Zhang Yanyu, Liu Xiaoyi, Luo Deyun, Chen Bingli, Lai Chenyi, He Chenyu, Yan Luo, Ding Haifeng, Li Shiyang
Clinical Laboratory, Panzhihua Central Hospital, Panzhihua, China.
Department of Geriatrics, Panzhihua Central Hospital, Panzhihua, China.
Clin Transl Sci. 2025 Jan;18(1):e70122. doi: 10.1111/cts.70122.
Hyperuricemia (HUA) is a metabolic abnormality syndrome caused by disorders of purine metabolism. This study aimed to investigate the predictive value of the low-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (LHR) for the risk of developing HUA. We extracted data from the China Health and Retirement Longitudinal Study (CHARLS) database from 2011 to 2016. Multivariable logistic regression, restricted cubic splines (RCSs) analysis, and linear correlation analysis were conducted to evaluate the association between LHR and risk of developing HUA. Subgroup analyses and interaction tests were also performed. A higher LHR was associated with an increased incidence of HUA (7.8% vs. 9.9% vs. 13.9, p < 0.001). The LHR was also higher in the HUA group compared to the non-HUA group (2.64 ± 1.07 vs. 2.40 ± 0.91, p < 0.001). When assessed as a continuous variable, LHR was independently associated with the risk of HUA (OR = 1.27, 95% CI = 1.16-1.39, p < 0.001). The risk of developing HUA was significantly higher among individuals with the highest LHR subgroup than those with the lowest LHR subgroup (OR = 1.81, 95% CI = 1.47-2.23, p < 0.001). RCS analysis revealed a significant nonlinear association between an increased LHR and a higher risk of developing HUA. The predictive abilities of LHR for HUA were 0.577. The composite variable comprising LHR and other traditional risk factors could significantly enhance the ability to predict HUA (C statistic = 0.677). In conclusion, a higher LHR was associated with an increased risk of developing HUA. Further studies on LHR could be beneficial for preventing and treating HUA.
高尿酸血症(HUA)是一种由嘌呤代谢紊乱引起的代谢异常综合征。本研究旨在探讨低密度脂蛋白胆固醇与高密度脂蛋白胆固醇比值(LHR)对发生HUA风险的预测价值。我们从中国健康与养老追踪调查(CHARLS)数据库中提取了2011年至2016年的数据。进行多变量逻辑回归、受限立方样条(RCS)分析和线性相关分析,以评估LHR与发生HUA风险之间的关联。还进行了亚组分析和交互检验。较高的LHR与HUA发病率增加相关(7.8%对9.9%对13.9,p<0.001)。与非HUA组相比,HUA组的LHR也更高(2.64±1.07对2.40±0.91,p<0.001)。当作为连续变量评估时,LHR与HUA风险独立相关(OR=1.27,95%CI=1.16-1.39,p<0.001)。LHR最高亚组的个体发生HUA的风险显著高于LHR最低亚组的个体(OR=1.81,95%CI=1.47-2.23,p<0.001)。RCS分析显示LHR升高与发生HUA的较高风险之间存在显著的非线性关联。LHR对HUA的预测能力为0.577。包含LHR和其他传统风险因素的复合变量可显著提高预测HUA的能力(C统计量=0.677)。总之,较高的LHR与发生HUA的风险增加相关。对LHR的进一步研究可能有助于HUA的防治。