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Determinants of Physical Activity in Rural, African American Adolescents. Mike Bamman, PhD.
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Transcript of Determinants of Physical Activity in Rural, African American Adolescents. Mike Bamman, PhD.
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Determinants of Physical Activity in Rural, African American Adolescents.
Mike Bamman, PhD
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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)
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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).
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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
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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
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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.
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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
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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%
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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.
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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)
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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
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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)
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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.
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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.
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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