Longer sleep duration during infancy and toddlerhood predicts weight normalization among high birth weight infants
Bibliographic record
Abstract
Study Objectives: High birth weight (HBW; ≥ 4000 g) is strongly associated with later overweight, yet little is known about how to disrupt this trajectory. The current study examined sleep practices during infancy and toddlerhood among children born HBW or normal birth weight (NBW; 2500-3999 g). Methods: Latent growth curve models were used to examine sleep during infancy and toddlerhood among 270 mother-child dyads enrolled in the Health Outcomes and Measures of the Environment Study. Total sleep duration in 24 hr, sleep maintenance, and restlessness/vocalizations were collected at 6 month intervals between ages 6 and 24 months. Height and weight were obtained at ages 24 or 36 months, and normal and overweight BMI were derived. Sleep was examined among children with a normal BMI during the preschool years who were either HBW (HBW-Normal, n = 36) or NBW (NBW-Normal, n = 184) compared with overweight preschoolers (Overweight, n = 50). It was predicted that the Overweight group would have poorer sleep across infancy and toddlerhood compared with HBW-Normal and NBW-Normal. Results: HBW-Normal had the longest and Overweight had the shortest mean 24 hr sleep duration across all time points with NBW-Normal falling in-between the two groups. Compared with Overweight, HBW-Normal exhibited longer 24 hr sleep duration at age 6 months with this group difference maintained over infancy and toddlerhood. No group difference was found for NBW-Normal. Conclusions: A longer sleep duration in the first several years of life is associated with development of normal BMI among HBW children. These findings suggest that longer sleep duration may protect HBW children from becoming overweight.
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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 | 0.001 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".