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Exposure assessment 2
Combining job exposure matrices and exposure measurements to assess occupational exposure to benzene, lead fume, and lead dust in a population-based cohort in Shanghai, China
  1. Melissa Friesen1,
  2. Dong-Hee Koh1,
  3. Joseph Coble1,
  4. Wei Lu2,
  5. Xiao-Ou Shu3,
  6. Bu-Tian Ji1,
  7. Shouzheng Xue1,
  8. Lutzen Portengen4,
  9. Wong-Ho Chow1,
  10. Yu-Tang Gao5,
  11. Gong Yang3,
  12. Nathaniel Rothman1,
  13. Roel Vermeulen4
  1. 1NCI, Bethesda, USA
  2. 2Shanghai Center for Disease Control, Shanghai, China
  3. 3Vanderbilt University, Nashville, USA
  4. 4Utrecht University, Utrecht, The Netherlands
  5. 5Shanghai Cancer Institute, Shanghai, China

Abstract

Objectives To better discriminate between job, industry, and time differences in exposure levels within a population cohort of 74 942 Shanghai women, we combined job exposure matrix (JEM) ratings with inspection measurements collected between 1954 and 2000.

Methods Mixed-effects models were used to predict concentrations of benzene (n=63 221 measurements), lead fume (n=20 084), and lead dust (n=5383). The fixed effects included JEM intensity ratings (ordinal: 0–3) and year (b-spline). The random effects included job and industry nested within job, which allowed us to calculate job/industry-specific estimates when there was sufficient data. The predicted concentrations were applied to the cohort when either the job or industry JEM probability rating was high (3 on a 0–3 scale).

Results The average exposure levels were 9-12 times higher in 1965 than in 2000 for the three agents. The ranges of the job/industry group exposure concentrations were 2–7 times wider for the job/industry-specific estimates than for the JEM-specific estimates. Using the probability ratings, we estimated that 15% and 8% of the subjects were exposed to benzene and lead, respectively.

Conclusions Our approach calibrated the JEM to a concentration scale across ratings and time and allowed the job/industry groups' exposure levels to deviate from the JEM estimate when there were sufficient measurements. It also provided a mechanism to estimate exposure when a job/industry group was not represented in the exposure database. As a result, our approach accounted for substantial exposure differences across time and between jobs and industries that would not be accounted for using the JEM alone.

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