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

Kate Lewkowski, Kahlia McCausland, Jane S Heyworth, Ian W Li, Warwick Williams, Lin Fritschi

Research output: Contribution to journalArticle

3 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)237-242
Number of pages6
JournalOccupational and Environmental Medicine
Volume75
Issue number3
DOIs
Publication statusPublished - Mar 2018

Fingerprint Dive into the research topics of 'Questionnaire-based algorithm for assessing occupational noise exposure of construction workers'. Together they form a unique fingerprint.

Cite this