The Association Between Physical Activity and Uterine Leiomyoma and Its Symptoms: A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
ABSTRACT Background and Aims Although many studies have focused on the impact of physical activity on hormone‐mediated tumors, its effect on uterine leiomyomas (UL) remains unclear. This systematic review synthesizes the scientific evidence on the role of physical activity in the occurrence and symptomatology of UL while putting forward a research agenda. Methods The PubMed, Scopus, Web of Science, SciELO, and Cochrane Library databases were searched for studies published up to January 10, 2025. The Newcastle‒Ottawa Scale was used to assess study quality, and the GRADE tool was used to determine evidence certainty. Dear‐Simonian and Laird random effects models were used to estimate the pooled odds ratio (OR) and 95% confidence interval (CI) of the association between physical activity and UL. The PRISMA guidelines were followed. Results Fifteen studies were included (three cross‐sectional, 6 case–control, and 6 cohort studies), of which 11 were considered in the meta‐analysis. The difference between women who did and did not regularly practice physical activity (OR = 0.93; 95% CI: 0.82, 1.05; I 2 = 77.6%, n = 8 studies) in the likelihood of having UL did not meet conventional levels of statistical significance. Moreover, those women who engaged in more intense physical activity were less likely to have UL (OR = 0.86; 95% CI: 0.75, 0.99; I 2 = 80.5%, n = 5 studies) than those who engaged in less intense physical activity. Conclusion Increased physical activity is associated with a slight decrease in the risk of UL and may provide relief from associated symptoms. Since current evidence is still limited to supporting specific physical activity recommendations, a research agenda is proposed for future studies on this subject. PROSPERO Registration CRD42021247505.
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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 | 0.012 | 0.030 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.035 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".