Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2017 Nov 14;14(11):1366.
doi: 10.3390/ijerph14111366.

Food Swamps Predict Obesity Rates Better Than Food Deserts in the United States

Affiliations

Food Swamps Predict Obesity Rates Better Than Food Deserts in the United States

Kristen Cooksey-Stowers et al. Int J Environ Res Public Health. .

Abstract

This paper investigates the effect of food environments, characterized as food swamps, on adult obesity rates. Food swamps have been described as areas with a high-density of establishments selling high-calorie fast food and junk food, relative to healthier food options. This study examines multiple ways of categorizing food environments as food swamps and food deserts, including alternate versions of the Retail Food Environment Index. We merged food outlet, sociodemographic and obesity data from the United States Department of Agriculture (USDA) Food Environment Atlas, the American Community Survey, and a commercial street reference dataset. We employed an instrumental variables (IV) strategy to correct for the endogeneity of food environments (i.e., that individuals self-select into neighborhoods and may consider food availability in their decision). Our results suggest that the presence of a food swamp is a stronger predictor of obesity rates than the absence of full-service grocery stores. We found, even after controlling for food desert effects, food swamps have a positive, statistically significant effect on adult obesity rates. All three food swamp measures indicated the same positive association, but reflected different magnitudes of the food swamp effect on rates of adult obesity (p values ranged from 0.00 to 0.16). Our adjustment for reverse causality, using an IV approach, revealed a stronger effect of food swamps than would have been obtained by naïve ordinary least squares (OLS) estimates. The food swamp effect was stronger in counties with greater income inequality (p < 0.05) and where residents are less mobile (p < 0.01). Based on these findings, local government policies such as zoning laws simultaneously restricting access to unhealthy food outlets and incentivizing healthy food retailers to locate in underserved neighborhoods warrant consideration as strategies to increase health equity.

Keywords: fast food retail; food deserts; food environments; food swamps; instrumental variables; obesity; zoning.

PubMed Disclaimer

Conflict of interest statement

The authors declare no conflict of interest.

Similar articles

Cited by

References

    1. Centers for Disease Control and Prevention . Behavioral Risk Factor Surveillance System Survey Data. U.S. Department of Health and Human Services, Centers for Disease Control and Prevention; Atlanta, GA, USA: 2009.
    1. Glickman D. Accelerating Progress in Obesity Prevention: Solving the Weight of the Nation. National Academies Press; Washington, DC, USA: 2012. - PubMed
    1. Hill J.O., Wyatt H.R., Melanson E.L. Genetic and environmental contributions to obesity. Med. Clin. N. Am. 2000;84:333–346. doi: 10.1016/S0025-7125(05)70224-8. - DOI - PubMed
    1. Slack T., Myers C.A., Martin C.K., Heymsfield S.B. The geographic concentration of U.S. adult obesity prevalence and associated social, economic, and environmental factors. Obesity. 2014;22:868–874. doi: 10.1002/oby.20502. - DOI - PubMed
    1. Ver Ploeg M., Breneman V., Farrigan T., Hamrick K., Hopkins D., Kaufman P., Lin B., Nord M., Smith T.A., Williams R. Access to Affordable and Nutritious Food: Measuring and Understanding Food Deserts and Their Consequences. United States Department of Agriculture Economic Research Service; Washington, DC, USA: 2009.