Evidence map›Paper›PMID 42609392›Full record

ArticleFrontiers in nutrition2026

Associations between the gut microbiome and diet, body composition, and glycemic profiles: a cross-sectional

Chan Wang, Lauren Berube, Margaret Curran, Mary Lou Pompeii, Lu Hu, Souptik Barua, Huilin Li, David E St-Jules, Antoinette Schoenthaler, Eran Segal and 2 more

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In one paragraph

Article in Frontiers 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.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

12 authors.

Chan WangDivision of Biostatistics, Department of Population Health, New York University Langone Health, New York, NY, United States.
Lauren BerubeDepartment of Epidemiology, Public Health Nutrition Program, NYU School of Global Public Health, New York, NY, United States.
Margaret CurranDepartment of Population Health, Center for Healthful Behavior Change, Institute for Excellence in Health Equity, New York University Langone Health, New York, NY, United States.
Mary Lou PompeiiDepartment of Population Health, Center for Healthful Behavior Change, Institute for Excellence in Health Equity, New York University Langone Health, New York, NY, United States.
Lu HuDepartment of Population Health, Center for Healthful Behavior Change, Institute for Excellence in Health Equity, New York University Langone Health, New York, NY, United States.
Souptik BaruaDivision of Precision Medicine, Department of Medicine, New York University Langone Health, New York, NY, United States.
Huilin LiDivision of Biostatistics, Department of Population Health, New York University Langone Health, New York, NY, United States.
David E St-JulesDepartment of Nutrition, University of Nevada, Reno, Reno, NV, United States.
Antoinette SchoenthalerDepartment of Population Health, Center for Healthful Behavior Change, Institute for Excellence in Health Equity, New York University Langone Health, New York, NY, United States.
Eran SegalDepartment of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.
Michael BergmanDepartment of Population Health, Center for Healthful Behavior Change, Institute for Excellence in Health Equity, New York University Langone Health, New York, NY, United States.
Collin J PoppDepartment of Population Health, Center for Healthful Behavior Change, Institute for Excellence in Health Equity, New York University Langone Health, New York, NY, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The gut microbiome is implicated in obesity and type 2 diabetes (T2D), but how diet, body composition, glycemic status, and self-efficacy factors relate to the microbiome in high-risk individuals is not well characterized. The purpose of this post-hoc analysis is to examine the relationship between the gut microbiome and obesity-related metabolic factors, including body composition, resting energy expenditure (REE), and glycemic variability (GV). Methods: Data for this Results: Participants were a mean age of 58 years old, mostly female (75.8%), with a mean BMI of 34.6 kg/m Conclusion: In adults with prediabetes and obesity, the gut microbiome at baseline was most strongly associated with diet, with additional associations observed for body composition and selected host characteristics. These findings underscore diet as a key correlate of gut microbiome structure in a high-risk metabolic population and support further development of microbiome-informed precision nutrition strategies for obesity prevention and management.

Indexed as

glycemic variabilitygut microbiomepersonal dietprecision nutritiontype 2 diabetes

Identifiers

PMID42609392
PMCPMC13478278

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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.