There are well-documented disparities in both dietary intake and diet-related health conditions among racial, ethnic and socio-economic groups in the United States [1]. Understanding the causes of these differences has become a major focus of research and policy [2]. Physical environment has been associated with numerous health behaviors and outcomes [3,4], leading many to hypothesize that difference in eating behavior originate from differences in access to healthy food options [5-9]. For example, consumption of fruit and vegetables is recommended through the Dietary Guidelines for Americans [10], but these foods are often not easily accessible by racial and ethnic minority groups in large urban centers or populations in rural areas [1,11-19]. Along with reduced access, fresh fruit and vegetables may also be less affordable to rural populations and racial/ethnic minority groups, which would also contribute to nutrition-related disparities [13,16,20-22].

Attempts to study the relationship between neighborhood characteristics and the affordability of healthy food options, such as fresh fruits and vegetables, have utilized data from predominantly urban areas [11,12,21,23-27]. Studies that do consider rural populations have focused on differences in affordability across store types, rather than across the characteristics of residents [16,26]. As a result, very little is known about how the demographic and economic composition of rural neighborhoods is related to the affordability of healthy food items. Therefore, the aim of this article is to investigate whether stores located in rural neighborhoods with lower socio-economic status or with higher proportions of African-American and Hispanic residents charge more for fresh fruit and vegetables. Previous findings on the relationship between the affordability of healthy food options and neighborhood economic status using in urban settings are mixed. While some find a positive relationship between socio-economic status [24,25], others have reported that there is no statistically significant differences [23,27].

We examine fruits and vegetables since their consumption is associated with positive health outcomes, they account for a substantial portion of the USDA Thrifty Food Plan market basket, and previous research on their availability, affordability and consumption provide a basis from which we can compare our results. We focus on fresh fruit items since they account for roughly 81% of total non-juice fruit consumption. Fresh vegetables account for 52% of total vegetable consumption that is neither dehydrated or chipped (i.e. potato chips) [28].

Our approach is novel in several respects. Our information on the price of fresh fruits and vegetables comes from ground-truthed data collected by taking an on-site census of food stores in a large regional area. Moreover, this rural region in central Texas is home to a socio-economically and demographically diverse population. This differs from previous work on rural affordability, which has generally considered smaller geographic areas that are racially homogenous or used only a sample of stores. Finally, we handle missing prices through an imputation strategy based on economic theory; specifically the decision of a profit-maximizing store owner to stock a particular item for sale. Previous methods that used simple mean imputation procedures, e.g. replacing missing prices with the mean price over similar store types, have raised concerns that this method may lead to biased results [21].

Among the 25 stores that sold at least 3 fruit items (1 supercenter, 12 supermarkets, 10 grocery and 2 convenience), apples, oranges, avocado and banana were the most commonly found (Table 1 provides both the number of stores with price data by item along with the proportion of stores doing so). On a per weight basis, bananas were the cheapest fruit type, while berries were the most expensive. Among the 32 stores that sold at least 4 vegetable items (1 supercenter, 12 supermarkets, 11 grocery stores and 8 convenience stores), carrots, lettuce, onions, potatoes and tomatoes were the most common. Potatoes were the least expensive vegetable type, while green beans were the most expensive.

There were 25 stores that sold at least 3 types of fruit; however, 22 stores posted the requisite information--the prices of apples, oranges and bananas--to calculate the basic variety price index (1 supercenter, 12 supermarkets, 8 grocery stores, and 1 convenience store). Similarly, of the 32 stores that sold at least four types of vegetables, 23 posted the requisite price information to calculate the basic vegetable price index (1 supercenter, 12 supermarkets, 8 grocery stores and 2 convenience stores). The mean cost of meeting the USDA recommended level of fruit consumption from a high variety basket of fruit types in our sample of stores was just over $27.50 per week (Table 2). In contrast, relying on only the three most common fruits lowered the weekly expense to just under $17.25 per week, a reduction of 37.6%. The effect of moving from a high variety to a low variety basket was much less when considering vegetable consumption: a 4.3% decline from $29.23 to $27.97 per week.

Although there are 101 CBG in the six counties of the rural Brazos Valley region, the overwhelming majority either does not have a food store located within their boundaries or the only food stores are convenience stores that do not sell fresh fruits or vegetables. Nevertheless, the 23 food stores with sufficient price information to be included in the subsequent analysis are located across diverse neighborhoods. The median household income at the level of the CBG was highly variable, ranging from $14,400 to $50,500. On average, African American comprised 21.2% of the CBG population, while Hispanics accounted for 16.5%. There were also several minority-majority CBG in which more than 50% of the population was either African American or Hispanic. Indeed, the CBG were these 23 food stores are located (Table 2) appear slightly more diverse than the region in general.

Multivariate regression analysis of the store-level price indices on CBG characteristics (Table 3) revealed that stores in CBG with higher median household incomes tended to charge more for fresh fruits and vegetables, holding racial composition equal. The coefficient on the logarithm of median household income was positive and statistically significant (P < 0.05) for both vegetable price indices. For example, every ten percent increase in the CBG median household income was associated with an increase of $1.39 (P < 0.05) in the high variety index and $1.61 (P < 0.05) in the basic index. The coefficient estimate was also positive and was statistically significant at the 10% level for the high variety fruit index, implying that a 10% increase in median income was associated with a $1.02 (P = 0.089) increase.

In addition, stores in CBG with greater proportions of Black residents tended the charge more for fresh produce, holding income equal. The coefficient estimates on the proportion of Black residents were positive for all four indices and were statistically significant at the 10% level for two. Holding everything else constant, a 10 percentage point increase in the proportion of African American residents was associated with an increase of $1.49 (P = 0.085) in the high variety fruit index and $2.30 (P = 0.062) in the basic vegetable index. In contrast, the coefficient on the proportion of Hispanic residents was typically close to zero and never approached significance (the smallest P-value is 0.621). Finally, the mean VIF was at or below 2.0 in each regression and the maximum was never larger than 2.5, indicating that collinearity between explanatory variables is not problematic.

The results using multivariate analysis differ quite substantially from the univariate analysis (Table 4). For example, stores in higher income areas do not charge more for the basket of fresh fruits and vegetables when differences in racial composition are not simultaneously controlled. Similarly, stores in neighborhoods with higher proportions of African American resident do not tend to charge more for fresh fruits and vegetables. The difference between the multivariate and univariate analyses is explained by the negative relationship between the proportion of African American residents in a neighborhood and the median household income.

We also repeated our multivariate regression analysis replacing price indices with the prices (imputed price if missing) of individual fruit and vegetable items. Among fruits (Table 5), the price of avocado was strongly related to both income and the racial/ethnic composition of the neighborhood, whereas the remaining fruit types were very weakly associated with either. This result likely explains why the R² for the high variety index reported in Table 4 is much larger than that for the basic index, which does not incorporate avocado. It is worth noting that this finding cannot be explained by the imputation process, as the price of avocado did not need to be imputed at any of the 21 stores used in the analysis. Although the relationship between household income and affordability of fruit (and between racial/ethnic composition and affordability) is principally the results of one item, avocado is nonetheless an important ingredient in local Tex-Mex cuisine and accounts for a non-trivial proportion of total fruit consumption, 9.1%.

Among vegetables (Table 6), green beans actually exhibit a negative relationship to both income and the proportion of Black or Hispanic residents, but more common items like onions, lettuce, potatoes and tomatoes display qualitatively similar results to those presented in Table 4 for the price indices. Although the coefficient estimates in these regressions are not statistically significant, estimating a statistically significant association between a particular neighborhood characteristic and an index of prices when the individual price relationships are not statistically significant should not be troubling. Since stores that sell high prices for one type likely charge a higher price for similar items, i.e. a positive covariance between prices, the sum of variances will be less than the variance of the sum. Contrary to being troubling, this is evidence that the intuition underlying our imputation strategy was reasonable. It also suggests that studies of affordability should report results using both aggregate and disaggregated measures of affordability, since aggregate prices can obscure important behavior among individual items, while results for individual goods may not adequately account for the positive covariance of prices within a given store.

Finally, we repeated the analysis using mean imputation (not reported). In this particular application, the choice of imputation method did not affect coefficient estimates, but it may nevertheless be influential in other settings.

The goal of this article was to describe the relationship between the prices charged by stores for healthy food items and the characteristics of the surrounding communities. We found that holding racial composition constant, stores located in neighborhoods with higher income residents charge more for fresh fruits and vegetables. This is consistent with previous results in other urban settings [24,25]. For fruit, much of the difference in cost between stores was accounted for by differences in the price of one item, avocado. For vegetables, however, the relationship between neighborhood income and price was present for many of the most common types.

A positive relationship between the affluence of surrounding communities and the cost of fresh produce (holding racial composition constant) can be explained by a number of forces. First, fresh produce is a normal good, i.e. households purchase more fresh fruits and vegetables as their incomes increase. Some of this increase can be attributed to a general increase in all purchases as income goes up. It is also possible that households with higher incomes shift their consumption of fruits and vegetables toward fresh items, instead of canned or frozen versions. Of course, these explanations are not mutually exclusive and could be occurring concurrently. Regardless of the mechanism through which income causes demand for fresh produce to increase, basic economic theory predicts that as demand for fresh produce increases, the price of produce will also increase.

A second explanation is that fresh produce is not a homogenous product. Quality is also a normal attribute so that as incomes increase, individuals attempt to replace low-quality items with higher quality version. Hence, differences in prices between stores may reflect differences in the freshness of items.

Finally, stores in rural areas may face less price competition. In densely populated areas, higher demand for fresh produce may not lead to appreciably higher prices since there are many stores competing for the same set of potential consumers. Since rural areas typically exhibit low population densities combined with large distances between population centers, the number of stores that are reasonably accessible to residents will be smaller, reducing the amount of competition.

Holding the median household income constant, stores located in neighborhoods with higher proportions of African American residents also tended to charge a higher price for fresh produce items. Part of the explanation may be that greater proportions of African Americans reside in CBG where there is greater access to small grocery and convenience stores, where prices are higher than charged in the larger supermarkets and supercenters [16,17,32]. In contrast, the proportion of Hispanic residents did not exhibit a statistically significant relationship to affordability. As is well-documented, African Americans in the United States suffer from higher rates of nutrition-related illness such as diabetes and are much more likely than Whites to be obese [37,38]. This is also evident in the Brazos Valley region, where one study found that the obesity rate for Blacks is 46.4% compared to 32.0% for Whites [39]. The affordability of fresh produce may be one factor that contributes to the disparity.

Univariate analysis revealed that failing to control for income and racial composition simultaneously can influence coefficient estimates, and thus policy implications. For example, our multivariate regression results suggest that a policy that sought to reduce income inequality between neighborhoods with high and low proportions of Black residents could drive up the price of fresh produce, so that in real (purchasing power) terms, neighborhoods with higher proportions of Black residents would remain relatively disadvantaged. This clearly important effect is missed in the univariate analysis.

Despite these limitations, this study extends prior work by examining the affordability of fresh fruit and vegetables from food stores in a large rural area; and how access to an affordable supply of fresh fruit and vegetables differs by neighborhood inequalities. The approach and findings of this study are relevant and have important research and policy implications for understanding access and availability of affordable, healthy foods. Access to a good variety of affordable healthy foods, such as fruit and vegetables, can play a pivotal role in the nutritional health of rural families. Many of these families live in socioeconomically-deprived neighborhoods; many have a low household income, are unemployed, older, or lack access to a vehicle. In order for rural families to be food secure and have access to fruit and vegetables, food resources need to be available and affordable in local stores.

The authors declare that they have no competing interests.

RAD, JRS, and RN designed research; RAD and JRS conducted research; RAD, JL-M., and YB analyzed data; RAD and YB were responsible for the final analyses; RAD and JRS wrote the paper. All authors read, commented on, and approved the final manuscript.