Related Factors and Preventive Measures of Hyperuricemia in Elderly Men

doi:10.12114/j.issn.1007-9572.2025.0040

Chinese General Practice ›› 2026, Vol. 29 ›› Issue (27): 3915-3923.DOI: 10.12114/j.issn.1007-9572.2025.0040

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Related Factors and Preventive Measures of Hyperuricemia in Elderly Men

1. Department of Nephrology, Xuzhou Central Hospital, Xuzhou Clinical College, Xuzhou Medical University, Xuzhou 221000, China
2. Department of Endocrinology, Peking University People's Hospital, Beijing 100044, China
3. School of Management, Xuzhou Medical University, Xuzhou 221004, China
4. School of Public Health, Xuzhou Medical University, Xuzhou 221004, China
5. Department of Endocrinology and Metabolism, Tianjin Medical University General Hospital, Tianjin 300052, China

Received:2026-02-27 Revised:2026-03-16 Published:2026-09-20 Online:2026-08-11
Contact: WANG Xiuying

老年男性高尿酸血症的关联因素研究

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

通讯作者: 汪秀英
作者简介:
作者贡献：
蒋华杰提出主要研究目标，负责研究的构思与设计，研究的实施，撰写论文，对文章的知识性内容作批判性审阅；金瑞、马悦进行数据的收集与整理，统计学处理，图、表的绘制与展示；卓琳、李欣悦、崔景秋进行论文的修订，对文章的知识性内容作批判性审阅；汪秀英负责文章的质量控制与审查，对文章整体负责，监督管理。
基金资助:
国家自然科学基金资助项目(82070854)

Abstract

Abstract:

Background

With the development of society, hyperuricemia (HUA) has become the "fourth high" alongside the traditional "three highs": hypertension, hyperglycemia and hyperlipidemia. As a high-risk group, the factors associated with illness in elderly men deserve attention.

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 total of 7 713 elderly men who underwent physical examinations at the Xuzhou Central Hospital (Xuzhou Clinical College of Xuzhou Medical University) in 2021 were included. Baseline data, physical examination results, and laboratory test results were collected to calculate the estimated glomerular filtration rate (eGFR). Univariate analysis and multivariate Logistic regression analysis were employed to investigate the influencing factors of HUA. The IEU database (https://gwas.mrcieu.ac.uk/) was queried, and GWAS datasets from East Asian populations were utilized to examine the clustering of different serum uric acid (SUA) levels with high systolic blood pressure (SBP), high triglycerides (TG), low eGFR, and low high-density lipoprotein cholesterol (HDL-C). Mediation effect analysis was also conducted.

Results

Participants were categorized into a normal group (n=6 934) and an abnormal group (n=779) based on HUA status. Statistically significant differences were observed between the two groups regarding age, height, weight, BMI, SBP, blood urea nitrogen (BUN), serum creatinine (Scr), eGFR, total cholesterol (TC), TG, HDL-C, low-density lipoprotein cholesterol (LDL-C), and plasma viscosity (PV) (P<0.05). Multivariate Logistic regression analysis indicated that high SBP, high TG, low eGFR, and low HDL-C were risk factors for HUA (P<0.05). Chain mediation effect analysis revealed that the total effect of TG on SUA metabolism was 13.100, with a direct effect proportion of 94.37%, identifying it as the primary mechanism. Elevated TG positively predicted increased SBP (B=1.286, 95%CI=0.931-1.642) and elevated SUA (B=13.110, 95%CI=11.572-14.627), while negatively predicting renal function (B=-1.961, 95%CI=-3.102--0.820). Elevated blood pressure negatively predicted renal function (B=-0.094, 95%CI=-0.166--0.023) and positively predicted elevated SUA (B=0.240, 95%CI=0.145-0.334). Renal function negatively predicted elevated SUA (B=-0.206, 95%CI=-0.236--0.177).

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 SUA through the damage of renal function, and eGFR decline plays a mediating role in it. Early control of hyperlipidemia and hypertension in elderly men can protect renal function. When choosing antihypertensive, lipid-lowering and SUA-lowering drugs, a comprehensive assessment of their synergistic effects on metabolism and related organ functions should be conducted, with particular attention paid to the protection of renal function.

Key words: Hyperuricemia, Dyslipidemias, Systolic blood pressure, Decreased kidney function, Logistic model, Correspondence analysis, Mediating effect, Venn diagram

摘要：

背景

随着社会发展，高尿酸血症（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"，老年男性作为高危人群，患病关联因素值得关注。

目的

探究老年男性HUA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

纳入2021年于徐州医科大学徐州临床学院徐州市中心医院健康体检的老年男性7 713例为研究对象，收集基线资料、体格检查结果与实验室检查结果，计算估算肾小球滤过率（eGFR）。采用单因素分析和多因素Logistic回归分析探究HUA的影响因素。检索IEU数据库（https://gwas.mrcieu.ac.uk），利用东亚人群GWAS数据集探讨不同水平的血尿酸（SUA）与高收缩压（SBP）、高甘油三酯（TG）、低eGFR和低高密度脂蛋白胆固醇（HDL-C）不同分组间的聚集性，并进行中介效应分析。

结果

依据是否患有HUA将患者分为正常组（n=6 934）和异常组（n=779）。正常组与异常组研究对象年龄、身高、体质量、BMI、SBP、尿素氮（BUN）、血肌酐（Scr）、eGFR、总胆固醇（TC）、TG、HDL-C、低密度脂蛋白胆固醇（LDL-C）、血浆黏度（PV）比较，差异有统计学意义（P<0.05）。多因素Logistic回归分析结果显示，高SBP、高TG、低eGFR、低HDL-C是HUA的危险因素（P<0.05）。链式中介效应分析结果显示，TG对SUA代谢的总效应为13.100，直接效应占比94.37%，是主要作用机制。TG升高正向预测SBP升高（B=1.286，95%CI=0.931~1.642），正向预测SUA的升高（B=13.110，95%CI=11.572~14.627），负向预测肾功能（B=-1.961，95%CI=-3.102~-0.820）；血压升高负向预测肾功能（B=-0.094，95%CI=-0.166~-0.023），正向预测SUA升高（B=0.240，95%CI=0.145~0.334）；肾功能负向预测SUA升高（B=-0.206，95%CI=-0.236~-0.177）。

结论

老年男性HUA患病率高。SUA与高SBP、高TG、低eGFR、低HDL-C有关联。SBP、TG、HDL-C通过损伤肾功能导致SUA升高，eGFR下降在其中起中介作用。老年男性早期控制高血脂、高血压能保护肾功能，在选用降压、降脂及降SUA药物时，应综合评估其对代谢及相关器官功能的协同影响，尤其需注重对肾功能的保护。

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, 韦恩图

JIANG Huajie,ZHUO Lin,LI Xinyue, et al. Related Factors and Preventive Measures of Hyperuricemia in Elderly Men[J]. Chinese General Practice, 2026, 29(27): 3915-3923. DOI: 10.12114/j.issn.1007-9572.2025.0040.
蒋华杰,卓琳,李欣悦等. 老年男性高尿酸血症的关联因素研究[J]. 中国全科医学, 2026, 29(27): 3915-3923. DOI: 10.12114/j.issn.1007-9572.2025.0040.

Figures/Tables 8

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组别	例数	年龄（±s，岁）	身高（±s，cm）	体质量（±s，kg）	BMI（±s，kg/m²）	SBP（±s，mmHg）	DBP（±s，mmHg）	BUN（±s，μmol/L）	Scr（±s，μmol/L）	eGFR[±s，mL·min^-1·（1.73 m²）^-1]	FPG（±s，mmol/L）
正常组	6 934	69.0±6.4	167.5±5.8	71.7±10.3	25.5±3.2	138±18	83±11	5.45±1.43	76.61±18.83	108.12±57.11	5.92±1.62
异常组	779	70.7±6.6	168.0±5.8	75.5±11.0	26.7±3.5	141±19	83±12	6.46±2.05	94.65±27.62	84.70±47.38	5.82±1.29
t（χ²）值		-7.345	-2.271	-9.754	-9.845	-3.784	-1.169	-17.760	-24.000	11.030	1.627
P值		<0.001	0.023	<0.001	<0.001	<0.001	0.243	<0.001	<0.001	<0.001	0.104
组别	TC（±s，mmol/L）	TG（±s，mmol/L）	HDL-C（±s，mmol/L）	LDL-C（±s，mmol/L）	PV（±s，mPa·s）	职业[例（%）]				高血压[例（%）]
组别	TC（±s，mmol/L）	TG（±s，mmol/L）	HDL-C（±s，mmol/L）	LDL-C（±s，mmol/L）	PV（±s，mPa·s）	企业工人	企业文职	事业单位	公务员	高血压[例（%）]
正常组	5.05±0.92	1.41±1.05	1.25±0.34	3.06±0.75	1.55±0.06	392（88.89）	1 424（90.99）	1 586（90.53）	3 532（89.30）	3 479（89.55）
异常组	5.14±1.05	1.85±1.52	1.17±0.32	3.12±0.80	1.55±0.06	49（11.11）	141（9.01）	166（9.47）	423（10.70）	406（10.45）
t（χ²）值	-2.579	-10.740	6.591	-2.010	-2.019	4.844^a				1.060^a
P值	0.010	<0.001	<0.001	0.044	0.044	0.184				0.303

组别	例数	年龄（±s，岁）	身高（±s，cm）	体质量（±s，kg）	BMI（±s，kg/m²）	SBP（±s，mmHg）	DBP（±s，mmHg）	BUN（±s，μmol/L）	Scr（±s，μmol/L）	eGFR[±s，mL·min^-1·（1.73 m²）^-1]	FPG（±s，mmol/L）
正常组	6 934	69.0±6.4	167.5±5.8	71.7±10.3	25.5±3.2	138±18	83±11	5.45±1.43	76.61±18.83	108.12±57.11	5.92±1.62
异常组	779	70.7±6.6	168.0±5.8	75.5±11.0	26.7±3.5	141±19	83±12	6.46±2.05	94.65±27.62	84.70±47.38	5.82±1.29
t（χ²）值		-7.345	-2.271	-9.754	-9.845	-3.784	-1.169	-17.760	-24.000	11.030	1.627
P值		<0.001	0.023	<0.001	<0.001	<0.001	0.243	<0.001	<0.001	<0.001	0.104
组别	TC（±s，mmol/L）	TG（±s，mmol/L）	HDL-C（±s，mmol/L）	LDL-C（±s，mmol/L）	PV（±s，mPa·s）	职业[例（%）]				高血压[例（%）]
组别	TC（±s，mmol/L）	TG（±s，mmol/L）	HDL-C（±s，mmol/L）	LDL-C（±s，mmol/L）	PV（±s，mPa·s）	企业工人	企业文职	事业单位	公务员	高血压[例（%）]
正常组	5.05±0.92	1.41±1.05	1.25±0.34	3.06±0.75	1.55±0.06	392（88.89）	1 424（90.99）	1 586（90.53）	3 532（89.30）	3 479（89.55）
异常组	5.14±1.05	1.85±1.52	1.17±0.32	3.12±0.80	1.55±0.06	49（11.11）	141（9.01）	166（9.47）	423（10.70）	406（10.45）
t（χ²）值	-2.579	-10.740	6.591	-2.010	-2.019	4.844^a				1.060^a
P值	0.010	<0.001	<0.001	0.044	0.044	0.184				0.303

变量	β	SE	Z值	OR（95%CI）	P值	PARc（sPAR）
高SBP	0.239	0.090	2.66	1.270（1.065~1.514）	0.008	0.097
高TG	0.591	0.128	4.61	1.806（1.405~2.322）	<0.001	0.056
低eGFR	1.464	0.081	18.10	4.322（3.689~5.063）	<0.001	0.301
低HDL-C	0.294	0.109	2.70	1.342（1.084~1.662）	<0.001	0.053
预测模型	-3.061	0.070	-43.60	0.047（0.041~0.054）	<0.001	0.430^a

变量	β	SE	Z值	OR（95%CI）	P值	PARc（sPAR）
高SBP	0.239	0.090	2.66	1.270（1.065~1.514）	0.008	0.097
高TG	0.591	0.128	4.61	1.806（1.405~2.322）	<0.001	0.056
低eGFR	1.464	0.081	18.10	4.322（3.689~5.063）	<0.001	0.301
低HDL-C	0.294	0.109	2.70	1.342（1.084~1.662）	<0.001	0.053
预测模型	-3.061	0.070	-43.60	0.047（0.041~0.054）	<0.001	0.430^a

路径	B	95%CI	SE	效应占比（%）
总效应	13.100	9.964~16.235	1.600
直接效应	12.362	9.359~15.365	1.532	94.37
总的间接效应	0.738	0.439~1.037	0.152	5.63
TG→SBP→SUA	0.308	0.139~0.477	0.086	2.35
TG→eGFR→SUA	0.405	0.200~0.609	0.104	3.09
TG→SBP→eGFR→SUA	0.025	0.005~0.045	0.010	0.19

Related Factors and Preventive Measures of Hyperuricemia in Elderly Men

老年男性高尿酸血症的关联因素研究

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组合变量	SUA 1组	SUA 2组	SUA 3组	SUA 4组	SUA 5组	SUA 6组	SUA 7组	SUA 8组	SUA 9组	合计
0000	72	516	1 165	1 056	434	118	22	5	5	3 393
0001	3	39	113	113	56	19	3	1	0	347
0010	9	125	393	521	382	178	71	20	11	1 710
0011	0	8	37	67	53	36	8	6	3	218
0100	4	9	30	38	38	9	1	1	0	130
0101	3	7	30	35	27	5	3	1	0	111
0110	0	2	7	25	24	23	7	2	0	90
0111	1	0	9	20	19	12	2	0	2	65
1000	28	104	301	261	119	36	9	2	0	860
1001	3	11	22	19	20	5	1	0	0	81
1010	1	18	92	156	117	64	22	10	5	485
1011	0	3	11	22	17	8	7	2	2	72
1100	0	3	12	14	11	4	3	1	0	48
1101	0	1	6	16	7	2	1	0	0	33
1110	0	0	7	11	12	5	3	1	1	40
1111	0	1	4	7	7	4	3	1	3	30
合计	124	847	2 239	2 381	1 343	528	166	53	32	7 713

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