An analysis of contributing mining factors in coal workers’ pneumoconiosis prevalence in the United States coal mines, 1986–2018
In the United States, an unexpected and severe increase in coal miners’ lung diseases in the late 1990s prompted researchers to investigate the causes of the disease resurgence. This study aims to scrutinize the effects of various mining parameters, including coal rank, mine size, mine operation typ...
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Veröffentlicht in: | International journal of coal science & technology 2021-12, Vol.8 (6), p.1227-1237 |
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description | In the United States, an unexpected and severe increase in coal miners’ lung diseases in the late 1990s prompted researchers to investigate the causes of the disease resurgence. This study aims to scrutinize the effects of various mining parameters, including coal rank, mine size, mine operation type, coal seam height, and geographical location on the prevalence of coal worker's pneumoconiosis (CWP) in surface and underground coal mines. A comprehensive dataset was created using the U.S. Mine Safety and Health Administration (MSHA) Employment and Accident/Injury databases. The information was merged based on the mine ID by utilizing SQL data management software. A total number of 123,589 mine-year observations were included in the statistical analysis. Generalized Estimating Equation (GEE) model was used to conduct a statistical analysis on a total of 29,707, and 32,643 mine-year observations for underground and surface coal mines, respectively. The results of the econometrics approach revealed that coal workers in underground coal mines are at a greater risk of CWP comparing to those of surface coal operations. Furthermore, underground coal mines in the Appalachia and Interior regions are at a higher risk of CWP prevalence than the Western region. Surface coal mines in the Appalachian coal region are more likely to CWP development than miners in the Western region. The analysis also indicated that coal workers working in smaller mines are more vulnerable to CWP than those in large mine sizes. Furthermore, coal workers in thin-seam underground mine operations are more likely to develop CWP. |
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This study aims to scrutinize the effects of various mining parameters, including coal rank, mine size, mine operation type, coal seam height, and geographical location on the prevalence of coal worker's pneumoconiosis (CWP) in surface and underground coal mines. A comprehensive dataset was created using the U.S. Mine Safety and Health Administration (MSHA) Employment and Accident/Injury databases. The information was merged based on the mine ID by utilizing SQL data management software. A total number of 123,589 mine-year observations were included in the statistical analysis. Generalized Estimating Equation (GEE) model was used to conduct a statistical analysis on a total of 29,707, and 32,643 mine-year observations for underground and surface coal mines, respectively. The results of the econometrics approach revealed that coal workers in underground coal mines are at a greater risk of CWP comparing to those of surface coal operations. Furthermore, underground coal mines in the Appalachia and Interior regions are at a higher risk of CWP prevalence than the Western region. Surface coal mines in the Appalachian coal region are more likely to CWP development than miners in the Western region. The analysis also indicated that coal workers working in smaller mines are more vulnerable to CWP than those in large mine sizes. Furthermore, coal workers in thin-seam underground mine operations are more likely to develop CWP.</description><identifier>ISSN: 2095-8293</identifier><identifier>EISSN: 2198-7823</identifier><identifier>DOI: 10.1007/s40789-021-00464-y</identifier><language>eng</language><publisher>Singapore: Springer Singapore</publisher><subject>Analysis ; Coal industry ; Coal miners ; Coal mines ; Coal mining ; Data management ; Disease susceptibility ; Energy ; Fossil Fuels (incl. 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This study aims to scrutinize the effects of various mining parameters, including coal rank, mine size, mine operation type, coal seam height, and geographical location on the prevalence of coal worker's pneumoconiosis (CWP) in surface and underground coal mines. A comprehensive dataset was created using the U.S. Mine Safety and Health Administration (MSHA) Employment and Accident/Injury databases. The information was merged based on the mine ID by utilizing SQL data management software. A total number of 123,589 mine-year observations were included in the statistical analysis. Generalized Estimating Equation (GEE) model was used to conduct a statistical analysis on a total of 29,707, and 32,643 mine-year observations for underground and surface coal mines, respectively. The results of the econometrics approach revealed that coal workers in underground coal mines are at a greater risk of CWP comparing to those of surface coal operations. Furthermore, underground coal mines in the Appalachia and Interior regions are at a higher risk of CWP prevalence than the Western region. Surface coal mines in the Appalachian coal region are more likely to CWP development than miners in the Western region. The analysis also indicated that coal workers working in smaller mines are more vulnerable to CWP than those in large mine sizes. Furthermore, coal workers in thin-seam underground mine operations are more likely to develop CWP.</description><subject>Analysis</subject><subject>Coal industry</subject><subject>Coal miners</subject><subject>Coal mines</subject><subject>Coal mining</subject><subject>Data management</subject><subject>Disease susceptibility</subject><subject>Energy</subject><subject>Fossil Fuels (incl. Carbon Capture)</subject><subject>Geotechnical Engineering & Applied Earth Sciences</subject><subject>Medical research</subject><subject>Medicine, Experimental</subject><subject>Mineral industry</subject><subject>Mineral Resources</subject><subject>Mines</subject><subject>Mining accidents & safety</subject><subject>Mining industry</subject><subject>Pneumoconiosis</subject><subject>Rankings</subject><subject>Research Article</subject><subject>Statistical analysis</subject><subject>Workers</subject><issn>2095-8293</issn><issn>2198-7823</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>C6C</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNp9kc1q3DAUhU1poSHNC3Ql6KpQp1c_lu3lEPoTCBSSZi1U-WqqdCxNJbnt7LLIG2TV18uTVK4DYSAELSSk71x0zqmq1xSOKUD7Pglou74GRmsAIUW9e1YdMNp3ddsx_rycoW_qjvX8ZXWU0hUAUNEzQcVBdbPyRHu92SWXSLDEBJ-j-zZl59dkdH7erDY5xEScL896Q36H-ANjurv-S7YepzEUkQvzgG3EX3qD3uAM5-9ILr3LOJCLrDOmRV6mYnpHyv_k3fUtA9q9ql5YvUl4dL8fVpcfP3w9-Vyfffl0erI6q01xleuGd9iybkABMBjGG9swqTUw3oLWaIdBNhYosMG0ugHBZV_oTvLW6ob2kh9Wb5a52xh-TpiyugpTLO6TYrIkJ0uO9IFaFyvKeRty1GZ0yaiV7ATvG9nzQh0_QpU14OhKIGhdud8TvN0TzEnjn7zWU0rq9OJ8n2ULa2JIKaJV2-hGHXeKgpo7V0vnqnSu_neudkXEF1EqsF9jfHD3hOofh3iuzQ</recordid><startdate>20211201</startdate><enddate>20211201</enddate><creator>Shekarian, Younes</creator><creator>Rahimi, Elham</creator><creator>Shekarian, Naser</creator><creator>Rezaee, Mohammad</creator><creator>Roghanchi, Pedram</creator><general>Springer Singapore</general><general>Springer</general><general>Springer Nature B.V</general><scope>C6C</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>ISR</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>PCBAR</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><orcidid>https://orcid.org/0000-0003-4696-8845</orcidid></search><sort><creationdate>20211201</creationdate><title>An analysis of contributing mining factors in coal workers’ pneumoconiosis prevalence in the United States coal mines, 1986–2018</title><author>Shekarian, Younes ; Rahimi, Elham ; Shekarian, Naser ; Rezaee, Mohammad ; Roghanchi, Pedram</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c464t-538e728de400dc235f526aa02370aaefdd65f0102dc7a50436928d8637fa51963</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Analysis</topic><topic>Coal industry</topic><topic>Coal miners</topic><topic>Coal mines</topic><topic>Coal mining</topic><topic>Data management</topic><topic>Disease susceptibility</topic><topic>Energy</topic><topic>Fossil Fuels (incl. 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This study aims to scrutinize the effects of various mining parameters, including coal rank, mine size, mine operation type, coal seam height, and geographical location on the prevalence of coal worker's pneumoconiosis (CWP) in surface and underground coal mines. A comprehensive dataset was created using the U.S. Mine Safety and Health Administration (MSHA) Employment and Accident/Injury databases. The information was merged based on the mine ID by utilizing SQL data management software. A total number of 123,589 mine-year observations were included in the statistical analysis. Generalized Estimating Equation (GEE) model was used to conduct a statistical analysis on a total of 29,707, and 32,643 mine-year observations for underground and surface coal mines, respectively. The results of the econometrics approach revealed that coal workers in underground coal mines are at a greater risk of CWP comparing to those of surface coal operations. Furthermore, underground coal mines in the Appalachia and Interior regions are at a higher risk of CWP prevalence than the Western region. Surface coal mines in the Appalachian coal region are more likely to CWP development than miners in the Western region. The analysis also indicated that coal workers working in smaller mines are more vulnerable to CWP than those in large mine sizes. Furthermore, coal workers in thin-seam underground mine operations are more likely to develop CWP.</abstract><cop>Singapore</cop><pub>Springer Singapore</pub><doi>10.1007/s40789-021-00464-y</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0003-4696-8845</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Analysis Coal industry Coal miners Coal mines Coal mining Data management Disease susceptibility Energy Fossil Fuels (incl. Carbon Capture) Geotechnical Engineering & Applied Earth Sciences Medical research Medicine, Experimental Mineral industry Mineral Resources Mines Mining accidents & safety Mining industry Pneumoconiosis Rankings Research Article Statistical analysis Workers |
title | An analysis of contributing mining factors in coal workers’ pneumoconiosis prevalence in the United States coal mines, 1986–2018 |
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