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O38-6 A general population job exposure matrix for occupational noise
  1. Zara Ann Stokholm1,
  2. Mogens Erlansen2,
  3. Vivi Schünssen3,
  4. Ioannis Basinas4,
  5. Jens Peter Bonde5,
  6. Jens Brandt6,
  7. Jesper Medom Vestergaard1,
  8. Henrik Kolstad1
  1. 1Department of Occupational Medicine, Danish Ramazzini Centre, Aarhus University Hospital, Aarhus, Denmark
  2. 2Section for Biostatistics, Department of Public Health, Aarhus University, Aarhus, Denmark
  3. 3Section for Environment, Occupation and Health, Danish Ramazzini Centre, Department of Public Health, Aarhus University, Aarhus, Denmark
  4. 4Institute of Occupational Medicine, Edinburgh, Denmark
  5. 5Department of Occupational and Environmental Medicine, Bispebjerg University Hospital, Copenhagen, Denmark
  6. 6CRECEA, Aarhus, Denmark

Abstract

Aims The aim of this ongoing study is to create a quantitative job exposure matrix (JEM) for occupational noise exposure assessment of the general working population combining personal noise exposure measurements with expert ratings.

Methods Between 2001and 2010 we recruited 1140 workers from manufacturing industries with high reporting of noise induced hearing loss: manufacturers of food, wood products, non-metallic mineral products, basic metals, fabricated metal, machinery, motor vehicles, furniture, publishing and printing, and construction together with workers of financial services and children day care for optimising the exposure contrast. All wore a personal dosimeter during the full shift and 1357 noise exposure measurements were obtained. We examined variance components and contrasts by linear mixed effect models for different grouping strategies of occupation and industry. An extended model is under elaboration that includes all 373 occupations on a 4-digit level of the Danish version of the International Standard Classification of Occupations (ISCO-88). Worker-id is included as a random effect together with calendar year of measurement, sampling duration (minutes), and expert ratings of average full-shift noise exposure levels for each occupational title as fixed effects. Expert ratings (non-exposed, exposed and high exposed) will be obtained independently from 5 specialists in occupational hygiene and medicine.

Results Grouping by occupation provided higher contrast (0.83) than grouping by industry (0.63), and therefore occupation was chosen for the development of the JEM. Preliminary results show a 10 year decline in occupational noise exposure between 2001–2010 for blue-collar industrial workers. Occupational noise exposure in financial services and children day care remained unchanged.

Discussion The resulting model will enable us to assess occupation and calendar year specific exposure levels of occupational noise in community-based epidemiological studies.

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