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Record W7119532223 · doi:10.15302/entd.2025.120005

Does Vestibular Function Truly Impact Cognitive Changes in the Elderly Population?

2025· article· en· W7119532223 on OpenAlexaboutno aff
Ruiqi Zhang, Yanli Zhao, Jiangli Wei, Ziling Ma, Wenyan Li, Xingdong Chen, Peixia Wu

Bibliographic record

VenueENT Discovery · 2025
Typearticle
Languageen
FieldNeuroscience
TopicVestibular and auditory disorders
Canadian institutionsnot available
FundersFudan University
KeywordsVestibular systemCognitionBalance (ability)Logistic regressionDementiaCorrelationPopulation

Abstract

fetched live from OpenAlex

Background: : Emerging evidence highlights the vestibular system's critical role in cognitive function, though the mechanisms linking vestibular dysfunction to cognitive decline remain unclear, necessitating further large-scale studies. This study aimed to analyze the relationship between vestibular function and cognitive impairment in older adults.Methods: : We assessed the impact of vestibular function on cognitive performance in rural older adults aged 60 and above (n = 479) using data of the 2024 Taizhou Imaging Study Cohort. Vestibular function was measured using the modified Romberg test and self-designed balance questionnaire, while cognitive function was assessed with the MMSE and MoCA scale. Diagnosis of dementia and mild cognitive impairment (MCI) was based on comprehensive cognitive assessments. Correlation analyses and multivariable unconditional logistic regression were performed to evaluate the relationship between vestibular function and cognitive performance.Results: : The average age of the study population was 67.73 years (SD = 3.9). The prevalence of dementia was 7.5%, and the prevalence of mild cognitive impairment was 26.7%. Vestibular dysfunction, as assessed by the modified Romberg test, had a prevalence of 11.4%, while the prevalence of subjective vestibular dysfunction, based on self-reported symptoms from the balance questionnaire, was 19%. The self-reported rate of dizziness was significantly higher in females (24%) compared to males (12.7%) (p = 0.003). Correlation analysis revealed a significant positive correlation between vestibular function and cognitive function (Montreal Cognitive Assessment [MoCA]: r = 0.16, p < 0.05; Mini-Mental State Examination [MMSE]: r = 0.19, p < 0.05). However, logistic regression analysis indicated that vestibular dysfunction was not a significant factor influencing dementia prevalence, while education level and hearing status were identified as protective factors for cognitive function.Conclusions: : Our study reveals a high prevalence of both vestibular dysfunction and cognitive impairment among the elderly in rural China. While there is a significant correlation between vestibular function and cognitive performance, multivariable analysis failed to identify vestibular dysfunction as an independent risk factor for dementia. This suggests that vestibular function may influence overall cognitive abilities but does not directly drive the onset of dementia. Future research is warranted to elucidate the specific mechanisms linking vestibular health to cognitive decline.

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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.012
GPT teacher head0.285
Teacher spread0.273 · 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

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