摘要
目的探讨PM2.5浓度与急性呼吸道感染性疾病的关联。方法收集2015-2017年环境空气主要污染物浓度指标、气象指标、11种急性呼吸道感染性疾病的发病或就诊资料,应用Spearman相关分析和因子分析等统计学方法分析每种疾病发病情况与PM2.5浓度的关联。结果 2015-2017年武清区月均PM2.5浓度范围为41.00~137.00 μg/m^3,中位数为62.00 μg/m^3,每年4-9月份53.00(46.50,63.00)μg/m^3较低,10月-翌年3月份74.50(61.00,94.25)μg/m^3较高,差异有统计学意义(U=43.000,P<0.001)。三年间的月均PM2.5浓度差异无统计学意义(H=1.435,P=0.488)。研究病种每年4-9月份和10月-翌年3月份两时间段发病数据差异有统计学意义的是肺炎(t=2.850,P=0.007)、上感(U=30.000,P<0.001)和急性咽部炎症(U=79.000,P=0.009)和急性气管炎(t=3.529,P=0.001),三年间百日咳(H=6.751,P=0.034)、肺炎(F=16.671,P<0.001)和急性下呼吸道感染(H=16.727,P<0.001)的发病数据差异有统计学意义。研究病种中与PM2.5浓度单因素分析相关系数具有统计学意义(P<0.05)的病种是水痘(r=0.375,P=0.024)、上感(r=0.503,P=0.002)、急性咽部炎症(r=0.385,P=0.020)和急性气管炎(r=0.575,P<0.001)。多因素因子分析中月均PM2.5浓度在各自因子上的载荷系数分别为0.865、0.841、0.807和0.841,四个病种与含月均PM2.5浓度的各因子得分相关系数也均有统计学意义(P<0.05)。急性气管炎与前一月的月均PM2.5浓度单因素分析有关联(r=0.591,P<0.001),多因素分析与含月均PM2.5浓度的因子得分也有关联(r=0.360,P=0.031),存在明显的滞后效应。结论环境空气PM2.5浓度的增加可使水痘、上感、急性咽部炎症和急性气管炎这些急性呼吸道感染性疾病发病升高。政府部门应采取措施减少环境空气污染,做好大众预防急性呼吸道感染性疾病的健康教育。
Objective To explore the association between ambient air PM2.5 and acute respiratory tract infectious disease.Methods We collected the data concerning concentration of main pollutants in ambient air, meteorological indexes, and incidence and medical records regarding 11 types of acute respiratory tract infectious diseases in Wuqing District of Tianjin in 2015-2017. Statistical methods like Spearman correlation analysis and factor analysis were used to determine the association of each type of disease with PM2.5 concentration.Results The monthly average concentration of PM2.5 in Wuqing District during 2015-2017 was 41.00-137.00 μg/m^3, with the median being 62.00 μg/m^3. The PM2.5 concentration was lower in April-September [53.00 μg/m^3 (46.50 μg/m^3, 63.00 μg/m^3)] each year, but higher from October each year to March of the next [74.50 μg/m^3 (61.00 μg/m^3, 94.25 μg/m^3)], showing statistically significant differences (U=43.000, P<0.001). No statistically significant difference was found in the monthly average concentration of PM2.5 in 2015-2017 (H=1.435, P=0.488). There were statistically significant differences in the incidence data of pneumonia (t=2.850, P=0.007), upper respiratory tract infection (U=30.000, P<0.001), acute inflammation of the pharynx (U=79.000,P=0.009) and acute tracheitis (t=3.529, P=0.001) in April-September each year and from October each year to March of the next as well as in the incidence data of pertussis (H=6.751, P=0.034), pneumonia (F=16.671, P<0.001) and acute lower respiratory tract infection (H=16.727, P<0.001) in 2015-2017. Univariate analysis using Spearman correlation coefficient showed that the following studied diseases were significantly correlated with PM2.5 concentration: varicella (r=0.375, P=0.024), upper respiratory tract infection (r=0.503, P=0.002), acute inflammation of the pharynx (r=0.385, P=0.020) and acute tracheitis (r=0.575, P<0.001). Multivariate analysis of the factors influencing the above-mentioned four diseases indicated that the factor loadings of monthly average concentration of PM2.5 were 0.865, 0.841, 0.807 and 0.841 respectively. The correlation coefficients between the above-mentioned four diseases and factor score of common factor including monthly average PM2.5 concentration were also statistically significant respectively (P<0.05). Univariate analysis showed that acute tracheitis was related to the monthly average concentration of PM2.5 in the previous month (r=0.591, P<0.001), whereas multivariate analysis presented acute tracheitis was also correlated with factor score of common factor including monthly average PM2.5 concentration (r=0.360,P=0.031), with a significant lag effect.Conclusions The increment of ambient air PM2.5 concentration can increase the incidence of acute respiratory infectious diseases, including varicella, upper respiratory tract infection, acute inflammation of the pharynx and acute tracheitis. Government departments should take measures to reduce environmental air pollution and carry out health education for public prevention of acute respiratory infectious diseases.
作者
李平
孙梅青
李彭辉
卫沛楠
丁占林
王洪
于光平
冯哲
LI Ping;SUN Mei-qing;LI Peng-hui;WEI Pei-nan;DING Zhan-lin;WANG Hong;YU Guang-ping;FENG Zhe(Wuqing District Center for Disease Control and Prevention,Tianjin 301700,China;School of Environmental Science and Safety Engineering,Tianjin University of Technology,Tianjin 300384,China)
出处
《实用预防医学》
CAS
2019年第7期775-780,共6页
Practical Preventive Medicine
基金
国家自然科学基金(41601548)
天津市教委科研计划项目(2017KJ244)
天津市武清区科技发展计划项目(WQKJ201614)