Abstract
Metabolic syndrome (MetS) is an important risk factor for atherosclerotic cardiovascular disease (ASCVD). Elevated triglyceride (TG) levels and decreased high-density lipoprotein levels (HDL-C) are predisposing factors for the development of ASCVD. Evidence on the association between atherosclerotic index of plasma [AIP = log (TG/HDL-C)] and MetS is limited. Our study aimed to investigate the association between AIP and MetS. This is a cross-sectional study that determines the presence of MetS by assessing anthropometric and biochemical parameters. Multivariate log-binomial regression models were used to analyze the relationship between AIP and MetS risk. To further test the stability of the results, we performed sensitivity analyses in young, non-obese, and normal lipid population. Smoothing plots explored the potential nonlinear relationship between the AIP index for MetS and the estimated potential risk threshold. Predictive power of AIP for MetS using respondent operating characteristic (ROC) curves. The prevalence of MetS was 67.35%. Multivariate logistic regression analysis showed an independent and positive association between AIP and MetS (Per 1 SD increase, PR = 1.31, 95% CI: 1.15-1.47). Sensitivity analysis demonstrated the stability of the results. Smoothing plot showed a nonlinear relationship between AIP and MetS, with an inflection point of 0.66. ROC curve analysis, AIP was an accurate indicator for assessing MetS in type 2 diabetics (AUC = 0.840, 95% CI: 0.819-0.862). AIP is a stable and independently powerful predictor of MetS in T2DM patients. AIP can be used as a simple assessment tool for the early detection of MetS and disease management for the prevention of cardiovascular disease.