The nation is experiencing an obesity epidemic, with 35% of all adults classified as having obesity [1
]. However, disparities exist and obesity rates are higher in low-income populations and racial and ethnic minority groups than in socially-advantaged populations [2
]. There are also inequalities in obesity rates by geographic region, which has serious implications for exacerbating health disparities [3
]. The relationship between where people live and their risk of obesity has led to research on the relationship between one’s food environment and health.
1.1. Food Deserts and Food Swamps
“Food deserts”, defined as residential areas with limited access to affordable and nutritious food, [5
] have been posited as one driver of the obesity epidemic [6
]. Living in a food desert has been linked to a poor diet [7
] and greater risk of obesity [8
]; while people who live near a grocery store are more likely to consume fruits and vegetables and less likely to be obese [6
Food deserts are often assessed by measuring the distance between people’s homes and supermarkets [5
], which has been found to vary significantly with a neighborhood’s racial/ethnic and socioeconomic composition [12
]. To address the problem of food deserts, the Healthy Food Financing Initiative supports opening full-service grocery stores where none exist [15
]. Surprisingly, quasi-experimental and longitudinal studies evaluating the impact of opening new grocery stores have shown that while perceived access to healthy food improves, diet quality and body mass index (BMI) do not [15
]. These findings suggest that the influence of introducing healthier foods into a neighborhood may be tempered by the continued accessibility of unhealthy foods.
To capture the idea that both healthy and unhealthy food access is important, Rose and colleagues coined the term “food swamp” as a spatial metaphor to describe neighborhoods where fast food and junk food inundate healthy alternatives [19
]. Low-income and racial-ethnic minorities are more likely than Whites to live near unhealthy food retailers, which has been associated with poor diet [20
]. In a review of the research on fast food access, 10 out of 12 studies provided evidence that fast food restaurants are more likely to locate in areas where there are higher concentrations of ethnic minorities than Whites [24
]. These associations raise questions about causality and suggest that the race and ethnicity of a community shapes the actions of the food industry and community design decision makers, which in turn, influence the food environment.
Alternatively, reverse causality may occur at the individual behavior level. Observational studies tend to assume that the food environment shapes individual health behaviors and health outcomes, but not vice versa. However, individuals may self-select into neighborhoods, and it is important that studies on neighborhood food environments and obesity account for this endogeneity problem [5
]. Because it is not feasible to assign people to neighborhoods in an experimental design, statistical adjustments are necessary.
In summary, there is evidence that living in a food desert increases the risk of obesity. There is also emerging evidence that food swamps may better capture the characteristics of an obesogenic neighborhood food environment. The research to date on food swamps highlights two substantial gaps in knowledge: how to operationalize the food swamp concept for empirical analysis; and how to adjust for the possibility that obese adults choose to live in neighborhoods that are food swamps.
1.2. Study Objectives
To our knowledge, this is the first study to test relative measures of food swamps alongside food deserts as predictors of obesity rates across all United States (U.S.) counties, adjusting for reverse causality. We have three key objectives.
First, the present study makes a novel contribution by examining the countrywide existence of “food swamps” in the U.S. This builds upon previous work on food swamps abroad [33
] and studies identifying food swamps in two major U.S. cities [21
]. For instance, Hager and colleagues identified food swamps as areas in Baltimore City, with four or more convenience/corner stores within 0.25 miles of a study participant’s home.
Second, this study contributes to the literature on food swamps in the U.S. by considering the relative balance
among multiple food outlets in the environment rather than absolute metrics of grocery store or restaurant access [36
]. We examined multiple ways of categorizing food environments as food swamps, including alternate versions of the Retail Food Environment Index (RFEI) [23
]. This builds upon previous work by Colón-Ramos and colleagues, which employed a relative food environment measure to identify a food swamp in the District of Columbia and predict food acquisition behaviors among recently migrated mothers from Central America [35
]. The other studies that have used relative measures of food access were conducted outside the US, in Waterloo, Canada [33
] and Porirua, New Zealand [34
Third, this paper addresses the question of reverse causality
, which is relevant because both individuals and the builders of food outlets choose to go into certain neighborhoods. Different statistical methods have been utilized to account for unobserved characteristics that may influence where individuals and food retailers choose to locate [5
]. An increasingly common approach is to instrument for food store access with highways (counts within, or distance from, a predetermined geographic area), street connectivity or land zoned for commercial use [26
To substantiate the use of highway exits as an instrument for restaurant access, previous papers have referenced the clustering of fast food retailers near highways, independent of demand or health outcomes [26
]. With the exception of work by Dunn and colleagues using a nationally representative dataset, these studies have been limited to rural areas [26
]. We expand upon this work by accounting for fast food retail options beyond the largest national brands and controlling for food deserts. We also include a measure of the conduciveness to physical activity to address the critical role of physical activity as a correlate of obesity [26
Last, we offer an aggregated unit of analysis to facilitate policy discussions. We test the effect of food access on obesity rates by using a county-level unit of analysis [26
]. This approach complements the current literature as it is more aggregated than the local community level [27
], but less aggregated than the state level [32
]. Previous work by Dunn [26
] and Blanchard and Lyson [43
] documents significant county-level variations in access to fast food restaurants or grocery stores. Land-use and zoning policies are usually implemented at the county and city-level; therefore, our county-level assessment of this topic can potentially inform an identification strategy for municipalities that would most benefit from revising zoning policies related to the local food environment [44
The key hypotheses were that: (1) food swamps are a distinct and separate phenomenon to food deserts; and (2) food swamps have a stronger positive effect on obesity rates than food deserts, even after controlling for physical activity indicators and sociodemographic information.