摘要
目的研究佛山市大气PM_(2.5)日均浓度对综合医院门诊呼吸系统疾病日均门诊量的影响。方法收集2017年大气PM_(2.5)、PM_(10)、SO_2、NO_2、CO、O_3-1h、O_3-8h 7个指标污染物资料、气象资料以及佛山市2家综合医院门诊呼吸系统疾病日均门诊量资料,采用广义相加模型的时间序列分析,控制长期趋势、星期几效应和气象等影响因素后,研究佛山市大气PM_(2.5)与呼吸系统疾病日均门诊量的关系。结果 2017年佛山市大气污染物污染整体呈优良水平,主要污染物PM_(2.5)、PM_(10)、SO_2、NO_2、CO、O_3-1h、O_3-8h均符合国家《环境空气质量标准》(GB 3095—2012)二级或以上标准。大气PM_(2.5)日均浓度为33.2μg/m^3,符合国家二级标准,全年超标天数为9 d,2家医院全年呼吸系统疾病门诊量为261 158人次,平均715.50人次/d。Spearman相关分析提示呼吸系统疾病日均门诊量与SO_2、NO_2、PM_(10)呈正相关,相关系数分别为0.19、0.33和0.20,均有统计学意义(P<0.05)。广义相加模型分析结果显示,大气PM_(2.5)日均浓度与呼吸系统疾病日均门诊量呈正相关关系,当天(lag0)PM_(2.5)日均浓度对呼吸系统疾病门诊量的影响最大(ER=2.744,95%CI:0.701～4.827),PM_(2.5)每增加10μg/m^3,每日呼吸系统疾病门诊量增加2.744%。在多污染物模型分析中,引入O_3-1h(ER=3.425,95%CI:1.278～5.617)、O_3-8h(ER=4.611,95%CI:2.373～6.899)时与PM_(2.5)联合作用对呼吸系统疾病门诊量相关性明显升高。结论佛山市大气PM_(2.5)污染与呼吸系统疾病门诊量呈正相关关系。
Objective To analyze the impact of ambient PM2.5 on hospital outpatient visits for respi- ratory diseases. Methods Data on ambient PM2.5, PM10, SO2, NO2, CO, O3-1h and O3-8h in 2017 were collected from Foshan Meteorological Bureau and Foshan Environmental Protection Bureau. Data on daily hospital outpatient visits were collected from two hospitals in Foshan. A time-series analysis using a gener- alized additive model （GAM） was applied to assess the association between ambient PMzs concentration and hospital outpatient visits for respiratory diseases after adjustment for long-term trend, day-of-week, meteorological factors and other air pollutants. Results Air pollution in Foshan City showed excellent lev- el as a whole in 2017. The main pollutants of PM25, PM10, SO2, NO2, CO, O3-1h, and O3-8h met the sec- ond or higher standards of the National Environmental Air Quality Standard （GB 3095-2012）. The aver- age PM2.5 concentration in Foshan in 2017 was 33.2 μg/m3, meeting the national second-level standard. The numbers of days exceeding the standard were 9 days all the year round. The total outpatient visits for respiratory diseases in the two hospitals were 261 158 with average 715.50 visits per day. The hospital dai- ly average outpatient visits for respiratory diseases were positively correlated with the air pollutants of SO2, NO2, and PM10 by the Spearman correlation analysis （R=0.19, 0.33, 0.20; P〈0.05 for all）. The GAM analysis showed that the daily average concentration of ambient PM2.5 was positively correlated with the hos-pital outpatient visits for respiratory diseases. The effect of ambient PM2.5 was the largest on lag 0 day （ER = 2.744; 95% Ch 0.701,4.827）. For every 10 trg/m3increment of ambient PM2.5, the daily outpatient vis- its for respiratory diseases increased by 2.744%. In the analysis of multi-pollutant model, when introduc- ing O3-1h （ER = 3.425 ; 95% CI：1.278, 5.617） and O3-8h （ER = 4.611 ; 95% CI： 2.373, 6.899）, their combined effect with PM25 made the correlation between PM2.5 and outpatient visits for respiratory diseases increased significantly. Conclusion The ambient PM2.5 concentration was positively associated with hospi- tal outpatient visits for respiratory diseases in Foshan City.
作者
关绮华
梁自勉
莫莹莹
GUAN Qi-hua;LIANG Zi-mian;MO Ying-ying(Foshan Center for Disease Control and Prevention,Foshan 528000,China)
出处
《华南预防医学》
2018年第5期406-410,共5页
South China Journal of Preventive Medicine
关键词
颗粒物
呼吸系统
广义相加模型
时间序列
Particulate matter
Respiratory system
Generalized additive model
Time-series
