Higher physical activity levels are related to faecal microbiotadiversity and composition in young adults
Bibliographic record
Abstract
Increasing physical activity (PA) is recognised as an efficacious approach for preventing and treating cardiometabolic diseases. Recently, the composition of microorganisms living within the gut has been proposed as an important appropriate target for treating these diseases. Whether PA is related to faecal microbiota diversity and composition in humans remains to be ascertained. Thus, we examined the association of the time spent in objectively measured PA with faecal microbiota diversity and composition in young adults. A cross-sectional study enrolled 88 young adults aged 22.0 ± 2.3 years (72.7% women), whose time spent in PA at different intensities was objectively measured with a wrist-worn accelerometer for 7 consecutive days. Faecal microbiota diversity and composition were analysed with hypervariable tag sequencing of the V3-V4 region of the 16S rRNA gene. The mean Euclidean Norm of the raw accelerations Minus One (mg) during waking time, considered as overall PA, and the time spent in vigorous PA were positively correlated with alpha diversity indexes (all rho ≥ 0.23, P ≤ 0.034). Regarding faecal microbiota composition, participants with low time spent in vigorous PA had higher relative abundance of the Gammaproteobacteria class (q = 0.021, FDR = q-value) compared to the participants with high time spent in vigorous PA, and lower relative abundance of the Porphyromonadaceae family (q = 0.031) and the Alistipes genus (q = 0.015) compared to the individuals with high and intermediate time spent in vigorous PA, respectively. Our results suggest that PA, especially of vigorous intensity, is related to faecal microbiota diversity and the Gammaproteobacteria class and Porphyromonadaceae family in young adults.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".