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中国全科医学

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老年男性高尿酸血症的关联因素与防治策略探讨

蒋华杰1，卓琳2，李欣悦1，金瑞3，马悦4，崔景秋5，汪秀英1*   

  1. 1.221000 江苏省徐州市，徐州医科大学徐州临床学院徐州市中心医院肾内科 2.100044 北京市，北京大学人民医院内分泌科 3.221004 江苏省徐州市，徐州医科大学管理学院 4.221004 江苏省徐州市，徐州医科大学公共卫生学院 5.300052 天津市，天津医科大学总医院内分泌代谢科
  • 收稿日期:2025-02-27 接受日期:2025-03-25
  • 通讯作者: 汪秀英
  • 基金资助:
    国家自然科学基金资助项目（82070854）

  • Received:2025-02-27 Accepted:2025-03-25
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摘要： 背景　随着社会发展，高尿酸血症(hyperuricemia, HUA)已与传统“三高”——高血压、高血糖、高血脂并驾齐驱，成为“第四高”。目的　探究老年男性高尿酸血症的关联因素及防治策略，为临床HUA早期干预和治疗提供参考依据。方法　使用横断面研究，观察老年男性健康体检者7 713例，HUA的研究定义为空腹血尿酸(serum uric acid, SUA)≥420μmol/L者。通过单因素分析、Logistic回归分析筛选HUA异常的关联因素。使用综合归因危险度分析、频数分析、对应分析展示HUA危险因素的主要归因、比较共病频数与关联SNP频数以及SUA与相关因素的聚集性。使用中介效应验证HUA与关联因素的效应关系。结果　共检出老年男性高尿酸血症779例，检出率10.10%。单因素分析显示，年龄、身高、体重、BMI、收缩压(SBP)、尿素氮(BUN)、血肌酐(Cr)、肾小球滤过率(eGFR)、三酰甘油(TG)、高密度脂蛋白胆固醇(HDL_C)、低密度脂蛋白胆固醇(LDL_C)、血浆黏度(PV)为老年男性高尿酸血症的关联因素(P<0.05)。Logistic回归分析显示，高SBP、高TG、低eGFR和低HDL_C是HUA的独立关联因素。频数分析显示共同遗传因素仅占极少数，而疾病之间存在大量共病关系。对应分析显示，在SUA逐渐升高的过程中，最先出现高TG、低eGFR和低HDL_C异常组合，SBP、TG、eGFR和HDL_C均正常出现在尿酸3组附近，随后依次出现异常的组合变量。中介效应显示，TG和HDL_C通过SBP致eGFR降低总的中介效应仅占6.00% ； SBP、TG和HDL_C通过eGFR致UA升高总的中介效应为31.88%。结论　老年男性高尿酸血症患病率高。血尿酸与高SBP、高TG、低eGFR、低HDL_C有关联。SBP、TG、HDL_C通过对肾功能损伤导致尿酸升高，eGFR下降在其中起中介作用。

关键词: 高尿酸血症, 脂代谢异常, 收缩压, 肾功能下降, Logistic模型, 对应分析, 中介效应

Abstract: Background With the development of society, hyperuricemia(hyperuricemia, HUA) has become the "fourth high" alongside the traditional "three highs" - hypertension, hyperglycemia and hyperlipidemia.Objective To explore the associated factors and prevention and treatment strategies of hyperuricemia (HUA) in elderly men, and to provide reference for the early intervention and treatment of HUA. Methods A cross-sectional study was conducted in 7 713 healthy elderly men. HUA was defined as serum uric acid (SUA)≥420μmol/L. The associated factors of abnormal HUA were screened by univariate analysis and Logistic regression analysis. Comprehensive attributable risk analysis, frequency analysis, and correspondence analysis were used to demonstrate the main attribution of HUA risk factors, comparison of comorbidity frequency and associated SNP frequency, and aggregation of SUA and related factors. Mediating effect was used to verify the effect relationship between HUA and associated factors. Results A total of 779 cases of hyperuricemia were detected, the detection rate was 10.10%. Single factor analysis showed that Age, height, weight, BMI, systolic blood pressure (SBP), urea nitrogen (BUN), serum creatinine (Cr), glomerular filtration rate (eGFR), triglyceride (TG), high density lipoprotein cholesterol (HDL_C), low density lipoprotein cholesterol (LDL_C), and plasma viscosity (PV) were associated with hyperuricemia in elderly men (P Logistic regression analysis showed that high SBP, high TG, low eGFR and low HDL_C were independent associated factors for HUA. Frequency analysis showed that common genetic factors accounted for only a small number of diseases, but there were a large number of comorbidity relationships between diseases. Correspondence analysis showed that abnormal combinations of high TG, low eGFR and low HDL_C appeared first in the process of SUA increasing gradually, and SBP, TG, eGFR and HDL_C all appeared normally near the uric acid group, followed by abnormal combination variables. The mediating effect showed that the total mediating effect of TG and HDL_C on eGFR decreased by SBP only accounted for 6.00%. The total mediating effect of SBP, TG and HDL_C on UA increase through eGFR was 31.88%. Conclusion The prevalence of hyperuricemia in elderly men is high. Blood uric acid is associated with high SBP, high TG, low eGFR and low HDL_C,SBP, TG and HDL_C lead to the increase of uric acid through the damage of renal function, and eGFR decline plays a mediating role in it.

Key words: hyperuricemia, dyslipidemias, Systolic blood pressure, decreased kidney function, Logistic model, correspondence analysis, mediating effect

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