Association Between County-Level Food Retail and Socioeconomic Environment and Nutritional Quality of Household Food Purchases, 2015.

BACKGROUND

About 40 million Americans do not have easy access to affordable nutritious foods. Healthier foods are less likely to be available to those living in rural and/or lower-income communities.

OBJECTIVE

The objective of this study was to analyze the association between nutritional quality of household food purchases and county-level food retail environment; county-level demographic, health, and socioeconomic indicators; and household composition, demographic characteristics, and socioeconomic characteristics.

DESIGN

This study is a secondary analysis of the 2015 Information Resources Inc Consumer Network panel; Purchase-to-Plate Crosswalk, which links US Department of Agriculture nutrition databases to Information Resources Inc scanner data; County Health Rankings; and the Food Environment Atlas data.

PARTICIPANTS AND SETTINGS

A total of 63,285 households, representative of the contiguous US population, consistently provided food purchase scanner data from retail stores throughout 2015.

MAIN OUTCOME MEASURES

Nutritional quality of retail food purchases was assessed using the Healthy Eating Index 2015 (HEI-2015).

STATISTICAL ANALYSIS

Multivariate linear regression analysis was used to simultaneously test the relationship between the main outcome and household-level demographic and socioeconomic characteristics as well as the county-level demographic, health, socioeconomic, and retail food environment.

RESULTS

Household heads who had higher education and households with higher incomes purchased food of better nutritional quality (ie, higher HEI-2015 scores). Also, the association between retail food purchase HEI-2015 scores and the food environment was weak. Higher density of convenience stores was associated with lower retail food purchase nutritional quality for higher-income households and households living in urban counties, whereas low-income households in counties with higher specialty (including ethnic) store density purchased higher nutritional quality food. Both in the full sample and when stratified by household income or county rural vs urban status, no association was found between grocery store, supercenters, fast-food outlets, and full-service restaurant densities and retail food purchase HEI-2015 scores. HEI-2015 scores were negatively correlated with the county average number of mental health days for higher income and urban households.

CONCLUSIONS

The study findings suggest that availability of healthier food alone may not improve healthfulness of retail food purchases. Future studies examining the influence of demand-side factors/interventions, such as habits, cultural preferences, nutrition education, and cost/affordability, on household purchasing patterns could provide complementary evidence to inform effective intervention strategies.