What question did this study set out to answer?

This research aims to determine how demographic factors influence the effectiveness of TyG and TyG-BMI indices as markers for insulin resistance and mortality risk.

April 17, 2026Open Access

Demographic-specific TyG and TyG-BMI thresholds improve insulin resistance and mortality risk

Key Points

This research aims to determine how demographic factors influence the effectiveness of TyG and TyG-BMI indices as markers for insulin resistance and mortality risk.
Observational, cross-sectional design using data from 11,061 adults in NHANES (1999-2018).
TyG and TyG-BMI indices were calculated and their associations with insulin resistance (HOMA-IR) and mortality were analyzed.
Receiver Operating Characteristic curves, Cox regression, and Kaplan–Meier survival analyses were employed to evaluate performance and mortality associations.
Stratified thresholds were derived based on age, biological sex, and ethnicity.
TyG and TyG-BMI values were significantly influenced by age, biological sex, and ethnicity, with higher values seen in males and older individuals.
TyG-BMI correlated more strongly with HOMA-IR (r = 0.574) compared to TyG (r = 0.409).
Demographic-specific thresholds improved sensitivity (93.8%) and specificity (82.4%), particularly in older males from underrepresented ethnic groups.
Higher TyG indices had a stronger association with all-cause mortality (Hazard Ratio = 2.3) compared to TyG-BMI or HOMA-IR.

Abstract

Introduction: Insulin resistance (IR) is a key contributor to metabolic disorders and mortality. The triglyceride–glucose (TyG) and TyG–body mass index (TyG-BMI) indices are increasingly used as surrogate markers of IR. However, the influence of demographic factors, such as age, biological sex, and ethnicity, on their performance remains unclear. Materials and methods: This observational, cross-sectional study utilized 11,061 adults (n-weighted = 39,603,280) from the 1999–2018 National Health and Nutrition Examination Survey (NHANES), linked to mortality follow-up through 2018. TyG and TyG-BMI indices were calculated, and their associations with IR defined by Homeostatic Model Assessment for IR (HOMA-IR) and all-cause mortality were examined using Receiver Operating Characteristic (ROC) curves, Cox regression, and Kaplan–Meier survival analyses. Thresholds were derived for the overall population and by age, biological sex, and ethnicity. Results: TyG and TyG-BMI were significantly influenced by age, biological sex, and ethnicity. Males and older individuals had higher index values, while ethnic differences were notable, particularly among Mexican Americans and non-Hispanic Black individuals. TyG-BMI showed a stronger correlation with HOMA-IR (r = 0.574, p < 0.001) than TyG (r = 0.409, p < 0.001). Stratified thresholds were associated with improved diagnostic performance, with TyG-BMI showing the highest sensitivity (93.8%) and specificity (82.4%) among older males from underrepresented ethnic groups. Elevated TyG and TyG-BMI indices were significantly associated with all-cause mortality, with TyG showing a stronger association (Hazard Ratio = 2.3, 95% confidence interval: 1.8–2.8, p < 0.001) than TyG-BMI or HOMA-IR. Conclusions: Demographic-specific TyG and TyG-BMI thresholds are associated with improved identification of IR and stratification of mortality risk, supporting their potential utility as accessible, cost-effective tools for metabolic risk assessment in diverse populations.

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