Adjustment for Temporal Confounders in a Reanalysis of a Case-Control Study of Beryllium and Lung Cancer

Details

• Personal Author:
  Deddens JA ; Petersen, Martin R. ; Sanderson, Wayne T. ; Schubauer-Berigan, Mary K. ; Steenland, Kyle
• Description:
  OBJECTIVES: To evaluate potential confounding of the association between beryllium and lung cancer in a reanalysis of data from a published case-control study of workers at a beryllium processing facility. METHODS: The association of cumulative and average beryllium exposure with lung cancer among 142 cases and five age-match controls per case was reanalyzed using conditional logistic regression. Adjustment was made independently for potential confounders of hire age and birth year. Alternative adjustments to avoid taking the logarithm of zero were explored. RESULTS: Adjustment for either birth cohort or hire age (two highly correlated factors) attenuated lung cancer risk associated with cumulative exposure; however, lung cancer risk was significantly associated with average exposure using a 10-year lag following adjustment. Stratification of analyses by birth cohort found greater lung cancer risk from cumulative and average exposure for workers born before 1900 than for workers born later. The magnitude of the association between lung cancer and average exposure was not reduced by modifying the method used to take the log of exposure. CONCLUSION: In this reanalysis, average-but not cumulative-beryllium exposure was related to lung cancer risk after adjustment for birth cohort. Confounding by birth cohort is likely related to differences in smoking patterns for workers born before 1900 and the tendency for workers hired during the World War II era to have been older at hire. [Description provided by NIOSH]
• Subjects:
  Age Factors Lung Lung Diseases Neoplasms Occupational Health Respiratory System Respiratory Tract Diseases Safety
• Keywords:
  Age-factors Analytical-methods Analytical-processes Lung-cancer Lung-cells Lung-disease Lung-disorders Lung-irritants Mathematical-models Statistical-analysis
• ISSN:
  1351-0711
• Document Type:
  Text
• Funding:
  Grant
• Genre:
  Journal Article
• Place as Subject:
  Ohio ; OSHA Region 5
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Division:
  DSHEFS - Division of Surveillance, Hazard Evaluations, and Field Studies
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Pages in Document:
  379-383
• Volume:
  65
• Issue:
  6
• NIOSHTIC Number:
  nn:20032648
• Citation:
  Occup Environ Med 2008 Jun; 65(6):379-383
• Contact Point Address:
  Dr Mary K Schubauer-Berigan, NIOSH, DSHEFS, MS-R15, 4676 Columbia Pkwy, Cincinnati, Ohio 45226, USA
• Email:
  zcg3@cdc.gov
• Federal Fiscal Year:
  2008
• Performing Organization:
  University of Iowa
• Peer Reviewed:
  True
• Start Date:
  20050701
• Source Full Name:
  Occupational and Environmental Medicine
• End Date:
  20290630
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:78f35485f59ec0f7a42a18d641a0035fcd895e280ed8b3ffff486b798a23fef63d0e37d91bbc95d5644d160aa7dd33643b109da7ba98a7eddaac0f9563932b5a
• Download URL:
  https://stacks.cdc.gov/view/cdc/186546/cdc_186546_DS1.pdf
• File Type:
  [PDF - 202.52 KB ]