Micronutrient Status and Its Effect on Infant Neurocognitive Development in Rural Cambodia
Bibliographic record
Abstract
Objectives: Micronutrient deficiencies can significantly impair cognitive development especially during critical periods in early infant life. It is also possible that micronutrient levels which are not explicitly deficient, but still limited, could confer developmental risk. The present study aims to assess the severity of thiamine, iron, and vitamin A deficiency in a sample of infants participating in a randomized control trial (RCT) in rural Cambodia (Whitfield et al., 2019). Methods: Data were collected in Kampong Thom, Cambodia from exclusively breastfed infants (n=335) participating in a four armed RCT; mothers were supplemented with thiamine (0, 1.2, 2.4, 10 mg/day dosage levels) across the first 6 months postpartum. Infant blood at 6 months was assayed for erythrocyte transketolase activity coefficient (ETKac) for thiamine, ferritin for iron, and retinol binding protein (RBP) for vitamin A. Neurocognition was assessed at 6 and 12 months with Mullen Scales of Early Learning (MSEL). Results: 4.8% (3.6% to 5.7%) of the sample was deficient on each of the micronutrient biomarkers, whereas upwards of 36.5% (26.3% to 52.2%) were marginally deficient. Correlational analysis further revealed that measures of infant thiamine, vitamin A, and iron were associated with infant language development at one or both of the 6- and 12-month timepoints. Additional multivariate regression models are underway to explore the joint and interactive effects of all three micronutrients on infant language and neuro-cognitive development more generally. Conclusions: Our findings underscore that infants in rural Cambodia face risk of deficiency on multiple micronutrients, and these deficiencies – even at marginal levels – are associated with negative consequences for their language development. Results will be considered in terms of the collective impact that multiple micronutrient deficiencies hold for infants’ neuro-cognitive development across the first year of life. These findings will contribute in significant ways to designing nutritional interventions to protect infants' neurocognitive outcomes. Funding Sources: New York Academy of Sciences and the Bill and Melinda Gates Foundation.
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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 | 0.001 |
| 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) | 0.000 | 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".