AUTHOR=Liu Lei , Luo Yufang , Liu Min , Tang Chenyi , Liu Hong , Feng Guo , Wang Meng , Wu Jinru , Zhang Wei 

TITLE=Triglyceride glucose-related indexes and lipid accumulation products—reliable markers of insulin resistance in the Chinese population

JOURNAL=Frontiers in Nutrition

VOLUME=Volume 11 - 2024

YEAR=2024

URL=https://www.frontiersin.org/journals/nutrition/articles/10.3389/fnut.2024.1373039

DOI=10.3389/fnut.2024.1373039

ISSN=2296-861X

ABSTRACT=Background: Insulin resistance (IR) is the pivotal pathogen for metabolic diseases. It is urgently needed to seek out convenient and reliable insulin resistance indicators to early identify IR. This study is aimed to assess the predictive ability of 7 novel obesity and lipid-related indices.
Methods: A total of 5847 female and 3532 male health subjects were included. triglyceride glucose (TyG) index, TyG-BMI, TyG-WC, lipid accumulation products (LAP), body roundness index (BRI), body adiposity index (BAI), visceral obesity index (VAI) were measured and calculated using established formulas. IR was diagnosed by the HOMA-IR index over the third quantile. 
Results: The levels of all 7 lipid-related indices were significantly higher in subjects with higher HOMA-IR values than those with lower HOMA-IR values and displayed moderate to high values (ROC-AUC > 0.6) in predicting IR. Among them, TyG-BMI (AUC:0.729), LAP (AUC:0.708), and TyG-WC (AUC:0.698) showed the strongest association with HOMA-IR. In the female population, the AUC of TyG-BMI for predicting IR was 0.732, LAP was 0.705, and TyG-WC was 0.718. Logistic regression analysis showed the optimal cut-off values of those indicators in predicting IR were: TyG-BMI: male 111.16 (OR=6.05, 95% CI 5.09-9.19), female 101.58 (OR=4.55, 95% CI 4.00-5.16); LAP: male 25.99 (OR=4.53, 95% CI 3.82-5.38), female 16.11 (OR=3.65, 95% CI 3.22-4.14); TyG-WC: male 409.43 (OR=5.23, 95% CI 4.48-6.24), female 342.48 (OR=4.07, 95% CI 3.59-4.61). 
Conclusions: TyG index-related parameters and LAP appear to be good predictors of IR in the Chinese population. Specifically, TyG-BMI may be the most appropriate predictor of IR.