Abstract
The cholesterol-high-density lipoprotein-glucose (CHG) index reflects integrated lipid and glucose metabolism, yet its predictive value for cardiovascular disease (CVD) within the cardiovascular-kidney-metabolic (CKM) framework remains unclear. This study developed CHG-BMI, CHG-WC, and CHG-WHtR by incorporating obesity metrics and evaluated their associations with CVD risk. Data were derived from the China Health and Retirement Longitudinal Study (CHARLS). Cox models estimated hazard ratios (HRs) and 95% confidence intervals (CIs). Kaplan-Meier and restricted cubic spline (RCS) analyses assessed cumulative incidence and dose-response patterns. Predictive utility was evaluated using receiver operating characteristic (ROC) curves, Harrell's C-index, net reclassification improvement (NRI), and integrated discrimination improvement (IDI). During a median follow-up of 7 years, 6,705 participants were included, contributing 42,098 person-years of observation, and 1,262 incident CVD events occurred. Cumulative incidence and incidence rates increased progressively across quartiles of CHG-related indices. In the fully adjusted model, each 1-SD increase in CHG, CHG-BMI, CHG-WC, and CHG-WHtR was associated with 8% (HR = 1.08, 95% CI: 1.02-1.14), 15% (HR = 1.15, 95% CI: 1.09-1.21), 16% (HR = 1.16, 95% CI: 1.09-1.23), and 13% (HR = 1.13, 95% CI: 1.07-1.21) higher risk of CVD, respectively. Compared with the lowest quartile, participants in the highest quartile had higher CVD risks for CHG, CHG-BMI, CHG-WC, and CHG-WHtR, with HRs of 1.23, 1.48, 1.44, and 1.50, respectively. RCS analyses showed a generally linear association for CHG-BMI and nonlinear associations for CHG-WC and CHG-WHtR. CHG-derived indices showed modestly higher discriminatory and reclassification performance than CHG alone, with CHG-WHtR generally showing the most favorable but still limited performance. CHG-derived indices were associated with incident CVD among individuals with early-stage CKM syndrome. These indices may provide supplementary information for cardiovascular risk stratification, but their clinical utility requires further validation.