Home fortification with calcium reduces Hb response to iron among anaemic Bangladeshi infants consuming a new multi-micronutrient powder formulation
Bibliographic record
Abstract
OBJECTIVE: To investigate whether the recommended dietary intake of Ca in anaemic infants compromises the expected Hb response, via home fortification with a new Ca- and Fe-containing Sprinkles™ micronutrient powder (MNP). DESIGN: A double-blind, randomized controlled, 2-month trial was conducted in Bangladesh. Infants were randomized to one of two MNP intervention groups containing Fe and other micronutrients, with or without Ca. Hb, anthropometrics and dietary intake were measured pre- and post-intervention while family demographics were collected at baseline. SETTING: Twenty-six rural villages in the Kaliganj sub-district of Gazipur, Bangladesh. SUBJECTS: One hundred infants aged 6-11 months. RESULTS: A significant increase in Hb (MNP, 13·3 (sd 12·6) g/l v. Ca-MNP, 7·6 (sd 11·6) g/l; P < 0·0001) was noted in infants from both groups. However, infants receiving MNP without Ca had a significantly higher end-point Hb concentration (P = 0·024) and rate of anaemia recovery (P = 0·008). Infants receiving MNP with Ca were more likely to remain anaemic (OR 3·2; 95 % CI 1·4, 7·5). Groups did not differ in dietary intake or demographic and anthropometric indicators. CONCLUSIONS: Although both groups showed significant improvement in Hb status, the nutrient-nutrient interaction between Fe and Ca may have diminished the Hb response in infants receiving the Ca-containing MNP.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".