Publication:
Selecting the best non-invasive matrix to measure mercury exposure in human biomonitoring surveys

dc.contributor.authorEsteban-Lopez, Marta
dc.contributor.authorArrebola, Juan Pedro
dc.contributor.authorJuliá Molina, Miguel
dc.contributor.authorPärt, Peter
dc.contributor.authorSoto, Eva
dc.contributor.authorCañas Portilla, Ana Isabel
dc.contributor.authorPedraza-Diaz, Susana
dc.contributor.authorGonzález-Rubio, Juana María
dc.contributor.authorCastaño, Argelia
dc.date.accessioned2024-02-06T10:51:31Z
dc.date.available2024-02-06T10:51:31Z
dc.date.issued2022-03
dc.description.abstractExposure to mercury, even at low doses, can affect human health, well-being and life quality at a broad scale. Human biomonitoring is the most straightforward approach to measure and quantify mercury exposure in humans. The objective of the present study is to compare and discuss the relationships between Hg levels in the most used matrices, hair, urine and blood, with the aim to ascertain to what extent mercury exposure and internal mercury levels could be predicted by monitoring non-invasive matrices. The study population (n = 527) is a subsample from Spanish BIOAMBIENT. ES study (18-65 y, both sexes), with data of Hg levels in blood, hair, and urine from the same individuals. We found strong inter-matrix Spearman correlations between blood and hair mercury (r2 = 0.84), while the correlations for urine and blood mercury (r2=0.64) and urine and hair mercury (r2=0.65) were weaker. The geometric mean of the ratios between matrices were (GM, 95%CI): Hair/Blood 280 (271-290), Urine/Blood 0.174 (0.163-0.186) and Hair/Urine 2070 (1953-2194) and Urine/Blood 0.135 (0.128-0.144) for urine corrected by creatinine. High individual variation was observed particularly in those ratios involving urine. Considering the wide range of values observed in the ratios, we do not recommend applying them at individual level. The predictive models indicate that hair Hg was a more accurate predictor than urine. The inclusion of urine values did not increase the predictive accuracy, so, we recommend a cautious interpretation of urine mercury levels. Our study presents clear evidence that in a population highly exposed to food-borne mercury, a large portion of urinary mercury primarily emanates from methylmercury demethylation. We conclude that urine, as a non-invasive matrix, can be used as a reliable qualitative biomarker for Hg exposure when hair measurements not are available. For quantitative individual assessments, still blood measurements are to be preferred.es_ES
dc.description.peerreviewedes_ES
dc.format.numberPt Des_ES
dc.format.page112394es_ES
dc.format.volume204es_ES
dc.identifier.citationEnviron Res. 2022 Mar;204(Pt D):112394.es_ES
dc.identifier.doi10.1016/j.envres.2021.112394es_ES
dc.identifier.e-issn1096-0953es_ES
dc.identifier.journalEnvironmental researches_ES
dc.identifier.pubmedID34801545es_ES
dc.identifier.urihttp://hdl.handle.net/20.500.12105/17508
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.relation.publisherversionhttps://doi.org/10.1016/j.envres.2021.112394es_ES
dc.repisalud.centroISCIII::Centro Nacional de Sanidad Ambientales_ES
dc.repisalud.institucionISCIIIes_ES
dc.rights.accessRightsopen accesses_ES
dc.rights.licenseAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectBloodes_ES
dc.subjectHaires_ES
dc.subjectHuman biomonitoringes_ES
dc.subjectMatrix-ratioes_ES
dc.subjectMercuryes_ES
dc.subjectNon-invasivees_ES
dc.subjectUrinees_ES
dc.subject.meshMercuryes_ES
dc.subject.meshMethylmercury Compoundses_ES
dc.subject.meshBiological Monitoringes_ES
dc.subject.meshEnvironmental Monitoringes_ES
dc.subject.meshFemalees_ES
dc.subject.meshHaires_ES
dc.subject.meshHumanses_ES
dc.subject.meshMalees_ES
dc.titleSelecting the best non-invasive matrix to measure mercury exposure in human biomonitoring surveyses_ES
dc.typeresearch articlees_ES
dc.type.hasVersionVoRes_ES
dspace.entity.typePublication
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relation.isAuthorOfPublication.latestForDiscovery27208892-1792-4232-8be8-5338006f6857

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