A higher TyG-CVAI was associated with an increased risk of new-onset cardiovascular disease, with the highest quartile having a significantly higher risk than the lowest (HR 1.64; 95% CI 1.35-2.00).
Cohort (n=7,977)
Yes
Does a higher TyG-CVAI predict an increased risk of new-onset cardiovascular disease in middle-aged and older Chinese adults?
The TyG-CVAI is a strong, nonlinear predictor of new-onset cardiovascular disease in middle-aged and older Chinese adults, outperforming its individual components.
Hazard Ratio: 1.64 (95% CI 1.35–2)
p-value: p=<0.001
BACKGROUND: Insulin resistance and visceral adiposity are established pathophysiological drivers of cardiovascular disease (CVD). The triglyceride‒glucose (TyG) index and the Chinese visceral adiposity index (CVAI) are respective indicators of these conditions. However, the association of their combination, the TyG-CVAI, with the risk of new-onset CVD in the general population remains unclear. This study aimed to investigate this relationship using data from a large national cohort. METHODS: This prospective study included participants in the China Health and Retirement Longitudinal Study (CHARLS) who lacked CVD at baseline. The TyG-CVAI was calculated and used to categorize participants into quartiles. The primary endpoint was the incidence of new-onset CVD. Kaplan‒Meier analysis was performed to assess the cumulative incidence, while multivariable Cox proportional hazards models were used to estimate risk ratios (HRs) and 95% confidence intervals (CIs). The nonlinearity of the relationship was examined using restricted cubic splines (RCSs), and the predictive performance of the TyG-CVAI was evaluated and compared to that of its components using receiver operating characteristic (ROC) curve analysis. RESULTS: Among the 7977 participants, 1221 ultimately developed a CVD. Kaplan‒Meier analysis showed a significantly higher cumulative incidence of CVD with increasing TyG-CVAI quartiles (log-rank P < 0.001). After full adjustment for demographic, lifestyle, and cardiometabolic risk factors, participants in the highest quartile (Q4) had a significantly higher CVD risk (HR = 1.64, 95% CI 1.35-2.00) than those in the lowest quartile (Q1). RCS analysis revealed a significant nonlinear association between the TyG-CVAI and CVD risk, with a threshold at 778.62; below this point, no significant association was observed, whereas above it, each unit increase in the index conferred a 47% higher CVD risk (HR 1.47, 95% CI 1.31-1.64; P < 0.001). Furthermore, the TyG-CVAI (AUC = 0.6315) outperformed the TyG index (AUC = 0.5938) and the CVAI (AUC = 0.5851) alone in predicting the risk of CVD. CONCLUSIONS: In this national cohort of middle-aged and older Chinese adults, a higher TyG-CVAI was independently and nonlinearly associated with an increased risk of new-onset CVD, demonstrating superior predictive value over its individual components. The TyG-CVAI may serve as a simple and effective integrated tool for the early identification of high-risk individuals for primary CVD prevention.
Zheng et al. (Tue,) conducted a cohort in new-onset cardiovascular disease (n=7,977). TyG-CVAI vs. Lowest quartile (Q1) of TyG-CVAI was evaluated on incidence of new-onset CVD (HR 1.64, 95% CI 1.35-2.00, p=<0.001). A higher TyG-CVAI was associated with an increased risk of new-onset cardiovascular disease, with the highest quartile having a significantly higher risk than the lowest (HR 1.64; 95% CI 1.35-2.00).