The direct and mediating effects of cognitive impairment on the occurrence of falls: a cohort study based on community-dwelling old adults
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".