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Workplace
Original article
Whole-body vibration and back pain-related work absence among heavy equipment vehicle mining operators
  1. Lope H Barrero1,
  2. Manuel Cifuentes2,
  3. Andrés C Rodríguez1,
  4. Estefany Rey-Becerra3,
  5. Peter W Johnson4,
  6. Luz S Marin5,
  7. Hugo Piedrahita6,
  8. Jack T Dennerlein7
  1. 1 Department of Industrial Engineering, School of Engineering, Pontificia Universidad Javeriana, Bogotá, Colombia
  2. 2 Program of Public Health, School of Health Sciences, Regis College, Weston, Massachusetts, USA
  3. 3 Department of Civil and Industrial Engineering, Pontificia Universidad Javeriana, Cali, Colombia
  4. 4 Department of Industrial Engineering, University of Washington, Seattle, Washington, USA
  5. 5 Department of Safety Sciences, Indiana University of Pennsylvania, Indiana, Pennsylvania, USA
  6. 6 Health and Welfare Department, Cerrejón, La Guajira, Colombia
  7. 7 Department of Physical Therapy, Movement, and Rehabilitation Sciences, Bouvé College of Health Sciences, Northeastern University, Boston, Massachusetts, USA
  1. Correspondence to Professor Lope H Barrero, Department of Industrial Engineering, School of Engineering, Pontificia Universidad Javeriana, 40 - 62, Bogotá, Colombia; lopehugo{at}javeriana.edu.co

Abstract

Objective To determine the association between several whole-body vibration (WBV) exposure estimates and back pain-related work absence.

Methods Exposures (based on the weighted daily root mean square acceleration, A(8); the daily vibration dose value, VDV(8); and the daily equivalent static compression dose, Sed(8)) of 2302 workers during 4 years were estimated using each worker’s monthly vehicle operation records and WBV measurements from 11 different types of heavy equipment vehicles in a large coal mine. Company payroll data provided work absence during the concurrent 4 years of exposure. Cox regression models estimated the associations between the different WBV metrics and time to first work absence related to back pain. An adjusted R2 statistic provided a measure of model fit.

Results All estimated metrics of WBV exposures were positively and significantly associated with back pain-related absence. HRs varied from 2.03 to 12.39 for every 0.21 m/s2 increase in the A(8)-based exposures; from 1.03 to 1.18 for every 1.72 m/s1.75 increase in VDV(8)-based exposures; and from 1.04 to 1.07 for every 0.06 MPa increase in Sed(8)-based exposures. Models using the estimated VDV(8) metric for the z axis fit the data best as measured by the R2 statistic.

Conclusion Higher WBV exposures were associated with back pain-related absences in this population, which appears after a few years of follow-up. Introducing controls to lower exposure levels may help reduce back pain-related work absences.

  • dorsalgia
  • back pain
  • epidemiology
  • vibration metrics
  • cox-regression

https://doi.org/10.1136/oemed-2019-105914

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    Footnotes

    • Contributors LHB wrote the first draft of the paper and conducted the statistical analyses. MC led the statistical analysis strategy and edited the paper. ACR and ER-B collected the data, helped to edit the manuscript and provided feedback to the statistical analysis. PWJ led the data collection, edited the paper and provided feedback to the statistical analysis. LSM edited the paper and provided feedback to the statistical analysis. HP facilitated the data collection and edited the paper. JTD was the PI of the project, formulated the general study design, edited the paper and provided feedback to the statistical analysis.

    • Funding The ALPHA Foundation funded this study with grant number 120113E01011O5.

    • Competing interests None declared.

    • Ethics approval All data were anonymised prior to data analysis. As such, the study received exempt status approval from the institutions' human subject internal review boards.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Patient consent for publication Not required.