OBJECTIVE: To examine the individual, behavioral, social and built environment correlates of body mass index (BMI) in an Australian adult population. METHOD: Using data from 2003 to 2005 on 1151 participants in the RESIDential Environments project (RESIDE), Perth, Western Australia, linear regression was used to construct multivariate models to examine the variance in BMI explained by significant socio-demographic, environmental and health behavior variables. Both self-report and GIS-derived measures of the built environment were examined. RESULTS: Age, gender, hours of work, total physical activity, sedentary leisure time and dietary fat were all associated with BMI (p≤0.05). BMI was not associated with any objective measures of the built environment or social capital, social cohesion or dog ownership but was independently associated with one perceived environment measure (perceived safety from crime). Overall, 3.3% of the variance in BMI was explained by socio-demographic factors, a further 2.7% by health behaviors and a further 1.5% by perceived environment factors. CONCLUSION: Whilst evidence mounts of built environment correlates to physical activity, the demonstrated translation of these effects on BMI remain more elusive. Nevertheless, built environment factors that constrain physical activity warrant further exploration.
OBJECTIVE: To examine the individual, behavioral, social and built environment correlates of body mass index (BMI) in an Australian adult population. METHOD: Using data from 2003 to 2005 on 1151 participants in the RESIDential Environments project (RESIDE), Perth, Western Australia, linear regression was used to construct multivariate models to examine the variance in BMI explained by significant socio-demographic, environmental and health behavior variables. Both self-report and GIS-derived measures of the built environment were examined. RESULTS: Age, gender, hours of work, total physical activity, sedentary leisure time and dietary fat were all associated with BMI (p≤0.05). BMI was not associated with any objective measures of the built environment or social capital, social cohesion or dog ownership but was independently associated with one perceived environment measure (perceived safety from crime). Overall, 3.3% of the variance in BMI was explained by socio-demographic factors, a further 2.7% by health behaviors and a further 1.5% by perceived environment factors. CONCLUSION: Whilst evidence mounts of built environment correlates to physical activity, the demonstrated translation of these effects on BMI remain more elusive. Nevertheless, built environment factors that constrain physical activity warrant further exploration.
Authors: Anna M Adachi-Mejia; Chanam Lee; Chunkuen Lee; Heather A Carlos; Brian E Saelens; Ethan M Berke; Mark P Doescher Journal: Prev Med Date: 2017-03-23 Impact factor: 4.018
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