Neighborhood Food Environment and Walkability Predict Obesity in New York City

Andrew Rundle; Kathryn M. Neckerman; Lance Freeman; Gina S. Lovasi; Marnie Purciel; James Quinn; Catherine Richards; Neelanjan Sircar; Christopher Weiss2

Disclosures

Environ Health Perspect. 2009;117(3):442-447. 

In This Article

Abstract and Introduction

Abstract

Background: Differences in the neighborhood food environment may contribute to disparities in obesity.
Objectives: The purpose of this study was to examine the association of neighborhood food environments with body mass index (BMI) and obesity after control for neighborhood walkability.
Methods: This study employed a cross-sectional, multilevel analysis of BMI and obesity among 13,102 adult residents of New York City. We constructed measures of the food environment and walkability for the neighborhood, defined as a half-mile buffer around the study subject's home address.
Results: Density of BMI-healthy food outlets (supermarkets, fruit and vegetable markets, and natural food stores) was inversely associated with BMI. Mean adjusted BMI was similar in the first two quintiles of healthy food density (0 and 1.13 stores/km2, respectively) , but declined across the three higher quintiles and was 0.80 units lower [95% confidence interval (CI) , 0.27–1.32] in the fifth quintile (10.98 stores/km2) than in the first. The prevalence ratio for obesity comparing the fifth quintile of healthy food density with the lowest two quintiles combined was 0.87 (95% CI, 0.78–0.97) . These associations remained after control for two neighborhood walkability measures, population density and land-use mix. The prevalence ratio for obesity for the fourth versus first quartile of population density was 0.84 (95% CI, 0.73–0.96) and for land-use mix was 0.91 (95% CI, 0.86–0.97) . Increasing density of food outlets categorized as BMI-unhealthy was not significantly associated with BMI or obesity.
Conclusions: Access to BMI-healthy food stores is associated with lower BMI and lower prevalence of obesity.

Introduction

The United States faces an epidemic of overweight and obesity (Ogden et al. 2006). Analyses of National Health and Nutrition Examination Survey data for 1999–2004 show that 32% of Americans > 20 years of age are obese (Ogden et al. 2006). New York City Department of Health and Mental Hygiene statistics show that New York City, our study site, likewise faces high rates of overweight/obesity (Roberts et al. 2005). There is a growing understanding that the availability of residential neighborhood resources that support physical activity and healthy food choices may influence obesity rates (Larkin 2003; Rao et al. 2007).

Previous studies linking food environment measures with dietary intake or obesity have found mixed results. Proximity to supermarkets has been positively associated with consumption of a healthy diet (Laraia et al. 2004; Morland et al. 2002; Zenk et al. 2005) and negatively associated with overweight or obesity (Morland et al. 2006). Individuals with access to lower-priced fruits and vegetables have a lower body mass index (BMI) (Sturm and Datar 2005), whereas those living near convenience stores have higher rates of overweight and obesity (Morland et al. 2006). To date, however, there is no evidence that proximity to fast-food restaurants influences diet or obesity risk (Burdette and Whitaker 2004; Jeffery et al. 2006; Liu et al. 2007). Most analyses relating the density of other types of restaurants or grocery stores to BMI or obesity risk found no significant association (Jeffery et al. 2006; Liu et al. 2007; Powell et al. 2007; Sturm and Datar 2005).

Two concerns can be raised about this existing literature. First, most analyses do not control for built environment characteristics, such as land-use mix and population density, associated with pedestrian travel and lower BMI, which also tend to covary with density of retail food outlets (Rundle et al. 2007). Second, with a few exceptions (e.g., Morland et al. 2006), most studies relating the food environment to diet or body weight focus on just a few types of food outlets rather than considering the food environment as a whole. Because density measures for different types of food outlets are likely to be correlated with each other and with commercial space availability in general, their individual associations with BMI may be difficult to disentangle.

In this study we related the food environment to BMI and obesity in New York City. Addressing the concerns noted above, the analysis controls for neighborhood and built environment features already shown to influence BMI and includes measures of all restaurants, grocery stores, and specialty food vendors in the city (Rundle et al. 2007). To address problems of multicollinearity raised by simultaneous inclusion of a large number of food outlet measures, we constructed density measures for three food environment categories: BMI-healthy food outlets such as supermarkets and fruit and vegetable markets, BMI-unhealthy food outlets such as fast-food restaurants and convenience stores, and a BMI-intermediate category.

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