Background: Acute exacerbations of COPD (AECOPD) are important events during disease procedure. AECOPD have negative effect on patients' quality of life, symptoms and lung function, and result in high socioeconomic costs. Though previous studies have demonstrated the significant association between outdoor air pollution and AECOPD hospitalizations, little is known about the spatial relationship utilized a spatial analyzing technique- Geographical Information System (GIS). Objective: Using GIS to investigate the spatial association between ambient air pollution and AECOPD hospitalizations in Jinan City, 2009. Methods: 414 AECOPD hospitalization cases in Jinan, 2009 were enrolled in our analysis. Monthly concentrations of five monitored air pollutants (NO2, SO2, PM10, O-3, CO) during January 2009-December 2009 were provided by Environmental Protection Agency of Shandong Province. Each individual was geocoded in ArcGIS10.0 software. The spatial distribution of five pollutants and the temporal-spatial specific air pollutants exposure level for each individual was estimated by ordinary Kriging model. Spatial autocorrelation (Global Moran's I) was employed to explore the spatial association between ambient air pollutants and AECOPD hospitalizations. A generalized linear model (GLM) using a Poisson distribution with log-link function was used to construct a core model. Results: At residence, concentrations of SO2, PM10, NO2, CO, O-3 and AECOPD hospitalization cases showed statistical significant spatially clustered. The Z-score of SO2, PM10, CO, O-3, NO2 at residence is 15.88, 13.93, 12.60, 4.02, 2.44 respectively, while at workplace, concentrations of PM10, SO2, O-3, CO and AECOPD hospitalization cases showed statistical significant spatially clustered. The Z-score of PM10, SO2, O-3, CO at workplace is 11.39, 8.07, 6.10, and 5.08 respectively. After adjusting for potential confounders in the model, only the PM10 concentrations at workplace showed statistical significance, with a 10 mu g/m(3) increase of PM10 at workplace associated with a 7% (95%Cl: [3.3%, 10%]) increase of hospitalizations due to AECOPD. Conclusions: Ambient air pollution is correlated with AECOPD hospitalizations spatially. A 10 mu g/m(3) increase of PM10 at workplace was associated with a 7% (95%Cl: [3.3%, 10%]) increase of hospitalizations due to AECOPD in Jinan, 2009. As a spatial data processing tool, GIS has novel and great potential on air pollutants exposure assessment and spatial analysis in AECOPD research. (c) 2015 Elsevier Ltd. All rights reserved.
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外文
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出版当年[2014]版:
大类|3 区医学
小类|3 区心脏和心血管系统3 区呼吸系统
最新[2025]版:
大类|3 区医学
小类|3 区心脏和心血管系统3 区呼吸系统
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出版当年[2013]版:
Q2CARDIAC & CARDIOVASCULAR SYSTEMSQ2RESPIRATORY SYSTEM
最新[2023]版:
Q2CARDIAC & CARDIOVASCULAR SYSTEMSQ2RESPIRATORY SYSTEM
第一作者单位:[1]Shandong Univ, Qilu Hosp, Dept Resp Med, Jinan 250012, Shandong, Peoples R China[2]Peking Univ, China Japan Friendship Hosp, Dept Resp Dis, Beijing 100871, Peoples R China
通讯作者:
通讯机构:[1]Shandong Univ, Qilu Hosp, Dept Resp Med, Jinan 250012, Shandong, Peoples R China[*1]Shandong Univ, Qilu Hosp, Dept Resp Med, 107 Wenhua Xi Rd, Jinan 250012, Shandong, Peoples R China
推荐引用方式(GB/T 7714):
Wang Wenqiao,Ying Yangyang,Wu Quanyuan,et al.A GIS-based spatial correlation analysis for ambient air pollution and AECOPD hospitalizations in Jinan, China[J].RESPIRATORY MEDICINE.2015,109(3):372-378.doi:10.1016/j.rmed.2015.01.006.
APA:
Wang, Wenqiao,Ying, Yangyang,Wu, Quanyuan,Zhang, Haiping,Ma, Dedong&Xiao, Wei.(2015).A GIS-based spatial correlation analysis for ambient air pollution and AECOPD hospitalizations in Jinan, China.RESPIRATORY MEDICINE,109,(3)
MLA:
Wang, Wenqiao,et al."A GIS-based spatial correlation analysis for ambient air pollution and AECOPD hospitalizations in Jinan, China".RESPIRATORY MEDICINE 109..3(2015):372-378