摘要
目的采用meta分析的方法,评价基于相关系数的气象因素与细菌性痢疾发病的相关关系。方法以计算机检索PubMed、Web of Science、CNKI、万方和CBM数据库,查找2017年8月前发表的关于细菌性痢疾与气象因素相关性的文献。按照事先规定的纳入及排除标准筛选文献、提取信息,进行meta分析。结果共检出相关文献145篇,最终纳入21篇文献。meta分析结果显示,细菌性痢疾发病与气象因素有一定关系。在纳入分析的9个气象因素中,细菌性痢疾发病与平均水汽压呈强正相关(r=0.905),与平均气温、平均最高气温、平均最低气温、平均相对湿度和降雨量均呈中等程度正相关(r值分别为0.652,0.601,0.631,0.403,0.451),与日照时间呈弱正相关(r=0.181),且均有统计学意义(P<0.05);细菌性痢疾发病与平均气压呈中等程度负相关(r=-0.449),而与平均风速无明显相关性(P>0.05)。结论气象因素在一定程度上可影响细菌性痢疾发病。
Objective To evaluate the correlation between meteorological factors and the incidence of bacillary dysentery based on correlation coefficients. Methods The eligible research papers which studied the correlation between meteorological factors and the incidence of bacillary dysentery from database and the retrieval platform,including PubMed,Web of Science,CNKI, Wanfang and CBM,were collected before August 2017,meta-analysis was conducted,and the correlation coefficients of meteorological factors and dysentery were calculated. Results A total of 21 studies were included in the present study, involving nine meteorological factors. The average water vapor pressure revealed strong correlation with dysentery(r=0.905, P<0.05),the average temperature,average maximum temperature,average minimum temperature,average relative humidity and rainfall were moderately correlated with it (r:0.652,0.601,0.631,0.403,0.451 ;P <0.05),sunshine duration was weakly correlated with it (r=0.181 ,P<0.05). The mean air pressure was negatively correlated with dysentery in a moderate degree (r=-0.449,P<0.05),while the mean wind speed was not correlated with it(P>0.05). Conclusion Meteorological factors may have some effects on the incidence of bacillary dysentery to some extent.
作者
刘言玉
吴含
劳家辉
姜宝法
LIU Yan-yu;WU Han;LAO Jia-hui;JIANG Bao-fa(Department of Ep idemiology ,School of Public .Health,Shandong University,Ji 'nan,Shandong250012,China)
出处
《环境与健康杂志》
CAS
北大核心
2018年第6期487-491,共5页
Journal of Environment and Health
基金
国家科技基础资源调查专项(2017FY101202)
关键词
细菌性痢疾
气象因素
META分析
相关系数
Bacillary dysentery
Meteorological factors
Meta analysis
Correlation coefficients