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Record W4384663635 · doi:10.1289/ehp11301

The Contribution across Three Generations of Mercury Exposure to Attempted Suicide among Children and Youth in Grassy Narrows First Nation, Canada: An Intergenerational Analysis

2023· article· en· W4384663635 on OpenAlexafffundabout
Donna Mergler, Aline Philibert, Myriam Fillion, Judy Da Silva

Bibliographic record

VenueEnvironmental Health Perspectives · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsUniversité TÉLUQUniversité du Québec à Montréal
FundersCanadian Institutes of Health ResearchHealth CanadaOntario Ministry of Health and Long-Term CareNorthwestern University
KeywordsDemographyGrandparentEnvironmental healthLivelihoodGeographyPregnancyMental healthPublic healthMedicinePsychologyBiologySociologyAgricultureDevelopmental psychology

Abstract

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Background: For 60 y, the people of Asubpeeschoseewagong Anishinabek (Grassy Narrows First Nation) have endured the effects of massive mercury (Hg) contamination of their river system, central to their traditions, culture, livelihood, and diet. In the years following the Hg discharge into the English–Wabigoon River system by a chloralkali plant in the early 1970s, there was a dramatic increase in youth suicides. Several authors attributed this increase solely to social disruption caused by the disaster. Objective: This research examined the possible contribution of Hg exposure across three generations on attempted suicides among today’s children (5–11 y old) and youth (12–17 y old), using a matrilineal intergenerational paradigm. Methods: Information from the 2016–2017 Grassy Narrows Community Health Assessment (GN-CHA) survey was merged with Hg biomonitoring data from government surveillance programs (1970–1997). Data from 162 children/youth (5–17 years of age), whose mothers (n=80) had provided information on themselves, their parents, and children, were retained for analyses. Direct and indirect indicators of Hg exposure included a) grandfather had worked as a fishing guide, and b) mother’s measured and estimated umbilical cord blood and childhood hair Hg and her fish consumption during pregnancy with this child. Structural equation modeling (SEM) was used to examine significant links from grandparents (G0) to mothers’ exposure and mental health (G1) and children/youth (G2) risk for attempted suicide. Results: Mothers’ (G1) median age was 33 y, 86.3% of grandmothers (G0) had lived in Grassy Narrows territory during their pregnancy, and 52.5% of grandfathers (G0) had worked as fishing guides. Sixty percent of children (G2) were <12 years of age. Mothers reported that among teenagers (G2: 12–17 years of age), 41.2% of girls and 10.7% of boys had ever attempted suicide. The SEM suggested two pathways that significantly linked grandparents (G0) to children’s (G2) attempted suicides: a) through mothers’ (G1) prenatal and childhood Hg exposure and psychological distress, and b) through maternal fish consumption during pregnancy (G1/G2), which is an important contributor to children’s emotional state and behavior. Discussion: Despite minimal individual information on G0 and G1 past life experiences, the findings support the hypothesis that Hg exposure over three generations contributes to the mental health of today’s children and youth. The prevalence of Grassy Narrows youth ever having attempted suicide is three times that of other First Nations in Canada. https://doi.org/10.1289/EHP11301

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)0.001
metaresearch head score (Gemma)0.003
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 score0.129

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0040.001
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.020
GPT teacher head0.280
Teacher spread0.260 · 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

Citations19
Published2023
Admission routes3
Has abstractyes

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