Abstract
Whole body vibration (WBV) exposure is recognised as a risk factor to the high prevalence of spinal musculoskeletal disorders (MSDs) experienced by farmers. The purpose of this study was to identify self-reported predictors that could be used to develop statistical models for WBV exposure (expressed as A8rms and VDV) in farmers operating agricultural quad bikes. Data were collected in the field from 130 farmers. Linear mixed effects modeling was used to determine the models of best fit. The prediction model for A8rms exposure (explaining 57% of the variance) included farmer age, estimated quad bike driving hours on day of testing and the type of quad bike rear suspension (rigid-axle rear suspension with two shock absorbers). The best model for VDV exposure (explaining 33% of the variance) included farmer age, estimated quad bike driving hours on day of testing and the type of quad bike rear suspension (rigid-axle rear suspension with two shock absorbers). In large epidemiological studies of spinal MSDs, these models would provide an acceptable indication of WBV without the costs of direct measurement.