Evidence map›Paper›PMID 40594421›Full record

ArticleScientific reports2025

Gut microbiota differences in children classified by extreme physical fitness and physical activity levels from a Chinese Cross-Sectional study.

Xiang Pan, Yibo Gao, Yanfeng Zhang, Koya Suzuki, Jin He, Xiaoxiao Chen, Lupei Jiang, Aoyu Zhang

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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
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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

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

8 authors.

Xiang Pan *China Institute of Sport Science, Beijing, China.
Yibo Gao *China Institute of Sport Science, Beijing, China.
Yanfeng ZhangChina Institute of Sport Science, Beijing, China. zhangyanfeng0310@126.com.
Koya SuzukiGraduate School of Health and Sports Science, Juntendo University, Inzai, Japan. ko-suzuki@juntendo.ac.jp.
Jin HeChina Institute of Sport Science, Beijing, China.
Xiaoxiao ChenChina Institute of Sport Science, Beijing, China.
Lupei JiangChina Institute of Sport Science, Beijing, China.
Aoyu ZhangChina Institute of Sport Science, Beijing, China.

Funding

Ministry of Science and Technology of the People's Republic of China 2022YFC3600204
6 · The paper itself

Abstract

This study investigated the diversity, structure, dominant microbial populations, and their relationships with physical fitness (PF) and physical activity (PA) metrics within the gut microbiota of children by comparing the gut microbiome composition and functional differences across four groups: low PA-high PF, high PA-high PF, high PA-low PF, and low PA-low PF. A total of 6,074 children aged 6-9 years were selected from full-time ordinary primary and secondary schools. Based on the quartiles of PF and PA, we sampled 120 individuals from each of the four groups (30/group) and collected fecal samples for high-throughput sequencing to analyze the gut microbiome composition. This study revealed that children with high PF exhibited a more abundant and diverse gut microbiome within the same PA level group. Under high PA conditions, the Chao1 and Shannon indices of the high PF group were significantly higher. Different dominant microbial taxa were identified within each group, and specific microbial populations were significantly correlated with various physical and exercise-related indices. This study indicates that the composition of children's gut microbiota varies significantly based on the combined levels of PA and PF. Children with high PF show greater microbial diversity within similar PA levels, particularly under high PA conditions.

Indexed as

ExerciseGastrointestinal MicrobiomePhysical FitnessChildChinaCross-Sectional StudiesEast Asian PeopleFecesFemaleHumansMaleChildrenGut microbiotaMicrobial diversityPhysical activityPhysical fitness

Identifiers

PMID40594421
PMCPMC12217701

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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.