Frank, L. D, Saelens, B. E, Chapman, J. E, Sallis, J. F, Kerr, J., Glanz, K., Couch, S. C, Learnihan, V., Zhou, C., Colburn, T. & Cain, KL. (2012). Objective assessment of obesogenic environments in youth: Geographic information system methods and spatial findings from the neighborhood impact on kids study. American Journal of Preventive Medicine,42(5), e47-e55. United States of America: Elsevier BV. Retrieved from https://doi.org/10.1016/j.amepre.2012.02.006
Background: GIS-based walkability measures designed to explain active travel fail to capture “playability” and proximity to healthy food. These constructs should be considered when measuring potential child obesogenic environments. Purpose: The aim of this study was to describe the development of GIS-based multicomponent physical activity and nutrition environment indicators of child obesogenic environments in the San Diego and Seattle regions. Methods: Block group–level walkability (street connectivity, residential density, land-use mix, and retail floor area ratio) measures were constructed in each region. Multiple sources were used to enumerate parks (∼900–1600 per region) and food establishments (∼10,000 per region). Physical activity environments were evaluated on the basis of walkability and presence and quality of parks. Nutrition environments were evaluated based on presence and density of fast-food restaurants and distance to supermarkets. Four neighborhood types were defined using high/low cut points for physical activity and nutrition environments defined through an iterative process dependent on regional counts of fast-food outlets and overall distance to parks and grocery stores from census block groups where youth live. Results: To identify sufficient numbers of children aged 6–11 years, high physical activity environment block groups had at least one high-quality park within 0.25 miles and were above median walkability, whereas low physical activity environment groups had no parks and were below median walkability. High nutrition environment block groups had a supermarket within 0.5 miles, and fewer than 16 (Seattle) and 31 (San Diego) fast-food restaurants within 0.5 miles. Low nutrition environments had either no supermarket, or a supermarket and more than 16 (Seattle) and 31 (San Diego) fast-food restaurants within 0.5 miles. Income, educational attainment, and ethnicity varied across physical activity and nutrition environments. Conclusions: These approaches to defining neighborhood environments can be used to study physical activity, nutrition, and obesity outcomes. Findings presented in a companion paper validate these GIS methods for measuring obesogenic environments.
Institute for Health and Ageing
Access may be restricted.