Tehran University of Medical Sciences

Science Communicator Platform

Stay connected! Follow us on X network (Twitter):
Share this content! On (X network) By
Comprehensive Causal Analysis of Occupational Accidents’ Severity in the Chemical Industries; a Field Study Based on Feature Selection and Multiple Linear Regression Techniques



Soltanzadeh A1 ; Heidari H1 ; Mohammadi H2 ; Mohammadbeigi A3 ; Sarsangi V4 ; Jazari MD5
Authors
Show Affiliations
Authors Affiliations
  1. 1. Occupational Safety & Health Engineering Department, Research Center for Environmental Pollutants, Health Faculty, Qom University of Medical Sciences and Health Services, Qom, Iran
  2. 2. Department of Occupational Safety & Health Engineering, School of Health, Larestan University of Medical Sciences, Fars, Iran
  3. 3. Epidemiology & Biostatistics Department, Neuroscience Research Center, Health Faculty, Qom University of Medical Sciences and Health Services, Qom, Iran
  4. 4. Department of occupational Health, Tehran University of Medical Sciences, Tehran, Iran
  5. 5. Faculty of Health, Baqiyatallah University of Medical Sciences, Tehran, Iran

Source: Journal of Health and Safety at Work Published:2019

Abstract

Introduction: The causal analysis of occupational accidents’ severity in the chemical industries may improve safety design programs in these industries. This comprehensive study was implemented to analyze the factors affecting occupational accidents’ severity in the chemical industries. Material and Methods: An analytical study was conducted in 22 chemical industries during 2016-2017. The study data included 41 independent factors and 872 accidents in a ten-year period (2006-2015) as a dependent variable. Feature selection algorithm and multiplied linear regression techniques were used to analyze this study. Results: Accident severity rate mean was calculated 214.63 ± 145.12. The results of feature selection showed that 30 factors had high impacts on the severity of accidents. In addition, based on regression analysis, the severity of accidents in the chemical industries was affected by 22 individuals, organizational, HSE training, risk management, unsafe conditions and unsafe acts, as well as accident types (p<0.05). Conclusion: The findings of this study confirmed that accidents’ severity in the chemical industry followed the multi-factorial theory. In addition, the main finding of this study indicated that the combination of features selection algorithm and multiple linear regression methods can be useful and applicable for comprehensive analysis of accidents and other HSE data. © 2019, Tehran University of Medical Sciences. All rights reserved.
Related Docs
1. Incidence Investigation of Accidents in Chemical Industries: A Comprehensive Study Based on Factor Analysis, Process Safety Progress (2022)
2. Development of a New Technique for Safety Risk Assessment in Construction Projects Based on Fuzzy Analytic Hierarchy Process, ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems# Part A: Civil Engineering (2021)
3. Analyzing Health, Safety, and Environmental Risks of Construction Projects Using the Fuzzy Analytic Hierarchy Process: A Field Study Based on a Project Management Body of Knowledge, Sustainability (Switzerland) (2022)
4. Construction Accident Data Mining: A Retrospective Study Using Structural Equation Modeling Based on 10-Year Data, Work (2023)