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Record W3111572177 · doi:10.1002/alz.041154

The role of cognitively stimulating activities throughout the lifespan on risk and timing of conversion to dementia

2020· article· en· W3111572177 on OpenAlexaff
Nathan A. Lewis, David A. Bennett, Scott M. Hofer

Bibliographic record

VenueAlzheimer s & Dementia · 2020
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsDementiaCognitive reserveCognitionNeuropathologyPsychologyCognitive declineGerontologyPathologicalClinical psychologyMedicineDevelopmental psychologyCognitive impairmentDiseasePsychiatryInternal medicine

Abstract

fetched live from OpenAlex

Abstract Background Previous research suggests that modifiable lifestyle factors, such as engagement in cognitively stimulating activities, contributes to cognitive reserve such that some individuals can tolerate more pathological burden before cognitive symptoms emerge. However, it is unclear whether such benefits persist throughout the lifespan or are limited to certain critical periods. The present study sought to explore if cognitive engagement at various points in the lifespan uniquely contributes to cognitive reserve in late life. Method Data were from 1977 older adults from the Memory and Aging Project without dementia at study onset (M age = 80.10 at baseline). Cognitive assessments were performed annually for an average of 7.42 years until death. Each participant agreed to brain donation for post‐mortem analysis of neuropathologies. Multistate survival modeling was used to examine the influence of lifelong cognitive engagement on risk of transitioning between normal cognition, mild cognitive impairment (MCI), dementia, and death states. Life expectancies for individuals with and without cognitive impairment were then estimated. An additional model was run for participants with available neuropathology data (n = 841), accounting for overall pathological burden. Results A total of 560 participants developed dementia during the follow‐up period. Cognitive activity in childhood, young and middle adulthood were included as predictors of risk of transitioning between cognitive states, controlling for age, sex, and education. Only midlife cognitive activity predicted cognitive transitions, with higher activity predicting decreased risk of developing MCI (OR = .82, 95% CI: .71, .95). In the subset of participants with pathology data, cognitive activity in midlife predicted decreased risk of transitioning to MCI (OR = .74, 95% CI: .61, .90) after accounting for pathologic burden. Midlife cognitive activity moderated the effect of pathological burden such that individuals high in pathology and high in cognitive activity were more likely to transition directly from healthy cognition to death without developing impairment. Conclusion With no known cure for Alzheimer’s Disease, delaying the onset of cognitive decline represents a key target for future dementia research. These findings suggest that cognitive engagement in midlife may help to delay impairment and buffer the effect of brain pathologies on cognition.

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)0.006
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 score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.036
GPT teacher head0.323
Teacher spread0.287 · 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
Published2020
Admission routes1
Has abstractyes

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