Social epidemiology of multidimensional sleep health in early adolescence
Bibliographic record
Abstract
BACKGROUND: Poor sleep health is a significant concern in adolescents. This study examines the social epidemiology of sleep health in a large, diverse, national US sample of early adolescents. METHODS: We analyzed cross-sectional data from Year 3 (2019-2021) of the US Adolescent Brain Cognitive Development Study to examine adjusted associations between sociodemographic factors and sleep duration, sleep efficiency (percentage of time asleep while in bed), chronotype (midpoint of sleep on free days), and social jet lag (difference in sleep onset between free and school days) using multiple linear regression models. Sleep metrics were derived from the Munich Chronotype Questionnaire. Interaction with race/ethnicity and sleep outcomes by household income and parental education was evaluated. RESULTS: Among 10,082 adolescents (mean age 12.9 ± 0.7), average sleep duration was 8.9 (±1.5) hours, chronotype was 28.3 (midpoint 4:13 a.m.), and social jet lag was 2.3 h. Older age was associated with shorter sleep duration, later chronotype, and greater social jet lag. Gay/bisexual adolescents reported shorter sleep duration, later chronotype, and greater social jet lag. Black, Latino/Hispanic, and Native American adolescents generally had poorer sleep outcomes. Lower-income households were associated with shorter sleep duration and greater social jet lag. Black race and worse sleep outcomes were more strongly associated among higher-income/parental education households. CONCLUSION: Sociodemographic disparities in adolescent sleep call for targeted interventions to promote healthier sleep. IMPACT: Sociodemographic disparities in adolescent sleep health outcomes have been studied, but few have explored associations with multidimensional sleep metrics. US early adolescents reported an average sleep duration of 8.9 h, with 50.5% of 11-12-year-olds and 61.0% of 13-14-year-olds meeting the American Academy of Sleep Medicine's sleep guidelines. Older age, gay/bisexual, Black, Latino/Hispanic, Native American, lower household income, and lower parental education were associated with worse sleep outcomes, including shorter sleep duration, later chronotype, and greater social jet lag. The association between Black race and worse sleep outcomes was stronger among higher-income/parental education households.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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".