The Risk Rating System for Noise-induced Hearing Loss in Korean Manufacturing Sites Based on the 2009 Survey on Work Environments

Abstract

ObjectivesIn Korea, an average of 258 workers claim compensation for their noise-induced hearing loss (NIHL) on an annual basis. Indeed, hearing disorder ranks first in the number of diagnoses made by occupational medical check-ups. Against this backdrop, this study analyzed the impact of 19 types of noise-generating machines and equipment on the sound pressure levels in workplaces and NIHL occurrence based on a 2009 national survey on work environments.MethodsThrough this analysis, a series of statistical models were built to determine posterior probabilities for each worksite with an aim to present risk ratings for noise levels at work.ResultsIt was found that air compressors and grinding machines came in first and second, respectively in the number of installed noise-generating machines and equipment. However, there was no direct relationship between workplace noise and NIHL among workers since noise-control equipment and protective gear had been in place. By building a logistic regression model and neural network, statistical models were set to identify the influence of the noise-generating machines and equipment on workplace noise levels and NIHL occurrence.ConclusionThis study offered NIHL prevention measures which are fit for the worksites in each risk grade.

Associations between dietary quality, noise, and hearing: Data from the National Health and Nutrition Examination Survey, 1999–2002

“…Worldwide, industries with high numbers of noise-exposed workers (and high rates of NIHL in workers) include agriculture, mining, construction, manufacturing, utilities, and transportation (Dasgupta et al, 2009; Kim, 2010; Kim et al, 2011; Vigeh et al, 2011; Chung et al, 2012; Kelly et al, 2012; Masilamani et al, 2012; Pingle, 2012; Singh et al, 2012; Belojevic, 2013; Cruz et al, 2013; Pawlaczyk-Luszczynska et al, 2013). Although NIHL secondary to occupational noise is a known issue, within this NHANES cohort, there was not a statistically significant relationship between reported occupational noise (here defined as working in noise loud enough to need to raise voice to hear for at least 3 months) and hearing status.…”

Contributions and limitations of using machine learning to predict noise-induced hearing loss

“…Although the study by Mohd Nawi et al ( 2011 ) reported over 99% accuracy of the prediction model, incomplete information of the model construction created the risk of bias. Another study constructed a large database ( n = 2,420,330) to analyzed the impact of diverse noise to the generation of NIHL using ANN but unraveled the unsatisfactory performance with less than 65% accuracy, which was no better than LR model (Kim et al 2011 ). The accuracies of some algorithms were also investigated in several studies which either tried to predict hearing loss with specific etiologies, such as sudden hearing loss (Bing et al 2018 ; Park et al 2020 ), ototoxic hearing loss (Tomiazzi et al 2019 ) and cochlear dead regions (Chang et al 2019 ), or predict SNHL by specific auditory measures, such as OAE (de Waal et al 2002 ; Liu et al 2020 ; Ziavra et al 2004 ) and ABR (Acır et al 2006 ; Molina et al 2016 ).…”

“…Other studies showed similar high accuracies with ML models used to predict sudden sensorineural hearing loss (SSNHL) and otoxic-induced hearing loss (Bing et al 2018 ; Tomiazzi et al 2019 ). Varied accuracies between 64 and 99% were reported by different studies using different ML algorithms and inputs to predict risk factors for NIHL (Aliabadi et al 2015 ; Farhadian et al 2015 ; Kim et al 2011 ; Mohd Nawi et al 2011 ; Zhao et al 2019a ).…”

Study of Personal Hearing Protection Devices Usage in Kashan Carpet Industry Workers

“…Hearing loss due to industrial noise is a sensoryneural hearing loss that normally increases and progresses during the years of noise exposure and is an irreversible damage. However, it is preventable through avoiding excessive exposure to noise and proper use of personal protective equipment such as HPDs (18)(19)(20)(21). Studies have found that the prevention of hearing damage through the use of Hearing Protective Devices (HPDs) in the industry is low, varying from 20% usage in some studies (3) to 30% -50% in others (22)(23)(24).…”