The American journal of the medical sciences · 2025
TyG and TyG-BMI indices as predictive biomarkers for T2DM risk in overweight and obese individuals: Insights from the CHNS database clinical study.
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Li Ranhao, Wang Yangxingyun, Wang Wei
Аннотация
BACKGROUND: Diabetes mellitus (DM) is a metabolic disorder that lacks specific early diagnostic markers and is often associated with serious complications and comorbidities. The triglyceride-glucose index (TyG) and the triglyceride-glucose-body mass index (TyG-BMI) are key metabolic indicators related to insulin resistance and β-cell dysfunction. However, their association with the development of type 2 diabetes mellitus (T2DM) remains unclear. This study aimed to examine the relationship between TyG and TyG-BMI levels and the incidence of T2DM, evaluate their predictive performance, and support the identification of populations at high risk for T2DM.
METHODS: Data were obtained from the 2009 China Health and Nutrition Survey (CHNS), including 9498 participants. TyG and TyG-BMI were calculated, and their associations with T2DM risk were assessed using a Cox regression model. Predictive performance was evaluated with receiver operating characteristic (ROC) curve analysis.
RESULTS: In the overall population, including both sexes, individuals aged >50 years and ≤50 years, and both urban and rural residents, higher TyG and TyG-BMI levels were independently associated with T2DM, showing a linear dose-response relationship. Both indicators demonstrated predictive value for T2DM, with TyG-BMI showing stronger associations, a larger area under the ROC curve, and greater clinical relevance.
CONCLUSIONS: These results suggest that both TyG and TyG-BMI are useful predictors of T2DM, with TyG-BMI providing superior predictive accuracy. These findings support the use of these indices in the early screening of high-risk T2DM populations.
METHODS: Data were obtained from the 2009 China Health and Nutrition Survey (CHNS), including 9498 participants. TyG and TyG-BMI were calculated, and their associations with T2DM risk were assessed using a Cox regression model. Predictive performance was evaluated with receiver operating characteristic (ROC) curve analysis.
RESULTS: In the overall population, including both sexes, individuals aged >50 years and ≤50 years, and both urban and rural residents, higher TyG and TyG-BMI levels were independently associated with T2DM, showing a linear dose-response relationship. Both indicators demonstrated predictive value for T2DM, with TyG-BMI showing stronger associations, a larger area under the ROC curve, and greater clinical relevance.
CONCLUSIONS: These results suggest that both TyG and TyG-BMI are useful predictors of T2DM, with TyG-BMI providing superior predictive accuracy. These findings support the use of these indices in the early screening of high-risk T2DM populations.