Comparison of triglyceride-glucose index and HOMA-IR for predicting prevalence and incidence of metabolic syndrome

Da Hye Son, Hye Sun Lee, Yong Jae Lee, Jun Hyuk Lee, Jee Hye Han

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Abstract

Background and aims: Insulin resistance is related closely to metabolic syndrome (MetS). The homeostasis model assessment of insulin resistance (HOMA-IR) is the most commonly used insulin resistance index, but the triglyceride-glucose (TyG) index has been suggested as a reliable alternative insulin resistance index. This study aims to compare the predictive powers of TyG index and HOMA-IR for the prevalence and incidence of MetS in a large, community-based, prospective cohort over 12 years of follow-up. Methods and results: Data from 9730 adults with or without MetS at baseline, 6091 adults without MetS who were followed as part of the Korean Genome and Epidemiology Study were analyzed. Receiver-operating-characteristic (ROC) curves and time-dependent ROC curves were performed to compare the areas under the ROC curve (AUROC) of the TyG index and HOMA-IR for predicting the prevalence and incidence of MetS. The optimal cut-off points were calculated. Cox proportional hazard spline curves were used to verify dose-response relationship between TyG index/HOMA-IR and incident MetS. TyG index showed higher predictive power for prevalent MetS than HOMA-IR (0.837 vs. 0.680, p < 0.001). The AUROC for incident MetS of TyG index and HOMA-IR was 0.654 (0.644–0.664) and 0.556 (0.531–0.581), respectively (p < 0.001). Cut-off points of TyG index and HOMA-IR for predicting the prevalence of MetS were 8.718 and 1.8 and for predicting incident MetS were 8.518 and 1.5, respectively. Both TyG index and HOMA-IR had a linear relationship with incident MetS. Conclusions: TyG index is superior to HOMA-IR for predicting MetS.

Original languageEnglish
Pages (from-to)596-604
Number of pages9
JournalNutrition, Metabolism and Cardiovascular Diseases
Volume32
Issue number3
DOIs
Publication statusPublished - 2022 Mar

Bibliographical note

Funding Information:
This study was supported by the 2021 JOMES Research Grant (Grant No. KSSO-J-2021003) of the Korean Society for the Study of Obesity. Data in this study were from the Korean Genome and Epidemiology Study (KoGES; 4851-302), National Research Institute of Health, Centers for Disease Control and Prevention, Ministry for Health and Welfare, Republic of Korea.

Funding Information:
This study was supported by the 2021 JOMES Research Grant (Grant No. KSSO-J-2021003 ) of the Korean Society for the Study of Obesity . Data in this study were from the Korean Genome and Epidemiology Study (KoGES; 4851-302), National Research Institute of Health, Centers for Disease Control and Prevention, Ministry for Health and Welfare, Republic of Korea.

Publisher Copyright:
© 2021 The Italian Diabetes Society, the Italian Society for the Study of Atherosclerosis, the Italian Society of Human Nutrition and the Department of Clinical Medicine and Surgery, Federico II University

All Science Journal Classification (ASJC) codes

  • Medicine (miscellaneous)
  • Endocrinology, Diabetes and Metabolism
  • Nutrition and Dietetics
  • Cardiology and Cardiovascular Medicine

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