Da-Hye Son1, Hye Sun Lee2, Yong-Jae Lee3, Jun-Hyuk Lee4, Jee-Hye Han5. 1. Department of Family Medicine, Yonsei University College of Medicine, Gangnam Severance Hospital Seoul, Republic of Korea; Department of Medicine, Yonsei University Graduate School, Seoul, Republic of Korea. 2. Biostatistics Collaboration Unit, Department of Research Affairs, Yonsei University College of Medicine, Seoul, Republic of Korea. 3. Department of Family Medicine, Yonsei University College of Medicine, Gangnam Severance Hospital Seoul, Republic of Korea. 4. Department of Family Medicine, Nowon Eulji Medical Center, Eulji University School of Medicine, Seoul, Republic of Korea. Electronic address: swpapa@eulji.ac.kr. 5. Department of Family Medicine, Nowon Eulji Medical Center, Eulji University School of Medicine, Seoul, Republic of Korea. Electronic address: hanjh1611@eulji.ac.kr.
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.
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.
Authors: Shiau Chin Chong; Norlela Sukor; Sarah Anne Robert; Kim Fong Ng; Nor Azmi Kamaruddin Journal: Front Endocrinol (Lausanne) Date: 2022-10-04 Impact factor: 6.055