Association of sleep duration with cognitive impairment: A mediation by metabolic factors and intracranial atherosclerosis
Bibliographic record
Abstract
BackgroundDespite the association between sleep disorders and mental impairments, controversies persist over the connection between sleep duration and cognitive impairment and the underlying mechanisms remain unexplored.ObjectiveWe investigated this controversial association in a Chinese population and explored the potential mediators.MethodsParticipants (aged 50-75 years) were recruited from a Chinese population-based cohort study, the PRECISE (PolyvasculaR Evaluation for Cognitive Impairment and vaScular Events) study. Sleep duration and Montreal Cognitive Assessment (MoCA) scores were collected during the baseline survey. Participants were divided by sleep duration into short sleep (<7 h), normal sleep (7-9 h), and long sleep (>9 h) groups. The association between sleep duration and MoCA scores was assessed by mediation analysis.ResultsOf the 3028 participants (mean age: 61.1 ± 6.7 years; females: 53.4%), 362 (12.0%) participants were enrolled in the short-sleep group, 2163 (71.4%) in the normal-sleep group, and 503 (16.6%) in the long-sleep group. Long sleep duration was negatively associated with MoCA scores (long versus normal: β = -0.82, 95% CI: -1.21 to -0.43, p < 0.001), after the adjustment for age, sex, education, body mass index, current smoking, and current drinking. The observed association was mediated by cardiometabolic factors (systolic blood pressure and fasting plasma glucose) and intracranial atherosclerotic plaque, with a cumulative mediating proportion of 12.4%.ConclusionsA long sleep duration may be associated with cognitive impairment, which is partially mediated by blood pressure, fasting plasma glucose, and intracranial atherosclerosis. Therefore, individuals who sleep excessively should be monitored for abnormal cardiometabolic factors.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".