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Record W4312104139 · doi:10.1093/geroni/igac059.2067

FACTORS ASSOCIATED WITH COGNITIVE FUNCTION AMONG OLDER ADULTS IN VIETNAM

2022· article· en· W4312104139 on OpenAlexaboutno aff
Yasuhiko Saito, Choy Lye Chei, Vu Cong Nguyen, Linh Dong

Bibliographic record

VenueInnovation in Aging · 2022
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Health and Risk Factors
Canadian institutionsnot available
Fundersnot available
KeywordsCognitionGerontologySocioeconomic statusCognitive declinePsychologyMontreal Cognitive AssessmentMedicineDementiaEnvironmental healthPopulationCognitive impairmentPsychiatryDisease

Abstract

fetched live from OpenAlex

Abstract While Viet Nam is aging rapidly, there are few studies on cognitive function of older adults. We aimed to study status of cognitive function among older adults in Viet Nam and examine factors associated with cognitive function. The baseline data of the Longitudinal study of Ageing and Health in Viet Nam conducted in 2018/2019 was used for the study. LSAHV was a nationally representative survey of those aged 60 and above and computer-assisted personal interview (CAPI) using a tablet was conducted for data collection. The number of older person included in the study was 5,530. Cognitive function was measured by Short Portable Mental Status Questionnaire (SPMSQ). Factors such as demographic, socioeconomic, health behavior and daily activities such as reading newspaper were examined for their association with cognitive function by linear regression analyses. We found that better cognitive function was associated with engaging in physical activity in both male and female, listening to radio and receiving material support from children in male, and reading in female. Poorer cognitive function was associated with IADL limitation and financial support in both male and female, obesity in male, and hypertension and hearing loss in female. Our study provides an understanding of the associated factors with cognitive function of older people in Viet Nam. Some of the factors examined are modifiable and can be improved to prevent cognitive decline. It is also important to consider sex differences in planning and implementation of interventions and programs to prevent cognitive decline in Viet Nam.

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 score0.005
Threshold uncertainty score0.369

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
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 head0.022
GPT teacher head0.273
Teacher spread0.251 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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