Short-term effects of ambient air pollution and cause-specific emergency department visits in Guangzhou
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摘要:
目的 分析广州市空气污染物浓度与居民因不同疾病(循环系统疾病、消化系统疾病、神经系统疾病和呼吸系统疾病)而寻求急救服务人次的关系，探讨广州市空气污染对人群健康影响的短期效应。 方法 收集广州市2015-2017年空气污染物二氧化硫(sulfur dioxide，SO2)、二氧化氮(nitrogen dioxide，NO2)、一氧化碳(carbon monoxide，CO)、细颗粒物(fine particulate matter，PM2.5)的每日24 h平均浓度和臭氧(ozone，O3)最大8 h浓度、日均气温、相对湿度和4大疾病别每日急救人次，采用时间序列分析的广义相加模型，分析空气中污染物浓度和居民4大疾病别急救人次的关系。 结果 研究期间空气中SO2、NO2、CO、O3、PM2.5的日平均浓度分别是13.24 μg/m3、45.96 μg/m3、0.97 mg/m3、123.77 μg/m3、和36.22 μg/m3。经过单污染物模型分析，空气中SO2每增加4.70 μg/m3，循环系统急救量增加2.91%(95%CI：1.00%~4.85%)，在多污染物模型中，循环系统急救量则增加4.39%(95%CI：1.22%~7.67%)。 结论 大气SO2污染可能增加居民循环系统疾病的风险，应采取防控措施降低SO2排放。 Abstract:Objective To understand the relationship between the concentration of air pollutants and daily emergency department visits for different diseases (circulatory system disease, digestive system disease, nervous system disease and respiratory system disease) in Guangzhou, Guangdong Province. Methods The daily average concentrations of sulfur dioxide (SO2), nitrogen dioxide (NO2, carbon monoxide (CO) and PM2.5 and the daily maximum 8-hour concentrations of O3, the daily average temperature, the relative humidity and cause -specific emergency department visits of the four major diseases from 2015 to 2017 were collected in Guangzhou. Semi-parametric generalized additive model was used to analyze the relationship between the concentration of pollutants and daily cause-specific emergency department visits. Results The daily average concentrations of SO2, NO2, CO, O3 and PM2.5 during the study period were 13.24 μg/m3, 45.96 μg/m3, 0.97 mg/m3, 123.77 μg/m3 and 36.22 μg/m3, respectively. For circulatory system disease, the independently significant associations of SO2 with emergency department visits in single-pollutant models (2.91%, 95% CI: 1.00%-4.85%), and multipollutant models (4.39%, 95% CI: 1.22%-7.67%) were observed. Conclusion The ambient SO2 increases the risk of emergency department visits due to circulatory diseases in Guangzhou. Comprehensive prevention and control measures should be taken to reduce the emission of SO2. -
图 1 2015-2017年各疾病别急救人次和空气污染物浓度(SO2、NO2、CO、O3、PM2.5)日时间序列图
Figure 1. Daily time-series plots of case-specific emergency department visits and air pollution (SO2, NO2, CO, O3, PM2.5) concentrations from 2015 to 2017
图 2 大气各污染物浓度每升高IQR对居民四大系统疾病急救人次影响的0~3 d滞后效应
注：空心圆点表示差异有统计学意义，条形表示95%置信区间
Figure 2. Percent change in cause-specific emergency department visits for four major diseases per interquartile range (IQR) increment in SO2, NO2, CO, O3, PM2.5concentrations at single-day exposure lags(the current day(lag0) or up to 3 days prior to current day(lag3)), based on single-pollutant models
图 3 单污染物模型和多污染物模型中各污染物浓度每升高IQR对居民四大系统疾病急救人次影响的两天移动平均值的滞后效应图
注：空心圆点表示差异有统计学意义，条形表示95%置信区间。
Figure 3. Percent change in cause-specific emergency department visits for four major diseases per interquartile range (IQR) increment in 2-day moving average (current day and previous day) of daily SO2, NO2, CO, O3, PM2.5 concentrations according to single-pollutant and multipollutant models
表 1 2015-2017年急诊门诊量、气象因素和空气污染物的统计学描述
Table 1. Descriptive statistics of cause-specific emergency department visits, meteorological factors, and concentrations of air pollutants (SO2, NO2, CO, O3, PM2.5) in Guangzhou, China from 2015 to 2017
变量 x±s 最小值 最大值 IQR 急诊门诊量 神经系统 91±13 57 150 16 呼吸系统 26±7 9 51 9 消化系统 26 ±6 12 50 7 循环系统 38 ±8 20 69 10 气象学因素 相对湿度(%) 80.09±10.01 34.00 100.00 14.00 气温(℃) 22.12 ±6.06 3.40 31.10 10.10 空气污染物 SO2(μg/m3) 13.24 ±4.08 5.93 35.00 4.70 NO2(μg/m3) 45.96 ±16.52 18.65 136.70 20.56 CO(mg/m3) 0.97±0.16 0.65 1.76 0.19 O3(μg/m3) 123.77±55.42 17.31 380.04 78.19 PM2.5(μg/m3) 36.22 ±18.90 8.31 134.02 24.01 
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表 2 各污染物与气象因素的相关性分析
Table 2. The corrclation of pollutant concentrations and meteorological measurements
变量 SO2 NO2 CO O3 PM2.5 相对湿度 气温 SO2 1 NO2 0.668b 1 CO 0.074a 0.175b 1 O3 0.194b 0.078b -0.095b 1 PM2.5 0.674b 0.798b 0.163b 0.240b 1 相对湿度 -0.287b 0.023 0.024 -0.361b -0.253b 1 气温 -0.057 -0.370b -0.181b 0.402b -0.386b 0.152b 1 注：aP＜0.05；bP＜0.01。
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