Questionnaire-based algorithm for assessing occupational noise exposure of construction workers.

Abstract

OBJECTIVES: Occupational noise exposure is a major cause of hearing loss worldwide. In order to inform preventative strategies, we need to further understand at a population level which workers are most at risk. METHODS: We have developed a new questionnaire-based algorithm that evaluates an individual worker's noise exposure. The questionnaire and supporting algorithms are embedded into the existing software platform, OccIDEAS. Based on the tasks performed by a worker during their most recent working shift and using a library of task-based noise exposure levels, OccIDEAS estimates whether a worker has exceeded the full-shift workplace noise exposure limit (LAeq,8h=85 dBA). We evaluated the validity of the system in a sample of 100 construction workers. Each worker wore a dosimeter for a full working shift and was then interviewed using the OccIDEAS software. RESULTS: The area under the receiver operating characteristic curve was 0.81 (95% CI 0.72 to 0.90) indicating that the ability of OccIDEAS to identify construction workers with an LAeq,8h=85 dBA was excellent. CONCLUSION: This validated noise questionnaire may be useful in epidemiological studies and for workplace health and safety applications.