Determinants of Physical Activity in Rural, African American Adolescents.

Mike Bamman, PhD

Health risks in children and adolescents - overweight and obesity 13% of adolescents obese, 15% overweight

(CDC, 2008)

60% of overweight (<85%, BMI) children had at least one cardiovascular risk factor compared to 10% of normal weight. 25% had two or more risk factors. (Freedman, Dietz, Srinivasan, and

Berenson, 1999)

Independent predictor for developing HTN, NIDDM, CHOL, beginning in childhood (Berenson et al., 1998)

Health risks in children and adolescents HTN – Obese children have a 9x risk (Lauer, Connor, & Leaverton,

1975)

NIDDM – Relationship between PA and insulin resistance in obese youth. (Pinhas-Hamiel, Dolan, Daniels, Standiford, Khoury, & Zeitler, 1996; Schmitz, Jacobs, Hong, Steinberger, Moran, & Sinaiko, 2002; Quarry-Horn, et al, 2003).

CHOL 90 percent of the children with elevated TG were also

overweight. A strong positive relationship exists between physical

activity (PA) levels and HDL cholesterol. (Armstrong & Simmons-Morton,

1994; Riddoch & Boreham, 1995; Freedman, Dietz, Srinivasan, and Berenson, 1999; Twisk, 2000).

Adolescent PA levels (2007 YRBS)

Nationwide adolescent PA levels Only 37% of students grade 9-12 meet PA guidelines Over 22% of students are sedentary Only 30% (32%, 2003) receive daily physical education

Mississippi adolescent PA levels 36% meet PA guidelines 23% are sedentary 23% receive daily PE

Determinants of PA in adolescents Self efficacy – Reynolds, et al, 1990;Zakarian, Hovell, Hofstetter,

Salles, & Keating, 1994 & Trost, et al, 1997; Dwyer et al, 1998; Allison, Dwyer, Makin, May 1999.

Barriers to PA - Allison, Dwyer, Makin, August 1999

Sex differences - Aaron, et al, 1993; Garcia, et al, 1995; Trost, et al, 2000

Age differences - Aaron, 1993; Saris, Elvers, Van’t Hof & Binkhorst, 1986; Verschuur & Kemper, 1985; Allison, Dwyer, & Makin, May, 1999; Trost, et al, 2002

BMI - Berkowitz, 1984

Purpose

The purpose of this study was to identify the determinants of PA in African-American schoolchildren ages 12-19 in Tunica County, Mississippi. A secondary function of this study was to determine the relationships among and identify any differences between recognized determinants of PA (body mass index, age, perceived barriers to exercise, and self-efficacy) of the students.

Significance

The results of this study will allow researchers, school officials, community leaders, and parents to better understand the possible determinants of PA in African-American adolescents in Tunica County, Mississippi. This research will also make a significant contribution to the existing literature relating to determinants of PA in African American adolescents

Tunica County, MS (2000, US Census)

Predominantly African American - 70%

Tunica County US

Median Household Income (per year) $19,000 $37,000

Poverty (% of families living at or below the HHS poverty threshold)

27% 13%

Undereducated (% of persons >25 yrs with a HS diploma)

24% 54%

Unemployed (February, 2009) 17.8% 8.9%

Hypotheses

To address the purpose of the study the following null hypotheses were tested.

There is no significant relationship between level of PA and perceived self-efficacy, perceived barriers to exercise, age, and BMI for males.

There is no significant relationship between level of PA and perceived self-efficacy, perceived barriers to exercise, age, and BMI for females.

Instrumentation Physical Activity

MTI (Manufacturing Technology Inc) accelerometer (Trost, Pate, Freedson, Sallis & Taylor, 2000)(r = 0.87)

7-day physical activity recall – PAR (Wallace, McKenzie & Nader, 1985; Sallis, Buono, Roby, Micale & Nelson, 1993; Blair, et al, 1998; Dunn, et al, 1997)(r = 0.81)

Self-efficacy (SE)– subset of SAHHS questionnaire (Reynolds, et al, 1990)(r = 0.89)

Barriers to PA – Campbell’s well-being questionnaire (Stephens, Craig, 1990; Allison, Dwyer & Makin, 1999)(r = 0.76)

BMI, Age

Procedures Permission – IRB (#04-081), Tunica County

Schools, NMDBGC Session 1 - Program description, handouts

(program, MTI), parental consent form Session 2 - Student verbal/written assent, study

procedures review, instruments (medical history/demographic data form, SAHHS, Campbell, BMI), MTI and log book, contact information

Intermediate - Phone calls, incentive distribution Session 3 - MTI and logbook collection, feedback

information, incentive distribution

Statistics

Means and standard errors Correlation of PA instruments Stepwise multiple regression

Equations for both males and females Chow test Alpha level set at 0.05 a priori

Subjects AA Adolescents - Tunica County, MS

Age 12-19; Grades 8-12 (975 enrolled)

Rosa Fort High School Physical Education Classes (Total Enrollment 168 – 5 classes)

North MS Delta Boys and Girls Club (Total Enrollment 78)

Sample size: > 40 males and >40 females Based upon power analysis = alpha 0.05, power of 0.80 and

an effect size of 0.25 Total Students Eligible - 246 Total Parental Consents Returned - 172 Total Subjects Initiating Protocol - 141 Total Subjects Completing Protocol – 84

Females n = 43; Males n = 41

Results – DescriptivesMean SE Min Max

M F M F M F M F

Age 15.4 16.2 0.25 0.21 12 14 18 19

BMI 24.9 25.1 0.93 0.97 16.6 18.2 46.4 54.8

SE 32.9 31.7 1.31 1.32 8 8 48 48

Barriers to PA 38.8 47.3 2.17 1.47 15 28 70 66

PAR 6894 6303 328.2 351.2 3645 3548 12942 14046

MTI 4593 2818 410.8 182.7 1148 1127 14002 6352

males n = 41, females n = 43

Results – FrequenciesFrequency Percent of Total

Free Lunch F M F MYes 35 29 81.4 70.7

No 8 12 18.6 29.3

Current Sport F M F MYes 0 17 0 41.5

No 43 24 100.0 58.5

Usual Act. Level F M F MMore 9 10 20.9 24.4

Less 11 6 25.6 14.6

About the same 23 25 53.5 61

females n = 43, males n = 41

Correlation of PA measures

Instrument N Mean SE Pearson r

PAR (kcal/wk) 84 6,592 241.6 0.90a

PAR (METs/wk) 84 10,137 382.9

MTI (kcal/wk) 84 3,685 240.5 0.67a

MTI (METs/wk) 84 5,582 367.7

ap<0.05

Results – Validation of PA measures

Instrument N Mean SE Pearson r

PAR (kcal/wk) 84 6892 241.54 0.57a

MTI (kcal/wk) 84 3685 240.47

ap<0.05

Results – Correlations, FemalesAge BMI SAHHP Barriers

to PAPAR MTI

Age 1.0 0.372a -0.056 0.070 0.101 0.151

BMI 0.372a 1.0 0.148 0.154 0.508a 0.203

SE -0.056 0.148 1.0 0.179 0.411a 0.137

Barriers to PA

0.070 0.154 0.179 1.0 0.241 0.064

PAR 0.101 0.508a 0.411a 0.241 1.0 0.412a

MTI 0.151 0.203 0.137 0.064 0.412a 1.0

n = 43; ap<0.05

Results – Regression, Females βa βb R2 F p

Step 1

BMI 0.508 184.39 0.258 14.23 0.001

Step 2

βa βb R2 F p R2∆

BMI 0.457 165.98

SE 0.343 91.54 0.373 11.89 0.001 0.115

n = 43; aStandardized Beta Coefficient; bUnstandardized Beta Coefficient

Results – Correlation, MalesAge BMI SAHHP Barriers

to PAPAR MTI

Age 1.0 0.289 -0.014 0.226 0.426a 0.387a

BMI 0.289 1.0 0.085 -0.137 0.543a 0.360a

SE -0.014 0.085 1.0 0.050 0.102 0.096

Barriers to PA

0.226 -0.137 0.050 1.0 -0.005 0.093

PAR 0.426a 0.543a 0.102 -0.005 1.0 0.735a

MTI 0.387a 0.360a 0.096 0.093 0.735a 1.0

n = 41; ap<0.05

Results – Regression, Males βa βb R2 F p

Step 1

BMI 0.543 192.55 0.295 16.31 0.000

Step 2

βa βb R2 F p R2∆

BMI 0.458 162.44

Age 0.294 394.56 0.347 11.349 0.000 0.097

n = 41; aStandardized Beta Coefficient; bUnstandardized Beta Coefficient

Results – Chow test formula

Used traditionally in economics. Assesses the equality between sets of coefficients in two

linear regression equations.

F = [SSe(M/F)a – SSe(M)b – SSe(F)c ] / pd

[SSe(M)b + SSe(F)c ] / (ne +mf -2pd)

aStandard regression analysis, both groups bStandard regression analysis, males cStandard regression analysis, females dParameters (#IV +1) eFemale n fMale n

Results – Chow test

Group R2

Standardized Beta Coefficients

Chow Test

FcvAge BMI SE Barriers

to PA

Males 0.38 0.30a 0.45a

Females 0.39 0.47a 0.32a 1.849 2.37

Males n= 41; females n = 43ap<0.05

Discussion – Female PA

Significant Predictors of PA level BMI accounts for 26% of the variance in PA

level SE and BMI account for 34% of the variance in

PA level.

PARBMI R2 = 0.26

BMI

PARSE

R2 = 0.34

Discussion – Females

Nonsignificant results were found for PAR and barriers to PA (r = 0.101, p = 0.518)

Barriers to PA Found to be predictive in 9th grade female students.

Expected r is negative. Specific barriers – Internal vs External Recent research has assessed barriers in:

Urban setting Minorities – Hispanic and African American

Discussion – Females

Nonsignificant results were found for PAR and age (r = 0.241, p = 0.119)

Age Found to decrease sig. after 12 years. Expected r is

negative. 30% (6 of 18) of subjects ages 17-19 had PAR scores

at or above +1 SEM. The most active subjects were 17 and 18 years old

Discussion – Males PA

Significant Predictors of PA level BMI accounts for 29.5% of the variance in PA

level Age and BMI account for 34% of the variance

in PA level.

PARBMI R2 = 0.295

BMI

PARAge

R2 = 0.34

Discussion – Males

Nonsignificant results were found for PAR and SE (r = 0.102, p = 0.527)

Maximum possible range 8-48, both min. and max. score were reached

Outliers removed (5 subjects) - (r = 0.305, p<0.05)

Discussion – Males

Nonsignificant results were found for PAR and barriers to PA (r = -0.005, p = 0.977)

Barriers to PA Found to be predictive in 9th grade male students.

Expected r is negative. Specific barriers – Internal vs External Recent research has assessed barriers in:

Urban setting Minorities – Hispanic and African American

Discussion – Chow test Results

F (5, 74) = 1.85, Fcv = 2.37

Significance Males /Females – BMI (β= - 0.45, p<0.05; β = 0.47,

p<0.05) Males – Age (β = 0.49, p<0.05) Females – SE (β = 0.32, p<0.05)

Nonsignificance Males/Females – barriers to PA (β= -0.01, p = 0.92; β =

0.12, p = 0.37) Males – SE (β= 0.07, p = 0.61) Females – Age (β= -0.06, p = 0.65)

Conclusions

Females PA predicted by BMI and SE. Nonsignificant relationships found between PA

and barriers to PA and age. Ho1: There is no significant relationship between

level of PA and perceived self-efficacy, perceived barriers to exercise, age, and BMI for females.

Ha1: Females’ level of PA will be influenced by their level of perceived self-efficacy, followed by the perceived barriers to pa, followed by age, and BMI.

Conclusions

Males PA predicted by BMI and age. Nonsignificant relationships found between PA

and barriers to PA and SE. Ho2: There is no significant relationship between

level of PA and perceived self-efficacy, perceived barriers to exercise, age, and BMI for males.

Ha2: Males’ level of PA will be influenced by their level of perceived self-efficacy, followed by the perceived barriers to pa, followed by age, and BMI.

Recommendations

Random selection of subjects Interview process for 7-day PAR Additional measures assessing barriers to PA

and SE Comparison of internal vs external barriers to

PA