Evidence mapPaperPMID 42035178Full record

ArticleArchives of public health = Archives belges de sante publique2026

L-shaped association of skeletal muscle mass with all-cause mortality among US adults: a population-based cohort study.

Jinhua Chen, Yundan Bai, Xinyi Zhao, Yijun Tang, Yongjie Deng

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Article in Archives of public health = Archives belges de sante publique, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 authors.

Jinhua ChenDepartment of General Practice, Chengdu Integrated TCM & Western Medicine Hospital, Chengdu, 610041, China. 13348904520@163.com.
Yundan BaiHealth Management Medical Center, Chengdu Integrated TCM & Western Medicine Hospital, Chengdu, 610041, China.
Xinyi ZhaoDepartment of Endocrinology and Metabolism, Chengdu Integrated TCM & Western Medicine Hospital, Chengdu, 610041, China.
Yijun TangGuixi Community Health Service Center, Chengdu Hi-tech Zone, Chengdu, 610041, China.
Yongjie DengGuixi Community Health Service Center, Chengdu Hi-tech Zone, Chengdu, 610041, China.

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6 · The paper itself

Abstract

backgroundThe predicted skeletal muscle mass index (pSMI), derived from the serum creatinine-to-cystatin C ratio (CCR), has emerged as a novel biomarker for predicting the onset of type 2 diabetes mellitus. However, its application remains primarily limited to East Asian populations, and the relationship between pSMI and mortality in general populations remains unclear. Therefore, this study aimed to investigate the association between pSMI and all-cause mortality in a nationally representative US adult population.

methodsWe analyzed data from three cycles (1999-2004) of the National Health and Nutrition Examination Survey (NHANES). pSMI levels were analyzed both as a continuous variable and categorized into tertiles. To assess the association between pSMI and all-cause mortality, we performed multivariable Cox regression, restricted cubic spline (RCS) analysis, and Kaplan-Meier survival analysis.

resultsDuring a median follow-up of 193.2 months (2217 deaths), multivariable-adjusted analyses revealed that higher pSMI levels were significantly associated with reduced all-cause mortality (HR 0.76, 95% CI 0.72-0.80; p < 0.001). Compared to the lowest tertile (T1:4.98-7.83), T2 (7.84-9.18) and T3 (9.19-19.24) showed progressively lower mortality risks (T2: HR 0.79, 95% CI 0.67-0.94, p = 0.009; T3: HR 0.66, 95% CI 0.50-0.88, p = 0.004). Restricted cubic spline analysis demonstrated an L-shaped association (p for non-linear = 0.003) with an inflection point at 10.0 (HR 0.632, 95% CI 0.543-0.721; p < 0.001). Sex-stratified analyses revealed inflection points at 10.5 (males) and 7.6 (females). Kaplan-Meier analysis confirmed significantly improved survival with higher pSMI levels (all p < 0.001 for total population, males and females).

conclusionsThis study identifies pSMI as an independent predictor of lower all-cause mortality, revealing a nonlinear L-shaped association with a distinct threshold effect. The protective relationship remains consistent across both sexes, though with differing inflection points. These findings highlight the clinical importance of assessing skeletal muscle mass for mortality risk stratification.

Indexed as

MortalityNutrition surveysSkeletal muscle mass

Identifiers

PMID42035178
PMCPMC13244961

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