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A Quantitative General Population Job Exposure Matrix for Occupational Noise Exposure
Author(s) -
Zara Ann Stokholm,
Mogens Erlandsen,
Vivi Schlünssen,
Ioannis Basinas,
Jens Peter Bonde,
Susan Peters,
Jens Brandt,
Jesper Medom Vestergaard,
Henrik Albert Kolstad
Publication year - 2020
Publication title -
annals of work exposures and health
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.62
H-Index - 77
eISSN - 2398-7316
pISSN - 2398-7308
DOI - 10.1093/annweh/wxaa034
Subject(s) - job exposure matrix , noise (video) , noise exposure , danish , population , variance (accounting) , occupational safety and health , environmental health , medicine , hearing loss , linear regression , statistics , demography , audiology , mathematics , business , computer science , linguistics , philosophy , accounting , pathology , artificial intelligence , sociology , image (mathematics)
Occupational noise exposure is a known risk factor for hearing loss and also adverse cardiovascular effects have been suggested. A job exposure matrix (JEM) would enable studies of noise and health on a large scale. The objective of this study was to create a quantitative JEM for occupational noise exposure assessment of the general working population. Between 2001–2003 and 2009–2010, we recruited workers from companies within the 10 industries with the highest reporting of noise-induced hearing loss according to the Danish Working Environment Authority and in addition workers of financial services and children day care to optimize the range in exposure levels. We obtained 1343 personal occupational noise dosimeter measurements among 1140 workers representing 100 different jobs according to the Danish version of the International Standard Classification of Occupations 1988 (DISCO 88). Four experts used 35 of these jobs as benchmarks and rated noise levels for the remaining 337 jobs within DISCO 88. To estimate noise levels for all 372 jobs, we included expert ratings together with sex, age, occupational class, and calendar year as fixed effects, while job and worker were included as random effects in a linear mixed regression model. The fixed effects explained 40% of the total variance: 72% of the between-jobs variance, −6% of the between-workers variance and 4% of the within-worker variance. Modelled noise levels showed a monotonic increase with increasing expert score and a 20 dB difference between the highest and lowest exposed jobs. Based on the JEM estimates, metal wheel-grinders were among the highest and finance and sales professionals among the lowest exposed. This JEM of occupational noise exposure can be used to prioritize preventive efforts of occupational noise exposure and to provide quantitative estimates of contemporary exposure levels in epidemiological studies of health effects potentially associated with noise exposure.

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