title: Current approaches used in epidemiologic studies to examine short-term multipollutant air pollution exposures.
abstract: OBJECTIVE
  Air pollution epidemiology traditionally focuses on the relationship between individual air pollutants and health outcomes (e.g., mortality). To account for potential copollutant confounding, individual pollutant associations are often estimated by adjusting or controlling for other pollutants in the mixture. Recently, the need to characterize the relationship between health outcomes and the larger multipollutant mixture has been emphasized in an attempt to better protect public health and inform more sustainable air quality management decisions.
  
  
  METHODS
  New and innovative statistical methods to examine multipollutant exposures were identified through a broad literature search, with a specific focus on those statistical approaches currently used in epidemiologic studies of short-term exposures to criteria air pollutants (i.e., particulate matter, carbon monoxide, sulfur dioxide, nitrogen dioxide, and ozone).
  
  
  RESULTS
  Five broad classes of statistical approaches were identified for examining associations between short-term multipollutant exposures and health outcomes, specifically additive main effects, effect measure modification, unsupervised dimension reduction, supervised dimension reduction, and nonparametric methods. These approaches are characterized including advantages and limitations in different epidemiologic scenarios.
  
  
  CONCLUSIONS
  By highlighting the characteristics of various studies in which multipollutant statistical methods have been used, this review provides epidemiologists and biostatisticians with a resource to aid in the selection of the most optimal statistical method to use when examining multipollutant exposures.
authors.affiliation: Department of Biostatistics, University of North Carolina, Chapel Hill.
authors.forename: Angel D
authors.initials: AD
authors.lastname: Davalos
authors.affiliation: National Center for Environmental Assessment, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC.
authors.forename: Thomas J
authors.initials: TJ
authors.lastname: Luben
authors.affiliation: Department of Biostatistics, University of North Carolina, Chapel Hill.
authors.forename: Amy H
authors.initials: AH
authors.lastname: Herring
authors.affiliation: National Center for Environmental Assessment, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC. Electronic address: sacks.jason@epa.gov.
authors.forename: Jason D
authors.initials: JD
authors.lastname: Sacks
mesh_terms: D000393:Air Pollutants / Q000032:analysis*; D000397:Air Pollution / Q000032:analysis*; D004781:Environmental Exposure / Q000032:analysis* / Q000706:statistics & numerical data*; D004784:Environmental Monitoring / Q000379:methods*; D016021:Epidemiologic Studies; D006801:Humans; D052638:Particulate Matter / Q000032:analysis*; D012621:Seasons; D013997:Time Factors
chemical_list: D000393:Air Pollutants; D052638:Particulate Matter
keywords: Air pollution health effects; Differential effects; Dimension reduction; Interactions; Joint effects; Multipollutant; Nonparametric methods