0338 Self-reported Multidimensional Sleep Health Is Not Associated with Cognitive Decline and the Risk of Dementia in Two Population-Based Cohort Studies
Bibliographic record
Abstract
Abstract Introduction The links between sleep disturbances, cognitive decline, and dementia are increasingly recognized, but few studies have considered that sleep health is multidimensional. We evaluated how multidimensional sleep health relates to cognitive decline and the risk of dementia in middle-aged and elderly populations. Methods Self-reported sleep health indicators (satisfaction, alertness, timing, efficiency, and duration) were measured in 7892 participants in the Rotterdam Study (RS) (median [Q1-Q3] age: 68.5 [61.6-76.1] years, 58.2% female) and 1601 participants in the Rush Memory and Aging Project and Minority Aging Research Project (MAP/MARS) (79.2 [73.8-85.3] years, 77.3% female). A multidimensional sleep health score was calculated as the number of adverse sleep health indicators. Latent class analysis identified three multidimensional sleep health profiles: average sleep, inefficient sleep, and poor sleep. Sleep health scores, profiles, and individual indicators were related to five cognitive tests measured repeatedly over time (linear mixed effects models) and to risk of dementia (Cox proportional hazards models). Results In RS, 1148 (14.5%) participants developed dementia during a median of 11 (7.7-14.3) years. In MAP/MARS, 287 (17.9%) participants developed dementia during a median of 5.0 (3.0-8.0) years. Multidimensional sleep health scores and profiles were not associated with accelerated cognitive decline or the risk of dementia in either sample (Hazard Ratios [HRs] between 0.72-1.15). The individual indicators early timing (RS: HR 1.60; 95%CI [1.23-2.09]; MAP/MARS: HR 1.37 [0.95-2.00]) and long sleep duration (RS: HR 1.61, [1.34-1.94]; MAP/MARS: HR 1.23 [0.81-1.88]) were associated with a higher risk of dementia. Long sleep duration was associated with accelerated cognitive decline on word learning, substitution, and category fluency tasks in MAP/MARS. Conclusion Self-reported multidimensional sleep health was not associated with cognitive decline and the risk of dementia in two samples of middle-aged and elderly persons. Individual sleep health indicators might be more informative than aggregate measures for predicting cognitive decline and dementia. Future research should consider more complex combinations of self-reported sleep health features and objective measures of sleep. Support (if any) RF1AG056331 (Wallace); R01AG017917 and R01AG022018 (Rush Alzheimer’s Disease Center); the ALIVE flagship, funded by the Convergence of Erasmus MC Rotterdam, Erasmus University Rotterdam and Delft University of Technology (Luik).
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".