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Developing physical exposure-based back injury risk models applicable to manual handling jobs in distribution centers
Steven A Lavender1, William S Marras, Sue A Ferguson
1The Ohio State University, Integrated Systems Engineering, Columbus, OH 43210, USA. lavender.1@osu.edu
Abstract:
Using our ultrasound-based "Moment Monitor," exposures to biomechanical low back disorder risk factors were quantified in 195 volunteers who worked in 50 different distribution center jobs. Low back injury rates, determined from a retrospective examination of each company's Occupational Safety and Health Administration (OSHA) 300 records over the 3-year period immediately prior to data collection, were used to classify each job's back injury risk level. The analyses focused on the factors differentiating the high-risk jobs (those having had 12 or more back injuries/200,000 hr of exposure) from the low-risk jobs (those defined as having no back injuries in the preceding 3 years). Univariate analyses indicated that measures of load moment exposure and force application could distinguish between high (n = 15) and low (n = 15) back injury risk distribution center jobs. A three-factor multiple logistic regression model capable of predicting high-risk jobs with very good sensitivity (87%) and specificity (73%) indicated that risk could be assessed using the mean across the sampled lifts of the peak forward and or lateral bending dynamic load moments that occurred during each lift, the mean of the peak push/pull forces across the sampled lifts, and the mean duration of the non-load exposure periods. A surrogate model, one that does not require the Moment Monitor equipment to assess a job's back injury risk, was identified although with some compromise in model sensitivity relative to the original model.
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