王鸿, 高俊宏, 方乐, 刘志永, 刘进仁, 范小琳, 李存治, 卢青, 孔庆博, 赵国栋. 西安市大气PM2.5短期暴露对人群心脑血管系统疾病死亡的影响[J]. 环境与职业医学, 2020, 37(10): 975-980. DOI: 10.13213/j.cnki.jeom.2020.20213
引用本文: 王鸿, 高俊宏, 方乐, 刘志永, 刘进仁, 范小琳, 李存治, 卢青, 孔庆博, 赵国栋. 西安市大气PM2.5短期暴露对人群心脑血管系统疾病死亡的影响[J]. 环境与职业医学, 2020, 37(10): 975-980. DOI: 10.13213/j.cnki.jeom.2020.20213
WANG Hong, GAO Jun-hong, FANG Le, LIU Zhi-yong, LIU Jin-ren, FAN Xiao-lin, LI Cun-zhi, LU Qing, KONG Qing-bo, ZHAO Guo-dong. Effects of short-term exposure to atmospheric PM2.5 on deaths due to cardiovascular and cerebrovascular diseases in Xi'an[J]. Journal of Environmental and Occupational Medicine, 2020, 37(10): 975-980. DOI: 10.13213/j.cnki.jeom.2020.20213
Citation: WANG Hong, GAO Jun-hong, FANG Le, LIU Zhi-yong, LIU Jin-ren, FAN Xiao-lin, LI Cun-zhi, LU Qing, KONG Qing-bo, ZHAO Guo-dong. Effects of short-term exposure to atmospheric PM2.5 on deaths due to cardiovascular and cerebrovascular diseases in Xi'an[J]. Journal of Environmental and Occupational Medicine, 2020, 37(10): 975-980. DOI: 10.13213/j.cnki.jeom.2020.20213

西安市大气PM2.5短期暴露对人群心脑血管系统疾病死亡的影响

Effects of short-term exposure to atmospheric PM2.5 on deaths due to cardiovascular and cerebrovascular diseases in Xi'an

  • 摘要: 背景

    PM2.5的健康效应是环境健康领域的研究热点,也是与我国居民身体健康密切相关的重大社会问题。

    目的

    分析西安市大气PM2.5短期暴露对人群心脑血管疾病死亡的影响。

    方法

    收集2014年1月1日—2018年12月31日西安市人群心脑血管疾病死亡资料、大气污染物(PM2.5、PM10、CO、SO2、NO2、O3)和气象数据(温度、相对湿度),并作相关性分析。采用基于时间序列的广义线性模型,控制时间趋势和星期几效应等混杂因素,将日均气温和日均相对湿度作为协变量,分析PM2.5单滞后(lag0~lag7)的效应,研究PM2.5单污染和多污染物累积滞后2 d(lag02)对心脑血管系统疾病死亡的效应,同时对性别和年龄(0~44,45~59,60~74,75~89和90岁以上)进行分层分析。

    结果

    研究期内PM2.5日均浓度为(67.0±55.4)μg·m-3,每日心脑血管疾病平均死亡人数为(70.17±18.53)人。PM2.5与PM10、SO2、NO2和CO呈正相关(r=0.88、0.64、0.68、0.79,P < 0.01),与O3、气温和湿度呈负相关(r=-0.42、-0.51和-0.05,P < 0.05)。PM2.5浓度每升高10 μg·m-3,在lag0~lag2的超额危险度(ER)分别为0.32%(95% CI:0.12%~0.52%)、0.28%(95% CI:0.07%~0.49%)和0.31%(95% CI:0.09%~0.52%),lag3~lag7的效应均无统计学意义。lag02时PM2.5单污染模型的ER为0.45%(95% CI:0.19%~0.70%),多污染物模型中PM2.5分别与SO2、NO2、O3组合,ER分别为0.38%(95% CI:0.10%~0.66%)、0.42%(95% CI:0.14%~0.70%)、0.45%(95% CI:0.20%~0.71%),经Z检验发现,多污染物模型与单污染物模型的累积滞后效应差异没有统计学意义(P>0.05)。PM2.5对男性与女性lag02时的ER分别为0.47%(95% CI:0.17%~0.78%)和0.42%(95% CI:0.10%~0.74%),P < 0.05;PM2.5对60~74、75~89和90岁以上人群lag02时的ER分别为0.41%(95% CI:0.01%~0.82%)、0.43%(95% CI:0.11%~0.75%)和0.99%(95% CI:0.26%~1.74%),P < 0.05;但Z检验显示不同性别、年龄组间差异无统计学意义(P>0.05)。

    结论

    2014—2018年西安市PM2.5污染可能会导致居民心脑血管疾病死亡风险的增加。

     

    Abstract: Background

    The health effect of PM2.5 is a research hotspot in the field of environmental health, as well as a major social issue closely related to the physical health of residents.

    Objective

    This study evaluates the effects of short-term exposure to PM2.5 on the mortality of cardio-cerebrovascular diseases in Xi'an.

    Methods

    Population deaths due to cardiovascular and cerebrovascular diseases, atmospheric pollutants (PM2.5, PM10, CO, SO2, NO2, and O3), and meteorological data (temperature and relative humidity) were collected in Xi'an from January 1, 2014 to December 31, 2018. Correlation analysis of the variables was conducted. Generalized additive model based on time series was used to analyze the exposure-response relationship between the concentration of PM2.5 and cardio-cerebrovascular disease deaths after controlling confounding factors such as time trend and day-of-the-week effect and having average daily temperature and relative humidity as covariates. On the basis of the single lag effect of PM2.5 (lag0-lag7), the cumulative effect of PM2.5 and other pollutants on the deaths due to cardio-cerebrovascular diseases at lag02 was estimated. Meanwhile, the effects of PM2.5 were stratified by gender and age (0-44, 45-59, 60-74, 75-89, and ≥ 90 years).

    Results

    During the study period, the average daily concentration of PM2.5 was (67.0±55.4) μg·m-3, and the average number of daily deaths from cardio-cerebrovascular diseases was 70.17±18.53. PM2.5 was positively correlated with PM10, SO2, NO2, and CO (r=0.88, 0.64, 0.68, and 0.79, P < 0.01), and negatively correlated with O3, temperature, and humidity (r=-0.42, -0.51, and -0.05, P < 0.05). For every 10μg·m-3 increase in PM2.5 concentration, the excess risks (ER) at lag0-lag2 were 0.32% (95% CI:0.12%-0.52%), 0.28% (95% CI:0.07%-0.49%), and 0.31% (95% CI:0.09%-0.52%), respectively, while the effects at lag3-lag7 were not significant. At lag02, the ER of the PM2.5 single pollutant model was 0.45% (95% CI:0.19%-0.70%), and the ERs of PM2.5 combined with SO2, NO2, and O3 were 0.38% (95% CI:0.10%-0.66%), 0.42% (95% CI:0.14%-0.70%), 0.45% (95% CI:0.20%-0.71%), respectively. The Z test results found that the cumulative lag effect of the multi-pollutant model was comparable to that of the single pollutant model, without significant differences (P>0.05). The ERs of PM2.5 at lag02 were 0.47% (95% CI:0.17%-0.78%) and 0.42% (95% CI:0.10%-0.74%) for men and women (P < 0.05), and 0.41% (95% CI:0.01%-0.82%), 0.43% (95% CI:0.11%-0.75%), and 0.99% (95% CI:0.26%-1.74%) for the 60-74, 75-89, and ≥ 90 years groups (P < 0.05), respectively. However, the Z test results showed no differences between the sex groups or among the age groups (P>0.05).

    Conclusion

    PM2.5 may increase the risk of deaths from cardio-cerebrovascular diseases in Xi'an from 2014 to 2018.

     

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