Journal of Obesity & Metabolic Syndrome



J Obes Metab Syndr 2023; 32(2): 179-180

Published online June 30, 2023

Copyright © Korean Society for the Study of Obesity.

Letter: Triglyceride-Glucose Index Predicts Cardiovascular Outcome in Metabolically Unhealthy Obese Population: A Nationwide Population-Based Cohort Study (J Obes Metab Syndr 2022;31:178-86)

Gwanpyo Koh *

Department of Internal Medicine, Jeju National University College of Medicine, Jeju, Korea

Correspondence to:
Gwanpyo Koh
Department of Internal Medicine, Jeju National University College of Medicine, 15 Aran 13-gil, Jeju 63241, Korea
Tel: +82-64-754-8163
Fax: +82-64-717-1131

Received: February 8, 2023; Reviewed : March 30, 2023; Accepted: April 2, 2023

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Cardiovascular diseases (CVDs) are the most common cause of physical disability and mortality globally1 and the second leading cause of death in Korea.2 Hence, determining predictors of CVD is crucial to promoting human health. Currently, traditional cardiovascular (CV) risk factors are used in CVD prediction models.3 In addition to diabetes mellitus (DM), insulin resistance is the fundamental etiology of atherosclerotic CVD and is used to predict CVD in both people with and without DM.4 The gold standard for diagnosis of insulin resistance is the euglycemic insulin clamp technique; however, this method is complex, invasive, and costly.5 The homeostasis model assessment-estimated insulin resistance index is widely used owing to its convenience; only one blood sample is required. However, it has the following drawbacks: (1) blood insulin concentration must be measured; (2) it cannot be used for individuals receiving insulin therapy; and (3) it is inaccurate in patients with DM with diminished beta-cell function.6 The triglyceride-glucose (TyG) index overcomes these drawbacks. It is calculated using fasting glucose and triglyceride levels and can be used to indicate insulin resistance in people with and without DM.7

Cho et al.8 classified 292,206 participants of the Korean National Health Insurance Service National Health Screening Cohort into four groups (metabolically healthy non-obese, metabolically unhealthy non-obese, metabolically healthy obese [MHO], and metabolically unhealthy obese [MUO]) that were followed from 2009 to 2015. The baseline TyG index was found to be correlated with CV events and CV mortality in the MUO group. However, this study analyzed the correlation between baseline TyG index and the incidence of CVD over 6 years of follow-up. Changes in the TyG index during the follow-up period may have influenced the gradual onset of CVD. Therefore, predicting CVD based on TyG index taken at one time point may be inaccurate and vulnerable to regression dilution biases.9 Furthermore, Cho et al.8 divided the participants into groups based on obesity and metabolic health at baseline to investigate CV events and mortality throughout the follow-up period. Obesity and metabolic health also change over time. Soriguer et al.10 reported that many study participants progressed from MHO to MUO during a 6- or 11-year of follow-up. Furthermore, the incidence of type 2 DM decreased among individuals who lost weight during the follow-up period. Thus, obesity and metabolic health are dynamic and change over time, and ultimately, the incidence of obesity-related outcomes such as type 2 DM and CVD may also differ accordingly.

Additional analysis considering changes in TyG index, obesity, and metabolic health during follow-up would enhance the predictive value of TyG index for CV outcomes.

The authors declare no conflict of interest.

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