Mutailipu Kelibinuer, Guo Junwei, Yin Jiajing, Wang Yue, Lu Liesheng, Jia Xuyang, Zhang Jie, Qu Shen, Chen Haibing, Bu Le
Department of Endocrinology and Metabolism, Shanghai Tenth People's Hospital, Institute of Obesity, School of Medicine, Tongji University, Shanghai, People's Republic of China.
Department of Metabolic Surgery, Shanghai Tenth People's Hospital, Institute of Obesity, School of Medicine, Tongji University, Shanghai, People's Republic of China.
Endocrinol Diabetes Metab. 2025 Mar;8(2):e70028. doi: 10.1002/edm2.70028.
This study aimed to explore the relationship between hyperuricemia (HUA), the triglyceride-glucose index (TyG) and its derivatives in adult women.
A cross-sectional analysis was conducted on 1105 female patients from Shanghai Tenth People's Hospital. Participants were divided into HUA (n = 331) and non-HUA (n = 774) groups. Clinical and laboratory data were collected, and indices such as body mass index (BMI), TyG and TyG-BMI were calculated. Statistical analyses included univariate and multivariate logistic regression and receiver operating characteristic (ROC) curve analysis.
The HUA group showed higher BMI, blood pressure and metabolic parameters. TyG, TyG-BMI and BMI were positively correlated with uric acid levels. ROC analysis revealed that TyG-BMI (AUC = 0.877) had better predictive power for HUA than TyG (AUC = 0.829) or BMI (AUC = 0.867). Multivariate analysis showed TyG-BMI and BMI as independent predictors, with women in the highest quartiles having a 3.111-fold and 2.779-fold higher risk for HUA, respectively.
TyG-BMI is the most effective predictor of HUA in women, surpassing TyG and BMI alone. It offers a practical tool for early identification and intervention in women at risk of HUA.
本研究旨在探讨成年女性高尿酸血症（HUA）、甘油三酯-葡萄糖指数（TyG）及其衍生指标之间的关系。
对上海市第十人民医院的1105例女性患者进行横断面分析。参与者分为高尿酸血症组（n = 331）和非高尿酸血症组（n = 774）。收集临床和实验室数据，并计算体重指数（BMI）、TyG和TyG-BMI等指标。统计分析包括单因素和多因素逻辑回归以及受试者工作特征（ROC）曲线分析。
高尿酸血症组的BMI、血压和代谢参数较高。TyG、TyG-BMI和BMI与尿酸水平呈正相关。ROC分析显示，TyG-BMI（AUC = 0.877）对高尿酸血症的预测能力优于TyG（AUC = 0.829）或BMI（AUC = 0.867）。多因素分析显示，TyG-BMI和BMI是独立的预测因素，处于最高四分位数的女性患高尿酸血症的风险分别高3.111倍和2.779倍。
TyG-BMI是女性高尿酸血症最有效的预测指标，优于单独的TyG和BMI。它为早期识别和干预有高尿酸血症风险的女性提供了一种实用工具。
