title: Air pollution indicators predict outbreaks of asthma exacerbations among elementary school children: integration of daily environmental and school health surveillance systems in Pennsylvania.
abstract: Objectives of this study are to determine if a relationship exists between asthma exacerbations among elementary school children in industrialized countries (with climatic seasons) and exposure to daily air pollution with particulate matter, sulfur dioxide, nitrogen dioxide, nitrogen oxides, carbon monoxide, and ozone, when controlled for potential confounders; and, if so, to derive a statistical model that predicts variation of asthma exacerbations among elementary school children. Using an ecological study design, health records of 168,25 students from elementary schools in 49 Pennsylvania counties employing "Health eTools for Schools" were analyzed. Asthma exacerbations were recorded by nurses as treatment given during clinic visits each day. Daily air pollution measurements were obtained from the EPA's air quality monitoring sites. The distribution of asthmatic grouping for pollen and calendar seasons was developed. A Poisson regression model was used to predict the number of asthma exacerbations. The greatest occurrence of asthma exacerbations was in autumn, followed by summer, spring and winter. If the number of asthma exacerbations on a day is N and the daily mean of asthma exacerbations for the three-year period is 48, the probabilities of N > 48 in tree pollen and grass pollen seasons were 56.5% and 40.8%, respectively (p < 0.001). According to the Poisson regression, the week number and prior day CO, SO₂, NO₂, NOx, PM₂.₅, and O₃ had significant effects on asthma exacerbations among students. Monitoring of air pollutants over time could be a reliable new means for predicting asthma exacerbations among elementary school children. Such predictions could help parents and school nurses implement effective precautionary measures.
authors.affiliation: Department of Epidemiology and Biostatistics, Indiana University Bloomington, Indiana, USA.
authors.forename: Ahmed H
authors.initials: AH
authors.lastname: YoussefAgha
authors.forename: Wasantha P
authors.initials: WP
authors.lastname: Jayawardene
authors.forename: David K
authors.initials: DK
authors.lastname: Lohrmann
authors.forename: Gamal S
authors.initials: GS
authors.lastname: El Afandi
mesh_terms: D000393:Air Pollutants / Q000032:analysis*; D000397:Air Pollution / Q000706:statistics & numerical data*; D000485:Allergens / Q000032:analysis; D001249:Asthma / Q000453:epidemiology*; D002648:Child; D002675:Child, Preschool; D004196:Disease Outbreaks / Q000706:statistics & numerical data*; D004784:Environmental Monitoring / Q000379:methods*; D005260:Female; D006801:Humans; D008297:Male; D015233:Models, Statistical; D009585:Nitrogen Dioxide / Q000032:analysis; D009589:Nitrogen Oxides / Q000032:analysis; D010126:Ozone / Q000032:analysis; D052638:Particulate Matter / Q000032:analysis; D010414:Pennsylvania / Q000453:epidemiology; D011058:Pollen; D012572:School Health Services; D012621:Seasons; D013458:Sulfur Dioxide / Q000032:analysis
chemical_list: D000393:Air Pollutants; D000485:Allergens; D009589:Nitrogen Oxides; D052638:Particulate Matter; D013458:Sulfur Dioxide; D010126:Ozone; D009585:Nitrogen Dioxide