National trends and disparities in retail food environments in the USA between 1990 and 2014 - Jana A Hirsch; Yuzhe Zhao; Steven Melly; Kari A Moore; Nicolas Berger; James Quinn; Andrew Rundle; Gina S Lovasi (Cambridge University Press, 2023)
Abstract Objective: To describe national disparities in retail food environments by neighbourhood composition (race/ethnicity and socio-economic status) across time and space. Design: We examined built food environments (retail outlets) between 1990 and 2014 for census tracts in the contiguous USA (n 71 547). We measured retail food environment as counts of all food stores, all unhealthy food sources (including fast food, convenience stores, bakeries and ice cream) and healthy food stores (including supermarkets, fruit and vegetable markets) from National Establishment Time Series business data. Changes in food environment were mapped to display spatial patterns. Multi-level Poisson models, clustered by tract, estimated time trends in counts of food stores with a land area offset and independent variables population density, racial composition (categorised as predominantly one race/ethnicity (>60 %) or mixed), and inflation-adjusted income tertile. Setting: The contiguous USA between 1990 and 2014. Participants: All census tracts (n 71 547). Results: All food stores and unhealthy food sources increased, while the subcategory healthy food remained relatively stable. In models adjusting for population density, predominantly non-Hispanic Black, Hispanic, Asian and mixed tracts had significantly more destinations of all food categories than predominantly non-Hispanic White tracts. This disparity increased over time, predominantly driven by larger increases in unhealthy food sources for tracts which were not predominantly non-Hispanic White. Income and food store access were inversely related, although disparities narrowed over time. Conclusions: Our findings illustrate a national food landscape with both persistent and shifting spatial patterns in the availability of establishments across neighbourhoods with different racial/ethnic and socio-economic compositions.