Work

Association of triglyceride-glucose index and its combinations with sarcopenia among community-dwelling older adults: based on the Chongqing Aging and Sarcopenia Evaluation (CHASE) cohort

Year: 2025

Type: article

Abstract: Background: The triglyceride-glucose (TyG) index serves as an alternative index for assessing insulin resistance (IR). The relationship between the TyG index and its combined indicators and sarcopenia remains insufficiently explored. Aim: To investigate the association between the TyG index and its combined parameters and sarcopenia. Methods: This cross-sectional study encompassed 792 community-dwelling older adults from the Chongqing Aging and Sarcopenia Evaluation (CHASE) cohort. The multivariate logistic regression model was used to analyze the relationship between the TyG index and its combined parameters, which include the triglyceride glucose-body mass index (TyG-BMI), triglyceride glucose-calf girth (TyG-CG), triglyceride glucose-waist circumference (TyG-WC), and triglyceride glucose-waist-to-hip ratio (TyG-WHR). The receiver operator characteristic (ROC) curve was utilized to assess the diagnostic effect of each index. The integrated discrimination improvement index (IDI) and net reclassification improvement (NRI) were applied to compare the diagnostic efficacy among the indices. Results: < 0.05). The area under the ROC curve (AUC) for the TyG index in predicting the risk of sarcopenia was 0.623 (95% confidence interval: 0.570-0.675). Notably, composite parameters incorporating the TyG index showed enhanced predictive performance. Specifically, TyG-BMI showing the highest AUC of 0.892 (95% confidence interval: 0.860-0.924), indicating its strong predictive potential. Furthermore, the diagnostic efficacy of TyG-BMI was superior to that of all other indicators in both the IDI and NRI. Conclusion: The TyG index demonstrates diagnostic potential for sarcopenia identification, with significantly enhanced accuracy when combined with other parameters. Among them, TyG-BMI is a robust sarcopenia risk predictor due to its superior predictive power.

Source: Frontiers in Physiology

DOI: 10.3389/fphys.2025.1595517