Comparison of Perceived and Quantitative Measures of Occupational Noise Exposure

    loading  Checking for direct PDF access through Ovid



Characterization of highly variable noise exposures over long periods of time presents a major challenge. Common exposure assessment strategies such as assignment of exposure levels based on job title information may not provide adequate exposure contrast or precision for variable exposures. Subjective exposure data may offer an alternative or complementary exposure assessment strategy. This study evaluated the relationship between perceived and quantitatively measured exposure.


Twenty subjects were recruited at each of three worksites with different noise environments (continuous, intermittent and highly variable). Full-shift quantitative measurements (n=206) were made on each subject during four workshifts over 2 weeks. Perceived exposure data were collected via surveys on subjects’ first (n=58) and last (n=57) monitored shifts, as well as through timeline logs completed by subjects during each monitored shift. The first survey focused on the first shift only, while the second survey covered the whole 2-week period.


Timeline log data suggested that subjects could differentiate between different noise levels and degrees of noise variability. Survey items on perceived exposure variability and impulsiveness performed well at the continuous and highly variable sites. Analyses of contrast between exposure grouping strategies showed that job title generally did not produce statistically distinct exposure groups and that several survey items provided greater contrast than job title. The precision of exposures predicted from survey items was comparable to, or slightly better than, that of job title for several survey items, and the addition of survey items to prediction models which included job title improved model fit and precision.


Supplemental perceived noise exposure information appears to offer promise for improving exposure estimates, particularly for individuals with highly variable exposures.

Related Topics

    loading  Loading Related Articles