Community-level risk associated with overweight and obesity in the District of Columbia

Introduction

In 2007, 22% of the District of Columbia adults were classified as obese, and 33% as overweight. This obesity rate is higher than the Healthy People 2010 goal of 15%. African Americans were more likely to be obese (35%) compared with Hispanics (22%), and Caucasians (9%). Poor dietary patterns and obesity have been linked to the surrounding environment in under-resourced neighborhoods and neighborhoods of higher minority composition. The neighborhood differences in access to food may contribute to disparities in obesity.

Objective

To determine the effect of environmental factors, such as the distribution of food purchasing options, and ward of residence, on increased risk for obesity.

Methodology

Data on fruit and vegetable consumption and obesity were obtained from the 2007 District of Columbia BRFSS data set, and analyzed using SAS version 9.1 (SAS Institute Inc, Cary, NC). Data on locations of food purchasing options were obtained from the DC Food and Hygiene Inspection Services and mapped by ward. To assess the dispersion of establishments and obesity prevalence, Pearson's correlation coefficients were calculated and spatial analysis was conducted using ArcView GIS 9.2. Moran's I was calculated to determine spatial correlations between locations and obesity rates.

Results

Since 2000, the rate of overweight and obesity in the District of Columbia has slowly increased. In 2007, ward 3 had the lowest percentage of obesity (11.7%), while Ward 8, the highest (42%). Positive correlations were seen between grocery store and fast food locations (r=0.72, p=0.04), and fast food and dine-in restaurant locations (r=0.97, p<0.0001). Additionally, positive correlations were seen between the locations of farmer's markets and convenience stores (r=0.80, p=0.02), and famer's markets and fast food restaurants (r=0.88, p=0.003). Some observed clustering of dine-in restaurants and organic markets may be due to random chance (Moran's I=0.08 z-stat=1.07 and Moran's I=0.18 z-stat=1.25, respectively).

Conclusion

These findings suggest evidence of ethnic and socio-economic differences among various wards. Reversing the obesity epidemic will require an all-inclusive synchronized approach, community design and environmental changes to transform communities in the District of Columbia into places that sustain, and promote healthy lifestyle choices for all residents.