Associations between cognitive function, actigraphy‐based and self‐reported sleep in older community‐dwelling adults: Findings from the Irish Longitudinal Study on Ageing
Bibliographic record
Abstract
OBJECTIVE: Cognitive impairment is prevalent in older ages. Associations with sleep are well established; however, ambiguity remains in which sleep characteristics contribute to this impairment. We examined cross-sectional associations between both self-reported and actigraphy-based sleep and cognitive performance across a number of domains in community-dwelling older adults. METHODS: 1520 participants aged 50 and older with self-reported and actigraphy-based total sleep time (TST) (≤5, 6, 7-8, 9 and ≥10 h) and self-reported sleep problems were analysed. Cognitive function was assessed using the Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), verbal fluency, immediate and delayed recall memory, colour trails tests, and choice reaction tests (CRT). Associations between sleep and cognition were modelled using linear and negative binomial regression. RESULTS: Negative associations were found between ≥10 h of self-reported TST and MoCA error rate (incidence rate ratio [IRR] = 1.42; 95% confidence interval [CI] = 1.18, 1.71; p < 0.001); verbal fluency (beta [B] = -2.32 words; 95% CI = -4.00, -0.65; p < 0.01); and delayed recall (B = -0.91 words; 95% CI = -1.58, -0.25; p < 0.05) compared to 7-8 h. Significant associations with actigraphy-based TST were limited to MoCA error rate in ≤5 h (IRR = 1.22; 95% CI = 1.02, 1.45; p < 0.05) compared to 7-8 h. Higher numbers of sleep problems were associated with slower performance in CRT cognitive response time (IRR = 1.02; 95% CI = 1.00, 104; p < 0.05) and total response time (IRR = 1.02; 95% CI = 1.00, 1.04; p < 0.05). CONCLUSIONS: Self-reported long sleep duration was consistently associated with worse cognitive performance across multiple domains. Marginal associations between cognition and both actigraphy-based sleep and self-reported sleep problems were also apparent. These results further affirm poor sleep as a risk factor for cognitive impairment.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".