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Determinants of Physical Activity in Rural, African American Adolescents.

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)

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Determinants of Physical Activity in Rural, African American Adolescents.

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  1. Determinants of Physical Activity in Rural, African American Adolescents. Mike Bamman, PhD

  2. 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)

  3. 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).

  4. 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

  5. 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

  6. 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.

  7. 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

  8. Tunica County, MS (2000, US Census) • Predominantly African American - 70%

  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.

  10. 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

  11. 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

  12. 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

  13. 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

  14. Results – Descriptives

  15. Results – Frequencies females n = 43, males n = 41

  16. Correlation of PA measures ap<0.05

  17. Results – Validation of PA measures ap<0.05

  18. Results – Correlations, Females

  19. Results – Regression, Females n = 43; aStandardized Beta Coefficient; bUnstandardized Beta Coefficient

  20. Results – Correlation, Males

  21. Results – Regression, Males n = 41; aStandardized Beta Coefficient; bUnstandardized Beta Coefficient

  22. 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

  23. Results – Chow test

  24. 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. R2 = 0.34 R2 = 0.26

  25. 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

  26. 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

  27. 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. R2 = 0.34 R2 = 0.295

  28. 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)

  29. 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

  30. 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)

  31. 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.

  32. 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.

  33. 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

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