瘦体质量
医学
内科学
比例危险模型
队列
体质指数
肌萎缩
肌肉团
队列研究
心脏病学
体重
作者
Chen-An Liu,Tong Liu,Yi-Zhong Ge,Meng-Meng Song,Guo-Tian Ruan,Shi-Qi Lin,Hai-Lun Xie,Jin-Yu Shi,Xin Zheng,Yue Chen,Liuyi Shen,Li Ding,Hanping Shi
标识
DOI:10.1186/s12967-023-04008-7
摘要
Abstract Background The relationship between muscle and prognosis, especially that between muscle distribution across different body parts, and the related prognosis is not well established. Objective To investigate the relationship between muscle distribution and all-cause and cause-specific mortality and their potential modifiers. Design Longitudinal cohort study. C-index, IDI, and NRI were used to determine the best indicator of prognosis. COX regression analysis was performed to explore the relationship between variables and outcomes. Interaction and subgroup analyses were applied to identify the potential modifiers. Participants A total of 5052 participants (weighted: 124,841,420) extracted from the NHANES 2003–2006 of median age 45 years and constituting 50.3% men were assessed. For validation, we included 3040 patients from the INSCOC cohort in China. Main measures Muscle mass and distribution. Key Results COX regression analysis revealed that upper limbs (HR = 0.41, 95% CI 0.33–0.51), lower limbs (HR = 0.54, 95% CI 0.47–0.64), trunk (HR = 0.71, 95% CI, 0.59–0.85), gynoid (HR = 0.47, 95% CI 0.38–0.58), and total lean mass (HR = 0.55, 95% CI 0.45–0.66) were all associated with the better survival of participants (P trend < 0.001). The changes in the lean mass ratio of the upper and lower limbs and the lean mass ratio of the android and gynoid attenuated the protective effect of lean mass. Age and sex acted as potential modifiers, and the relationship between lean mass and the prognosis was more significant in men and middle-aged participants when compared to that in other age groups. Sensitive analyses depicted that despite lean mass having a long-term impact on prognosis (15 years), it has a more substantial effect on near-term survival (5 years). Conclusion Muscle mass and its distribution affect the prognosis with a more significant impact on the near-term than that on the long-term prognosis. Age and sex acted as vital modifiers.
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