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预防医学  2021, Vol. 33 Issue (3): 231-235    DOI: 10.19485/j.cnki.issn2096-5087.2021.03.004
  论著 本期目录 | 过刊浏览 | 高级检索 |
居民每日死亡例数与空气污染物日均浓度的关系
曹洋1, 杨丽梅1, 坑斌2, 刘羽1
1.北京市怀柔区疾病预防控制中心信息统计科,北京 101400;
2.北京市怀柔区疾病预防控制中心环境卫生科
The relationship between air pollutants and mortality in Huairou District
CAO Yang*, YANG Limei, KENG Bin, LIU Yu
*Institute of Information and Statistics, Huairou Center for Disease Control and Prevention, Beijing 101400, China
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摘要 目的 评价北京市怀柔区居民每日死亡例数与空气污染物日均浓度的关系,为制订空气污染治理措施提供依据。方法 通过北京市环境保护监测中心怀柔镇环境监测站点、怀柔区气象局和北京市卫生防病监测信息资源整合分析平台收集2014—2018年怀柔区空气污染物监测、气象监测及死因监测资料,采用广义相加模型分析居民每日死亡例数与空气污染物日均浓度的关系。结果 2014—2018年怀柔区SO2、NO2、CO、O3、PM10和PM2.5日均浓度的中位数分别为5.00 μg/m3、24.00 μg/m3、0.71 mg/m3、77.27 μg/m3、64.25 μg/m3和44.13 μg/m3,除O3外均呈下降趋势(P<0.05)。单污染物模型结果显示,NO2日均浓度每升高10 μg/m3,全人群、女性和<65岁人群每日非意外死亡风险在滞后2 d时分别增加1.69%(95%CI:0.31%~3.08%)、3.31%(95%CI:1.24%~5.42%)和3.31%(95%CI:0.51%~6.19%);CO和PM2.5日均浓度每升高10 μg/m3,<65岁人群每日非意外死亡风险在滞后2 d时分别增加0.08%(95%CI:0.01%~0.14%)和0.88%(95%CI:0.12%~1.64%);O3日均浓度每升高10 μg/m3,男性每日非意外死亡风险在滞后4 d时增加0.69%(95%CI:0.02%~1.36%)。多污染物模型结果显示,NO2、CO和PM2.5在分别调整其他2种空气污染物的影响后,对<65岁人群每日非意外死亡的影响在滞后2 d时均无统计学意义(P>0.05)。结论 怀柔区NO2、CO、O3和PM2.5日均浓度升高可能增加居民每日非意外死亡的风险,且存在一定的滞后性。
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曹洋
杨丽梅
坑斌
刘羽
关键词 空气污染物非意外死亡广义相加模型    
AbstractObjective To evaluate the relationship between air pollutants and mortality of residents in Huairou District, Beijing, providing a basis for the formulation of air pollution control measures. Methods The data of daily deaths, meteorological factors and air pollutants in Huairou District from 2014 to 2018 were collected from Beijing Disease Prevention Monitoring Information Integration and Analysis System, Huairou Meteorological Bureau and Environmental Monitoring Station. The generalized additive models were used to analyze the relationship between the average daily concentration of air pollutants and the daily deaths. Results The medians of daily average concentrations of SO2, NO2, CO, O3, PM10 and PM2.5 were 5.00 μg/m3, 24.00 μg/m3, 0.71 mg/m3, 77.27 μg/m3, 64.25 μg/m3 and 44.13 μg/m3, respectively. Except for O3, the daily average concentrations of SO2, NO2, CO, PM10 and PM2.5 showed decreasing trends from 2014 to 2018. An increase of 10 μg/m3 of NO2 resulted in an elevation of 1.69% ( 95%CI: 0.31%-3.08% ) , 3.31% ( 95%CI: 1.24%-5.42% ) and 3.31% ( 95%CI: 0.51%-6.19% ) for non-accidental death in the whole population, females and people under 65 years old, respectively, with a delay of 2 days (lag2). For every 10 μg/m3 increase in the daily average concentrations of CO and PM2.5, the risk of non-accidental death among people under 65 years old at lag2 increased by 0.08% ( 95%CI: 0.01%-0.14% ) and 0.88% ( 95%CI: 0.12%-1.64% ) , respectively. For every 10 μg/m3 increase in daily average concentration of O3, there was 0.69% ( 95%CI: 0.02%-1.36% ) increase in daily male non-accidental death risk at lag4. The results of the multi-pollutant model showed that after adjusting the effects of the other two air pollutants, NO2, CO and PM2.5 had no statistically significant effects on the daily non-accidental deaths of people under 65 years old at lag2 ( P>0.05 ) . Conclusion The ambient NO2, CO, O3 and PM2.5 pollution increase daily non-accidental deaths, which shows a lag effect.
Key wordsair pollutants    non-accidental death    generalized additive model
收稿日期: 2020-09-15      修回日期: 2020-12-01      出版日期: 2021-03-10
中图分类号:  R122  
  R195  
基金资助:国家科技基础资源调查专项(2017FY101200-03)
通信作者: 曹洋,E-mail:caoyangcq@sina.cn   
作者简介: 曹洋,硕士,医师,主要从事死因信息报告工作
引用本文:   
曹洋, 杨丽梅, 坑斌, 刘羽. 居民每日死亡例数与空气污染物日均浓度的关系[J]. 预防医学, 2021, 33(3): 231-235.
CAO Yang, YANG Limei, KENG Bin, LIU Yu. The relationship between air pollutants and mortality in Huairou District. Preventive Medicine, 2021, 33(3): 231-235.
链接本文:  
http://www.zjyfyxzz.com/CN/10.19485/j.cnki.issn2096-5087.2021.03.004      或      http://www.zjyfyxzz.com/CN/Y2021/V33/I3/231
[1] CAREY I M,ATKINSON R W,KENT A J,et al.Mortality associations with long-term exposure to outdoor air pollution in a national English cohort[J] . Am J Respir Crit Care Med,2013,187(11):1226-1233.
[2] BEELEN R,RAASCHOU-NIELSEN O,STAFOGGIA M,et al.Effects of long-term exposure to air pollution on natural-cause mortality:an analysis of 22 European cohorts within the multicentre ESCAPE project[J] . Lancet,2014,383(9919):785-795.
[3] 薛江丽,王旗,蔡玥,等. 北京市大气可吸入性颗粒物污染对居民死亡影响的时间序列分析[J] . 中华预防医学杂志,2012,46(5):447-451.
[4] 李静,王焕新,屈龙,等. 昌平区PM2.5和气温对日门诊量的交互影响[J] . 预防医学,2019,31(6):593-596,599.
[5] 张云权,朱耀辉,李存禄,等. 广义相加模型在R软件中的实现[J] . 中国卫生统计,2015,32(6):1073-1075.
[6] 中华人民共和国环境保护部. 环境空气质量标准:GB 3095—2012[S] . 北京:中国标准出版社,2012.
[7] 何晓庆,王小红,罗进斌. 大气PM10与呼吸系统疾病死亡的关系研究[J] . 预防医学,2019,31(10):987-991.
[8] 陈丽,汪曦,顾怡勤,等. 大气污染对上海市闵行区居民糖尿病死亡的急性影响[J] . 职业与健康,2019,35(5):656-659,665.
[9] 苏健婷,杜婧,王春梅,等. 大气污染物对北京市常住居民死亡影响的时间序列研究[J] . 环境与健康杂志,2018,35(5):421-424.
[10] 张亮,张秋平,谭爱军. 珠海市空气污染对人群死亡的影响[J] . 实用预防医学,2019,26(4):446-449.
[11] 胡星星. SO2、NO2污染及温度变化对合肥市区非意外死亡的影响及模型预测[D] . 合肥:安徽医科大学,2019.
[12] 谷亚亚,甄国新,谈敦芳,等. 北京市顺义区大气臭氧对居民每日死亡的影响[J] . 环境与健康杂志,2019,36(4):329-334.
[13] 张开月,金武,姚庆兵,等. 扬州市空气细颗粒物与居民死亡关系的时间序列分析[J] . 南通大学学报(医学版),2019,39(4):299-301.
[14] 陈浪,赵川,关茗洋,等. 石家庄市大气颗粒污染物浓度与居民死亡率的时间序列分析[J] . 中华疾病控制杂志,2018,22(3):272-277.
[15] 钱旭君,沈月平,贺天锋,等. 宁波市大气颗粒物与人群因心脑血管疾病死亡的时间序列研究[J] . 中华流行病学杂志,2016,37(6):841-845.
[16] DASTOORPOOR M,GOUDARZI G,KHANJANI N,et al.Lag time structure of cardiovascular deaths attributed to ambient air pollutants in Ahvaz,Iran,2008-2015[J] . Int J Occup Med Environ Health,2018,31(4):459-473.
[17] 褚圆圆. 武汉市大气污染与呼吸系统疾病死亡的关联研究[D] . 武汉:武汉大学,2017.
[18] 周海泓,张杨,雍宗锋,等. 基于广义相加模型分析可吸入颗粒物对人群呼吸系统的短期健康效应[J] . 江苏预防医学,2018,29(4):389-392.
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