Relationship Between Four Non-Insulin-Based Indexes of Insulin Resistance and Serum Uric Acid in Patients with Type 2 Diabetes: A Cross-Sectional Study

Abstract

Aim: The aim of this study was to investigate the association between serum uric acid (SUA) levels and four insulin resistance surrogates in patients with type 2 diabetes (T2DM). The four non-insulin-based indexes of insulin resistance (IR) include the glucose and triglycerides index (TyG), TyG index with body mass index (TyG-BMI), ratio of triglycerides to high-density lipoprotein cholesterol (TG/HDL-c) and metabolic score for insulin resistance (METS-IR). Methods: A total of 687 patients with T2DM were enrolled in the current study. Patients were stratified into three groups according to their levels of SUA. Spearman correlation was used to analyze the correlation between SUA and clinical variables. Multiple linear regression analysis was used to assess the association between SUA and the four insulin resistance surrogates. Receiver operating characteristic (ROC) analyses and the area under the ROC curve (AUC) were then used to assess the ability of TyG, TyG-BMI, TG/ HDL-c, and METS-IR to discriminate hyperuricemia (HUA) in T2DM. Results: SUA in T2DM was significantly positively correlated with TyG (r 0.406 P < 0.01), TyG-BMI (r 0.272 P < 0.01), TG/HDL-c (r 0.493 P < 0.01), and METS-IR (r 0.238 P < 0.01). Furthermore, higher values of the four insulin resistance surrogates were independently correlated with higher SUA levels in T2DM patients (P < 0.01 for all) after adjusting for confounding factors. TyG, TyG-BMI, TG/HDL-c, and METS-IR all had a significant discriminative ability for HUA in patients with T2DM. The AUC values were 0.693 (95% CI 0.645–0.741), 0.649 (95% CI 0.599–0.699), 0.768 (95% CI 0.726–0.811), and 0.660 (95% CI 0.609–0.710), respectively. Conclusion: The present study suggests that TyG, TyG-BMI, TG/HDL-c and METS-IR had a significant correlation with SUA in T2DM. TG/HDL-c was the best marker among the four insulin resistance surrogates for the identification of HUA in T2DM.