Abstract
A retrospective study on accident analysis of the United States mines for 36 years was achieved using statistical analysis on the MSHA’s accident databases between 1983 and 2018. A regression model of generalized estimation equation (GEE) was used for unbalanced panel data that provided 95,812 observations for 19,924 mine-ID-year in aggregate, coal, metal, and nonmetal mines. The contributions of various parameters, including mine type, injured body part, days lost, age, and experience on the rate of accidents and injuries were investigated across the commodity types. The results showed coal miners in the East region are at a higher risk of an accident. The results of regression analysis show that mine-tenured workers have a vital role in accident frequencies. Analysis of the injured body part on the injury rate indicates that the upper body injuries are the most significant among all mine types. Also, the fatality rate is significant in aggregate and coal mines in comparison with metal and nonmetal mines.
| Original language | English |
|---|---|
| Article number | 3 |
| Pages (from-to) | 27-44 |
| Number of pages | 18 |
| Journal | Journal of Sustainable Mining |
| Volume | 21 |
| Issue number | 1 |
| DOIs | |
| State | Published - 2022 |
Bibliographical note
Publisher Copyright:© Central Mining Institute, Katowice, Poland.
Keywords
- Accident
- Generalized Estimation Equation (GEE)
- Mines
- Statistical analysis
ASJC Scopus subject areas
- Environmental Engineering
- Renewable Energy, Sustainability and the Environment
- Geotechnical Engineering and Engineering Geology
- Pollution
- Geology
