{"title":"不同睡眠特征对长期骨骼肌损失的影响:一项队列研究","authors":"Seok Woo Hong , Kyung Jae Yoon , Jeong-Hyun Kang","doi":"10.1016/j.maturitas.2025.108739","DOIUrl":null,"url":null,"abstract":"<div><h3>Objective</h3><div>Poor sleep may contribute to hormonal imbalance, increased adiposity, and disruption of energy metabolism. This study aimed to clarify the long-term impact of sleep characteristics on loss of skeletal muscle mass.</div></div><div><h3>Methods</h3><div>We analyzed data from 421,688 participants (220,902 males, 200786 females; mean age 39.1 ± 10.2 years) without a low skeletal muscle index at baseline. Sleep quality was assessed using the Pittsburgh Sleep Quality Index. Skeletal muscle mass was estimated using bioelectrical impedance analysis. Low skeletal muscle index was diagnosed by the Asian Working Group for Sarcopenia 2019 Consensus. Covariates included demographic characteristics, health behavior, and lifestyle-related factors, comorbidities, biochemical markers, and dietary intake. Multivariate Cox regression analyses were conducted to assess effects of sleep characteristics on incidence of low skeletal muscle index.</div></div><div><h3>Results</h3><div>Participants who developed low skeletal muscle index exhibited poorer general sleep quality. Notably, skeletal muscle index, body fat mass, visceral fat area, and body fat percentage all significantly differed with sleep quality. Biochemical assessment revealed significant variations in serum proteins, glucose metabolism markers, lipid profiles, kidney and liver function, and inflammatory markers with sleep quality. After adjusting for confounders, longer sleep latency and lower sleep efficiency remained significant contributors to low skeletal muscle index. Additionally, frequent use of sleep medication and severe sleep disturbances were significantly associated with low skeletal muscle index.</div></div><div><h3>Conclusion</h3><div>Poor sleep quality, particularly longer sleep latency, lower sleep efficiency, frequent use of sleep medication and severe sleep disturbance, significantly impacts maintenance of skeletal muscle mass.</div></div>","PeriodicalId":51120,"journal":{"name":"Maturitas","volume":"202 ","pages":"Article 108739"},"PeriodicalIF":3.6000,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Impact of diverse sleep characteristics on long-term skeletal muscle loss: A cohort study\",\"authors\":\"Seok Woo Hong , Kyung Jae Yoon , Jeong-Hyun Kang\",\"doi\":\"10.1016/j.maturitas.2025.108739\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Objective</h3><div>Poor sleep may contribute to hormonal imbalance, increased adiposity, and disruption of energy metabolism. This study aimed to clarify the long-term impact of sleep characteristics on loss of skeletal muscle mass.</div></div><div><h3>Methods</h3><div>We analyzed data from 421,688 participants (220,902 males, 200786 females; mean age 39.1 ± 10.2 years) without a low skeletal muscle index at baseline. Sleep quality was assessed using the Pittsburgh Sleep Quality Index. Skeletal muscle mass was estimated using bioelectrical impedance analysis. Low skeletal muscle index was diagnosed by the Asian Working Group for Sarcopenia 2019 Consensus. Covariates included demographic characteristics, health behavior, and lifestyle-related factors, comorbidities, biochemical markers, and dietary intake. Multivariate Cox regression analyses were conducted to assess effects of sleep characteristics on incidence of low skeletal muscle index.</div></div><div><h3>Results</h3><div>Participants who developed low skeletal muscle index exhibited poorer general sleep quality. Notably, skeletal muscle index, body fat mass, visceral fat area, and body fat percentage all significantly differed with sleep quality. Biochemical assessment revealed significant variations in serum proteins, glucose metabolism markers, lipid profiles, kidney and liver function, and inflammatory markers with sleep quality. After adjusting for confounders, longer sleep latency and lower sleep efficiency remained significant contributors to low skeletal muscle index. Additionally, frequent use of sleep medication and severe sleep disturbances were significantly associated with low skeletal muscle index.</div></div><div><h3>Conclusion</h3><div>Poor sleep quality, particularly longer sleep latency, lower sleep efficiency, frequent use of sleep medication and severe sleep disturbance, significantly impacts maintenance of skeletal muscle mass.</div></div>\",\"PeriodicalId\":51120,\"journal\":{\"name\":\"Maturitas\",\"volume\":\"202 \",\"pages\":\"Article 108739\"},\"PeriodicalIF\":3.6000,\"publicationDate\":\"2025-09-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Maturitas\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S037851222500547X\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"GERIATRICS & GERONTOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Maturitas","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S037851222500547X","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GERIATRICS & GERONTOLOGY","Score":null,"Total":0}
Impact of diverse sleep characteristics on long-term skeletal muscle loss: A cohort study
Objective
Poor sleep may contribute to hormonal imbalance, increased adiposity, and disruption of energy metabolism. This study aimed to clarify the long-term impact of sleep characteristics on loss of skeletal muscle mass.
Methods
We analyzed data from 421,688 participants (220,902 males, 200786 females; mean age 39.1 ± 10.2 years) without a low skeletal muscle index at baseline. Sleep quality was assessed using the Pittsburgh Sleep Quality Index. Skeletal muscle mass was estimated using bioelectrical impedance analysis. Low skeletal muscle index was diagnosed by the Asian Working Group for Sarcopenia 2019 Consensus. Covariates included demographic characteristics, health behavior, and lifestyle-related factors, comorbidities, biochemical markers, and dietary intake. Multivariate Cox regression analyses were conducted to assess effects of sleep characteristics on incidence of low skeletal muscle index.
Results
Participants who developed low skeletal muscle index exhibited poorer general sleep quality. Notably, skeletal muscle index, body fat mass, visceral fat area, and body fat percentage all significantly differed with sleep quality. Biochemical assessment revealed significant variations in serum proteins, glucose metabolism markers, lipid profiles, kidney and liver function, and inflammatory markers with sleep quality. After adjusting for confounders, longer sleep latency and lower sleep efficiency remained significant contributors to low skeletal muscle index. Additionally, frequent use of sleep medication and severe sleep disturbances were significantly associated with low skeletal muscle index.
Conclusion
Poor sleep quality, particularly longer sleep latency, lower sleep efficiency, frequent use of sleep medication and severe sleep disturbance, significantly impacts maintenance of skeletal muscle mass.
期刊介绍:
Maturitas is an international multidisciplinary peer reviewed scientific journal of midlife health and beyond publishing original research, reviews, consensus statements and guidelines, and mini-reviews. The journal provides a forum for all aspects of postreproductive health in both genders ranging from basic science to health and social care.
Topic areas include:• Aging• Alternative and Complementary medicines• Arthritis and Bone Health• Cancer• Cardiovascular Health• Cognitive and Physical Functioning• Epidemiology, health and social care• Gynecology/ Reproductive Endocrinology• Nutrition/ Obesity Diabetes/ Metabolic Syndrome• Menopause, Ovarian Aging• Mental Health• Pharmacology• Sexuality• Quality of Life