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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- 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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