A critical appraisal on the injury susceptibility of underground metalliferous mine workers: Application of Logistic Regression model

Abstract The aim of this study is to analyze the occupational injury data of Indian underground metalliferous mines for scrutinizing the injury proneness of different groups of mine workers. In this context, injury records from 2011 to 2022 were obtained from underground metalliferous mines situated at Eastern part of India. The data were characterized and segregated based on different individual and workplace level variables. The workplace injury is categorized as ‘no injury’ and ‘all injury’. Subsequently, Frequency and Classification Based analysis (FCBA), Standardized Injury Rate (SIR) analysis and Logistic Regression Model (LRM) analysis were performed sequentially (FCBA-SIR-LRM) to predict the susceptibility of injuries of different worker groups and their categories. The result shows that the age, experience, occupation, workplace and mine variables have significant influence on accident susceptibility. Based on the results, potential causes of accidents were assessed and suggestions for reducing the likelihood of their occurrences were discussed in detail.