Integration of triglyceride-glucose index and biological aging to predict cardiovascular disease risk in cardiovascular–kidney–metabolic syndrome stages 0–3: a multiple prospective cohort study

The triglyceride–glucose (TyG) index serves as a surrogate marker of insulin resistance and reflects underlying metabolic dysfunction, while biological aging (KDM-BA) independently contributes to cardiovascular vulnerability. However, no study has attempted to integrate metabolic dysfunction and biological aging to improve cardiovascular disease (CVD) risk prediction in individuals with cardiovascular–kidney–metabolic (CKM) syndrome stages 0–3. Multiple prospective cohorts were used, including 286,864 participants from the UK Biobank (UKB), 7237 from the China Health and Retirement Longitudinal Study (CHARLS), and 517 from Sun Yat-sen Memorial Hospital, Sun Yat-sen University, which were further included for external validation of the primary outcome. TyG-KDM-BA was calculated by multiplying the TyG index by KDM-BA. Cox proportional hazards models were used to evaluate the association. Time-dependent receiver operating characteristic (ROC) curves, as well as analyses of incremental predictive value, sensitivity analyses, and external validation were conducted to evaluate predictive performance. During a median follow-up of 15.27 years in UKB, 57,896 incident CVD events occurred (cumulative incidence: 20.18%). During a median follow-up of 7.84 years in CHARLS cohort, 1,610 incident CVD events were observed (cumulative incidence: 22.25%). CVD risk increased progressively across TyG-KDM-BA quartiles in both cohorts. In the fully adjusted model, each 1-SD increase in TyG-KDM-BA was associated with higher CVD risk in both cohorts (UKB: HR = 1.65, 95% CI 1.64–1.67; CHARLS: HR = 1.25, 95% CI 1.18–1.32). Participants in the highest quartile had significantly higher CVD risk than those in the lowest (UKB: HR = 3.97, 95% CI 3.86–4.09; CHARLS: HR = 1.92, 95% CI 1.63–2.25). TyG-KDM-BA was positively associated with CHD and stroke risk in both cohorts. Compared with conventional TyG-derived indices, TyG-KDM-BA achieved higher discrimination for CVD risk prediction, with an area under the curve of 0.657–0.659 over 5–15 years in UKB and moderate, consistent performance in CHARLS. Incremental analyses demonstrated that TyG-KDM-BA provided additional predictive value beyond conventional models and its individual components. External validation analyses supported the robustness of results. TyG-KDM-BA integrates metabolic and aging dimensions, demonstrating superior predictive ability for CVD risk among individuals with CKM stages 0–3 compared to traditional TyG-derived indicators, and may serve as a more effective tool for the early screening and intervention.