Non-chemical Risk Assessment for Lifting and Low Back Pain Based on Bayesian Threshold Models.
10.1016/j.shaw.2016.10.001
- Author:
Sudha P PANDALAI
1
;
Matthew W WHEELER
;
Ming Lun LU
Author Information
1. Education and Information Division, Risk Evaluation Branch, National Institute for Occupational Safety and Health, Cincinnati, OH, USA. SPandalai@cdc.gov
- Publication Type:Original Article
- Keywords:
Bayes theorem;
musculoskeletal diseases;
occupational exposure;
risk assessment
- MeSH:
Bayes Theorem;
Benchmarking;
Lifting*;
Low Back Pain*;
Musculoskeletal Diseases;
National Institute for Occupational Safety and Health (U.S.);
Occupational Exposure;
Prospective Studies;
Risk Assessment*
- From:Safety and Health at Work
2017;8(2):206-211
- CountryRepublic of Korea
- Language:English
-
Abstract:
BACKGROUND: Self-reported low back pain (LBP) has been evaluated in relation to material handling lifting tasks, but little research has focused on relating quantifiable stressors to LBP at the individual level. The National Institute for Occupational Safety and Health (NIOSH) Composite Lifting Index (CLI) has been used to quantify stressors for lifting tasks. A chemical exposure can be readily used as an exposure metric or stressor for chemical risk assessment (RA). Defining and quantifying lifting nonchemical stressors and related adverse responses is more difficult. Stressor–response models appropriate for CLI and LBP associations do not easily fit in common chemical RA modeling techniques (e.g., Benchmark Dose methods), so different approaches were tried. METHODS: This work used prospective data from 138 manufacturing workers to consider the linkage of the occupational stressor of material lifting to LBP. The final model used a Bayesian random threshold approach to estimate the probability of an increase in LBP as a threshold step function. RESULTS: Using maximal and mean CLI values, a significant increase in the probability of LBP for values above 1.5 was found. CONCLUSION: A risk of LBP associated with CLI values > 1.5 existed in this worker population. The relevance for other populations requires further study.
