National trends and disparities in retail food environments in the USA between 1990 and 2014

Abstract

Objective: To describe national disparities in retail food environments by neighborhood composition (race/ethnicity and socioeconomic status) across time and space. Design: We examined built food environments (retail outlets) between 1990-2014 for census tracts in the contiguous U.S. (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 (categorized as predominantly one race/ethnicity (>60%) or mixed), and inflation-adjusted income tertile. Setting: The contiguous U.S. between 1990-2014 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 neighborhoods with different racial-ethnic and socioeconomic compositions.

Consumer food environment assessment and its association with socioeconomic factors in a midsize city in Brazil

“…Best access to healthy food, according to the HFSI score, was found in supermarkets and FV retail shops, similar to the literature, as these establishments offer healthier foods compared to local markets, small grocery stores, and convenience stores [34]. Studies show that greater access to supermarkets is associated with healthy diets [28,35]; however, it is important to emphasize that supermarkets offer healthy and ultra-processed products.…”

Food environment trajectories: a sequence analysis from the CARTaGENE cohort

“…Furthermore, individuals belonging to households earning less than 100 000 $CAD annually were found to have a greater likelihood of experiencing a disadvantaged food environment trajectory as compared with those in higher-income households. It has been established that socio-economic disadvantage is linked with an unhealthy food environment over a long period ( 17 , 34 , 35 , 47 ) . Additionally, other studies have found that low median household income is associated with a higher concentration of fast-food outlets in the neighbourhood over a long period ( 12 , 33 , 47 ) .…”

“…It has been established that socio-economic disadvantage is linked with an unhealthy food environment over a long period ( 17 , 34 , 35 , 47 ) . Additionally, other studies have found that low median household income is associated with a higher concentration of fast-food outlets in the neighbourhood over a long period ( 12 , 33 , 47 ) .…”

“…It has been established that socio-economic disadvantage is linked with an unhealthy food environment over a long period (17,34,35,47) . Additionally, other studies have found that low median household income is associated with a higher concentration of fast-food outlets in the neighbourhood over a long period (12,33,47) . The results of our study indicate that the level of education of participants is linked to socio-economic inequality and has an impact on the food environment trajectories.…”

Systematic Review of Longitudinal Evidence and Methodologies for Research on Neighborhood Characteristics and Brain Health

“…Without diverse cohorts and comprehensive evaluation of the impact of systemic and interpersonal racism, we may be missing key contributors of disparities in brain health. The distribution of neighborhood features and resources varies by neighborhoodlevel SES and racial composition [21,[81][82][83][84][85][86][87][88]. Relative differences in these neighborhood features may be the clue to deciphering racial/ethnic and SES disparities in AD/ADRD.…”