Poverty and Food Environments: EBT Access at Healthy and Unhealthy Retailers over Space and Time
*Names in bold indicate Presenter
Two recent trends complicate the relationship between food environments and low-income communities, adding difficulty to targeting these programs. First, the economic downturn has resulted in greater levels of poverty. Second, the geography of poverty has changed. Although many low-income households remain clustered in high-poverty neighborhoods, others are dispersed in the suburbs and once poor inner-city neighborhoods have experienced gentrification.
Measures of healthy food access are often cross-sectional and static and do not take in to account economic accessibility of healthy and unhealthy retail outlets. Understanding the dynamics of the healthy retail sector over time and space can help craft policies to have a meaningful impact on health outcomes. Therefore, we focus our study on the changing food environment - for both healthy and unhealthy retail outlets - between 2000 and 2010 across an entire state. In addition, we focus on outlets that presumably are more economically accessible to low-income individuals, namely outlets that accept EBT. Our research question is how has the retail sector responded to changes in poverty and what is the resulting healthy (and unhealthy) food environment across the rural-urban continuum?
To address our research question, we geo-coded point data for all retail stores accepting EBT for every two years from 2000 to 2010 for the state of Ohio, categorizing the stores as unhealthy (convenience) or healthy (full-service grocery stores). We coupled this data with tract-level census data to create measures of unhealthy and healthy access, using various measures to ensure the robustness of our results. We then conducted an ordinary least squares regression of first differences to examine which factors are associated with changes in accessibility between 2000 and 2010.
Our results suggest that unhealthy and healthy retailers have different responses to changes in poverty and population, with poverty changes playing a greater role in the location of unhealthy outlets and changes in population playing a greater role in the location of healthy outlets. In addition, initial conditions in 2000, such as levels of access and poverty, racial make-up, and the tract's location on the rural-urban continuum correlate differently for the two types of outlets. For example, tracts with the lowest initial access gained unhealthy outlets and tracts with the highest initial access gained healthy outlets. Higher levels of minority residents are correlated with reduced access over time. The results suggest that incentives to target store development and EBT authorization may need to differ depending on the location and pre-conditions of the outlet.