Key result
TyG-relative fat mass was independently associated with incident myocardial infarction (HR per SD 1.36; 95% CI 1.04-1.80), while TyG-ABSI and TyG-WHR modesty improved risk prediction over base models.
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Why the study?
Comparative evidence on the performance of the triglyceride-glucose index combined with anthropometric indices for myocardial infarction risk prediction remains limited.
Do integrated triglyceride-glucose and body shape indices (TyG-ANI) improve incident myocardial infarction risk prediction beyond conventional cardiovascular risk factors in adults aged ≥40 years?
Cohort (n=5,044)
Do integrated triglyceride-glucose and body shape indices (TyG-ANI) improve incident myocardial infarction risk prediction beyond conventional cardiovascular risk factors in adults aged ≥40 years?
Hazard Ratio: 1.36 (95% CI 1.04–1.8)
Integrating triglyceride-glucose scores with body shape indices, particularly TyG-ABSI and TyG-WHR, provides modest but significant improvements in predicting incident myocardial infarction over traditional risk factors.
TyG-ANI associations with MI are hypothesis-generating; leaves open their role in risk prediction pending validation.
BACKGROUND The triglyceride-glucose (TyG) index, a surrogate marker of insulin resistance (IR), may improve myocardial infarction (MI) risk prediction when combined with anthropometric indices (ANI). However, comparative evidence on their performance remains limited. OBJECTIVE This study aimed to identify which TyG-ANI were most strongly associated with incident MI in a Middle Eastern population. METHODS This cohort study included 5044 adults aged ≥40 years from the Tehran Lipid and Glucose Study, followed for up to 20 years. Eleven TyG-ANI were evaluated. Random survival forest (RSF) identified predictive indices, and associations with incident MI were examined using Cox proportional hazards models. Incremental predictive performance was assessed using the C-index, net reclassification improvement (NRI), integrated discrimination improvement (IDI), Akaike, and Bayesian information criteria (AIC, BIC). RESULTS During a median follow-up of 19.8 years, 215 participants developed MI. The RSF identified 6 TyG-ANI as predictive indices. In fully adjusted continuous models, TyG-relative fat mass showed the strongest association with incident MI (hazard ratio per SD: 1.36; 95% CI: 1.04-1.80). Adding TyG-ANI to the base model, which included conventional cardiovascular risk factors, resulted in modest but significant improvements in MI risk prediction. TyG-waist-to-hip ratio (WHR) yielded the greatest improvement in discrimination (ΔC-index = 0.006), followed by TyG-a body shape index (ABSI), TyG-conicity index, and TyG-weight-adjusted waist index (ΔC-index ≈ 0.005). TyG-ABSI demonstrated the greatest improvement in NRI (0.144; P = .022) and IDI (0.003; P = .032). TyG-WHR and TyG-ABSI also improved model fit, as indicated by lower AIC and BIC than the base model. CONCLUSION TyG-ABSI and TyG-WHR were independently associated with incident MI and provided modest improvements in risk prediction beyond traditional cardiovascular risk factors.
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Ramezankhani et al. (2026) conducted a cohort in Myocardial infarction risk (n=5,044). Triglyceride-glucose combined with anthropometric indices (TyG-ANI), specifically TyG-relative fat mass vs. Conventional cardiovascular risk factors (base model) was evaluated on Incident myocardial infarction (HR 1.36, 95% CI 1.04-1.80). TyG-relative fat mass was independently associated with incident myocardial infarction (HR per SD 1.36; 95% CI 1.04-1.80), while TyG-ABSI and TyG-WHR modesty improved risk prediction over base models.
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