Association of obesity, triglyceride-glucose and its derivatives index with risk of hyperuricemia among college students in Qingdao, China.

Abstract

ObjectiveTo analyze and compare the associations of hyperuricemia (HUA) with obesity, triglyceride-glucose (TyG), and its derivatives in college students. To provide early guidance on risk predictors of HUA in college students.MethodsThis study was a cross-sectional survey including 23,411 participants (age: 17-20 years). Investigators conducted face-to-face interview surveys and physical examinations. Automated biochemical methods were used to detect biochemical indicators such as serum uric acid (UA). Calculation of obesity, TyG, and their derivatives indices were performed. Logistic regression was used to analyze the relationship between different indexes and hyperuricemia. OR value and 95% CI were also calculated. ROC curve was used for assessing the predictive ability of different indices of hyperuricemia.ResultsAfter adjusting for age, SBP, DBP, ALT, AST, TC, BUN, and CREA, multivariate logistic regression showed that the OR value of LAP in the obesity index was higher, especially in women (male OR: 4.347, 95%CI: 3.807, 4.964; female OR: 4.672, 95%CI: 3.800, 5.744). The other three quartiles of TyG derivatives were highly associated with hyperuricemia in men and women compared with the top quartile (all P< 0.05). The risk of hyperuricemia increased with an increase in quartiles. For college students, all indicators could distinguish the presence of hyperuricemia. For men, the area under the curve (AUC) of TyG-WC was the largest (AUC: 0.694; 95%CI: 0.684-0.704; P<0.05), according to the Maximum Youden index 0.290 with cut point value 477.853. In women, TyG-BMI showed a maximum AUC value of 0.702 (95%CI: 0.685-0.719; P<0.05), according to the maximum Youden index of 0.317 with cut point value 132.446. The TyG-WC, TyG-WHtR, TyG-LAP, and LAP indices also had relatively high AUC.ConclusionIn clinical practice, LAP, TYG, and their related derivatives may be used as sensitive indicators for HUA prediction in college students.