Sleep Health and White Matter Integrity in the UK Biobank
Bibliographic record
Abstract
Impaired sleep health is common in the communityplace, yet knowledge about its neurobiological correlates basis is limited fragmentary. Impaired white matter integrity has been discussed as a potential correlate that could also shed light on the various health effects that accompany poor sleep health . Previous studies have found associations between white matter integrity and several sleep characteristics but these studies were often limited by sub-optimal classification of exposures/outcomes and small . However, both white matter and sleep variables were often only evaluated to a limited extent and in small sample size. Here, we thoroughly correlate multiple indices of white matter integrity and sleep health in 29,114the UK Biobank participantscohort (n = 29,114). Several sleep traits were independently associated with impaired white matter integrity: Late chronotype, daytime sleepiness, insomnia symptoms and, most strongly, long sleep duration were associated with diffusion MRI markers of reduced white matter integrity. In contrast, the previously supposed association between insomnia symptoms and decreased fractional anisotropy (FA) in the anterior internal capsule could not be replicated. To sum up, the present large-scale correlational study found for the first time a strong link between long sleep duration and impaired white matter integrity, while rejecting previously held assumptions concerning associations between insomnia and short sleep duration with white matter integrity.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".