Sleep and circadian health in the UK Biobank: Report on the 2023 sleep questionnaire enhancement
Bibliographic record
Abstract
Abstract Study Objectives Our study introduced the 2023 UK Biobank sleep questionnaire and described variation in sleep health dimensions and prevalence of disordered sleep. Methods A questionnaire comprising validated measures and bespoke items was developed to capture key self-reported domains of sleep health and symptoms of sleep disorders. We quantified cohort prevalence of operationally defined sleep disorders and assessed patterning of sleep health dimensions across key sociodemographic and clinically relevant variables. Results 327,752 individuals were invited of whom 185,056 (56.5%) completed at least one module and were included in the analysis. Respondents were predominately from a White ethnic background (96.8%), had a mean age of 69.9 (SD, 7.5) years, 57.9% were female, and 25.5% were in employment. Compared to non-respondents, respondents were more likely to be female, tended to be better educated, healthier, and exhibit lower levels of socioeconomic deprivation, although baseline sleep variables were similar between respondents and non-respondents. Around 40% of respondents reported sleep duration less than 7 hours and 49% reported poor sleep quality (Pittsburgh Sleep Quality Index > 5). Approximately one-quarter (25.2%) met criteria for at least one operationally defined sleep disorder, with insomnia being the most common (14.4%) followed by obstructive sleep apnoea (8.0%), restless legs syndrome (4.1%), and frequent nightmares (3.7%). Sleep disorders were associated with higher levels of anxiety, depression, fatigue, and cognitive complaints. Conclusions Poor sleep quality and operationally defined sleep disorders are common in the UK Biobank cohort. Sleep questionnaire data can now be integrated with a range of biomedical information to advance understanding of sleep. Statement of significance A comprehensive sleep questionnaire was introduced to the UK Biobank, with over 185,000 participants providing data. Overall, respondents reported relatively poor sleep quality; 40% reported sleep duration less than 7 hours, and 25% met criteria for at least one sleep disorder. Enhanced assessment of sleep in UK Biobank now enables integration with extensive biomedical data, including genetic, wearable, imaging, lifestyle, biomarker, and electronic health record data, offering opportunities to investigate the biological and environmental factors that influence sleep and circadian systems, and their impact on health.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".