Risk of falls and fear of falling in older adults residing in public housing in Ontario, Canada: findings from a multisite observational study
Bibliographic record
Abstract
BACKGROUND: Falls in older adults is a widely researched topic. However, older adults residing in public housing are a vulnerable population that may have unique risk factors for falls. This study aims to describe the prevalence and risk factors for falls, fear of falling, and seeking medical attending for falls in this population. METHODS: Sociodemographic and health-related data was collected as part of a community-based health assessment program with older adults in public housing. Three pre-screening questions identified individuals at potential risk for falls; individuals who screened positive performed the objective Timed Up and Go (TUG) test. Logistic regression was used to evaluate risk factors for four outcome variables: falls in the past year, seeking medical attention for falls, fear of falling, and objectively measured fall risk via TUG test. RESULTS: A total of 595 participants were evaluated, of which the majority were female (81.3%), white (86.7%), did not have a high school diploma (50.0%), and reported problems in mobility (56.2%). The prevalence of falls in the past year was 34.5%, seeking medical attention for falls was 20.2% and fear of falling was 38.8%. The TUG test was completed by 257 participants. Notably, males had significantly reduced odds of seeking medical attention for a fall (OR = 0.50, 95%CI 0.25-0.98) and having a fear of falling (OR = 0.42, 95%CI 0.24-0.76); daily fruit and vegetable consumption was associated with decreased odds of having a fall in the past year (OR = 0.55, 95%CI 0.37-0.83), and alcohol consumption was associated with increased odds of fear of falling (OR = 1.72, 95%CI 1.03-2.88). CONCLUSION: Older adults residing in public housing have unique risk factors associated with social determinants of health, such as low fruit and vegetable consumption, which may increase their risk for falls. The findings of this study can be used to inform falls interventions for this population and identify areas for further research.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".