Neighbourhood food environments and body mass index among New York City adults. Issue 9 (13th July 2013)

• Record Type: Journal Article
• Authors: Stark, James H; Neckerman, Kathryn; Lovasi, Gina S; Konty, Kevin; Quinn, James; Arno, Peter; Viola, Deborah; Harris, Tiffany G; Weiss, Christopher C; Bader, Michael D M; Rundle, Andrew
• Is Part Of: Journal of epidemiology and community health. Volume 67:Issue 9(2013)
• Page Start: 736
• Page End: 742
• Publication Date: 2013-07-13
• Subjects: Public health -- Periodicals; Epidemiology -- Periodicals; 614.4
• DOI: 10.1136/jech-2013-202354
• Languages: English
• ISSNs: 0143-005X

Abstract

Abstract : Background: Studies 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). Methods: Individual 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/km 2 ) and the proportion of outlets classified as BMI-unhealthy (eg, fast food, bodegas). Results: Results 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. Conclusions: These results support a more nuanced assessment of the impact of the food environment and its association with obesity.