Pathways to obesity

Identifying local, modifiable determinants of physical activity and diet

Mai Stafford, Amanda Sacker Dept of Epidemiology & Public Health, UCL

Sally Macintyre, Anne Ellaway MRC Social & Public Health Sciences Unit, Glasgow

Steve Cummins Dept of Geography, Queen Mary College London

R D Wiggins Dept of Sociology, City University

• Neighbourhood influences on health of increasing interest

• Methodological developments

• Empirical evidence focuses on deprivation index as exposure

• Neighbourhood deprivation associated with

- mortality (all-cause, suicide, deaths from heart disease)

- morbidity (self-rated health, disability, smoking, quality of life, common mental disorder)

Background/rationale

• Composition or context?

• Multilevel data and analysis

• Reviews of evidence conclude there is an association between neighbourhood deprivation and health

• Neighbourhood deprivation = black box

What neighbourhood characteristics might influence health?

Neighbourhood deprivation index

Service environment e.g. health services, public transport, retail

Built environment

Social environment e.g. social disorder, social capital

Unpacking the black box

• Identify specific, amenable neighbourhood determinants of health

• How do these relate to each other?

• How do they jointly influence health?

• Focus on obesity – a major public health issue

• Key determinants of obesity are diet and physical activity

Service environment and diet, physical activity and obesity

Local sport & leisure facilities

Greater physical activity Giles-Corti et al, 2002

Presence of supermarket

Higher fruit & veg consumption, lower fat intake

Morland et al, 2002

Poorer access (proximity & car)

Lower fruit & veg consumption Cheadle et al, 1991

Availability low fat/high fibre foods

Greater intake low fat & high fibre

Rose et al, 2004

No. fast foodoutlets

Obesity Maddock, 2004

Built environment

Mixed commercial-residential land use

Greater levels of walking

Doyle et al, 2006; Frank et al, 2006

Urban sprawl (population density)

Lower levels of walking Morenoff et al, 2006

Attractive scenery

open spaces

Greater physical activity

Brownson et al, 2001; Sugiyama et al, 2005

Social environment- neighbourhood disorder

Neighbourhood

safety

Childhood obesity Lumeng et al, 2006

Fear on streets

fear of attack

Less outdoor physical activity

Ross, 1993

Fear of crime Less walking for pleasure

Parkes & Kearns, 2006

Litter and graffiti Obesity Ellaway et al, 2005

Leisure centres

Neighbourhood disorder

High physical activity

Obesity

Good diet

Urban sprawl

Supermarkets

Fast-food outlets

Demographic & socioeconomic characteristics

Environmental characteristics Individual characteristics

Mixed commercial/

residential use

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-

+

+

-

-

-

-

+

?

-

-

Data & methodsI. Measuring obesity

• Health Survey for England (1994-1999) and Scottish Health Survey (1995 & 1998)• Nationally representative• Height and weight measured by trained nurse• Obesity = body mass index = weight/height2

• Age, gender and occupation-based SES• Neighbourhood unit = postcode sector• Average population ~ 5000

Data & methodsII. Selecting neighbourhoods for study

Eligible neighbourhoods

Ensure range of environments

Select sample of neighbourhoods

≥ 35 Health Survey participants

Stratify on population density & Carstairs index of deprivation

Stratified random sample

Data complete for 398 neighbourhoods

Collect neighbourhood data

Data & methodsIII. Measuring the service & built environment

• Various sources: administrative data from central government, local government, commercial organisations

e.g. violent crime per capita, number of supermarkets

• Difficult to obtain data

– not available

– not complete

– not comparable England and Scotland

• Data collected or converted to postcode sector

Data & methodsIV. Measuring neighbourhood disorder

• Local Area Social Capital Survey conducted in 2000• 70-item postal questionnaire• Sent to random sample of residents 16+ years• Response rate 42%• 5 items capture neighbourhood disorder

Tick one per row

There is no problem with vandalism and

graffiti in this area

Vandalism and graffiti are a big problem in this area

Most people in this area can be trusted

Most people in this area can’t be trusted

People feel safe walking alone in this

area after dark

People would be afraid to walk alone in this area after dark

This area is kept very

clean

This area is always full of litter and rubbish

Neighbours are unthreatening

Neighbours are threatening

Data & methodsV. Linking data

Administrative/commercial data

Service environmentBuilt environment

Postal survey

Neighbourhood disorder

Existing health survey

Individual level obesity

Link via postcode sector identifier

Violent crime rate

# special constables

Vacant/derelict land

Sports participation

rate

BMI

Population density

# supermarkets

Age Male SES

Neighbour-hood

disorder

# police officers

# missed waste collections

High street facilities

# swimming pools

# McDonalds

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+ - -

Data & methodsVI. Structural Equation Modeling

• Aim to investigate inter-relationships between various neighbourhood characteristics and their relationship with obesity

• Beyond estimation of direct effects

• Examine causal processes underlying observed relationships

• Estimate relative importance of different causal pathways

Data & methods

• Some neighbourhood characteristics modeled using latent variables

i.e. measured variables are indicators of underlying construct

• Want to know about relationships between underlying constructs (not between measured variables)

Neighbourhood disorder

Graffiti/vandalism

People can‘t be trusted

Afraid to walk alone

Area full of rubbish

Neighbours threatening

High street facilities

# pharmacies

# optician practices

# dental practices

# libraries

# building societies

# banks

# Bingo halls

distance to post office

Data & methods

• Step 1: confirmatory factor analysis to assess how well measured variables capture underlying construct• Step 2: structural equation model linking neighbourhood characteristics to obesity• Allow for clustering of participants within neighbourhoods• Present standardised factor loadings and path coefficients• Mplus software

Results• Factor analysis confirmed that

i) neighbourhood disorder well-measured by the 5 items from the Social Capital Survey

ii) high street facilities well-measured by 5 items (3 dropped)

High street facilities

# pharmacy

# optician practices

# dental practices

# building societies

# banks

High street facilities

# pharmacy

# optician practices

# dental practices

# libraries

# building societies

# banks

# Bingo halls

distance to P.O.

Violent crime rate

# special constables

Vacant/derelict land

Sports participation

rate

BMI

Population density

Supermarkets

Age M SES

Neighbourhood disorder# police officers

Missed waste

High street facilities

Swimming pools

0.114

-0.258

0.488

0.181

0.105

-0.013

-0.033

-0.024

-0.001

-0.305

-0.038

0.207

-0.323

0.073

Post office

-0.019

Summary of findings

• Previous studies show neighbourhood deprivation is associated with obesity• Our findings illustrate some specific features of the neighbourhood environment that are associated with

obesity• These are neighbourhood disorder, mixed commercial/residential land use and urban sprawl• In turn, policing and vacant/derelict land influence levels of neighbourhood disorder

Discussion• Study illustrates how data from various sources can be combined• Latent variables can be used when have several indicators of the same underlying construct • Structural equation models can be used to explore theoretical causal pathways• Limitations include

i. lack of neighbourhood data capturing the theoretical constructs of interest

ii. self-selection of participants into different types of neighbourhood

iii. cross-sectional

iv. defining neighbourhood boundaries – to fit the data or to fit resident’s perceptions and experience

Concluding remarks• Our findings illustrate that several determinants of obesity are not within traditional remit of healthcare sector• Private sector and non-healthcare public sector has an important role • Stronger links and even representation of public health in police force, land use planning bodies and groups

supporting local business are needed• Don’t forget individual characteristics also strongly related to obesity