环境因素对水痘发病影响的研究进展

栾桂杰; 张伟燕; 刘少楠; 陈萌; 孙靓

doi:10.16462/j.cnki.zhjbkz.2024.01.016

环境因素对水痘发病影响的研究进展

doi: 10.16462/j.cnki.zhjbkz.2024.01.016

山东省疾病预防控制中心免疫预防管理所，济南 250014

基金项目:

“齐鲁卫生与健康杰出青年人才”项目 Luwei Talent Word 〔2020〕 No.3

山东省医药卫生科技发展计划项目 202012050267

详细信息

通讯作者:
栾桂杰，E-mail: luanguijie@sina.com

中图分类号: R122
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- 文章访问数: 159
- HTML全文浏览量: 97
- PDF下载量: 32
- 被引次数: 0
出版历程
- 收稿日期: 2022-03-10
- 修回日期: 2022-06-04
- 网络出版日期: 2024-02-05
- 刊出日期: 2024-01-10

A review on the impact of environmental factors on the incidence of chickenpox

Institute for Immunization Management, Shandong Center for Disease Control and Prevention, Jinan 250014, China

Funds:

"Qilu Health Outstanding Young Talents" Project Luwei Talent Word 〔2020〕 No.3

Shandong Medical and Health Science and Technology Development Plan Project 202012050267

More Information

Corresponding author: LUAN Guijie, E-mail: luanguijie@sina.com

摘要

摘要: 目的综合分析气象因素和大气污染等环境因素对水痘发病的影响。方法在中国知网、万方、Web of Science、PubMed等数据库检索2021年12月31日前发表的环境因素与水痘发病关系的文献，对纳入研究的基本信息、方法和结果等进行整理分析。结果共纳入19项气象因素研究和3项大气污染研究。气温、相对湿度和降水的变化会造成水痘发病的增多，大气压、风速、日照等与水痘发病之间的相关性存在地区差异；PM_2.5、PM₁₀和NO₂等大气污染物会增加水痘发病的风险。结论气象因素和大气污染等环境因素暴露会影响水痘的发病，需采取针对性的防护措施。
- 环境因素 /
- 气象因素 /
- 大气污染 /
- 水痘
Abstract: Objective We aims to provide a comprehensively analysis of the impact of environmental factors, such as meteorological factors and air pollution, on the incidence of chickenpox. Methods A systematic literature search using databases including China CNKI, Wanfang, Web of Science and PubMed was conducted, foucing on relevant articles published up to December 31, 2021, that explored the association between environmental factors and chickenpox. This involved analyzing basic study information, methodologies, and outcomes. Results Nineteen studies on meteorological factors and three studies on air pollution were included in this study. It was found that changes in temperature, relative humidity and precipitation are associated with increased chickenpox indidence. Additionally, we found regional differences in the correlation between atmospheric pressure, wind speed, sunshine and chickenpox. Furthermore, air pollutants, such as PM_2.5, PM₁₀ and NO₂, were identified as risk factors for chickenpox. Conclusions There are significant correlations between both meteorological factors and air pollution with the incidence of chickenpox. It is imperative to take targeted protective measures.
- Environmental factors /
- Meteorological factors /
- Air pollution /
- Chickenpox

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图 1 文献检索流程

Figure 1. Flow diagram of articles included

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表 1 气象因素相关研究的基本特征

Table 1. Basic characteristics of included meteorological factors studies

序号 No.	参考文献 References	发表年份 Year of publication	国家/地区 Country/Region	研究方法 Method	气象因素 Meteorological factor	主要结果(相关性) Results (correlation)
1	Kokaze, 等^[6] Kokaze, et al^[6]	2001	日本 Japan	Spearman相关分析 Spearman correlation analysis	气温 Temperature	正相关 Positive correlation
2	Wu, 等^[7] Wu, et al^[7]	2007	中国台湾 Taiwan, China	广义估计方程 Generalized estimating equations	气温 Temperature	负相关 Negative correlation
3	Chan, 等^[8] Chan, et al ^[8]	2011	中国香港 Hong Kong, China	Spearman相关分析 Spearman correlation analysis	气温、相对湿度、降水 Temperature, humidity, rainfall	相对湿度、降水负相关 Negative correlation with humidity and rainfall
4	金飒, 等^[9] Jin Sa, et al^[9]	2013	中国孝感 Xiaogan, China	Spearman相关分析 Spearman correlation analysis	气温、相对湿度、降水 Temperature, humidity, rainfall	无相关性 No correlation
5	韩微笑^[10] Han Weixiao^[10]	2014	中国广州 Guangzhou, China	分布滞后非线性模型 Distributed lag nonlinear model	气温 Temperature	正相关 Positive correlation
6	Chan, 等^[11] Chan, et al ^[11]	2014	中国香港 Hong Kong, China	病例交叉研究 Case-crossover study	气温、大气压、相对湿度、风速、降水 Temperature, atmospheric pressure, humidity, wind speed, rainfall	气温、大气压正相关；相对湿度负相关 Positive correlation with temperature and atmospheric pressure; Negative correlation with humidity
7	Hervás, 等^[12] Hervás, et al^[12]	2014	西班牙马洛卡 Mallorca, Spain	Spearman相关分析 Spearman correlation analysis	气温、相对湿度、降水、水汽压、大气压、风速、日照 Temperature, humidity, rainfall, vapor pressure, atmospheric pressure, wind speed, sunshine	气温、水汽压负相关；风速、日照正相关 Negative correlation with temperature and vapor pressure; Positive correlation with wind speed and sunshine
8	魏晓娟, 等^[13] Wei Xiaojuan, et al^[13]	2014	中国临沂 Linyi, China	Spearman相关分析 Spearman correlation analysis	气温、风速、降水、日照、大气压 Temperature, wind speed, rainfall, sunshine, atmospheric pressure	气温、日照正相关；大气压负相关 Positive correlation with temperature and sunshine; Negative correlation with atmospheric pressure
9	Yang, 等^[14] Yang, et al^[14]	2015	中国上海 Shanghai, China	广义加性模型 Generalized additive model	气温 Temperature	负相关 Negative correlation
10	Harigane, 等^[15] Harigane, et al^[15]	2015	日本 Japan	Spearman相关分析 Spearman correlation analysis	气温、相对湿度、降水 Temperature, humidity, rainfall	气温、降水季节相关性 Seasonal correlation with temperature and rainfall
11	Yang, 等^[16] Yang, et al^[16]	2016	中国济南 Jinan, China	泊松回归 Poisson regression	气温、大气压、相对湿度、风速、降水、日照 Temperature, atmospheric pressure, humidity, wind speed, rainfall, sunshine	大气压、日照、降水正相关；气温、相对湿度负相关 Positive correlation with atmospheric pressure, sunshine and rainfall; Negative correlation with temperature and humidity
12	Chen, 等^[17] Chen, et al^[17]	2017	中国武汉、香港 Wuhan and Hong Kong, China	时间序列分析 Time-series analysis	气温、相对湿度和降水 Temperature, humidity, rainfall	气温、降水季节相关性 Seasonal correlation with temperature and rainfall
13	王金玉, 等^[18] Wang Jinyu, et al^[18]	2018	中国兰州 Lanzhou, China	Spearman相关分析、分布滞后非线性模型 Spearman correlation analysis, distributed lag nonlinear model	气温、大气压、风速、相对湿度、降水 Temperature, atmospheric pressure, wind speed, humidity, rainfall	气温、风速、降水、相对湿度负相关；大气压正相关 Negative correlation with temperature, wind speed, rainfall and humidity; Positive correlation with atmospheric pressure
14	Sumi^[19]	2018	丹麦、芬兰 Denmark, Finland	时间序列分析 Time-series analysis	气温 Temperature	季节相关性 Seasonal correlation
15	罗玲, 等^[20] Luo Ling, et al^[20]	2018	中国湖北 Hubei, China	Spearman相关分析 Spearman correlation analysis	气温、相对湿度、降水、日照 Temperature, humidity, rainfall, sunshine	季节相关性 Seasonal correlation
16	叶雯婧, 等^[21] Ye Wenjing, et al^[21]	2019	中国福建 Fujian, China	广义线性模型 Generalized linear model	气温、降水、风速、相对湿度、大气压 Temperature, rainfall, wind speed, humidity, atmospheric pressure	气温、相对湿度、风速负相关；降水、大气压正相关 Negative correlation with temperature, humidity and wind speed; Positive correlation with rainfall and atmospheric pressure
17	Lu, 等^[22] Lu, et al ^[22]	2020	中国广州 Guangzhou, China	分布滞后非线性模型 Distributed lag nonlinear model	气温、降水、大气压、风速、相对湿度、日照 Temperature, rainfall, atmospheric pressure, wind speed, humidity, sunshine	降水、大气压、日照正相关；风速负相关 Positive correlation with rainfall, atmospheric pressure and sunshine; Negative correlation with wind speed
18	俞佳珂, 等^[23] Yu Jiake, et al^[23]	2021	中国温州 Wenzhou, China	线性回归、多元回归 Linear regression, multiple regression	气温、相对湿度、降水、风速 Temperature, humidity, rainfall, wind speed	降水、风速负相关 Negative correlation with rainfall and wind speed
19	邱海岩, 等^[24] Qiu Haiyan, et al^[24]	2021	中国张家港 Zhangjiagang, China	Spearman相关分析、多元回归 Spearman correlation analysi, multiple regression	气温、大气压、相对湿度、降水、风速、日照 Temperature, atmospheric pressure, humidity, rainfall, wind speed, sunshine	季节相关性 Seasonal correlation

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表 2 大气污染相关研究的基本特征

Table 2. Basic characteristics of included air pollution studies

序号 No.	参考文献 References	发表年份 Year of publication	国家/地区 Country/Region	研究方法 Method	空气污染因素 Air pollution factor	主要结果(相关性) Result (correlation)
1	李平, 等^[25] Li Ping, et al^[25]	2019	中国天津 Tianjin, China	Spearman相关分析 Spearman correlation analysi	PM_2.5、PM₁₀、SO₂、NO₂、CO	PM_2.5、PM₁₀、NO₂正相关 Positive correlation with PM_2.5、PM₁₀、NO₂
2	Yu, 等^[26] Yu, et al ^[26]	2020	中国上海 Shanghai, China	分布滞后非线性模型 Distributed lag nonlinear model	PM₁₀、NO₂、O₃、SO₂、CO	PM₁₀正相关 Positive correlation with PM₁₀
3	Wang, 等^[27] Wang, et al ^[27]	2021	中国青岛 Qingdao, China	分布滞后非线性模型 Distributed lag nonlinear model	PM₁₀、PM_2.5、NO₂、SO₂、O₃	PM_2.5正相关、高浓度NO₂负相关、低浓度NO₂正相关 Positive correlation with PM_2.5, negative correlation with high concentration NO₂, positive correlation with low concentration NO₂

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参考文献(36)

[1]	李意兰, 陈纯, 刘艳慧, 等. 广州市2014-2018年学校传染病突发公共卫生事件分析[J]. 中国热带医学, 2020, 20(1): 35-38. DOI: 10.13604/j.cnki.46-1064/r.2020.01.08. Li YL, Chen C, Liu YH, et al. Public health emergencies of infectious events in schools in Guangzhou, 2014-2018[J]. China Trop Med, 2020, 20(1): 35-38. DOI: 10.13604/j.cnki.46-1064/r.2020.01.08.
[2]	鲍武波, 党露希, 祝明清, 等. 2011-2018年武汉市某区水痘流行特征分析[J]. 公共卫生与预防医学, 2019, 30(6): 67-70. DOI: 10.3969/j.issn.1006-2483.2019.06.017. Bao WB, Dang LX, Zhu MQ, et al. Epidemiological characteristics of varicella in a district of Wuhan, 2011-2018[J]. J Public Health Prev Med, 2019, 30(6): 67-70. DOI: 10.3969/j.issn.1006-2483.2019.06.017.
[3]	董蒲梅, 王淼, 刘燕敏. 2016-2019年中国水痘流行病学特征[J]. 中国疫苗和免疫, 2020, 26(4): 403-406. DOI: 10.19914/j.cjvi.2020.04.011. Dong PM, Wang M, Liu YM. Epidemiological characteristics of varicella in China from 2016 to 2019[J]. Chin J Vaccines and Immun, 2020, 26(4): 403-406. DOI: 10.19914/j.cjvi.2020.04.011.
[4]	随海田, 李锦成, 王淼, 等. 2005-2015年中国水痘流行病学特征[J]. 中国疫苗和免疫, 2019, 25(2): 155-159. DOI: 10.19914/j.cjvi.2019.02.009. Sui HT, Li JC, Wang M, et al. Varicella epidemiology in China, 2005-2015[J]. Chin J Vaccines and Immun, 2019, 25(2): 155-159. DOI: 10.19914/j.cjvi.2019.02.009.
[5]	武晶晶, 张先慧, 刘晓雪, 等. 2008-2017年济南市水痘流行病学特征分析[J]. 现代预防医学, 2018, 45(19): 3488-3491, 3495. Wu JJ, Zhang XH, Liu XX, et al. Epidemiological characteristics of Varicella in Jinan, 2008-2017[J]. Modern Preventive Medicine, 2018, 45(19): 3488-3491, 3495.
[6]	Kokaze A, Yoshida M, Sekine Y, et al. The magnitude of variation in temperature within a year has an effect on the seasonal variations of chickenpox incidence in Japan[J]. Epidemiol Infect, 2001, 126(2): 269-277. DOI: 10.1017/s0950268801005246.
[7]	Wu PY, Li YC, Wu HD. Risk factors for chickenpox incidence in Taiwan from a large-scale computerized database[J]. Int J Dermatol, 2007, 46(4): 362-366. DOI: 10.1111/j.1365-4632.2006.03050.x.
[8]	Chan JY, Tian L, Tian L, et al. Hospitalizations for varicella in children and adolescents in a referral hospital in Hong Kong, 2004 to 2008: a time series study[J]. BMC Public Health, 2011, 11: 366. DOI: 10.1186/1471-2458-11-366.
[9]	金飒, 孙国运, 邱明, 等. 湖北省孝感市2009-2012年水痘发病与环境因素的相关性分析[J]. 皮肤性病诊疗学杂志, 2013, 20(4): 288-290. DOI: 10.3969/j.issn.1674-8468.2013.04.023. Jin S, Sun GY, Qiu M, et al. The epidemiology of varicella and its correlation with environmental factors in Xiaogan City during 2009-2012[J]. J Diagn Ther J Dermatol-Venereol, 2013, 20(4): 288-290. DOI: 10.3969/j.issn.1674-8468.2013.04.023.
[10]	韩微笑. 2009~2013年广州市气温对常见传染病的短期影响: 基于分布滞后非线性模型的研究[D]. 济南: 山东大学, 2017. Han WX. Short-term Impacts of Temperature on Major Infectious Disease in Guangzhou City, 2009-2013-a study based on distributed lag nonlinear models[D]. Jinan: Shandong University, 2017.
[11]	Chan JY, Lin HL, Tian LW. Meteorological factors and El Nino Southern Oscillation are associated with paediatric varicella infections in Hong Kong, 2004-2010[J]. Epidemiol Infect, 2014, 142(7): 1384-1392. DOI: 10.1017/S0950268813002306.
[12]	Hervás D, Hervás-Masip J, Nicolau A, et al. Solar radiation and water vapor pressure to forecast chickenpox epidemics[J]. Eur J Clin Microbiol Infect Dis, 2015, 34(3): 439-446. DOI: 10.1007/s10096-014-2243-3.
[13]	魏晓娟, 张晓丽. 临沂市重点传染病与气候的相关性研究及预测模型分析[J]. 社区医学杂志, 2014, 12(16): 24-27. Wei XJ, Zhang XL. Correlation study and prediction model analysis of key infectious diseases and climate in Linyi City[J]. J Communtity Med, 2014, 12(16): 24-27.
[14]	Yang YY, Chen RJ, Xu JH, et al. The effects of ambient temperature on outpatient visits for varicella and Herpes zoster in Shanghai, China: a time-series study[J]. J Am Acad Dermatol, 2015, 73(4): 660-665. DOI: 10.1016/j.jaad.2015.07.015.
[15]	Harigane K, Sumi A, Mise K, et al. The role of temperature in reported chickenpox cases from 2000 to 2011 in Japan[J]. Epidemiol Infect, 2015, 143(12): 2666-2678. DOI: 10.1017/S095026881400363X.
[16]	Yang YQ, Geng XY, Liu XX, et al. Association between the incidence of varicella and meteorological conditions in Jinan, Eastern China, 2012-2014[J]. BMC Infect Dis, 2016, 16: 179. DOI: 10.1186/s12879-016-1507-1.
[17]	Chen BN, Sumi A, Wang L, et al. Role of meteorological conditions in reported chickenpox cases in Wuhan and Hong Kong, China[J]. BMC Infect Dis, 2017, 17(1): 538. DOI: 10.1186/s12879-017-2640-1.
[18]	王金玉, 李盛, 马汉平, 等. 2008-2016年兰州市日均气温与水痘发病的关联陛研究[J]. 中华预防医学杂志, 2018, 52(8): 842-848. DOI: 10.3760/cma.j.issn.0253-9624.2018.08.013. Wang JY, Li S, Ma HP, et al. Research on the relationship between the daily mean temperature and the daily cases of varicella during 2008-2016 in Lanzhou, China[J]. Chin J Prev Med, 2018, 52(8): 842-848. DOI: 10.3760/cma.j.issn.0253-9624.2018.08.013.
[19]	Sumi A. Role of temperature in reported chickenpox cases in northern European countries: Denmark and Finland[J]. BMC Res Notes, 2018, 11(1): 377. DOI: 10.1186/s13104-018-3497-0.
[20]	罗玲, 黎明. 湖北省水痘发病情况与气象因素的关系研究[J]. 中国全科医学, 2018, 21(9): 1114-1117. DOI: 10.3969/j.issn.1007-9572.2018.00.062. Luo L, Li M. Association between incidence of chickenpox and meteorological factors in Hubei Province, China[J]. Chin Gen Prac, 2018, 21(9): 1114-1117. DOI: 10.3969/j.issn.1007-9572.2018.00.062.
[21]	叶雯婧, 陈彩粼, 杨林, 等. 福建省2006-2015年度呼吸道传染病与气候因素关联分析[J]. 医学理论与实践, 2019, 32(7): 959-962. DOI: 10.19381/j.issn.1001-7585.2019.07.009. Ye WJ, Chen CL, Yang L, et al. Analysis of the association between intestinal infectious diseases and climate factors of Fujian Province in 2006-2015[J]. J Med Theory Pract, 2019, 32(7): 959-962. DOI: 10.19381/j.issn.1001-7585.2019.07.009.
[22]	Lu JY, Zhang ZB, He Q, et al. Association between climatic factors and varicella incidence in Guangzhou, Southern China, 2006-2018[J]. Sci Total Environ, 2020, 728: 138777. DOI: 10.1016/j.scitotenv.2020.138777.
[23]	俞佳珂, 陈小春, 钟佩佩, 等. 温州市儿童水痘流行特征与气象因素的相关性研究[J]. 国际流行病学传染病学杂志, 2021, 48(1): 38-42. DOI: 10.3760/cma.j.cn331340-20200630-00213. Yu JK, Chen XC, Zhong PP, et al. Relationship between epidemiological characteristics of pediatric varicella and meteorology in Wenzhou[J]. Inter J Epidemiol Infect Dis, 2021, 48(1): 38-42. DOI: 10.3760/cma.j.cn331340-20200630-00213.
[24]	邱海岩, 沈艳, 邵海枫, 等. 张家港市水痘发病与季节气象因素相关性分析[J]. 医学动物防制, 2021, 37(5): 442-445. DOI: 10.7629/yxdwfz202105009. Qiu HY, Shen Y, Shao HF, et al. Correlation analysis on seasonal and meteorological factors and chickenpox incidence grouped by seasons in Zhangjiagang[J]. J Med Pest Control, 2021, 37(5): 442-445. DOI: 10.7629/yxdwfz202105009.
[25]	李平, 孙梅青, 李彭辉, 等. 天津市武清区环境空气PM_2.5与急性呼吸道感染性疾病的关联研究[J]. 实用预防医学, 2019, 26(7): 775-780. DOI: 10.3969/j.issn.1006-3110.2019.07.003. Li P, Sun MQ, Li PH, et al. Association between ambient air PM2.5 and acute respiratory tract infectious disease in Wuqing District, Tianjin[J]. Pract Prev Med, 2019, 26(7): 775-780. DOI: 10.3969/j.issn.1006-3110.2019.07.003.
[26]	Yu HJ, Wang YJ, Peng Q, et al. Influence of coarse particulate matter on chickenpox in Jiading District, Shanghai, 2009-2018: a distributed lag non-linear time series analysis[J]. Environ Res, 2020, 190: 110039. DOI: 10.1016/j.envres.2020.110039.
[27]	Wang Z, Li X, Hu P, et al. Influence of air pollutants on varicella among adults[J]. Sci Rep, 2021, 11(1): 21020. DOI: 10.1038/s41598-021-00507-z.
[28]	Hao JY, Yang ZY, Huang SQ, et al. Association between short-term exposure to ambient air pollution and the incidence of mumps in Wuhan, China: a time-series study[J]. Environ Res, 2019, 177: 108660. DOI: 10.1016/j.envres.2019.108660.
[29]	Zhang M, Zhu Y. Association between particulate matter pollution and the incidence of mumps in 31 provinces from China[J]. Environ Sci Pollut Res Int, 2021, 28(37): 51210-51216. DOI: 10.1007/s11356-021-14287-6.
[30]	Gu SN, Li DC, Lu BB, et al. Associations between ambient air pollution and daily incidence of pediatric hand, foot and mouth disease in Ningbo, 2014-2016: a distributed lag nonlinear model[J]. Epidemiol Infect, 2020, 148: e46. DOI: 10.1017/S0950268820000321.
[31]	Ji XY, Huang LY, Song J, et al. Short-term effects of meteorological factors, air pollution, and sunspot on childhood hand, foot, and mouth disease in Tianjin, China: a new time series regression, 2014-2018[J]. Environ Sci Pollut Res Int, 2020, 27(29): 37022-37035. DOI: 10.1007/s11356-020-09794-x.
[32]	Copat C, Cristaldi A, Fiore M, et al. The role of air pollution (PM and NO₂) in COVID-19 spread and lethality: a systematic review[J]. Environ Res, 2020, 191: 110129. DOI: 10.1016/j.envres.2020.110129.
[33]	Jones RM, Brosseau LM. Aerosol transmission of infectious disease[J]. J Occup Environ Med, 2015, 57(5): 501-508. DOI: 10.1097/jom.0000000000000448.
[34]	Jayaweera M, Perera H, Gunawardana B, et al. Transmission of COVID-19 virus by droplets and aerosols: a critical review on the unresolved dichotomy[J]. Environ Res, 2020, 188: 109819. DOI: 10.1016/j.envres.2020.109819.
[35]	Huang CH, Lin HC, Tsai CD, et al. The interaction effects of meteorological factors and air pollution on the development of acute coronary syndrome[J]. Sci Rep, 2017, 7: 44004. DOI: 10.1038/srep44004.
[36]	Niu ZC, Qi YJ, Zhao PQ, et al. Short-term effects of ambient air pollution and meteorological factors on tuberculosis in semi-arid area, northwest China: a case study in Lanzhou[J]. Environ Sci Pollut Res Int, 2021, 28(48): 69190-69199. DOI: 10.1007/s11356-021-15445-6.