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Record W4408378654 · doi:10.1016/j.jtcms.2025.03.010

Factors influencing cognitive function in Chinese elderly individuals: The role of traditional Chinese medicine in a large-scale cross-sectional study

2025· article· en· W4408378654 on OpenAlexaboutno aff
Houqin Li, Ran Chen, Jing Xia, Feiyu He, Yan Zhang, Shulan Tang, Cheng Ni

Bibliographic record

VenueJournal of Traditional Chinese Medical Sciences · 2025
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
FundersNational Key Research and Development Program of China
KeywordsCognitionScale (ratio)Traditional Chinese medicineFunction (biology)Cross-sectional studyMedicinePsychologyTraditional medicineGerontologyAlternative medicinePsychiatryGeographyPathologyBiologyCartography

Abstract

fetched live from OpenAlex

To identify key factors influencing cognitive function in the elderly, including Traditional Chinese medicine (TCM) constitutional classification, and to rank their relative importance. We used cross-sectional data from seven geographical regions across mainland China. The Changsha version of the Montreal Cognitive Assessment was used to assess cognitive function. A “least absolute shrinkage and selection operator” (LASSO) model, multivariate linear regression analysis, and random forest (RF) model were used. Subgroup analyses were performed to examine the correlation between key TCM constitution types and cognitive function in different population subgroups. A total of 24 803 individuals aged 60 and above were included in the study. We selected 18 influential factors using the LASSO model. Higher education, being married, and having insurance were positively correlated with cognitive function in the elderly (all P < .05). In contrast, poor sleep, vision impairment, hearing impairment, basic activities of daily living disability, instrumental activities of daily living disability, depression, hypertension, coronary heart disease, diabetes, stroke, yang-deficiency constitution (YADC), yin-deficiency constitution (YIDC), qi deficiency constitution (QDC), and blood stasis constitution (BSC) were negatively correlated with cognitive function (all P < .05). YIDC and BSC affected all dimensions of cognitive function (all P < .05). YADC mainly affected attention, language, abstraction (verbal analogies), memory, and orientation to time and place dimensions ( P < .001). QDC mainly affected language and abstraction (verbal analogies) dimensions ( P < .05). The negative correlations between BSC, YADC, YIDC, and QDC scores and cognitive function revealed statistically significant differences across most subgroups. The RF model identified education, BSC, and poor sleep quality as the three most influential factors in our study. BSC, YADC, YIDC, and QDC were associated with cognitive decline in the elderly. Our findings provide new perspectives and significant references for interventions for early-stage cognitive disorders.

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)0.007
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.045
GPT teacher head0.372
Teacher spread0.327 · 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.

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

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