Lost work days as a measure of risk assessment in underground coal mines
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Objectives: Underground coal mining, has always been a dangerous occupation. Injuries are one of the major occupational risks that all miners live with. Reportable injury monitoring and data analysis can provide us valuable information on the causes of injuries and enable us to establish a model between the conditions in the work environment and the number of injuries, which can further lead to proper prevention and mitigation measures. Methods: In this study, a binary logistic regression method was applied to reportable injuries from February 1994 to January 2009 of an underground coal mine in India. The injury records were categorised on the basis of shift, occupation, body part injured and reason of injury as well as lost workdays, and the SPSS package was used for the analyses. Logistic regression method was applied to predict the probability of injuries that resulted in less or more lost workdays (threshold limit 9 days). Results: It is found that the shift variables did not have any significant effect on the lost workdays. Whereas, the occupation variable has the significant role with the injuries of greater than 9 lost workdays from reportable injuries were the miscellaneous job. Meanwhile, the body part variable with the highest risk was the torso. Additionally, employees engaged with manual and mechanical handling has significant role in more lost workdays. Conclusion: It is concluded that miscellaneous personnel are not properly trained for different jobs. As personal protective equipment is not used in torso; it leads to more lost days.
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