Does More Accurate Exposure Prediction Necessarily Improve Health Effect Estimates?

Details

• Personal Author:
  Paciorek CJ ; Sheppard L ; Szpiro AA
• Description:
  A unique challenge in air pollution cohort studies and similar applications in environmental epidemiology is that exposure is not measured directly at subjects' locations. Instead, pollution data from monitoring stations at some distance from the study subjects are used to predict exposures, and these predicted exposures are used to estimate the health effect parameter of interest. It is usually assumed that minimizing the error in predicting the true exposure will improve health effect estimation. We show in a simulation study that this is not always the case. We interpret our results in light of recently developed statistical theory for measurement error, and we discuss implications for the design and analysis of epidemiologic research. [Description provided by NIOSH]
• Subjects:
  Air Pollution Cohort Studies Environmental Exposure Epidemiology Occupational Health Safety
• Keywords:
  Air Pollution Cohort Studies Exposure Levels Health Effects Statistical Quality Control
• ISSN:
  1044-3983
• Document Type:
  Text
• Funding:
  Grant
• Genre:
  Journal Article
• Place as Subject:
  California ; Massachusetts ; OSHA Region 1 ; OSHA Region 10 ; OSHA Region 9 ; Washington
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Volume:
  22
• Issue:
  5
• NIOSHTIC Number:
  nn:20054750
• Citation:
  Epidemiology 2011 Sep; 22(5):680-685
• Contact Point Address:
  Adam A. Szpiro, Department of Biostatistics, University of Washington, Seattle, WA 98195
• Email:
  aszpiro@u.washington.edu
• Federal Fiscal Year:
  2011
• Performing Organization:
  University of Washington
• Peer Reviewed:
  True
• Start Date:
  20050701
• Source Full Name:
  Epidemiology
• End Date:
  20250630
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:46ed0950cf7d0f7cb5876f71b623146b07b778a4e18f4620cdf5247a48d964292f6394fd8df1e8aa0b493069b45b4cabed7989c41ad051f8c05403acfa117158
• Download URL:
  https://stacks.cdc.gov/view/cdc/217186/cdc_217186_DS1.pdf
• File Type:
  [PDF - 396.56 KB ]