Joint association of triglyceride glucose index and relative fat mass with new-onset cardiovascular events: a prospective study from CHARLS

BACKGROUND AND AIM: Insulin resistance (IR), as measured by the triglyceride glucose index (TyG-i), and whole body fat, assessed through relative fat mass (RFM), are significant risk factors for cardiovascular disease (CVD). However, the combined impact of these two parameters on the incidence of new-onset CVD events remains underexplored. This cohort study aims to investigate the individual, synergistic, and potential interactive effects of RFM and TyG-i on the risk of developing new-onset CVD. METHODS: A total of 6,762 participants free of CVD from the China Health and Retirement Longitudinal Study (CHARLS) were included. Participants were stratified into four groups based on the median values of RFM and TyG-i, categorized by sex. To assess the relationships between TyG-i, RFM, and their joint effect on new-onset CVD events, Cox proportional hazards regression and Kaplan-Meier (KM) survival analysis were employed. Both multiplicative and additive interaction effects were evaluated. Furthermore, restricted cubic spline (RCS) methods were used to examine the linear or non-linear relationship between TyG-i, RFM, and the incidence of new-onset CVD events, stratified by sex. The predictive performance of TyG-i alone, RFM alone, and the combination of both for new-onset CVD events was assessed at each wave. Receiver operating characteristic (ROC) analysis was conducted to compare the predictive accuracy of TyG-RFM, TyG-waist circumference (WC), and TyG-waist-to-height ratio (WHR) for CVD risk. The results were further validated through stratified, subgroup, and sensitivity analyses. RESULTS: This study included 6,762 participants aged ≥ 45 years, with a median (interquartile range [IQR]) age of 58 (52-65) years. Of these, 2,951 participants (47.22%) were male. Over a follow-up period of up to nine years, 1,611 participants developed new-onset CVD events. Comparison between individuals with low TyG-i and RFM levels and those with higher values revealed a significant increase in risk, as indicated by the adjusted hazard ratios (HRs). Specifically, stratified analyses showed that high TyG-i alone was associated with an HR of 1.11 (95% confidence interval [CI]: 1.00-1.23), high RFM alone with an HR of 1.18 (95% CI: 1.06-1.31), and the combined high TyG-i/high RFM group with an HR of 1.33 (95% CI: 1.15-1.54), reflecting independent effects without significant interaction. The combination of TyG-i and RFM demonstrated a stronger predictive ability for new-onset CVD events than either marker alone. However, no additive or multiplicative interaction was observed between these two variables (P = 0.15). Subgroup analyses confirmed the absence of significant interaction effects between the exposure variables and any categorical covariates. A J-shaped, non-linear interaction was found between TyG-RFM and new-onset CVD risk in men (Pnon-linear < 0.001), while a linear relationship was observed in women (Pnon-linear = 0.06). Evaluation of the predictive value of TyG-RFM, TyG-WC, and TyG-WHR for new-onset CVD risk showed similar predictive performance for these three obesity-related TyG-i indicators in both men and women. These associations persisted even after excluding participants on antihyperglycemic, antihypertensive, or lipid-lowering medications at baseline, or those with a follow-up period of less than two years. CONCLUSION: This study uncovers a strong association between TyG-i, RFM, and their combined effect on the occurrence of new-onset CVD events. While no synergistic interaction was detected, the joint assessment of TyG-i and RFM improved the predictive ability for new-onset CVD events beyond the individual markers. These findings highlight the potential of these accessible tools for early CVD risk identification, contributing to preventive strategies aimed at reducing the burden of non-communicable diseases in aging populations.