Iodine status of Eeyou Istchee community members of northern Quebec, Canada, and potential sources
Bibliographic record
Abstract
A multi community environment-and-health study among six of the nine communities of Eeyou Istchee in northern Quebec, Canada provided greater insight into iodine intake levels among these Cree First Nation communities. Using data from this large population-based study, descriptive statistics of measured urinary iodine concentrations (UICs) and iodine-creatinine ratios (stratified by age, sex, community of residence, and water consumption) were calculated, and the associations between independent variables and iodine concentration measures were examined through a general linear model. Traditional food consumption contributions were examined through Pearson partial correlation tests and linear regression analyses; and the importance of water sources through ANOVA. Generally speaking, urinary iodine levels of Eeyou Istchee community members were within the adequate range set out by the World Health Organization, though sex and community differences existed. However, men in one community were considered to be at risk of iodine deficiency. Older participants had significantly higher mean iodine-creatinine ratios than younger participants (15-39 years = 90.50 μmol mol(-1); >39 years = 124.52 μmol mol(-1)), and consumption of beaver (Castor canadensis) meat, melted snow and ice, and bottled water were predictive of higher iodine excretion. It is concluded that using both urinary iodine indicators can be helpful in identifying subgroups at greater risk of iodine deficiency.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".