{"id":60242,"date":"2013-09-01T00:00:00","date_gmt":"2018-12-04T07:36:22","guid":{"rendered":"https:\/\/aprifel-pp.mentalworks.biz\/fr\/resume-scientifique\/neighbourhood-food-environments-and-body-mass-index-among\/"},"modified":"2018-12-04T08:36:22","modified_gmt":"2018-12-04T07:36:22","slug":"neighbourhood-food-environments-and-body-mass-index-among","status":"publish","type":"resume","link":"https:\/\/aprifel-pp.mentalworks.biz\/fr\/resume-scientifique\/neighbourhood-food-environments-and-body-mass-index-among\/","title":{"rendered":"Neighbourhood food environments and body mass index among New York City adults."},"content":{"rendered":"

BACKGROUND<\/strong>
\nStudies evaluating the impact of the neighbourhood food environment on obesity have summarised the density or proximity of individual food outlets. Though informative, there is a need to consider the role of the entire food environment; however, few measures of whole system attributes have been developed. New variables measuring the food environment were derived and used to study the association with body mass index (BMI).<\/p>\n

METHODS<\/strong>
\nIndividual data on BMI and sociodemographic characteristics were collected from 48 482 respondents of the 2002-2006 community health survey in New York City and linked to residential zip code-level characteristics. The food environment of each zip code was described in terms of the diversity of outlets (number of types of outlets present in a zip code), the density of outlets (outlets\/km²) and the proportion of outlets classified as BMI-unhealthy (eg, fast food, bodegas).<\/p>\n

RESULTS<\/strong>
\nResults of the cross-sectional, multilevel analyses revealed an inverse association between BMI and food outlet density (-0.32 BMI units across the IQR, 95% CI -0.45 to -0.20), a positive association between BMI and the proportion of BMI-unhealthy food outlets (0.26 BMI units per IQR, 95% CI 0.09 to 0.43) and no association with outlet diversity. The association between BMI and the proportion of BMI-unhealthy food outlets was stronger in lower (<median for % poverty) poverty zip codes than in high-poverty zip codes.<\/p>\n

CONCLUSIONS<\/strong>
\nThese results support a more nuanced assessment of the impact of the food environment and its association with obesity.<\/p>\n","protected":false},"template":"","mots_cles":[],"class_list":["post-60242","resume","type-resume","status-publish","hentry"],"acf":{"adresse":"Division of Epidemiology, New York City Department of Health and Mental Hygiene, New York, NY, USA.","annee":"2013","mois":"9","numero":"67:9","page":"736-742","auteurs":[{"ID":60236,"post_author":"0","post_date":"2018-12-04 08:36:16","post_date_gmt":"2018-12-04 07:36:16","post_content":"","post_title":"James H Stark","post_excerpt":"","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"james-h-stark","to_ping":"","pinged":"","post_modified":"2018-12-04 08:36:16","post_modified_gmt":"2018-12-04 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