Author(s) :

Yun Koo.

Volume/Issue :

Abstract :

This study investigates the relationship between economic inequality and the prevalence of food deserts among 300 U.S. census tracts with quantitative model, focusing on the prediction of food inaccessibility through poverty, unemployment, and lack of transportation access. This study seeks to answer the research question about whether structural socioeconomic factors influence the prevalence of food deserts in the United States, and whether their effects may differ between urban and rural areas. This study hypothesized that each factor of poverty, unemployment, and the lack of transportation access would influence food accessibility, along with compounded effects from multiple disadvantages. Multiple regression model was generated by using data from the USDA Food Access Research Atlas and the American Community Survey, analyzing the stratified modeling and interaction terms between poverty and vehicle access. With the interaction term-included model, 83% of the variance was explained in the prevalence of food deserts (=0.83). All predictors were statistically significant (p < 0.001). Unemployment rate proved to be the strongest influence in the prevalence of food deserts, followed by poverty and vehicle access. With stratified models generated for each urban-only ( = 0.41) and rural-only ( = 0.32) settings, vehicle access was shown to have greater relative importance in rural areas than urban areas. When including the interaction term to generate a unified model, correlation coefficient increased to 0.85, indicating that the impact of poverty was exacerbated when transportation access problem was compounded. These findings provide a coherent quantitative framework to understand food deserts as a structural outcome from intersecting economic inequalities. This study underscores the role of intersectional and geographically-targeted policy interventions to address these structural economic barriers and promote equitable food security.