| dc.creator | Fonseca, Márlon de Freitas | |
| dc.creator | Hacon, Sandra De Souza | |
| dc.creator | Grandjean, Philippe | |
| dc.creator | Choi, Anna Lai | |
| dc.creator | Bastos, Wanderley Rodrigues | |
| dc.date | 2014-10-07T19:31:38Z | |
| dc.date | 2014-10-07T19:31:38Z | |
| dc.date | 2014 | |
| dc.date.accessioned | 2023-09-26T22:10:02Z | |
| dc.date.available | 2023-09-26T22:10:02Z | |
| dc.identifier | FONSECA, Márlon de Freitas. et al. Iron status as a covariate in methylmercury-associated neurotoxicity risk. Chemosphere., Oxford, v. 100, p. 89-96, 2014. | |
| dc.identifier | 0045-6535 | |
| dc.identifier | https://www.arca.fiocruz.br/handle/icict/8525 | |
| dc.identifier.uri | https://repositorioslatinoamericanos.uchile.cl/handle/2250/8875667 | |
| dc.description | 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. | |
| dc.format | application/pdf | |
| dc.language | eng | |
| dc.publisher | Elsevier Science Ltd | |
| dc.rights | restricted access | |
| dc.subject | Iron Stores | |
| dc.subject | Mercury | |
| dc.subject | Negative Confounding | |
| dc.subject | Fertile Women | |
| dc.subject | Amazon | |
| dc.subject | Fish Consumption | |
| dc.subject | Mercúrio | |
| dc.subject | Ecossistema Amazônico | |
| dc.subject | Peixes | |
| dc.title | Iron status as a covariate in methylmercury-associated neurotoxicity risk | |
| dc.type | Article | |
