Depleted iron stores and iron deficiency anemia associated with reduced ferritin and hepcidin and elevated soluble transferrin receptors in a multiethnic group of preschool-age children
Bibliographic record
Abstract
Iron deficiency anemia is prevalent in subgroups of the Canadian population. The objective of this study was to examine iron status and anemia in preschool-age children. Healthy children (n = 430, 2-5 years old, Montreal, Quebec, Canada) were sampled from randomly selected daycares. Anthropometry, demographics, and diet were assessed. Biochemistry included hemoglobin, ferritin, soluble transferrin receptors (sTfR), ferritin index, markers of inflammation (C-reactive protein, interleukin 6 (IL-6), and tumour necrosis factor alpha (TNFα)), and hepcidin. Iron deficiency and anemia cutoffs conformed to the World Health Organization criteria. Differences among categories were tested using mixed-model ANOVA or χ(2) tests. Children were 3.8 ± 1.0 years of age, with a body mass index z score of 0.48 ± 0.97, and 51% were white. Adjusted intakes of iron indicated <1% were at risk for deficiency. Hemoglobin was higher in white children, whereas ferritin was higher with greater age and female sex. Inflammatory markers and hepcidin did not vary with any demographic variable. The prevalence of iron deficiency was 16.5% (95% confidence interval (CI), 13.0-20.0). Three percent (95% CI, 1.4-4.6) of children had iron deficiency anemia and 12.8% (95% CI, 9.6-16.0) had unexplained anemia. Children with iron deficiency, with and without anemia, had lower plasma ferritin and hepcidin but higher sTfR, ferritin index, and IL-6, whereas those with unexplained anemia had elevated TNFα. We conclude that iron deficiency anemia is not very common in young children in Montreal. While iron deficiency without anemia is more common than iron deficiency with anemia, the correspondingly reduced circulating hepcidin would have enabled heightened absorption of dietary iron in support of erythropoiesis.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".