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Record W4406030180 · doi:10.1002/alz.089859

Sleep Duration and Cognitive Performance in Middle‐Aged and Older Adults: What is the Role of Depression?

2024· article· en· W4406030180 on OpenAlexaff
Vanessa M. Young, Rebecca Bernal, Andrée‐Ann Baril, Joy Zeynoun, Crystal Wiedner, Alexa Beiser, Matthew P. Pase, Jayandra J. Himali, Sudha Seshadri

Bibliographic record

VenueAlzheimer s & Dementia · 2024
Typearticle
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsUniversité de MontréalCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalHôpital du Sacré-Cœur de Montréal
Fundersnot available
KeywordsCognitionDementiaPsychologyEffects of sleep deprivation on cognitive performanceDepression (economics)Association (psychology)Sleep (system call)NeuropsychologyAudiologyVerbal memoryClinical psychologyMedicinePsychiatryInternal medicineDisease

Abstract

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BACKGROUND: Recent research has highlighted the importance of sleep on cognitive processes. However, conflicting evidence exists regarding optimal sleep duration and the impact of other co-occurring conditions, such as depression. A diagnosis of depression in mid-life may increase the risk of developing dementia. We examined the association between self-reported sleep duration and cognition and whether depression status modified this relationship. METHOD: Dementia-and-stroke-free participants 45 years and older from the Framingham Heart Study Third-Generation, Omni 2, and New Off-spring Cohorts were included (n = 1,853; age 49.8[SD 9.2] years; 42.69% male; Table 1). Neuropsychological testing assessed verbal learning and memory abilities, abstract reasoning skills, processing speed and visuospatial memory. Depression was defined as having CES-D ≥16 or being under pharmacological treatment (n = 448; 32%). Multivariable linear regression models examined the association between sleep duration categories (≤6h; >6-<9h [reference]; ≥9h), individual cognitive tasks and global cognition, adjusting for age, sex, education and time between sleep and cognitive assessments. A second model included further adjustment for vascular risk factors and APOE4 status. RESULT: Long sleep duration (≥9h) was associated with worse global cognition (β±SE: -0.24±0.07; p<0.001) compared to average sleep duration. In cognitive domain-specific tasks, long sleep was associated with worse verbal learning and memory abilities (-1.50±0.60, p = 0.013), visuospatial memory (-1.74±0.42, p<0.001), and processing speed (-0.08±0.03, p = 0.014), but not with abstract reasoning skills (-0.06±0.28, p = 0.838). Depression status significantly modified the association (global cognition int. p = 0.015; visual int. p = 0.006; and processing speed int. p = 0.038), where long sleep duration was associated with global cognition (-0.34±0.11; p = 0.003), visuospatial memory (-2.16±0.68; p = 0.002), and processing speed (-0.14±0.05; p = 0.011) in those with depression. Long sleep duration was also associated with visuospatial memory in those without depression (-1.27±0.55, p = 0.022) (Table 3). Short sleep duration (≤6h) was not associated with cognition (Table 2) and did not interact with depression status (Table 3). CONCLUSION: Long sleep duration was associated with worse cognition particularly among adults with depression, underscoring the complex sleep-mood-cognition interplay. Further research should explore the longitudinal impacts and causal mechanisms of suboptimal sleep. These findings may inform public health promotion of optimal sleep to maintain cognitive health among persons with depression.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.009
GPT teacher head0.253
Teacher spread0.244 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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