Evidence map›Paper›PMID 42056082›Full record

ArticleNutrition & diabetes2026

Distinct meal timing and frequency patterns contribute to daily glycemic variability.

Dong-Hwa Jeong, YoonJu Song

Abstract read
In one paragraph

Article in Nutrition & diabetes, 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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0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Dong-Hwa JeongDepartment of Artificial Intelligence, The Catholic University of Korea, Bucheon-si, South Korea.
YoonJu SongDepartment of Food Science & Nutrition, The Catholic University of Korea, Bucheon-si, South Korea. yjsong@catholic.ac.kr.ORCID 0000-0002-4764-5864

Funding

National Research Foundation of Korea (NRF) NRF-2023R1A2C1006065
6 · The paper itself

Abstract

Glycemic variability is an emerging marker of metabolic health, yet its behavioral determinants in healthy populations remain unclear. This study investigated whether meal patterns-specifically timing, distribution, and frequency-are associated with glycemic variability. Ninety-six individuals aged 18-27 years wore continuous glucose monitors for 14 consecutive days, providing 1036 complete daily records. Daily glucose profiles were clustered using dynamic time warping, and concurrent meal and sleep logs were analyzed to characterize dietary patterns across clusters. Cluster 2 (765 days) exhibited broader distributions and higher densities of elevated glucose values compared with cluster 1 (271 days), reflecting greater variability (17.7% vs. 14.1%, p = 0.0001). Peak daily glucose was also significantly higher in cluster 2, although average glucose did not differ. Total energy intake was lower in cluster 2 than cluster 1 (1781.1 vs. 1981.4 kcal, p = 0.0003), with no significant differences in macronutrient composition. By contrast, meal patterns differed substantially: cluster 2 was characterized by fewer eating occasions, later breakfast timing, and a greater proportion of daily energy intake at dinner. These findings suggest that meal timing and distribution are important dimensions of dietary recommendations, indicating a shift in focus from nutrient intake alone toward including meal patterns.

Indexed as

Blood GlucoseFeeding BehaviorMealsAdolescentAdultContinuous Glucose MonitoringEnergy IntakeFemaleHumansMaleSleepTime FactorsYoung AdultBlood Glucose

Identifiers

PMID42056082
PMCPMC13269695

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LicenceCC BY-NC-ND
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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.