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Using observation and self-report to predict mean, 90th percentile, and cumulative low back muscle activity in heavy industry workers
Högskolan i Gävle, Akademin för hälsa och arbetsliv, Avdelningen för arbets- och folkhälsovetenskap, CBF. Högskolan i Gävle, Centrum för belastningsskadeforskning. 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 (Engelska)Ingår i: Annals of Occupational Hygiene, ISSN 0003-4878, E-ISSN 1475-3162, Vol. 54, nr 5, s. 595-606Artikel i tidskrift (Refereegranskat) 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.

Ort, förlag, år, upplaga, sidor
2010. Vol. 54, nr 5, s. 595-606
Nyckelord [en]
determinants of exposure, ergonomics, exposure assessment, exposure prediction, low back disorders, observation, self-report
Nationell ämneskategori
Arbetsmedicin och miljömedicin
Identifikatorer
URN: urn:nbn:se:hig:diva-7331DOI: 10.1093/annhyg/meq011ISI: 000280415100011PubMedID: 20413415Scopus ID: 2-s2.0-84929469265OAI: oai:DiVA.org:hig-7331DiVA, id: diva2:343234
Tillgänglig från: 2010-08-12 Skapad: 2010-08-12 Senast uppdaterad: 2020-12-31Bibliografiskt granskad

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Trask, Catherine

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