Low prevalence of iron deficiency and iron deficiency anemia in children attending daycare in a large Canadian city
Bibliographic record
Abstract
Children are vulnerable to iron deficiency (ID) and iron deficiency anemia (IDA) due to rapid tissue expansion. Recent Canadian surveys reported that 1–3 y and 4–8 y in Québec had an iron intake of 10.1 mg and 13.7 mg/day respectively; however, iron status was not assessed. This study examined the prevalence of ID and IDA and iron intake in children (n=523) from randomly selected daycares in Montréal. Ferritin was measured using an autoanalyzer (Liason®, DiaSorin) and hemoglobin using a radiometer (ABL80 FLEX Radiometer Medical A/S) in capillary samples. Iron intake over 24 h for 469 children with 72 having a repeat assessment was analyzed using Nutritionist Pro™ (Axxya Systems LLC.) and the Canadian Nutrient File. The data was adjusted for day‐to‐day variation, and all children met the EAR (3 mg/day for 1–3 y, 4 mg/day for 4–5 y olds). Mean daily intake for these age groups was 10.22±5.70 mg (n=272) and 11.06±5.32 mg (n=197), respectively, was similar to national data. ID (ferritin <12 μg/L) was present in 13.4% of children and IDA (hemoglobin <110 g/L) in 2.9% of this population. Corresponding means were 22±13 μg/L and 126±19 g/L. This data complements our recent cross‐sectional study reporting ID in 18.0% and IDA in 5.4% in 3–5 y Inuit children; confirming that urban dwelling preschoolers in a large Canadian city have a lower prevalence of ID and IDA. Supported by the Beef Information Centre.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".