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Using observation and self-report to predict mean, 90th percentile, and cumulative low back muscle activity in heavy industry workers
University of Gävle, Faculty of Health and Occupational Studies, Department of Occupational and Public Health Sciences, CBF. University of Gävle, Centre for Musculoskeletal Research. University of British Columbia School of Environmental Health, Vancouver, BC, Canada.
University of British Columbia School of Population and Public Health, Vancouver, Canada .
Simon Fraser University School of Kinesiology, Burnaby, Canada.
University of British Columbia School of Environmental Health, Vancouver, Canada.
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2010 (English)In: Annals of Occupational Hygiene, ISSN 0003-4878, E-ISSN 1475-3162, Vol. 54, no 5, p. 595-606Article in journal (Refereed) Published
Abstract [en]

Occupational injury research depends on the ability to accurately assess workplace exposures for large numbers of workers. This study used mixed modeling to identify observed and self-reported predictors of mean, 90th percentile, and cumulative low back muscle activity to help researchers efficiently assess physical exposures in epidemiological studies. Full-shift low back electromyography (EMG) was measured for 133 worker-days in heavy industry. Additionally, full-shift, 1-min interval work-sampling observations and post-shift interviews assessed exposure to work tasks, trunk postures, and manual materials handling. Data were also collected on demographic and job variables. Regression models using observed variables predicted 31-47% of the variability in the EMG activity measures, while self-reported variables predicted 21-36%. Observation-based models performed better than self-report-based models and may provide an alternative to direct measurement of back injury risk factors.

Place, publisher, year, edition, pages
2010. Vol. 54, no 5, p. 595-606
Keywords [en]
determinants of exposure, ergonomics, exposure assessment, exposure prediction, low back disorders, observation, self-report
National Category
Occupational Health and Environmental Health
Identifiers
URN: urn:nbn:se:hig:diva-7331DOI: 10.1093/annhyg/meq011ISI: 000280415100011PubMedID: 20413415Scopus ID: 2-s2.0-84929469265ISBN: 1475-3162 (Electronic) 0003-4878 (Linking) (print)OAI: oai:DiVA.org:hig-7331DiVA, id: diva2:343234
Available from: 2010-08-12 Created: 2010-08-12 Last updated: 2018-03-13Bibliographically approved

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Trask, Catherine

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CiteExportLink to record
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  • apa
  • harvard-cite-them-right
  • ieee
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  • sv-SE
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