Associations of three metabolic biomarkers with the risk of cardiometabolic multimorbidity: a national prospective study

BACKGROUND: Metabolic dysfunction is a key contributor to cardiometabolic diseases (CMD); however, its role in the development of cardiometabolic multimorbidity (CMM) remains insufficiently understood. Using data from the China Health and Retirement Longitudinal Study (CHARLS), this study examined the associations between three metabolic indices and the risk of developing CMM among Chinese adults, namely the triglyceride glucose index (TyG), the cholesterol-high-density lipoprotein-glucose index (CHG), and the C-reactive protein triglyceride glucose index (CTI). METHODS: A total of 5,666 participants were included in this study. The associations between the three metabolic indices and incident CMM were estimated using Cox proportional hazards regression models with adjustment for relevant confounders. Restricted cubic spline analyses were performed to evaluate potential nonlinear associations. The discriminative performance of the metabolic indices was assessed using receiver operating characteristic (ROC) curves and the area under the curve (AUC). Subgroup analyses were conducted according to age and sex. RESULTS: Incident CMM occurred in 473 of 5,666 participants (8.3%). Cox regression analyses showed that higher values of the TyG, CHG, and CTI indices were associated with an increased risk of CMM. Compared with participants in the lowest quartile, those in the highest quartiles of TyG and CTI had substantially higher risks of CMM, with HRs (95% CIs) of 2.10 (1.50-2.94) for TyG Q4 versus Q1 and 2.55 (1.82-3.57) for CTI Q4 versus Q1. In contrast, participants in CHG Q4 did not have a significantly higher risk of CMM than those in Q1, with an HR (95% CI) of 1.12 (0.85-1.48). No significant effect modification by age or sex was observed. ROC analyses indicated that CTI and composite indices incorporating CTI showed relatively better discriminative performance, with AUC values of 0.670 for CTI and 0.671 for the TyG-CTI index. CONCLUSIONS: The three metabolic indices were independently associated with an elevated risk of CMM, with composite indices incorporating CTI showing the strongest discriminative performance. These findings support the use of metabolic indices for early risk stratification and targeted interventions, thereby potentially contributing to healthier aging and reducing the societal burden of CMM.