0189 High Levels of Sleep Disturbance across Early Childhood Increases Cardiometabolic Disease Risk Index in Early Adolescence: Longitudinal Sleep Analysis Using the HOME Study
Bibliographic record
Abstract
Abstract Introduction Sleep is a predictor of cardiometabolic disease (CMD) risk, and new evidence links early childhood sleep to later CMD risk. This study examines the impact of early childhood sleep duration, bedtime timing, and sleep disturbance on a CMD risk score in early adolescence. Methods Within the Health Outcomes and Measures of Environment (HOME) Study, a prospective pregnancy and birth cohort study, we assessed sleep patterns among 346 children using the Children’s Sleep Habits Questionnaire from ages 2 to 8 years. We calculated cardiometabolic risk scores ate age 12 for 183 of these children from visceral adiposity area, blood pressure, fasting serum triglyceride, high density lipoprotein, leptin, and adiponectin concentrations. We used a group-based semi-parametric mixture model to identify distinct trajectories in sleep duration, bedtime timing, and sleep disturbance for the entire sample. We then examined the associations between sleep trajectories and CMD risk score using general linear models for children with a CMD risk score, using both an unadjusted model (no covariates) and an adjusted model (adjusting for child pubertal stage, child sex, duration of breastfeeding, household income, and maternal education). Results Three sleep trajectories emerged for bedtime timing (late timing, medium timing, and early timing) and for sleep disturbance (high, medium, and low), and two for sleep duration (high and low). In the unadjusted model, we found significant differences in CMD risk scores by trajectories of sleep disturbance. Children in the ‘high’ trajectory had higher CMD risk scores (Least Square Mean=1.51; 95% CI: 0.39, 2.64) than those in the ‘low’ trajectory (Least Square Mean =-0.51; 95% CI: -1.16, 0.15; p=.002) and ‘medium’ trajectory (Least Square Mean=-0.15; 95% CI: -1.14, 0.85; p=.03). These findings only approached significance after adjusting for covariates. No significant differences in CMD risk were observed for bedtime timing or total sleep time trajectories in the unadjusted or adjusted models. Conclusion In this cohort, parent-reported sleep disturbance in early childhood was associated with more adverse cardiometabolic profiles in early adolescence. Our findings suggest that trials to reduce CMD risk via sleep interventions – which have been conducted in adolescents and adults – may be implemented too late. Support (If Any) National Institute of Environmental Health Sciences grants PO1 ES11261, R01 ES014575, R01 ES020349, R01 ES027224, R01 ES025214.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".