Cardiometabolic multimorbidity (CMM) is a growing global health challenge. Whether the baseline or cumulative triglyceride glucose and Chinese visceral adiposity index product (TyG-CVAI) can predict incident CMM remains unclear. We constructed two prospective cohorts from the China Health and Retirement Longitudinal Study (CHARLS): Cohort 1 (n = 8895 patients) to assess the association of the baseline TyG-CVAI with CMM and Cohort 2 (n = 5839 patients) to assess the association of the cumulative TyG-CVAI with CMM. The cumulative TyG-CVAI was calculated as the average TyG-CVAI between baseline and the 2015 wave multiplied by the exposure time. Incident CMM was confirmed via a self-reported physician diagnosis, medication use, and clinical data. Cox regression models were used to estimate hazard ratios (HRs). Nonlinearity was assessed using restricted cubic splines, and predictive performance was evaluated by performing a receiver operating characteristic (ROC) curve analysis. During follow-up, 875 and 492 incident CMM cases were documented in Cohort 1 and Cohort 2, respectively. Both the baseline and cumulative TyG-CVAI showed graded, positive associations with the CMM risk. Compared with the lowest quartile, the highest quartile was associated with significantly increased risks (baseline: HR = 1.93, 95% CI = 1.46–2.54; cumulative: HR = 1.76, 95% CI = 1.22–2.53). Significant nonlinear relationships with threshold effects were observed for both indices ( P for nonlinearity < 0.001). Furthermore, compared with their individual components (TyG or CVAI), both the baseline and cumulative TyG-CVAI demonstrated superior predictive ability for CMM, as indicated by a larger area under the ROC curve. Both the baseline and cumulative TyG-CVAI are independent and nonlinear predictors of incident CMM, outperforming TyG or CVAI alone. This easily obtainable metric may enhance risk stratification and help identify high-risk individuals for early preventive intervention.
Zheng et al. (Wed,) studied this question.