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Record W4407241276 · doi:10.1186/s12889-025-21649-z

Dose-response associations of device-measured sleep regularity and duration with incident dementia in 82391 UK adults

2025· article· en· W4407241276 on OpenAlexaff
Raaj Kishore Biswas, Matthew Ahmadi, Yu Sun Bin, Svetlana Postnova, Andrew J. K. Phillips, Nicholas A. Koemel, Jean‐Philippe Chaput, Shantha M. W. Rajaratnam, Peter A. Cistulli, Emmanuel Stamatakis

Bibliographic record

VenueBMC Public Health · 2025
Typearticle
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsWilfrid Laurier UniversityChildren's Hospital of Eastern OntarioUniversity of Ottawa
FundersNational Health and Medical Research CouncilMedical Research Council
KeywordsDementiaMedicineHazard ratioProportional hazards modelProspective cohort studyCohort studyCohortSleep (system call)PopulationGerontologyInternal medicineConfidence interval

Abstract

fetched live from OpenAlex

BACKGROUND: Sleep is a crucial lifestyle factor with impacts on mental and cognitive health. The associations between objectively measured sleep and risk of incident dementia are not yet fully understood. To evaluate the associations of device-measured sleep duration and regularity with incident dementia and explore whether sleep regularity moderates the association of sleep duration with dementia. METHODS: Population-based prospective cohort study of 82,391 adults aged 43 to 79 years from the UK Biobank accelerometry subsample, collected between 2013 and 2015, followed up to 2022. Device-based sleep duration (h/day) and sleep regularity index (SRI), a metric ranging from 0-100 that quantifies a person's sleep regularity (with a greater value indicating higher consistency), were calculated from wrist-worn accelerometry data recorded over the course of one week. Incident all-cause dementia cases were obtained from national hospital admission, primary care and mortality data followed up to 30 November 2022. We used Cox proportional hazard models to estimate the hazard ratios (HRs) for incident dementia after adjustment for common demographic and clinical covariates. RESULTS: Over a mean follow-up of 7.9 years, 694 incident dementia cases occurred. We observed a U-shaped association between sleep duration and incident dementia, with only short sleep (< 7 h) being significantly associated with a higher risk of dementia. The median sleep duration for short sleepers (< 7 h) of 6.5 h, compared to the reference point of 7.9 h was associated with HR of 1.19 (95%CI 1.01,1.40) for incident dementia. Sleep regularity was negatively associated with dementia risk in a near-linear fashion (linear p = 0.01, non-linear p = 0.57). When we dichotomized sleep regularity, those in the higher sleep regularity group (SRI ≥ 70) had an HR of 0.74 (95%CI 0.63, 0.87) compared to those with lower sleep regularity (SRI < 70). The beneficial associations between sleep regularity and incident dementia were present only among participants with short (< 7 h) and long (≥ 8 h) sleep duration. CONCLUSIONS: Assuming that the associations we observed are causal, maintaining a regular sleep pattern may help offset the deleterious association of inadequate sleep duration with dementia. Interventions aimed at improving sleep regularity may be a viable option for people not able to achieve the recommended hours of sleep.

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)0.004
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 score0.026
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.031
GPT teacher head0.330
Teacher spread0.298 · 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

Citations7
Published2025
Admission routes1
Has abstractyes

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