Shorter and longer durations of sleep are associated with an increased twelve-month prevalence of psychiatric and substance use disorders: Findings from a nationally representative survey of US adults (NESARC-III)
Bibliographic record
Abstract
The lack of comprehensive data on the association between psychiatric and substance use disorders and habitual sleep duration represents a major health information gap. This study examines the 12-month prevalence of mental disorders stratified by duration of sleep. Data were drawn from face-to-face interviews conducted in the National Epidemiologic Survey on Alcohol and Related Conditions III, a nationally representative survey of US adults (N = 36,309). There were 1893 (5.26%) participants who reported <5h of sleep/night; 2434(6.76%) 5 h/night; 7621(21.17%) 6 h/night; 9620(26.72%) 7 h/night; 11,186(31.07%) 8 h/night, and 3245(9.01%) ≥9 h/night. A U-shaped association was observed between sleep duration and all mental disorders. The prevalence of mental disorders was 55% for individuals with <5 h/night and 47.81% for ≥9 h/night, versus 28.24% for the 7 h/night (aOR = 1.90 and 1.39 respectively). The greatest odds ratios were for the <5 h/night group, with an increased risk above 3-fold for panic disorder (PD), post-traumatic stress disorder (PTSD), psychotic disorder, and suicide attempt; between 2 and 3 fold for major depressive disorder (MDD), bipolar disorder (BD), and generalized anxiety disorder (GAD); and between 1 and 2 fold for tobacco and drug use disorders, specific and social phobias. The ≥9 h/night group had an increased risk above 1 to 2-fold regarding tobacco and drug use disorders, MDD, BD, PD, social phobia, GAD, PTSD, psychotic disorder, and suicide attempt. U-shaped associations exist between sleep duration and mental disorders, calling for respect to recommendations for adequate sleep duration in routine clinical care as well as to actions for primary prevention in public health settings.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".