1. Predicting and Weighting the Factors Affecting Workers’ Hearing Loss Based on Audiometric Data Using C5 Algorithm
- Author
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Sajad Zare, Mina Rostami, Mohammad Reza Ghotbi-Ravandi, Mostafa Ghazizadeh Ahsaee, and Hossein ElahiShirvan
- Subjects
Hearing loss ,Infectious and parasitic diseases ,RC109-216 ,Iran ,Mining ,High weight ,03 medical and health sciences ,0302 clinical medicine ,Noise exposure ,Audiometry ,Predictive Value of Tests ,Occupational Exposure ,Linear regression ,medicine ,otorhinolaryngologic diseases ,Humans ,030212 general & internal medicine ,Prospective Studies ,Sound pressure ,Original Research ,medicine.diagnostic_test ,business.industry ,030503 health policy & services ,General Medicine ,Weighting ,Occupational Diseases ,Mining industry ,Cross-Sectional Studies ,Hearing Loss, Noise-Induced ,Noise, Occupational ,medicine.symptom ,Public aspects of medicine ,RA1-1270 ,0305 other medical science ,business ,Algorithm ,Algorithms - Abstract
Introduction: With the extensively spread of industrialization in the world, noise exposure is becoming more prevalent in the industrial settings. The most important and definite harmful effects of sound include hearing loss, both permanent and temporary. Objective: This study was designed aimed to use the C5 algorithm to determine the weight of factors affecting the workers’ hearing loss based on the audiometric data. Methods: This cross-sectional, descriptive, analytical study was conducted in 2018 in a mining industry in southeastern Iran. In this study, workers were divided into three exposed groups with different sound pressure levels (one control group and two case groups). Audiometry was conducted for each group of 50 persons; hence, the total number of subjects was 150. The stages of this study include: 1) selecting factors (predictive) to check and weigh them; 2) conducting the audiometry for both ears; 3) calculating the permanent hearing loss in each ear and permanent hearing loss of both ears; 4) classifying the types of hearing loss; and 5) investigating and determining the weight of factors affecting the hearing loss and their classification based on the C5 algorithm and determining the error and accuracy rate of each model. To assess and determine the factors affecting the hearing loss of workers, the C5 algorithm and IBM SPSS Modeler 18.0 were used. SPSS V.18 was used to analyze the linear regression and paired t-test tests, too. Results: The results showed that in the first model (SPL 85 dBA), the 4KHz frequency with the weight of 31% had the highest effect, and the work experience with a weight of 1% had the lowest effect, and the accuracy of the model was 94%. In the fourth model, the 4KHz frequency with the weight of 22% had the highest effect and 250Hz and age each with the weight of 8% had the lowest effects; the accuracy of this model was calculated to be 99.05%. Conclusions: During investigating and determining the weight of the factors affecting hearing loss by the C5 algorithm, the high weight and effect of the 4KHz frequency were predicted in hearing loss changes. Considering the high accuracy obtained in this modeling, this algorithm is a suitable and powerful tool for predicting and modeling the hearing loss.
- Published
- 2019