Developing Asbestos Job Exposure Matrix Using Occupation and Industry Specific Exposure Data (1984-2008) in Republic of Korea
Background: The goal of this study is to develop a general population job-exposure matrix (GPJEM) on asbestos to estimate occupational asbestos exposure levels in the Republic of Korea. Methods: Three Korean domestic quantitative exposure datasets collected from 1984 to 2008 were used to build the G...
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Published in | Safety and health at work Vol. 8; no. 1; pp. 105 - 115 |
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Main Authors | , , , , |
Format | Journal Article |
Language | Korean |
Published |
2017
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Subjects | |
Online Access | Get full text |
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Summary: | Background: The goal of this study is to develop a general population job-exposure matrix (GPJEM) on asbestos to estimate occupational asbestos exposure levels in the Republic of Korea. Methods: Three Korean domestic quantitative exposure datasets collected from 1984 to 2008 were used to build the GPJEM. Exposure groups in collected data were reclassified based on the current Korean Standard Industrial Classification ($9^{th}$ edition) and the Korean Standard Classification of Occupations code ($6^{th}$ edition) that is in accordance to international standards. All of the exposure levels were expressed by weighted arithmetic mean (WAM) and minimum and maximum concentrations. Results: Based on the established GPJEM, the 112 exposure groups could be reclassified into 86 industries and 74 occupations. In the 1980s, the highest exposure levels were estimated in "knitting and weaving machine operators" with a WAM concentration of 7.48 fibers/mL (f/mL); in the 1990s, "plastic products production machine operators" with 5.12 f/mL, and in the 2000s "detergents production machine operators" handling talc containing asbestos with 2.45 f/mL. Of the 112 exposure groups, 44 groups had higher WAM concentrations than the Korean occupational exposure limit of 0.1 f/mL. Conclusion: The newly constructed GPJEM which is generated from actual domestic quantitative exposure data could be useful in evaluating historical exposure levels to asbestos and could contribute to improved prediction of asbestos-related diseases among Koreans. |
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Bibliography: | KISTI1.1003/JNL.JAKO201718155358792 |
ISSN: | 2093-7911 2093-7997 |