Abstract
BACKGROUND: This study compares the association of eight insulin resistance (IR)-related markers (triglyceride-glucose index (TyG), TyG-body mass index (TyG-BMI), TyG-waist circumference (TyG-WC), TyG-waist-to-height ratio (TyG-WHtR), triglycerides-to-high-density lipoprotein cholesterol ratio (TG/HDL), lipid accumulation product (LAP), visceral adiposity index (VAI), and estimated glucose disposal rate (eGDR)) with cardiovascular disease (CVD). METHODS: Spearman's coefficients were used for correlations between IR-related markers. Predictive capacities were evaluated using receiver operating characteristic (ROC) curve analysis, Akaike Information Criterion, and Bayesian Information Criterion were calculated. Multivariable-adjusted Cox regression models and restricted cubic spline (RCS) analysis were performed to explore associations between IR-related markers and CVD. RESULTS: In Pearson correlation analysis, TyG-WC and TyG-WHtR had a correlation coefficient of 0.95, while TG/HDL ratio and VAI had a correlation coefficient of 0.97. Regarding predictive capacity across different glycemic states, eGDR showed the best performance among the 8 IR-related markers, particularly in predicting stroke. According to Cox regression analysis, with each unit increase in TyG, TyG-BMI, TyG-WC, and TyG-WHtR, the risk of heart disease increased by 24.1%, 0.4%, 0.1%, and 17.56%, respectively; and the risk of stroke increased by 69.3%, 0.6%, 0.2%, and 36.5%, respectively. Additionally, TG/HDL ratio, VAI, and LAP exhibited nonlinear associations with heart disease and stroke risk. For each unit increase in eGDR, the risks of heart disease and stroke decreased by 21% and 14.2%, respectively. CONCLUSION: eGDR is the most effective marker for predicting CVD, especially stroke, across all glycemic states. Modified TyG indices provide better predictive value than TyG alone.