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Database for a hearing conservation program.

I V Pyykkö1, E M Toppila, J P Starck

  • 1Department of Otolaryngology, Karolinska Hospital, Stockholm, Sweden.

Scandinavian Audiology
|March 16, 2000
PubMed
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NoiseScan is a new program for assessing noise-induced hearing loss (NIHL). It evaluates noise exposure and other risk factors to predict hearing loss and assess hearing conservation effectiveness.

Area of Science:

  • Audiology
  • Occupational Health
  • Environmental Health

Background:

  • Noise-induced hearing loss (NIHL) is a significant occupational health concern.
  • Accurate assessment of NIHL requires comprehensive data on noise exposure and confounding factors.
  • Existing methods may not fully capture the complexity of combined risk factors.

Purpose of the Study:

  • To introduce NoiseScan, a database and analysis program for NIHL.
  • To provide a tool for evaluating noise exposure, risk factors, and hearing conservation efficacy.
  • To enable more precise prediction of individual hearing loss and the development of hearing loss over time.

Main Methods:

  • NoiseScan evaluates noise immission levels, including duration, frequency, and hearing protector performance.

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  • It collects data on confounding medical factors (e.g., hypertension, cholesterol) and combined exposures (e.g., vibration, smoking).
  • The program utilizes the ISO 1999 model to predict hearing loss based on total exposure and stores unlimited audiograms.
  • Main Results:

    • NoiseScan handles extensive exposure data and estimates exposure when unknown by referencing comparable workplaces.
    • It facilitates the determination of occupational origin for hearing loss and assesses hearing conservation measures.
    • The program predicts hearing loss development in 5-year intervals for individuals.

    Conclusions:

    • NoiseScan is a valuable tool for data collection and analysis of NIHL risk factors.
    • It aids in identifying occupational hearing loss and evaluating the success of hearing conservation programs.
    • Ongoing development aims to improve the prediction accuracy of NIHL by validating risk factor contributions.