Association between physical activity and infertility: a comprehensive systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Background Physical activity (PA) may protect against infertility by modulating the hypothalamic-pituitary–gonadal axis, thereby reducing gonadotropin levels, elevating immune function, and inhibiting inflammation and circulating sex hormones. However, whether PA reduces the risk of infertility remains largely unknown. We therefore conducted a systematic review and meta-analysis to determine the preventive effects of PA on infertility. Methods We searched PubMed, Cochrane Library, EMBASE, and CINAHL databases to retrieve published epidemiologic studies on the relationship between PA and infertility. Following the PRISMA guidelines, we selected English literature publishedprior to 11 April 2022, and assessed study quality using the Newcastle–Ottawa Scale. Our protocol, including the full methods employed for this review, is available on PROSPERO (ID = CRD42020143344). Results Six cohort studies and four case–control studies based on 708,965 subjects and 12,580 cases were eventually screened and retained. High levels of PA were shown to reduced risk of infertility relative to low levels (cumulative relative risk [RR] = 0.59, with a 95% confidence interval CI 0.49–0.71), and we reported results for cohort studies (RR = 0.63, 95% CI 0.50–0.79) and case–control studies (RR = 0.49, 95% CI 0.35–0.67). Our findings were comparable for men (RR = 0.65, 95% CI 0.41–1.04) and women (RR = 0.56, 95% CI 0.47–0.66). The meta-analysis of six risk estimates from five studies of low, moderate, and high PA levels showed that moderate PA may also reduce the risk of infertility compared with low PA (RR = 0.54, 95% CI 0.38–0.77). However, high PA also appeared to slightly augment the risk of infertility compared with moderate PA (RR = 1.31, 95% CI 1.08–1.59). Conclusions This present systematic review comprehensively reflected an inverse relationship between different levels of PA and infertility, and our meta-analysis showed that a moderate-to-high PA level significantly reduced the overall risk of infertility, and that this level of PA activity was a common protective factor. In addition, limited evidence suggested that compliance with international PA guidelines would greatly lower the risk of infertility (RR = 0.58, 95% CI 0.45–0.74; I2 = 0.0%). Future studies, however, need to be executed to further determine the frequency, optimal dosage, and duration required to effectively attenuate the risk of infertility.
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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 | 0.011 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.031 |
| Bibliometrics | 0.008 | 0.009 |
| 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) | 0.004 | 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".