Association between physical activity and gynecological cancers: a meta-analysis of prospective cohort studies
Bibliographic record
Abstract
OBJECTIVE: Previous evidence has unveiled that physical activity (PA) may affect gynecologic cancer (GC). However, existing research findings remain inconsistent. Hence, this comprehensive meta-analysis was to quantify updated evidence on the association between PA and GC risk. METHODS: A meta-analysis of prospective cohort studies was conducted to evaluate the association between PA and GC risk, including endometrial cancer (EC), ovarian cancer (OC), and cervical cancer (CC). PubMed, Web of Science, and Embase were searched for relevant studies until May 13, 2025. Case-control and cross-sectional studies were excluded to reduce bias and improve causal inference. Study quality was appraised via the Newcastle-Ottawa Scale. The relative risks (RRs) along with 95% confidence intervals (CIs) were pooled through a random-effects model. Heterogeneity was judged with the Q and I² statistics, and publication bias was tested through funnel plot analysis and Egger's regression test. RESULTS: 71 risk estimates were summarized in 36 studies. Individuals participating in moderate PA had a lower risk of EC than those in low PA (RR = 0.94, 95% CI: 0.89-0.99, P = 0.024), while those in high PA exhibited an even lower EC risk (RR = 0.82, 95% CI: 0.76-0.89, P < 0.001). Besides, moderate PA (RR = 1.04, 95% CI: 0.97-1.10, P = 0.263) and high PA levels (RR = 1.04, 95% CI: 0.92-1.18, P = 0.488) were not associated with OC risk. For CC, only two studies were available; one assessed moderate PA and the other assessed high PA. Moderate PA was not associated with CC risk (RR = 1.06, 95% CI: 0.90-1.25), and high PA also showed no significant association with CC risk (RR = 0.77, 95% CI: 0.50-1.18). CONCLUSION: High PA is associated with a reduced risk of EC, while no significant association was found for OC. Evidence for CC remains limited and inconsistent. These findings support current PA guidelines for cancer prevention but should be interpreted with caution due to study heterogeneity and limited data. Further prospective studies are needed to clarify these associations, particularly for OC and CC.
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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 | 0.022 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.066 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".