Assessing whole body vibration exposure for use in epidemiological studies of back injuries: measurements, observations and self-reports

Abstract

Improved assessment of whole body vibration exposure is needed for epidemiological studies investigating the causes of low back disorders. Vibration was measured on 54 worker-days in five heavy industries, with data collected on observed and self-reported driving conditions, demographics, and vehicle characteristics. Variables significant at p < 0.1 in simple linear regressions (20 of 34) were retained for mixed effects multiple regressions to determine the best prediction of rms vibration level and 8-h equivalent vibration exposure. Vibration was measured, on average, for 205 min per work shift (SD 105). Means and standard deviations in m · s⁻² were: x-axis 0.35 (0.19); y-axis 0.34 (0.28); z-axis 0.54 (0.23); vector sum 0.90 (0.49); and 8-h equivalent vector sum 0.70 (0.37). The final three regression models retained only 2 or 3 of the 34 variables (driving speed (<20 km/h and/or 20–40 km/h) and industry and/or vehicle type and explained up to 60% of the variance (R ² = 0.26–0.6).

Practitioner summary

The purpose of the project was to create a model that can predict whole body vibration exposure from a number of observed or self-reported variables. This could eliminate the need for costly and time-consuming field measurements of WBV in epidemiological studies. Despite a large number of variables included in the model (34) and 54 worker-days of WBV measurement, the final models contained only two or three variables, and explained 60% of the variance. While this is an improvement over use of job title in epidemiological studies, it still leaves a considerable amount of WBV variance unexplained.

Keywords:

• whole-body vibration
• exposure assessment
• determinants modelling
• heavy equipment
• epidemiology

Acknowledgements

The authors thank all the study participants and their employers for time and commitment to the study. Thanks also go to the study's data collectors: James Cooper, Nancy Luong, Melissa Knott, and Kevin Hong. This study was funded in part by the WorkSafeBC Research Secretariat, the Canadian Institutes of Health Research Strategic Training Program Bridging Public Health, Engineering and Policy Research, and the University of British Columbia Centre for Health and Environment Research. Koehoorn was supported in part by a Michael Smith Foundation for Health Research Scholar Award; Trask was supported by a Michael Smith Foundation for Health Research Junior Research Studentship Training Award and a WorkSafeBC Research Training Award.