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Estimation of Lead Exposure Intensity by Industry Using Nationwide Exposure Databases in Korea

BACKGROUND: In a previous study, we estimated exposure prevalence and the number of workers exposed to carcinogens by industry in Korea. The present study aimed to evaluate the optimal exposure intensity indicators of airborne lead exposure by comparing to blood lead measurements for the future deve...

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Autores principales: Koh, Dong-Hee, Park, Ju-Hyun, Lee, Sang-Gil, Kim, Hwan-Cheol, Jung, Hyejung, Kim, Inah, Choi, Sangjun, Park, Donguk
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Occupational Safety and Health Research Institute 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8640577/
https://www.ncbi.nlm.nih.gov/pubmed/34900362
http://dx.doi.org/10.1016/j.shaw.2021.07.008
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author Koh, Dong-Hee
Park, Ju-Hyun
Lee, Sang-Gil
Kim, Hwan-Cheol
Jung, Hyejung
Kim, Inah
Choi, Sangjun
Park, Donguk
author_facet Koh, Dong-Hee
Park, Ju-Hyun
Lee, Sang-Gil
Kim, Hwan-Cheol
Jung, Hyejung
Kim, Inah
Choi, Sangjun
Park, Donguk
author_sort Koh, Dong-Hee
collection PubMed
description BACKGROUND: In a previous study, we estimated exposure prevalence and the number of workers exposed to carcinogens by industry in Korea. The present study aimed to evaluate the optimal exposure intensity indicators of airborne lead exposure by comparing to blood lead measurements for the future development of the carcinogen exposure intensity database. METHODS: Data concerning airborne lead measurements and blood lead levels were collected from nationwide occupational exposure databases, compiled between 2015 and 2016. Summary statistics, including the arithmetic mean (AM), geometric mean (GM), and 95th percentile level (X95) were calculated by industry both for airborne lead and blood lead measurements. Since many measurements were below the limits of detection (LODs), the simple replacement with half of the LOD and maximum likelihood estimation (MLE) methods were used for statistical analysis. For examining the optimal exposure indicator of airborne lead exposure, blood lead levels were used as reference data for subsequent rank correlation analyses. RESULTS: A total of 19,637 airborne lead measurements and 32,848 blood lead measurements were used. In general, simple replacement showed a higher correlation than MLE. The results showed that AM and X95 using simple replacement could be used as optimal exposure intensity indicators, while X95 showed better correlations than AM in industries with 20 or more measurements. CONCLUSION: Our results showed that AM or X95 could be potential candidates for exposure intensity indicators in the Korean carcinogen exposure database. Especially, X95 is an optimal indicator where there are enough measurements to compute X95 values.
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spelling pubmed-86405772021-12-10 Estimation of Lead Exposure Intensity by Industry Using Nationwide Exposure Databases in Korea Koh, Dong-Hee Park, Ju-Hyun Lee, Sang-Gil Kim, Hwan-Cheol Jung, Hyejung Kim, Inah Choi, Sangjun Park, Donguk Saf Health Work Original Article BACKGROUND: In a previous study, we estimated exposure prevalence and the number of workers exposed to carcinogens by industry in Korea. The present study aimed to evaluate the optimal exposure intensity indicators of airborne lead exposure by comparing to blood lead measurements for the future development of the carcinogen exposure intensity database. METHODS: Data concerning airborne lead measurements and blood lead levels were collected from nationwide occupational exposure databases, compiled between 2015 and 2016. Summary statistics, including the arithmetic mean (AM), geometric mean (GM), and 95th percentile level (X95) were calculated by industry both for airborne lead and blood lead measurements. Since many measurements were below the limits of detection (LODs), the simple replacement with half of the LOD and maximum likelihood estimation (MLE) methods were used for statistical analysis. For examining the optimal exposure indicator of airborne lead exposure, blood lead levels were used as reference data for subsequent rank correlation analyses. RESULTS: A total of 19,637 airborne lead measurements and 32,848 blood lead measurements were used. In general, simple replacement showed a higher correlation than MLE. The results showed that AM and X95 using simple replacement could be used as optimal exposure intensity indicators, while X95 showed better correlations than AM in industries with 20 or more measurements. CONCLUSION: Our results showed that AM or X95 could be potential candidates for exposure intensity indicators in the Korean carcinogen exposure database. Especially, X95 is an optimal indicator where there are enough measurements to compute X95 values. Occupational Safety and Health Research Institute 2021-12 2021-07-17 /pmc/articles/PMC8640577/ /pubmed/34900362 http://dx.doi.org/10.1016/j.shaw.2021.07.008 Text en © 2021 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Original Article
Koh, Dong-Hee
Park, Ju-Hyun
Lee, Sang-Gil
Kim, Hwan-Cheol
Jung, Hyejung
Kim, Inah
Choi, Sangjun
Park, Donguk
Estimation of Lead Exposure Intensity by Industry Using Nationwide Exposure Databases in Korea
title Estimation of Lead Exposure Intensity by Industry Using Nationwide Exposure Databases in Korea
title_full Estimation of Lead Exposure Intensity by Industry Using Nationwide Exposure Databases in Korea
title_fullStr Estimation of Lead Exposure Intensity by Industry Using Nationwide Exposure Databases in Korea
title_full_unstemmed Estimation of Lead Exposure Intensity by Industry Using Nationwide Exposure Databases in Korea
title_short Estimation of Lead Exposure Intensity by Industry Using Nationwide Exposure Databases in Korea
title_sort estimation of lead exposure intensity by industry using nationwide exposure databases in korea
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8640577/
https://www.ncbi.nlm.nih.gov/pubmed/34900362
http://dx.doi.org/10.1016/j.shaw.2021.07.008
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