Diabetol Metab Syndr. 2026 Jun 12. doi: 10.1186/s13098-026-02209-w. Online ahead of print.
ABSTRACT
BACKGROUND: Cardiovascular disease (CVD) remains a major global health challenge. The triglyceride-glucose (TyG) index and its derived indices serve as indicators of insulin resistance (IR) and are closely associated with CVD incidence. This study aimed to compare the predictive value of different TyG-related indices for CVD incidence and assess the impact of the TyG-BMI across various subgroups, including potential interaction effects.
METHODS: This study conducted a secondary analysis using data from the China Health and Retirement Longitudinal Study (CHARLS), which included 5,382 participants aged 45 years and older. Kaplan-Meier analysis, receiver operating characteristic (ROC) curves, and Cox proportional hazards regression models were employed to evaluate the associations between TyG-related indices and CVD incidence. Subgroup analyses were performed to evaluate the predictive performance of the TyG-BMI across different population categories and assess potential interactions.
RESULTS: Cox proportional hazards regression indicated a significantly increased risk of CVD among participants in the highest quartile of the TyG-BMI, with a hazard ratio (HR) of 1.60 (95% CI: 1.33-1.99). Subgroup analyses confirmed this association across multiple demographic and clinical subgroups, including sex, residence, education level, alcohol consumption, smoking history, and history of hypertension, diabetes, stroke, liver disease, and kidney disease. Restricted cubic spline (RCS) analysis revealed a nonlinear relationship between the TyG-BMI and CVD incidence. Interaction analysis revealed a significant positive interaction between kidney disease and the TyG-BMI.
CONCLUSIONS: The TyG-BMI demonstrated a modestly higher predictive value than other TyG-related indices in predicting CVD risk, establishing it as a valuable tool for clinicians assessing the incidence of CVD.
PMID:42286665 | DOI:10.1186/s13098-026-02209-w