Association between various insulin resistance surrogates and gallstone disease based on national health and nutrition examination survey.

Previous studies have reported potential associations between insulin resistance (IR) and the occurrence of gallstone disease (GSD). Recently, some novel indexes have been developed and applied for the assessment of IR. However, the association of these IR surrogates with GSD is unclear. The present study was designed to investigate the correlation between these novel IR surrogates and the risk of developing GSD and to explore the index with the best predictive value. We conducted a cross-sectional analysis using data from the National Health and Nutrition Examination Survey 2017-March 2020. Participants who self-reported a history of GSD and other necessary information were available and were enrolled. Ten IR surrogates were created based on previous literature. Univariate and multivariate logistic regression models were applied to estimate the effect of higher IR surrogates on the risk of GSD and restricted cubic splines (RCS) were used to show the dose-response relationships. Receiver operating characteristics (ROC) curves were depicted and the areas under the curves (AUC) were calculated to show the diagnostic value of ten indexes, respectively. Finally, the best index was selected and subgroup analysis was performed to further evaluate the risk level in different populations. Among the 2811 participants, 305 (11%) were diagnosed with GSD. According to results from univariate and multivariate logistic regression models, elevated levels of IR surrogates were significantly associated with an increased risk of GSD, including triglyceride glucose-body mass index (TyG-BMI), triglyceride glucose-waist circumference (TyG-WC), triglyceride glucose-waist to height ratio (TyG-WHtR), homeostasis model assessment-insulin resistance (HOMA-IR), metabolic score for insulin resistance (METS-IR), Chinese visceral adiposity index (CVAI), and lipid accumulation product (LAP). The RCS also confirmed the trend of positive correlation between the above indexes and GSD (p for overall < 0.0001). The ROC curves showed that TyG-WHtR demonstrated the strongest predictive power among these indexes, with an area under the curve of 0.6796 (95% CI 0.6513-0.7090). Subgroup analysis of the correlation between TyG-WHtR and GSD showed that the correlation was more pronounced among females, the never-married group, the nondiabetic group, and the group that did not use hypoglycemic or lipid-lowering medication. This study identified several novel IR surrogates that had significant positive correlations with the development of GSD. Among these indexes, TyG-WHtR was the strongest predictor of GSD, and the correlation was more pronounced in female groups and non-diabetic groups, which may provide significant value for screening, disease prediction, and early intervention in high-risk groups in clinical practice.