唐山市PM<sub>2.5</sub>污染对城市居民呼吸系统疾病日门诊量的影响

doi:10.3969/j.issn.1006-3110.2019.07.006

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摘要目的评价PM_2.5污染程度对唐山市城市居民呼吸系统疾病日门诊量的影响。方法收集唐山市2013年11月－2014年3月、2014年11月－2015年3月、2015年11月－2016年3月的气象监测数据、大气污染物浓度资料及各三级甲等综合性医院呼吸系统疾病日门诊人数,采用Pearson相关分析大气污染物、气象因素以及呼吸系统疾病门诊量之间的相关性；采用时间序列的广义相加模型分析大气污染浓度与呼吸系统疾病日门诊量之间的关联性。结果 2013年11月－2014年3月、2014年11月－2015年3月、2015年11月－2016年3月三个时间段内,各大气污染物之间每日浓度的相关性分析结果显示PM₁₀、PM_2.5、SO₂、NO₂、CO之间存在明显的正相关,各大气污染物与气湿之间呈正相关,除PM_2.5外,其他污染物与呼吸系统疾病日门诊量之间无明显的相关性。其中PM_2.5分别滞后1、2、4 d对呼吸系统疾病日门诊量影响最大。且PM_2.5浓度每增加10 μg/m3时,呼吸系统疾病日门诊量分别增加0.25%(95%CI：0.18%~0.32%)、0.65% (95%CI：0.31%~0.99%)、0.42% (95%CI：0.11%~0.73%)。结论唐山市PM_2.5污染程度增高会导致呼吸系统疾病日门诊量的增加。

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	秦萌
	李松
	蒋守芳
	王金
	李培帅
	佟俊旺

关键词 ： PM_2.5, 时间序列, 呼吸系统疾病, 广义相加模型

Abstract：Objective To estimate the impact of PM_2.5 pollution on the daily outpatient visits for respiratory diseases in urban residents in Tangshan City. Methods We collected meteorological monitoring data, air pollutant concentration data and daily outpatient visits for respiratory diseases from all grade-A tertiary general hospitals in Tangshan City from November 2013 to March 2014, from November 2014 to March 2015 and from November 2015 to March 2016. The correlations among air pollutants, meteorological factors and daily outpatient volume of respiratory diseases were evaluated by Pearson correlation. The associations between air pollutants and daily outpatient volume of respiratory diseases were analyzed by using the generalized additive model (GAM) of time series.Results The correlation analysis on daily concentration of all air pollutants during the above-mentioned three periods showed thatthere were significantly positive correlations among PM₁₀, PM_2.5, SO₂ , NO₂ and COas well as between each air pollutant and humidity,but there was no significant correlation between all air pollutants except PM_2.5 and daily outpatient visits for respiratory diseases. PM_2.5 for 1-day, 2-day and 4-day lag was positively associated with daily outpatient volume of respiratory diseases; moreover, the daily outpatient volume of respiratory diseases increased by 0.25% (95%CI:0.18%-0.32%), 0.65% (95%CI:0.31%-0.99%) and 0.42% (95%CI: 0.11%-0.73%) respectively with PM_2.5 concentration increase per 10 μg/m³. Conclusions The increase of atmospheric PM_2.5 pollution in Tangshan City can lead to the increment of daily outpatient volume of respiratory diseases.

Key words： PM_2.5 time series respiratory diseases generalized additive model

收稿日期: 2018-09-25

R122.2

基金资助:华北理工大学大学生创新创业计划项目(X2015158)

通讯作者: 佟俊旺,E-mail:junwangtong@163.com。

作者简介: 秦萌(1991-),女,硕士研究生,主要从事环境卫生学研究工作。

引用本文:

秦萌,李松,蒋守芳,王金,李培帅,佟俊旺. 唐山市PM_2.5污染对城市居民呼吸系统疾病日门诊量的影响[J]. 实用预防医学, 2019, 26(7): 791-794. QIN Meng, LI Song, JIANG Shou-fang, WANG Jin, LI Pei-shuai, TONG Jun-wang. Effect of PM_2.5 on daily outpatient visits for respiratory diseases among urban residents in Tangshan City. , 2019, 26(7): 791-794.

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https://www.syyfyx.com/CN/10.3969/j.issn.1006-3110.2019.07.006 或 https://www.syyfyx.com/CN/Y2019/V26/I7/791

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