Evidence map›Paper›PMID 42668651›Full record

ArticleCurrent developments in nutrition2026

Aligning Dietary Intake and Food Purchase Data in United States Older Adults: Insights from the National Health and Nutrition Examination Survey and Circana Consumer Network.

Naglaa H El-Abbadi, Joshua Rutt, Marcus Lehr, Frederick Nusetor, Cristina Moraga Franco, Andrea C Carlson, M Kyla Shea, Chao-Qiang Lai, Laurence D Parnell, Eric Miller and 1 more

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Article in Current developments in nutrition, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Naglaa H El-AbbadiJean Mayer USDA Human Nutrition Research Center on Aging, at Tufts University, Boston, MA, United States.
Joshua RuttJean Mayer USDA Human Nutrition Research Center on Aging, at Tufts University, Boston, MA, United States.
Marcus LehrJean Mayer USDA Human Nutrition Research Center on Aging, at Tufts University, Boston, MA, United States.
Frederick NusetorJean Mayer USDA Human Nutrition Research Center on Aging, at Tufts University, Boston, MA, United States.
Cristina Moraga FrancoJean Mayer USDA Human Nutrition Research Center on Aging, at Tufts University, Boston, MA, United States.
Andrea C CarlsonRetired From Economic Research Service, U.S. Department of Agriculture, Washington, DC, United States.
M Kyla SheaJean Mayer USDA Human Nutrition Research Center on Aging, at Tufts University, Boston, MA, United States.
Chao-Qiang LaiUSDA ARS, Jean Mayer USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, United States.
Laurence D ParnellUSDA ARS, Jean Mayer USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, United States.
Eric MillerJean Mayer USDA Human Nutrition Research Center on Aging, at Tufts University, Boston, MA, United States.
Jose M OrdovasJean Mayer USDA Human Nutrition Research Center on Aging, at Tufts University, Boston, MA, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Diet quality is a key determinant of healthy aging, yet fully assessing dietary intake remains a challenge partly because of data limitations and difficulty in integrating information from methodologically distinct datasets. Different nationally representative datasets can offer complementary perspectives: the National Health and Nutrition Examination Survey (NHANES) captures self-reported dietary intake using 1 to 2 d of 24-h recall, whereas the Circana Consumer Network (CN) is a national retail dataset that records year-long grocery purchases from ∼60,000 United States households. Objectives: This study aimed to evaluate whether dietary intake reported in NHANES 2017-2018 aligns with food purchase trends in CN 2018 among United States adults aged ≥55 y. Methods: We examined self-reported dietary intake of grocery/store-bought foods from 24-h recalls in NHANES ( Results: Mean total HEI scores were modest and comparable across datasets (NHANES: 55.7 ± 0.9; CN: 51.3 ± 0.1; Conclusions: In United States adults aged ≥55 y, grocery/store-sourced intake from NHANES and household grocery purchases from CN showed broadly similar but not interchangeable patterns of diet quality, indicating that purchase data can complement, but not replace, recall-based dietary surveillance. Integrating purchase records with recalls could provide deeper insights into older adults' dietary behaviors and strengthen precision nutrition research.

Indexed as

Circana Consumer Networkdietary intakediet qualityfood purchaseHealthy Eating Index (HEI)NHANESnutrition datasetsolder adultsPurchase-to-Plate Crosswalk (PPC)

Identifiers

PMID42668651
PMCPMC13524882

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.