Triglyceride–Glucose-Based Anthropometric Indices for Predicting Incident Cardiovascular Disease: Relative Fat Mass (RFM) as a Robust Indicator

Background/Objectives: The triglyceride-glucose (TyG) index is a recognized marker for cardiovascular disease (CVD) risk linked to insulin resistance. Combining TyG with anthropometric indicators (AIs) may improve risk prediction, but the comparative value of different AIs, including novel ones like Relative Fat Mass (RFM), is unclear. This study aimed to identify which combination of TyG and AIs has the strongest association with incident CVD in a middle-aged and elderly Chinese cohort. Methods: In this prospective study, we evaluated the association between the cumulative average of TyG combined with eight AIs (TyG-AIs) and incident CVD, heart disease, and stroke. Using data from 5192 participants in the China Health and Retirement Longitudinal Study (CHARLS), we used multivariable logistic regression to compare the predictive value of these composite indices. Results: During follow-up, 1382 (26.6%) participants developed CVD. After full adjustment, the TyG index alone was only significantly associated with stroke. In contrast, most TyG-AIs showed stronger associations with all outcomes. Notably, the index combining TyG with Relative Fat Mass (TyG-RFM) exhibited the most robust associations with total CVD (OR = 2.236), heart disease (OR = 1.679), and stroke (OR = 3.288) when comparing the highest to lowest quartiles. Conclusions: Cumulative average TyG-AIs, particularly TyG-RFM, demonstrated more robust associations with incident CVD than the TyG index alone. The TyG-RFM index shows promise as a valuable tool to improve cardiovascular risk stratification, especially for identifying at-risk non-obese individuals.