Our results show that neighborhoods differ in the types of food stores that are available, and that the location of food stores is associated with neighborhood racial/ethnic and socioeconomic composition. Predominantly White and wealthier areas were found to have more supermarkets than were predominantly minority and poorer areas after we accounted for population and geographic size. In contrast, small grocery stores were more common in predominantly minority areas and in poorer areas. In general, poorer areas and non-White areas also tended to have fewer fruit and vegetable markets, bakeries, specialty stores, and natural food stores. Liquor stores were more common in poorer than in wealthier areas.
In a study of 4 areas (of which 1 was Forsyth County, NC, also included in these analyses), Morland et al. also found that significantly more supermarkets were located in White than in Black neighborhoods and that smaller grocery stores were more common in Black neighborhoods. Sloane et al. also reported that a higher proportion of convenience stores and small grocery stores were in predominantly minority communities than were in predominantly White neighborhoods. To the extent that supermarkets offer a broader choice of affordable healthy foods, these patterns could have consequences for the diets of residents.
By examining a range of different types of stores, we showed that the pattern is significantly more complex than simply fewer supermarkets and more small grocery stores in predominantly minority neighborhoods. Minority and poor neighborhoods also had proportionately fewer bakeries, natural food stores, and specialty stores. Predominantly Black neighborhoods had fewer fruit and vegetable markets in 2 of the 3 sites. In contrast, meat and fish markets were more common in minority neighborhoods in New York and North Carolina and in poor neighborhoods generally. Convenience stores were more common in minority neighborhoods in New York. In general, the food environment appears to be less diverse in poor and minority neighborhoods than in wealthier and predominantly White neighborhoods. Clearly, the food store environment differs across the 3 sites studied and also differs in complex ways across neighborhoods within sites. The types of stores present are clearly a limited measure of the availability of healthy foods, because even the same "type" of store may offer very different food choices in different types of neighborhoods. A recent study by Horowitz et al. found that only 18% of bodegas, or small grocery stores, in a minority neighborhood carried a selection of healthy foods compared with 58% of those in a predominantly White area. Thus, more detailed assessment of actual food offered may show even greater differences in the local food environment than those suggested by differences in the simple counts of different types of stores.
The dietary consequences of neighborhood differences in food stores depends on many factors including the types of foods available at the stores and the extent to which residents rely on local stores for shopping. If small grocery stores do indeed offer fewer healthy foods than supermarkets and other types of stores are not present (as suggested by our data), residents of poor and minority neighborhoods who depend on local stores as their main source of food may be nutritionally disadvantaged. However, it is important to emphasize that the relation between the type of store and the products offered is by no means fixed. It is perfectly possible that a multiplicity of varied small stores could offer the range of food products necessary for a healthy diet. There are also important trade-offs between large supermarkets (which often require large parking lots) and small stores in terms of automobile traffic and consequences for neighborhood walkability and street life (including social interactions between neighborhoods), all of which may have health consequences. In the US context, the presence of a supermarket may be an adequate marker for the availability of affordable healthy foods. However, it does not necessarily follow that improving the food environment of disadvantaged communities requires only increasing the number of large supermarkets.
The primary source of data for this study is a commercial database established for marketing purposes rather than data collected for research purposes. However, we are aware of no better source of data for our analyses, and primary data collection across the very broad areas that we studied was not feasible. Although there was some under-representation of stores (approximately 12% of stores were not listed) and it is plausible that participation rate differed across store characteristics (e.g., type of store and store size), it is unlikely that these patterns differed systematically across neighborhoods in ways that explain the patterns that we observed. In addition, our findings are consistent with those of researchers using other sources of data.[4,7] Moreover, the use of this commercial database allowed us to examine 3 large diverse areas and multiple types of food stores, key strengths of our analyses, and a clear addition to prior work.
We relied on SIC codes, a standard classification system, to classify businesses into store types. Although any store classification scheme has its limitations, the use of a standard system allows replication across studies. There is no doubt that some misclassification occurred; however, we have no reason to believe that misclassification differed systematically across neighborhoods in ways that could have generated the patterns that we observed. Unfortunately, neither SIC codes nor the more recent standard classification system, the North American Industry Classification System codes, distinguish supermarkets from other grocery stores. We based our classification criteria on prior work.[14,16] In sensitivity analyses, we compared our supermarket classification scheme to that used by Kaufman and found that only 8% of businesses were classified differently. Thus, we believe our results are likely to be robust to different approaches to classifying supermarkets.
An obvious limitation of using lists of businesses in the analyses is that they do not capture informal food sources such as street vendors and roadside stands. These sources may be important in certain types of neighborhoods. We were also unable to capture qualitative differences in the foods offered by the same type of store in different contexts. For example, a convenience store in New York could offer a plethora of healthful options compared with a small grocery store in North Carolina. The use of standardized data sources on businesses across large areas necessarily implies a lack of detailed, qualitative information. For these reasons, large studies like ours need to be complemented with more detailed in-depth assessments of the local food environment in small areas.
The analyses we present here show important differences across neighborhoods in the types of food stores available but do not answer the question of what implications this has for diet. Providing answers to this question requires characterizing the foods available at different types of stores and relating food availability and food store type to the dietary patterns of individuals. Although 2 recent studies have shown that the presence or proximity of supermarkets in neighborhoods is associated with the probability of meeting dietary recommendations in certain populations,[5,10] there is still very limited data on this question. Studies that examine how changes in the local food environments are related to changes in diet using experimental or quasi-experimental designs are an important need if causal inferences are to be drawn.
Our results provide empirical support for the often-cited claim that food options differ across neighborhoods and that healthy food options may be reduced in poor and minority areas. The location of food stores depends on a complex set of factors including the marketing decisions of large corporations, the perception of the market by small businesses, consumer demand and purchasing power, competition, local regulations, and also local culture. Thus, changing the local food environment will require intersectorial approaches. Our data also show that the patterns are complex. For example, poor and minority neighborhoods tend to have larger numbers of small stores, which may have substantial secondary benefits over small numbers of very large stores in terms of street life, social interactions, and traffic. Moreover, not all poor or minority neighborhoods have unhealthy food environments; in fact some poor, ethnic neighborhoods may offer more healthy choices than wealthier areas. Identifying the processes that allow poor and minority neighborhoods to attract and retain healthy food choices may suggest important avenues for intervention.
The infrastructure of the local food environment is yet-another feature of the built environment that varies substantially across neighborhoods and may contribute to disparities and social inequalities in health. Accurate description of area differences in the local food environment is an important step. However, future research will need to move beyond descriptive studies to investigations of how best to effect change in the local food environment and studies of whether changes in the local food environment are associated with changes in residents' diets. Collaboration between community organizations, economic development planners, and public health researchers will be key in moving this agenda forward.
This study was funded by the Columbia Center for the Health of Urban Minorities (MD00206) via the National Center on Minority Health and Health Disparities, National Institutes of Health, and the National Heart, Lung, and Blood Institute (R01-HL071759).
Ana V. Diez Roux, MD, PhD, Center for Social Epidemiology and Population Health, University of Michigan, 1214 S University, Ann Arbor, MI 48104-2548 (e-mail: firstname.lastname@example.org ).
Am J Public Health. 2006;96(2):325-331. © 2006 American Public Health Association
Human Participant Protection
No protocol approval was needed for this study.
Cite this: Associations of Neighborhood Characteristics With the Location and Type of Food Stores - Medscape - Feb 01, 2006.