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Citation |
Wang C, Wang J, Wang X, Yu H, Bai L, Sun Q. Safety Sci. 2019; 115: 339-348. |
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Copyright |
(Copyright © 2019, Elsevier Publishing) |
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DOI |
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PMID |
unavailable |
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Abstract |
Currently, it is reported that approximately 1000 occupational injuries, especially the front-line miners occurring the coal industry of China in 2015. Previous researches have indicated that miners' unsafe behavior is the predominant reason of safety accidents and listed numerous factors which influence their behavior. Owing to the complexities of the relationship among these influencing factors in the coal industry, the improvement of coal mine safety level is still facing enormous challenges. With an aim towards exploring and sorting the influencing factors for increasing safety behavior or reducing unsafe behavior, a cross-sectional survey which lasted three months was conducted on 1590 front-line coal miners from seven mining areas in Shandong province, China. Principal component analysis (PCA), binary logistic regression (BLR) and Poisson regression (PR) were selected as analytical techniques. In order to eliminate the correlation and collinearity among independent variables, PCA was used firstly. Then, as the core method, BLR was introduced to estimate relationships between different components and coal miners' unsafe behavior. In addition, we also concluded that coal miners who are younger and less experienced are more likely to behave safely through the results of PR. On the basis of the above results, we highlighted the useful measures, such as strengthening the safety education and training of miners, building safety climate and grasping the rationality of management system, which might motivate miners' safety behavior. Language: en |
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Keywords |
Binary logistic regression; Coal miners; Principal component analysis; Safety behavior |