Cargando…

Non-chemical Risk Assessment for Lifting and Low Back Pain Based on Bayesian Threshold Models

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 Inde...

Descripción completa

Detalles Bibliográficos
Autores principales: Pandalai, Sudha P., Wheeler, Matthew W., Lu, Ming-Lun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Occupational Safety and Health Research Institute 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5447412/
https://www.ncbi.nlm.nih.gov/pubmed/28593078
http://dx.doi.org/10.1016/j.shaw.2016.10.001
_version_ 1783239337784115200
author Pandalai, Sudha P.
Wheeler, Matthew W.
Lu, Ming-Lun
author_facet Pandalai, Sudha P.
Wheeler, Matthew W.
Lu, Ming-Lun
author_sort Pandalai, Sudha P.
collection PubMed
description 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.
format Online
Article
Text
id pubmed-5447412
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher Occupational Safety and Health Research Institute
record_format MEDLINE/PubMed
spelling pubmed-54474122017-06-07 Non-chemical Risk Assessment for Lifting and Low Back Pain Based on Bayesian Threshold Models Pandalai, Sudha P. Wheeler, Matthew W. Lu, Ming-Lun Saf Health Work Original Article 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. Occupational Safety and Health Research Institute 2017-06 2016-11-09 /pmc/articles/PMC5447412/ /pubmed/28593078 http://dx.doi.org/10.1016/j.shaw.2016.10.001 Text en http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Original Article
Pandalai, Sudha P.
Wheeler, Matthew W.
Lu, Ming-Lun
Non-chemical Risk Assessment for Lifting and Low Back Pain Based on Bayesian Threshold Models
title Non-chemical Risk Assessment for Lifting and Low Back Pain Based on Bayesian Threshold Models
title_full Non-chemical Risk Assessment for Lifting and Low Back Pain Based on Bayesian Threshold Models
title_fullStr Non-chemical Risk Assessment for Lifting and Low Back Pain Based on Bayesian Threshold Models
title_full_unstemmed Non-chemical Risk Assessment for Lifting and Low Back Pain Based on Bayesian Threshold Models
title_short Non-chemical Risk Assessment for Lifting and Low Back Pain Based on Bayesian Threshold Models
title_sort non-chemical risk assessment for lifting and low back pain based on bayesian threshold models
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5447412/
https://www.ncbi.nlm.nih.gov/pubmed/28593078
http://dx.doi.org/10.1016/j.shaw.2016.10.001
work_keys_str_mv AT pandalaisudhap nonchemicalriskassessmentforliftingandlowbackpainbasedonbayesianthresholdmodels
AT wheelermattheww nonchemicalriskassessmentforliftingandlowbackpainbasedonbayesianthresholdmodels
AT luminglun nonchemicalriskassessmentforliftingandlowbackpainbasedonbayesianthresholdmodels