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Am J Prev Med. 2012 May;42(5):e47-55. doi: 10.1016/j.amepre.2012.02.006.

Objective assessment of obesogenic environments in youth: geographic information system methods and spatial findings from the Neighborhood Impact on Kids study.

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  • 1Schools of Population and Public Health and Community and Regional Planning, University of British Columbia, Vancouver, Canada. ldfrank@exchange.ubc.ca

Abstract

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.

Copyright © 2012 American Journal of Preventive Medicine. All rights reserved.

PMID:
22516503
[PubMed - indexed for MEDLINE]
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