DETERMINANTS OF ACCIDENT IN THE MINES: A RETROSPECTIVE STATISTICAL ANALYSIS OF MINING ACCIDENTS IN GHANA

Francis Frimpong, Kingsley Kwakye

Abstract


The mining industry continues to be an important sector of the Ghanaian economy, contributing to the foreign exchange, employment and socioeconomic development after the colonial period. The current trend of mining operations requires greater skills and technical knowledge because they involve sophisticated machines, dangerous chemicals and explosive mechanisms, underground operations etc. Accidents in the mines just like any occupational accident may lead to deaths, injuries, disabilities and financial losses. One of the ways of improving occupational knowledge and skills is to acquire some level of understanding of accident causation mechanism. An analytical technique which will form the basis for accident and injury epidemiological studies is therefore necessary to ensure operational safety improvement. A retrospective statistical analysis of accidents in eight gold mining companies was undertaken through measures of association, hypothesis testing, trend analysis and predictive measurements. The results of the study indicate that 20% of accident cases resulted in deaths, 30% were serious and 50% minor accidents. Underground mining increases the risk fatal accident by 1.46, morning shift increases the risk of fatal accident by 4.81 and being a contract miner increases the risk of fatal accident by 1.05. The part of body injured can predict the degree of injury by reducing the error of prediction by 40.2%. Since proportion of accident fatalities increases with increasing age of miners, it is recommended that miners with higher age should not be task with high risk jobs. It is recommended again that, miners should be given improved protective clothes to guide against occurrences of fatal incidents. Especially, clothes to cover the head and upper part of the body since they top the fatality chart and the fact that fatality is strongly associated with body part.

Article visualizations:

Hit counter


Keywords


accidents; statistical analysis; causation models; hypothesis testing; trend analysis; predictive measurement; confounding variables; odds ratio

Full Text:

PDF

References


World Health Organisation (WHO). (2001). Guidelines on Occupational Safety and Health management systems. International Labour Office, Geneva. ISBN 92-2-111634-4

Patterson J. (2009). Human Error in Mining: Multivariable Analysis of Mining Accident/Incidents in Queensland, Australia and the United States of America Using the Human Factors Analysis and Classification System Framework. All Dissertations Paper 464, Clemson University.

HaSPA (Health and Safety Professionals Alliance) (2012). The Core Body of Knowledge for Generalist Occupation Health Safety Professionals. Safety Institute of Australia Ltd, Tullamarine, Victoria, Australia. ISBN 978-0-9808743-1-0.

Amegbey, N., Ndur, S. and Adjei R. K. (2008). Analysis of underground mining accidents at Anglogold Ashanti Limited, Obuasi Mine. Ghana Mining Journal, pp 25-29.

Rahman N. A. A. (2014). Analysis of the Perception of Occupational Accident in Mining and Quarry Sector toward Safe and Healthy Working Environment. International Journal of Current Research and Academic Review Special Issue – 1 pp. 95 – 102.

Ruff T., Coleman P. & Martini L. (2008). Machine related Injuries in the U.S Mining Industry and Priorities for Safety Research. National Institute for Occupational Safety and Health, Office of Mine Safety and Health Research, 315 E. Montgomery Ave., Spokane, WA99207, USA.

Kamardeen I. & Rameedeen R. (2015). Modelling accident Severity in the Construction Industry. Proc. Of the 32nd CIB W78 Conference, Eindhoven, The Netherlands.

Kamardeen I. (2009). Controlling Accidents and Insurers’ Risks in Construction: A Fuzzy Knowledge-based Approach. New York: Nova Science.

Dumrak J., Mostafa S., Kamardeen I. & Rameezdeen R. (2013). Factors associated with the severity ofconstruction accidents: the case of South Australia, Australasian Journal of Construction Econmicsand Building, 13(4), 32-49.

Felipe – Blancha J. J., Freijo-Alvarez. M., Alfonso. P., Sanmiquel. L., Sanchez. P & Vintro C. (2014). Occupational Injuries in the Mining Sectors (2000 - 2010), Comparison with the Construction Sector. Universidad Nacional de Colombia Sede Medellin Facultad de Minas, DYNA 81(186), pp. 153 – 158.

Ceylan H. (2012). Analysis of Occupational Accidents According to the Sectors in Turkey, Gazi University Journal of Science, GUJ Sci 25(4): 909 – 918 (2012).

MacNeill P. (2008). International Mining Fatality Database, Project Report. University of Wollongong.

Brzezinska J. (2013). Odds Ratio in the Analysis of Contingency Table, University of Economics, Katowice.

Osborne J. W. (2006). Bringing balance and technical accuracy to reporting Odds ratios and the results of logistic regression analyses. Practical Assessment research & Evaluation, a peer – reviewed electronic journal, vol. 11, No. 7. ISSN 153 – 7714.

Andresen M. A. (2009). The Odds ratio: what it is and why it should be used with caution. School of Criminology and Institute for Canadian Urban Research, Simon Fraser University.

Heinrich H. W., Peterson D. & Roos N. (1980). Industrial Accident Prevention, 5Th Edition, McGraw Hill, New York.

Bird F. E & Germain G. L. (1986). Practical Loss Control Leadership, International Loss Control Institute, Loganville, Georgia.

Peterson D. (1978). Techniques of Safety Management. 2nd Edition, McGraw Hill.

Pai M. (2015). Overview of Epidemiological Study Designs. McGill University, Montreal Canada.

Kanchanaraksa S. (2008). Bias and Confounding. Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University.

Mayo N. E. & Goldberg M. S. (2009). When is a Case – Control Study A Case – Control Study, Department of Medicine, Division of Clinical Epidemiology, McGill University, Montreal, Quebec, Canada.

Mosteller F. (1968). Association and Estimation in Contingency Tables. Journal of the American Statistical Association 63, 1-28.

Lamothe G. (2011). Adjusting the Mantel Haenszel Test Statistic and Odds Ratio for Cluster Sampling. Department of Mathematics and Statistics, University of Ottawa.

Brzezinska J. (2013). Odds Ratio in the Analysis of Contingency Table, University of Economics, Katowice.

Goodman, L. A., & Kruskal, W. H. (1954). Measures of Association for cross classifications. Journal of the American Statistical Association. (49) 732-769.

Rasmussen, J. (1982). Human Errors – A Taxonomy for Describing Human Malfunction in Industrial installations. Journal of Occupational Accidents, 4(2-4), 311-333. https://doi.org/10.1016/0376-6349(82)90041-4

Gyekye, S. A. (2003). Causal attributions of Ghanaian industrial workers for accident occurrence: Miners and non-miners perspective. J. Saf. Res. 34, 533–538.

Martín, J. E.; Rivas, T.; Matías, J.M.; Taboada, J.; Argüelles, A. (2009). A Bayesian network analysis of workplace accidents caused by falls from a height. Saf. Sci., 47, 206–214.

Zhang, Y.; Shao, W.; Zhang, M.; Li, H.; Yin, S.; Xu, Y. (2016). Analysis 320 coal mine accidents using structural equation modeling with unsafe conditions of the rules and regulations as exogenous variables. Accid. Anal. Prev. 92, 189–201.

Sanmiquel, L.; Rossell, J.M.; Vintró, C. (2015). Study of Spanish mining accidents using data mining techniques. Saf. Sci. 75, 49–55.




DOI: http://dx.doi.org/10.46827/ejphs.v3i2.25

Refbacks

  • There are currently no refbacks.


Copyright (c) 2019 Francis Frimpong, Kingsley Kwakye

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Copyright © 2019 - 2023. European Journal of Public Health Studies (ISSN 2668-1056/ISSN-L 2668-1056) is a registered trademark of Open Access Publishing Group. All rights reserved.

This journal is a serial publication uniquely identified by an International Standard Serial Number (ISSN) serial number certificate issued by Romanian National Library. All the research works are uniquely identified by a CrossRef DOI digital object identifier supplied by indexing and repository platforms. All the research works published on this journal are meeting the Open Access Publishing requirements and standards formulated by Budapest Open Access Initiative (2002), the Bethesda Statement on Open Access Publishing (2003) and Berlin Declaration on Open Access to Knowledge in the Sciences and Humanities (2003) and can be freely accessed, shared, modified, distributed and used in educational, commercial and non-commercial purposes under a Creative Commons Attribution 4.0 International License. Copyrights of the published research works are retained by authors.