Abstract
BACKGROUND: Type 2 diabetes (T2D) presents a growing global health burden, with early identification of high-risk individuals remaining a critical challenge. The modified cardiometabolic index (MCMI), which integrates visceral fat, lipid ratios, and glucose measures, has emerged as a promising alternative, offering a more comprehensive assessment of metabolic risk. However, no large-scale cohort study has directly assessed the long-term predictive performance of the MCMI for incident T2D, particularly in normoglycemic populations. This study investigates the 12-year predictive performance of the MCMI for incident T2D and compares its efficacy with that of the triglyceride-glucose (TyG) index. METHODS: In this longitudinal cohort study, 15,453 adults with normal baseline glucose were selected from the NAGALA study. The associations of the MCMI and the TyG index with T2D risk were examined using Cox regression models and restricted cubic spline (RCS) analysis. Predictive performance was compared through receiver operating characteristic (ROC) analysis, and subgroup analyses assessed consistency across different populations. RESULTS: Among participants, 373 (2.41%) developed T2D during a mean 6.05-year follow-up. In unadjusted analyses, the TyG index showed an HR of 3.76 (95% CI 3.22–4.38, P < 0.001), while the MCMI demonstrated a stronger association (HR 6.25, 95% CI 5.28–7.40, P < 0.001). These relationships persisted in fully adjusted models. RCS analysis revealed the TyG index and the MCMI maintained a positive linear relationship with T2D risk. ROC analysis indicated superior predictive performance for the MCMI within 1 to 12 years compared to the TyG index and remained relatively consistent in various subgroups. CONCLUSIONS: The MCMI shows a strong, linear association with incident T2D and offers better predictive performance than the TyG index. These findings support the potential clinical utility of the MCMI for T2D risk stratification in normoglycemic individuals. From a broader health system perspective, its application in community-based screening, particularly within underserved regions, may strengthen early detection and support more efficient and accessible preventive care, thereby helping to alleviate the future burden on health systems. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12944-025-02839-5.