Iodized Salt Improves Child's Iodine Status, Mental Development, and Physical Growth in a Cluster Randomized Trial in Ethiopia
Bibliographic record
Abstract
The effectiveness of iodized salt programs to improve mental development and physical growth has not been studied in children < 36 months. Using a cluster randomized design, 1835 infants 5‐11 mo old were enrolled in 60 villages in Amhara, Ethiopia. Following salt iodization legislation, iodized salt was forced early into the markets of 30 villages (intervention, I) before it became available in the 30 control (C) villages. The two groups were similar at baseline. Children (85% of the baseline sample) were re‐assessed at age 20‐29 mo. Treatment effects were analyzed using linear mixed models. The median endline urinary iodine concentration (UIC) was significantly higher in group I (161.6 vs 124.0 µg/L; p<0.001). Group I had significantly higher scores at reassessment on three of the four Bayley‐III subscales: cognitive (std mean 6.40 vs 6.14; p<0.05), receptive language (std mean 7.19 vs 6.92; p<0.05), and fine motor (std mean 7.97 vs 7.59; p<0.05). Moderator analysis indicated that length‐for‐age in children was higher in group I for those with high household assets. UIC was higher in I vs C children with an unschooled mother, unimproved water, and no recent illness. These results support universal salt iodization to improve children's life. [Funded by Micronutrient Initiative, Canada]
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".