Association of the triglyceride-glucose index combined with a body shape index with all-cause and cardiovascular mortality in individuals with cardiovascular-kidney-metabolic syndrome stage 0-3: findings from two prospective cohorts.

backgroundThe triglyceride-glucose (TyG) index, as a measure of insulin resistance, has been confirmed to be associated with adverse clinical outcomes. The new composite indicator, TyG-A body type index (TyG-ABSI), by integrating the TyG index and the A body type index, has demonstrated superior efficacy in predicting the risk of cardiovascular death in the general population compared to traditional indicators. This study aims to deeply explore the association between TyG-ABSI and all-cause mortality and CVD mortality in the population with cardiovascular kidney-metabolic syndrome (CKM) stages 0-3. The analysis will be conducted from multiple dimensions such as the intensity of indicator correlation and potential influencing mechanisms, in order to comprehensively reveal the relationship between the two.

resultsWe analyzed data from 13,480 participants in the NHANES cohort (1999-2018) using Cox proportional hazards models and restricted cubic spline functions. The results indicated that elevated TyG-ABSI values were independently associated with a higher risk of all-cause mortality (HR = 1.226, 95% CI 1.104-1.361) and cardiovascular mortality (HR = 1.377, 95% CI 1.149-1.651). Time-dependent receiver operating characteristic (ROC) curves and concordance index evaluations demonstrated that TyG-ABSI yielded more accurate long-term prognostic performance than other TyG-derived metrics. The area under the curve (AUC) of this indicator reached 0.688-0.708 in the prediction of all-cause mortality risk over 5-15 years, and 0.696-0.739 in the prediction of cardiovascular mortality risk. External validation using CHARLS data confirmed the robustness of these findings in predicting all-cause mortality.

conclusionsAmong individuals with CKM stages 0-3, TyG-ABSI demonstrates a stronger association with mortality risk and superior predictive ability compared with other TyG-derived metrics. Its performance suggests a potential role in capturing variations across diverse clinical subgroups, and informing optimal timing for preventive interventions.