Prediction of risk of hearing loss by industry noise from cross-sectional and longitudinal data

Noise exposure at work can damage hearing at speech-frequency essential for speech perception, leading to communication difficulties, life quality decline, and adverse mental and cognitive outcomes. Early identification of individuals at high risk is crucial for occupational health management. This study aims to develop prediction models to estimate the risk of speech-frequency hearing loss among noise-exposed workers.

We developed and validated multimodal prediction models using epidemiological, hearing assessment, and genetic information from shipyard workers. The training cohort included 5053 workers and the testing cohort included 2086 workers recruited between 2012 and 2024. Noise exposure was estimated using detailed work durations and workplace measurements. Participants completed questionnaires, underwent standardized hearing examinations, and provided blood samples for genetic analysis. Sex-specific models were constructed based on two commonly used definitions of speech-frequency hearing loss. Longitudinal risk was evaluated using repeated-measures statistical approaches.

Here we show that binaural hearing thresholds at 3 and 6 kHz are the strongest predictors of subsequent speech-frequency hearing loss, together with age and noise exposure (P < 0.001). Longitudinal prediction models demonstrate good discrimination and calibration, with AUCs exceeding 0.80 and C-indices above 0.78 in both training and testing cohorts. Incorporation of genetic variants further improves predictive performance, increasing discrimination by approximately 2% in males and 3% in females.

These findings provide evidence-based prediction tools that enable individualized risk assessment. Practically, identifying workers at high risk would benefit the hearing preservation in the frequencies more relevant to speech sounds and maintain good communication.