title: A GIS-based spatial correlation analysis for ambient air pollution and AECOPD hospitalizations in Jinan, China.
abstract: 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, O3, 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, O3 and AECOPD hospitalization cases showed statistical significant spatially clustered. The Z-score of SO2, PM10, CO, O3, NO2 at residence is 15.88, 13.93, 12.60, 4.02, 2.44 respectively, while at workplace, concentrations of PM10, SO2, O3, CO and AECOPD hospitalization cases showed statistical significant spatially clustered. The Z-score of PM10, SO2, O3, 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 μg/m(3) increase of PM10 at workplace associated with a 7% (95%CI: [3.3%, 10%]) increase of hospitalizations due to AECOPD.
  
  
  CONCLUSIONS
  Ambient air pollution is correlated with AECOPD hospitalizations spatially. A 10 μg/m(3) increase of PM10 at workplace was associated with a 7% (95%CI: [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.
authors: Department of Respiratory Medicine, Qilu Hospital, Shandong University, No. 107, Wenhua Xi Road, Jinan, Shandong, 250012, PR China; Department of Respiratory Diseases, China-Japan Friendship Hospital, Peking University, Beijing, PR China. Electronic address: wangwenqiao1989@163.com.
authors: Wenqiao
authors: W
authors: Wang
authors: Department of Respiratory Medicine, Qilu Hospital, Shandong University, No. 107, Wenhua Xi Road, Jinan, Shandong, 250012, PR China. Electronic address: 13256742856@163.com.
authors: Yangyang
authors: Y
authors: Ying
authors: College of Population, Resources and Environment, Shandong Normal University, No. 88, Wenhua Dong Road, Jinan, Shandong, 250012, PR China. Electronic address: wqy6420582@163.com.
authors: Quanyuan
authors: Q
authors: Wu
authors: College of Population, Resources and Environment, Shandong Normal University, No. 88, Wenhua Dong Road, Jinan, Shandong, 250012, PR China. Electronic address: gissuifeng@163.com.
authors: Haiping
authors: H
authors: Zhang
authors: Department of Respiratory Medicine, Qilu Hospital, Shandong University, No. 107, Wenhua Xi Road, Jinan, Shandong, 250012, PR China. Electronic address: ma@qiluhuxi.com.
authors: Dedong
authors: D
authors: Ma
authors: Department of Respiratory Medicine, Qilu Hospital, Shandong University, No. 107, Wenhua Xi Road, Jinan, Shandong, 250012, PR China. Electronic address: xiaowei4226@163.com.
authors: Wei
authors: W
authors: Xiao
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000393:Air Pollutants / Q000032:analysis*; D000395:Air Pollutants, Occupational / Q000032:analysis; D000397:Air Pollution / Q000032:analysis*; D002248:Carbon Monoxide / Q000032:analysis; D002681:China / Q000453:epidemiology; D004784:Environmental Monitoring / Q000706:statistics & numerical data; D005260:Female; D040362:Geographic Information Systems / Q000706:statistics & numerical data*; D006760:Hospitalization / Q000706:statistics & numerical data*; D006801:Humans; D008297:Male; D015233:Models, Statistical; D010126:Ozone / Q000032:analysis; D052638:Particulate Matter / Q000032:analysis; D029424:Pulmonary Disease, Chronic Obstructive / Q000191:economics / Q000401:mortality* / Q000503:physiopathology*; D011788:Quality of Life; D012189:Retrospective Studies; D012307:Risk Factors; D012621:Seasons; D013458:Sulfur Dioxide / Q000032:analysis; D013997:Time Factors
chemical_list: D000393:Air Pollutants; D000395:Air Pollutants, Occupational; D052638:Particulate Matter; D013458:Sulfur Dioxide; D010126:Ozone; D002248:Carbon Monoxide
keywords: AECOPD hospitalization; Ambient air pollution; GIS; Spatial autocorrelation