Cross‐sectional and prospective associations of sleep duration and bedtimes with adiposity and obesity risk in 15 810 youth from 11 international cohorts
Bibliographic record
Abstract
OBJECTIVES: To investigate associations of bedtimes and sleep durations with adiposity levels in children and adolescents. METHODS: Individual data were pooled for 12 247 children (5819 with follow-up adiposity at 2.3 ± 1.4 years post-baseline) and 3563 adolescents from 11 international studies. Associations between questionnaire-based sleep durations, bedtimes and four groups of combined bedtimes and sleep lengths (later-shorter [reference]/earlier-shorter/later-longer/earlier-longer) with measured adiposity (body mass index [BMI] and waist circumference z-scores) and weight status, were investigated. RESULTS: In children, longer sleep durations were consistently associated with lower adiposity markers, and earlier bedtimes were related to lower BMI z-score. Compared to sleeping <10 h, longer baseline sleep duration favourably predicted Δwaist z-score in girls (≥10 and <11 h (β-coefficient (95% confidence interval [CI])): -0.06 (-0.12 to -0.01)) and boys (≥11 h: -0.10 [-0.18 to -0.01]). Combined groups that were defined by longer sleep (later-longer and earlier-longer sleep patterns) were associated with lower adiposity, and later-longer sleep favourably predicted Δwaist z-score in girls (-0.09 [-0.15 to -0.02]). In adolescents, longer sleep durations and earlier bedtimes were associated with lower BMI z-score in the whole sample, and also with lower waist z-score in boys. Combined groups that were characterized by earlier bedtimes were associated with the same outcomes. For example, earlier-shorter (-0.22 (-0.43 to -0.01) and earlier-longer (-0.16 (-0.25 to -0.06) sleep were both associated with lower BMI z-score. CONCLUSIONS: If the associations are causal, longer sleep duration and earlier bedtimes should be targeted for obesity prevention, emphasizing longer sleep for children and earlier bedtimes for adolescents.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".