Evaluating the associations and predictive performance of triglyceride-glucose index and related indicators for chronic diseases in a Chinese cohort - Hongli Liu; Xinmei Mao; Xuechen Wang; Dan Xu; Ting Wen; Jipeng Li (PLoS ONE, 2025)
Background Triglyceride and glucose (TyG) indices have been used as predictors of several chronic diseases. However, there is currently a lack of research that can comprehensively reflect the impact of TyG-related indicators on chronic diseases in middle-aged and elderly populations. The aim of this study was to investigate the relationship of TyG and its related indicators with chronic diseases and their time-dependent predictive ability in the elderly. Study design Retrospective observational cohort study using China Health and Retirement Longitudinal Study (CHARLS) 2011–2020 data. Methods Based on longitudinal data obtained from the CHARLS from 2011 to 2020, a total of 12,966 participants were included in the study. Participants were stratified into three groups according to their TyG index. Pearson correlation coefficient and Cox model are used to assess the relationship between the TyG index, its parameters, and common chronic diseases, while Harrell’s C-index is used to evaluate their risk prediction capability. Results The TyG index and its related indicators exhibit a positive dose-response relationship with the risk of diabetes, heart disease, dyslipidemia, hypertension, and stroke, while demonstrating a negative dose-response relationship with digestive system diseases. Harrell’s C-index results indicated that TyG-WC demonstrates superior predictive performance overall. Conclusion The TyG index and its related indicators are significantly correlated with newly onset emerging chronic diseases, with TyG-WC exhibits superior risk prediction performance.