Environmental risk score of multiple pollutants for kidney damage among residents in vulnerable areas by occupational chemical exposure in Korea
This study aimed to develop an environmental risk score (ERS) of multiple pollutants (MP) causing kidney damage (KD) in Korean residents near abandoned metal mines or smelters and evaluate the association between ERS and KD by a history of occupational chemical exposure (OCE). Exposure to MP, consis...
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| Veröffentlicht in: | Environmental science and pollution research international 2024-05, Vol.31 (24), p.35938-35951 |
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| creator | Jang, Hyuna Choi, Kyung-Hwa Cho, Yong Min Han, Dahee Hong, Young Seoub |
| description | This study aimed to develop an environmental risk score (ERS) of multiple pollutants (MP) causing kidney damage (KD) in Korean residents near abandoned metal mines or smelters and evaluate the association between ERS and KD by a history of occupational chemical exposure (OCE). Exposure to MP, consisting of nine metals, four polycyclic aromatic hydrocarbons, and four volatile organic compounds, was measured as urinary metabolites. The study participants were recruited from the Forensic Research via Omics Markers (FROM) study (
n
= 256). Beta-2-microglobulin (β2-MG), N-acetyl-β-D-glucosaminidase (NAG), and estimated glomerular filtration rate (eGFR) were used as biomarkers of KD. Bayesian kernel machine regression (BKMR) was selected as the optimal ERS model with the best performance and stability of the predicted effect size among the elastic net, adaptive elastic net, weighted quantile sum regression, BKMR, Bayesian additive regression tree, and super learner model. Variable importance was estimated to evaluate the effects of metabolites on KD. When stratified with the history of OCE after adjusting for several confounding factors, the risks for KD were higher in the OCE group than those in the non-OCE group; the odds ratio (OR; 95% CI) for ERS in non-OCE and OCE groups were 2.97 (2.19, 4.02) and 6.43 (2.85, 14.5) for β2-MG, 1.37 (1.01, 1.86) and 4.16 (1.85, 9.39) for NAG, and 4.57 (3.37, 6.19) and 6.44 (2.85, 14.5) for eGFR, respectively. We found that the ERS stratified history of OCE was the most suitable for evaluating the association between MP and KD, and the risks were higher in the OCE group than those in the non-OCE group. |
| doi_str_mv | 10.1007/s11356-024-33567-5 |
| format | Article |
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n
= 256). Beta-2-microglobulin (β2-MG), N-acetyl-β-D-glucosaminidase (NAG), and estimated glomerular filtration rate (eGFR) were used as biomarkers of KD. Bayesian kernel machine regression (BKMR) was selected as the optimal ERS model with the best performance and stability of the predicted effect size among the elastic net, adaptive elastic net, weighted quantile sum regression, BKMR, Bayesian additive regression tree, and super learner model. Variable importance was estimated to evaluate the effects of metabolites on KD. When stratified with the history of OCE after adjusting for several confounding factors, the risks for KD were higher in the OCE group than those in the non-OCE group; the odds ratio (OR; 95% CI) for ERS in non-OCE and OCE groups were 2.97 (2.19, 4.02) and 6.43 (2.85, 14.5) for β2-MG, 1.37 (1.01, 1.86) and 4.16 (1.85, 9.39) for NAG, and 4.57 (3.37, 6.19) and 6.44 (2.85, 14.5) for eGFR, respectively. We found that the ERS stratified history of OCE was the most suitable for evaluating the association between MP and KD, and the risks were higher in the OCE group than those in the non-OCE group.</description><identifier>ISSN: 1614-7499</identifier><identifier>ISSN: 0944-1344</identifier><identifier>EISSN: 1614-7499</identifier><identifier>DOI: 10.1007/s11356-024-33567-5</identifier><identifier>PMID: 38743333</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Abandoned mines ; Adult ; Aquatic Pollution ; Atmospheric Protection/Air Quality Control/Air Pollution ; Bayes Theorem ; Bayesian analysis ; Bayesian theory ; Biomarkers ; Biomarkers - urine ; Damage ; Earth and Environmental Science ; Ecotoxicology ; Environment ; Environmental Chemistry ; Environmental Health ; Environmental Pollutants ; Environmental risk ; Epidermal growth factor receptors ; Exposure ; Female ; forensic sciences ; Glomerular Filtration Rate ; Glucosaminidase ; Humans ; Kidney Diseases - chemically induced ; Kidney Diseases - epidemiology ; Kidneys ; Korean Peninsula ; Male ; Metabolites ; Metals ; Middle Aged ; Occupational Exposure ; odds ratio ; Organic compounds ; Pollutants ; Polycyclic aromatic hydrocarbons ; Regression analysis ; Republic of Korea ; Research Article ; risk ; Risk Assessment ; Smelters ; VOCs ; Volatile hydrocarbons ; Volatile organic compounds ; Waste Water Technology ; Water Management ; Water Pollution Control ; β2 Microglobulin</subject><ispartof>Environmental science and pollution research international, 2024-05, Vol.31 (24), p.35938-35951</ispartof><rights>The Author(s) 2024</rights><rights>2024. The Author(s).</rights><rights>The Author(s) 2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c3745-723f14fd60220354fe21efabf49ed4b6d676d75e5593117b3aa91e07e2245f563</cites><orcidid>0000-0001-8206-4574</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s11356-024-33567-5$$EPDF$$P50$$Gspringer$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s11356-024-33567-5$$EHTML$$P50$$Gspringer$$Hfree_for_read</linktohtml><link.rule.ids>230,314,776,780,881,27901,27902,41464,42533,51294</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/38743333$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Jang, Hyuna</creatorcontrib><creatorcontrib>Choi, Kyung-Hwa</creatorcontrib><creatorcontrib>Cho, Yong Min</creatorcontrib><creatorcontrib>Han, Dahee</creatorcontrib><creatorcontrib>Hong, Young Seoub</creatorcontrib><title>Environmental risk score of multiple pollutants for kidney damage among residents in vulnerable areas by occupational chemical exposure in Korea</title><title>Environmental science and pollution research international</title><addtitle>Environ Sci Pollut Res</addtitle><addtitle>Environ Sci Pollut Res Int</addtitle><description>This study aimed to develop an environmental risk score (ERS) of multiple pollutants (MP) causing kidney damage (KD) in Korean residents near abandoned metal mines or smelters and evaluate the association between ERS and KD by a history of occupational chemical exposure (OCE). Exposure to MP, consisting of nine metals, four polycyclic aromatic hydrocarbons, and four volatile organic compounds, was measured as urinary metabolites. The study participants were recruited from the Forensic Research via Omics Markers (FROM) study (
n
= 256). Beta-2-microglobulin (β2-MG), N-acetyl-β-D-glucosaminidase (NAG), and estimated glomerular filtration rate (eGFR) were used as biomarkers of KD. Bayesian kernel machine regression (BKMR) was selected as the optimal ERS model with the best performance and stability of the predicted effect size among the elastic net, adaptive elastic net, weighted quantile sum regression, BKMR, Bayesian additive regression tree, and super learner model. Variable importance was estimated to evaluate the effects of metabolites on KD. When stratified with the history of OCE after adjusting for several confounding factors, the risks for KD were higher in the OCE group than those in the non-OCE group; the odds ratio (OR; 95% CI) for ERS in non-OCE and OCE groups were 2.97 (2.19, 4.02) and 6.43 (2.85, 14.5) for β2-MG, 1.37 (1.01, 1.86) and 4.16 (1.85, 9.39) for NAG, and 4.57 (3.37, 6.19) and 6.44 (2.85, 14.5) for eGFR, respectively. We found that the ERS stratified history of OCE was the most suitable for evaluating the association between MP and KD, and the risks were higher in the OCE group than those in the non-OCE group.</description><subject>Abandoned mines</subject><subject>Adult</subject><subject>Aquatic Pollution</subject><subject>Atmospheric Protection/Air Quality Control/Air Pollution</subject><subject>Bayes Theorem</subject><subject>Bayesian analysis</subject><subject>Bayesian theory</subject><subject>Biomarkers</subject><subject>Biomarkers - urine</subject><subject>Damage</subject><subject>Earth and Environmental Science</subject><subject>Ecotoxicology</subject><subject>Environment</subject><subject>Environmental Chemistry</subject><subject>Environmental Health</subject><subject>Environmental Pollutants</subject><subject>Environmental risk</subject><subject>Epidermal growth factor receptors</subject><subject>Exposure</subject><subject>Female</subject><subject>forensic sciences</subject><subject>Glomerular Filtration Rate</subject><subject>Glucosaminidase</subject><subject>Humans</subject><subject>Kidney Diseases - chemically induced</subject><subject>Kidney Diseases - epidemiology</subject><subject>Kidneys</subject><subject>Korean Peninsula</subject><subject>Male</subject><subject>Metabolites</subject><subject>Metals</subject><subject>Middle Aged</subject><subject>Occupational Exposure</subject><subject>odds ratio</subject><subject>Organic compounds</subject><subject>Pollutants</subject><subject>Polycyclic aromatic hydrocarbons</subject><subject>Regression analysis</subject><subject>Republic of Korea</subject><subject>Research Article</subject><subject>risk</subject><subject>Risk Assessment</subject><subject>Smelters</subject><subject>VOCs</subject><subject>Volatile hydrocarbons</subject><subject>Volatile organic compounds</subject><subject>Waste Water Technology</subject><subject>Water Management</subject><subject>Water Pollution Control</subject><subject>β2 Microglobulin</subject><issn>1614-7499</issn><issn>0944-1344</issn><issn>1614-7499</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>C6C</sourceid><sourceid>EIF</sourceid><recordid>eNqFks1u1DAUhS1ERcvAC7BAltiwCfjfkxVCVfkRlbopa8tJrqduHTvYyYh5Cx4ZD1NKYUG98ZXud8-5tg5CLyh5QwnRbwulXKqGMNHwWuhGPkInVFHRaNG2j-_Vx-hpKdeEMNIy_QQd87UWvJ4T9OMsbn1OcYQ424CzLze49CkDTg6PS5j9FABPKYRltnEu2KWMb_wQYYcHO9oNYDumuMEZih9gT_iIt0uIkG1XR20GW3C3w6nvl8nOPsXq01_B6PtawPcplaXa1akv1dY-Q0fOhgLPb-8V-vrh7PL0U3N-8fHz6fvzpudayEYz7qhwgyKMES6FA0bB2c6JFgbRqUFpNWgJUracUt1xa1sKRANjQjqp-Aq9O-hOSzfC0NfVsw1myn60eWeS9ebvTvRXZpO2htZfV2u-V3h9q5DTtwXKbEZfegjBRkhLMZxKrpQmLXkYJVIKyXSVXqFX_6DXacn1z_aUqpJrIdeVYgeqz6mUDO5ucUrMPhzmEA5Tw2F-hcPIOvTy_pPvRn6noQL8AJTaihvIf7z_I_sT6DPHzw</recordid><startdate>20240501</startdate><enddate>20240501</enddate><creator>Jang, Hyuna</creator><creator>Choi, Kyung-Hwa</creator><creator>Cho, Yong Min</creator><creator>Han, Dahee</creator><creator>Hong, Young Seoub</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>C6C</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QL</scope><scope>7SN</scope><scope>7T7</scope><scope>7TV</scope><scope>7U7</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>K9.</scope><scope>M7N</scope><scope>P64</scope><scope>7X8</scope><scope>7S9</scope><scope>L.6</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0001-8206-4574</orcidid></search><sort><creationdate>20240501</creationdate><title>Environmental risk score of multiple pollutants for kidney damage among residents in vulnerable areas by occupational chemical exposure in Korea</title><author>Jang, Hyuna ; 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Exposure to MP, consisting of nine metals, four polycyclic aromatic hydrocarbons, and four volatile organic compounds, was measured as urinary metabolites. The study participants were recruited from the Forensic Research via Omics Markers (FROM) study (
n
= 256). Beta-2-microglobulin (β2-MG), N-acetyl-β-D-glucosaminidase (NAG), and estimated glomerular filtration rate (eGFR) were used as biomarkers of KD. Bayesian kernel machine regression (BKMR) was selected as the optimal ERS model with the best performance and stability of the predicted effect size among the elastic net, adaptive elastic net, weighted quantile sum regression, BKMR, Bayesian additive regression tree, and super learner model. Variable importance was estimated to evaluate the effects of metabolites on KD. When stratified with the history of OCE after adjusting for several confounding factors, the risks for KD were higher in the OCE group than those in the non-OCE group; the odds ratio (OR; 95% CI) for ERS in non-OCE and OCE groups were 2.97 (2.19, 4.02) and 6.43 (2.85, 14.5) for β2-MG, 1.37 (1.01, 1.86) and 4.16 (1.85, 9.39) for NAG, and 4.57 (3.37, 6.19) and 6.44 (2.85, 14.5) for eGFR, respectively. We found that the ERS stratified history of OCE was the most suitable for evaluating the association between MP and KD, and the risks were higher in the OCE group than those in the non-OCE group.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><pmid>38743333</pmid><doi>10.1007/s11356-024-33567-5</doi><tpages>14</tpages><orcidid>https://orcid.org/0000-0001-8206-4574</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Abandoned mines Adult Aquatic Pollution Atmospheric Protection/Air Quality Control/Air Pollution Bayes Theorem Bayesian analysis Bayesian theory Biomarkers Biomarkers - urine Damage Earth and Environmental Science Ecotoxicology Environment Environmental Chemistry Environmental Health Environmental Pollutants Environmental risk Epidermal growth factor receptors Exposure Female forensic sciences Glomerular Filtration Rate Glucosaminidase Humans Kidney Diseases - chemically induced Kidney Diseases - epidemiology Kidneys Korean Peninsula Male Metabolites Metals Middle Aged Occupational Exposure odds ratio Organic compounds Pollutants Polycyclic aromatic hydrocarbons Regression analysis Republic of Korea Research Article risk Risk Assessment Smelters VOCs Volatile hydrocarbons Volatile organic compounds Waste Water Technology Water Management Water Pollution Control β2 Microglobulin |
| title | Environmental risk score of multiple pollutants for kidney damage among residents in vulnerable areas by occupational chemical exposure in Korea |
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