These results support the idea that travel distance to supermarkets is associated with obesity and fruit and vegetable intake in adults, but they highlight important differences in these relationships between metropolitan and nonmetropolitan areas. We found that distance to supermarket had positive associations with obesity and negative associations with fruit and vegetable consumption in metropolitan areas, but not in nonmetropolitan areas. The prevalence of obesity was higher in nonmetropolitan areas than in metropolitan areas, and this fact may be in part due to the longer distances to supermarkets in nonmetropolitan areas.
Although obesity and fruit and vegetable consumption were analyzed separately, the increased likelihood of obesity with longer distance to supermarket that was seen in metropolitan areas may be related to the decreased likelihood of consuming fruit and vegetables with longer distance to supermarket. Our findings indicated, however, that distance to supermarket was not associated with either obesity or fruit and vegetable consumption in nonmetropolitan areas. Physical distance to reach supermarkets likely has a different impact in metropolitan and nonmetropolitan areas. For example, traveling for a few miles may take longer in congested urban areas than in rural areas with less traffic. Thus, the role of supermarket accessibility measured by distance in the food environment appears to be fundamentally different in urban- versus rural-dominated environments.
One possible explanation for the lack of association of supermarket distance with obesity and fruit and vegetable consumption in nonmetropolitan areas is differences in transportation infrastructure and travel behavior compared to metropolitan areas. Inner-city residents make the most trips, but their trips have the shortest durations and they spend the least time in travel, whereas residents of commuter belt areas beyond the suburbs make fewer trips, but their trips have the longest durations and they spend the most time in travel [54
]. Similarly, rural populations travel further and spend more time travelling for medical care than urban populations do, and distance traveled and time spent in travel are inversely related to population density [55
]. These differences could explain the higher obesity and lower fruit and vegetable consumption in nonmetropolitan areas than in metropolitan areas if the residents of these rural areas make fewer trips to supermarkets, and as a result, purchase more processed foods and fewer perishable food items elsewhere as alternative diets.
Because of limited public transportation, rural residents rely on private automobiles for most travel needs, regardless of age, race, and income, whereas urban and suburban residents with good access to public transportation and mixed land use have lower automobile ownership [54
]. Despite having to drive long distances, rural residents may not vary greatly in their ability to reach various types of services, including grocery shopping. Private automobiles allow rural residents to travel to reach services according to their own schedules. Variability in distance to supermarkets in nonmetropolitan areas, therefore, may not translate into differences in higher obesity prevalence and lower fruit and vegetable consumption. In contrast, supermarket distance may have a greater impact on food shopping behavior in metropolitan areas if urban residents do not own private automobiles and are dependent on public transportation. For example, if supermarkets are scarce in low-income urban neighborhoods, then residents of these neighborhoods would have less access to healthy foods if they cannot reach supermarkets while stores are open.
In many nonmetropolitan areas, residents may have limited accessibility to healthy food, but accessing supermarkets may not impose a greater burden if communities make efforts to change the local food infrastructures. Some unique characteristics of nonmetropolitan areas may contribute to the weaker association of distance to supermarkets with obesity and healthy food consumption. For example, availability of alternative local sources of fruit and vegetables through nonconventional food-selling environments, such as farmer's markets, fruit and vegetable stands, home gardens, and general merchandise stores, may reduce the importance of supermarket accessibility in determining diet and health [31
]. In addition, direct exchange of food among rural residents through personal connections and community social capital, such as distributing foods through rural churches and community centers, has been reported in some areas where few or no grocery stores exist [41
]. Furthermore, an important element of the urban food desert concept is that decreased access to supermarkets and other sources of healthy food occurs in conjunction with increased access to convenience stores, fast-food restaurants, and other sources of unhealthy foods [19
]. It may be that in many nonmetropolitan areas, residents have limited accessibility to all sources of food, and accessing supermarkets is not more difficult than accessing alternative sources of unhealthy food.
Another important assumption of supermarket accessibility research is that larger supermarkets provide a more extensive and affordable selection of healthy foods than smaller supermarkets [18
]. Although we examined three-size classes of supermarkets, we found no store size effects on the prevalence of obesity in either the metropolitan or nonmetropolitan area models, as well as for F/V consumption, except for the large/medium/small supermarkets combined model. However, we did not directly quantify food selections or prices in these three sizes of supermarkets. If supermarkets in nonmetropolitan areas do not provide as wide a selection of fruit and vegetables as supermarkets in metropolitan areas, the supermarkets may have a weaker relationship to the food environment in nonmetropolitan areas.
The significant positive association of obesity with distance to supermarket in metropolitan areas may also reflect the indirect impacts of suburban sprawl. Within metropolitan areas, urban-dominated counties in the core central cities typically had shorter distances to supermarkets, whereas outlying counties had longer distances. Newer suburban housing developments are typically oriented toward automobile travel, which leads to the increased risk of obesity due to limited connectivity and walkability between residential and commercial locations [61
]. At the metropolitan area level, an index of urban sprawl was a significant predictor for the risk of being overweight and obese among adults [64
]. In addition, there was an association between travel distance by automobiles and obesity in California [65
] and each additional hour spent in a car per day was also associated with increase in the likelihood of obesity in Georgia [66
]. These studies provide some evidence that suburban sprawl forces people to travel by automobiles and it discourages physical activity, which in turn, contributes to the increased risk of obesity. Our findings in the metropolitan area models are consistent with such suburban sprawl hypotheses if the distance to supermarket is considered a proxy for time spent in a car.
Caveats and limitation
Analyses using data drawn from telephone surveys may be subject to bias because BMI and F/V consumption measures in the BRFSS are based on individuals' recall. Studies showed that population-level bias in self-reported height and weight was larger in telephone surveys, compared to in-person interviews that involved physical examinations. BRFSS underestimates the overall prevalence of overweight and obesity, and this bias could be attributed to such survey mode effects [67
]. Our study, however, focused on studying the correlates of spatial variability in obesity rather than precisely quantifying the prevalence of obesity from multiple databases, and these self-reporting biases should not influence our ability to detect these relationships. In addition we only examined one broad metric of healthy food consumption (the number of daily servings of fruit and vegetables). Different results could be obtained based on more detailed measurements on the quality and quantity of healthy food consumption [69
The advantage of using the BRFSS data for this analysis was the availability of a representative sample covering virtually all counties within the conterminous United States. However, because counties are the finest geographic resolution at which the BRFSS data can be obtained, we had to summarize distance to supermarket as a population-weighted mean at the county level. In our analyses, this statistic was assumed to define the food environment for all individuals within the county. In reality, most counties encompass a mixture of neighborhoods with varying scales of supermarket accessibility, and this variability is not captured by our county-level indices. Different results could, therefore, be obtained by more localized analyses accounting for neighborhood and household effects.
Because we obtained supermarket data from the Zip Code Business Patterns dataset classified by the NAICS, we geocoded supermarkets to the population-weighted centroid of each ZCTA. Population-weighted centroids generally fall within the largest town or a segment of a city in the ZCTA, which is where supermarkets and other large retail stores are most likely to be located. Although we did not have the exact spatial locations of supermarkets, this lack of precision is probably not critical because distances were aggregated at the county level. More detailed, localized studies based on geocoded street addresses of individual residences and supermarkets in rural areas are needed in order to corroborate the results of this study, and provide additional insights into the proximal effects of supermarket accessibility in rural areas.
In addition, industry classification systems may be increasingly irrelevant as local economies become more diversified. Business establishments may involve sector changes, and newly emerging firms may not be recognized by existing classifications [70
]. Despite this limitation, a study showed that business listings provided by commercial databases based on the NAICS and direct observations of business establishments were highly compatible at the neighborhood level [71
]. Although rural areas may be associated with greater uncertainty for business existence and operations, the NAICS is a standardized business classification used by Federal statistical agencies for analyzing the U.S. economy.