Evidence map›Paper›PMID 40765741›Full record

ArticleFrontiers in nutrition2025

Differing dietary patterns according to body composition.

Yea-Chan Lee, Hyung-Mi Kim, Hye Sun Lee, Soyoung Jeon, Yu-Jin Kwon, Ji-Won Lee

Abstract read
In one paragraph

Article in Frontiers in nutrition, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Yea-Chan LeeDepartment of Family Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea.
Hyung-Mi KimDepartment of Food and Nutrition, Dongduk Women's University, Seoul, Republic of Korea.
Hye Sun LeeBiostatistics Collaboration Unit, Department of Research Affairs, Yonsei University College of Medicine, Seoul, Republic of Korea.
Soyoung JeonBiostatistics Collaboration Unit, Department of Research Affairs, Yonsei University College of Medicine, Seoul, Republic of Korea.
Yu-Jin KwonDepartment of Family Medicine, Yongin Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea.
Ji-Won LeeDepartment of Family Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: This study aimed to investigate dietary patterns in relation to body composition, categorized into four groups using large-scale nationwide data: neither low muscle mass nor high body fat (N), low muscle mass only (LMo), high body fat only (HFo), and low muscle mass with high body fat (LMHF). Methods: A total of 15,917 participants from the 2008-2011 Korea National Health and Nutrition Examination Survey were analyzed. Propensity score matching (PSM) values, representing the predicted probability of patients having LMo, HFo, or LMHF, were estimated using logistic regression analysis while adjusting for confounders. Analysis of covariance was then used to compare daily macronutrient intake and weekly consumption frequency of food groups among the study groups, adjusting for total calorie intake. Results: Participants in the LMHF and HFo groups consumed lower amounts of carbohydrates and higher proportions of proteins and fats compared to the N group. Those in the LMHF and LMo groups had less frequent consumption of rice and vegetables and more frequent intake of ultra-processed foods. Additionally, participants in the LMo and HFo groups consumed beverages more frequently than those in the N group. Conclusion: Imbalances in body composition, such as LMo, HFo, and LMHF, are associated with less favorable dietary patterns, including higher consumption of ultra-processed foods and beverages, and lower intake of rice and vegetables. Further research is needed to explore targeted nutritional interventions for these groups.

Indexed as

body compositionnutritionobesitysarcopeniasarcopenic obesity

Identifiers

PMID40765741
PMCPMC12321545

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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.