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改善睡眠质量的最佳运动方式和剂量:一项网状Meta分析及剂量反应关系研究

The best approaches and doses of exercise for improving sleep quality: a network meta-analysis and dose-response relationship study.

作者信息

Wang Hai, Xin Xianyang, Pan Yingxu

机构信息

Capital University of Physical Education and Sports, Beijing, 100191, China.

出版信息

BMC Public Health. 2025 Apr 11;25(1):1371. doi: 10.1186/s12889-025-22570-1.

Abstract

BACKGROUND

Poor sleep quality not only diminishes people's quality of life and work efficiency but is also closely associated with various diseases. A reasonable exercise regimen can improve sleep quality to some extent, but there is a lack of comparative studies on the effects of different types of exercise, especially varying exercise doses, on sleep quality.

OBJECTIVE

To systematically evaluate the effects of different exercise modalities and doses on sleep quality.

METHODS

A search was conducted in PubMed, Web of Science, EBSCO, Cochrane Library, and China National Knowledge Infrastructure (CNKI) databases for randomized controlled trials (RCTs) on the effects of different exercise modalities on sleep quality, from database inception to November 2024. Two researchers independently screened the literature, extracted data, and assessed the risk of bias in the included studies. Network meta-analysis and dose-response analysis were performed using Stata 16.0 and R software with a random-effects model.

RESULTS

A total of 86 RCTs involving 7,276 participants were included. Six types of interventions were assessed: Aerobic Exercise (AE), Resistance Training (RT), Combined Aerobic and Resistance training (AE + RT), Yoga, Pilates, and Traditional Chinese Sports (TCS). The network meta-analysis results showed that compared to the control group, AE (SMD = -1.21, 95% CI: -1.50, -0.91, P < 0.01), RT (SMD = -1.12, 95% CI: -1.80, -0.44, P < 0.01), AE + RT (SMD = -1.11, 95% CI: -1.56, -0.66, P < 0.01), YOGA (SMD = -0.82, 95% CI: -1.22, -0.42, P < 0.01), Pilates (SMD = -1.65, 95% CI: -2.42, -0.88, P < 0.01), and TCS (SMD = -0.94, 95% CI: -1.28, -0.60, P < 0.01) all significantly improved sleep quality. The cumulative ranking probability (SUCRA) ranking showed that Pilates (91.7%) was the most effective, followed by AE (69.7%), AE + RT (59.4%), RT (58.6%), TCS (40.5%), and YOGA (30.1%). Additionally, the relationship between exercise dose and sleep quality was nonlinear, following a U-shaped curve. The overall optimal exercise dose for improving sleep quality was 920 MET-min/week. The optimal doses varied across exercise types, ranging from 390 MET-min/week for Pilates to 1,100 MET-min/week for aerobic exercise.

CONCLUSION

This study provides strong support for non-pharmacological interventions to improve sleep quality. For individuals aiming to improve their sleep through exercise, Pilates and aerobic exercise are recommended as the preferred options. Additionally, controlling the exercise dose within the optimal range (e.g., 920 MET-min/week) can significantly enhance the intervention effect.

CLINICAL TRIAL NUMBER

Not applicable.

摘要

背景

睡眠质量差不仅会降低人们的生活质量和工作效率,还与多种疾病密切相关。合理的运动方案可以在一定程度上改善睡眠质量,但缺乏关于不同类型运动,尤其是不同运动剂量对睡眠质量影响的比较研究。

目的

系统评价不同运动方式和剂量对睡眠质量的影响。

方法

在PubMed、Web of Science、EBSCO、Cochrane图书馆和中国知网(CNKI)数据库中进行检索,查找从建库至2024年11月关于不同运动方式对睡眠质量影响的随机对照试验(RCT)。两名研究人员独立筛选文献、提取数据并评估纳入研究的偏倚风险。使用Stata 16.0和R软件,采用随机效应模型进行网络荟萃分析和剂量反应分析。

结果

共纳入86项RCT,涉及7276名参与者。评估了六种干预类型:有氧运动(AE)、抗阻训练(RT)、有氧和抗阻联合训练(AE+RT)、瑜伽、普拉提和中国传统运动(TCS)。网络荟萃分析结果显示,与对照组相比,AE(标准化均数差[SMD]=-1.21,95%可信区间[CI]:-1.50,-0.91,P<0.01)、RT(SMD=-1.12,95%CI:-1.80,-0.44,P<0.01)、AE+RT(SMD=-1.11,95%CI:-1.56,-0.66,P<0.01)、瑜伽(SMD=-0.82,95%CI:-1.22,-0.42,P<0.01)、普拉提(SMD=-1.65,95%CI:-2.42,-0.88,P<0.01)和TCS(SMD=-0.94,95%CI:-1.28,-0.60,P<0.01)均能显著改善睡眠质量。累积排序概率(SUCRA)排名显示,普拉提(91.7%)最有效,其次是AE(69.7%)、AE+RT(59.4%)、RT(58.6%)、TCS(40.5%)和瑜伽(30.1%)。此外,运动剂量与睡眠质量之间呈非线性关系,呈U形曲线。改善睡眠质量的总体最佳运动剂量为920梅脱-分钟/周。最佳剂量因运动类型而异,从普拉提的390梅脱-分钟/周到有氧运动的1100梅脱-分钟/周不等。

结论

本研究为改善睡眠质量的非药物干预提供了有力支持。对于旨在通过运动改善睡眠的个体,推荐普拉提和有氧运动作为首选。此外,将运动剂量控制在最佳范围内(如920梅脱-分钟/周)可显著增强干预效果。

临床试验编号

不适用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fbc9/11987399/8e68f47bcf00/12889_2025_22570_Fig1_HTML.jpg

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