Assessing three novel composite anthropometric-metabolic indices for predicting 10-year incidence of metabolic syndrome: findings from the kerman coronary artery disease risk factors study (KERCADRS)

Purpose: Metabolic syndrome (MetS) is a condition of high prevalence worldwide associated with increased risk of cardiovascular disease. The predictive value of novel indices of combined anthropometric and serum lipid parameters as predictors of MetS is, to our knowledge, unexplored. We aimed to assess the 10-year predictive value of three indices of triglyceride-glucose index (TyG), visceral adiposity index (VAI), and lipid accumulation product (LAP) for incidence of MetS in Southeastern Iran.

Methods: A total of 1084 healthy adults aged 15 to 75 years (among 5895 participants in the KERCADR study) were followed for 10 years. Baseline calculations were performed for LAP, TyG, and VAI. Logistic regression models were employed to assess the association of these indices with the incidence of MetS during the follow-up period. We also evaluated the cut-off value and predictive performance of these indices for predicting MetS using the area under their ROC curves (AUCs).

Results: During 10-year follow-up, 506 MetS cases were documented. The adjusted odds ratio (AOR) with 95% confidence intervals (CI) of the 10-year MetS risk for LAP, VAI, and TyG was as follows: 3.13 (1.79, 5.48), 2.57 (1.60, 4.12), and 2.20 (1.45, 3.35), respectively. In both sexes, LAP exhibited the highest performance (AUC values) compared to the other two composite indices and to the traditional single indices, such as BMI and WC.

Conclusion: Overall, this study revealed significant elevations of LAP, TyG, and VAI in individuals with MetS. LAP demonstrated the highest AUC, over the new and traditional single risk indices of MetS. These findings underscore the potential predictive value of LAP in assessing the 10-year incidence of MetS.