Insomnia and Neurocognitive Functioning in Cognitively Healthy Older Adults
Bibliographic record
Abstract
Abstract Background Insomnia is the most common sleep disorder in older adults, affecting the ability to fall and stay asleep for approximately 15‐35% of aging adults (Buysse et al., 2011). Additionally, sleep fragmentation and disordered sleep are well‐established symptoms of Alzheimer’s disease (AD). Patients and their caregivers frequently find these sleep changes distressing; however, the relationship between insomnia and preclinical Alzheimer’s disease remains unclear. The purpose of the present study is to compare performance on neurocognitive measures between cognitively healthy older adults with and without clinician‐determined insomnia to assess whether insomnia acutely impacts cognitive functioning. Method Data were obtained from the National Alzheimer’s Coordinating Center (NACC) database. As part of ongoing data collection, NACC participants completed surveys and underwent a neuropsychological evaluation. Participants who were cognitively healthy at baseline, reported insomnia status, and were at least 65 years of age were included (N = 3,733). Clinicians determined the presence of insomnia (present/absent). A series of Welch’s t‐tests were used to compare insomnia status groups on demographic factors (age, educational attainment, and sex) as well as neurocognitive measures typically related to Alzheimer’s disease (animal and vegetable fluency, letter fluency, Trail‐Making Test, Benson Complex Figure delayed recall, Montreal Cognitive Assessment delayed recall). Result Preliminary analyses of sample characteristics found evidence that individuals with insomnia were older than those without insomnia (t(784.11) = 2.046, p = 0.041). As expected, clinician‐determined insomnia was more common in men than women (χ2 (1) = 29.638, p < .001). Group comparisons indicated no cross‐sectional relationship between insomnia status and neurocognitive measures (all p >.05, all d ≤ .06). Conclusion Disordered sleep is often seen in Alzheimer’s disease, yet the nature and timing of this relationship are unclear. We found no association between insomnia status and neurocognitive performance in a large, cross‐sectional sample of healthy older adults. It is possible that sleep disturbance is not a preclinical symptom of AD but instead may emerge closer to or following AD diagnosis. Alternatively, the nature of the disordered sleep may not be related to insomnia per se but could reflect difficulty sleeping during the night and remaining awake during the day.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| 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".