title: Health effects of multi-pollutant profiles.
abstract: BACKGROUND
  The association between exposure to particle mass and mortality is well established; however, there are still uncertainties as to whether certain chemical components are more harmful than others. Moreover, understanding the health effects associated with exposure to pollutant mixtures may lead to new regulatory strategies.
  
  
  OBJECTIVE
  Recently we have introduced a new approach that uses cluster analysis to identify distinct air pollutant mixtures by classifying days into groups based on their pollutant concentration profiles. In Boston during the years 1999-2009, we examined whether the effect of PM2.5 on total mortality differed by distinct pollution mixtures.
  
  
  METHODS
  We applied a time series analysis to examine the association of PM2.5 with daily deaths. Subsequently, we included an interaction term between PM2.5 and the pollution mixture clusters.
  
  
  RESULTS
  We found a 1.1% increase (95% CI: 0.0, 2.2) and 2.3% increase (95% CI: 0.9-3.7) in total mortality for a 10 μg/m(3) increase in the same day and the two-day average of PM2.5 respectively. The association is larger in a cluster characterized by high concentrations of the elements related to primary traffic pollution and oil combustion emissions with a 3.7% increase (95% CI: 0.4, 7.1) in total mortality, per 10 μg/m(3) increase in the same day average of PM2.5.
  
  
  CONCLUSIONS
  Our study shows a higher association of PM2.5 on total mortality during days with a strong contribution of traffic emissions, and fuel oil combustion. Our proposed method to create multi-pollutant profiles is robust, and provides a promising tool to identify multi-pollutant mixtures which can be linked to the health effects.
authors.affiliation: Department of Environmental Health, Harvard School of Public Health, Boston, United States. Electronic address: azanobet@hsph.harvard.edu.
authors.forename: Antonella
authors.initials: A
authors.lastname: Zanobetti
authors.affiliation: Department of Environmental Health, Harvard School of Public Health, Boston, United States.
authors.forename: Elena
authors.initials: E
authors.lastname: Austin
authors.affiliation: Department of Biostatistics, Harvard School of Public Health, Boston, United States.
authors.forename: Brent A
authors.initials: BA
authors.lastname: Coull
authors.affiliation: Department of Environmental Health, Harvard School of Public Health, Boston, United States.
authors.forename: Joel
authors.initials: J
authors.lastname: Schwartz
authors.affiliation: Department of Environmental Health, Harvard School of Public Health, Boston, United States.
authors.forename: Petros
authors.initials: P
authors.lastname: Koutrakis
mesh_terms: D000397:Air Pollution / Q000032:analysis*; D001900:Boston / Q000453:epidemiology; D016000:Cluster Analysis; D004781:Environmental Exposure; D004784:Environmental Monitoring / Q000379:methods / Q000706:statistics & numerical data*; D006801:Humans; D009026:Mortality / Q000639:trends*; D052638:Particulate Matter / Q000032:analysis*; D013997:Time Factors; D001335:Vehicle Emissions / Q000032:analysis
chemical_list: D052638:Particulate Matter; D001335:Vehicle Emissions
keywords: Fine particulate air pollution; Pollutant mixtures; Total mortality