Jianzhong Zhang1, Dunqiang Ren2, Xue Cao1, Tao Wang1, Xue Geng1, Xin Li1, Jinglong Tang1, Shuguang Leng1, Hongmei Wang2, Yuxin Zheng3. 1. Department of Occupational and Environmental Health, School of Public Health, Qingdao University, Qingdao, 266021, Shandong, China. 2. Department of Respiratory Medicine and Critical care, The Affiliated Hospital of Qingdao University, Qingdao, 266003, Shandong, China. 3. Department of Occupational and Environmental Health, School of Public Health, Qingdao University, Qingdao, 266021, Shandong, China. yxzheng@qdu.edu.cn.
Abstract
BACKGROUND: Pneumonia is one of the principal reasons for incidence and death in the world. The former research mainly concentrated on specific sources of patients. Besides, due to the heterogeneity among regions, there are inconsistencies in the outcome of these surveys. To explore the relationship between atmospheric pollution and hospital visits for pneumonia under the climate and pollution conditions in Qingdao, we carried out this study. METHODS: The medical records of pneumonia patients were gathered from the affiliated hospital of Qingdao University during Jan 1st, 2014, and Dec 31st,2018. Daily concentrations of PM2.5, PM10, SO2, NO2, as well as CO, were collected from the national air quality monitoring stations in Qingdao. Case-crossover study design and conditional logistic regression model were used to estimate the associations. Daily temperature, relative humidity, and atmospheric pressure were adjusted as the covariates in all models. A principal component analysis was used to solve the multicollinearity between atmospheric pollutants and investigate the relationship between various air pollutants and pneumonia occurs. RESULTS: In the single pollutant model, with interquartile range increment of the density of PM2.5, PM10, NO2 and SO2 at the lag2 days, the odds ratio of hospital visits for pneumonia patients increased by 6.4% (95%CI, 2.3-10.7%), 7.7% (95%CI, 3.2-12.4%), 6.7% (95%CI, 1.0-12.7%), and 7.2% (95%CI, 1.1-13.5%). Stratified analysis showed that pollutants were more significant in the cold period. Besides, the impact of atmospheric particulates on different ages mainly occurs in the young child (0 to 3-year-old). The odds ratio was 1.042 (95%CI, 1.012-1.072) when the principal components of atmospheric pollutants were included in the conditional logistic model. CONCLUSIONS: Our study found a significant relationship between short-term uncovering to PM2.5, PM10, NO2, SO2, and hospital visits for pneumonia in Qingdao. The effect of atmospheric pollutants mainly arose in a cold period. The particulate matter might be the principal reason in inducing hospital visits for pneumonia.
BACKGROUND:Pneumonia is one of the principal reasons for incidence and death in the world. The former research mainly concentrated on specific sources of patients. Besides, due to the heterogeneity among regions, there are inconsistencies in the outcome of these surveys. To explore the relationship between atmospheric pollution and hospital visits for pneumonia under the climate and pollution conditions in Qingdao, we carried out this study. METHODS: The medical records of pneumoniapatients were gathered from the affiliated hospital of Qingdao University during Jan 1st, 2014, and Dec 31st,2018. Daily concentrations of PM2.5, PM10, SO2, NO2, as well as CO, were collected from the national air quality monitoring stations in Qingdao. Case-crossover study design and conditional logistic regression model were used to estimate the associations. Daily temperature, relative humidity, and atmospheric pressure were adjusted as the covariates in all models. A principal component analysis was used to solve the multicollinearity between atmospheric pollutants and investigate the relationship between various air pollutants and pneumonia occurs. RESULTS: In the single pollutant model, with interquartile range increment of the density of PM2.5, PM10, NO2 and SO2 at the lag2 days, the odds ratio of hospital visits for pneumoniapatients increased by 6.4% (95%CI, 2.3-10.7%), 7.7% (95%CI, 3.2-12.4%), 6.7% (95%CI, 1.0-12.7%), and 7.2% (95%CI, 1.1-13.5%). Stratified analysis showed that pollutants were more significant in the cold period. Besides, the impact of atmospheric particulates on different ages mainly occurs in the young child (0 to 3-year-old). The odds ratio was 1.042 (95%CI, 1.012-1.072) when the principal components of atmospheric pollutants were included in the conditional logistic model. CONCLUSIONS: Our study found a significant relationship between short-term uncovering to PM2.5, PM10, NO2, SO2, and hospital visits for pneumonia in Qingdao. The effect of atmospheric pollutants mainly arose in a cold period. The particulate matter might be the principal reason in inducing hospital visits for pneumonia.
Entities:
Keywords:
Air pollutants; Case-crossover design; PM10; PM2.5; Pneumonia; Principal component analysis
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