Frailty and Risk of Falls in Community-Dwelling Older Adults Living in a Rural Setting. The Atahualpa Project
Bibliographic record
Abstract
BACKGROUND: Data supporting a link between frailty and risk of falls is mostly confined to individuals living in urban centers, where risk factors and lifestyles are different from that of rural settings. OBJECTIVE: To assess the association between frailty and risk of falls in older adults living in rural Ecuador. DESIGN: Population-based cross-sectional study. PARTICIPANTS: Community-dwellers aged ≥60 years living in a rural Ecuadorian village, in whom frail status and risk of falls were assessed. MEASUREMENTS: Frailty was evaluated by the Edmonton Frailty Scale (EFS) and risk of falls by the Downton Fall Risk Index (DFRI). Multivariate models were fitted to evaluate whether frailty was associated with risk of falls (dependent variable), after adjusting for demographics, alcohol intake, cardiovascular risk factors, sleep quality, symptoms of depression, and history of an overt stroke. Correlation coefficients were constructed to assess confounders modifying this association. RESULTS: A total of 324 participants (mean age: 70.5±8 years) were included. The mean EFS score was 4.4±2.5 points, with 180 (56%) participants classified as robust, 76 (23%) as pre-frail and 68 (21%) as frail. The DFRI was positive in 87 (27%) participants. In univariate analysis, the EFS score was higher among participants with a positive DFRI (p<0.001). The number of frail individuals was higher (p<0.001), while that of robust individuals was lower (p<0.001) among those with a positive DFRI. Adjusted logistic regression models showed no association between frailty and the DFRI. Correlation coefficients showed that age, high glucose levels, and history of an overt stroke tempered the association between frailty and the risk of falls found in univariate analyses. CONCLUSIONS: Frailty is not independently associated with risk of falls in older adults living in a remote rural setting. Further studies are needed to assess the impact of frailty on the risk of falls in these populations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".