

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physical activity and fitness in school-aged children and youth. International Journal of Behavioral Nutrition and Physical Activity, 2010. 7(1): p. 40.

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42. Maitland, C., et al., A place for play? The influence of the home physical environment on children's physical activity and sedentary behaviour. International Journal of Behavioral Nutrition and Physical Activity, 2013. 10(1): p. 99.

43. Veitch, J., et al., Children’s perceptions of the factors helping them to be ‘resilient’ to sedentary lifestyles. Health Education Research, 2013.

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45. Hinkley, T., et al., The correlates of preschoolers' compliance with screen recommendations exist across multiple domains. Preventive Medicine, 2013. 57(3): p. 212-219.

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138

CHAPTER EIGHT

Thesis Discussion and Conclusion

Through inter-related studies, this thesis by publication identified the importance

of the after-school period for children’s physical activity and sedentary

behaviours, and also the limitations and gaps within the current literature

examining these behaviours. Subsequently, this thesis addressed many of these

limitations and generated valuable new knowledge of children’s and adolescents’

behaviours during the critical after-school period. Using the standardised

definition of the ‘after-school period’ identified in Chapter Four (end of school-

6pm), this thesis examined the cross-sectional and longitudinal prevalence of

Australian children’s after-school physical activity and sedentary behaviours. In

doing so, it identified the large contribution this period makes to children’s daily

levels of physical activity and sedentary behaviour, providing a strong rationale

for interventions to be implemented during this period. To inform the

development of interventions targeting this period, an understanding of the

correlates of these behaviours is required. The intrapersonal, social and physical

environment correlates of children’s after-school physical activity and sedentary

behaviour were therefore examined, adding to the limited evidence base in this

area.

Contained in each paper of this thesis is a discussion of the findings specific to

that study. Therefore, this chapter synthesises the findings across all studies in

this thesis and discusses them in relation to previous research. The state of the

current literature is briefly summarised, however this discussion is predominantly

Chapter Eight: Thesis Discussion and Conclusion

139

focussed on the original research conducted as part of this thesis. Future research

recommendations and directions, and the practical implications based on the

findings from this thesis are provided.

8.1 Overview and discussion of findings

8.1.1 Previous state of the literature

The literature reviews that summariesed the prevalence of children’s after-school

physical activity and sedentary behaviour (Chapter Two) showed that despite the

variety of definitions of the ‘after-school period’ used, children have the

opportunity to be active during this period, yet their participation levels are

generally low. For example, boys and girls from the UK performed only 13.2 and

10.6 minutes of moderate- to vigorous-intensity physical activity respectively

between 3-5pm (Fairclough et al., 2007), and boys and girls from Denmark,

Portugal, Estonia and Norway performed between 34-52 minutes and 24-39

minutes of moderate- to vigorous-intensity physical activity respectively, between

2pm/3pm and midnight (Nilsson et al., 2009b). In addition, children and

adolescents spent approximately half of the after-school period in objectively

measured sedentary time. However, this was comprised of both screen- and non-

screen based sedentary behaviours. For example, children and adolescents spent

20% of the after-school period engaged in TV viewing and almost 60% in non-

screen based sedentary behaviours such as homework and social sedentary

behaviours. Further, these behaviours differed according to location (e.g. after-

school care or other locations) and age. Importantly, this has highlighted that TV

viewing is not the main sedentary behaviour after school as homework, motorised


140

transport and social sedentary behaviours were also large contributors to after-

school sedentary behaviours.

The correlates of children’s after-school physical activity are beginning to

emerge. However, the literature is predominantly cross-sectional, among samples

from the US, and has typically examined the correlates within just one of the

domains of the ecological framework. The correlates identified as associated with

after-school physical activity were predominantly within the intrapersonal and

social domains of the ecological framework (e.g. self-efficacy (Chaoqun et al.,

2012) and social support (Chaoqun et al., 2012; McMinn et al., 2013)),

highlighting important gaps for future research to address.

Of the 58 variables explored as potential correlates of children’s after-school

sedentary behaviour, only two non-modifiable correlates were associated: sex

(null association with after-school overall sedentary behaviour and after-school

TV viewing) and age (inconsistent association with TV viewing and a positive

association with overall sedentary behaviour). The lack of associations found

highlighted that the examination of children’s after-school sedentary behaviours,

and their correlates, is still in its infancy and more research is needed.

8.1.2 Prevalence of physical activity and sedentary behaviour during the

after-school period

To build on the limited research to date, this thesis has provided valuable

information about children’s after-school physical activity and sedentary

behaviour levels both cross-sectionally (Chapter Five) and longitudinally

(Chapter Six) (Table 8.1). As shown in Table 8.1, children from both the

younger and older cohorts of the longitudinal study increased their after-school


141

sedentary behaviour and reduced their light- and moderate- to vigorous-intensity

physical activity over five years. This positive relationship between age and

overall sedentary behaviour is aligned with the finding from the systematic review

of the correlates of after-school sedentary behaviours (Chapter Two).

Table 8.1 The percentage of the after-school period spent in sedentary

behaviour (SED), light- (LPA) and moderate- to vigorous-intensity (MVPA)

physical from cross-sectional and longitudinal prevalence studies in this

thesis.

SED LPA MVPA

Cross-sectional sample (Chapter Five)

aged 8.1 years

54%

32%

14%

Longitudinal sample (Chapter Six)

Younger cohort

aged 5-6 years (baseline)

28%

48%

24%

aged 10-11 year (5-year follow-up) 43% 47% 11%

Older cohort

aged 10-12 years (baseline)

38%

51%

12%

aged 15-16 year (5-year follow-up) 56% 43% 8%

Interestingly, children in the cross-sectional study spent over half of the after-

school period in sedentary behaviour, which parallels the findings from the

systematic review of after-school sedentary behaviour prevalence (Chapter

Two). However, this was higher than the majority of findings regarding after-


142

school sedentary behaviour from the longitudinal study. Only the 5-year follow-

up prevalence data from children aged 10-12 at baseline (aged 15-17 at follow-

up) are similar to the findings from the cross-sectional study and systematic

review. Further, the moderate- to vigorous-intensity physical activity performed

by children in the cross-sectional study is higher than all of the longitudinal

findings with the exception of the younger cohort’s baseline moderate- to

vigorous-intensity physical activity levels.

The differences in the percentage of time spent across sedentary and physical

activity intensities between the cross-sectional and longitudinal studies may be

due to the age differences within the samples (5-6 and 10-12 years at baseline in

the longitudinal analysis compared to 8 years in the cross-sectional analysis).

Secular changes in physical activity and sedentary behaviours over the nine year

period between when the cross-sectional and longitudinal studies were conducted

may have contributed to the behaviour differences. For example, average

organised sport duration declined by 48 minutes per fortnight between 2006 and

2012 among Australian 5-8, 9-11 and 12-14 year olds (Australian Bureau of

Statistics, 2012; Australian Bureau of Statistics, 2006a). The differences may also

be due to seasonality which has shown to influence the behaviours of children

(Ridgers et al., 2015) and adolescents (Belanger et al., 2009). In addition,

differences may be due to technical variations in the accelerometers used to

measure behaviour (i.e. accelerometer model and epoch length), which are further

discussed in the strengths and limitations of this thesis in Section 8.2.

The percentage of time spent in moderate- to vigorous-intensity physical activity

after school is less than other periods of the day where children also have

discretion over the behaviours they perform, such as recess and lunchtime. For


143

example, children aged 5-6 years and 10-12 years spent approximately 41% and

27% of recess in moderate- to vigorous-intensity physical activity respectively,

and 42% and 29% of lunchtime in moderate- to vigorous-intensity physical

activity respectively. Further, this thesis showed that children performed more

sedentary behaviour after school than at recess and lunchtime, as children aged 5-

6 years and 10-12 years spent approximately 15% and 14% of recess sedentary

respectively, and 22% and 21% of lunchtime sedentary respectively (Ridgers et

al., 2011). This highlights that the after-school period is a key period that holds

great potential for setting-specific interventions to target increases in physical

activity and reductions in sedentary time.

Sex difference in after-school physical activity prevalence reported in this thesis

have important implications for intervention development. This thesis found that

cross-sectionally (Chapter Five) and longitudinally (Chapter Six), girls

performed more light-intensity physical activity after school than boys, whereas

boys performed more moderate- to vigorous-intensity physical activity than their

female counter parts. This is consistent with studies examining daily physical

activity (Ajja et al., 2012; Steele et al., 2010) and physical activity performed

during other periods of the day such as recess, lunch (Ridgers et al., 2012a) and

school time (Hubbard et al., 2016). Conversely, no sex differences in objectively

measured after-school sedentary behaviour were observed within Chapter Five

(cross-sectional) or Chapter Six (longitudinal); a finding also supported by the

systematic review of the correlates of after-school sedentary behaviours contained

in Chapter Two. The literature examining daily sex differences in sedentary

behaviour levels is varied with some studies suggesting girls are more sedentary

overall than boys (Steele et al., 2010) while others have found mixed associations


144

between sex and screen time (Stierlin et al., 2015). However, in relation to

sedentary behaviours after school, it appears that the association with sex may be

dependent on the specific sedentary behaviour being performed. For example,

girls spend more time in social sedentary behaviours such as telephone use and

shopping/hanging out (which may be also be of a light intensity) than boys (Atkin

et al., 2008), yet boys engage in more computer and video game use (Atkin et al.,

2008) and combined TV viewing and computer use (Wen et al., 2009).

There may be specific behavioural differences that explain this variability in light-

and moderate- to vigorous-intensity physical activity between boys and girls,

particularly as there were no differences in sedentary time. However, further

research is required to investigate this. Subsequently, there may also be sex

differences in the correlates of specific after-school physical activities and

sedentary behaviours. As explained in section 8.3, future research that explores

this is needed to inform intervention development and potential sex-specific

tailoring of strategies which has previously occurred in interventions targeting

children’s daily behaviours (Okely et al., 2011; Pate et al., 2007).

8.1.3 Contribution of the after-school period to daily physical activity and

sedentary behaviour levels

While the previous section discussed the percentage of time children spend in

sedentary behaviour and physical activity after school, this thesis also explored

the contribution that this period makes to overall daily participation cross-

sectionally (Chapter Five) and longitudinally (Chapter Six). Importantly, this

thesis found that although after school moderate- to vigorous-intensity physical

activity declined with age (from 18.5 minutes at 10-12 years to 11.5 minutes at


145

15-17 years), the contribution of this period to daily physical activity levels

increased over this five-year period (from 23% to 33%). This increase in

contribution to daily behaviours was particularly evident during the transition

from primary (elementary) to secondary school. In addition, the after-school

period became more important for girls over time than for boys, as girls’

moderate- to vigorous-intensity physical activity levels were lower than boys’, yet

this period made a greater contribution to their daily levels. Simply, the after-

school period becomes more important over time in contributing to adolescents’

physical activity levels, particularly among girls. The contribution that the after-

school period made to daily physical activity levels within this thesis is similar to

previous research that also used accelerometers to examine after-school

behaviours (Hager, 2006). Children (aged 9-12 years) in Hager’s study performed

46% of their daily physical activity between 3pm-9pm; however, it peaked in the

early after-school hours (i.e. 3pm-6.30pm) during which time boys and girls

performed 37.2% and 33.7% of their daily physical activity levels respectively

(Hager, 2006). This further highlights that the definition of ‘after-school period’

produced in this thesis (end-of-school to 6pm) should be used for future research

as behaviours in the later evening period (e.g. 6.30pm-9pm) appear to be very

different to those performed immediately after school.

Despite the high levels of sedentary behaviour performed after school, this thesis

found that 5-6 and 8 year-old children performed approximately 20% of their

daily sedentary behaviours during the after-school period. Although sedentary

behaviours increased during the after-school period, the contribution to daily

levels remained relatively stable with age (15-16 year olds performed

approximately 16% of their daily sedentary behaviours after school). This


146

contribution is lower than the 26% of daily sedentary behaviours that 10-14 year

old children from the UK perform after school (Bailey et al., 2012). It is also

considerably higher than the 1.8% and 6% of daily sedentary behaviours

performed during recess and lunchtime respectively (Bailey et al., 2012). This

again indicates that the after-school period is a unique period of the day that

offers great opportunity for intervention targeting children’s sedentary

behaviours, and such changes may make a large difference to daily sedentary

behaviour levels.

Another novel finding from this thesis was that small changes in children’s after-

school physical activity and sedentary behaviours significantly impacted their

likelihood of achieving the associated physical activity or sedentary behaviour

guidelines (Chapter Five). For every additional 1% of the after-school period

spent in physical activity, children were 31% more likely to achieve the physical

activity guidelines of at least an hour per day; and for every 1% decrease in the

after-school period spent in sedentary behaviour, children were 3% more likely to

achieve the sedentary behaviour guidelines of less than two hours per day of

screen time. These findings, in addition to the cross-sectional and longitudinal

prevalence and contribution to daily behaviour levels, highlight that the after-

school period represents a window where significant increases in physical activity

and reductions in sedentary behaviour could be made. Further, behaviour changes

during the after-school period would make a substantial improvement to

children’s compliance with the physical activity and sedentary behaviour

recommendations. There is therefore a need to better understand the correlates of

these behaviours to inform future intervention development.


147

8.1.4 Correlates of physical activity and sedentary behaviour during the

after-school period

To address the gaps within the literature examining the correlates of after-school

sedentary behaviours and physical activity identified in Chapter Two, this thesis

explored the correlates of children’s after-school physical activity and sedentary

behaviour (Chapter Seven). Using an ecological framework (Bronfenbrenner,

1989), this thesis examined the correlates within the intrapersonal, social and

physical environmental domains. Of the 16 variables included in the final model,

only physical activity co-participation with siblings, the number of days at a

sporting club, and frequency of non-organised physical activity were positively

associated with after-school physical activity. Parental concern about their child’s

health behaviours was the only variable negatively associated with children’s

after-school physical activity.

This thesis found that co-participation in physical activity with a sibling was

associated with a 4% (or 6 minute) increase in moderate- to vigorous-intensity

physical activity after school among children (aged 8.2 years). This association is

consistent with previous research examining daily physical activity levels (Efrat,

2009). Interestingly, there was no relationship between friend co-participation and

children’s after-school physical activity in this thesis. However, among

adolescents (12 years) co-participation with friends, but not siblings, is associated

with more physical activity out of school hours (Garcia-Cervantes et al., 2016).

This may indicate an age-related change in who children are active with outside

of school, potentially stemming from changes in social networks and independent

behaviours. It is also likely that the setting and context of the after-school period


148

changes with age, for example, older children are more likely to be at home

unsupervised after school than younger children (Australian Bureau of Statistics,

2007). Subsequently, interventions targeting children’s and adolescents’ after-

school physical activity and sedentary behaviours should consider this, for

example, through provision of examples of active pastimes children can do with

their siblings and adolescents can do with their friends.

An important finding for intervention development is that both the number of

days at a sporting club and the frequency of non-organised physical activity were

associated with after-school physical activity. Interventions targeting after-school

physical activity levels may therefore be effective if they promote physical

activity regardless of the type. The existence of barriers to organised sport

participation (e.g. financial and logistical barriers) may limit participation for

some children. However, this study shows that children can still be active after

school through non-organised physical activity which requires minimal cost and

equipment.

Although the inverse association between parental concerns about their child’s

health behaviours and children’s after-school physical activity levels is surprising,

it has been previously observed among pre-school children (Hinkley et al., 2013).

It does, however, suggest that parents can accurately determine if their child is

performing suboptimal levels of physical activity and sedentary behaviour after

school, which may assist recruitment for interventions targeting children with

these behavioural characteristics. Due to the cross-sectional nature of this study

and associated limitations (discussed further in section 8.2), causality between

these variables cannot be determined. Further longitudinal investigation is needed


149

to determine if parental concerns regarding their child’s health behaviours is

predictive of after-school physical activity levels.

Of the 17 correlates of children’s after-school sedentary behaviours in the final

model, only the frequency of non-organised physical activity was negatively

associated, and lack of the right facilities for children to be active was positively

associated with after-school sedentary behaviour. As discussed previously, the

promotion of non-organised physical activity after-school is a simple and cost-

effective intervention strategy that may increase in after-school physical activity.

Findings from this thesis suggest that it may also simultaneously result in

reductions in after-school sedentary behaviours as it may be an easy yet engaging

alternative behaviour. However, as this is one of the first studies to investigate the

relationship between non-organised physical activity and after-school sedentary

behaviour, further research is warranted.

As noted in the systematic review of the correlates of children’s after-school

sedentary behaviour (Chapter Two), no other studies have previously examined

the relationship between physical activity facilities and after-school sedentary

behaviour levels (Arundell et al., 2016). Only one has looked at the provision of

non-fixed equipment and sedentary behaviour levels (null association), however

this was only within an after-school program setting (Rosenkranz et al., 2011a).

Instead research has focused on the relationship between physical activity

facilities and physical activity levels (Stanley et al., 2012; D'Haese et al., 2015a),

which was not significant in this thesis. The current findings suggest that

interventions targeting after-school sedentary behaviours may be effective if they

increased parental awareness of the facilities within their neighbourhood that can

be used for physical activity or provide suggestion of how to use the facilities


150

they have (e.g. yard). However, as the agreement between subjective and

objective measures of physical activity facilities is poor (Ball et al., 2008), global

positions systems (GPS) or audits of the local neighbourhood would provide

accurate information regarding the availability of physical activity facilities that

could be then communicated to families when targeting reductions in after-school

sedentary behaviour.

No social environment correlates of after-school sedentary behaviour were

observed in this thesis. Further, the systematic review in this thesis (Chapter

Two) did not identify any social environmental correlates associated with

children’s sedentary behaviours, most likely due to the limited number of

published studies examining these associations. However, previous research has

found contrasting results between the social environment and children’s daily

sedentary behaviours. TV viewing co-participation with the child’s mother was

found to be positively associated with overall home-based sedentary behaviours

(Granich et al., 2011), and parent and sibling modelling was positively associated

with electronic-based sedentary behaviours (Granich et al., 2010). The influence

of the social environment on after-school sedentary behaviour, particularly role

modelling, may be behaviour specific where parental, sibling or peer modelling of

a specific behaviour, such as TV viewing or screen-based sedentary behaviours, is

associated with elevated levels of that behaviour among children. As this thesis

assesses overall sedentary behaviour, the associations with specific sedentary

behaviours was not able to be determined, but warrants further investigation.

Despite correlates from three domains of the ecological model being identified as

associated with after-school moderate- to vigorous-intensity physical activity and

sedentary behaviour in the model 1 findings, the few significant findings from the


151

final analyses indicate that further research examining the correlates of after-

school physical activity and sedentary behaviours is required. As explored in the

discussion section of Chapter Seven, there are a number of reasons why many of

the variables were not associated with the outcome behaviours. Firstly, the sample

was not stratified according to the child’s location, which has shown to impact the

correlates associated with after-school behaviours (Arundell et al., 2016).

Secondly, the majority of the survey measures were global measures of the

correlate rather than measures specific to the after-school period. As explained in

section 8.3, this is a limitation of this study and may be why there were many null

findings. Thirdly, the correlates consistently associated with daily behaviours may

not be as relevant during the after-school period as other times of the day such as

the later evening period. Two such examples include the presence of a TV in a

child’s bedroom and rules. Having a TV in a child’s bedroom is consistently

associated with higher daily electronic media use (Granich et al., 2011); however,

as suggested by the findings from the systematic review of after-school sedentary

behaviour prevalence, TV viewing is not the main sedentary behaviour performed

after-school. Children may therefore be watching TV in their bedroom during the

later evening period, and subsequently there is no association between having a

TV in the bedroom and after-school sedentary behaviour. Another example is the

presence of rules which have been shown to be inversely related to overall screen

time (Ramirez et al., 2011; Hoyos Cillero and Jago, 2010). However, parents may

not be home after school to enforce these rules, or home-based rules regarding

sedentary behaviour may not be required if the child is at after-school care or a

sporting club. Lastly, this thesis may have missed potentially important correlates

of after-school physical activity such as homework expectations and distance of


152

school to home which may influence active or sedentary travel. Also, few

correlates relating to the policy environment within the physical environment

domain of the ecological model were included in the variables examined. The

existence of policies regarding use of school facilities or equipment after school

or mandated physical activity requirements at after-school care may be

particularly important during the after-school period, and should be examined in

future research.

This thesis has provided an initial step in identifying the correlates of children’s

after-school physical activity and sedentary behaviour required for informing the

development of intervention strategies aiming to increase physical activity and

reduce sedentary behaviours after school. There are many considerations for

future research and practical implications based on these findings which are

described in Sections 8.3 and 8.4. Strengths and limitations of the current research

are discussed below.

8.2 Strengths and limitations of this thesis

Each of the six publications contained within this thesis included a discussion of

the strengths and limitation specific to that study. Therefore, this section provides

only a brief overall discussion of the strengths and limitations of this thesis.

Both studies which examined the prevalence of children’s after-school physical

activity and sedentary behaviour (cross-sectionally and longitudinally) used

objective measures of physical activity and sedentary behaviours. However, the

model of accelerometer differed (GT3X compared to GT1M) as did the epoch

used for data collection (15 seconds compared to 60 seconds). Considerable

literature has explored the impact of these methodological differences on the


153

behaviour outcomes. The model 7164, which preceded the GT1M, has been

shown to underestimate time spent sedentary and overestimate light-intensity

physical activity compared with the GT1M among children (Corder et al., 2007).

However, no differences in the time children spent in sedentary, light- or

moderate- to vigorous-intensity physical activity have been observed (Ramirez-

Rico et al., 2014) when comparing the GT1M and the GT3X models (Hänggi et

al., 2013).

Many studies have also examined the effect of the epoch length on time spent in

light-, moderate- and vigorous-intensity physical activity (Welk et al., 2000;

Edwardson and Gorely, 2010; Nilsson et al., 2002). When comparing the time

children aged 7-11 years spent in these behaviours using data collected in 5-, 15-,

30- and 60-second epochs, a shorter epoch resulted in identification of less time

spent in light-, moderate- and vigorous-intensity physical activity (Edwardson and

Gorely, 2010). However, a shorter epoch has been found to result in higher

estimates of very vigorous-intensity (6-8.99 METS) physical activity (Nilsson et

al., 2002; Edwardson and Gorely, 2010). There is also emerging evidence that

caution should be taken when applying cut points created using a particular length

epoch (e.g. 15 seconds as used for the Evenson cut points (Evenson et al., 2008))

to data collected in a different epoch length (e.g. 60 seconds) (Banda et al., 2016).

Doing so may influence physical activity and sedentary behaviour levels as a

longer epoch results in elevated light intensity physical activity and reduced

sedentary time (Banda et al., 2016). These methodological considerations may in

part explain the different prevalence rates of physical activity in the cross-

sectional study that used 15 second epochs compared with the longitudinal study

that used 60 second epochs.


154

An additional consideration regarding the use of accelerometers to measure after-

school physical activity throughout this thesis is that accelerometers cannot be

worn during aquatic activities (Trost, 2001). Further, accelerometers can

underestimate physical activity performed when riding a bike or walking/running

up an incline (Trost, 2001), and they cannot assess upper body activities such as

throwing, catching or carrying heavy objects (Welk et al., 2000). As these

behaviours are often performed by children, physical activity levels may have

been underestimated within the studies of this thesis that used accelerometers.

Subjective measures of behaviours and correlates also have limitations which

have been thoroughly discussed within the literature (Melanson and Freedson,

1996; Telford et al., 2004; Sirard and Pate, 2001; Baranowski, 1988; Warnecke et

al., 1997; Welk et al., 2000). These include social desirability bias (Warnecke et

al., 1997), recall difficulties (Melanson and Freedson, 1996) and poor time

perception skills (Welk et al., 2000) among children under 10 years.

Consequently, parents of children younger than 10 years proxy-reported their

child’s behaviours; however, this relies on the respondent observing the behaviour

of interest and understanding the terminology used (e.g. “moderate”, “physical

activity”) (Baranowski, 1988). However, the behavioural and contextual

information provided by self- and proxy- report surveys (i.e. what activity was

being performed and where) is valuable when examining the prevalence and

correlates of specific behaviours (e.g. TV viewing, active travel) as this

information cannot be obtained from accelerometers.

In spite of the above limitations, a major strength of this thesis is the combined

use of objective and subjective techniques to assess children’s after-school


155

physical activity and sedentary behaviours. This mixed methods approach

provides a comprehensive understanding of these behaviours. The combination of

child self- and parent proxy-report surveys also provides rich data about the

potential influences on children’s after-school behaviours. As children’s and

parents’ beliefs and perceptions are likely to differ, but still influence behaviour,

examining self- and parent proxy-reported correlates builds a thorough

understanding of factors influencing children’s after-school behaviours.

The cross-sectional design of the correlates study (Chapter Seven) is limited in

that it is not able to identify causal pathways. For example, while the number of

days at a sporting club was associated with physical activity, it cannot be

determined if the number of days at a sporting club predicts physical activity or if

the reverse is true. However, the use of an ecological model (Bronfenbrenner,

1989) to frame the exploration of correlates across multiple domains is a strength

of the study, as often studies only examine the potential correlates from one or

two domains. This thesis assessed a broad range of potential correlates of

children’s after-school behaviours within the intrapersonal, social and physical

environment domains acknowledging that characteristics of all three domains may

influence behaviour. However, not all correlates were purpose-designed for the

after-school period and were instead global measures of the correlate, such as

survey items asking about social support in general without an associated time

frame. This may limit specificity of the analysis and findings.

An additional strength of this thesis is the inclusion of longitudinal data to

highlight how children’s after-school behaviours change over time. Further, the

longitudinal data examined behaviours over an important transition from

elementary school to secondary school and from early to late secondary school,


156

identifying potential intervention targets. Given the findings from this thesis and

the remaining gaps in evidence, many future research recommendations and

directions, and practical implications have emerged and are described in Sections

8.3 and 8.4.

8.3 Future research recommendations and directions

This thesis has highlighted the importance of the after-school period for children’s

physical activity and sedentary behaviour participation levels. It also provides a

foundation for the development of intervention strategies targeting these

behaviours. Consequently, there are many implications and recommendations for

future research stemming from the findings of this thesis.

Researchers should adopt the standardised definition of the after-school period

identified in this thesis for future research on children’s after-school physical

activity and sedentary behaviour. This would allow meaningful comparisons

between studies of after-school behaviours and population sub-groups (e.g.

boys and girls, low and high SES groups, etc), developing the evidence base

on this important time period.

In addition to targeting reductions in TV viewing and screen-time after

school, future interventions should focus on strategies to reduce non-screen

based sedentary behaviours after school. For example, homework that

incorporates a physical activity component or requires children to be standing

throughout the task could be provided by teachers (e.g. a homework task

could be to develop and teach family members a new active game) to reduce

or interrupt long periods of sedentary behaviours at home. Alternatively,


157

recommendations regarding the time of day that sedentary homework tasks

are completed (e.g. after 6pm, or after daylight hours) could be developed by

teachers in collaboration with parents. This would free the daylight hours for

active play and potentially reduce the time for other non-homework related

sedentary behaviours prior to bedtime.

Interventions targeting after-school physical activity may benefit from

promoting both non-organised physical activity and organised physical

activity such as attendance at sporting clubs. However, the barriers to

participation in these activities after school (e.g. logistical and financial

barriers, not appealing to children who do not like sport), need to be identified

and the feasibility of potential solutions investigated (e.g. government

subsidies or reduced sporting club fees for low SES participants, walking

buses to the sporting clubs or local parks where children can play, supervision

at local parks during the after-school hours etc.).

Additional research examining the correlates of children’s after-school

physical activity and sedentary behaviour is needed to guide intervention

development. In addition, to build upon the correlates literature, longitudinal

research into the determinants of these behaviours is also required. There are a

number of suggestions for future correlate and determinant research identified

from this thesis that should be considered:

o Future research should examine the longitudinal determinants of

children’s after-school behaviours across all domains of the ecological

model to provide a comprehensive understanding of the factors that


158

influence participation. This will also provide information on the context

within which the identified determinants can be understood.

o Survey items that are purposefully designed to measure the correlates and

determinants of after-school physical activity and sedentary behaviour

should be used in future studies instead of global measures of these

variables (e.g. presence of friends to be active with during the after-school

period, frequency of support for after-school physical activity).

o Further investigation into behaviour-specific correlates and determinants is

warranted as the correlates appear to differ according to the behavioural

outcome (e.g. TV viewing or Computer/DVD/video games). This would

require the use of valid and reliable measures that can capture behaviour-

specific information and the correlates specific to the after-school period.

o Research should also consider and assess the context of the behaviour (i.e.

where the child is located and who they are with) as the behaviours differ

according to context. Consequently, intervention strategies targeting these

behaviours may need to be tailored accordingly. For example by

developing strategies that target home or after-school care physical

activity and sedentary behaviours or behaviour performed with siblings or

peers.

o As boys and girls display different after-school physical activity and

sedentary behaviour levels, large study samples that enable stratification

by sex are needed to investigate the behaviours performed, and the sex-

specific correlates and determinants of boys’ and girls’ after-school

physical activity and sedentary behaviour. This would assist the


159

development of sex-specific intervention strategies to promote after-school

physical activity and restrict sedentary behaviour participation.

8.4 Practical implications from this thesis

The findings from this thesis should be considered by, and may be useful for,

researchers, parents, teachers, schools, after-school care and extracurricular

activity providers, and policy makers. Some suggestions and recommendations

are outlined below:

After school, physical activity should be promoted and both screen and non-

screen based sedentary behaviours restricted particularly when children are at

locations other than after-school care. For example, parents could promote

non-organised physical activity when at home during the after-school period.

This should be done from a young age to reduce the age-related declines in

physical activity and increases in sedentary behaviour.

To increase opportunities for physical activity and reduce sedentary

behaviours, after-school care programs should be developed with a focus on

physical activity and the amount to be included in the program potentially

mandated (e.g. 30 minutes of physical activity per day). After-school care

providers may also be required to undertake training specific to the provision

of physical activity. Furthermore, screen-based sedentary behaviours should

be excluded from these programs and non-screen based sedentary behaviours

limited.

To increase participation in after-school physical activity and reduce

sedentary behaviour, extracurricular sports and training programs conducted


160

either by schools or external organisations should be promoted to children.

For example, schools could provide opportunities for children to use their

facilities and equipment after school hours, and financial support made

available to those who need it to facilitate participation. Alternatively, schools

may become involved in government strategies promoting physical activity,

such as Sporting Schools (www.sportingschools.gov.au) which targets

Australian primary schools (Australian Government Australia Sports

Commission, 2015). Within these strategies, schools could opt to have a

strong focus on promoting physical activity during the after-school period.

Further, such strategies could also be adapted to an international audience to

target after-school behaviours among children in other countries.

Strategies to increase the availability of facilities or awareness of facilities for

children to be active could be implemented to target reductions in after-school

sedentary behaviour. Examples of these include informing parents of the

facilities currently in their neighbourhood and providing suggestions of how

children could use the facilities they have (e.g. driveway, yard) to be active.

Although not examined in this thesis, the availability of physical activity

facilities may be increased through collaboration with local government and

urban planners. For example, by ensuring adequate walking paths and parks

are included when upgrading or developing new suburbs.

To further increase availability of facilities or awareness of facilities,

communities could become involved in “Play Streets”, where streets are

closed to traffic for a certain time of the day to allow children to play on them.

Although these have only been trailed in three streets in Melbourne Australia,

they are established in Ghent, London and Edinburgh where they have shown


161

to increase children’s moderate- to vigorous-intensity physical activity and

sedentary behaviour (D'Haese et al., 2015b).

To encourage girls’ participation in physical activity and limit their sedentary

behaviour, parents and teachers could refer to Government initiatives such as

“Girls make your move” (Australian Government Department of Health,

2016). Tips and resources for parents and teachers are provided to encourage

girls to be active at any intensity. While this is not specifically focused on the

after-school period, many suggestions, for example making physical activity

part of the family routine, could be implemented during this time.

Australian recommendations for children’s physical activity and sedentary

behaviours previously specified that sedentary behaviours should be restricted

during daylight hours (Department of Health and Aging Australian

Government, 2004); however, this has since been removed from the current

guidelines (Australian Government Department of Health, 2014). Given the

contribution the after-school period makes to the likelihood of achieving the

recommendations, future iterations may need to specify that physical activity

should be promoted and sedentary behaviour restricted during this period.

8.5 Conclusions

This thesis has built on the limited Australian and international literature

examining children’s physical activity and sedentary behaviour during the

important after-school period. Despite a variety of definitions of ‘after-school’

previously used within the literature, children and adolescents spend

approximately half of the period sedentary and after-school sedentary behaviours


162

increase as children age. Further, children and adolescents perform many screen-

and non-screen based sedentary behaviours during this time, providing a variety

of potential intervention targets. Conversely, physical activity is performed for a

much shorter duration after school. However, the physical activity undertaken

during the after-school period makes a large contribution to children’s daily

physical activity levels and this contribution increases over time. There is,

therefore, a strong rationale for interventions to target after-school physical

activity and sedentary behaviour levels from a young age.

Investigation into the correlates of children’s after-school physical activity and

sedentary behaviours is still in its infancy, but is required for intervention

development. Importantly, such correlates appear to be context-specific as where

the child is (i.e. after-school care, sporting clubs or other locations) and who they

are with (e.g. siblings) are important for participation in physical activity and

sedentary behaviour.

Participation in non-organised physical activity after school is a simple, low cost

and feasible intervention strategy that may result in increases in physical activity

and reductions in sedentary behaviour during this time. Further, physical activity

co-participation with siblings and attending a sporting club are also potential

intervention strategies that may increase children’s after-school physical activity;

however, these may require additional financial and logistical considerations.

Interventions targeting reductions in after-school sedentary behaviour may benefit

from ensuring appropriate facilities for children to be active are available. Future

longitudinal research using purpose-developed and context-specific survey items


163

would build on the evidence regarding correlates of children’s after-school

physical activity and sedentary behaviour produced from this thesis.

This thesis has highlighted that although the after-school period is one of several

periods of the day in which children can be active and sedentary, the period

provides a great opportunity for children and adolescents to accumulate their

physical activity, screen- and non-screen based sedentary behaviours.

Subsequently, the potential to target these behaviours through interventions is also

recognised. Interventions that are developed taking into consideration the

correlates identified as important for the promotion of after-school physical

activity and reductions in sedentary behaviour, may result in positive behaviour

change and therefore, benefit the current and future health of children and

adolescents.

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Appendices

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Appendices

Appendix 2.1: Authorship Statement: Paper One

Appendix 2.2: Authorship Statement: Paper Two


Appendix 3.2: Transform-Us! Deakin University Human Research Ethics Committee Approval



Appendix 3.5: CLAN Deakin University Human Research Ethics Committee Approval

Appendix 3.6: HEAPS Deakin University Human Research Ethics Committee Approval

Appendix 4.1: Authorship Statement: Paper Three

Appendix 5.1: Authorship Statement: Paper Four

Appendix 6.1: Authorship Statement: Paper Five

Appendix 6.2: Copywrite Permission: Paper Five

Appendix 7.1: Authorship Statement: Paper Six

Appendix .1: Authorship Statement: Paper One

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Appendix .2: Authorship Statement: Paper Two

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STUDY PROTOCOL Open Access

A cluster-randomized controlled trial to reducesedentary behavior and promote physical activityand health of 8-9 year olds: The Transform-Us!StudyJo Salmon1*, Lauren Arundell1, Clare Hume1, Helen Brown1, Kylie Hesketh1, David W Dunstan2, Robin M Daly1,Natalie Pearson3, Ester Cerin4, Marj Moodie5, Lauren Sheppard5, Kylie Ball1, Sarah Bagley1, Mai Chin A Paw6 andDavid Crawford1

Abstract

Background: Physical activity (PA) is associated with positive cardio-metabolic health and emerging evidencesuggests sedentary behavior (SB) may be detrimental to children’s health independent of PA. The primary aim ofthe Transform-Us! study is to determine whether an 18-month, behavioral and environmental intervention in theschool and family settings results in higher levels of PA and lower rates of SB among 8-9 year old childrencompared with usual practice (post-intervention and 12-months follow-up). The secondary aims are to determinethe independent and combined effects of PA and SB on children’s cardio-metabolic health risk factors; identify thefactors that mediate the success of the intervention; and determine whether the intervention is cost-effective.

Methods/design: A four-arm cluster-randomized controlled trial (RCT) with a 2 × 2 factorial design, with schools asthe unit of randomization. Twenty schools will be allocated to one of four intervention groups, sedentary behavior(SB-I), physical activity (PA-I), combined SB and PA (SB+PA-I) or current practice control (C), which will be evaluatedamong approximately 600 children aged 8-9 years in school year 3 living in Melbourne, Australia. All children inyear 3 at intervention schools in 2010 (8-9 years) will receive the intervention over an 18-month period with amaintenance ‘booster’ delivered in 2012 and children at all schools will be invited to participate in the evaluationassessments. To maximize the sample and to capture new students arriving at intervention and control schools,recruitment will be on-going up to the post-intervention time point. Primary outcomes are time spent sitting andin PA assessed via accelerometers and inclinometers and survey.

Discussion: To our knowledge, Transform-Us! is the first RCT to examine the effectiveness of intervention strategiesfor reducing children’s overall sedentary time, promoting PA and optimizing health outcomes. The integration ofconsistent strategies and messages to children from teachers and parents in both school and family settings is acritical component of this study, and if shown to be effective, may have a significant impact on educationalpolicies as well as on pedagogical and parenting practices.

Trial registration: ACTRN12609000715279; Current Controlled Trials ISRCTN83725066

* Correspondence: [email protected] for Physical Activity and Nutrition Research, Faculty of Health,Medicine, Nursing and Behavioral Sciences, Deakin University, Victoria,AustraliaFull list of author information is available at the end of the article

Salmon et al. BMC Public Health 2011, 11:759http://www.biomedcentral.com/1471-2458/11/759

© 2011 Salmon et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative CommonsAttribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction inany medium, provided the original work is properly cited.

BackgroundIn the past few decades, rates of overweight and obesityand related metabolic and cardiovascular risk factors inchildren have steadily increased worldwide [1-4]. Physi-cal activity plays an important role in the prevention ofmetabolic and cardiovascular health risk factors in chil-dren [5]. Increasingly, evidence suggests that sedentarybehaviors, such as prolonged periods of television view-ing, electronic games, and computer use (collectivelycalled screen-time) may adversely affect children’sweight status, independent of physical activity participa-tion [6,7]. While these screen behaviors are most com-monly performed during children’s leisure-time thereare many opportunities throughout the day for childrento be sedentary (e.g., being driven to school, sitting inclass, and sedentary homework). Further, while somelongitudinal evidence suggests that increases in the timechildren spend in sedentary behaviors seem to be off-setby corresponding decreases in physical activity duringthe primary school years [8], other studies have reportedindependent changes in these behaviors over time sug-gesting that they should be viewed as separate ratherthan converse constructs [9].There is emerging evidence that not just screen time,

but total sedentary time may be detrimental to chil-dren’s health. A cross-sectional study of 208 Portuguesechildren (mean age 9.8 years) found positive associationsbetween accelerometer-measured sedentary time(defined as < 500 Actigraph counts per minute [cpm])and insulin resistance, and inverse associations betweenmoderate- to vigorous-intensity physical activity(MVPA; ≥2, 000 cpm) and insulin resistance [10]. Astudy of 111 US children (aged 3-8 years), however,found no cross-sectional associations between timespent sedentary (< 100 cpm) and systolic or diastolicblood pressure (BP) [11]. Nevertheless, that studyreported that children in the highest tertile for proxy-reported television viewing time (approximately 155mins/day) were significantly more likely to have highersystolic and diastolic BP compared with children in thelowest tertile (approximately 8 mins/day).Observational evidence from studies among adults

suggests that the manner in which time spent sedentaryis accumulated may also be detrimental to health. Forexample, a cross-sectional study with 168 Australianadults (mean age 53 years) found that independent ofMVPA levels, those with less frequent interruptions toaccelerometer-measured sedentary time (≥100 cpm)with light-intensity physical activity had less favourablehealth profiles (waist circumference, body mass index,triglycerides, 2-hour plasma glucose) compared to thosewith more frequent interruptions [12]. Interestingly, theaverage duration of light-intensity breaks was less than

five minutes, suggesting that even brief interruptions totime spent sedentary may be beneficial to health. To ourknowledge, no observational or experimental studieshave examined the association of interruptions to seden-tary or sitting time and health in children, nor has therole of light-intensity physical activity and children’shealth been previously studied.While few intervention studies have examined the

effectiveness of strategies to reduce children’s overallsedentary time, several review papers have summarizedthe effectiveness of interventions to reduce children’sscreen time [6,13,14]. While this evidence suggests thesestrategies (delivered primarily through school-based cur-riculum), have positive effects on children’s weight andhave successfully reduced TV viewing, as noted earlier,there are many opportunities to be active throughoutthe day both at school and at home [15] and few if anyof these interventions to reduce children’s screen timehave resulted in corresponding increases in physicalactivity.Several studies have reported significant positive

effects on children’s physical activity in the school set-ting by targeting the school curriculum or throughchanges in the school environment [16-19]; however,few studies report on intervention effects on children’ssedentary time. A recent experimental study by Bendenet al. among children in four classes in Central Texasintroduced standing desks into classrooms and foundthat after 12 weeks all children were standing for 75% ofthe time [17]. However, the intervention only targetedenergy expenditure at school and did not incorporatestrategies to increase energy expenditure or reducesedentary behavior outside of school hours. A furtherchallenge with this type of intervention is whether theaim is to reduce children’s sedentary time, increase phy-sical activity or both. In a meta-analysis of interventionstudies that aimed to promote young people’s physicalactivity or reduce screen time, pooled effect sizes of 0.12and -0.29 respectively were reported [14]. The authorsconcluded that strategies to reduce sedentary behaviorappeared to be more effective than strategies to increasephysical activity. However, the efficacy of strategies toincrease physical activity and reduce sedentary behaviorseparately and in combination has not been examined.Ecological models suggest that settings-based

approaches may be an effective method for interveningwith children’s health behaviors [20,21]. Interventionsthat target places and contexts in which large numbersof children are sedentary or active are likely to have agreater public health impact than approaches thatinvolve one-on-one program delivery. In addition, animportant aspect in the development of effective andefficacious behavioral interventions is the use of a


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theoretical framework [22,23]. The use of behavioraltheory helps guide the development of strategies thatare most likely to result in changes in behavior throughtargeting the key mechanisms or mediating constructsof change [24,25]. Commonly employed theories in chil-dren’s physical activity and sedentary behavior interven-tion studies include: social cognitive theory [26]; theoryof planned behavior [27]; and behavioral choice theory[28]. A limitation of many of these theories is the focuson intrapersonal factors, which on the one hand areimportant for targeting change at the individual level,but are less useful when targeting changes at the popu-lation level. More recently, but less frequently, ecologicalmodels such as the social ecological model of healthpromotion [29] and the family-based ecological systemstheory [20] have also been employed in interventions topromote children’s physical activity with mixed success[30,31].Very few studies, even those that report use of beha-

vioral theory in the design of their intervention, examinethe mediators or mechanisms of behavior change. Sev-eral reviews of mediators of physical activity interven-tions in children and youth have identified keymediators to target including: self-efficacy; behavioralcapability; perceived social support; physical activityknowledge and beliefs; and enjoyment of or preferencefor physical activity [32-34]. Just two studies have exam-ined possible mediators of change in sedentary behaviorssuch as television viewing and computer use in youngpeople [35,36]. The DOiT study was an obesity preven-tion intervention based on the theory of planned beha-vior and habit strength theory [37] that aimed toimprove dietary and physical activity habits as well asreduce sedentary time of Dutch adolescents [35]. In thatstudy there were no mediating effects of attitude, subjec-tive norms (i.e. the degree to which an individual isinclined to agree with the expectation of other impor-tant persons’ opinions, normative beliefs), behavioralcontrol or habit strength on youth screen time. Basedon the self-determination theory [38] and the theory ofmeanings of behavior [39], the Get Moving! programwas a media-based intervention delivered via the schoolsetting that aimed to increase physical activity anddecrease sedentary behaviors in predominantly Latinomiddle school girls in California, USA [36]. The authorsfound a non-significant trend for a mediating effect ofintrinsic motivation to be physically active on televisionviewing time. No other mediating effects were observed.It is therefore important that intervention studies not

only target key mediators that lie on the behaviorchange pathway, but that these pathways are then testedstatistically. This will ensure a better understanding ofwhy an intervention worked or not and will furtherinform the utility of behavior change theories. Another

often-overlooked aspect of children’s health behaviorchange interventions is the economic cost of programdelivery. Not only is it important to test whether anintervention works and why, it is also critical that it iscost effective. Cost-effectiveness analysis combines effec-tiveness and cost data to show whether an interventionrepresents ‘value for money’, with results expressed asincremental cost-effectiveness ratios. A range of stan-dard methods are available to guide economic evaluationof an intervention program [40,41]. For example, theAssessing Cost Effectiveness (ACE)-Obesity study exam-ined the economic evaluation of thirteen interventionswhich targeted unhealthy weight gain in children andadolescents [42,43]. While the cost-effectiveness ofinterventions varied greatly, the most cost-effective stra-tegies included ‘Reduction of TV advertising of high fatand/or high sugar foods and drinks to children’, ‘Laparo-scopic adjustable gastric banding’ and the ‘multi-facetedschool-based programme with an active physical educa-tion component’[42]. Further research is required toidentify the cost-effectiveness of strategies to reducechildren’s sedentary behavior and promote physicalactivity in the school and home settings.This proposal builds on our program of research

[42,44,45] aimed at identifying effective and cost-effec-tive strategies that positively influence children’s healthbehavior and translate to improved health outcomes.This paper presents a summary of the Transform-Us!intervention including its aims, development, interven-tion methods and assessment protocols.

AimsThe primary aim of the Transform-Us! study is to deter-mine whether an 18-month, behavioral and environmen-tal intervention in the school and family settings resultsin higher levels of physical activity and lower rates ofsedentary behavior among 8-9 year old children com-pared with usual practice (post-intervention and 12-months follow-up). The secondary aims are to deter-mine the independent and combined effects of PA andSB on children’s cardio-metabolic health risk factors;identify the factors that mediate the success of the inter-vention; and determine whether the intervention is cost-effective.

Study Protocol OverviewTransform-Us! is a four-arm cluster randomized con-trolled trial with primary schools in Melbourne, Austra-lia being the unit of randomization. The interventionwill run for approximately 18 months (end of Term 2,2010 to end of Term 4, 2011), with a 12-month taperedmaintenance period in 2012. Transform-Us! is fundedby a National Health and Medical Research CouncilGrant (No.533815). Ethical approval was obtained from


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the Deakin University Human Research Ethics Commit-tee (EC 141-2009), the Victorian Department of Educa-tion and Early Childhood Development (2009_000344)and the Catholic Education Office (Project Number1545).

Methods/DesignStudy populationTwenty primary schools within a 50 km radius of Mel-bourne will be involved in Transform-Us!. All year 3children in the intervention schools will receive the pro-gram and all year 3 children in all schools will be invitedto participate in the evaluation of the intervention withthe aim to recruit 600 students. Due to significantincreases in sedentary behaviors and declines in physicalactivity among children in primary school, 8-9 year oldswere considered a key target population. In addition, forpractical purposes a three-year study implemented inyear 3 would ensure children remained at primaryschool throughout the entire study ensuring ease of fol-low-up.

Recruitment of schoolsSchool principals will be contacted via fax or email andinvited to participate in the Transform-Us! study. Allinterested principals (and teachers if in attendance) willbe given a detailed presentation outlining the programand required commitment. Principals who agree to par-ticipate in the study will then be provided with a plainlanguage statement and consent form to be signed andreturned prior to participation. As the Transform-Us!program will involve modification to the delivery of theschool curriculum, approval from the school council/board will also be required.

Recruitment of participantsAll year 3 children in eligible schools will be providedwith an information pack for their parents or carers/guardians (hereafter referred to as parents) containing aplain language statement and consent form for the par-ents’ and child’s participation. As the school will haveconsented to the program being delivered to all year 3children and parents, consent will only be required forthe evaluation components. Parents will be able tonominate which assessment components they give con-sent for their child to participate in (i.e., accelerometer,inclinometer, anthropometry, survey, blood pressureand/or blood sample, or all components). At baseline,all year 3 teachers will be provided with an informationpack containing a plain language statement and consentform to be signed and returned prior to participation inthe evaluation assessments. To maximize the sampleand to capture new students arriving at interventionschools, recruitment will be on-going up to the post-

intervention time point. The schools, teachers and parti-cipants will not be paid to participate in Transform-Us!.

Sample size calculationsIt is expected that the intervention effects on behavioraland biological primary outcomes will be moderate insize (standardized difference ~ 0.32, equivalent to amean change in objectively-measured PA of 8 minutesper day [SD = 18 min] and a change in body massindex (BMI) units (age-sex difference from populationnorm data) of 1.9 kg/m2 [SD = 0.25]) [25,46]. Withoutaccounting for school cluster effects, the number of par-ticipants needed to detect a standardized difference of0.32 with 0.8 power for sedentary behavior (SB-I) andphysical activity (PA-I) alone and in combination (SB+PA-I), using a significance level of 0.05 with a two-tailed test, assuming a retention rate of 91% (based onthe team’s previous experience) and 20 participatingschools, would be 340 in total (17 per school). With apreviously observed school clustering effect of 0.018(intra-class correlations [ICCs] for sedentary behavior,physical activity and BMI outcomes estimated usingdata from a previous intervention study)[44], the mini-mal total number of participants needed is 520, i.e., 26per school. Hence, we will conservatively recruit 30 par-ticipants per school, giving a total sample size of 600participants.Moderate mediated effects of the intervention on the

behavioral outcomes are expected (here a moderatemediated effect size is defined as standardized regressioncoefficients a and b of ~ 0.39)[47]. According to a 2007simulation study by Fritz and MacKinnon [48], to detecta moderate mediated effect size with 0.8 power, using asignificance level of 0.05 with a two-tailed test and bias-corrected bootstrap methods, ~ 61 independent observa-tions are needed. If we assume a 9% rate of loss to fol-low-up, an average school cluster effect of 0.03 for themediators (ICCs estimated using data from a previousintervention study)[44] and an average of 30 observa-tions per school (see above), the sample size needed todetect a moderate mediated effect size would be 100 (20per school). Hence, the sample size needed to detectmoderate intervention effect sizes with 0.8 power for theprimary outcomes (n = 600) will also be sufficient todetect a moderate-sized effect with 0.8 power for themediating variables.

RandomizationA listing of Melbourne suburban primary schools (n =367), their enrolment number and associated suburbsocioeconomic index for areas (SEIFA) score (suburbdisadvantage score) will be obtained. Schools with anenrolment of over 300 students will be grouped in quin-tiles of SEIFA score and schools from the first, third


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and fifth quintiles will be selected to represent low, midand high SEIFA strata respectively. Schools in each stra-tum will be randomly ordered with probabilistic weight-ing according to enrolment number, and will beapproached consecutively and offered participation.Schools will then be randomly allocated to either SB-I,PA-I, SB+PA-I or current practice control (C).

InterventionDevelopment and Pilot PhaseA previous research-to-practice study (Switch-2-Activ-ity) demonstrated the feasibility of teachers deliveringmaterials targeting the promotion of children’s physicalactivity and reductions in screen time [49]. For the cur-rent study, seven teachers, including a vice-principal,were interviewed regarding the feasibility of introducingregular classroom standing breaks. Short breaks wereconsidered feasible with consistent feedback regardingthe duration; anything longer than 2-minutes wasviewed as being unlikely to be adopted by teachers. Asubsequent pilot study to assess the feasibility and effec-tiveness of regular 2-minute classroom breaks found a20-minute decline in children’s objectively measuredsedentary time during class and a corresponding 20-minute increase in moderate- to vigorous-intensity phy-sical activity [50]. All class-based components of Trans-form-Us! were developed by the investigators with inputfrom current and previous primary schools and

representatives of the Victorian Department of Educa-tion and Early Childhood Development.

Theoretical basis of Transform-Us!Physical activity interventions that base their strategieson behavioral theories are more likely to be effectivethan atheoretical approaches [51]. Table 1 shows themediators that will be targeted in Transform-Us!. Thesemediators are based on elements of the behavioral the-ories that have previously been shown to be effective inencouraging behavior change in children’s physicalactivity and sedentary behavior [44,51-54] including:social cognitive theory [26]; behavioral choice theory[28] and ecological systems theory [20]. These theoriesrecognize that there are multiple levels of influence onhealth behavior including intrapersonal (e.g., awareness,self-efficacy, enjoyment), interpersonal (e.g., parents, sib-lings, peers, teachers), physical environmental (e.g., tele-vision in child’s bedroom, access to parks/playgrounds),and policy influences (e.g., school physical activity poli-cies and timetables). As previous research has shownconsistent sex differences in physical activity [55] and insome sedentary behaviors (particularly computer useand playing electronic games [56-58]) and sex was a sig-nificant moderator in the Switch-Play study [44] theintervention will be tailored for boys and girls whereverpossible. See Table 2 for a summary of the interventionstrategies.

Table 1 Theoretical* basis of the Transform-Us! intervention and links to program objectives

Constructs Mediators ordeterminants

Program Objectives

Intrapersonal

Confidence Self-efficacy Improve confidence in ability to be active or reduce sedentary time

Preference Enjoyment Increase enjoyment and preference for physical activity

Expectations Benefits/barriers Increase knowledge of benefits & strategies to overcome barriers

Expectancies Evaluation of anticipatedoutcome

Alter perception of pros and cons of being more active

Skills Self-management Self-rewards, self instructions, TV viewing styles

Behavioralrehearsal

Self-monitoring &contracting

Goal setting, contracting with others, rewards

Interpersonal

Observationallearning

Modelling by parents/siblings

Encourage parents & siblings to reduce their own SB & increase PA

Social support Modelling/social support Encourage parents & siblings to support child to spend less time in SB & more time in PA; teachersencourage/support PA during recess/lunch

Social structure Rules Parents enforce rules regarding limiting screen time at home, during meals, during daylight hours

Environmental

Imposedenvironment

Availability Increase the amount of PA equipment available at school & home. Reduce the availability of TVs/computers/electronic games at home

Imposedenvironment

Access Increase access/opportunities for PA at school & at home. Decrease access to TV/computers/electronicgames at home

Imposedenvironment

Policy Interrupted sitting during class-time; presence of supervising teachers during recess/lunch

* Based on social cognitive theory [26], behavioral choice theory [28], ecological systems theory [20]


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Sedentary behavior intervention arm (SB-I)Reducing uninterrupted time spent sitting during schoolhours will be aimed for in the school setting; and redu-cing overall sitting time and discretionary screen-basedbehaviors (i.e., television viewing, computer use andelectronic games) will be aimed for in the family setting.In addition, key mediators of sedentary behavior changewill be targeted (Table 1).

School settingCurriculum-based key learning messagesKey learning messages will be adapted from Switch-Playmaterials incorporating key principles of behaviorchange and delivered by classroom teachers in 18 les-sons (9 lessons per year). Teachers will be provided withcomplete lesson plans but encouraged to modify thematerials to suit their class and teaching style. The sec-ond year of the intervention will reinforce and enhancethe lessons from the first year. Key messages will focuson raising awareness; self-monitoring; goal setting; beha-vioral contracts; social support (team-based activities atschool; homework to do with parents); and feedbackand reinforcement (external and intrinsic rewards). Alllessons are developed in line with the Victorian EssentialLearning Standards for year levels 3 and 4. Furthermore,children will be encouraged to meet the national recom-mendations for young people of less than two hours perday in electronic entertainment media [59].Interrupting classroom sitting timeTeachers will modify the delivery of one class lesson perday (~30 minutes) so that children will complete thelesson standing up. Teachers will be provided with asuite of standing lesson delivery methods that can bemodified to any class topic (e.g., ‘Stations around theroom’ shown in Appendix 1). If administered asintended, this should result in approximately 150-

minutes less sitting time per week. In addition, everytwo-hour classroom teaching block will be interruptedevery 30 minutes with a 2-minute guided light-intensityactivity break (e.g., ‘Bean-bag Spelling/counting’ shownin Appendix 2). This will equate to a total of six min-utes interrupted sitting time every two hours. On aver-age, schools in Victoria have two 2-hour teaching blocksper day so this should result in up to 60-minutes lesssitting time per week. Teachers will be provided with amenu of activities to deliver during the 2-minute breaks.Environmental cues and promptsEach class will be provided with several standing easelsso that children can rotate learning activities at ‘standingstations’. In addition, a novelty timer will be given toeach class so that teachers can monitor 2-minute stand-ing breaks and every 30-minutes of sitting class time.

Family settingNewslettersNine newsletters per year (18 in total) will be sent hometo parents providing project updates and tips on redu-cing their child’s sedentary behaviors. The newsletterswill support the key learning messages delivered to thechildren in the classroom and will help parents reinforcemaintaining children’s screen-time to a minimum. Theywill be translated into the most common languages spo-ken among the families with non-English speaking back-grounds. Newsletters will incorporate family basedactivities for parents to complete with their child andcontain information about ways to reduce their child’sscreen time, including the effective use of rules (i.e., notelevision viewing during mealtimes, restrictions onsmall screen use, etc.).Homework assignmentsHomework tasks will be modified to reduce sitting timewhile completing them at home (e.g., complete

Table 2 Transform-Us! intervention components

SB-I PA-I SB+PA-I

School setting

Curriculumcomponent

• 18 key learning messages (9 peryear)

• 18 key learning messages (9 per year) • 18 key learning messages (9 per year)

Class strategies • Standing lessons (1 × 30-min/day)• Active 2- min breaks after 30-minclass time

NA • Standing lessons (1 × 30-min/day)• Active 2- min breaks after 30-min class time

Physicalenvironment

• Standing easels• Novelty timer

• Provision of sporting equipment, linemarkings and signage• Provision of pedometers

• Standing easels• Provision of sporting equipment, linemarkings and signage• Provision of pedometers

Family setting

Homework tasks • Reduce sitting time whilecompleting home work

• Homework tasks incorporate PA • Homework tasks incorporate PA andreductions in sitting time

Newsletters • Tips for reducing sitting time athome

• Tips for increasing PA at home • Tips to reduce sitting time and promote PAat home

PA: physical activity; SB: sedentary behavior; PA-I: physical activity intervention; SB-I: sedentary behavior intervention


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worksheets while standing at the kitchen bench). Chil-dren will also be given homework tasks to completewith their parents; for example, to switch off the televi-sion for a whole weekend day and do something withtheir parents (a menu of alternative light-intensity activ-ities will be provided).

Physical activity intervention arm (PA-I)Increasing or maintaining moderate- to vigorous-inten-sity physical activity (e.g., active play, organized andnon-organized games) during recess and lunch breakswill be targeted in the school setting and time spentoutdoors will be targeted in the family setting. The keymediators of change in physical activity will also be tar-geted (shown in Table 1).

School settingCurriculum-based programAs for SB-I, 18 key learning messages (9 lessons peryear) modified from Switch-Play [44] but focusing onincreasing physical activity will be delivered by teachers.Children will be encouraged to meet the national physi-cal activity recommendations for young people of 60-minutes of moderate- to vigorous-intensity physicalactivity every day. All lessons will be developed in linewith the Victorian Essential Learning Standards for yearlevels 3 and 4.Physical activity during recess and lunch breaksPhysical activity will be promoted and encouraged dur-ing recess and lunch breaks. Based on previously effica-cious intervention strategies promoting physical activityduring recess and lunch breaks [60], schools will be pro-vided with sports equipment to make available for chil-dren to use in recess and lunch breaks, and teachersand peers will provide encouragement and support foractive games.Environmental cues and promptsSignage will be used to promote physical activity inschools and will be regularly updated. Consistent withpreviously successful interventions [61], schools willselect and receive novel line markings promoting activeplay in asphalt areas in the school playground. Eachclass will be provided with a set of pedometers for useduring the key learning messages based on physicalactivity capability. Furthermore, the pedometers can berotated throughout the class for children to gain aware-ness of their steps in different environments (e.g. week-day, weekend, school camp).

Family settingNewslettersEighteen newsletters (nine per year) will be sent hometo parents providing project updates and tips on pro-moting their child’s physical activity. The newsletters

will support the key learning messages delivered to thechildren in the classroom and will help parents reinforcephysical activity promotion at home. They will be trans-lated into the most common languages spoken amongthe families with non-English speaking backgrounds.Newsletters will incorporate family-based activities forparents to complete with their child. For example, news-letters will contain information about activities to do athome and in their neighborhood (suitable for boys andgirls). Parents will also be directed to the Kinect Austra-lia website http://www.kinectaustralia.org.au/content/Public/Homepage.aspx and free Infoline, both of whichcontain information for parents on ways to engage theirchild in physical activity at home, ways to be active withtheir child, as well as identifying specific places in theirown neighborhood where they can take their child toplay (e.g., playgrounds, walking trails, local sports clubs).Homework assignmentsHomework tasks will be modified to incorporate physi-cal activity and children will be encouraged to completethese tasks with their parents (e.g., go for a walk withtheir parents and write about where they went and whatthey saw; mathematics homework using their stride asthe unit of measurement).

Combined sedentary behavior and physical activityintervention arm (SB+PA-I)Schools randomized to the combined SB+PA-I interven-tion arm will receive a blended version of the two inter-ventions, but with the same intervention ‘dose’. Forexample, when children in this arm complete a beha-vioral contract to switch off the television, they will beencouraged to participate in physical activity (SB-I chil-dren will not be directly encouraged to participate inactivity when they switch off their television). The com-bined intervention arm will include 18 class lessons (9per year), standing lessons and interruptions to chil-dren’s classroom sitting time (short breaks), the promo-tion of physical activity during recess and lunch breaks,and 18 newsletters to parents.

Control - usual practiceSchools assigned to the usual practice control group willbe asked to continue their usual lesson delivery and willreceive all intervention materials (apart from line mark-ings) at the completion of the 12-month follow-upperiod

Teacher trainingIn the first year of the intervention (2010), all participat-ing year 3 teachers at intervention schools will berequired to attend a professional development (PD) ses-sion. In the second year of the intervention (2011), allyear 4 teachers will undergo the same training. There


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may be some teachers who teach both years of theintervention, or the second year may contain new tea-chers who have not been previously involved in thedelivery of the intervention. The PD session will run forapproximately two hours and will inform and/or refreshthe teachers about the intervention including the aims,procedures of the study and strategies to be used. Amid-year morning tea meeting will be held with teachersto ensure that they are delivering the intervention asintended and to answer any questions or solve any diffi-culties they may be experiencing in intervention deliv-ery. At the beginning of the third year (2012), all year 5teachers at the intervention schools will be trained intheir specific intervention components but will have nofurther contact or support from the study team through-out the year. This tapered approach will enable themaintenance of the strategies to be examined.

Measurement protocolAssessments will be conducted at baseline (Feb-May2010), mid-intervention (Nov-Dec 2010), post-interven-tion (Nov-Dec 2011), and 12-months follow-up (Nov-Dec 2012). To minimize participant burden, blood pres-sure assessments will be taken at baseline, post-interven-tion and 12-months follow-up only, and blood sampleswill be taken at baseline and post-intervention only. Allof the children’s measurements (except the blood sam-ples) will be conducted at school by trained researchstaff using regularly calibrated equipment. Children willcomplete the survey in small groups with trainedresearch staff. The blood sample will be undertaken at acommercial pathology laboratory by a trained phleboto-mist and the parent survey will be sent home to parentsto complete.

Primary outcomesSedentary time and physical activityActiGraph accelerometer Sedentary time and physicalactivity will be objectively-assessed using the uniaxialfunction in the ActiGraph Model GT3X accelerometershttp://www.theactigraph.com/. Children will wear theActiGraph on a belt positioned over the right hip duringwaking hours (apart from during water-based activities)for eight days at each of the measurement points. Datawill be collected in 15-second epochs. The movementcount threshold for sedentary time will be set at 25counts per 15-second epoch [62], and the number ofbreaks or interruptions to time spent sedentary will bedefined as the frequency of occasions data exceeded 100counts.min-1. The Freedson age-adjusted equation [63],will be applied to calculate the time spent in light (1.7-3.9 METS), moderate- (4.0-5.9 METs) and vigorous-intensity (≥6.0 METs) physical activity. We will alsoextract accelerometry data from specific times of the

day (e.g., after-school hours, during class time) to iden-tify when changes in sedentary time or physical activitymay have occurred.activPAL™ inclinometer A sub-sample of randomlyselected children will concurrently wear a PAL Technol-ogies Ltd, Glasgow, Scotland http://www.paltech.plus.com/products.htm inclinometer activPAL™. The activ-PAL™ is a small device (5 × 3.5 × 0.7 cm) weighing 20g and is worn on a garter belt positioned at the mid-anterior aspect of the right thigh during waking hours(apart from water-based activities) for eight days at eachof the measurement points. The following parameterswill be calculated from this device: sedentary time (sit-ting/lying time); stand time (not walking); walk time;and sit-to-stand events. The device has been found tohave acceptable validity in assessing these parameters inadults [64,65].ActiGraph and activPAL™ data validity criteria will be

assessed prior to inclusion in analysis. A minimum offour valid days, including one weekend day will berequired. To be included in analyses, a day will be con-sidered valid if the child has at least eight hours of weartime per day or at least 50% wear time within periods ofthe day (e.g., classtime). Further, 20 minutes of consecu-tive zeros will be considered non-wear time. Recordingsof over 16000 counts per minute (cpm) will be excludedas it indicates unit malfunction.Survey measures Behavioral information on the types ofphysical activities and sedentary behaviors in which chil-dren participate (not detectable by accelerometry orinclinometers) will be collected by a parental proxy-report version of the validated CLASS questionnaire[66]. Time spent outdoors will be assessed using a pre-viously validated proxy-report measure [67].

Secondary outcomesAnthropometry: height, weight and waist circumferenceHeight will be measured to the nearest 0.1 cm usingSECA portable stadiometers (mod 220). Weight will bemeasured to the nearest 0.1 kg using portable electronicWedderburn Tanita scales. Two height and weight mea-surements will be taken and the average calculated.Where a discrepancy of over 1 cm or 1 kg is noted, athird measurement will be taken.BMI (kg/m2) will be calculated and converted as

recommended for analysis of longitudinal adiposity data[68]. This involves subtracting the sex-age populationmedian (based on US data)[69] from the child’s rawBMI score. Children will also be categorized as healthyweight or overweight/obese based on International Obe-sity Task Force definitions [70].Waist circumference will be measured using a flexible

steel tape at the narrowest point between the bottomrib and the iliac crest, in the midaxillary plane. If there


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is no obvious narrowing the mid-point between thesetwo landmarks will be used [71]. Two waist circumfer-ence measurements will be taken and the average calcu-lated. Where a discrepancy of over 1 cm is noted, athird measurement will be taken. Continuous data willbe compared to UK charts [72]. Sex and age-specificwaist circumference thresholds for children that corre-spond to clustering of cardiovascular disease risk factorswill also be applied [71].Blood pressureAfter a quiet two-minute seated rest, children will havetheir blood pressure measured on their right arm usingthe OMRON HEM-907 automatic digital blood pressuremachine. Three measurements will be taken one-minuteapart on two occasions (one week apart). The first mea-surement on each occasion will be discarded. Theremaining four measurements will be averaged to obtainsystolic and diastolic blood pressure measurements.Serum BiomarkersA fasted, morning blood sample (16.5 ml) will be takenby a phlebotomist at a commercial pathology laboratoryto assess children’s cholesterol, high density lipoprotein(HDL) cholesterol, low density lipoprotein (LDL) choles-terol, triglycerides, glucose, insulin, C-reactive proteinand 25-Hydroxy Vitamin D levels. Biomarkers will betaken at baseline and post-intervention data collectionpoints only.Survey measuresMediators Intrapersonal, interpersonal and environ-mental mediators of children’s sedentary behaviors andphysical activity will be assessed by parental proxy-report and child self-report survey (Table 1). Intraper-sonal mediators include: self-efficacy; enjoyment andpreference; sports competency; TV viewing style (e.g.,channel surfing, selective viewing); benefits and bar-riers; and beliefs. Interpersonal mediators include:social norms; rules; social support in the neighbor-hood, at school, and at home; and parental modelling.Environmental mediators include: perceptions of theschool environment; access and availability; and policy.These measures have been previously developed andhave acceptable psychometric properties and predictivevalidity [52,56-58,73-78].Moderators Although not powered to conduct moderat-ing analyses, exploratory analyses will examine moderat-ing effects of sex of the child, parental country of birth,and parental education attainment.ConfoundersSociodemographic characteristicsChild’s age and sex, family structure (e.g., siblings, num-ber people living in household), parents’ age, sex, maritalstatus, education attainment, postcode, and country ofbirth will be collected in the parent survey. Childrenwill report the number of working cars their family has,

the number of holidays they went on in the last yearand if they have their own bedroom to assess sociode-mographic position [79].General health and family historyThe responding parent will report the general healthstatus of their child, and the medical history and familyrisk factors for diabetes and cardiovascular disease riskfactors and their own height and weight.Nutritional intakeParent proxy-report food/drink frequency questionsderived from food items previously identified from theNational Nutrition Survey for the target age groups (8-12 years) as important contributors to energy and fatintakes, and thus the energy density of the diet, will beincluded (items include sweet and savoury snacks andhigh energy drinks) [80]. Literature supports the accu-racy of parent reports of usual food intakes [81].Stage of pubertal maturationSince all children will be aged 8-9 years old at baseline,it is expected that they will all be pre-pubertal and thusthe assessment of pubertal status is not considerednecessary. However, to account for any potential growth(maturity) effects, growth rates (change in height) willbe assessed from the height measurements taken at eachassessment time point.

Economic EvaluationAn economic evaluation will be undertaken to deter-mine whether Transform-Us! is cost-effective. A societalperspective will be adopted, such that all costs and out-comes will be identified and valued regardless of whobears the cost, receives the benefits or provides theresources [82,83]. Three methods for collecting resourceuse data will be applied: a diary will be given to teachersto capture any extra preparation time or equipmentneeded to implement the intervention strategies; anitem on the parent survey will capture how much timefamily members participate in completing school home-work tasks; and project monitoring processes will beused to capture other resources used that are pertinentto implementation. Diaries will be completed each dayfor four weeks throughout the intervention period andat follow-up.

Process EvaluationThroughout the intervention (2010 and 2011), the pro-ject team will maintain regular contact with teachers.We will monitor the intervention delivery quantity (howmany children participated in the various lessons) andquality (that the intervention was delivered as it wasintended and any modifications to provided materials)throughout the intervention (teachers to record and ratelessons delivered, sections of class lessons completedwith children, number of children present, engagement


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of the children). In addition to annual interviews withkey personnel in the school (e.g., teachers, co-ordina-tors), we will make unannounced visits to schools toensure that the teachers understand the interventiondelivery requirements, to solve any difficulties or con-cerns, and to ensure that they are delivering the inter-vention as intended.Subjective evaluations of intervention components will

also be provided by children, parents and teachersthroughout the intervention. At the mid- and post-inter-vention assessments, teachers will be asked to report onthe lesson delivery (e.g., did you deliver the key learningmessages, ease with which they were embedded in cur-rent curriculum, ease of delivery) and school-basedstrategy implementation (e.g., were you successful ingetting students to complete standing lessons? Was thesporting equipment made available at recess/lunch-times?). At the post-intervention assessments, teacherswho were involved in year one, but not year two, of theintervention will be asked about their continuation ofany of the strategies. At the 12-month follow-up assess-ments, all teachers who have been involved in the SB-Ior SB+PA-I intervention in year one and/or year twowill be asked to complete a survey to examine mainte-nance of the class based strategies (i.e., are you still con-ducting standing lessons?). The uptake of theintervention by teachers not previously involved in yearone or two will also be determined.At the mid- and post-intervention assessments, all

participating children will be asked to describe whatthey know about Transform-Us!. Children in the threeintervention groups will be asked to rate how they feelabout the school-based components specific to theirintervention group (e.g., standing while completingwork, availability of sports equipment at recess/lunch-times); and the home-based components specific totheir intervention group (e.g., standing homework tasks,active family pastimes). At the mid- and post-interven-tion assessments, parents will be asked about the news-letters (e.g., number received, usefulness and their use ofstrategies to change their child’s behavior containedwithin the newsletters).

Data analysisAll statistical analyses will be performed using Stata 9.1for Windows (StataCorp LP) and will adjust for cluster-ing by observations by school (the unit of randomiza-tion). All analyses will be conducted using the intentionto treat principle. Generalized Estimating Equations(GEE) [84] will be used to fit regression models todescribe the effects of the intervention on key outcomevariables among children. Separate models will be fittedto determine differences in key outcome variables in theintervention and control groups.

Separate models will be evaluated for each assessmentpoint (mid-intervention; post-intervention; 12 monthsfollow-up), adjusting for baseline levels of the outcome,and, where appropriate, baseline levels of the mediatingvariables. PA-I and SB-I intervention conditions will bethe predictors of primary interest (entered in the formof two indicator variables and their interaction term).Analyses will be performed excluding and includingchildren who were recruited to the study after baseline.For physical activity outcomes, we will compare the PA-I and SB+PA-I versus the SB-I and C groups. For seden-tary behavior outcomes, we will compare SB-I and SB+PA-I versus the PA-I and C groups. For health out-comes, we will compare C versus the other three groupsand the SB+PA-I versus the single intervention groups.All models will be adjusted for measured confounders.As it has been argued that adjustment for multiple com-parisons should not be used when assessing evidenceabout specific hypotheses no adjustment for multiplecomparisons will be performed [85]. To evaluate themagnitude and direction of the intervention effectsmediated by intrapersonal, interpersonal and environ-mental processes, the product-of-coefficient method willbe used [86]. A first set of GEE regression models willassess the impact of the intervention condition (regres-sion coefficient a) on the residualized change score ofthe hypothesized mediators (Table 1), after controllingfor significant covariates. A second set of GEE regres-sion models will estimate the independent effects of theintervention condition and residualized changes in themediators (regression coefficient b) on changes in theoutcome variables. The significance of the product ofthe regression coefficients a and b (representing themediated effect of the intervention) will be tested usingbias-corrected bootstrap methods as outlined by Pituchand colleagues [87].For the economic evaluation, pathway analysis will be

used to identify component activities of the interventionin order to ascertain the associated resource utilization.The cost-effectiveness analysis will measure differentialcosts between the three intervention groups and C inrelation to the outcomes, and intervention costs will beassessed as additional expenditure (savings) against C,expressed as an incremental cost-effectiveness ratio.Incremental cost-effectiveness ratios will be calculatedas the cost AUD per BMI unit ‘saved’ and Disability-Adjusted Life Years (DALYs) ‘saved’. The interventionwill be modelled for one year as if applied to the Victor-ian population of children in the target group. The timehorizon for measuring the associated health-care cost-offsets and DALY benefits will be the rest of life or 100years. The reference year will be 2010. The interventionswill be run through a model, developed as a part of theACE-Obesity study, which converts BMI changes to


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DALY benefits and cost-offsets saved over the lifetimeof the cohort [88]. The ACE-Obesity methodology willguide the evaluation to allow cost-effectiveness resultsto be directly comparable to those of the 13 interven-tions previously evaluated [89].

DiscussionSedentary behavior and physical activity may have inde-pendent detrimental and positive effects (respectively) onchildren’s cardio-metabolic health. Very few interven-tions have targeted reductions in children’s total sittingtime in the school and family settings. Even fewer inter-ventions have examined the separate and combinedeffects of targeting reductions in sedentary behavior andincreases in physical activity and only two have usedobjective measures. This 18-month intervention with 12-month tapered maintenance period is unique in itsapproach to delivery of school curriculum and homeworkin less sedentary and more active ways. As the key agentsof change in children’s health behaviors, involvement ofteachers and parents is critical. If shown to be successfuland cost-effective this intervention may have implicationsfor educational policy and practice, and ultimately thehealth of young children in Australia and elsewhere.

Appendix 1’Road trip/Stations around the room’ standing lessonstrategy

AimTo complete small group activities related to a specificarea of study, by physically moving between stationslocated around the room.

OutlineThe lesson is planned as a series of activities, placed atstations around the classroom. Children are organisedinto groups (allocated by the teacher). Groups spend adesignated period of time at each station completing theactivity, before moving onto the next station. All chil-dren must remain standing at each station as activitiesare designed to be easily performed standing (e.g.through use of high benches or clipboards; by keepingwritten work relatively minimal; by telling children totake turns at being ‘scribe’ etc).Teachers can specify the group structure (number of

children, how groups are selected), the number of sta-tions, amount of time spent at each station and theassociated activities.

Examples- Fill in worksheets- Leave your group’s answer on a pile at the station

- Keep a journal of all of the activities (write sen-tences or draw pictures)- Write responses on large sheets of paper/whiteboards

Suggestions for stations• English: One chapter/event from a story at each sta-tion including comprehension questions.• L.O.T.E.: Match up word-cards and picture-cards;

sentences on large posters or interactive whiteboardswith blank spaces for children to fill with the correctword (offer lists of choices).Culturally relevant creative activities, such as origami.• Maths: Set of addition, multiplication or simple divi-

sion problems - one series per station.Spatial tasks - fitting shapes into defined spaces

(puzzles).Problem-solving activities +/- problems- Example:

“You have a bucket with 150 mL of water, a 40 mL jarand a 50 mL jar. How will you use these to measure out30 mL of water into this pot?” (If possible, supply thewater and jars at the station, so the children can physi-cally do the task).Fractions tasks - each station based around a different

theme- Example: different ways to express ‘1/2’ (50%,0.5, 2/4, 3/6). Include props, such as blocks or colouredpaper cut into a number of fractions.•Humanities: Historical events. These could be read-

and-comprehend tasks- Example: “In which year didCaptain Cook discover Australia? Describe his landing.”•Creative task: “Imagine you are living in Antarctica,

draw some of the clothes you would need to wear tokeep warm.”

Options•At the end of the lesson, the children can cometogether and the teacher can lead a discussion of theirwork; or groups can exchange work for correction.

Equipment/preparation required✓Activities for each station (copies/laminated cards ofreading passages, math problems, props for problem-sol-ving activities etc)✓Pens/pencils and paper/workbooks (for children to

record answers at each station)✓ (optional) One clipboard per group/per child✓ (optional) Worksheets for each station (if these are

to be completed)

Appendix 2’Road trip/Stations around the room’ standing lessonstrategy


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AimsTo practice spelling or simple number patterns verballywhile standing and passing a bean-bag.

OutlineThe children are asked to stand and the teacher nomi-nates a number series or a set of words, relevant to thecurrent lesson. The teacher gives a bean-bag to one stu-dent, who states the first number in the pattern or letterin the word. That child then throws the bean-bag toanother child, who says the next number/letter thenpasses the bean-bag on, and so on.All children remain standing throughout the game,

but once a child has passed the bean-bag, they mustchange their posture/position to signify that they havehad their turn.

Equipment/preparation required✓Bean-bag (provided) or newspaper balls to throw✓ (optional) Spelling-list on the board

AcknowledgementsThis study is supported by a National Health and Medical Research Council(NHMRC) Project Grant (2009-2013; ID533815) and a Diabetes AustraliaResearch Trust (DART) grant. The funding bodies played no role in the studydesign; data collection, analysis, and interpretation; in the writing of themanuscript; or in the decision to submit the manuscript for publication. JSand KH are supported by National Heart Foundation of Australia (NHFA)Career Development Awards; CH is supported by a NHFA Post-DoctoralResearch Fellowship; RD is supported by a NHMRC Career DevelopmentAward (ID425849); DD is supported by an Australian Research Council FutureFellowship; KB is supported by a NHMRC Senior Research Fellowship(ID479513); DC is supported by a Victorian Health Promotion FoundationSenior Research Fellowship; and SB is supported by a NHFA Post-GraduateScholarship.

Author details1Centre for Physical Activity and Nutrition Research, Faculty of Health,Medicine, Nursing and Behavioral Sciences, Deakin University, Victoria,Australia. 2Baker IDI Heart and Diabetes Institute, Melbourne, Victoria,Australia. 3School of Sport, Exercise and Health Sciences, LoughboroughUniversity, UK. 4Institute of Human Performance, The University of HongKong, Hong Kong, Hong Kong SAR. 5Deakin Health Economics, Faculty ofHealth, Medicine, Nursing and Behavioral Sciences, Deakin University,Victoria, Australia. 6Department of Public and Occupational Health, EMGOInstitute for Health and Care Research, VU University Medical Center,Amsterdam, The Netherlands.

Authors’ contributionsJS took the lead in designing the study subsequently funded by a NationalHealth and Medical Research Council Project Grant and in writing thismanuscript.LA contributed to drafts of this manuscript and coordinated comments fromco-authors.

MM and LS wrote the sections related to the economic evaluation protocol.CH, KH, RD, DD, EC, NP, HB, KB, DC provided expert input and supportoverall for the writing of this manuscript with particular emphasis on design,measures of physical activity and statistical analyses.All authors read and approved the final manuscript.


Received: 4 August 2011 Accepted: 4 October 2011Published: 4 October 2011

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Teachers can specify

Subject of game (examples): The actions performed by children before/after their turns (examples):

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39. Spruijt-Metz D: Adolescence, affect and health London: Psychology Press;1999.

40. Gold MRSJ, Russell LB, Weinstein MC: Cost-effectiveness in health andmedicine New York: Oxford University Press; 1996.

41. Drummond MF, Sculpher MJ, Torrance GW, O’Brien BJ, Stoddart GL:Methods for the economic evaluation of health care programmes Oxford:Oxford University Press; 2005.

42. Haby MM, Vos T, Carter R, Moodie M, Markwick A, Magnus A, Tay-Teo K-S,Swinburn B: A new approach to assessing the health benefit fromobesity interventions in children and adolescents: The Assessing Cost-Effectiveness in Obesity project. Int J Obes 2006, 30:1463-75.

43. Moodie ML, Carter RC, Swinburn BA, Haby MM: The cost-effectiveness ofAustralia’s active after-school communities program. Obesity 2010,18:1585-1592.

44. Salmon J, Ball K, Hume C, Booth M, Crawford D: Outcomes of a group-randomized trial to prevent excess weight gain, reduce screenbehaviours and promote physical activity in 10-year-old children:Switch-play. Int J Obes 2008, 32:601-612.

45. Salmon J, Ball K, Crawford D, Booth M, Telford A, Hume C, Jolley D,Worsley A: Reducing sedentary behaviour and increasing physicalactivity among 10-year-old children: Overview and process evaluation ofthe ‘Switch-Play’ intervention. Health Promot Int 2004, 19:1-11.

46. Manios Y, Kafatos A, Preventive Med Nutr Clinic Univ C: Health andnutrition education in primary schools in Crete: 10 years’ follow-up ofserum lipids, physical activity and macronutrient intake. Br J Nutr 2006,95:568-575.

47. Cohen J: Statistical power analysis for the behavioral sciences. 2 edition.Hilldale, NJ: Erlbaum; 1988.

48. Fritz MS, MacKinnon DP: Required sample size to detect the mediatedeffect. Psychol Sci 2007, 18:233-239.

49. Salmon J, Jorna M, Hume C, Arundell L, Chahine N, Tienstra M, Crawford D:A translational research intervention to reduce screen behaviours andpromote physical activity among children: Switch-2-Activity. HealthPromot Int 2010, Published on-line.

50. Salmon J: Novel strategies to promote children’s physical activities andreduce sedentary behavior. J Phys Act Health , accepted August 2010.

51. Salmon J, Booth M, Phongsavan P, Murphy N, Timperio A: Promotingphysical activity participation among children and adolescents. EpidemRev 2007, 29:144-159.

52. Salmon J, Hume C, Ball K, Booth M, Crawford D: Individual, social andhome environment determinants of change in children’s televisionviewing: The Switch-Play intervention. J Sci Med Sport 2006, 9:378-387.

53. McCabe MP, Ricciardelli LA, Salmon J: Evaluation of a prevention programto address body focus and negative affect among children. J HealthPsychol 2006, 11:589-598.

54. Campbell KJ, Crawford DA, Ball K: Family food environment and dietarybehaviors likely to promote fatness in 5-6 year-old children. Int J Obes2006, 30:1272-1280.

55. Sallis J, Prochaska J, Taylor W: A review of correlates of physical activity ofchildren and adolescents. Med Sci Sports Exerc 1999, 32:963-975.

56. Salmon J, Timperio A, Telford A, Carver A, Crawford D: Association offamily environment with children’s television viewing and with low levelof physical activity. Obes Res 2005, 13:1939-1951.

57. Hesketh K, Crawford D, Salmon J: Children’s television viewing andobjectively measured physical activity: Associations with familycircumstance. Int J Behav Nutr Phys Act 2006, 3:36-36.

58. Hesketh K, Ball K, Crawford D, Campbell K, Salmon J: Mediators of therelationship between maternal education and children’s TV viewing. AmJ Prev Med 2007, 33:41-47.

59. Australian Government Department of Health and Ageing: Australia’sphysical activity recommendations for children and young people Departmentof Health and Ageing: Canberra; 2004.

60. Sallis JF, McKenzie TL, Conway TL, Elder JP, Prochaska JJ, Brown M,Zive MM, Marshall SJ, Alcaraz JE: Environmental interventions for eatingand physical activity. A randomized controlled trial in middle schools.Am J Prev Med 2003, 24:209-217.

61. Stratton G: Promoting children’s physical activity in primary school: Anintervention study using playground markings. Ergonomics 2000,43:1538-1546.

62. Treuth MS, Schmitz K, Catellier DJ, McMurray RG, Murray DM, Almeida MJ,Going S, Norman JE, PateR : Defining accelerometer thresholds foractivity intensities in adolescent girls. Med Sci Sports Exerc 2004,36:1259-66.

63. Freedson P, Pober D, Janz KF: Calibration of accelerometer output forchildren. Med Sci Sports Exerc 2005, 37(Suppl):S523-S530.


Page 13 of 14

64. Ryan CG, Gray H, Newton M, Granat MH: The convergent validity of free-living physical activity monitoring as an outcome measure of functionalability in people with chronic low back pain. J Back Musc Rehab 2008,21:137-142.

65. Grant PM, Ryan CG, Tigbe WW, Granat MH: The validation of a novelactivity monitor in the measurement of posture and motion duringeveryday activities. Br J Sports Med 2006, 40:992-997.

66. Telford A, Salmon J, Jolley D, Crawford D: Reliability and validity ofphysical activity questionnaires for children: The Children’s LeisureActivities Study Survey (CLASS). Pediatr Exerc Sci 2004, 16:64-78.

67. Burdette HL, Whitaker RC, Daniels SR: Parental report of outdoor playtimeas a measure of physical acticivity in preschool-aged children. ArchPediatr Adol Med 2004, 158:353-357.

68. Cole TJ, Faith MS, Pietrobelli A, Heo M: What is the best measure ofadiposity change in growing children: BMI, BMI%, BMI z-score or BMIcentile? Eur J Clin Nutr 2005, 59:419-425.

69. Kuczmarski RJ, Ogden CL, Grummer-Strawn LM, Flegal KM, Guo SS, Wei R,Mei Z, Curtin LR, Roche AF, Johnson CL: CDC growth charts: United statesUS Department of Health and Human Services, Centers for DiseaseControl and Prevention, National Center for Health Statistics. AdvanceData 2000, 1-27.

70. Cole T, Bellizzi M, Flegal K, Dietz W: Establishing a standard definition forchild overweight and obesity worldwide: International survey. BMJ 2000,320:1240-3.

71. Katzmarzyk PT, Srinivasan SR, Wei C, Malina RM, Bouchard C, Berenson GS:Body mass index, waist circumference, and clustering of cardiovasculardisease risk factors in a biracial sample of children and adolescents.Pediatrics 2004, 114:e198-e205.

72. Child Growth Foundation: Waist circumference charts Harlow Printing Ltd:Shields, Tyne and Wear; 2004.

73. Salmon J, Salmon L, Crawford DA, Hume C, Timperio A: Associationsamong individual, social, and environmental barriers and children’swalking or cycling to school. Am J Health Promot 2007, 22:107-113.

74. Timperio A, Ball K, Salmon J, Roberts R, Giles-Corti B, Simmons D, Baur LA,Crawford D: Personal, family, social, and environmental correlates ofactive commuting to school. Am J Prev Med 2006, 30:45-51.

75. Hume C, Salmon J, Ball K: Associations of children’s perceivedneighborhood environments with walking and physical activity. Am JHealth Promot 2007, 21:201-207.

76. Hume C, Ball K, Salmon J: Development and reliability of a self-reportquestionnaire to examine children’s perceptions of the physical activityenvironment at home and in the neighbourhood. Int J Behav Nutr PhysAct 2006, 3.

77. Hume C, Salmon J, Ball K: Children’s perceptions of their home andneighbourhood environments, and their association with objectivelymeasured physical activity: A qualitative and quantitative study. HealthEduc Res 2005, 20:1-13.

78. Hesketh K, Crawford D, Salmon J, Jackson M, Campbell K: Associationsbetween family circumstance and weight status of Australian children.Int J Pediatr Obes 2007, 2:86-96.

79. Currie C, Gabhainn S, Godeau E, Comm I: The Health Behaviour in School-aged Children: Who collaborative cross-national (HBSC) study: Origins,concept, history and development 1982-2008. Int J Public Health 2009,54:131-139.

80. Salmon J, Campbell KJ, Crawford D: Television viewing habits associatedwith obesity risk factors: A survey of Melbourne schoolchildren. Med JAust 2006, 184:64-67.

81. Basch CE, Shea S, Arliss R, Contento IR, Rips J, Gutin B, Irigoyen M, Zybert P:Validation of mothers’ reports of dietary intake by four to seven year-old children. Am J Public Health 1990, 80:1314-1317.

82. Gold MR, Siegel JE, Russell LB, Weinstein MC: Cost-effectiveness in health andmedicine New York: Oxford University Press; 1996.

83. Drummond MF, Sculpher MJ, Torrance GW, O’Brien BJ, Stoddart GL:Methods for the economic evaluation of health care programmes. 3 edition.Oxford: Oxford University Press; 2005.

84. Hardin JW, Hilbe JM: Generalized estimating equations Boca Raton: Chapman& Hall/CRC.; 2003.

85. Perneger TV: What’s wrong with Bonferroni adjustments? BMJ 1998,316:1236-8.

86. MacKinnon DP, Fairchild AJ, Fritz MS: Mediation analysis. Annu Rev Psychol2007, 58:593-614.

87. Pituch KA, Stapleton LM, Kang JY: A comparison of single samplebootstrap methods to assess mediation in cluster randomized trials.Multivar Behav Res 2006, 41:367-400.

88. Haby MM, Vos T, Carter R, Moodie M, Markwick A, Magnus A, Tay-Teo KS,Swinburn B: A new approach to assessing the health benefit fromobesity interventions in children and adolescents: The assessing cost-effectiveness in obesity project. Int J Obes 2006, 30:1463-1475.

89. Moodie ML, Carter RC, Swinburn BA, Haby MM: The cost-effectiveness ofAustralia’s active after-school communities program. Obesity 2010,18:1585-92.

Pre-publication historyThe pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2458/11/759/prepub

doi:10.1186/1471-2458-11-759Cite this article as: Salmon et al.: A cluster-randomized controlled trialto reduce sedentary behavior and promote physical activity and healthof 8-9 year olds: The Transform-Us! Study. BMC Public Health 2011 11:759.

Submit your next manuscript to BioMed Centraland take full advantage of:



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Page 14 of 14

Appendix 3.2: Transform-Us! Deakin University Human Research Ethics

Committee Approval

Memorandum

To:

From:

Date:

Subject: 2009-141

A multi-setting intervention to reduce sedentary behaviour, promote physical activity andimprove children's health

Prof Jo Salmon

School of Exercise and Nutrition Sciences

B

Deakin University Human Research Ethics Committee (DUHREC)

11 December, 2013

Please quote this project number in all future communications

The modification to this project, submitted on 25/11/2013 has been approved by the committee executive on11/12/2013.

cc:

Human Research Ethics

Deakin Research Integrity 70 Elgar Road Burwood Victoria Postal: 221 Burwood Highway Burwood Victoria 3125 Australia Telephone 03 9251 7123 Facsimile 03 9244 6581 [email protected]

Approval has been given for Prof Jo Salmon, School of Exercise and Nutrition Sciences, to continue this projectas modified to 31/12/2017.

In addition you will be required to report on the progress of your project at least once every year and at theconclusion of the project. Failure to report as required will result in suspension of your approval to proceed withthe project.

DUHREC may need to audit this project as part of the requirements for monitoring set out in the NationalStatement on Ethical Conduct in Human Research (2007).

• Serious or unexpected adverse effects on the participants• Any proposed changes in the protocol, including extensions of time.• Any events which might affect the continuing ethical acceptability of the project.• The project is discontinued before the expected date of completion.• Modifications are requested by other HRECs.

The approval given by the Deakin University Human Research Ethics Committee is given only for the project andfor the period as stated in the approval. It is your responsibility to contact the Human Research Ethics Unitimmediately should any of the following occur:

Human Research Ethics [email protected]: 03 9251 7123

TRANSFORM - US!

CHILD QUESTIONNAIRE

Today's date: __ __ / __ __ / 20__ __

Your name: _________________________________

Your grade: _________________________________

Your teacher’s name: _________________________

What school do you go to? ______________________________

FOR OFFICE USE ONLY

ID:

DATE RECEIVED:

IMPORTANT INSTRUCTIONS – PLEASE READ

Please answer each question by circling your answer. There are no right or wrong answers. We want to know what you think! If you are not sure which answer to pick, please pick the answer that is closest to what you think.

For example:

When asked to circle your answer, please do so like this:

If you make a mistake, just cross it out and circle the answer you want. For example:

1. Do you have the following things at home and do you play with it/them? (Please circle one response for part a. and circle one response for part b.)

a. Do you have this at home?

b. Do you play with it at home?

Yes No Yes No

EXAMPLE Billy cart

Yes1 No2 Yes1 No2

a. Balls (footballs, basketballs, tennis balls, baseballs)

Yes1 No2 Yes1 No2

b. Basketball ring

Yes1 No2 Yes1 No2

c. Bats, racquets, golf clubs

Yes1 No2 Yes1 No2

d. Billy cart

Yes1 No2 Yes1 No2

e. Bowls (ten pin, skittles)

Yes1 No2 Yes1 No2

f. Climbing equipment/trees that you can climb

Yes1 No2 Yes1 No2

g. Cubby house

Yes1 No2 Yes1 No2

h. Frisbee

Yes1 No2 Yes1 No2

i. Safety equipment for activities (eg bike helmet)

Yes1 No2 Yes1 No2

Do you have this

at home? Do you play with

it at home?

Yes No Yes No

ID:

Do you have this


it at home?

Yes No Yes No

j. Scooter/ Skateboard

Yes1 No2 Yes1 No2

k. Skipping rope

Yes1 No2 Yes1 No2

l. Slide/swings

Yes1 No2 Yes1 No2

m. Swimming/wading pool

Yes1 No2 Yes1 No2

n. Table tennis table, bats & balls

Yes1 No2 Yes1 No2

o. Trampoline

Yes1 No2 Yes1 No2

p. Tricycle/bicycle

Yes1 No2 Yes1 No2

q. Volleyball/badminton net

Yes1 No2 Yes1 No2

r. Other (Please write it down) ___________________

Yes1 No2 Yes1 No2

Do you have this


it at home?

Yes No Yes No

2. For each activity listed below, think about whether you did that activity YESTERDAY at school or after school and circle YES or NO. Then, think about how much you enjoy doing this activity and circle the face that shows how you feel.

Did you do this activity yesterday?

a. At recess/ Lunchtime

b. After- school

c. How much do you like doing this?

EXAMPLE Walking

yes1

no2

yes1

no2

a. Riding your Bike

yes1

no2

yes1

no2

b. Exercise: push-ups, jumping jacks

yes1

no2

yes1

no2

c. Basketball

yes1

no2

yes1

no2

d. Baseball, Rounders

yes1

no2

yes1

no2

e. Football

yes1

no2

yes1

no2

f. Cricket yes1

no2

yes1

no2

g. Soccer

yes1

no2

yes1

no2

h. Volleyball

yes1

no2

yes1

no2

i. Racket Sports: badminton, tennis

yes1

no2

yes1

no2


At recess/ Lunchtime

After- school

How much do you like doing this?

5 4 3 2 1

5 4 3 2 1

5 4 3 2 1

5 4 3 2 1

5 4 3 2 1

5 4 3 2 1

5 4 3 2 1

5 4 3 2 1

5 4 3 2 1

5 4 3 2 1



After- school


j. Ball Playing: four square, kickball

yes1

no2

yes1

no2

k. Water Play (swimming pool/lake)

yes1

no2

yes1

no2

l. Swimming Laps (swim team)

yes1

no2

yes1

no2

m. Jump Rope yes1

no2

yes1

no2

n. Dance

yes1

no2

yes1

no2

o. Outdoor Chores: gardening

yes1

no2

yes1

no2

p. Indoor Chores: vacuuming,

yes1

no2

yes1

no2

q. Walking

yes1

no2

yes1

no2

r. Running/ Jogging

yes1

no2

yes1

no2

s. Skateboarding/ Skating / Rollerblading

yes1

no2

yes1

no2

t. Weight Lifting / Strength Training

yes1

no2

yes1

no2

u. Martial Arts Karate, Judo

yes1

no2

yes1

no2



After- school


5 4 3 2 1

5 4 3 2 1

5 4 3 2 1

5 4 3 2 1

5 4 3 2 1

5 4 3 2 1

5 4 3 2 1

5 4 3 2 1

5 4 3 2 1

5 4 3 2 1

5 4 3 2 1

5 4 3 2 1



After- school


v. Sitting and talking

yes1

no2

yes1

no2

w. Drawing

yes1

no2

yes1

no2

x. Reading for fun

yes1

no2

yes1

no2

y. Reading for Homework

yes1

no2

yes1

no2

z. Play Board Games

yes1

no2

yes1

no2

aa. Computer/ video games NOT WII

yes1

no2

yes1

no2

bb. Nintendo Wii (played games where you were active)

yes1

no2

yes1

no2

cc. Homework/ Worksheets

yes1

no2

yes1

no2

dd. Watch TV, Videos

yes1

no2

yes1

no2

ee. Talking on the phone, hanging out with friends

yes1

no2

yes1

no2

ff. Listening to Music, playing an Instrument

yes1

no2

yes1

no2

gg. Other __________

yes1

no2

yes1

no2

5 4 3 2 1

5 4 3 2 1

5 4 3 2 1

5 4 3 2 1

5 4 3 2 1

5 4 3 2 1

5 4 3 2 1

5 4 3 2 1

5 4 3 2 1

5 4 3 2 1

5 4 3 2 1

5 4 3 2 1

3. Circle one sentence in each line that you agree with more… (Please circle one response per line)

EXAMPLE

I don’t do well at new outdoor games and sports1

OR

I am good at new outdoor games and sports2

a. I do well at all kinds of sports1 OR I don’t feel I am very good when it comes to games and sports2

b. I wish I could be a lot better at games and sports1

OR I feel I am good enough at games and sports2

c. I think I could do well at games and sports I have not tried before1

OR I am afraid I might not do well at games and sports I haven’t tried2

d. I feel I am better or as good as others my age at games and sports1

OR I don’t feel I can play games and sports as well as others my age2

e.

During recess and lunch breaks, I usually watch other children play games and sports1

OR During recess and lunch breaks, I usually play games and sports2

f.

I don’t do well at new outdoor games and sports1

OR I am good at new outdoor games and sports2

4. When you watch TV/videos/DVDs, which of the following statements are true for you? (Please circle one response per line)

Never/ Rarely1 Sometimes2 Always

3

EXAMPLE

I sit and watch TV no matter what is on Never/ Rarely1

Sometimes2 Always3

a. The first thing I do when I get home is turn the TV on

Never/ Rarely1

Sometimes2 Always3

b. I sit and watch TV no matter what is on Never/ Rarely1

Sometimes2 Always3

c. I continue to watch TV even after the program I wanted to watch is finished

Never/ Rarely1

Sometimes2 Always3

d. I sit and watch TV/videos/DVDs for so long that my Mum or Dad tells me to turn it off

Never/ Rarely1

Sometimes2 Always3

Never/ Rarely1

Sometimes2 Always3

Never/ Rarely1

Sometimes2 Always3

e. When the show I wanted to watch is finished I turn the TV off and go and do something else

Never/ Rarely1

Sometimes2 Always3

f. I sit in front of the TV and "channel surf" (flicking channels)

Never/ Rarely1

Sometimes2 Always3

g. Before I switch the TV on I find out what's on by looking in the TV guide

Never/ Rarely1

Sometimes2 Always3

h. I find out what's on TV by switching on the TV and "channel surfing" (flicking channels)

Never/ Rarely1

Sometimes2 Always3

i. After school, my Mum or Dad choose what I watch on TV/video/DVD

Never/ Rarely1

Sometimes2 Always3

j. In the evenings, my Mum or Dad choose what I watch on TV/video/DVD

Never/ Rarely1

Sometimes2 Always3

Never/ Rarely1

Sometimes2 Always3

ABOUT THE PEOPLE AROUND YOU 5. Cirlce one sentence in each line that you agree with more… (Please circle one

response per line)

EXAMPLE

Most of my friends do physical activity or sport after school1

OR

Not many of my friends do physical activity or sport after school2

a. Most of my friends play outside after school1

OR Not many of my friends play outside after school2

b. Most of my friends do physical activity or sport after school1

OR Not many of my friends do physical activity or sport after school2

c. Most of my friends watch TV after school1

OR Not many of my friends watch TV after school2

d. Most of my friends play on the computer after school1

OR Not many of my friends play on the computer after school2

6. Please indicate how much the following statements are true for you? (Please circle one response per line)

Never/ Rarely1 Sometimes2 Always3

EXAMPLE

During meal times, the TV is allowed to be on


a. I am allowed to watch any television show(s) I choose


b. My parents restrict how much time I spend watching TV


c. During meal times, the TV is allowed to be on Never/ Rarely1 Sometimes2 Always3

d. I am allowed to watch TV in my room Never/ Rarely1 Sometimes2 Always3

e. I am allowed to play on the computer whenever I choose


f. My parents restrict how much time I spend using the computer and playing electronic games


g. I am allowed to use the computer or play electronic games in my room (eg PSP)


h. I am allowed to play active games inside the house


i. I am allowed to throw balls or play ball-games inside the house


j. I am told off for watching too much TV Never/ Rarely1 Sometimes2 Always3

k. I am told to sit still and play quietly Never/ Rarely1 Sometimes2 Always3

l. I have to finish my homework before I can play outside


m. I must finish my homework before I can watch TV


n. I am allowed to walk/ride a bike in the street without an adult


o. I am allowed to go to the park without an adult Never/ Rarely1 Sometimes2 Always3

p. I am allowed to go to the local shops without an adult


ABOUT YOUR NEIGHBOURHOOD 7. Are these things true for you? (Please circle one response per line)

Yes1 No2

EXAMPLE I know many people in my area Yes1

No2

a. There are lots of children around my area to play with Yes1

No2

b. I often play in the street with other kids in my area Yes1

No2

c. I often visit other kids and families in my area Yes1

No2

d. I know my neighbours quite well Yes1

No2

ABOUT YOUR SCHOOL 8. Please answer the following questions (please circle one response per line)

Yes1 No2

EXAMPLE We are allowed to bring sports equipment (eg bats and balls) from home to use at school during recess and lunch breaks Yes1

No2

a. We are allowed to use school sports equipment (eg bats and balls) during recess and lunch breaks Yes1

No2

b. We are allowed to bring sports equipment (eg bats and balls) from home to use at school during recess and lunch breaks Yes1

No2

c. There are markings on the walls or on the school playground to help us play games (eg 4-square, target on the wall) Yes1

No2

9. During recess and lunch breaks, would you prefer to… (please circle one response per line)

EXAMPLE

Play a running game with friends1

OR

Sit and chat with friends2

a. Play indoors1 OR Play outdoors2

b. Play a running game with friends1 OR Sit and chat with friends2

c. Go for a walk with friends1 OR Sit and chat with friends2

10. After school would you prefer to… (please circle one response per line)

EXAMPLE

Play a running game with friends1

OR

Sit and chat with friends2

a. Play indoors1 OR Play outdoors2

b. Play a running game with friends1 OR Sit and chat with friends2

c. Play outside with friends1 OR Watch TV with friends2

11. Please answer the following questions about what your class teacher does during recess and lunch when NOT on yard duty (please circle one per line)

Yes1 No2

EXAMPLE

My class teacher comes outside with us Yes1

No2

a. My class teacher comes outside with us Yes1

No2

b. My class teacher plays games with us Yes1

No2

c. My class teacher watches us play games Yes1

No2

d. My class teacher rewards or praises us for playing active games Yes1

No2

e. My class teacher encourages us to play active games Yes1

No2

12. Please answer the following questions about what your class teacher does during recess and lunch when on yard duty (please circle one per line)

Yes1 No2

EXAMPLE

My class teacher encourages us to play games Yes1

No2

a. My class teacher stays inside Yes1

No2

b. My class teacher encourages us to play games Yes1

No2

13. How do you feel about the following (please circle one response per line)

EXAMPLE

The areas to play in at school

a. The work you do in class

b. Standing up while doing your work during class

c. The areas to play in at school

d. Homework

14. How often does the following happen? (please circle one response per line)


EXAMPLE

I like being at school Never/ Rarely1 Sometimes2

Always3

a. I have too much class work Never/ Rarely1 Sometimes2 Always3

b. I find class work difficult Never/ Rarely1 Sometimes2 Always3

c. I find class work tiring Never/ Rarely1 Sometimes2 Always3

d. We sit down during most of my class activities


e. My teacher gets us to do lots of class activities standing up


f. My teacher gets us to move around a lot during class


g. I look forward to going to school Never/ Rarely1 Sometimes2 Always3

h. My teacher encourages us to move around during class


i. My teacher makes sure we are not sitting down for a long time



5 4 3 2 1

5 4 3 2 1

5 4 3 2 1

5 4 3 2 1

5 4 3 2 1


j. I like being at school Never/ Rarely1 Sometimes2 Always3

k. There are many things about school I do not like


l. I wish I didn’t have to go to school Never/ Rarely1 Sometimes2 Always3

m. I enjoy my class work Never/ Rarely1 Sometimes2 Always3

n. My parents know what I am learning in class


o. My parents participate in classroom/school activities


p. My parents know who I play with at recess and lunch


q. My parents help me with my homework


r. My brothers/sisters help me with my homework

Never/ Rarely1 Sometimes2 Always3 Don’t have4

s. I do my homework standing up Never/ Rarely1 Sometimes2 Always3

t. I use the computer for my homework



ABOUT YOU

15. Are you a….? (Please tick one box)

1 Boy

2 Girl

16. How old are you now? (Please tick one box)

1 7 years

2 8 years

3 9 years

4 10 years

5 11 years

6 12 years and over

17. What grade are you in this year? (Please tick one box)

1 Grade 2 2 Grade 3 3 Grade 4 4 Grade 5

ABOUT YOUR HOME Now we would like to ask you about who you live with. Not everyone lives with both their parents. Sometimes people live with just one parent, sometimes they have two homes or two families.

Please tell us about your home, the place where you spend the most of your time.

18. Please place a tick next to all the adults who live with you at home:

1 Mother

2 Father

3 Stepmother (or father’s girlfriend)

4 Stepfather (or mother’s boyfriend)

5 Grandmother

6 Grandfather

7 I live in a foster home or children’s home

8 With someone or somewhere else: Please write it down:

___________________________________

19. Please write down how many children live in your home (including half, step or foster brothers/sisters). Please write 0 if there are none

a. Number of brothers? ____________

b. Number of sisters? _____________

20. Do you stay in this home…… (Please tick one box)

1 All the time

2 Most of the time

3 Half the time

21. How many working cars does your family have? (Please tick one box)

1 None

2 One

3 Two or more

22. This year, how many times did you travel away on holiday with your family? (Please tick one box)

1 Not at all

2 Once

3 Twice

4 More than twice

23. Do you have your own bedroom? (Please tick one box)

1 Yes

2 No

24. Do you have a TV in your bedroom? (Please tick one box)

1 Yes

2 No

25. Do you have a Playstation/ Nintendo/XBOX/ Sega/Gameboy in your bedroom? (Please tick one box)

1 Yes

2 No

26. Do you have a Nintendo Wii in your bedroom? (Please tick one box)

1 Yes

2 No

27. Do you have a laptop computer or a desktop (PC or Macintosh) computer in your bedroom? (Please tick one box)

1 Yes

2 No

28. Do you have your own Mobile phone? (Please tick one box)

1 Yes

2 No

29. Do you own one or more dogs? (Please tick one box)

1 Yes

2 No

30. Do you have a yard at home to play outside in? (Please tick one box)

1 Yes

2 No

31. Is your house in a cul-de-sac, court or no-through road? (Please tick one box)

1 Yes

2 No

Thank you for completing this survey for us!

TRANSFORM - US!

MAIN CARER QUESTIONNAIRE

It is important that the adult who is mainly

responsible for the care of the child participating in Transform-Us! completes this questionnaire

Your name: _______________________________________

Your child’s name: _________________________________

Your child’s School: _________________________________

Your child’s teacher: _________________________________

If you have any questions, please contact 9244 6278

IMPORTANT INSTRUCTIONS – PLEASE READ

FOR OFFICE USE ONLY

ID:

DATE RECEIVED:

Thank you for taking the time to complete this survey. It should take you approximately 20 minutes to complete, although this might vary depending on your answers. Once you have finished your survey, please place it in the envelope provided and return it to your child’s class teacher.

Please answer each question by ticking or circling the most suitable option. Where you are asked to write an answer please read the question carefully and answer the best you can in the space provided. If you are unsure about how to answer a question, please choose the answer that best reflects how you feel.

When marking your answers on the survey, please clearly tick or circle your response so we can easily see which answer you chose. For example:

When asked to tick your answer, please do so like this:

1 Yes

2 No

When asked to tick your answer, please do so like this:

Strongly disagree1 Disagree

2 Neither agree or

disagree3

Agree

4 Strongly agree

5

If you make an error, please clearly cross out the incorrect answer and tick the correct answer. For example:

Strongly disagree1

Disagree2

Neither agree or disagree

3

Agree4

Strongly agree5

Important definition:

Physical activity: is any bodily movement produced by skeletal muscle contraction that increases energy expenditure. For example, walking, running, playing soccer and dancing.

This questionnaire should be completed by the adult who is mainly responsible for the care of the child involved in Transform-Us! Throughout this survey, the child involved in this research

will be referred to as ‘your’ child and the person completing the survey as the ‘parent/guardian’.

ID:

Today's date: __ __ / __ __ / 20__ _

Today's date: __ __ / __ __ / 20__ __ 1. In the last week, how many times have you walked continuously, for at least 10

minutes, for recreation, exercise or to get to or from places?

__________times in the last week 2. What do you estimate was the total time that you spent walking in this way in the last

week? In hours and/or minutes

__________hours and __________minutes in the last week

3. In the last week, how many times did you do any vigorous gardening or heavy work

around the yard, which made you breathe harder or puff and pant?

__________times in the last week 4. What do you estimate was the total time that you spent doing vigorous gardening or

heavy work around the yard in the last week? In hours and/or minutes


5. In the last week, how many times did you do any vigorous physical activity which made

you breathe harder or puff and pant? (e.g. jogging, cycling, aerobics, competitive tennis)

__________times in the last week 6. What do you estimate was the total time that you spent doing this vigorous physical

activity in the last week? In hours and/or minutes


7. In the last week, how many times did you do any other more moderate physical

activities that you have not already mentioned? (e.g. gentle swimming, social tennis, golf)

__________times in the last week

8. What do you estimate was the total time that you spent doing these activities in the last week? In hours and/or minutes


These questions are about any physical activities that you may have done in the last week:

YOUR PHYSICAL ACTIVITY

The next questions exclude household chores, gardening or yard work:


WEEK DAYS (Monday - Friday) 9. a. During the last week, what was the total time you spent sitting from Monday

to Friday (INCLUDING the day and evening)?

Total: __________hours and __________minutes in the last week

b. During the last week, what was the total time you spent watching TV from Monday to Friday (including days and evenings)?

Total: __________hours and __________ minutes in the last week

c. During the last week, what was the total time you spent sitting at a computer AT HOME from Monday to Friday (including days and evenings)?


WEEKEND DAYS (Saturday and Sunday) 10. a. During the last week, what was the total time you spent sitting last Saturday

and Sunday (INCLUDING the day and evening)?


b. During the last week, what was the total time you spent sitting watching TV last Saturday and Sunday (INCLUDING the day and evening)?


c. During the last week, what was the total time you spent sitting at a computer AT HOME last Saturday and Sunday (INCLUDING the day and evening)?


The next questions are about the time you spend sitting while at work, at home, while doing study and during leisure time. This may include time spent sitting at a desk, visiting friends,

reading or sitting or lying down to watch television or sitting in a motor vehicle.

11. What is his/her date of birth (day / month / year)? _______/_______/_______ 12. What is his/her sex?

1 Male

2 Female

13. What grade is your child in this year? (Please tick one box)

1 Grade 2 2 Grade 3 3 Grade 4 4 Grade 5 5 Grade 6

14. In the current school term, NOT including school holidays, how many hours per night

does your child usually sleep?

Write the number here: _______ hours

15. Does your child in this study have a disability or suffer from poor health? (please tick one box)

1 2

If yes, please describe:___________________________________________________

16. If your child is CURRENTLY taking any PRESCRIPTION medications, please specify the

NAME of the medication, the DOSE, the DURATION OF USE and the REASON for using the PRESCRIPTION medication(s) your child is currently taking.

1 Tick if your child is currently taking any PRESCRIPTION medications.

Name of medication eg1. Ritalin

Dose eg1 5mg

Frequency/day eg1 twice a day

Duration of use eg1 6 weeks

Reason for taking medication eg1 ADHD

ABOUT YOUR CHILD

YOUR CHILD’S MEDICATIONS/SUPPLEMENTS

17. If your child is CURRENTLY taking any NON-PRESCRIPTION medications or supplements please specify the NAME of the medication/supplement, the DOSE, the DURATION OF USE and the REASON for using the NON-PRESCRIPTION medication(s). Supplements included vitamin, mineral and herbal types/remedies.

1 Tick if your child is currently taking any NON-PRESCRIPTION medications/supplements

Name of medication eg1. Vitamin

Dose eg1 105mg

Frequency/day eg1 once a day

Duration of use eg1 6 weeks

Reason for taking eg1 anaemia

18. In total how many hours/minutes does your child usually spend OUTSIDE during a typical week after school? (MONDAY to FRIDAY) Note: please add the time for each day to find the total.

a. During the warmer months (Terms 1 and 4)

__________hours and __________minutes/week (Monday to Friday)

b. During the cooler months (Terms 2 and 3)

__________hours and __________minutes/week (Monday to Friday)

19. In total how many hours/minutes does your child usually spend OUTSIDE on a typical weekend? (SATURDAY and SUNDAY) Note: please add the time for each day to find the total.

a. During the warmer months (Terms 1 and 4)

__________hours and __________minutes/week (Saturday and Sunday)

b. During the cooler months (Terms 2 and 3)

__________hours and __________minutes/week (Saturday and Sunday)

YOUR CHILD’S ACTIVITIES

20. Which of the following PHYSICAL or TRANSPORTATION activities does your child USUALLY do during a typical WEEK? (In the current school term. DO NOT include school holidays)

During a typical WEEK what activities does your

child usually do?

Does your child

usually do this

activity?

How many times in TOTAL

Monday-Friday?

TOTAL hours/minutes Monday-Friday

How many times in TOTAL

Saturday & Sunday?

TOTAL hours/minutes

Saturday & Sunday

EXAMPLE Walk for exercise

No1 Yes2 2 1 hour 30 minutes 0 0 hours

a. Ride a bicycle for fun No1 Yes2 ____Hrs____Mins ___Hrs____Mins

b. Walk for exercise No1 Yes2 ____Hrs____Mins ___Hrs____Mins

c. Walk the dog No1 Yes2 ____Hrs____Mins ___Hrs____Mins

d. Play with the dog or other pets

No1 Yes2 ____Hrs____Mins ___Hrs____Mins

e. Organised sport or activities No1 Yes2 ____Hrs____Mins ___Hrs____Mins

f. Travel by walking to destinations other than school


g. Travel by cycling to destinations other than school


h. Travel by car to destinations other than school


i. Travel by walking to school (to and from school = 2 times)

No1 Yes2 ____Hrs____Mins

j. Travel by cycling to school (to and from school = 2 times)


k. Travel by car/bus to school (to and from school = 2 times)


21. Which of the following LEISURE activities does your child USUALLY do during a typical WEEK? (In the current school term, do NOT include school holidays)

During a typical WEEK what leisure activities does your

child usually do?

Does your child usually

do this activity?

TOTAL hours/minutes AFTER SCHOOL

Mon-Fri

TOTAL hours/minutes

WHOLE DAY Mon-Fri

TOTAL hours/minutes

Saturday & Sunday

Example: TV No1 Yes2 10 hours 15hrs 6hrs 45mins

a. TV / videos/DVD’s No1 Yes2 ____Hrs____Mins ____Hrs____Mins ____Hrs____Mins

b. Playstation© / Nintendo© / computer games

No1 Yes2 ____Hrs____Mins ____Hrs____Mins ____Hrs____Mins

c. Nintendo Wii No1 Yes2 ____Hrs____Mins ____Hrs____Mins ____Hrs____Mins

d. Computer / Internet (excluding games)

No1 Yes2 ____Hrs____Mins ____Hrs____Mins ____Hrs____Mins

22. Think about a TYPICAL WEEK in the CURRENT SCHOOL TERM. How often does your child participate in physical activity or play sport...? (Please tick one response per line)

Never1 1-2 days/ week2

3-4 days/ week3

5-6 days/ week4

Everyday5 N/A6

a. With his/her siblings

b. With a parent/guardian/caregiver

c. With friends

The next question asks about your child’s TV viewing and computer use. Please note the following definitions:

• TOTAL hours/minutes AFTER SCHOOL Mon-Fri: refers to the TOTAL time between when the child arrives home from school and when they go to bed on Monday to Friday

• TOTAL hours/minutes including after school Monday-Friday: this includes the morning and after school periods (i.e, the whole day)

Eg. In the example provided the child watched TV for 2 hours after school each day of the week

(total: 2 hours x 5 days =10 hours).The child also watched TV for an hour before school each day of the week (total: 1 hour x 5 days =5 hours). The 10 after-school hours were added to these 5 hours to get the whole day total of 15 hours.

YOU AND YOUR CHILD

23. Think about a TYPICAL WEEK in the CURRENT SCHOOL TERM. How often does your child sit and watch TV, play video/electronic games, on the computer, or with other electronic devices … (Please tick one response per line)


3-4 days/ week3

5-6 days/ week4

Everyday5 N/A6

a. With his/her siblings

b. With a parent/guardian/caregiver

c. With friends

24. Think about a TYPICAL WEEK in the CURRENT SCHOOL TERM. How often do you or another adult in the household: (Please tick one response per line)


3-4 days/ week3

5-6 days/ week4

Everyday5

a. Watch your child participate in physical activity or sports

b. Watch your child play on the computer/electronic games

c. Praise your child for participating in physical activity or sports

d. Encourage your child to do physical activity or sports

e. Praise your child for playing on the computer/electronic games

f. Encourage your child to sit quietly and watch TV

g. Reward your child for being active

h. Provide transport to a place where your child could do physical activity or play sports

i. Provide practical support (eg club fees) for your child to do physical activity or sport

j. Tell your child off for watching too much TV

25. During the CURRENT SCHOOL TERM (NOT including holidays), what was your child's USUAL before and after school care arrangement? (Please tick one response per line)

My child...

Less than once per

week1

1 day/ week2

2 days/ week3

3 days/ week4

4 days/ week5

5 days/ week6

No/Doesn't apply7

a. …goes to before school care

b. …goes to after school care

c. …goes to a friend’s house

after school

d. …is looked after by a

babysitter/relative after school

e. …is looked after by me/my

partner after school

f. …is looked after by older

brother/ sister after school

g. …is home alone after school

h. …goes to a club (eg. Sport)

i. Other (please state): _________________

26. Think about the LAST WEEK. What was your child's after-school care arrangement? a. Last week my child went…

(Tick as many as apply)

Monday

Tuesday

Wednesday

Thursday

Friday

a. …home

b. …to a friend’s place

c. … to a relative’s place

d. …to after-school care

e. …to a sporting Club

f. … other (please state) ______________________

HOW YOUR CHILD SPENDS TIME OUTSIDE OF SCHOOL HOURS

b. After school last week, my child was with… (Tick as many as apply)

Monday

Tuesday

Wednesday

Thursday

Friday

1. …Mum/step-mum

2. …Dad/step-dad

3. …Step/Brother

4. …Step/Sister

5. …Friend

6. …Relative

7. …Grandparent/s

8. …Nanny/Minder

9. …Other (Please state)

________________________

27. During the school terms, on a typical school day, what time do you allow your child to be outdoors until? (Without adult supervision. May be with other children)

a. During warmer months (Terms 1 and 4): __________pm

b. During the cooler months (Terms 2 and 3): __________pm

28. During the school terms, on a typical school day, what time does your child eat dinner?

________:________pm

29. Below are some reasons that might stop your child from doing more physical activity than he/she already does. How much do you agree or disagree with each of the following statements? (Please tick one response per line)

Strongly disagree1

Disagree2

Neither agree or disagree3

Agree4 Strongly agree5

a. My child doesn’t have enough energy to do more physical activity

b. My child doesn’t have enough time to do physical activity

c. My child doesn’t have anyone to be physically active with

d. My child just doesn’t enjoy being physically active

e. The right facilities are not available for my child to do more physical activity

f. My child is too overweight to participate in physical activity

g. My child doesn’t have good enough skills (eg kicking, throwing, catching) to do more physical activity

30. Please tell us how much you agree with the following statements. (Please tick one response per line)

Strongly disagree1

Disagree2



a. I think that my child should do at least one hour of physical activity every day

b. I am satisfied with the amount of physical activity my child does

c. I would like my child to do more physical activity

d. My child does enough physical activity to keep him/her healthy

e. The amount of TV my child watches would adversely affect his/her health

f. The amount of time my child spends on the computer/playing electronic games would adversely affect his/her health

g. Using the computer is important for my child’s learning

h. I think my child should spend less than 2 hours per day watching TV or playing on the computer

i. If my child watched less TV and used the computer less, there would be nothing for my child to do

j. The TV/computer is useful for keeping my child occupied

k. My child prefers to watch TV/use the computer than play outside

l. I don’t have to worry about where my child is when he/she is watching TV/using the computer

m. My child might get up to mischief if he/she wasn’t allowed to watch TV/use the computer

n. My child’s siblings or friends encourage him/her to watch TV/use the computer with them

o. My child is ‘addicted’ to the computer

p. TV viewing is something my child does automatically

q. I am too busy after school to be concerned about my child’s activity levels

r. My child gets enough physical activity after school through extracurricular activities, so he/she doesn’t need to be active when he/she gets home.

31. How much do you agree with the following? (Please tick one response per line)

Strongly disagree1

Disagree2



a. My child needs to be encouraged to be physically active

b. My child is naturally active

c. My child is usually too active and must be ‘slowed down’

d. Physical activity is something my child does automatically

You are over halfway through!

You may like to stop for a break now and do the rest of the survey later

32. In the past month, about how often has your child had the following? (Please tick one response on each line)

Never or less than

once /month1

1-3 times/ month2

Once/ week3

2-4 times/week4

5-6 times/week5

Once a day6

2-3 times a

day7

4-5 times a

day8

6 or more

times a day9

a. Potato crisps or salty snack foods

b. Chocolate or lollies

c. Cake, doughnuts, sweet biscuits

d. Pies, pasties or sausage rolls

e. Fast foods (e.g. McDonalds, KFC, Pizza)

f. Hot chips, French fries, wedges, or fried potatoes

33. About how many serves of vegetables does your child usually eat per day? Do not include hot chips or fried potato. (1 serve = ½ cup cooked vegetables or 1 cup salad vegetables) (Please tick one response only)

My child does

not eat Vegetables1

Less than one serve/

day2

One serve/ day3

2 Serves/

day4

3 Serves/

day5

4 Serves/

day6

5 Serves/

day7

6 or more

Serves/ day8

Vegetables

34. About how many serves of fruit does your child usually eat per day? Do NOT include fruit juice. (1 serve = 1 medium piece or 2 small pieces of fruit or 1 cup of diced pieces) (Please tick one response only)

My child does not eat fruit1


day2

One serve/ day3

2 Serves/

day4

3 Serves/

day5

4 Serves/

day6

5 Serves/

day7

6 or more

Serves/ day8

Fruit

YOUR CHILD’S DIET

35. About how many serves of fruit juice does your child usually drink each day? (Please tick one response only) (1 serve = 125ml or ½ cup/glass or popper/tetra pack)

My child does not drink fruit

juice1


day2

One serve/ day3

2 Serves/

day4

3 Serves/

day5

4 Serves/

day6

5 Serves/

day7

6 or more

Serves/ day8

Fruit juice

36. About how much SOFT DRINK (excluding diet soft drinks) does your child usually drink each day? (include all types of soft drink, including fruit flavoured drinks and sports drinks, but exclude any diet soft drinks, fruit juice or plain water) (Please tick one response only) (1 serve = 125ml or ½ cup/glass; 1 can = 3 serves; 600ml bottle = 5 serves; 1.25ml bottle = 10 serves)

My child does not drink soft

drinks1


day2

One serve/ day3

2 Serves/

day4

3 Serves/

day5

4 Serves/

day6

5 Serves/

day7

6 or more

Serves/ day8

Soft Drinks

37. How much do you agree with the following statements? (Please tick one response per line)

Strongly disagree1

Disagree2



a. I let my child watch any television shows he/she chooses

b. I restrict how much time my child spends watching TV

c. During meal times, I do not allow the TV to be on

d. I restrict how much time my child spends using the computer and playing electronic games

e. My child is allowed to play on the computer when he/she chooses

f. My child is allowed to play on the computer or use electronic games (eg PSP) in his/her room

g. My child is allowed to play active games inside the house

h. My child is not allowed to throw balls or play ball-games inside the house

i. My child must finish his/her homework before playing outside

j. My child must finish his/her homework before watching TV

k. I don’t allow my child to walk/ride a bike on the street without an adult

l. My child is allowed to go to the park without an adult

m. My child is allowed to go to the local shops without an adult

RULES FOR YOUR CHILD

38. Please tell us about your child’s homework during the CURRENT SCHOOL TERM. (Please tick one response per line)

Never1

Once/ Month2

Once/ Fortnight3

1-2 days /week4

3-4 days /week5

Every day6

Don’t know7

a. My child completes reading homework

b. My child completes worksheet homework (eg Maths)

c. My child’s homework requires him/her to be active

39. Think about a TYPICAL WEEK in the CURRENT SCHOOL TERM, how much time do each of the following people participate in completing school homework tasks WITH your child?

a. Total time spent by adult/s (persons 18 years and over):

__________hours and __________minutes/week b. Total time spent by other children eg. older sibling (persons 18 year and under):

__________hours and __________minutes/week

40. Please tell us about your involvement in your child’s school and homework during the CURRENT SCHOOL TERM. (Please tick one response per line)

Never/Rarely1 Sometimes2 Always3

a. I supervise my child completing homework

b. I participate in my child’s homework with him/her

c. I complete my child’s homework for him/her

d. I and/or my partner take a keen interest in my child’s education

e. I and/or my partner attend parent teacher meetings at my child’s school

f. Most parents in my child’s class are involved in activities at the school (eg athletics days, Fetes, Canteen duty)

g. I regularly participate in classroom or school activities

h. I know what my child is currently doing in school

YOUR CHILD’S SCHOOL Please be assured your responses will remain confidential. Your child’s school will not be informed of your responses.

41. Please tell us how much you agree or disagree with the following statements. (Please tick one response per line)

42. Please indicate how much you agree with the following statements. (Please tick one response per line)

Strongly disagree1

Disagree2



a. My child gets enough physical activity at school (eg recess and lunch breaks) for health benefits

b. My child gets enough physical activity at school, so he/she doesn’t need to be active when he/she gets home

c. My child’s school does play an important role in the provision of physical activity for my child

d. My child should not receive any homework

e. I believe homework is important for my child’s educational development

f. If my child’s homework was completed in an active way (eg. go for a walk to count letter boxes), the education benefits of the homework tasks would be reduced.

If my child spent more time standing during class time…

Strongly disagree1

Disagree2



a. He/she would concentrate more

b. He/she would be less productive in class

c. He/she would be tired when he/she got home

d. He/she would be too tired to play outdoors after school

e. It would benefit his/her health

f. It would benefit his/her academic performance

43. Please indicate how much you agree with the following statements. (Please tick one response per line)

44. Which of the following do you have at your house? (tick as many as apply)

1 Pay TV

1 Internet

1 Video/DVD player

1 Nintendo Wii

1 Television, please write the number of working TVs in your home _______________

1 Electronic game consoles (eg playstation, EXCLUDING Nintendo Wii) please write the number of working consoles in your home _______________

45. Please tell us about your yard where your child is able to play. How big is your yard? (Please tick ONE box)

1 no yard at all

2 no private yard

3 a small yard (eg unit or courtyard)

4 a medium yard (eg standard block of land)

5 a large yard (eg ¼ acre block or larger)

46. Do you live on a cul-de-sac, court or no-through road? (Please tick ONE box)

1 yes 2 no

If my child spent more time standing completing homework… (eg standing while reading)

Strongly disagree1

Disagree2



a. He/she would be more likely to finish their task

b. He/she would be able to concentrate more

c. He/she would be too tired to complete his/her homework

YOUR HOME

47. What relation are you to the child involved in this study? (please tick one box)

1 Mother 2 Female carer

3 Father 4 Male carer

5 Grandparent 6 Guardian

7 Other (please state): _______________________

48. Thinking about the child involved in this study, which of the following applies to their

family situation? (please tick one box)

1 Both the child’s birth parents live together

2 The child’s birth parents live apart

3 Other family situation. Please describe: ________________________________

49. How old are you, the parent? _________ years

50. What is your sex? (please tick one box)

1 Male

2 Female

51. What is your current marital status? (please tick one box)

1 Married 4 Divorced

2 De facto/Living together 5 Widowed

3 Separated 6 Never married

52. Where were you born? (please tick one box)

1 Australia 6 Germany

2 UK or Ireland 7 New Zealand

3 Italy 8 Vietnam

4 Greece 9 Poland

5 Netherlands 10 Other (please state) ______________

53. In your household, do you usually speak English? (please tick one box)

1 Yes

2 No

ABOUT YOU

54. What is your highest level of schooling? (please tick one box)

1 Never attended school

2 Primary school

3 Some high school

4 Completed high school

5 Technical or trade school certificate/apprenticeship

6 University or tertiary qualification

55. How tall are you without shoes? (If unsure please state your best guess)

___________cm or ______________feet/inches

56. How much do you weigh without clothes or shoes? (If unsure please state your best guess)

___________kg or ______________stone/pounds

57. How many children ‘dependents’ currently live in your house (including the child in this study)?

Write the number here: _______

Please list the age and gender of each child below: (please INCLUDE the child in this study)

Age (years) Gender (M/F) 1) _________ _________ 2) _________ _________ 3) _________ _________ 4) _________ _________ 5) _________ _________ 6) _________ _________

58. Are you currently: (please tick as many as apply)

1 Employed full time in paid employment 2 A night-shift worker

3 Employed full time in unpaid employment 4 A shift worker

5 Employed part time in paid employment 6 Retired

7 Employed part time in unpaid employment 8 Unemployed

9 Home-duties full time 10 A student

11 Other (please state) _______________________________

59. Thinking about the last month, in a typical working week (Monday to Friday), on average, how many hours per day did you spend working in paid employment outside your home?

________ hours per day

60. Have you been diagnosed with diabetes? (Please tick one response)

1 yes 2 no 3 don’t know

If yes, what was your age at diagnosis__________ years

61. Have you been told by a Doctor or Nurse that you have high blood pressure of hypertension? (Please tick one response)


62. Are you currently taking tablets for high blood pressure? (Please tick one response)


63. Have you been told by a Doctor or Nurse that your blood cholesterol or triglycerides are high? (Please tick one response)


64. Are you currently taking tablets to lower your cholesterol/triglycerides? (Please tick one response)


Thank you for completing this survey for us!

YOUR HEALTH

We greatly appreciate the time you have taken to help us with our research. It would not be possible without your generous assistance. We will be conducting the next Transform-Us! assessment phase in 12 months time. This will allow us to look at changes in young people’s activity levels over time and to understand the influences on these. In order for us to contact you to inform you of when this will occur, please provide your details below, and the contact details of a close friend or relative, not living with you, who we can contact in the event that you move house.

My Name: ___________________________________________________________________ My Postal Address: __________________________________________________________ House number Street name __________________________________________________________ Suburb Post Code

Phone Numbers: (home) __________________________ (work) __________________________ (mobile)__________________________ Email Address: ___________________________________________________ Name of a close friend or relative (in the event I move) (1) Name: ___________________________________________________

Postal Address: ___________________________________________________ House number Street name

___________________________________________________ Suburb Post Code

Phone: ____________________ Email: _________________________

(2) Name: ___________________________________________________

Postal Address: ___________________________________________________ House number Street name

___________________________________________________ Suburb Post Code

Phone: ____________________ Email: _________________________

This page will be removed on receipt of the questionnaire

THANK YOU FOR YOUR TIME AND HELP WITH THIS RESEARCH

the after-school period: a critical window for children’s...

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