Parametric method for the noise risk assessment of professional orchestral musicians

Noise Health. Nov-Dec 2016;18(85):319-328. doi: 10.4103/1463-1741.195797.


Background: The Occupational Health and Safety (OH&S) literature shows that noise could represent a risk factor for professional orchestral musicians. The continuative exposition to elevated noise levels and the particular nature of the activity make necessary an "atypical" OH&S approach, which was identified to be necessarily organizational.

Materials and methods: In this study, a parametric-based method for orchestral exposure assessment and management was developed. The goal was to achieve a predictive tool to involve safety in the decision making of concert season program. After setting the parameters, the project's hypothesis was defined and then validated through a yearly-scale monitoring on an important European symphonic orchestra. Moreover, workers' exposure was assessed from the parametric study by a wide measurement campaign.

Results: A general validation of the method was obtained by the verification of the main parameters' (repertoire, headcount, and disposition) significant influence on the sound pressure levels produced by the orchestra. Exposure levels comparable to the trends in literature for symphonic orchestras were observed, with criticalities among brass musicians, which was the only group exceeding the upper exposure action values.

Conclusion: This research has emphasized that the exposure condition of musicians can be critical and requires the implementation of improvement plans. The study has shown that the predictive analysis can be performed on parameters describing the concert's emissive characteristics. The future development of research currently under study will focus on the concert's pieces and the use of parameters as indicators of the exposure context.

MeSH terms

  • Hearing Loss, Noise-Induced / etiology*
  • Humans
  • Music*
  • Noise, Occupational*
  • Occupational Diseases / etiology*
  • Occupational Exposure*
  • Predictive Value of Tests
  • Reproducibility of Results
  • Risk Assessment