Anemia, iron status, and associated protective and risk factors among children and adolescents aged 3 to 19 years old from four First Nations communities in Quebec
Bibliographic record
Abstract
OBJECTIVES: Anemia and iron deficiency (ID) are frequent among Indigenous children of Canada, but few data are available in Quebec. The present study aimed to characterize anemia and ID prevalence and associated protective and risk factors among First Nations youth in Quebec. METHODS: The 2015 First Nations (JES!-YEH!) pilot study was conducted among children and adolescents (3 to 19 years; n = 198) from four First Nations communities in Quebec. Blood and urine samples and anthropometric measurements were collected. Hemoglobin (Hb), serum ferritin (SF), plasma hs-CRP, and urinary cotinine levels were measured. Factors associated with anemia and ID (including traditional and market food consumption) were assessed using an interview-administered food frequency questionnaire, based on which nutritional intakes were calculated. Structural equation models were used to test associations. RESULTS: The prevalence of anemia and ID was elevated (16.8% and 20.5% respectively). Traditional meat, fruit, and fruit juice (natural and powdered)-via their positive association with vitamin C intake-were the only food variables positively associated with SF (coefficient [95% CI] 0.017 [0.000, 0.114]; 0.090 [0.027, 0.161]; and 0.237 [0.060, 0.411]). Male sex was also associated with higher SF (0.295 [0.093, 0.502]). Inflammation status (hs-CRP > 5 mg/L) was inversely associated with Hb (- 0.015 [- 0.025, - 0.005]), whereas SF was positively associated with Hb (0.066 [0.040, 0.096]). Fruit and juice consumption was also positively associated with Hb, via vitamin C intake and SF (0.004 [0.001, 0.010]; 0.008 [0.003, 0.017]). CONCLUSIONS: Interventions fostering healthier food environments as well as higher consumption of traditional meats and foods naturally rich in vitamin C, which is known to enhance iron absorption, and fighting inflammation could contribute to decrease the high prevalence of anemia and ID in this young Indigenous population.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".