Socio-economic and racial/ethnic disparities in the nutritional quality of packaged food purchases in the USA, 2008-2018

Abstract

Objective: To determine whether disparities exist in the nutritional quality of packaged foods and beverage purchases by household income, education and race/ethnicity and if they changed over time.

Design: We used Nielsen Homescan, a nationally representative household panel, from 2008 to 2018 (n = 672 821 household-year observations). Multivariate, multilevel regressions were used to model the association between sociodemographic groups and a set of nutritional outcomes of public health interest, including nutrients of concern (sugar, saturated fat and Na) and calories from specific food groups (fruits, non-starchy vegetables, processed meats, sugar-sweetened beverages and junk foods).

Setting: Household panel survey.

Participants: Approximately 60 000 households each year from the USA.

Results: Disparities were found by income and education for most outcomes and widened for purchases of fruits, vegetables and the percentage of calories from sugar between 2008 and 2018. The magnitude of disparities was largest by education. Disparities between Black and White households include the consumption of processed meats and the percentage of calories from sugar, while no disparities were found between White and Hispanic households. Disparities have been largely persistent, as any significant changes over time have been substantively small.

Conclusions: Policies to improve the healthfulness of packaged foods must be expanded beyond SSB taxes, and future research should focus on what mediates the relationship between education and diet so as not to exacerbate disparities.

Keywords: Diet disparities; Diet quality; Food purchases; Low education.

Fig. 1

Model-adjusted trends in packaged foods and beverage purchases (PFP) calories from healthy and unhealthy food groups from 2008 to 2018, by household income tertile^a. ^aModels were survey-adjusted and controlled for education, race/ethnicity, household composition and year, with an interaction between income tertile and year when significant. ^bMixed dishes include foods like canned soups and frozen entrees, while junk foods include salty snacks, candies, sweeteners and desserts (see online supplementary material, Supplementary Table 1 for more examples). *Significant difference between 2008 and 2018 for given income tertile, P < 0·01. **Significant difference between 2008 and 2018 for given income tertile, P < 0·001

Fig. 2

Model-adjusted trends in total calories and nutrients in packaged foods and beverage purchases (PFP) from 2008 to 2018, by household income tertile^a. ^aModels were survey-adjusted and controlled for education, race/ethnicity, household composition and year, with an interaction between income tertile and year when significant. **Significant difference between 2008 and 2018 for given income tertile, P < 0·001. , low income; , middle income; , high income; , sugar; , saturated fat

Fig. 3

Trends in differences and disparities^a for all sociodemographic subgroups and nutritional outcomes, 2008–2018. ^aDisparities are those differences where the more vulnerable demographic group also has an unhealthier purchasing pattern, that is, purchases fewer calories from healthy food groups, more calories from unhealthy food groups, or more of a nutrient of concern. In the table, disparities are bolded. Disparities that have narrowed are shaded in green, those that have remained constant are shaded in yellow and those that have widened are in red. The line graphs are selected examples included as illustration of changes in income disparities. ^bFruits and non-starchy vegetables are the only two outcomes for which a greater value for the outcome is indicative of a healthier purchasing pattern. Therefore, for these outcomes, differences are considered disparities when the more vulnerable demographic group purchases fewer calories per capita/d