H J Mason1, K Poole, C Young. 1. Occupational Hygiene Unit, Health and Safety Laboratory, Buxton SK17 9JN, UK. howardj.mason@hsl.gov.uk
Abstract
BACKGROUND: Assessing past cumulative vibration exposure is part of assessing the risk of hand-arm vibration syndrome (HAVS) in workers exposed to hand-arm vibration and invariably forms part of a medical assessment of such workers. AIMS: To investigate the strength of relationships between the presence and severity of HAVS and different cumulative exposure metrics obtained from a self-reporting questionnaire. METHODS: Cumulative exposure metrics were constructed from a tool-based questionnaire applied in a group of HAVS referrals and workplace field studies. These metrics included simple years of vibration exposure, cumulative total hours of all tool use and differing combinations of acceleration magnitudes for specific tools and their daily use, including the current frequency-weighting method contained in ISO 5349-1:2001. RESULTS: Use of simple years of exposure is a weak predictor of HAVS or its increasing severity. The calculation of cumulative hours across all vibrating tools used is a more powerful predictor. More complex calculations based on involving likely acceleration data for specific classes of tools, either frequency weighted or not, did not offer a clear further advantage in this dataset. This may be due to the uncertainty associated with workers' recall of their past tool usage or the variability between tools in the magnitude of their vibration emission. CONCLUSIONS: Assessing years of exposure or 'latency' in a worker should be replaced by cumulative hours of tool use. This can be readily obtained using a tool-pictogram-based self-reporting questionnaire and a simple spreadsheet calculation.
BACKGROUND: Assessing past cumulative vibration exposure is part of assessing the risk of hand-arm vibration syndrome (HAVS) in workers exposed to hand-arm vibration and invariably forms part of a medical assessment of such workers. AIMS: To investigate the strength of relationships between the presence and severity of HAVS and different cumulative exposure metrics obtained from a self-reporting questionnaire. METHODS: Cumulative exposure metrics were constructed from a tool-based questionnaire applied in a group of HAVS referrals and workplace field studies. These metrics included simple years of vibration exposure, cumulative total hours of all tool use and differing combinations of acceleration magnitudes for specific tools and their daily use, including the current frequency-weighting method contained in ISO 5349-1:2001. RESULTS: Use of simple years of exposure is a weak predictor of HAVS or its increasing severity. The calculation of cumulative hours across all vibrating tools used is a more powerful predictor. More complex calculations based on involving likely acceleration data for specific classes of tools, either frequency weighted or not, did not offer a clear further advantage in this dataset. This may be due to the uncertainty associated with workers' recall of their past tool usage or the variability between tools in the magnitude of their vibration emission. CONCLUSIONS: Assessing years of exposure or 'latency' in a worker should be replaced by cumulative hours of tool use. This can be readily obtained using a tool-pictogram-based self-reporting questionnaire and a simple spreadsheet calculation.