开滦研究人群全血铁与高尿酸血症的关联性研究

王洁蕊; 朱保杰; 王丽; 石慧婧; 崔刘福; 舒荣; 宋海澄; 徐爱刚; 张艳淑

doi:10.16766/j.cnki.issn.1674-4152.003411

开滦研究人群全血铁与高尿酸血症的关联性研究

doi: 10.16766/j.cnki.issn.1674-4152.003411

王洁蕊^{1, 2},
朱保杰¹,
王丽³,
石慧婧²,
崔刘福²,
舒荣²,
宋海澄²,
徐爱刚⁴,
张艳淑^1, ,

1.
华北理工大学公共卫生学院，河北唐山 063210
2.
开滦总医院风湿免疫科，河北唐山063000
3.
中国医学科学院基础医学研究所北京协和医学院基础学院，北京 100730
4.
开滦总医院林西医院急诊科，河北唐山 063100

基金项目:

河北省医学科学研究课题 20231857

详细信息

通讯作者:
张艳淑，E-mail：yanshuzhang@ncst.edu.cn

中图分类号: R446.1 R589.7
计量
- 文章访问数: 86
- HTML全文浏览量: 54
- PDF下载量: 5
- 被引次数: 0
出版历程
- 收稿日期: 2023-08-04
- 网络出版日期: 2024-05-27

Relationship between whole blood iron and hyperuricemia in Kailuan study population

1.
School of Public Health, North China University of Science and Technology, Tangshan, Hebei 063210, China

摘要

摘要: 目的探讨开滦研究人群全血铁与高尿酸血症的关联，为早期预防高尿酸血症提供依据。方法采用横断面研究，研究对象选自2017年8月—2018年5月在林西医院、马家沟医院、荆各庄医院参加健康体检且完成全血铁检测的开滦集团在职和离退休职工，其中符合入选标准的研究对象共3 579人。按血尿酸水平分为正常血尿酸组(2 983例)和高尿酸血症组(596例)，采用多因素logistic回归模型分析全血铁(按照三分位分为Q1~Q3三个亚层)与高尿酸血症的关联，并分析不同年龄对全血铁与高尿酸血症关联的影响。结果高尿酸血症组全血铁[(464.73±104.05)mg/L]显著高于正常血尿酸组[(420.96±109.60)mg/L]，差异有统计学意义(P < 0.001)。多因素logistic回归分析显示，在调整其他混杂因素后，与全血铁Q1组相比，全血铁Q3组发生高尿酸血症的OR值(95% CI)为1.989(1.487~2.661)。在 < 60岁的研究对象中，与全血铁Q1组相比，全血铁Q3组发生高尿酸血症的OR值(95%CI)为2.304(1.539~3.450)；而在≥60岁的研究对象中，与全血铁Q1组相比，全血铁Q3组发生高尿酸血症的OR值(95% CI)为1.269(0.818~1.969)。在敏感性分析中，与全血铁Q1组相比，全血铁Q3组发生高尿酸血症的OR值(95% CI)为2.018(1.499~2.716)。结论较高的全血铁水平与高尿酸血症风险增加相关，且在年龄 < 60岁的人群中有显著关联。
- 血尿酸 /
- 高尿酸血症 /
- 全血铁 /
- 开滦研究人群
Abstract: Objective To explore the relationship between whole blood iron level and hyperuricemia in Kailuan study population, and to provide evidence for the early prevention of hyperuricemia. Methods A cross-sectional study was conducted in 3 579 employees and retirees of Kailuan Group who participated in the health examination and completed the whole blood iron test in Linxi Hospital, Majiagou Hospital and Jinggezhuang Hospital from August, 2017 to May, 2018. According to the level of serum uric acid, the subjects were divided into normal serum uric acid group (n=2 983) and hyperuricemia group (n=596). Multivariate logistic regression model was used to analyze the association between whole blood iron (divided into Q1 to Q3 three subgroups according to tertiles) and hyperuricemia, and the effect of different ages on the association between whole blood iron and hyperuricemia was analyzed. Results The whole blood iron in hyperuricemia group [(464.73±104.05) mg/L] was significantly higher than that in normal serum uric acid group [(420.96±109.60) mg/L, P < 0.001]. Multivariate logistic regression analysis showed that after adjusting for other confounding factors, compared with the whole blood iron Q1 group, the OR value (95% CI) of hyperuricemia in the whole blood iron Q3 group was 1.989 (1.487-2.661). In the subjects aged < 60 years, the OR value (95% CI) of hyperuricemia in the whole blood iron Q3 group was 2.304 (1.539-3.450), while which was 1.269 (0.818-1.969) in the subjects aged ≥60 years. In sensitivity analysis, compared with the whole blood iron Q1 group, the OR value (95% CI) of hyperuricemia in the whole blood iron Q3 group was 2.018 (1.499-2.716). Conclusion Higher whole blood iron level is associated with an increased risk of hyperuricemia, especially in people younger than 60 years old.
- Serum uric acid /
- Hyperuricemia /
- Whole blood iron /
- Kailuan study population

HTML全文

表 1 研究对象基本情况比较

Table 1. Comparison of the basic characteristics of study subjects

项目	总人群(n=3 579)	正常血尿酸组(n=2 983)	高尿酸血症组(n=596)	统计量	P值
性别[例(%)]				60.855^a	< 0.001
男性	1 820(50.85)	1 430(47.94)	390(65.44)
女性	1 759(49.15)	1 553(52.06)	206(34.56)
年龄(x±s，岁)	54.84±12.65	55.18±12.48	53.11±13.34	3.494^b	< 0.001
血尿酸(x±s，μmol/L)	316.21±89.04	288.17±63.62	456.58±60.95	59.410^b	< 0.001
全血铁(x±s，mg/L)	428.25±109.90	420.96±109.60	464.73±104.05	8.979^b	< 0.001
收缩压(x±s，mmHg)	129.94±17.50	129.62±17.63	131.55±16.75	2.453^b	0.014
舒张压(x±s，mmHg)	82.33±10.02	81.88±10.00	84.60±9.80	6.079^b	< 0.001
HDL-C(x±s，mmol/L)	1.49±0.45	1.50±0.40	1.41±0.64	3.359^b	0.001
LDL-C(x±s，mmol/L)	2.74±0.82	2.72±0.83	2.83±0.73	3.258^b	0.001
TG[M(P₂₅, P₇₅), mmol/L]	1.47(0.97, 2.61)	1.41(0.92, 2.56)	1.80(1.24, 2.70)	7.328^c	< 0.001
Hs-CRP[M(P₂₅, P₇₅), mg/L]	1.48(0.58, 3.39)	1.34(0.53, 3.08)	2.48(1.22, 4.72)	11.805^c	< 0.001
BMI(x±s)	24.93±3.42	24.64±3.33	26.35±3.51	11.290^b	< 0.001
eGFR[x±s, mL/(min·1.73 m²)]	99.41±13.59	99.67±13.25	98.13±15.11	2.308^b	0.021
白细胞计数(x±s, ×10⁹/L)	5.96±1.79	5.80±1.78	6.74±1.65	12.502^b	< 0.001
高血压[例(%)]	1 234(34.48)	999(33.49)	235(39.43)	7.758^a	0.005
糖尿病[例(%)]	434(12.13)	379(12.71)	55(9.23)	5.636^a	0.018
注：HDL-C为高密度脂蛋白胆固醇(high density lipoprotein cholesterol)，LDL-C为低密度脂蛋白胆固醇(low density lipoprotein cholesterol)，hs-CRP为超敏C反应蛋白(hypersensitive C-reactive protein)，eGFR为估算的肾小球滤过率(estimated glomerular filtration rate)。^a为χ²值, ^b为t值，^c为Z值。

下载: 导出CSV

表 2 全血铁与高尿酸血症的logistic回归分析

Table 2. Logistic regression analysis of whole blood iron and hyperuricemia

组别	模型1		模型2		模型3
组别	OR(95% CI)	P值	OR(95% CI)	P值	OR(95% CI)	P值
Q2	1.908(1.497~2.433)	< 0.001	1.682(1.300~2.175)	< 0.001	1.653(1.263~2.164)	< 0.001
Q3	2.742(2.171~3.464)	< 0.001	2.120(1.609~2.792)	< 0.001	1.989(1.487~2.661)	< 0.001
注：按全血铁三分位数进行分组, Q1、Q2、Q3分别为 < 363.90、363.90~481.02、≥481.02 mg/L；以Q1为参照。模型1未调整；模型2调整性别、年龄、BMI；模型3在模型2的基础上进一步调整高血压、糖尿病、炎症状态、肾小球滤过率、高密度脂蛋白胆固醇、低密度脂蛋白胆固醇、甘油三酯、白细胞计数。均P_趋势 < 0.001。

下载: 导出CSV

表 3 不同年龄全血铁与高尿酸血症的logistic回归分析

Table 3. Logistic regression analysis of whole blood iron and hyperuricemia across various age groups

组别	≥60岁		< 60岁
组别	OR(95% CI)	P值	OR(95% CI)	P值
Q2	1.269(0.845~1.904)	0.251	1.737(1.198~2.520)	0.004
Q3	1.269(0.818~1.969)	0.287	2.304(1.539~3.450)	< 0.001
注：按全血铁三分位数进行分组, Q1、Q2、Q3分别为 < 363.90、363.90~481.02、≥481.02 mg/L；以Q1为参照。调整性别、年龄、BMI、高血压、糖尿病、炎症状态、肾小球滤过率、高密度脂蛋白胆固醇、低密度脂蛋白胆固醇、甘油三酯、白细胞计数。P_交互 < 0.001。≥60岁P_趋势=0.301， < 60岁P_趋势 < 0.001。

下载: 导出CSV

表 4 排除急性炎症后全血铁与高尿酸血症的logistic回归分析

Table 4. Logistic regression analysis of whole blood iron and hyperuricemia, excluding cases with acute inflammation

组别	模型1		模型2		模型3
组别	OR(95% CI)	P值	OR(95% CI)	P值	OR(95% CI)	P值
Q2	1.925(1.501~2.469)	< 0.001	1.682(1.292~2.190)	< 0.001	1.632(1.239~2.150)	< 0.001
Q3	2.857(2.250~3.628)	< 0.001	2.178(1.643~2.886)	< 0.001	2.018(1.499~2.716)	< 0.001
注：按全血铁三分位数进行分组, Q1、Q2、Q3分别为 < 363.90、363.90~481.02、≥481.02 mg/L；以Q1为参照。模型1未调整；模型2调整性别、年龄、BMI；模型3在模型2的基础上进一步调整高血压、糖尿病、炎症状态(hs-CRP < 1 mg/L、1~3 mg/L、>3 mg/L)、肾小球滤过率、高密度脂蛋白胆固醇、低密度脂蛋白胆固醇、甘油三酯、白细胞计数。均P_趋势 < 0.001。

下载: 导出CSV

参考文献(18)

[1]	ZHANG M, ZHU X, WU J, et al. Prevalence of hyperuricemia among Chinese adults: findings from two nationally representative cross-sectional surveys in 2015-16 and 2018-19[J]. Front Immunol, 2021, 12: 791983. DOI: 10.3389/fimmu.2021.791983.
[2]	李志军. 痛风及高尿酸血症的诊断与治疗[J]. 中华全科医学, 2020, 18(1): 5-6. http://www.zhqkyx.net/article/id/35702025-3b64-4c17-b820-044055abc76e
[3]	PONTICELLI C, PODESTà M A, MORONI G. Hyperuricemia as a trigger of immune response in hypertension and chronic kidney disease[J]. Kidney international, 2020, 98(5): 1149-1159. doi: 10.1016/j.kint.2020.05.056
[4]	CHEN F, YUAN L, XU T, et al. Association of hyperuricemia with 10-year atherosclerotic cardiovascular disease risk among Chinese adults and elders [J]. Int J Environ Res Public Health, 2022, 19(11): 6713. DOI: 10.3390/ijerph19116713.
[5]	LI X, HE T, YU K, et al. Markers of iron status are associated with risk of hyperuricemia among Chinese adults: Nationwide Population-Based Study[J]. Nutrients, 2018, 10(2): 191. doi: 10.3390/nu10020191
[6]	FATIMA T, MCKINNEY C, MAJOR T J, et al. The relationship between ferritin and urate levels and risk of gout[J]. Arthritis Res Ther, 2018, 20(1): 179. doi: 10.1186/s13075-018-1668-y
[7]	WANG Y, YANG Z, WU J, et al. Associations of serum iron and ferritin with hyperuricemia and serum uric acid[J]. Clin Rheumatol, 2020, 39(12): 3777-3785. doi: 10.1007/s10067-020-05164-7
[8]	DEPALMA R G, HAYES V W, O'LEARY T J. Optimal serum ferritin level range: iron status measure and inflammatory biomarker[J]. Metallomics, 2021, 13(6). DOI: 10.1093/mtomcs/mfab030.
[9]	VAN HEGHE L, DELANGHE J, VAN VLIERBERGHE H, et al. The relationship between the iron isotopic composition of human whole blood and iron status parameters[J]. Metallomics, 2013, 5(11): 1503-1509. doi: 10.1039/c3mt00054k
[10]	何国柱, 蔡载熙, 李麓维, 等. 天津市正常人全血和血清微量元素含量分析[J]. 核技术, 1993, 16(2): 119-122. https://www.cnki.com.cn/Article/CJFDTOTAL-HJSU199302012.htm
[11]	ZHAO M, SONG L, SUN L, et al. Associations of type 2 diabetes onset age with cardiovascular disease and mortality: the Kailuan Study[J]. Diabetes care, 2021, 44(6): 1426-1432. doi: 10.2337/dc20-2375
[12]	高尿酸血症相关疾病诊疗多学科共识专家组. 中国高尿酸血症相关疾病诊疗多学科专家共识[J]. 中华内科杂志, 2017, 56(3): 235-248. https://www.cnki.com.cn/Article/CJFDTOTAL-SYNK202306006.htm
[13]	中华医学会糖尿病学分会. 中国2型糖尿病防治指南(2017年版)[J]. 中国实用内科杂志, 2018, 38(4): 292-344. https://www.cnki.com.cn/Article/CJFDTOTAL-HBYX202112018.htm
[14]	中国高血压防治指南修订委员会. 中国高血压防治指南(2018年修订版)[J]. 中国心血管杂志, 2019, 24(1): 24-56. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGGZ201904005.htm
[15]	LEVEY A S, STEVENS L A, SCHMID C H, et al. A new equation to estimate glomerular filtration rate[J]. Ann Intern Med, 2009, 150(9): 604-612. doi: 10.7326/0003-4819-150-9-200905050-00006
[16]	PEARSON T A, MENSAH G A, ALEXANDER R W, et al. Markers of inflammation and cardiovascular disease: application to clinical and public health practice: a statement for healthcare professionals from the Centers for Disease Control and Prevention and the American Heart Association[J]. Circulation, 2003, 107(3): 499-511. doi: 10.1161/01.CIR.0000052939.59093.45
[17]	中国超重/肥胖医学营养治疗专家共识编写委员会. 中国超重/肥胖医学营养治疗专家共识(2016年版)[J]. 中华糖尿病杂志, 2016, 8(9): 525-540. https://www.cnki.com.cn/Article/CJFDTOTAL-SYNK201705019.htm
[18]	JIANG T, XIE D, WU J, et al. Association between serum copper levels and prevalence of hyperuricemia: a cross-sectional study[J]. Sci Rep, 2020, 10(1): 8687. DOI: 10.1038/s41598-020-65639-0.