Using categorical data analyses in determination of dust-related occupational diseases in mining

Abstract

Dust-related occupational diseases are common in the mining sector. It is important to identify employees who have high potential for these diseases and to investigate the factors affecting disease formation. For this reason, dust and dust-related occupational diseases should be carefully investigated in mining operations. In this study, dust-related occupational diseases in an open-pit lignite mine were investigated. Firstly, dust measurements were performed and then a health check of all employees was implemented. The obtained data set was categorized by taking into account the occupation, age, experience and level of dust exposure of the employees. While the logistic regression analysis was performed to determine the probability of the diseases, a hierarchical loglinear model was established to investigate the factors in the occurrence of these diseases for those employees with the diseases. Therefore, the most important factors for the development of the diseases were determined by the hierarchical loglinear model.

Keywords:

• respirable dust
• dust-related occupational diseases
• categorical data analyses
• mining
• occupational health

Acknowledgements

The authors would like to thank the Turkish Coal Enterprises staff and Dr Burak Geyik.

Disclosure statement

No potential conflict of interest was reported by the authors.