Literature DB >> 27030203

Impact of aggregating exposure information from cases and controls when building a population-based job-exposure matrix from past expert evaluations.

Tracy L Kirkham1, Jack Siemiatycki1, France Labrèche2, Jérôme Lavoué3.   

Abstract

OBJECTIVES: To assess whether the inclusion of data from cases would bias a job-exposure matrix (JEM), we evaluated whether exposures were systematically different between cases and controls from a large historical case-control study.
METHODS: Data included 10 381 jobs assessed for occupational exposure to 294 agents within a lung cancer case-control study. For each sex, 1 JEM was developed from case jobs, and 1 from control jobs: with occupation (four-digit occupational codes), time period (1945-1959, 1960-1984, 1985-1995) and agent axes. We estimated concordance in exposure status (defined as probability of exposure threshold ≥5%) and exposure metrics of probability and intensity of exposure, between the 2 JEMs.
RESULTS: Of all hypothetical occupation-period-agent combinations, most had no or few observations. Among males there were 8136 common cells (24-occupational codes, 3-periods, 226-agents), containing sufficient observations for comparison with 92% concordance in exposure status; discordance was equally likely to be towards cases or controls. Females had 1710 common cells (9-occupational codes, 3-periods, 114-agents) with 93% concordance in exposure status; discordant cells were more likely to reflect greater exposure among cases. Among concordantly exposed cells, probability and intensity of exposures were highly correlated between the case JEM and control JEM (Kendall τ>0.50), and absolute differences were small (median difference in probability <1.5%, median ratio in intensity=1.00) for both sexes.
CONCLUSIONS: Agreement between the case JEM and control JEM was high, suggesting that aggregating the case and control information in our study into a single JEM is justifiable given the benefits of increased sample size. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Entities:  

Keywords:  Case-control studies; Epidemiologic methods; Occupational health

Mesh:

Year:  2016        PMID: 27030203     DOI: 10.1136/oemed-2014-102690

Source DB:  PubMed          Journal:  Occup Environ Med        ISSN: 1351-0711            Impact factor:   4.402


  4 in total

1.  Development of and Selected Performance Characteristics of CANJEM, a General Population Job-Exposure Matrix Based on Past Expert Assessments of Exposure.

Authors:  Jean-François Sauvé; Jack Siemiatycki; France Labrèche; Lesley Richardson; Javier Pintos; Marie-Pierre Sylvestre; Michel Gérin; Denis Bégin; Aude Lacourt; Tracy L Kirkham; Thomas Rémen; Romain Pasquet; Mark S Goldberg; Marie-Claude Rousseau; Marie-Élise Parent; Jérôme Lavoué
Journal:  Ann Work Expo Health       Date:  2018-08-13       Impact factor: 2.179

2.  Development of a Coding and Crosswalk Tool for Occupations and Industries.

Authors:  Thomas Rémen; Lesley Richardson; Corinne Pilorget; Gilles Palmer; Jack Siemiatycki; Jérôme Lavoué
Journal:  Ann Work Expo Health       Date:  2018-08-13       Impact factor: 2.179

3.  Development of a Job-Exposure Matrix for Assessment of Occupational Exposure to High-Frequency Electromagnetic Fields (3 kHz-300 GHz).

Authors:  Lucile Migault; Joseph D Bowman; Hans Kromhout; Jordi Figuerola; Isabelle Baldi; Ghislaine Bouvier; Michelle C Turner; Elisabeth Cardis; Javier Vila
Journal:  Ann Work Expo Health       Date:  2019-11-13       Impact factor: 2.179

4.  Agreement in Occupational Exposures Between Men and Women Using Retrospective Assessments by Expert Coders.

Authors:  Aude Lacourt; France Labrèche; Mark S Goldberg; Jack Siemiatycki; Jérôme Lavoué
Journal:  Ann Work Expo Health       Date:  2018-11-12       Impact factor: 2.179

  4 in total

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