Modulation of gut microbiota through physical activity in individuals with obesity—a systematic review
Bibliographic record
Abstract
Overweight/obesity (OW/OB) has been associated with gut dysbiosis, changes in gastrointestinal motility and sedentary behavior, contributing to metabolic and inflammatory alterations. This systematic review aims to assess the evidence supporting the influence of physical activity and exercise on gut microbiota composition and diversity in OW/OB and was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, using MEDLINE, EMBASE, EBSCO, and Scopus databases. Risk of bias was assessed with RoB 2 for randomized controlled trials (RCTs), ROBINS-I for non-RCT, and JBI Critical Appraisal tool for cross-sectional studies. Eleven studies were selected including 476 OW/OB and 382 normal weight individuals. Seven studies included different types of exercise intervention while the other four were cross-sectional studies assessing physical activity. Results show no clear evidence of a less diverse microbiota in OW/OB. Exercise does not significantly affect alpha diversity of gut microbiota but modifies beta diversity depending on OB status. Moderate to vigorous physical activity positively associates with gut microbiota composition and short-chain fatty acid producing bacteria. These findings highlight the importance of considering gut microbiota contribution to inter-individual variability of response to obesity treatments. Modulation of gut microbiota through physical activity should be considered in the design of personalized therapeutic strategies in obesity. PROSPERO registration number: CRD42021262107.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".