Effects of different physical activity interventions on women's sleep: a systematic review and network meta-analysis

Sleep disorders are common among women, affecting quality of life and increasing disease risks. Physical activity is a recognized method to improve sleep, but existing meta-analyses lack clear criteria for female groups, with confounding factors from those with diseases or poor sleep, and lack universal advice for the general female population. This study aims to compare and rank different physical activity intervention strategies to provide effective references for improving sleep quality in the general female population.

A systematic search across four databases (PubMed, Cochrane Library, Embase, Web of Science) identified randomized controlled trials (RCTs) on physical activity for sleep in peri- and post-menopausal women. Search timeframe: database inception to June 2025. Two independent researchers selected studies, extracted data, and assessed quality via the Cochrane Risk of Bias Tool. We conducted frequentist network meta-analyses (Stata/SE 15.1) integrated direct and indirect evidence. Surface Under the Cumulative Ranking Curve (SUCRA) ranked interventions by efficacy probabilistically, with higher values indicating superior outcomes.

Fifteen RCTs were finally included in the meta-analysis for synthesis. The results showed that, in terms of the effect on sleep quality in women, aerobic exercise exhibited superior efficacy with a SUCRA value of 77.2%, followed by Multi mode motion with a SUCRA value of 70.5%. Mind body exercise and stretching exercise also showed improvements to a certain extent, with SUCRA values of 57.1% and 38.8%, respectively.

Our findings confirm aerobic exercise appears most effective for improving women's sleep quality, followed by multimodal exercise. Future research should focus on exercise intensity and optimal pre-bedtime timing this will further optimize non-pharmacological interventions for female sleep disorders and provide an evidence base for community health management.

https://www.crd.york.ac.uk/PROSPERO/view/CRD420251058655; identifier: CRD420251058655.