Triglyceride-glucose parameters as predictors of diabetes mellitus incidence in Korean adults: a secondary analysis of a Prospective Cohort Study
Year: 2025
Type: article
Abstract: Purpose: This study aimed to evaluate the association between triglyceride-glucose (TyG)-related parameters and the incidence of diabetes mellitus in Korean adults. Data were obtained from the Korean Genome and Epidemiology Study (KoGES). Methods: This secondary analysis examined data from 6,816 adults aged 40-69 years who participated in the KoGES from 2001 to 2020. TyG-related parameters, including the TyG index, TyG-body mass index (TyG-BMI), TyG-waist circumference (TyG-WC), and TyG-waist-to-height ratio (TyG-WHtR), were assessed. Cox proportional hazards models were employed to determine the association between these parameters and the incidence of diabetes mellitus, with adjustments made for demographic, lifestyle, and health-related characteristics. Results: Higher levels of all TyG-related parameters were significantly associated with an increased risk of developing diabetes mellitus. Specifically, participants in the highest quartile of the TyG index, TyG-BMI, TyG-WC, and TyG-WHtR exhibited significantly higher hazard ratios for diabetes mellitus incidence compared with those in the lowest quartile (p<.001 for all). Notably, the TyG index demonstrated a stronger predictive value for diabetes mellitus than traditional measures such as the homeostatic model assessment of insulin resistance. Conclusion: TyG-related parameters are robust predictors of diabetes mellitus incidence in Korean adults. These findings support the incorporation of TyG-related measures into clinical settings for the early identification and intervention of high-risk populations. Utilizing these parameters for early diagnosis and preventive strategies may significantly enhance diabetes mellitus management.
DOI: 10.4040/jkan.24108
Authors: Yu Jin Park, Miseon Shin, Hyun Seon Jeon, Eun Hee Yang
Language: English
Subfield: Endocrinology, Diabetes and Metabolism
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W4409026191