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基于健康大数据带状疱疹与抑郁症的关系——现实世界的研究实例

丁雄,  蒋蔚,  蒋静,  胡跃华,  武英,  李云,  赵丹丹,  殷大鹏

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文章导航 > 中华疾病控制杂志  > 2021 >  25(6): 730-733
丁雄, 蒋蔚, 蒋静, 胡跃华, 武英, 李云, 赵丹丹, 殷大鹏. 基于健康大数据带状疱疹与抑郁症的关系——现实世界的研究实例[J]. 中华疾病控制杂志, 2021, 25(6): 730-733. doi: 10.16462/j.cnki.zhjbkz.2021.06.019
引用本文: 丁雄, 蒋蔚, 蒋静, 胡跃华, 武英, 李云, 赵丹丹, 殷大鹏. 基于健康大数据带状疱疹与抑郁症的关系——现实世界的研究实例[J]. 中华疾病控制杂志, 2021, 25(6): 730-733. doi: 10.16462/j.cnki.zhjbkz.2021.06.019
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DING Xiong, JIANG Wei, JIANG Jing, HU Yue-hua, WU Ying, LI Yun, ZHAO Dan-dan, YIN Da-peng. The study on the relationship between herpes zoster and depression based on Health Big Data—Real world research examples[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2021, 25(6): 730-733. doi: 10.16462/j.cnki.zhjbkz.2021.06.019
Citation: DING Xiong, JIANG Wei, JIANG Jing, HU Yue-hua, WU Ying, LI Yun, ZHAO Dan-dan, YIN Da-peng. The study on the relationship between herpes zoster and depression based on Health Big Data—Real world research examples[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2021, 25(6): 730-733. doi: 10.16462/j.cnki.zhjbkz.2021.06.019
shu

基于健康大数据带状疱疹与抑郁症的关系——现实世界的研究实例

doi: 10.16462/j.cnki.zhjbkz.2021.06.019
  • 1.

    063210 唐山，华北理工大学公共卫生学院

  • 2.

    443003 宜昌，宜昌市疾病预防控制中心

  • 3.

    102206 北京，中国疾病预防控制中心流行病学办公室

丁雄和蒋蔚为共同第一作者
基金项目: 

2020年北京市自然科学基金 L202008

北航-首医大数据精准医疗高精尖创新中心计划 BHME-201801

中国疾病预防控制中心科研项目 59911917

详细信息
    通讯作者:

    武英，E-mail：wyzhdd@sina.com

    胡跃华，E-mail：huyueer@163.com

  • 中图分类号: R752.1; R749.4

The study on the relationship between herpes zoster and depression based on Health Big Data—Real world research examples

  • 1.

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

  • 2.

    Yichang Center for Disease Control and Prevention, Yichang 443003, China

  • 3.

    Office of Epidemiology, Chinese Center for Disease Control and Prevention, Beijing 102206, China

DING Xiong and JIANG Wei contributed equally to this article
Funds: 

2020 Beijing Natural Science Foundation L202008

Beihang University & Capital Medical University Advanced Innovation Center for Big Data-Based Precision Medicine Plan BHME-201801

Scientific Research Project of Chinese Center for Disease Control and Prevention 59911917

More Information

    摘要
  • 摘要:   目的  探讨宜昌市抑郁症与患带状疱疹风险的关系。  方法  根据中国宜昌市健康大数据，选取在2018年9月30日-2019年9月30日期间经临床医生诊断为带状疱疹的患者作为病例组，按年龄(组距为10岁)和性别进行1∶4匹配其他就诊者作为对照组。按就诊日期先确定抑郁症暴露，采用条件Logistic回归分析模型分析抑郁症与患带状疱疹风险的关系。  结果  共纳入5 370例病例，匹配21 480例对照，年龄为56(43, 67)岁，病例组男性2 533例，占47.17%，对照组中男性10 132例，占47.17%。调整潜在混杂因素后，病例组抑郁症患者发生带状疱疹的风险是非抑郁症患者的1.697倍(OR=1.697, 95% CI: 1.089~2.643, P=0.019)；在女性、就诊年龄 < 50岁和≥70岁人群中抑郁症与患带状疱疹有关联，OR值分别为1.983(95% CI: 1.124~3.498, P=0.018)、2.213(95% CI: 1.059~4.629, P=0.035)和2.738(95% CI: 1.264~5.929, P=0.011)。  结论  抑郁症会增加罹患带状疱疹的风险，尤其是女性以及年龄在50岁以下和70岁及以上人群中。
    Abstract:   Objective  The aim of our study was to explore the relationship between depression and the risk of herpes zoster in Yichang City.  Methods  With use of the Health Big Data of Yichang City, China, patients who were diagnosed with herpes zoster by clinicians between September 1, 2018 to September 30, 2019 were included. For each patient with herpes zoster, 4 matched controls were identified, matched for age (class interval: 10 years old) and sex. Controls took the index date of their matched case, and conditional Logistic regression analysis model was used to evaluate the relationship between depression and the risk of herpes zoster.  Results  In age was 56 (43, 67) years old, a total of 5 370 cases were included and 21 480 controls were matched. There were 2 533 males (47.17%) in the case group and 10 132 males (47.17%) in the control group. After adjusting for potential confounding factors, patients with depression had the 1.697 times risk of shingles as those without depression, the OR (odds ratio, OR) for case group was 1.697, (95% CI: 1.089-2.643, P=0.019), compared with matched controls. This relationship also observed in female (OR=1.983, 95% CI: 1.124-3.498, P=0.018), age under 50 years old (OR=2.213, 95% CI: 1.059-4.629, P=0.035) and older than 70 years old (OR=2.738, 95% CI: 1.264-5.929, P=0.011).  Conclusion  The recent study suggested that depression may be a risk factor for herpes zoster, especially in females, individuals under 50 years old and older than 70 years old.
    • HTML全文

  • 表  1  HZ组与对照组的一般基本特征[n(%)]

    Table  1.   General basic characteristics of HZ group and control group [n(%)]

    因素 HZ组
    (n=5 370)    		 对照组
    (n=21 480)    		 χ2值 P值
    抑郁症
      是 66(0.31) 28(0.52) 5.647 0.018
      否 21 414(99.69) 5 342(99.48)
    匹配因素
      性别
        男 2 533(47.17) 10 132(47.17)
        女 2 837(52.83) 11 348(52.83)
      就诊年龄
        18~＜35 806(15.01) 3 224(15.01)
        35~＜45 621(11.56) 2 484(11.56)
        45~＜55 1 050(19.55) 4 200(19.55)
        55~＜65 1 259(23.45) 5 036(23.45)
        65~＜75 1 032(19.22) 4 128(19.22)
        ≥75 602(11.21) 2 408(11.21)
    其他因素
      脑血管疾病 264(4.92) 931(4.33) 3.421 0.064
      腰椎间盘脱出 212(3.95) 739(3.44) 3.238 0.072
    下载: 导出CSV

    表  2  抑郁症与HZ的条件Logistic回归分析模型分析结果

    Table  2.   Results of conditional Logistic regression model analysis of depression and HZ

    模型 β值 sx值 χ2值 OR (95% CI)值 P值
    全人群
      模型一 0.532 0.226 5.547 1.703(1.093~2.652) 0.019
      模型二 0.532 0.226 5.538 1.702(1.093~2.651) 0.019
      模型三 0.529 0.226 5.469 1.697(1.089~2.643) 0.019
    男性
      模型一 0.289 0.366 0.623 1.335(0.652~2.734) 0.430
      模型二 0.288 0.366 0.618 1.333(0.651~2.731) 0.432
      模型三 0.293 0.366 0.640 1.340(0.654~2.745) 0.424
    女性
      模型一 0.696 0.289 5.787 2.006(1.138~3.538) 0.016
      模型二 0.697 0.289 5.797 2.007(1.138~3.540) 0.016
      模型三 0.684 0.290 5.584 1.983(1.124~3.498) 0.018
        注：模型一：未调整变量；模型二：调整年龄、性别；模型三：调整年龄、性别、脑血管疾病、腰间盘脱出。
    下载: 导出CSV

    表  3  按年龄分层的抑郁症与HZ的条件Logistic回归分析模型分析结果

    Table  3.   Results of conditional Logistic regression model analysis of depression and HZ by age stratification

    模型 β值 sx值 χ2值 OR (95% CI)值 P值
    < 50岁
      模型一 0.792 0.376 4.426 2.207(1.056~4.613) 0.035
      模型二 0.793 0.376 4.444 2.211(1.057~4.623) 0.035
      模型三 0.795 0.376 4.457 2.213(1.059~4.629) 0.035
    50~＜60岁
      模型一 -0.695 0.751 0.856 0.499(0.115~2.174) 0.355
      模型二 -0.691 0.751 0.847 0.501(0.115~2.183) 0.358
      模型三 -0.689 0.751 0.843 0.502(0.115~2.186) 0.358
    60~＜70岁
      模型一 0.134 0.568 0.056 1.143(0.376~3.479) 0.814
      模型二 0.134 0.568 0.055 1.143(0.376~3.479) 0.814
      模型三 0.115 0.568 0.041 1.122(0.368~3.418) 0.839
    ≥70岁
      模型一 1.018 0.393 6.706 2.768(1.281~5.982) 0.010
      模型二 1.025 0.393 6.786 2.787(1.289~6.025) 0.009
      模型三 1.007 0.394 6.528 2.738(1.264~5.929) 0.011
        注：模型一：未调整变量；模型二：调整年龄、性别; 模型三：调整年龄、性别、脑血管疾病、腰间盘脱出。
    下载: 导出CSV
    • 参考文献(13)
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  • 收稿日期:  2020-08-04
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