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中国人群中血脂成分与血尿酸间的剂量-反应关系

高倩 李婷 彭刘庆 王彤

高倩, 李婷, 彭刘庆, 王彤. 中国人群中血脂成分与血尿酸间的剂量-反应关系[J]. 中华疾病控制杂志, 2023, 27(10): 1140-1145. doi: 10.16462/j.cnki.zhjbkz.2023.10.005
引用本文: 高倩, 李婷, 彭刘庆, 王彤. 中国人群中血脂成分与血尿酸间的剂量-反应关系[J]. 中华疾病控制杂志, 2023, 27(10): 1140-1145. doi: 10.16462/j.cnki.zhjbkz.2023.10.005
GAO Qian, LI Ting, PENG Liuqing, WANG Tong. Dose-response association between lipid profiles and serum urate acid in Chinese adults[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2023, 27(10): 1140-1145. doi: 10.16462/j.cnki.zhjbkz.2023.10.005
Citation: GAO Qian, LI Ting, PENG Liuqing, WANG Tong. Dose-response association between lipid profiles and serum urate acid in Chinese adults[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2023, 27(10): 1140-1145. doi: 10.16462/j.cnki.zhjbkz.2023.10.005

中国人群中血脂成分与血尿酸间的剂量-反应关系

doi: 10.16462/j.cnki.zhjbkz.2023.10.005
基金项目: 

国家自然科学基金 82204163

国家自然科学基金 82073674

山西省基础研究计划资助项目 202203021212382

详细信息
    通讯作者:

    王彤,E-mail: tongwang@sxmu.edu.cn

  • 中图分类号: R181.3;R589

Dose-response association between lipid profiles and serum urate acid in Chinese adults

Funds: 

National Natural Science Foundation of China 82204163

National Natural Science Foundation of China 82073674

Fundamental Research Program of Shanxi Province 202203021212382

More Information
  • 摘要:   目的  探讨中国成人血脂成分与血尿酸(serum uric acid, SUA)间的剂量-反应关系,为高尿酸血症(hyperuricemia, HUA)的防治提供理论依据。  方法  基于中国健康与营养调查(China Health and Nutrition Survey, CHNS) 2009年和中国健康与养老追踪调查(China Health and Retirement Longitudinal Study, CHARLS) 2011-2012年的调查数据,分别纳入符合研究纳入排除标准的研究对象8 509名和6 749名。采用广义倾向性评分逆概率加权方法,均衡年龄、性别等潜在混杂因素后,估计血脂成分总胆固醇(cholesterol, TC)、低密度脂蛋白(low-density lipoprotein, LDL)、高密度脂蛋白(high-density lipoprotein, HDL)和三酰甘油(triglycerides, TG)与SUA间的剂量-反应关系。  结果  CHNS和CHARLS研究对象的平均年龄分别为(50.32±15.08)岁和(58.52±9.17)岁,SUA升高者分别占15.30%和5.34%。在均衡可能的混杂因素后,逆概率加权法分析结果显示,TG和HDL与SUA间存在统计学剂量-反应关系,SUA水平随TG水平的升高和HDL水平的降低而升高。  结论  血脂异常可能导致SUA升高,及时调节血脂水平可能有助于HUA的防治。
  • 图  1  CHNS和CHARLS数据集研究对象筛选流程图

    CHNS, 中国健康与营养调查; CHARLS, 中国健康与养老追踪调查。

    Figure  1.  Flow chart of subject screening for CHNS and CHARLS datasets

    CHNS, China Health and Nutrition Survey; CHARLS, China Health and Retirement Longitudinal Study.

    图  2  加权前后样本中协变量均衡性表现

    CHNS, 中国健康与营养调查; CHARLS, 中国健康与养老追踪调查; SUA, 血尿酸; TC, 总胆固醇; TG, 三酰甘油; LDL, 低密度脂蛋白; HDL, 高密度脂蛋白。
    图中星号表示离群点。

    Figure  2.  Performance of covariate balance in a sample before and after weighting

    CHNS, China Health and Nutrition Survey; CHARLS, China Health and Retirement Longitudinal Study; TC, cholesterol; TG, triglycerides; LDL, low-density lipoprotein; HDL, high-density lipoprotein.
    The asterisks in the figure indicate outliers.

    表  1  研究对象基线特征

    Table  1.   Baseline characteristics of the study subjects

    变量
    Variables
    变量赋值
    Value assignment
    CHNS CHARLS
    SUA正常
    Normal SUA levels
    (n=7 209)
    SUA升高
    High SUA levels
    (n=1 300)
    P
    value
    SUA正常
    Normal SUA levels
    (n=6 403)
    SUA升高
    High SUA levels
    (n=346)
    P
    value
    年龄组/岁Age group/years 49.82±15.02 53.06±15.14 < 0.001 58.36±9.12 61.38±9.71 < 0.001
        18~<45 2 684(37.2) 384(29.5) < 0.001 173(2.7) 7(2.0) < 0.001
        45~<60 2 600(36.1) 471(36.2) 3 670(57.3) 155(44.8)
        ≥60 1 925(26.7) 445(34.3) 2 560(40.0) 184(53.2)
    性别Gender < 0.001 < 0.001
        男Male 1 3 149(43.7) 797(61.3) 3 021(47.2) 208(60.1)
        女Female 2 4 060(56.3) 503(38.7) 3 382(52.8) 138(39.9)
    婚姻状况Marital status 0.321 0.157
        离婚/丧偶/分居/未婚Divorced/Widowed/Separated/Never married 0 1 127(15.6) 218(16.8) 3 610(56.4) 209(60.4)
        已婚/同居Married/Live with partners 1 6 082(84.4) 1 082(83.2) 2 793(43.6) 137(39.6)
    受教育程度Education 0.141 0.609
        小学及以下Primary school or lower 0 3 145(43.6) 538(41.4) 4 387(68.5) 232(67.1)
        初中及以上Middle school or higher 1 4 064(56.4) 762(58.6) 2 016(31.5) 114(32.9)
    吸烟Smoking < 0.001 0.742
        从不吸烟Never 0 5 101(70.8) 808(62.2) 4 596(71.8) 253(73.1)
        已戒烟Quit 1 224(3.1) 55(4.2) 455(7.1) 21(6.1)
        现在仍吸Currently 2 1 884(26.1) 437(33.6) 1 352(21.1) 72(20.8)
    饮酒Drinking < 0.001 0.013
        从不饮酒Never 0 5 026(69.7) 742(57.1) 5 207(81.3) 273(78.9)
        每月少于1次Less than once a month 1 312(4.3) 57(4.4) 650(10.2) 51(14.7)
        每月多于1次More than once a month 2 1 871(26.0) 501(38.5) 546(8.5) 22(6.4)
    TG/(mmol·L-1) 1.43±1.00 3.01±2.55 < 0.001 1.43±1.03 2.12±1.71 < 0.001
    HDL/(mmol·L-1) 1.47±0.47 1.28±0.59 < 0.001 1.33±0.40 1.20±0.42 < 0.001
    LDL/(mmol·L-1) 2.98±0.94 2.99±1.21 0.659 3.01±0.89 3.03±1.10 0.661
    TC/(mmol·L-1) 4.79±0.97 5.27±1.11 < 0.001 5.00±0.98 5.30±1.17 < 0.001
    BMI/(kg·m-2) 23.67±4.01 23.74±3.62 0.751
         < 18.5 448(7.0) 12(3.5) 0.065
        18.5~ < 24.0 3 177(49.6) 186(53.8)
        24.0~ < 28.0 1 959(30.6) 106(30.6)
        ≥28.0 819(12.8) 42(12.1)
    注:CHNS, 中国健康与营养调查; CHARLS, 中国健康与养老追踪调查; SUA, 血尿酸; TC, 总胆固醇; LDL, 低密度脂蛋白; HDL, 高密度脂蛋白; TG, 三酰甘油。
    ①以[人数(占比/%)]或(x±s)表示。
    Notes: CHNS, China Health and Nutrition Survey; CHARLS, China Health and Retirement Longitudinal Study; SUA, serum urate acid; TC, cholesterol; LDL, low-density lipoprotein; HDL, high-density lipoprotein; TG, triglycerides.
    ① [Number of people (proportion/%)]or (x±s).
    下载: 导出CSV

    表  2  SUA与血脂成分间剂量-反应关系分析结果

    Table  2.   Analysis results of dose-response relationship between SUA and blood lipid components

    数据集Datasets 单变量模型Univariate models β sx t值value P值value
    CHNS TC 35.84 18.57 1.93 0.054
    TG 33.67 5.49 6.13 < 0.001
    HDL -30.58 7.10 -4.31 < 0.001
    LDL -0.706 1.85 -0.38 0.702
    CHARLS TC 10.06 0.97 10.41 < 0.001
    TG 13.31 1.17 11.42 < 0.001
    HDL -16.34 2.46 -6.65 < 0.001
    LDL 4.68 1.10 4.24 < 0.001
    注:CHNS, 中国健康与营养调查; CHARLS, 中国健康与养老追踪调查; SUA, 血尿酸; TC, 总胆固醇; TG, 三酰甘油; LDL, 低密度脂蛋白; HDL, 高密度脂蛋白。
    上述单变量模型指各血脂成分与SUA间的加权单变量线性回归模型,权重由非参数的协变量均衡广义倾向性评分方法估计
    Notes: CHNS, China Health and Nutrition Survey; CHARLS, China Health and Retirement Longitudinal Study; TC, cholesterol; TG, triglycerides; LDL, low-density lipoprotein; HDL, high-density lipoprotein.
    The above univariate model refers to the weighted univariate linear regression model between each lipid component and SUA, the weight of which is estimated by the non-parametric covariate balancing generalized propensity score method.
    下载: 导出CSV
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  • 收稿日期:  2023-03-08
  • 修回日期:  2023-08-26
  • 网络出版日期:  2023-10-23
  • 刊出日期:  2023-10-10

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