Prospective associations of sleep duration and screen time with transition from overweight/obesity to normal BMI in U.S. adolescents
Bibliographic record
Abstract
BACKGROUND: Shorter sleep duration and longer screen time are established risk factors for adolescent obesity. However, the extent to which these behaviors are prospectively associated with the transition back from overweight/obesity to a healthy status remains unclear. We examined whether sleep duration and screen time among adolescents with overweight/obesity are associated with the likelihood of transitioning to a normal body mass index (BMI). METHODS: We used data from 3498 U.S. adolescents aged 9-11 years with overweight/obesity (45.1% female), from the Adolescent Brain Cognitive Development (ABCD) Study. Cox proportional hazards models examined the prospective associations of parent-reported sleep duration (9-11, 8-9, 7-8, and <7 h/day) and screen time (hours/day) with a shift from overweight/obesity (BMI percentile ≥85) to a normal (BMI percentile <85) accounting for key covariates including pubertal status. RESULTS: Over a median 657 days of follow-up, 643 (18.4%) adolescents transitioned from overweight/obesity to a normal BMI percentile. Compared with those sleeping 9-11 h, adolescents sleeping 7-8 h were less likely to transition to a normal BMI percentile (hazard ratio [HR]: 0.60, 95% CI 0.44, 0.82), with significant dose-response trend (p for trend = 0.003). The association remained significant in sex-stratified analyses for both females (HR: 0.55, 95% CI 0.30, 0.98) and males (HR: 0.59, 95% CI 0.41, 0.86), with similar significant trend in both groups (p for trend <0.05). Higher screen time was not associated with transitioning to a normal BMI overall (HR: 0.99, 95% CI 0.96, 1.02) or by sex (females, HR: 1.00, 95% CI 0.95, 1.05; males, HR: 0.99, 95% CI 0.95, 1.02). CONCLUSION: Short sleep duration was prospectively associated with a lower likelihood of transitioning to a normal BMI among adolescents with overweight/obesity. This association warrants further investigation as a potential intervention target.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".