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A method of identifying health-based benchmarks for psychosocial risks at work: A tool for risk assessment

Authors :
Lyndall Strazdins
Mark Clements
Lou Gallagher
Su Mon Kyaw-Myint
Peter Butterworth
Source :
Safety Science. 93:143-151
Publication Year :
2017
Publisher :
Elsevier BV, 2017.

Abstract

Objectives We present a novel approach to identify critical exposure levels or health-based benchmarks of job control using the benchmark dose (BMD) method. This method provides benchmarks for risk assessment of psychosocial risks, similar to benchmarks used for other occupational health hazards such as chemicals. Methods Two staged (bivariate and adjusted) BMD modelling was conducted using epidemiological data from an age-cohort study in south-eastern Australia. The adjusted BMD model incorporated age, gender, education, personality traits and mental health status at baseline. Results Depression is a more sensitive (health compromising) outcome for job control compared to anxiety in both types of BMD modelling. For an excess risk of 5% for depression, the adjusted benchmark dose was 0.49 and the critical exposure level, being the lower one sided 95% confidence limit of the adjusted BMD, was 0.37. If workplace guidelines are based on this critical exposure level, workers need to have a minimum of ten out of 15 aspects of job control measured in this study to reduce the excess risk of depression. Conclusions The BMD approach can identify critical exposure levels for job control. This suggests a similar approach can be used for other psychosocial risks for which no critical exposure levels are currently available. Critical exposure levels can provide guidance needed to assess risk and address psychosocial risks, similar to other health hazards. Benchmarks or critical exposure levels of psychosocial risks can assist the inspectorate and employers to conduct risk assessment of workplaces and identify areas for intervention.

Details

ISSN :
09257535
Volume :
93
Database :
OpenAIRE
Journal :
Safety Science
Accession number :
edsair.doi...........f0d1ccf4195387bf955a29a7e91844ce
Full Text :
https://doi.org/10.1016/j.ssci.2016.11.016