Performance of two general job-exposure matrices in a study of lung cancer morbidity in the Zutphen cohort

Am J Epidemiol. 1992 Sep 15;136(6):698-711. doi: 10.1093/oxfordjournals.aje.a116549.

Abstract

Data from a general population cohort of 878 men from the town of Zutphen, The Netherlands, were used to evaluate the performance of two general job-exposure matrices. Exposures generated by the job-exposure matrices on the basis of job histories were compared. The validity of those exposures was measured against exposures reported by the participants in 1977/1978. The performance of the different exposure measures was assessed in proportional hazards analyses of lung cancer morbidity incidence. The two general job-exposure matrices generally disagreed with regard to exposure classification because of differences in exposure assessment and level of detail of the job axis. When compared with self-reported exposures, the sensitivity of both job-exposure matrices was low (on average, below 0.51), while the specificity was generally high (on average, above 0.90). Self-reported exposures to asbestos, pesticides, and welding fumes showed elevated risk ratios for lung cancer which were absent for exposures generated by the two job-exposure matrices. Thus, a population-specific job-exposure matrix is proposed as an alternative to general job-exposure matrices developed elsewhere. Such a matrix can be constructed from the results of in-depth interviews of a job-stratified sample of cohort members. Sound validation and documentation of exposure assessment methods used in job-exposure matrices are recommended.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Confidence Intervals
  • Data Collection
  • Humans
  • Longitudinal Studies
  • Lung Neoplasms / epidemiology*
  • Lung Neoplasms / mortality
  • Male
  • Morbidity
  • Netherlands
  • Occupational Diseases / chemically induced
  • Occupational Diseases / epidemiology*
  • Occupational Exposure / statistics & numerical data*
  • Proportional Hazards Models
  • Risk Factors
  • Sensitivity and Specificity
  • Survival Analysis