Abnormal erythrocyte-related parameters in children with Pb, Cr, Cu and Zn exposure
The link between exposure to a particular heavy metal or metalloid and the development of anemia is well established. However, the association between combined exposure to multiple heavy metal(loid)s and anemia in children is still lacking in evidence. In this study, a total of 266 children aged 3 t...
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description | The link between exposure to a particular heavy metal or metalloid and the development of anemia is well established. However, the association between combined exposure to multiple heavy metal(loid)s and anemia in children is still lacking in evidence. In this study, a total of 266 children aged 3 to 7 were recruited from Guiyu, China. Inductively coupled plasma mass spectrometry (ICP-MS) was used to measure blood heavy metal(loid) concentrations. Blood cell count, hemoglobin (HGB), mean corpuscular hemoglobin (MCH), mean corpuscular volume (MCV), mean corpuscular hemoglobin concentration (MCHC), hematocrit (HCT), and red blood cell distribution width (RDW) were measured by an automated hematology analyzer. Erythrocyte-related parameters were negatively correlated with the Cu and Cu/Zn ratios and positively correlated with Cr, Ni, Zn, and Se by Spearman correlation analysis. Only blood Cu level was negatively correlated with HGB [β = −2.74, (95% Cl: −4.49, −0.995)], MCH [β = −0.505, (95% Cl: −0.785, −0.226)], MCV [β = −1.024, (95% Cl: −1.767, −0.281)], and MCHC [β = −2.137, (95% Cl: −3.54, −0.734)] by multiple linear regression analysis. The Bayesian Kernel Machine Regression (BKMR) model analysis indicated a negative correlation between the combined exposure to Cu, Zn, Pb, and Cr and MCH and MCV. The single-factor analysis showed a considerable statistical difference only with Cu on MCV, MCH, and HGB. Furthermore, the interaction analysis highlighted the interdependent effects of Cu and Zn, Pb and Zn, and Cr and Zn on MCH and MCV levels. Additionally, the oxidation and/or antioxidation reactions may play a significant role in the development of metal(loid)-induced anemia risk. It is crucial to investigate the effects of co-exposure to multiple heavy metal(loid) elements on anemia, especially the interrelationships and mechanisms among them. |
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However, the association between combined exposure to multiple heavy metal(loid)s and anemia in children is still lacking in evidence. In this study, a total of 266 children aged 3 to 7 were recruited from Guiyu, China. Inductively coupled plasma mass spectrometry (ICP-MS) was used to measure blood heavy metal(loid) concentrations. Blood cell count, hemoglobin (HGB), mean corpuscular hemoglobin (MCH), mean corpuscular volume (MCV), mean corpuscular hemoglobin concentration (MCHC), hematocrit (HCT), and red blood cell distribution width (RDW) were measured by an automated hematology analyzer. Erythrocyte-related parameters were negatively correlated with the Cu and Cu/Zn ratios and positively correlated with Cr, Ni, Zn, and Se by Spearman correlation analysis. Only blood Cu level was negatively correlated with HGB [β = −2.74, (95% Cl: −4.49, −0.995)], MCH [β = −0.505, (95% Cl: −0.785, −0.226)], MCV [β = −1.024, (95% Cl: −1.767, −0.281)], and MCHC [β = −2.137, (95% Cl: −3.54, −0.734)] by multiple linear regression analysis. The Bayesian Kernel Machine Regression (BKMR) model analysis indicated a negative correlation between the combined exposure to Cu, Zn, Pb, and Cr and MCH and MCV. The single-factor analysis showed a considerable statistical difference only with Cu on MCV, MCH, and HGB. Furthermore, the interaction analysis highlighted the interdependent effects of Cu and Zn, Pb and Zn, and Cr and Zn on MCH and MCV levels. Additionally, the oxidation and/or antioxidation reactions may play a significant role in the development of metal(loid)-induced anemia risk. It is crucial to investigate the effects of co-exposure to multiple heavy metal(loid) elements on anemia, especially the interrelationships and mechanisms among them.</description><identifier>ISSN: 0966-0844</identifier><identifier>ISSN: 1572-8773</identifier><identifier>EISSN: 1572-8773</identifier><identifier>DOI: 10.1007/s10534-024-00624-y</identifier><identifier>PMID: 39154116</identifier><language>eng</language><publisher>Dordrecht: Springer Netherlands</publisher><subject>Anemia ; Bayesian analysis ; Biochemistry ; Biomedical and Life Sciences ; Blood ; Blood levels ; Cell Biology ; Child ; Child, Preschool ; Children ; Chromium ; Chromium - blood ; Copper ; Copper - blood ; Correlation analysis ; Erythrocyte Indices ; Erythrocytes ; Erythrocytes, Abnormal - pathology ; Exposure ; Factor analysis ; Female ; Heavy metals ; Hematocrit ; Hematology ; Hemoglobin ; Humans ; Inductively coupled plasma mass spectrometry ; Lead ; Lead - blood ; Life Sciences ; Male ; Mass spectrometry ; Mass spectroscopy ; Medicine/Public Health ; Metal concentrations ; Metals, Heavy - blood ; Microbiology ; Oxidation ; Parameters ; Pharmacology/Toxicology ; Plant Physiology ; Regression analysis ; Regression models ; Statistical analysis ; Zinc ; Zinc - blood</subject><ispartof>Biometals, 2024-12, Vol.37 (6), p.1537-1549</ispartof><rights>The Author(s), under exclusive licence to Springer Nature B.V. 2024 Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</rights><rights>2024. The Author(s), under exclusive licence to Springer Nature B.V.</rights><rights>Copyright Springer Nature B.V. Dec 2024</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c256t-32c13b94cee87b45ba4833dbc909ee4128e16e119f2da78e7eedb981a93f56fe3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10534-024-00624-y$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10534-024-00624-y$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/39154116$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Zhang, Zhuxia</creatorcontrib><creatorcontrib>Xie, Bo</creatorcontrib><creatorcontrib>Zhong, Qi</creatorcontrib><creatorcontrib>Dai, Chenxu</creatorcontrib><creatorcontrib>Xu, Xijin</creatorcontrib><creatorcontrib>Huo, Xia</creatorcontrib><title>Abnormal erythrocyte-related parameters in children with Pb, Cr, Cu and Zn exposure</title><title>Biometals</title><addtitle>Biometals</addtitle><addtitle>Biometals</addtitle><description>The link between exposure to a particular heavy metal or metalloid and the development of anemia is well established. However, the association between combined exposure to multiple heavy metal(loid)s and anemia in children is still lacking in evidence. In this study, a total of 266 children aged 3 to 7 were recruited from Guiyu, China. Inductively coupled plasma mass spectrometry (ICP-MS) was used to measure blood heavy metal(loid) concentrations. Blood cell count, hemoglobin (HGB), mean corpuscular hemoglobin (MCH), mean corpuscular volume (MCV), mean corpuscular hemoglobin concentration (MCHC), hematocrit (HCT), and red blood cell distribution width (RDW) were measured by an automated hematology analyzer. Erythrocyte-related parameters were negatively correlated with the Cu and Cu/Zn ratios and positively correlated with Cr, Ni, Zn, and Se by Spearman correlation analysis. Only blood Cu level was negatively correlated with HGB [β = −2.74, (95% Cl: −4.49, −0.995)], MCH [β = −0.505, (95% Cl: −0.785, −0.226)], MCV [β = −1.024, (95% Cl: −1.767, −0.281)], and MCHC [β = −2.137, (95% Cl: −3.54, −0.734)] by multiple linear regression analysis. The Bayesian Kernel Machine Regression (BKMR) model analysis indicated a negative correlation between the combined exposure to Cu, Zn, Pb, and Cr and MCH and MCV. The single-factor analysis showed a considerable statistical difference only with Cu on MCV, MCH, and HGB. Furthermore, the interaction analysis highlighted the interdependent effects of Cu and Zn, Pb and Zn, and Cr and Zn on MCH and MCV levels. Additionally, the oxidation and/or antioxidation reactions may play a significant role in the development of metal(loid)-induced anemia risk. It is crucial to investigate the effects of co-exposure to multiple heavy metal(loid) elements on anemia, especially the interrelationships and mechanisms among them.</description><subject>Anemia</subject><subject>Bayesian analysis</subject><subject>Biochemistry</subject><subject>Biomedical and Life Sciences</subject><subject>Blood</subject><subject>Blood levels</subject><subject>Cell Biology</subject><subject>Child</subject><subject>Child, Preschool</subject><subject>Children</subject><subject>Chromium</subject><subject>Chromium - blood</subject><subject>Copper</subject><subject>Copper - blood</subject><subject>Correlation analysis</subject><subject>Erythrocyte Indices</subject><subject>Erythrocytes</subject><subject>Erythrocytes, Abnormal - pathology</subject><subject>Exposure</subject><subject>Factor analysis</subject><subject>Female</subject><subject>Heavy metals</subject><subject>Hematocrit</subject><subject>Hematology</subject><subject>Hemoglobin</subject><subject>Humans</subject><subject>Inductively coupled plasma mass spectrometry</subject><subject>Lead</subject><subject>Lead - blood</subject><subject>Life Sciences</subject><subject>Male</subject><subject>Mass spectrometry</subject><subject>Mass spectroscopy</subject><subject>Medicine/Public Health</subject><subject>Metal concentrations</subject><subject>Metals, Heavy - blood</subject><subject>Microbiology</subject><subject>Oxidation</subject><subject>Parameters</subject><subject>Pharmacology/Toxicology</subject><subject>Plant Physiology</subject><subject>Regression analysis</subject><subject>Regression models</subject><subject>Statistical analysis</subject><subject>Zinc</subject><subject>Zinc - blood</subject><issn>0966-0844</issn><issn>1572-8773</issn><issn>1572-8773</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kE1v1DAQhi1ERbeFP8ABWeLCgZSZ2PHHcbUqFGmlVipcuFhOMmFT5WOxE9H8-xpSQOLQw8wc_Mw71sPYa4QLBNAfIkIhZAZ5KlCpL8_YBgudZ0Zr8ZxtwCqVgZHylJ3FeAcAVoN6wU6FxUIiqg273ZbDGHrfcQrLdAhjtUyUBer8RDU_-uB7mihE3g68OrRdHWjgP9vpwG_K93wXUs3cDzX_NnC6P45xDvSSnTS-i_TqcZ6zrx8vv-yusv31p8-77T6r8kJNmcgrFKWVFZHRpSxKL40QdVlZsEQSc0OoCNE2ee21IU1Ul9agt6IpVEPinL1bc49h_DFTnFzfxoq6zg80ztEJsBKkQqMS-vY_9G6cw5B-5wRK0IXJBSYqX6kqjDEGatwxtL0Pi0Nwv5S7VblLyt1v5W5JS28eo-eyp_rvyh_HCRArENPT8J3Cv9tPxD4ANPiL4g</recordid><startdate>20241201</startdate><enddate>20241201</enddate><creator>Zhang, Zhuxia</creator><creator>Xie, Bo</creator><creator>Zhong, Qi</creator><creator>Dai, Chenxu</creator><creator>Xu, Xijin</creator><creator>Huo, Xia</creator><general>Springer Netherlands</general><general>Springer Nature B.V</general><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>7QO</scope><scope>7T7</scope><scope>7U5</scope><scope>7U7</scope><scope>8BQ</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>JG9</scope><scope>K9.</scope><scope>L7M</scope><scope>M7N</scope><scope>P64</scope><scope>7X8</scope></search><sort><creationdate>20241201</creationdate><title>Abnormal erythrocyte-related parameters in children with Pb, Cr, Cu and Zn exposure</title><author>Zhang, Zhuxia ; 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However, the association between combined exposure to multiple heavy metal(loid)s and anemia in children is still lacking in evidence. In this study, a total of 266 children aged 3 to 7 were recruited from Guiyu, China. Inductively coupled plasma mass spectrometry (ICP-MS) was used to measure blood heavy metal(loid) concentrations. Blood cell count, hemoglobin (HGB), mean corpuscular hemoglobin (MCH), mean corpuscular volume (MCV), mean corpuscular hemoglobin concentration (MCHC), hematocrit (HCT), and red blood cell distribution width (RDW) were measured by an automated hematology analyzer. Erythrocyte-related parameters were negatively correlated with the Cu and Cu/Zn ratios and positively correlated with Cr, Ni, Zn, and Se by Spearman correlation analysis. Only blood Cu level was negatively correlated with HGB [β = −2.74, (95% Cl: −4.49, −0.995)], MCH [β = −0.505, (95% Cl: −0.785, −0.226)], MCV [β = −1.024, (95% Cl: −1.767, −0.281)], and MCHC [β = −2.137, (95% Cl: −3.54, −0.734)] by multiple linear regression analysis. The Bayesian Kernel Machine Regression (BKMR) model analysis indicated a negative correlation between the combined exposure to Cu, Zn, Pb, and Cr and MCH and MCV. The single-factor analysis showed a considerable statistical difference only with Cu on MCV, MCH, and HGB. Furthermore, the interaction analysis highlighted the interdependent effects of Cu and Zn, Pb and Zn, and Cr and Zn on MCH and MCV levels. Additionally, the oxidation and/or antioxidation reactions may play a significant role in the development of metal(loid)-induced anemia risk. It is crucial to investigate the effects of co-exposure to multiple heavy metal(loid) elements on anemia, especially the interrelationships and mechanisms among them.</abstract><cop>Dordrecht</cop><pub>Springer Netherlands</pub><pmid>39154116</pmid><doi>10.1007/s10534-024-00624-y</doi><tpages>13</tpages></addata></record> |
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subjects | Anemia Bayesian analysis Biochemistry Biomedical and Life Sciences Blood Blood levels Cell Biology Child Child, Preschool Children Chromium Chromium - blood Copper Copper - blood Correlation analysis Erythrocyte Indices Erythrocytes Erythrocytes, Abnormal - pathology Exposure Factor analysis Female Heavy metals Hematocrit Hematology Hemoglobin Humans Inductively coupled plasma mass spectrometry Lead Lead - blood Life Sciences Male Mass spectrometry Mass spectroscopy Medicine/Public Health Metal concentrations Metals, Heavy - blood Microbiology Oxidation Parameters Pharmacology/Toxicology Plant Physiology Regression analysis Regression models Statistical analysis Zinc Zinc - blood |
title | Abnormal erythrocyte-related parameters in children with Pb, Cr, Cu and Zn exposure |
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