Comparison of novel nutritional index (TCBI) and insulin resistance index (TyG-BMI) for assessing cardiovascular disease risk: a cohort study

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BACKGROUND: Cardiovascular disease (CVD) is a leading cause of death and disability worldwide, particularly among middle-aged and elderly populations. And early risk assessment is essential for early intervention and effective prevention. This study aims to investigate and compare the associations of the triglyceride, total cholesterol and body weight index (TCBI), a novel nutritional index, and the widely researched insulin resistance index-triglyceride glucose-body mass index (TyG-BMI) with CVD risk. METHODS: Using data from the CHARLS (2011-2020), including 8,104 participants without CVD at baseline. The associations of TCBI and TyG-BMI with CVD risk were assessed using Cox proportional hazards models and restricted cubic spline (RCS) analysis. Additionally, receiver operating characteristic (ROC) analysis, subgroup analysis and sensitivity analyses were also conducted. RESULTS: After 9 years, 1,840 participants developed CVD. Each 1-unit increase in log-transformed TCBI (LgTCBI) was associated with a 59% higher risk of CVD (HR 1.59, 95%CI 1.31-1.92, p < 0.001), while a 10-unit increase in TyG-BMI corresponded to a 6% higher risk (HR 1.06, 95% CI 1.04-1.07, p < 0.001). RCS analysis revealed a nonlinear relationship for TCBI and a linear one for TyG-BMI. ROC analysis indicated limited independent predictive accuracy for both indices, with area under the curve (AUC) values ranging from 0.556 to 0.576. In short-term prediction (2-4 years), TCBI and TyG-BMI showed similar discriminatory ability, whereas TyG-BMI performed slightly better in long-term prediction (7-9 years). The subgroup analysis indicated that there was no interaction between the subgroups and the two indices (p for interaction > 0.05). Sensitivity analyses confirmed the robustness of the results. CONCLUSIONS: TCBI and TyG-BMI were significantly associated with an increased CVD risk. Both indices demonstrated limited discriminative ability as standalone predictive tools, but TCBI performed comparably to TyG-BMI in short-term risk assessment, TyG-BMI held a slight advantage in long-term prediction. These findings suggest that TCBI and TyG-BMI may serve as simple, complementary screening tools to help identify high-risk individuals warranting further comprehensive clinical evaluation, rather than as standalone primary screening instruments and their clinical applicability requires further validation in diverse cohorts.

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