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Record W7117239900 · doi:10.1002/alz70857_103902

Subjective Sleep Characteristics and Cognitive Impairment from Ages 60 to 90+: A Pooled Analysis of Four Prospective Cohorts

2025· article· en· W7117239900 on OpenAlexaff
Yi Fang, Allysa Quick, Sasha Milton, Kristine Yaffe, Katie L Stone, Andrew Lim, Lisa Laverne Barnes, Bennett Da, Meredith L. Wallace, Yue Leng

Bibliographic record

VenueAlzheimer s & Dementia · 2025
Typearticle
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCognitive impairmentPooled analysisSomnolenceSleep (system call)CognitionActigraphyProspective cohort studyCognitive decline

Abstract

fetched live from OpenAlex

BACKGROUND: Aging is associated with changes in sleep and cognitive function. While disrupted sleep is linked to cognitive decline, little is known about how subjective sleep characteristics relate to cognitive impairment across different age groups, particularly in the oldest old. METHOD: We harmonized data on self-reported sleep, cognitive outcomes, and covariates across four U.S. cohorts: the Memory and Aging Project (MAP), Minority Aging Research Study (MARS), Osteoporotic Fractures in Men Study (MrOS), and Study of Osteoporotic Fractures (SOF). Sleep measures included sleep duration, time in bed, subjective sleep quality, excessive daytime sleepiness, and difficulty falling/staying asleep. Cognitive outcomes, including mild cognitive impairment (MCI) and dementia, were assessed through clinical diagnoses, crosswalk MMSE scores (MrOS and SOF), and adjudicated diagnosis (MAP and MARS). Using Poisson regression, we examined associations between sleep characteristics and incident cognitive impairment in age-stratified groups (60-70, 70-80, 80-90, 90+ years), adjusting for age, sex, race, marital status, follow-up time, smoking, alcohol use, sleep medication use, depression, hypertension, and diabetes. RESULT: After exclusion of baseline MCI and dementia (N = 208), the pooled cohort (N = 4935; 60-70: N = 428, 70-80: N = 2306, 80-90: N = 2070, 90+: N = 131) included 2061 (41.8%) females and 849 (17.2%) non-White participants. During a mean follow-up of 3.92±1.17 years, 867 (17.6%) developed MCI or dementia. Prolonged sleep duration (>8 hours/day) in the 90+ age group (Risk Ratio [RR] = 2.167, 95% CI 1.327∼3.539, p = 0.002), and excessive time in bed (> 8 hours/day) in the 80-90 age group (RR = 1.201, 95% CI 1.037∼1.389, p = 0.014) were associated with an increased risk of cognitive impairment. Difficulty staying asleep >=3 times /week was associated with lower risk of cognitive impairment in the 80-90 age group (RR = 0.831, 95% CI 0.720∼0.959, p = 0.011). No significant associations were observed in other age groups and for other sleep characteristics. CONCLUSION: Prolonged sleep duration and excessive time in bed were associated with a higher risk of cognitive impairment in adults over 80, independent of comorbidities. These findings highlight somnolence as a potential marker for cognitive impairment in advanced aging, suggesting that tailored sleep monitoring could aid detection.

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)0.007
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.007
Bibliometrics0.0030.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.010
GPT teacher head0.280
Teacher spread0.269 · 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 designMeta-analysis
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
Published2025
Admission routes1
Has abstractyes

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