Chronic Iron Deficiency and Cognitive Function in Early Childhood
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: A landmark longitudinal study, conducted in Costa Rica in the 1980s, found that children with chronic iron deficiency compared with good iron status in infancy had 8 to 9 points lower cognitive scores, up to 19 years of age. Our objective was to examine this association in a contemporary, high-resource setting. METHODS: This was a prospective observational study of children aged 12 to 40 months screened with hemoglobin and serum ferritin. All parents received diet advice; children received oral iron according to iron status. After 4 months, children were grouped as: chronic iron deficiency (iron deficiency anemia at baseline or persistent nonanemic iron deficiency) or iron sufficiency (IS) (IS at baseline or resolved nonanemic iron deficiency). Outcomes measured at 4 and 12 months included the Early Learning Composite (from the Mullen Scales of Early Learning) and serum ferritin. RESULTS: Of 1478 children screened, 116 were included (41 chronic, 75 sufficient). Using multivariable analyses, the mean between-group differences in the Early Learning Composite at 4 months was -6.4 points (95% confidence interval [CI]: -12.4 to -0.3, P = .04) and at 12 months was -7.4 points (95% CI: -14.0 to -0.8, P = .03). The mean between-group differences in serum ferritin at 4 months was 14.3 μg/L (95% CI: 1.3-27.4, P = .03) and was not significantly different at 12 months. CONCLUSIONS: Children with chronic iron deficiency, compared with children with IS, demonstrated improved iron status, but cognitive scores 6 to 7 points lower 4 and 12 months after intervention. Future research may examine outcomes of a screening strategy on the basis of early detection of iron deficiency using serum ferritin.
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 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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".