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

Sudip Das, National Institute of Technology, Rourkela, Department of Mining Engineering, Odisha, IndiaFollow
Falguni Sarkar, National Institute of Technology, Rourkela, Department of Mining Engineering, Odisha, India
P.S. Paul, Indian Institute of Technology (ISM), Dhanbad, Department of Mining Engineering, Jharkhand, India,
B.K. Pal, National Institute of Technology, Rourkela, Department of Mining Engineering, Odisha, India

Author ORCID Identifier

Sudip Das: 0009-0003-0894-5391

Falguni Sarkar: 0000-0002-8254-4380

P.S. Paul: 0000-0002-0410-7898

B.K. Pal: 0000-0002-3538-9066

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.

Recommended Citation

Das, Sudip; Sarkar, Falguni; Paul, P.S.; and Pal, B.K. (2026) "A critical appraisal on the injury susceptibility of underground metalliferous mine workers: Application of Logistic Regression model," Journal of Sustainable Mining: Vol. 25 : Iss. 1 , Article 10.
Available at: https://doi.org/10.46873/2300-3960.1483