Evaluation of the Workplace Accident Severity in an Underground Coal Mine By Logistic Regression Analysis

Abstract

Background: Accidents in underground coal mining can cause deaths, serious injuries, and material losses. Methods: This study examined 10,334 work accidents that occurred between 2011 and 2021, resulting in injuries, and evaluated the causes, severity, and types of injuries. The accidents were investigated under the following subheadings: location of accidents, causes of accidents, work shifts when the accidents occurred, accident time, accident days, distribution of accidents by months and years, age of workers, occupational groups, educational status of workers, working day losses, and body parts that were injured. The severity of accidents was categorized into three levels: mild, moderate, and severe, based on the workday losses incurred by the workers after the accident. The severity of accidents and factors affecting their severity were analyzed using multinomial logistic regression. Results: There is a significant statistical relationship between the severity of accidents and factors such as experience, workplace, accident cause, age, education status, occupational category, and the affected body part, work shift, according to the analysis. The findings indicate that accident severity is influenced not only by the immediate circumstances of the incident but also by broader individual and occupational factors, such as the employee’s level of experience, the work environment, the occupational group, and the specific body part affected. The analysis revealed that the occupational group variable had statistically significant interaction effects with multiple other variables. Conclusions: The study presents all aspects of the hazards faced by the workers and suggests measures to reduce the number and severity of accidents that occur in underground coal mining.