Impact of Early‐Life Weight Status on Cognitive Abilities in Children
Bibliographic record
Abstract
OBJECTIVE: Whether obesity is associated with childhood cognition is unknown. Given the sensitivity of the developing brain to environmental factors, this study examined whether early-life weight status was associated with children's cognition. METHODS: Using data from mother-child pairs enrolled in the Health Outcomes and Measures of the Environment (HOME) Study (2003-2006), children's early-life weight status was assessed using weight-for-length/height standard deviation (SD) scores. A battery of neuropsychological tests was administered to assess cognition, executive function, and visual-spatial abilities at ages 5 and 8 years. Using linear mixed models, associations between early-life weight status and cognition were estimated. RESULTS: Among 233 children, 167 were lean (≤1 SD) and 48 were nonlean (>1 SD). After covariate adjustment, the results suggest that full-scale intelligence quotient scores decreased with a 1-unit increase in weight-for-height SD score (β = -1.4, 95% CI: -3.0 to 0.1). For individual component scores, with a 1-unit increase in weight-for-height SD score, perceptual reasoning (β = -1.7, 95% CI: -3.3 to 0.0) and working memory (β: -2.4, CI: -4.4 to -0.4) scores decreased. Weight status was generally not associated with other cognition measures. CONCLUSIONS: Within this cohort of typically developing children, early-life weight status was inversely associated with children's perceptual reasoning and working memory scores and possibly with full-scale intelligent quotient scores.
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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 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".