MétaCan
Menu
← Back to cohort
Record W7116900856 · doi:10.1002/alz70860_106910

The Effect of Social Determinants of Health on Cognitive Resilience to Alzheimer's Disease, Determined by Plasma <i>p</i> ‐tau217 in the Prospective INDE Cohort in Thailand: A Story from a Middle‐Income Country

2025· article· en· W7116900856 on OpenAlexaboutno aff
Thanapoom Taweephol, Thanakit Pongpitakmetha, Akarin Hiransuthikul, Kittithatch Booncharoen, Watayuth Luechaipanit, Thanaporn Haethaisong, Adipa Chongsuksantikul, Prawit Oangkhana, Poosanu Thanapornsangsuth

Bibliographic record

VenueAlzheimer s & Dementia · 2025
Typearticle
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsCognitionPsychological resilienceResilience (materials science)Social cognitive theoryIntervention (counseling)CohortSocial determinants of healthPublic health

Abstract

fetched live from OpenAlex

BACKGROUND: Social determinants of health (SDOH) contribute to cognitive resilience, ranging from healthy populations to aging individuals with cognitive impairment, including those with Alzheimer's disease (AD) and related dementias. Plasma phosphorylated tau 217 (p-tau217) has been proven to be a specific biomarker reflecting AD pathology and severity (Jack et al., 2024). We aim to assess factors contributing to cognitive resilience among the Thai population. METHOD: We prospectively enrolled participants into the INDE cohort in King Chulalongkorn Memorial Hospital, Bangkok, Thailand (NCT06375213), collecting exhaustive clinical information, neuropsychological tests, and plasma p-tau217. A regression model was fitted with Montreal Cognitive Assessment (MoCA) scores and plasma p-tau217 levels to calculate residuals, representing cognitive resilience. Positive residuals indicate high resilience, whereas negative residuals indicate low resilience. A second regression model examined factors associated with cognitive resilience, focusing on each SDOH, with adjustments for age and sex. RESULT: Among 297 participants (73.4% female and median age 66 years [IQR: 61, 71]), 166 (55.9%) had high resilience (Table 1). A linear regression model showed an inverse relationship between MoCA and log-transformed plasma p-tau217 levels (β = -3.96, p < 0.01), and a box-and-whisker plot illustrated MoCA distribution across resilience groups (Figure 1). Multivariable linear regression analysis demonstrated that property ownership exceeding 10-million-baht, higher educational attainment, and meeting American Heart Association (AHA) physical activity recommendations were significantly associated with greater cognitive resilience. Higher education level correlated with increased resilience in a progressive manner. In contrast, greater distance from the city, current smoking, longer sleep duration, and increased daily sitting time were significantly linked to lower resilience (Table 2). CONCLUSION: SDOH notably impacted cognitive resilience, determined by the residuals of p-tau217 and cognitive score. Public policy and clinical intervention regarding factors associated with cognitive resilience are warranted, even in low- and middle-income countries (LMICs).

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 score0.018
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.015
GPT teacher head0.344
Teacher spread0.329 · 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
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueAlzheimer s & Dementia→Same topicResilience and Mental Health→French-language works237,207→