Sleep duration and growth outcomes across the first two years of life in the GUSTO study
Bibliographic record
Abstract
BACKGROUND AND AIM: Short sleep duration is thought to be a factor contributing to increased body mass index (BMI) in both school-age children and adults. Our aim was to determine whether sleep duration associates with growth outcomes during the first two years of life. STUDY DESIGN: Participants included 899 children enrolled in the Growing Up in Singapore Towards healthy Outcomes (GUSTO) birth cohort study. Anthropometric data (weight and body length) and parental reports of sleep duration were collected at 3, 6, 9, 12, 18, and 24 months of age. A mixed-model analysis was used to evaluate the longitudinal association of BMI and body length with sleep duration. In subgroup analyses, effects of ethnicity (Chinese, Indian, and Malay) and short sleep at three months of age (≤12 h per day) were examined on subsequent growth measures. RESULTS: In the overall cohort, sleep duration was significantly associated with body length (β = 0.028, 95% confidence interval [CI] 0.002-0.053, p = 0.033), but not BMI, after adjustment for potential confounding factors. Only in Malay children, shorter sleep was associated with a higher BMI (β = -0.042, 95% CI -0.071 to -0.012, p = 0.005) and shorter body length (β = 0.079, 95% CI 0.030-0.128, p = 0.002). In addition, shorter sleep was associated with a higher BMI and shorter body length in children who slept ≤12 h per day at three months of age. CONCLUSION: The association between sleep duration and growth outcomes begins in infancy. The small but significant relationship between sleep and growth anthropometric measures in early life might be amplified in later childhood.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".