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Environmental Mercury Exposure and Blood Pressure Among Nunavik Inuit Adults

2009· article· en· W2062641425 on OpenAlexafffundabout
Béatriz Valéra, Éric Dewailly, Paul Poirier

Bibliographic record

VenueHypertension · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsCentre hospitalier universitaire de Québec
FundersCanadian Institutes of Health Research
KeywordsBlood pressureMercury (programming language)Pulse pressureDiastoleAnthropometryConfoundingMethylmercuryMedicinePhysiologyInternal medicineChemistryEnvironmental chemistry

Abstract

fetched live from OpenAlex

Epidemiological evidence suggests a negative impact of methylmercury on the cardiovascular system, but findings regarding the effect on blood pressure (BP) are not consistent. We aimed to study the impact of mercury levels on BP among Nunavik Inuit adults. The health survey Qanuippitaa? was conducted in Nunavik (northern Quebec, Canada), and data were obtained from 732 Inuit > or = 18 years of age. Anthropometric blood samples, as well as systolic BP and diastolic BP, were assessed. Pulse pressure (systolic BP-diastolic BP) was calculated. Mercury blood concentration was used as a biomarker of recent exposure. Simple relations between mercury and BP parameters were studied by using the Pearson correlation, whereas multiple regressions were performed to control for confounders. Mean age of the participants was 34.3 years (95% CI: 33.6 to 34.9 years). Systolic BP, diastolic BP, and pulse pressure means were 117 mm Hg (95% CI: 116 to 118 mm Hg), 73 mm Hg (95% CI: 72 to 74 mm Hg), and 43 mm Hg (95% CI: 42 to 44 mm Hg), respectively. Mercury mean was 50.2 nmol/L. In multivariable analyses, mercury was associated with systolic BP (beta=2.14; P=0.0004), whereas the association with diastolic BP was near the significance level (beta=0.96; P=0.069). In conclusion, mercury is associated with increasing BP and pulse pressure among Nunavik Inuit adults after considering the effect of fish nutrients (n-3 fatty acids and selenium) and other confounders.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.531
Threshold uncertainty score0.717

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.008
GPT teacher head0.196
Teacher spread0.188 · 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 teacher head, 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

Citations124
Published2009
Admission routes3
Has abstractyes

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