Relationship between nine triglyceride-glucose-related indices and cardiometabolic multimorbidity incidence in patients with cardiovascular-kidney-metabolic syndrome stage 0–3: a nationwide prospective cohort study

Abstract Background Cardiovascular-kidney-metabolic (CKM) syndrome integrates metabolic, renal, and cardiovascular disease risk. While increasing evidence suggests that triglyceride-glucose (TyG)-related indices are associated with the future risk of cardiometabolic multimorbidity (CMM), their link to CMM in CKM syndrome has not been established. Methods This study analyzed participants with CKM syndrome stage 0–3 from the China Health and Retirement Longitudinal Study (CHARLS) from 2011 to 2020. We used Cox regression analysis, restricted cubic spline (RCS) curves, and Kaplan–Meier (K–M) survival curves to evaluate the relationship between TyG-related indices and CMM risk in patients with CKM stage 0–3 syndrome. Receiver operating characteristic (ROC) curves, net reclassification improvement (NRI), and integrated discrimination improvement (IDI) analyses were used to assess the predictive performance of the TyG-related indices for CMM. Results During a median follow-up of 9 years, 652 participants (9.5%) developed CMM. The fully adjusted model revealed an elevated CMM risk across the highest quartiles of all indices, with hazard increases ranging from 72 to over 200%. A linear dose-response relationship was observed for most indices, except for triglyceride glucose-a body shape index (TyG-ABSI) and C-reactive protein-triglyceride-glucose index (CTI). The triglyceride glucose-Chinese visceral adiposity index (TyG-CVAI) achieved the highest area under the curve (AUC) for CMM prediction (0.679), and compared with the fully adjusted model (Model 4), all indices provided significant incremental predictive values. Conclusion Nine TyG-related indices, particularly TyG-CVAI, are strong independent predictors of future CMM in patients with CKM syndrome stage 0–3. These findings underscore the utility of TyG-related indices, particularly TyG-CVAI, in identifying high-risk individuals, thereby informing strategies for the early detection and prevention of CKM syndrome. Graphical abstract