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Record W4379882713 · doi:10.3389/fmed.2023.1190831

The direct and mediating effects of cognitive impairment on the occurrence of falls: a cohort study based on community-dwelling old adults

2023· article· en· W4379882713 on OpenAlexaboutno aff
Tianyi Zhang, Cunmei Yang, Gangming Shu, Chang Gao, Hongying Ma, Lin Zou, Jing Zuo, Shaoni Liu, Jin Yan, Yixin Hu

Bibliographic record

VenueFrontiers in Medicine · 2023
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsnot available
Fundersnot available
KeywordsCognitionMediationMontreal Cognitive AssessmentOdds ratioCohortPoison controlMedicinePsychologyCohort studyCognitive testGerontologyClinical psychologyCognitive impairmentPsychiatryInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

Background: Cognitive impairment has been reported to be associated with falls in older adults. However, the complex relationship among falls, cognitive impairment and its associated factors, which could be targeted with specific interventions, remains to be elucidated. This study aimed to examine the direct effects of cognitive impairment on falls, to identify the factors associated with cognitive impairment and to explore the mediation role of cognitive impairment in the association of fall with cognition related factors. Methods: This 1-year follow-up cohort study enrolled old adults aged 60 years or over. Information about demographic and anthropometric characteristics, fall outcomes, function and nutritional status were collected through face-to-face interview. Cognitive function was evaluated by the Montreal Cognitive Assessment (MoCA). Multivariable regression analyses were used to test the association between cognitive impairment and falls and to identify the factors related to cognitive impairment. Additionally, we conduct causal mediation analyses to estimate the mediation effects of cognitive impairment in the pathways of fall occurrence. Results: Of the 569 participants included in this study, 366 (64.32%) had cognitive impairment, 96 (16.87%) had fall history in the past 1 year, 81 (14.24%) experienced fall and 47 (8.26%) received treatment because of falling during the 1-year follow-up. The association between cognitive impairment and 1-year fall risk was confirmed after adjusting for multiple covariates [odds ratio (OR):2.03, 95% confidence interval (CI): 1.13-3.80]. IADL disability, depression and low grip strength were associated with a higher prevalence of cognitive impairment. While overweight, higher education and higher income level were found to be related to a lower risk of cognitive impairment. Among these associated factors, cognitive impairment mediated the positive association of falling with IADL ability and depression, and a negative relationship with education and income level. Conclusion: Our study not only confirmed the direct influence of cognitive impairment on fall risk in older adults, but also suggested a mediating role that cognitive impairment played in the pathways of fall occurrence. Our finding could help develop more specific interventions for fall prevention.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.026
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.021
GPT teacher head0.345
Teacher spread0.324 · 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

Citations3
Published2023
Admission routes1
Has abstractyes

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