158
Views
1
CrossRef citations to date
0
Altmetric
Articles

Work productivity loss due to musculoskeletal symptoms in the shoe and leather industry

ORCID Icon, , , &
Pages 925-930 | Published online: 26 Aug 2022
 

ABSTRACT

Objectives. This study aimed to explore the work productivity loss (WPL) due to musculoskeletal symptoms (MS) and its explanatory psychosocial, ergonomic and personal factors in Tunisian shoe and leather industry workers. Methods. We conducted a cross-sectional survey among 337 workers. We evaluated WPL using the work productivity and activity impairment questionnaire. We used the Nordic questionnaire to assess the MS prevalence, the job content questionnaire of Karasek to examine the psychosocial work environment and the quick exposure check (QEC) tool to estimate the ergonomic exposure levels. Results. The mean WPL was 44.9 ± 33%. In the multiple linear regression model, WPL was positively correlated with a history of MS, professional seniority, a rhythm perceived as restrictive, low social support and decision latitude, the number of symptomatic sites and the QEC strain level of the back. Conclusion. There was a decline in work productivity due to MS that results from a combination of personal, psychosocial and biomechanical factors. Once addressed, both work productivity and workers’ well-being should be restored.

Disclosure statement

No potential conflict of interest was reported by the authors.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 279.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.