Mechanisms linking height to early child development among infants and preschoolers in rural India
Bibliographic record
Abstract
Stunting has been negatively associated with children's development. We examined the range of height by testing hypotheses: (a) height is positively associated with children's development, with associations moderated by inflammation and (b) home environments characterized by nurturance and early learning opportunities is positively associated with children's development over time and attenuate associations with height. Data included 513 infants (mean age 8.6 months) and 316 preschoolers (mean age 36.6 months) in rural India from a randomized controlled trial of multiple micronutrient powders (MNPs). Measures included height (height-for-age z-scores based on WHO standards), inflammation (C-reactive protein concentration >5 mg/L), nurturance (HOME Inventory), child development (Mullens Scales of Early Learning), and inhibitory control (preschoolers). Linear mixed effects models accounting for repeated measures, clustering, and confounders were used to assess associations between height and child development over time (infants: enrollment, 6 and 12 months; preschoolers: enrollment and 8 months). Moderating effects of inflammation and nurturance were tested with interaction terms. Among infants and preschoolers, height and nurturance were positively associated with all domains of child development over time, with the exception of inhibitory control. Among preschoolers, in the presence of inflammation, height was not associated with child development. Among infants, but not preschoolers, a nurturant home environment attenuated significant associations between height with fine motor and receptive language development. The mechanisms associated with children's development over time are multifactorial and include direct and indirect associations among nutrition, health, and the home environment, as supported by the Nurturing Care Framework.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".