Aligning Dietary Intake and Food Purchases in U.S. Older Adults: Insights from NHANES and Circana Consumer Network

TL;DR

This study compares dietary intake and food purchases in older U.S. adults using two large datasets to better understand their eating habits and how they align.

Contribution

The study integrates nationally representative dietary intake and grocery purchase data to reveal discrepancies and similarities in older adults' diets.

Findings

Both datasets show older adults do not consistently meet dietary recommendations, especially for fruits, whole grains, and saturated fats.

Disparities were found in dairy, mixed dishes, and snacks between food purchases and dietary intake by mass and calories.

Integrating purchase and consumption data can improve understanding of dietary behaviors in older adults.

Abstract

Diet quality is critical for healthy aging, yet assessing dietary intake remains complex. Nationally representative datasets provide valuable but distinct perspectives. The National Health and Nutrition Examination Survey (NHANES) captures self-reported consumption, while the Circana Consumer Network (Circana) records grocery purchases of approximately 60,000 households. The objective of this analysis was to explore whether dietary patterns observed in NHANES 2017-2018 align with food purchase trends in Circana 2018 in U.S. adults 55 years and older. Dietary intake data were derived from single 24-hour recalls (NHANES n = 2132), or grocery food purchase from 1- and 2-person households (Circana n = 26432). We also conducted stratified analyses by sex and age group (55-64, 65-74, 75+). Diet quality was scored using the 2020 Healthy Eating Index (HEI), and food group composition was evaluated by % weight (g) and energy (kcal). The mean±SE total HEI in NHANES was 52.1±0.9. Though overall HEI scores improved with age in both datasets, neither dataset suggests that older adults consistently meet dietary recommendations. Older adults were below HEI component adequacy/moderation recommendations for Fruit, Greens/Beans, Whole Grains, and Saturated Fats; these also showed greatest variation by age. While food group proportion by mass aligned between consumption and purchase for various food groups, there were key disparities in Dairy, Mixed Dishes, Condiments, and Snacks/Sweets; and Vegetables by caloric energy. These observations underscore the potential for integrating food purchase data with dietary intake assessments to enhance understanding of older adults’ dietary behaviors. Further research should explore demographic and socioeconomic factors influencing these patterns.