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Record W4388771071 · doi:10.1177/00914150231208689

Social Capital Associates With Better Cognitive Health, Oral Health and Epigenetic Age Deceleration: Findings From the Canadian Longitudinal Study on Aging

2023· article· en· W4388771071 on OpenAlexafffundabout
Noha Gomaa

Bibliographic record

VenueThe International Journal of Aging and Human Development · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsChildren’s Health Research InstituteLawson Health Research InstituteWestern University
FundersSchulich School of Medicine and DentistryCanadian Institutes of Health ResearchSchulich School of Medicine and Dentistry, Western UniversityGovernment of CanadaLawson Health Research Institute
KeywordsEpigeneticsCognitionLongitudinal studySocial capitalHealth and Retirement StudyGerontologyMedicinePsychologyDemographyBiologyPsychiatryGeneticsPathologySociology

Abstract

fetched live from OpenAlex

Background: Social exposures are linked to an array of health outcomes, especially around aging. In this study, we examined the association of social capital, defined as social relationships and networks, with clinical and biological outcomes including cognitive health, oral inflammation, and epigenetic aging. Methods: We used data from the Canadian Longitudinal Study on Aging (CLSA) ( n = 1,479; aged 45–85 years), categorizing social capital as structural and cognitive capital. Oral inflammation was determined as the presence of gum bleeding. Epigenetic aging was computed as the difference between chronological age and DNA methylation age. We constructed multivariable regression models adjusted for covariates to assess the relationships of interest. Results: Higher structural social capital was associated with decelerated epigenetic aging and better cognitive health outcomes, while higher cognitive social capital was associated with better cognitive outcomes and less oral inflammation. Conclusion: Enhanced social capital may contribute to better clinical and biological outcomes around aging.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.071
Threshold uncertainty score0.943

Codex and Gemma teacher scores by category

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

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 head0.064
GPT teacher head0.350
Teacher spread0.286 · 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 teacher head, 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

Citations12
Published2023
Admission routes3
Has abstractyes

Explore more

Same venueThe International Journal of Aging and Human DevelopmentSame topicEpigenetics and DNA MethylationFrench-language works237,207