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 (R² = 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.