Grow Smart: An Integrated Nutrition and Early Child Development Intervention Among Infants Improves Expressive Language and Reduces Anemia and Iron Deficiency in Rural India (FS08-03-19)
Bibliographic record
Abstract
Nutritional deficiency and lack of early learning opportunities contribute to the loss of developmental potential. The objective is to evaluate the effects of an integrated nutrition and early learning intervention (ELI) on micronutrient status and the development of infants in rural India. 513 infants (6–12mo) were enrolled from 26 villages in rural India and randomized using a 2 × 2 design to receive multiple micronutrient powders (MNP containing iron, zinc, vitamins A, B2, B12, C and folic acid) vs. placebo (B2) and EL vs. control. The ELI was based on the UNICEF-developed Care for Child Development. Baseline (BL), post-intervention (6 mo) and follow-up (12 mo) evaluations included Mullens Scales of Early Learning, anthropometry, and 2 ml venous blood (BL & 12 mo). Data were analyzed using linear mixed effects regression models with random village/subject intercepts accounting for site of recruitment and repeated measures. For biomarker outcomes, main effects of MNP was assessed. P-values of <0.05 considered statistically significant. For child development outcomes, main effects of MNP and ELI were analyzed separately, and three-way interactions (MNP*ELI*midline or MNP*ELI*end line) were tested. At baseline, the mean age of mothers was 22.9y (SD = 2.9) and 99.6% were married. Most mothers (84.2%) had attended some schooling. Mean infant age was 8.6 mo (SD = 2.2); 53.0% were male. Anemia prevalence was 66.4%. No significant baseline differences were found. At end line, infants in the MNP group had significantly higher hemoglobin (11 g/dl vs.10 g/dl) and ferritin (18.2ug/l vs.11.5 ug/l) values compared to infants in the placebo groups, respectively. Infants in the MNP group (mean = 39.5; SE = 0.6) versus placebo group (mean = 37.7; SE = 0.6) also scored significantly higher in expressive language and marginally higher in visual reception (mean = 42.5; SE = 0.5; P = 0.06) and social-emotional behavior (mean = 24.1; SE = 0.2; P = 0.052), compared to the placebo (mean = 41.1; E = 0.6, mean = 23.5; SE = 0.2, respectively). Significant interactions in visual reception and expressive language performance showed that children who received either or both interventions had better scores than children who received neither. Home MNP and EL interventions can improve infant MN status and development. Mathile Institute for the Advancement of Human Nutrition, Nutrition International, Sackler Institute for Nutrition Science of the New York Academy of Science.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".