Association between the LDL/HDL ratio and sarcopenia in Chinese community-dwelling older adults

S Shanshan Lu (State Key Laboratory of Advanced Materials for Intelligent Sensing & Key Laboratory of Organic Integrated Circuits, Ministry of Education & Tianjin Key Laboratory of Molecular Optoelectronic Sciences, Department of Chemistry, School of Science) C Cheng Wu (Department of Gynecology, Women’s Hospital, School of Medicine) Y Yushuang Lin Z Zhengkai Shen X Xiang Lu

Abstract

Objectives The link between lipid disorders and diverse diseases is amply documented. Yet, research probing how serum lipid levels tie in with sarcopenia remains scarce. This study delves into the connection between the LDL/HDL ratio and sarcopenia among elderly Chinese people. Methods A total of 3,968 senior participants from Chinese communities were included in this cross-sectional study. To explore the relationship between the LDL/HDL ratio and sarcopenia, both a multivariate logistic regression model and a restricted cubic spline model were used. ROC curve analysis was employed to gauge how well the LDL/HDL ratio can detect sarcopenia. Results Among the participants, 780 were diagnosed with sarcopenia. Multivariable logistic regression unveiled a significant positive correlation between the LDL/HDL ratio and sarcopenia. After adjusting for potential confounders, each unit increase in the LDL/HDL ratio corresponded to an approximately 3-fold higher odds of sarcopenia (OR = 3.01, 95% CI: 2.66–3.41, P  < 0.001). A non – linear relationship between the LDL/HDL ratio and sarcopenia was confirmed by RSC analysis ( P  < 0.001). ROC curve analysis showed that the LDL/HDL ratio outperformed its individual components in predictive ability for sarcopenia. Conclusions This study indicates that the LDL/HDL ratio may serve as an independent risk factor for sarcopenia.

Article Details

Journal PLoS ONE
Volume / Issue Vol. 20, Issue 12
Published December 16, 2025
Pages e0339121
ISSN 1932-6203
Publisher Public Library of Science

Journal Info

PLoS ONE

Public Library of Science

ISSN: 1932-6203 Open Access Health Sciences

Authors (5)

S

Shanshan Lu

State Key Laboratory of Advanced Materials for Intelligent Sensing & Key Laboratory of Organic Integrated Circuits, Ministry of Education & Tianjin Key Laboratory of Molecular Optoelectronic Sciences, Department of Chemistry, School of Science

C

Cheng Wu

Department of Gynecology, Women’s Hospital, School of Medicine

Y

Yushuang Lin

Z

Zhengkai Shen

X

Xiang Lu