Changes of Occupational Noise-Induced Hearing Loss due to Working in the Steel Industry and Associated Effective Factors: Application of Bayesian Multivariate Multilevel Modeling using Skew Distribution

Background: There have been a limited number of studies on the relationships between time and occupational and demographical variables with the mean changes of low-frequency hearing (LFH) and high-frequency hearing (HFH). Objectives: This study investigated the rate of occupational noise-induced hearing loss (NIHL) due to working in the steel industry and associated effective factors. Methods: This historical cohort study was conducted within 2000 to 2010. Two LFH and HFH definitions of NIHL were used in this study. The average changes of LFH and HFL were considered the response variables. In addition, time and occupational (i.e., shift work and work experience) and demographic (i.e., age and educational level) variables were regarded as the independent variables. For data analysis, Bayesian multivariate multilevel modeling using skew distribution and OpenBUGS (version 3.2.2) and R (version 2.13.2) software were used in this study. Results: The present study was performed on 1,959 male workers with a mean age of 36.64±3.92 years. Among these subjects, 913 (46.6%), 134 (6.8%), and 912 (46.6%) participants were day workers, weekly-rotating shift workers, and routinely-rotating shift workers, respectively. The obtained results showed that age, work experience, educational level, and shift work had significant relationships with the changes of LFH and HFH. Conclusion: Overall, the findings of this 10-year historical cohort study demonstrated a relationship between time and demographic and occupational variables with the changes of LFH and HFL. Therefore, it is recommended to design preventive measures to reduce the deleterious effects of such variables on LFH and HFL.