Investigation of factors affecting hearing loss of open pit coal mine employees with categorical data analyses

Year 2022, Volume: 61 Issue: 1, 19 - 24, 07.03.2022

Mustafa Önder , Burcu Demir İroz , Seyhan Önder

https://doi.org/10.30797/madencilik.977752

Cited By: 1

Abstract

One of the most important occupational diseases encountered in mining is the noise induced hearing loss (NIHL). In this study, analyses were carried out to examine the NIHL in the open pit lignite mine in Turkey. The NIHL was evaluated in accordance with the miners’ age, experience, occupation, exposure value (Lex), and maximum noise level (Lpeak). Noise levels exposed the employees were measured with noise dosimeters and a hearing test was applied to the employees by a special hearing center. To determine the parameters that could be effective in NIHL, all of the obtained data were evaluated by the logistic regression analysis (LRA) and hierarchical log-linear analysis (HLA) methods. It was determined that the NIHL probability of field staff is approximately 6 times higher than operators and drivers. According to the 21-29 age group, it was found that the probability of NIHL in the 57-65 and in the 48-56 age group was 11.4 and 4.41 times higher, respectively. Experience and maximum noise levels were found to be the most important parameters in hearing loss. Besides these, it was determined that the interactions of age×experience, occupation×maximum noise levels, and occupation×average noise exposure levels increased the likelihood of NIHL. A logistic regression model has been developed for the NIHL estimation of employees and hearing loss was found to be a problem mostly for those working in the field. It was determined that hearing loss increased with age and experience, and varied according to occupational groups.

Keywords

Hierarchical log-linear analysis, Logistic regression, Mining, Noise induced hearing loss, Occupational disease

Thanks

The authors would like to thank the authorities of the Turkish Coal Enterprises for their valuable understanding in the data provision and evaluation during the work undertaken.

Investigation of factors affecting hearing loss of open pit coal mine employees with categorical data analyses

Abstract

Madencilikte karşılaşılan en önemli meslek hastalıklarından biri gürültüye bağlı işitme kaybıdır (GBİK). Bu çalışmada, Türkiye'deki bir açık ocak linyit madeninde GBİK'nın incelenmesine yönelik analizler yapılmıştır. GBİK madencilerin yaşı, deneyimi, mesleği, maruz kalma değeri (Lex) ve maksimum gürültü seviyesi (Lpeak) dikkate alınarak değerlendirilmiştir. Çalışanların maruz kaldıkları gürültü seviyeleri gürültü dozimetreleri ile ölçülmüş ve çalışanlara özel işitme merkezi tarafından işitme testi uygulanmıştır. GBİK'da etkili olabilecek parametreleri belirlemek için elde edilen verilerin tamamı lojistik regresyon analizi (LRA) ve hiyerarşik log-lineer analiz (HLA) yöntemleri ile değerlendirilmiştir. Saha personelinin GBİK olasılığının operatörlere ve sürücülere göre yaklaşık 6 kat daha fazla olduğu belirlenmiştir. 21-29 yaş grubuna göre 57-65 ve 48-56 yaş grubunda GBİK olasılığının sırasıyla 11,4 ve 4,41 kat daha fazla olduğu tespit edilmiştir. İşitme kaybında deneyim ve maksimum gürültü seviyesi en önemli parametreler olarak bulunmuştur. Bunların yanı sıra yaş×deneyim, meslek×maksimum gürültü düzeyleri ve meslek×ortalama gürültüye maruz kalma düzeylerinin etkileşimlerinin GBİK olasılığını artırdığı belirlenmiştir. Çalışanların GBİK tahmini için bir lojistik regresyon modeli geliştirilmiş ve işitme kaybının en çok sahada çalışanlar için sorun olduğu tespit edilmiştir. İşitme kaybının yaş ve tecrübe ile arttığı ve meslek gruplarına göre farklılık gösterdiği belirlenmiştir.

Keywords

Hiyerarşik log-lineer analiz, Lojistik regresyon, Madencilik, Gürültüye bağlı işitme kaybı, Meslek hastalığı

References

• Agresti, A. 2002. Categorical Data Analysis. New Jersey: John Wiley and Sons. Inc.
• Bauer, E.R., Babich, D.R., Vipperman, J.R. 2006. Equipment noise and worker exposure in the coal mining industry (No. 9492). Department of Health and Human Services, Public Health Service, Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health, Pittsburgh Research Laboratory.
• Concha-Barrientos, M., Campbell-Lendrum, D., Steenland, K. 2004. Occupational noise: assessing the burden of disease from work-related hearing impairment at national and local levels. WHO Environmental Burden of Disease Series, No:9, Geneva
• Goelzer, B.I.F. 2001. Hazard prevention and control programmes. Goelzer, B., Hansen, C.H., Sehrndt, G.A. (Ed.). Occupational Exposure to Noise: Evaluation, Prevention and Control, WHO, Geneva, 233-244.
• Hong, O., Kerr, M.J., Poling, G.L., Dhar, S. 2013. Understanding and preventing noise-induced hearing loss. Disease-a-Month 59(4):110-118. doi:10.1016/j.disamonth.2013.01.002
• ISO 1999. 2013. Acoustics—estimation of noise-induced hearing loss, in international standard. ISO, Switzerland
• Kovalchik, P.G., Matetic, R.J., Smith, A.K., Bealko, S.B. 2008. Application of prevention through design for hearing loss in the mining industry. Journal of Safety Research, 39(2), 251-254. doi:10.1016/j.jsr.2008.02.029
• Maiti, J., Bhattacherjee, A., Bangdiwala, S.I. 2001. Loglinear model for analysis of cross-tabulated coal mine injury data. Injury control and safety promotion, 8(4), 229-236. doi:10.1076/icsp.8.4.229.3335
• Nelson, D.I., Nelson, R.Y., Concha‐Barrientos, M., Fingerhut, M. 2005. The global burden of occupational noise‐induced hearing loss. American Journal of Industrial Medicine, 48(6), 446-458. doi:10.1002/ajim.20223
• Official Gazette. 2013. Regulation on protection of employees from noise related risks. No. 28721. https://www.resmigazete.gov.tr/eskiler/2013/07/20130728-11.htm. [Accessed 02 August 2013].
• Onder, M., Demir Iroz, B., Onder, S. 2021. Using categorical data analyses in determination of dust-related occupational diseases in mining, International Journal of Occupational Safety and Ergonomics. 27(1),112-120. doi:10.1080/10803548.2018.1531535
• Onder, S. 2013. Evaluation of occupational injuries with lost days among opencast coal mine workers through logistic regression models. Safety Science. 59, 86-92. doi:10.1016/j.ssci.2013.05.002
• Onder, S., Mutlu, M. 2017. Analyses of non-fatal accidents in an opencast mine by logistic regression model - a case study. International Journal of Injury Control and Safety Promotion. 24(3), 328-337. doi:10.1080/17457300.2016.1178299
• Phillips, J.I., Heyns, P.S., Nelson, G. 2007. Rock drills used in South African mines: a comparative study of noise and vibration levels. The Annals of occupational hygiene, 51(3), 305-310. doi:10.1093/annhyg/mel082
• Picard, M., Girard, S.A., Simard, M., Larocque, R., Leroux, T., Turcotte, F. 2008. Association of work-related accidents with noise exposure in the workplace and noise-induced hearing loss based on the experience of some 240,000 person-years of observation. Accident Analysis & Prevention, 40(5), 1644-1652. doi:10.1016/j.aap.2008.05.013
• Sensogut, C., Cinar, I. 2007. An empirical model for the noise propagation in open cast mines–A case study. Applied Acoustics, 68(9), 1026-1035. doi:10.1016/j.apacoust.2006.04.016
• Sharma, O., Mohanan, V., Singh, M. 1998. Noise emission levels in coal industry. Applied Acoustics, 54(1), 1-7. doi:10.1016/S0003-682X(97)00073-X
• TS 2607 ISO 1999. 2005. Acoustics - Determination of occupational noise exposure and estimation of noise-induced hearing impairment. ISO, Ankara (in Turkish).
• Vipperman, J. S., Bauer, E.R., Babich, D.R. 2007. Survey of noise in coal preparation plants. The Journal of the Acoustical Society of America, 121(1), 197-205. doi:10.1121/1.2372587