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    Loglinear Model for Assessment of Risk Factors of Occupational Injuries in Underground Coal Mines

    197669_110391_jgmr_article1379425336_Ghosh_and_Bhattacherjee.pdf (93.33Kb)
    Access Status
    Open access
    Authors
    Ghosh, Apurna
    Bhattacherjee, Ashis
    Date
    2009
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Ghosh, Apurna and Bhattacherjee, Ashis. 2009. Loglinear Model for Assessment of Risk Factors of Occupational Injuries in Underground Coal Mines. Journal of Geology and Mining Research. 1 (2): pp. 25-33.
    Source Title
    Journal of Geology and Mining Research
    Additional URLs
    http://www.academicjournals.org/journal/JGMR/article-abstract/346FD081270
    ISSN
    2006-9766
    Remarks

    This article is published under the Open Access publishing model and distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/deed.en_US. Please refer to the licence to obtain terms for any further reuse or distribution of this work.

    URI
    http://hdl.handle.net/20.500.11937/17153
    Collection
    • Curtin Research Publications
    Abstract

    In this study a loglinear model has been investigated to evaluate the role of various factors in coal mine injuries. Data on the varieties namely age, safety performance, working condition, safety environment, management and supervision, emotional stability, job involvement, job satisfaction, and job stress have been collected through questionnaire survey. The associations of the risk factors with occupational injuries are assessed through adjusted odds ratios (OR). The case study results reveal that significant contributing factors responsible for injuries are emotional stability (OR 2.36, 95% confidence interval(CI) 1.51-3.67), working condition (OR 2.14, 95% CI 1.37-3.35), safety performance (OR 2.04, 95% CI 1.30-3.17), safety environment (OR 1.96, 95% CI 1.25-3.06), and age with two ORs of 1.84 (95% CI 1.04 to 3.28), and 2.38 (95% CI 1.27 to 4.45). Identification of these risk factors of injuries will provide valuable information in injury preventive programs.

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