The relationship between sarcopenia and all–cause and cardiovascular mortality risk among middle–aged and older adults across stages 0–3 of cardiovascular–kidney–metabolic syndrome: evidence from NHANES and CHARLS

肌萎缩 医学 纵向研究 体质指数 全国健康与营养检查调查 比例危险模型 内科学 死亡风险 肌肉团 疾病 死亡率 老年学 前瞻性队列研究 心血管健康 代谢综合征 质量指数 临床营养学 肾脏疾病 瘦体质量 入射(几何) 心脏病学 风险因素 环境卫生 手部力量 风险评估 死因 回归分析
作者
Yan Chen,Yujun Liu,Shiqi Liu,Yafeng Mu,Zhihai Feng
出处
期刊:CardioRenal Medicine [Karger Publishers]
卷期号:: 1-21
标识
DOI:10.1159/000550891
摘要

BACKGROUND: Sarcopenia has been proved to be associated with cardiovascular diseases, chronic kidney disease, and metabolic disorders, but the relationship between sarcopenia and all-cause and cardiovascular mortality risk among middle-aged and older adults across stages 0-3 of cardiovascular-kidney-metabolic (CKM) syndrome remains unclear. PURPOSE: To investigate the relationship between sarcopenia and all-cause and cardiovascular mortality risk among middle-aged and older adults across stages 0-3 of CKM syndrome based on Nutrition Examination Survey (NHANES) 2011-2018 and the China Health and Retirement Longitudinal Study (CHARLS) 2011-2020. METHODS: Multivariable Cox regression analysis was performed to analyze the association of sarcopenia with all-cause and cardiovascular disease (CVD) mortality. Restricted cubic spline (RCS) analysis was conducted to explore the non-linear relationship between body mass index (BMI)-adjusted muscle mass (appendicular skeletal muscle mass divided by BMI, ASMI) and all-cause and CVD mortality, and machine learning (ML) models were developed for mortality risk prediction. The CHARLS database was utilized as validation to enhance the stability of the results. RESULTS: Over an average follow-up of 5.11 years, NHANES recorded 85 all-cause deaths and 12 CVD deaths. After the full adjustment, sarcopenia was significantly associated with all-cause mortality (weighted HR = 3.428, 95% CI 1.484-7.915, P = 0.004) and CVD mortality (weighted HR = 1.070, 95% CI 1.009-1.570, P = 0.049). RCS analysis revealed a nonlinear negative relationship between ASMI and CVD mortality (P for nonlinear = 0.009). ML models demonstrated robust predictive performance, with random forest (AUC=0.766) achieving the highest accuracy. In the CHARLS cohort, sarcopenia significantly increases all-cause mortality (HR = 2.519, 95% CI 1.402-4.527, P < 0.001), and subgroup analysis reported consistent results with the main analysis, Conclusion: Sarcopenia is significantly associated with all-cause and CVD mortality, and exhibits robust predictive performance for mortality among middle-aged and older individuals within CKM stages 0-3.
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