Alternative metrics for noise exposure among construction workers

Area of Science:

• Occupational Health
• Audiology
• Industrial Hygiene

Background:

• Established exposure-response relationships for noise-induced hearing loss exist, but consensus on optimal noise metrics is lacking.
• Discrepancies in noise metric usage (e.g., L(eq) with 3 dB ER vs. L(avg) with 5 dB ER) and the impact of peak exposures complicate risk assessment.
• Construction industry noise exposures, often characterized by peaks, require careful metric evaluation.

Purpose of the Study:

• To analyze a large database of construction worker noise exposures.
• To compare the effectiveness of various noise metrics, including novel variability and peakiness metrics, in representing hearing damage risk.
• To explore alternative models for estimating noise exposure and their application to a construction worker cohort.

Main Methods:

• Analysis of 730 workshifts and 361,492 minutes of noise exposure data from nine construction trades.
• Examination of established metrics: L(avg), L(eq), and L(max).
• Derivation and analysis of novel metrics: L(eq)/L(avg) for exposure variability and L(max)/L(eq) for 'peakiness'.

Main Results:

• High correlations were observed between average noise metrics (L(eq), L(avg), L(max)).
• Variability metrics (L(eq)/L(avg), L(max)/L(eq)) showed poor correlation with average levels and each other, indicating distinct characteristics.
• A task-within-trade specific mean level was adopted as the preferred exposure estimation model.

Conclusions:

• Novel metrics effectively characterize different aspects of noise exposure not captured by traditional average metrics.
• The distinct nature of variability and peakiness metrics suggests their importance in a comprehensive assessment of noise-induced hearing loss risk.
• Further application of these metrics to worker histories is needed to validate their role in predicting hearing damage.