Jiaxiang Gao1,2, Yudian Qiu3,4, Yunfei Hou1,2, Liyi Zhang1,2, Kai Wang1,2, Zhaoyu Chen1,2, Qian Liu1,2, Jianhao Lin5,6. 1. Arthritis Clinic & Research Center, Peking University People's Hospital, Peking University, Beijing, 100044, China. 2. Arthritis Institute, Peking University, Beijing, China. 3. Department of Orthopedics, Beijing Hospital, National Center of Gerontology, Beijing, China. 4. Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China. 5. Arthritis Clinic & Research Center, Peking University People's Hospital, Peking University, Beijing, 100044, China. linjianhao@pkuph.edu.cn. 6. Arthritis Institute, Peking University, Beijing, China. linjianhao@pkuph.edu.cn.
Abstract
BACKGROUND: The decline of muscle strength, a typical characteristic of sarcopenia, greatly affects aging-related health outcomes; however, prospective data on influencing factors and mortality in the Chinese population are relatively sparse. AIMS: We investigated the influencing factors for the declined limb muscle strength and the association with all-cause mortality among the elderly Chinese individuals aged ≥ 65 years in a large long-term prospective cohort study. METHODS: We used data from the China Health and Retirement Longitudinal Study (CHARLS). Logistic regression analyses were performed to investigate the influencing factors of declined limb muscle strength. Cox proportional hazard models were used to analyze the impact on all-cause mortality, whose performance was evaluated by train-test cross-validation. RESULTS: The prevalences of declined upper and lower limb strength, which were defined by low hand grip strength (HS) and gait speed (GS), respectively, were 34.4% and 59.7%. The declined HS was significantly associated with older age (p < 0.001), female (p < 0.001), lower educational level (p < 0.001), lower BMI (p < 0.001), and combined with chronic diseases (p = 0.001). Moreover, the declined limb muscle strength was correlated with all-cause mortality (HR: 1.13, 95% CI 1.03-1.21 for HS; HR: 1.09, 95% CI 1.04-1.15 for GS), according to a multi-adjusted model with moderate predictive ability (C-index: 0.714, AUC of 7 year follow-up: 0.716). CONCLUSIONS: The decline of limb muscle strength was prevalent among elderly Chinese individuals and had a strong impact on all-cause mortality. Identification of key populations and tailored interventions on their influencing factors should be implemented in further research.
BACKGROUND: The decline of muscle strength, a typical characteristic of sarcopenia, greatly affects aging-related health outcomes; however, prospective data on influencing factors and mortality in the Chinese population are relatively sparse. AIMS: We investigated the influencing factors for the declined limb muscle strength and the association with all-cause mortality among the elderly Chinese individuals aged ≥ 65 years in a large long-term prospective cohort study. METHODS: We used data from the China Health and Retirement Longitudinal Study (CHARLS). Logistic regression analyses were performed to investigate the influencing factors of declined limb muscle strength. Cox proportional hazard models were used to analyze the impact on all-cause mortality, whose performance was evaluated by train-test cross-validation. RESULTS: The prevalences of declined upper and lower limb strength, which were defined by low hand grip strength (HS) and gait speed (GS), respectively, were 34.4% and 59.7%. The declined HS was significantly associated with older age (p < 0.001), female (p < 0.001), lower educational level (p < 0.001), lower BMI (p < 0.001), and combined with chronic diseases (p = 0.001). Moreover, the declined limb muscle strength was correlated with all-cause mortality (HR: 1.13, 95% CI 1.03-1.21 for HS; HR: 1.09, 95% CI 1.04-1.15 for GS), according to a multi-adjusted model with moderate predictive ability (C-index: 0.714, AUC of 7 year follow-up: 0.716). CONCLUSIONS: The decline of limb muscle strength was prevalent among elderly Chinese individuals and had a strong impact on all-cause mortality. Identification of key populations and tailored interventions on their influencing factors should be implemented in further research.
Authors: Anne B Newman; Varant Kupelian; Marjolein Visser; Eleanor M Simonsick; Bret H Goodpaster; Stephen B Kritchevsky; Frances A Tylavsky; Susan M Rubin; Tamara B Harris Journal: J Gerontol A Biol Sci Med Sci Date: 2006-01 Impact factor: 6.053
Authors: Alfonso J Cruz-Jentoft; Jean Pierre Baeyens; Jürgen M Bauer; Yves Boirie; Tommy Cederholm; Francesco Landi; Finbarr C Martin; Jean-Pierre Michel; Yves Rolland; Stéphane M Schneider; Eva Topinková; Maurits Vandewoude; Mauro Zamboni Journal: Age Ageing Date: 2010-04-13 Impact factor: 10.668
Authors: Ran Li; Jin Xia; X I Zhang; Wambui Grace Gathirua-Mwangi; Jianjun Guo; Yufeng Li; Steve McKenzie; Yiqing Song Journal: Med Sci Sports Exerc Date: 2018-03 Impact factor: 5.411