Source-apportioned PM2.5 and cardiorespiratory emergency department visits: accounting for source contribution uncertainty

Details

• Alternative Title:
  Epidemiology
• Personal Author:
  Pennington, Audrey Flak ; Strickland, Matthew J. ; Gass, Katherine ; Klein, Mitchel ; Sarnat, Stefanie Ebelt ; Tolbert, Paige E. ; Balachandran, Sivaraman ; Chang, Howard H. ; Russell, Armistead G. ; Mulholland, James A. ; Darrow, Lyndsey A.
• Description:
  Background:
  
  Despite evidence suggesting that air pollution-related health effects differ by emissions source, epidemiologic studies on fine particulate matter (PM2.5) infrequently differentiate between particles from different sources. Those that do rarely account for the uncertainty of source apportionment methods.
  
  Methods:
  
  For each day in a 12-year period (1998 to 2010) in Atlanta, GA, we estimated daily PM2.5 source contributions from a Bayesian ensemble model that combined four source apportionment methods including chemical transport and receptor-based models. We fit Poisson generalized linear models to estimate associations between source-specific PM2.5 concentrations and cardiorespiratory emergency department visits (n=1,598,117). We propagated uncertainty in the source contribution estimates through analyses using multiple imputation.
  
  Results:
  
  Respiratory emergency department visits were positively associated with biomass burning and secondary organic carbon. For a 1 μg/m3 increase in PM2.5 from biomass burning during the past 3 days, the rate of visits for all respiratory outcomes increased by 0.4% (95% CI 0.0%, 0.7%). There was less evidence for associations between PM2.5 sources and cardiovascular outcomes, with the exception of ischemic stroke, which was positively associated with most PM2.5 sources. Accounting for the uncertainty of source apportionment estimates resulted, on average, in an 18% increase in the standard error for rate ratio estimates for all respiratory and cardiovascular emergency department visits, but inflation varied across specific sources and outcomes, ranging from 2% to 39%.
  
  Conclusions:
  
  This study provides evidence of associations between PM2.5 sources and some cardiorespiratory outcomes and quantifies the impact of accounting for variability in source apportionment approaches.
  
  
• Subjects:
  Air Pollution Arrhythmias, Cardiac Asthma Bayes Theorem Biomass Brain Ischemia Cardiovascular Diseases Coal Dust Emergency Service, Hospital Heart Failure Humans Linear Models Myocardial Ischemia Particulate Matter Pneumonia Pulmonary Disease, Chronic Obstructive Respiratory Tract Diseases Respiratory Tract Infections Stroke Vehicle Emissions

  More +
• Source:
  Epidemiology. 30(6):789-798
• Pubmed ID:
  31469699
• Pubmed Central ID:
  PMC6768727
• Document Type:
  Journal Article
• Funding:
  R21 ES022795/ES/NIEHS NIH HHS/United States ; T03 OH008609/OH/NIOSH CDC HHS/United States ; T03OH008609/ACL/ACL HHS/United States
• Place as Subject:
  Georgia
• Volume:
  30
• Issue:
  6
• Collection(s):
  CDC Public Access
• Main Document Checksum:
  urn:sha256:6ba4a4cc49851fd1bd5bc80d8dd4ca457764693c93e2c9311479fc81e8e8d0cf
• Download URL:
  https://stacks.cdc.gov/view/cdc/96111/cdc_96111_DS1.pdf
• File Type:
  [PDF - 584.78 KB ]