title: Exploring associations between multipollutant day types and asthma morbidity: epidemiologic applications of self-organizing map ambient air quality classifications.
abstract: BACKGROUND
  Recent interest in the health effects of air pollution focuses on identifying combinations of multiple pollutants that may be associated with adverse health risks.
  
  
  OBJECTIVE
  Present a methodology allowing health investigators to explore associations between categories of ambient air quality days (i.e., multipollutant day types) and adverse health.
  
  
  METHODS
  First, we applied a self-organizing map (SOM) to daily air quality data for 10 pollutants collected between January 1999 and December 2008 at a central monitoring location in Atlanta, Georgia to define a collection of multipollutant day types. Next, we conducted an epidemiologic analysis using our categories as a multipollutant metric of ambient air quality and daily counts of emergency department (ED) visits for asthma or wheeze among children aged 5 to 17 as the health endpoint. We estimated rate ratios (RR) for the association of multipollutant day types and pediatric asthma ED visits using a Poisson generalized linear model controlling for long-term, seasonal, and weekday trends and weather.
  
  
  RESULTS
  Using a low pollution day type as the reference level, we found significant associations of increased asthma morbidity in three of nine categories suggesting adverse effects when combinations of primary (CO, NO2, NOX, EC, and OC) and/or secondary (O3, NH4, SO4) pollutants exhibited elevated concentrations (typically, occurring on dry days with low wind speed). On days with only NO3 elevated (which tended to be relatively cool) and on days when only SO2 was elevated (which likely reflected plume touchdowns from coal combustion point sources), estimated associations were modestly positive but confidence intervals included the null.
  
  
  CONCLUSIONS
  We found that ED visits for pediatric asthma in Atlanta were more strongly associated with certain day types defined by multipollutant characteristics than days with low pollution levels; however, findings did not suggest that any specific combinations were more harmful than others. Relative to other health endpoints, asthma exacerbation may be driven more by total ambient pollutant exposure than by composition.
authors.affiliation: Department of Public Health Sciences, College of Medicine, Medical University of South Carolina, 135 Cannon Street, Charleston, SC, 29422, United States. pearcejo@musc.edu.
authors.forename: John L
authors.initials: JL
authors.lastname: Pearce
authors.affiliation: Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, United States. lwaller@emory.edu.
authors.forename: Lance A
authors.initials: LA
authors.lastname: Waller
authors.affiliation: School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA, United States. james.mulholland@ce.gatech.edu.
authors.forename: James A
authors.initials: JA
authors.lastname: Mulholland
authors.affiliation: Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, United States. sebelt@emory.edu.
authors.forename: Stefanie E
authors.initials: SE
authors.lastname: Sarnat
authors.affiliation: Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, United States. mjstric@emory.edu.
authors.forename: Matthew J
authors.initials: MJ
authors.lastname: Strickland
authors.affiliation: Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, United States. howard.chang@emory.edu.
authors.forename: Howard H
authors.initials: HH
authors.lastname: Chang
authors.affiliation: Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, United States. ptolber@emory.edu.
authors.forename: Paige E
authors.initials: PE
authors.lastname: Tolbert
mesh_terms: D000293:Adolescent; D000393:Air Pollutants / Q000009:adverse effects / Q000032:analysis* / Q000145:classification*; D000397:Air Pollution / Q000009:adverse effects* / Q000032:analysis; D001249:Asthma / Q000139:chemically induced* / Q000453:epidemiology; D002648:Child; D004781:Environmental Exposure / Q000009:adverse effects* / Q000032:analysis; D004784:Environmental Monitoring; D005260:Female; D005845:Georgia / Q000453:epidemiology; D015386:Hazardous Substances / Q000009:adverse effects / Q000032:analysis*; D006801:Humans; D016014:Linear Models; D008297:Male; D009017:Morbidity; D052638:Particulate Matter / Q000009:adverse effects / Q000032:analysis*; D012621:Seasons; D013997:Time Factors; D014887:Weather
chemical_list: D000393:Air Pollutants; D015386:Hazardous Substances; D052638:Particulate Matter