Journal
HUMAN FACTORS
Volume 56, Issue 1, Pages 6-28Publisher
SAGE PUBLICATIONS INC
DOI: 10.1177/0018720813486669
Keywords
epidemiology; ergonomics; occupational cohort; job analysis; risk assessment
Funding
- National Institute for Occupational Safety and Health (NIOSH/CDC) [1 U 01 OH008083-01]
- NIOSH Education and Research Center training grant [T42/CCT810426-10]
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Objective: The aim of this study was to evaluate relationships between the revised NIOSH lifting equation (RNLE) and risk of low-back pain (LBP). Background: The RNLE is commonly used to quantify job physical stressors to the low back from lifting and/or lowering of loads. There is no prospective study on the relationship between RNLE and LBP that includes accounting for relevant covariates. Method: A cohort of 258 incident-eligible workers from 30 diverse facilities was followed for up to 4.5 years. Job physical exposures were individually measured. Worker demographics, medical history, psychosocial factors, hobbies, and current LBP were obtained at baseline. The cohort was followed monthly to ascertain development of LBP and quarterly to determine changes in job physical exposure. The relationship between LBP and peak lifting index (PLI) and peak composite lifting index (PCLI) were tested in multivariate models using proportional hazards regression. Results: Point and lifetime prevalences of LBP at baseline were 7.1% and 75.1%, respectively. During follow-up, there were 123 incident LBP cases. Factors predicting development of LBP included job physical exposure (PLI and PCLI), history of LBP, psychosocial factors, and housework. In adjusted models, risk (hazard ratio [HR]) increased per-unit increase in PLI and PCLI (p = .05 and .02; maximum HR = 4.3 and 4.2, respectively). PLI suggested a continuous increase in risk with an increase in PLI, whereas the PCLI showed elevated, but somewhat reduced, risk at higher exposures. Conclusion: Job physical stressors are associated with increased risk of LBP. Data suggest that the PLI and PCLI are useful metrics for estimating exposure to job physical stressors.
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