Comparisons of three novel markers for insulin resistance to predict incident cardiovascular disease: a Korean cohort study from three different regions

Abstract

Background: Cardiovascular disease (CVD) is a crucial human health challenge. Previous studies have shown an association between CVD and the triglyceride-glucose (TyG) index, atherogenic index of plasma (AIP), and metabolic score for insulin resistance (METS-IR). However, a comparison of these novel markers for predicting CVD is not well known. Therefore, we aimed to assess the value of TyG, AIP, and METS-IR in predicting the incidence of CVD in three large cohorts of Korean adults.

Methods: Data from 28 437 participants in the Korean Genome and Epidemiology Study (KoGES) and Korea Health Insurance Review and Assessment (HERAS-HIRA) were assessed. The participants were divided into four groups according to the quartiles of TyG index: ln ([triglyceride × fasting plasma glucose]/2), AIP calculated as log (triglyceride/high-density lipoprotein cholesterol), and METS-IR index: (ln ([2 × fasting plasma glucose] + triglyceride) × body mass index)/(ln [high-density lipoprotein cholesterol-cholesterol]). We prospectively assessed the hazard ratios (HRs) with 95% confidence intervals (CIs) for CVD using multivariate Cox proportional hazard regression models after adjusting for potential confounding variables.

Results: During the follow-up period, 987 participants (3.5%) developed CVD. Compared with the referent first quartiles, the highest TyG index, AIP, and METS-IR quartiles, with HRs of 1.73 (95% CI 1.41-2.12), 1.47 (95% CI 1.19-1.80), and 2.61 (95% CI 1.83-3.72), respectively, significantly predicted future CVD, after adjusting for age, sex, and body mass index. When comparing the three biomarkers for insulin resistance, the TyG index and METS-IR showed similar predictive values, whereas AIP had a lower significance in predicting CVD.

Conclusions: Based on the current findings, novel surrogate markers of insulin resistance, particularly METS-IR and TyG index, may help predict the risk of CVD in Koreans.