Development and Validation of a Cumulative Exposure Shoulder Risk Assessment Tool Based on Fatigue Failure Theory
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2021/01/01
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Description:Objective: To present a new risk assessment tool for shoulder intensive occupational tasks based on fatigue failure theory. Methods: The tool estimates cumulative damage (CD) based on shoulder moments and loading cycles using an S-N curve derived from in vitro tendon fatigue failure tests. If multiple shoulder tasks are performed, the CD for each is summed. In the validation, 293 workers were evaluated for five separate shoulder outcomes. Logistic regression was used to assess the log CD against five shoulder outcomes adjusted for covariates including age, sex, body mass index (BMI), and plant site. Results: Both crude and adjusted logistic regression results demonstrated strong dose-response associations between the log CD measure and all five shoulder outcomes (continuous ORs ranged from 2.12 to 5.20). Conclusions: The CD measure of The Shoulder Tool demonstrated dose-response relationships with multiple health outcomes. This provides further support that MSDs may be the result of a fatigue failure process. Practitioner summary: This study presents a new, easy-to-use risk assessment tool for occupational tasks involving stressful shoulder exertions. The tool is based on fatigue failure theory. The tool was tested against an existing epidemiology study and demonstrated strong relationships to multiple shoulder outcomes. [Description provided by NIOSH]
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ISSN:0014-0139
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Pages in Document:39-54
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Volume:64
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Issue:1
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NIOSHTIC Number:nn:20062574
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Citation:Ergonomics 2021 Jan; 64(1):39-54
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Contact Point Address:Sean Gallagher, Department of Industrial and Systems Engineering, Auburn University, 3304 Shelby Center, Auburn, AL 36849, USA
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Email:seangallagher@auburn.edu
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Federal Fiscal Year:2021
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Performing Organization:University of Alabama at Birmingham
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Peer Reviewed:True
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Start Date:20050701
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Source Full Name:Ergonomics
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End Date:20270630
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Main Document Checksum:urn:sha-512:543fac33ad2c03f642e63440d09024c2f9fd94809778847385d8b24ea21f2c4b811adcdd9174ba32b5c05f7210f75ecb58f461bdab92df9772586aef410387e0
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