PDF(Pubmed)
Abstract：
It is unclear whether Gross Domestic Product (GDP) and greenness have additional modifying effects on the association between air pollution and respiratory system disease. Utilizing a time-stratified case-crossover design with a distributed lag linear model, we analyzed the association between six pollutants (PM2.5, PM10, NO2, SO2, O3, and CO) and 555,498 respiratory hospital admissions in Beijing from 1st January 2016 to 31st December 2019. We employed conditional logistic regression, adjusting for meteorological conditions, holidays and influenza, to calculate percent change of hospitalization risk. Subsequently, we performed subgroup analysis to investigate potential effect modifications using a two-sample z test. Every 10 μg/m3 increase in PM2.5, PM10, NO2, SO2, and O3 led to increases of 0.26% (95%CI: 0.17%, 0.35%), 0.15% (95%CI: 0.09%, 0.22%), 0.61% (95%CI: 0.44%, 0.77%), 1.72% (95%CI: 1.24%, 2.21%), and 0.32% (95%CI: 0.20%, 0.43%) in admissions, respectively. Also, a 1 mg/m3 increase in CO levels resulted in a 2.50% (95%CI: 1.96%, 3.04%) rise in admissions. The links with NO2 (p < 0.001), SO2 (p < 0.001), O3 (during the warm season, p < 0.001), and CO (p < 0.001) were significantly weaker among patients residing in areas with higher levels of greenness. No significant modifying role of GDP was observed. Greenness can help mitigate the effects of air pollutants, while the role of GDP needs further investigation.
摘要：
目前尚不清楚国内生产总值（GDP）和绿色是否对空气污染与呼吸系统疾病之间的关联具有额外的调节作用。利用分布滞后线性模型的时间分层案例交叉设计，我们分析了2016年1月1日至2019年12月31日北京6种污染物(PM2.5,PM10,NO2,SO2,O3和CO)与555,498例呼吸住院患者之间的关联.我们采用条件逻辑回归，根据气象条件进行调整，假期和流感，计算住院风险的百分比变化。随后，我们使用双样本z检验进行了亚组分析以研究潜在的效应修饰.PM2.5，PM10，NO2，SO2和O3每增加10μg/m3，导致0.26％的增加（95CI：0.17％，0.35%），0.15%（95CI：0.09%，0.22%），0.61%（95CI：0.44%，0.77%），1.72%（95CI：1.24%，2.21%），和0.32%（95CI：0.20%，0.43%)在招生中，分别。此外，CO水平增加1mg/m3导致2.50%(95CI：1.96%，3.04%）录取率上升。与NO2的链接（p<0.001），SO2（p<0.001），O3（在温暖的季节，p<0.001)，居住在绿色水平较高的地区的患者中，CO（p<0.001）明显较弱。没有观察到GDP的显着修饰作用。绿色可以帮助减轻空气污染物的影响，而GDP的作用需要进一步研究。
