Association of cumulative obesity- and insulin resistance-related indices with incident cardiovascular disease in Chinese middle-aged and elderly populations: a nationwide prospective cohort study

Obesity and insulin resistance (IR) are major contributors to cardiovascular disease (CVD). However, most studies have focused on single indices, and longitudinal evidence on multiple cumulative indices remains limited. This study aimed to systematically assess the associations between 18 cumulative obesity- and IR-related indices (OIRIs) and incident CVD in Chinese middle-aged and elderly adults, identifying the most predictive markers. A total of 2,124 participants from the China Health and Retirement Longitudinal Study (CHARLS) were included. Cumulative OIRIs were calculated as time-weighted averages from 2012 to 2015. The primary outcome was incident CVD, including heart disease and stroke, identified via self-report during follow-up from 2015 to 2020. Cox proportional hazards models were used to assess associations, while receiver operating characteristic (ROC) curves and restricted cubic spline (RCS) analyses evaluated predictive performance and dose–response relationships. Incremental predictive value beyond a base model was quantified using net reclassification improvement (NRI) and integrated discrimination improvement (IDI). During the follow-up period, 378 participants (17.80%) developed CVD. After adjusting for all covariates, eight cumulative OIRIs were significantly associated with CVD. Cumulative estimated glucose disposal rate (eGDR) was inversely associated with CVD risk (HR per SD increase = 0.683, 95% CI: 0.579–0.806). Seven other indices were positively associated with CVD risk: Chinese visceral adiposity index (CVAI), waist-to-height ratio (WHtR), body roundness index (BRI), triglyceride-glucose index (TyG), TyG-waist circumference (TyG-WC), TyG-waist-to-height ratio (TyG-WHtR), and lipid accumulation product (LAP) (all HRs > 1.10, P < 0.05). Cumulative eGDR demonstrated the highest predictive accuracy (AUC = 0.617), outperforming most other indices, followed by cumulative CVAI (AUC = 0.602). RCS models confirmed linear associations for all significant indices except the conicity index. Sex-stratified analyses showed stronger associations for eGDR (P-interaction = 0.024) and CVAI (P-interaction = 0.042) in males. Adding cumulative eGDR to traditional CVD risk models significantly improved prediction (AUC: 0.628→0.654; NRI = 0.285; IDI = 0.016; all P < 0.001). In this national cohort, cumulative eGDR and CVAI were associated with incident CVD. Incorporating cumulative eGDR into traditional risk models was accompanied by modest improvements in discrimination and risk reclassification. These findings suggest that cumulative eGDR and CVAI may offer additional value for CVD risk stratification, although further studies with clinically adjudicated outcomes are warranted.