Can adiposity measures enhance the predictive power of the triglyceride-glucose index for metabolic syndrome in adults in the United States?

Background: Insulin resistance is a hallmark feature of metabolic syndrome (MetSyn). The triglyceride-glucose (TyG) index is considered a reliable surrogate measure of insulin resistance. However, the efficacy of the TyG-index combined with adiposity measures for identifying MetSyn in U.S. adults is unknown.

Methods: In the present cross-sectional study, 2746 men and women from the 2017-2020 National Health and Nutrition Examination Survey (NHANES) with physical and laboratory characteristics were included. Predictive powers (estimated by the area under the curve of receiver operating characteristic [ROC-AUC]) of TyG-index combined with adiposity for MetSyn were compared with other traditional surrogate markers of insulin resistance including the TyG index, homeostatic assessment of insulin resistance (HOMA-IR), 1/fasting insulin, and quantitative insulin sensitivity check index (QUICKI).

Results: Predictive power of TyG-WHtR (ROC-AUC: 0.875) for MetSyn was highest, followed by TyG-WC (0.866), TyG-BMI (0.845), TyG index (0.832), HOMA-IR (0.820), QUICKI (0.820) and 1/fasting insulin (0.786). TyG-WHtR and TyG-WC showed significantly higher ROC-AUCs compared with TyG-index, HOMA-IR, 1/fasting insulin, and QUICKI (p ≤ 0.001).

Conclusions: TyG index combined with adiposity metrics is more effective in predicting MetSyn when compared to insulin resistance surrogates (TyG index, HOMA-IR, 1/fasting insulin, and QUICKI) which has been widely used in large cohort observational studies.