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.
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.
Authors: Maike K Kahr; Melissa A Suter; Jerasimos Ballas; Susan M Ramin; Manju Monga; Wesley Lee; Min Hu; Cindy D Shope; Arina Chesnokova; Laura Krannich; Emily N Griffin; Joan Mastrobattista; Gary A Dildy; Stacy L Strehlow; Ryan Ramphul; Winifred J Hamilton; Kjersti M Aagaard Journal: Am J Obstet Gynecol Date: 2015-08-28 Impact factor: 8.661
Authors: Brian E Saelens; Karen Glanz; Lawrence D Frank; Sarah C Couch; Chuan Zhou; Trina Colburn; James F Sallis Journal: Obesity (Silver Spring) Date: 2018-08 Impact factor: 5.002
Authors: Shannon M Robson; Sarah C Couch; James L Peugh; Karen Glanz; Chuan Zhou; James F Sallis; Brian E Saelens Journal: J Acad Nutr Diet Date: 2016-04-01 Impact factor: 4.910
Authors: Deborah A Cohen; Bing Han; Kathryn P Derose; Stephanie Williamson; Terry Marsh; Laura Raaen; Thomas L McKenzie Journal: Environ Behav Date: 2016-01
Authors: Stephanie Kneeshaw-Price; Brian E Saelens; James F Sallis; Karen Glanz; Lawrence D Frank; Jacqueline Kerr; Peggy A Hannon; David E Grembowski; C Gary Chan K; Kelli L Cain Journal: Pediatr Exerc Sci Date: 2013-07-12 Impact factor: 2.333