Author | Fonseca, Márlon de Freitas | pt_BR |
Author | Hacon, Sandra De Souza | pt_BR |
Author | Grandjean, Philippe | pt_BR |
Author | Choi, Anna Lai | pt_BR |
Author | Bastos, Wanderley Rodrigues | pt_BR |
Access date | 2014-10-07T19:31:38Z | |
Available date | 2014-10-07T19:31:38Z | |
Document date | 2014 | pt_BR |
Citation | FONSECA, Márlon de Freitas et al. Iron status as a covariate in methylmercury-associated neurotoxicity risk. Chemosphere, Oxford, v. 100, p. 89-96, Apr. 2014. | pt_BR |
ISSN | 0045-6535 | pt_BR |
URI | https://www.arca.fiocruz.br/handle/icict/8525 | |
Language | eng | pt_BR |
Publisher | Elsevier | pt_BR |
Rights | open access | pt_BR |
Title | Iron status as a covariate in methylmercury-associated neurotoxicity risk | pt_BR |
Type | Article | pt_BR |
DOI | 10.1016/j.chemosphere.2013.12.053 | |
Abstract | Intrauterine methylmercury exposure and prenatal iron deficiency negatively affect offspring’s brain development. Since fish is a major source of both methylmercury and iron, occurrence of negative confounding may affect the interpretation of studies concerning cognition. We assessed relationships between methylmercury exposure and iron-status in childbearing females from a population naturally exposed to methylmercury through fish intake (Amazon). We concluded a census (refuse <20%) collecting samples from 274 healthy females (12–49 years) for hair-mercury determination and assessed iron-status through red cell tests and determination of serum ferritin and iron. Reactive C protein and thyroid hormones was used for excluding inflammation and severe thyroid dysfunctions that could affect results. We assessed the association between iron-status and hair-mercury by bivariate correlation analysis and also by different multivariate models: linear regression (to check trends); hierarchical agglomerative clustering method (groups of variables correlated with each other); and factor analysis (to examine redundancy or duplication from a set of correlated variables). Hair-mercury correlated weakly with mean corpuscular volume (r = .141; P = .020) and corpuscular hemoglobin (r = .132; .029), but not with the best biomarker of iron-status, ferritin (r = .037; P = .545). In the linear regression analysis, methylmercury exposure showed weak association with age-adjusted ferritin; age had a significant coefficient (Beta = .015; 95% CI: .003–.027; P = .016) but ferritin did not (Beta = .034; 95% CI: .147 to .216; P = .711). In the hierarchical agglomerative clustering method, hair-mercury and iron-status showed the smallest similarities. Regarding factor analysis, iron-status and hair-mercury loaded different uncorrelated components. We concluded that iron-status and methylmercury exposure probably occur in an independent way. | pt_BR |
Affilliation | Fundação Oswaldo Cruz. Instituto Fernandes Figueira. Rio de Janeiro, RJ, Brasil. / Harvard School of Public Health. Department of Environmental Health. Boston, MA, USA. | pt_BR |
Affilliation | Fundação Oswaldo Cruz. Escola Nacional de Saúde Pública Sergio Arouca. Rio de Janeiro, RJ, Brasil. | pt_BR |
Affilliation | Harvard School of Public Health. Department of Environmental Health. Boston, MA, USA / University of Southern Denmark. Institute of Public Health. Odense C, Denmark. | pt_BR |
Affilliation | Harvard School of Public Health. Department of Environmental Health. Boston, MA, USA. | pt_BR |
Affilliation | Universidade Federal de Rondônia. Laboratório de Biogeoquímica Ambiental Wolfgang Christian Pfeiffer. Porto Velho, RO, Brasil. | pt_BR |
Subject | Iron Stores | pt_BR |
Subject | Mercury | pt_BR |
Subject | Negative Confounding | pt_BR |
Subject | Fertile Women | pt_BR |
Subject | Amazon | pt_BR |
Subject | Fish Consumption | pt_BR |
DeCS | Mercúrio | pt_BR |
DeCS | Ecossistema Amazônico | pt_BR |
DeCS | Peixes | pt_BR |