Accounting for Uncertainty in Systematic Bias in Exposure Estimates Used in Relative Risk Regression

Details

• Personal Author:
  Gilbert ES ; Gilbert ES
• Description:
  Techniques for addressing systematic biases in exposure estimates used for establishing exposure response relationships in epidemiologic studies were developed. The aim was to have strategies to deal with uncertainties associated with constructing dose response estimates for nuclear workers exposed to external ionizing radiation in studies examining the carcinogenic risk of exposure to ionizing radiation. Two approaches based on constructing 90 and 95% confidence intervals (CIs) for uncertainties in the dose estimates were used. The first approach used numerical methods based on the likelihood ratio statistic to compute the CIs. The second approach utilized computer simulations based on the likelihood ratio statistic to compute the CIs. Both approaches were applied to data obtained in a cohort study of leukemia in workers employed at the Hanford laboratory, Washington State, between 1944 and 1980, to a combined dataset of workers at the Hanford site, Oak Ridge National Laboratory, and the Rocky Flats weapons plant, and to simulated data sets created to examine the effects of variations in population size and exposure estimates on the risk estimates. When applied to the occupational data, both methods indicated that sampling errors accounted for most of the uncertainty in the risk estimates. Accounting for statistical biases, however, did not significantly alter the CIs for the estimates. In the simulated dataset, the CIs increased as the number of subjects with exposure data increased. The author concludes that accounting for statistical bias is very important when analyzing exposure response data obtained from a large population of workers. [Description provided by NIOSH]
• Subjects:
  Epidemiology Laboratories Neoplasms Occupational Health Radiation Radiation Dosimeters Risk Assessment Safety
• Keywords:
  Dose-response Dosimetry Grants-other Ionizing-radiation Laboratory-workers Malignant-neoplasms Mathematical-models NIOSH-Grant Radiation-exposure Risk-analysis Statistical-analysis

  More +
• Series:
  Grant Final Reports   ; Grant Final Reports  
• Publisher:
  National Institute for Occupational Safety and Health
• Document Type:
  Text
• Funding:
  Grant
• Genre:
  Final Grant Report ; Final Grant Report
• Place as Subject:
  OSHA Region 10 ; Washington
• CIO:
  National Institute for Occupational Safety and Health (NIOSH) ; National Institute for Occupational Safety and Health (NIOSH)
• Division:
  OEP - Office of Extramural Programs ; OEP - Office of Extramural Programs
• Topic:
  Workplace Safety & Health ; Workplace Safety & Health
• Location:
  North America ; North America
• Pages in Document:
  1-24
• NIOSHTIC Number:
  nn:00241825
• NTIS Accession Number:
  DE96-004128
• Citation:
  Atlanta, GA: U.S. Department of Health and Human Services, Public Health Service, Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health, R01-OH-003270, 1995 Dec; :1-21
• Contact Point Address:
  Health Risk Assessment Dept Battelle Memorial Inst PO Box 999 Msin P7 82 Richland, WA 99352
• Federal Fiscal Year:
  1996
• NORA Priority Area:
  Other Occupational Concerns ; Grants Other ; Other Occupational Concerns ; Grants Other
• Performing Organization:
  Battelle Pacific Northwest Laboratories, Richland, Washington
• Peer Reviewed:
  False
• Start Date:
  19940930
• Source Full Name:
  National Institute for Occupational Safety and Health
• End Date:
  19960929
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:fdc61728dac2b3874dbf52d2cff945d20e0027c472fe6da21c2ce89fc0573b53f07f57bb3b09c32488eb9020f1d853dceec8db94472aa68447004083dee47d19
• Download URL:
  https://stacks.cdc.gov/view/cdc/217951/cdc_217951_DS1.pdf
• File Type:
  [PDF - 1.75 MB ]