Stunting, selenium deficiency and anemia are associated with poor cognitive performance in preschool children from rural Ethiopia
Bibliographic record
Abstract
BACKGROUND: Anthropometric characteristics and iron status affect cognitive performance in children. In addition, selenium can influence cognitive outcomes; protection of the brain from oxidative stress and its role in thyroid hormone metabolism are putative mechanisms. METHODS: To investigate their association with cognitive performance, anthropometric indicators, iron biomarkers, and serum selenium of children (n = 541) of 54-60mo of age from rural Ethiopia were assessed. Cognitive assessment was conducted with the administration of two reasoning subtests of the Wechsler Preschool and Primary Scale of Intelligence and the school readiness test. RESULTS: Stunting was found in 41.4 % of children, 28.7 % were underweight, and 6.3 % were wasted. The mean score of stunted children was lower than that of non-stunted children on non-verbal reasoning (7.0 ± 3.2vs7.9 ± 3.1; p = 0.01) and the school readiness tests (4.3 ± 2.2 vs 3.3 ± 2.1; p < 0.001). Compared to non-anemic children, anemic children had lower score for the verbal reasoning test (9.5 ± 1.7 vs 8.9 ± 2.2; p = 0.02). However, except for hemoglobin, none of the iron biomarkers had significant associations with the cognitive score of the study children (p > 0.05). Selenium deficient children had lower scores on all cognitive tests than normal children (p < 0.05). CONCLUSION: The present study finding linking chronic undernutrition and micronutrient deficiency to cognitive deficits suggests the need for designing effective intervention programmes to control for protein energy malnutrition and micronutrient deficiency and address cognitive development in children.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".