Predictive value of the triglyceride-glucose index combined with novel body shape indices for cardiovascular disease: a cross-sectional study based on NHANES.
Cardiovascular disease (CVD) remains one of the leading causes of death worldwide. Insulin resistance (IR) and central obesity are key contributors. The triglyceride-glucose (TyG) index is a simple surrogate for IR, while novel adiposity indices, such as the visceral adiposity index (VAI), lipid accumulation product (LAP), cardiometabolic index (CMI), body roundness index (BRI), and a body shape index (ABSI), better reflect body fat distribution. However, the predictive value of combining TyG with these indices for CVD risk remains unclear.
This cross-sectional study used data from 19,822 adults aged ≥20 years in the U.S. NHANES (1999-2018). CVD was defined by self-reported physician diagnosis. The TyG index and its derivatives (TyG-BMI, TyG-WC, TyG-WHtR, TyG-CMI, TyG-VAI, TyG-LAP, TyG-BRI, TyG-ABSI) were calculated. Weighted logistic regression and restricted cubic spline (RCS) analyses assessed associations and potential nonlinear relationships. Receiver operating characteristic (ROC) curves compared predictive performance.
All TyG-derived indices were significantly associated with higher CVD risk (p<0.05). The strongest associations were observed for TyG-ABSI (OR=3.95, 95% CI: 1.99-7.85) and TyG-BRI (OR=2.10, 95% CI: 1.55-2.85). TyG-VAI and TyG-CMI showed nonlinear relationships with CVD. In ROC analysis, TyG-ABSI achieved the highest discriminative power (AUC=0.69), outperforming TyG and other indices. Subgroup analyses revealed stronger associations among younger, obese, hypertensive, and diabetic males.
Combining the TyG index with body-shape indices markedly improved CVD risk prediction. TyG-ABSI, TyG-BRI, and TyG-CMI showed superior diagnostic performance and may serve as cost-effective tools for early CVD risk assessment in clinical and public health settings.
This cross-sectional study used data from 19,822 adults aged ≥20 years in the U.S. NHANES (1999-2018). CVD was defined by self-reported physician diagnosis. The TyG index and its derivatives (TyG-BMI, TyG-WC, TyG-WHtR, TyG-CMI, TyG-VAI, TyG-LAP, TyG-BRI, TyG-ABSI) were calculated. Weighted logistic regression and restricted cubic spline (RCS) analyses assessed associations and potential nonlinear relationships. Receiver operating characteristic (ROC) curves compared predictive performance.
All TyG-derived indices were significantly associated with higher CVD risk (p<0.05). The strongest associations were observed for TyG-ABSI (OR=3.95, 95% CI: 1.99-7.85) and TyG-BRI (OR=2.10, 95% CI: 1.55-2.85). TyG-VAI and TyG-CMI showed nonlinear relationships with CVD. In ROC analysis, TyG-ABSI achieved the highest discriminative power (AUC=0.69), outperforming TyG and other indices. Subgroup analyses revealed stronger associations among younger, obese, hypertensive, and diabetic males.
Combining the TyG index with body-shape indices markedly improved CVD risk prediction. TyG-ABSI, TyG-BRI, and TyG-CMI showed superior diagnostic performance and may serve as cost-effective tools for early CVD risk assessment in clinical and public health settings.