Frank LD, Saelens BE, Chapman J, Sallis JF, Kerr J, Glanz K, Couch SC, Learnihan V, Zhou C, Colburn T, Cain KL.
\nBACKGROUND: GIS-based walkability measures designed to explain active travel fail to capture \u00ab\u00a0playability\u00a0\u00bb and proximity to healthy food. These constructs should be considered when measuring potential child obesogenic environments.<\/p>\n
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.<\/p>\n
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.<\/p>\n
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.<\/p>\n
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.<\/p>\n","protected":false},"template":"","mots_cles":[],"class_list":["post-36613","resume","type-resume","status-publish","hentry"],"acf":{"adresse":"Schools of Population and Public Health and Community and Regional Planning, University of British Columbia, Vancouver, Canada","annee":"2012","mois":"5","numero":"42:5","page":"47-55","auteurs":[],"sources":[{"ID":34363,"post_author":"0","post_date":"2018-12-04 00:28:07","post_date_gmt":"2018-12-03 23:28:07","post_content":"","post_title":"AM J PREV MED","post_excerpt":"","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"am-j-prev-med-2","to_ping":"","pinged":"","post_modified":"2018-12-04 00:28:07","post_modified_gmt":"2018-12-03 23:28:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/aprifel-pp.mentalworks.biz\/fr\/source\/am-j-prev-med-2\/","menu_order":0,"post_type":"source","post_mime_type":"","comment_count":"0","filter":"raw"}]},"yoast_head":"\n