MétaCan
Menu
← Back to cohort

Seasonal variations in exposure to methylmercury and its dietary sources among pregnant Inuit women in Nunavik, Canada

2020· article· en· W3097060257 on OpenAlexafffundabout
Mariana de Moraes Pontual, Pierre Ayotte, Matthew Little, Chris Furgal, Amanda D. Boyd, Gina Muckle, Ellen Avard, Sylvie Ricard, Marie-Josée Gauthier, Elhadji Anassour-Laouan Sidi, Mélanie Lemire

Bibliographic record

VenueThe Science of The Total Environment · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsNunavik Regional Board of Health and Social ServicesMakivik CorporationUniversité LavalInstitut National de Santé Publique du QuébecTrent UniversityUniversity of VictoriaUniversity of GuelphHôpital du Saint-Sacrement
FundersFonds de Recherche du Québec - SantéCrown-Indigenous Relations and Northern Affairs CanadaCanada First Research Excellence Fund
KeywordsBeluga WhaleMethylmercuryCircumpolar starSeasonalityBiomonitoringEnvironmental healthGeographyMedicineEcologyBiologyArcticBioaccumulation

Abstract

fetched live from OpenAlex

Among populations living in close connection with the sea, rivers and lakes for subsistence, diet varies according to local monthly wildlife species availability and food preferences. This may lead to variations in methylmercury (MeHg) exposure over a year, although no biomonitoring studies have documented this issue in Circumpolar populations, the most exposed to international Hg emissions. Our aim was to characterize seasonal variations in MeHg exposure among pregnant Inuit women from Nunavik and to identify country foods responsible for these variations. Between October 2016 and March 2017, 97 participants were recruited. Blood mercury (Hg) was tested and hair Hg was measured by centimeter as a surrogate for monthly MeHg exposure over the past year. Latent class growth analysis was conducted to identify groups of pregnant women with similar hair Hg monthly trajectories. Country foods consumption was documented by season. Seasonal daily intakes of MeHg were estimated based on concentrations in country foods. Retrospective monthly hair Hg analyses revealed that MeHg exposure was lowest in winter, and highest in summer and early fall months. Three latent classes (groups) of pregnant women with similar trajectories of monthly hair Hg variations were identified: high (n = 20, 21%), moderate (n = 38, 41%) and low variation (n = 35, 38%). Beluga meat was the country food contributing to most of daily MeHg intake, primarily during summer and fall, and was the only one associated with the odds of being classified into moderate and high variation groups (OR 95% CI: 1.19 [1.01-1.39] and 1.25 [1.04-1.50]). These findings underscore the importance of monthly variations in exposure to MeHg due to the seasonality of local foods consumed and responsible for elevated MeHg exposure. Further studies critically need to understand local diet fluctuations over a year to adequately assess MeHg exposure, adopt timely preventive interventions and evaluate the effectiveness of the Minamata Convention.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.209
Teacher spread0.196 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations14
Published2020
Admission routes3
Has abstractyes

Explore more

Same venueThe Science of The Total Environment→Same topicMercury impact and mitigation studies→French-language works237,207→