Introduction of iodised salt benefits infants’ mental development in a community-based cluster-randomised effectiveness trial in Ethiopia
Bibliographic record
Abstract
The effectiveness of salt iodisation in improving the mental development of young children has not been assessed. We implemented a community-based cluster-randomised effectiveness trial in sixty randomly selected districts in the Amhara region of Ethiopia. We randomly allocated each district to treatment and randomly selected one of its villages. In parallel to national salt iodisation efforts, iodised salt was brought early into the markets of the thirty intervention villages before it became widely available in the thirty control villages 4-6 months later. The primary outcome was children's mental development scores on the Bayley Scales. This was an intention-to-treat analysis using mixed linear models adjusted for covariates and clusters. The trial was registered at ClinicalTrials.gov, NCT013496. We assessed 1835 infants aged 5-11 months at baseline. The same children (85 % of the sample) were re-assessed at 20-29 months when all villages had iodised salt. At endline, urinary iodine concentration was higher in children in the intervention group compared with those in the control group (median 228·0 v. 155·1 µg/l, P=0·001). The intervention group had higher scores compared with the control group on the Bayley composite score (raw scores:130·60 v. 128·51; standardised scores: 27·8 v. 26·9; d=0·13; 95 % CI 0·02, 0·23) and three of the four subscales: cognitive (53·27 v. 52·54, d=0·13; 95 % CI 0·03, 0·23), receptive language (20·71 v. 20·18, d=0·13; 95 % CI 0·03, 0·24) and fine motor (35·45 v. 34·94, d=0·15; 95 % CI 0·04, 0·25). The introduction of iodised salt contributes to children's higher urinary iodine concentration and mental development.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".