Validation of an Asbestos Job-Exposure Matrix (AsbJEM) in Australia: Exposure–Response Relationships for Malignant Mesothelioma

Author:

Kamiya Hiroyuki1,Peters Susan12,Sodhi-Berry Nita1,Reid Alison3,Gordon Len4,de Klerk Nicholas15,Brims Fraser16,Musk Arthur W17,Franklin Peter1

Affiliation:

1. School of Population and Global Health, University of Western Australia, Perth, Western Australia, Australia

2. Environmental Epidemiology Division, Institute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands

3. School of Public Health, Curtin University, Perth, Western Australia, Australia

4. Caltex Australia, Perth, Western Australia, Australia

5. Telethon Kids Institute, University of Western Australia, Perth, Western Australia, Australia

6. Curtin Medical School, Curtin University, Perth, Western Australia, Australia

7. Department of Respiratory Medicine, Sir Charles Gairdner Hospital, Perth, Western Australia, Australia

Abstract

Abstract Objectives An asbestos job-exposure matrix (AsbJEM) has been developed to systematically and cost-effectively evaluate occupational exposures in population-based studies. The primary aim of this study was to examine the accuracy of the AsbJEM in determining exposure–response relationships between asbestos exposure estimates and malignant mesothelioma (MM) incidence (indirect validation). The secondary aim was to investigate whether the assumptions used in the development of the original AsbJEM provided accurate asbestos exposure estimates. Methods The study population consisted of participants in an annual health surveillance program, who had at least 3-month occupational asbestos exposure. Calculated asbestos exposure indices included cumulative asbestos exposure and the average exposure intensity, estimated using the AsbJEM and duration of employment. Asbestos and MM exposure–response relationships were compared between the original AsbJEM and its variations based on manipulations of the intensity, duration and frequency of exposure. Twenty-four exposure estimates were calculated for both cumulative asbestos exposure and the average exposure intensity using three exposure intensities (50th, 75th and 90th percentile of the range of mode exposure), four peak durations (15, 30, 60 and 120 min) and two patterns of peak frequency (original and doubled). Cox proportional hazards models were used to describe the associations between MM incidence and each of the cumulative and average intensity estimates. Results Data were collected from 1602 male participants. Of these, 40 developed MM during the study period. There were significant associations between MM incidence and both cumulative and average exposure intensity for all estimates. The strongest association, based on the regression-coefficient from the models, was found for the 50th percentile of mode exposure, 15-min peak duration and the doubled frequency of peak exposure. Using these assumptions, the hazard ratios for mesothelioma were 1 (reference), 1.91, 3.24 and 5.37 for the quartiles of cumulative asbestos exposure and 1 (reference), 1.84, 2.31 and 4.40 for the quartiles of the average exposure intensity, respectively. Conclusion The well-known positive exposure–response relationship between MM incidence and both estimated cumulative asbestos exposure and average exposure intensity was confirmed. The strongest relationship was found when the frequency of peak exposure in the AsbJEM was doubled from the originally published estimates.

Funder

Dust Diseases Board

Western Australia Department of Health

Publisher

Oxford University Press (OUP)

Subject

Public Health, Environmental and Occupational Health

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