Risk Factors for Falls in Community-Dwelling Older Adults: An Umbrella Review
Bibliographic record
Abstract
OBJECTIVES: Falls are a key public health concern, resulting in disability and increased mortality risk. An extensive body of literature has examined risk factors for falls; however, results vary across different studies and populations. We aimed to synthesize systematic reviews of fall risk factors in community-dwelling older adults. DESIGN: A systematic review of systematic reviews. Searches were executed in 6 databases (MEDLINE, Embase, CINAHL, Cochrane Library, PsychINFO, and AgeLine) from inception until June 13, 2023. SETTING AND PARTICIPANTS: Eligible studies included systematic reviews of prospective cohort studies that included a population of community-dwelling older adults (≥60 years of age) and reported fall risk factors. METHODS: Three reviewers screened 8173 records. Summary data were extracted, and the units of analyses were the relationships between risk factors and falls. Descriptive results are reported in counts and frequencies. RESULTS: Fifty-seven reviews were included examining 29 risk factors. Mobility-related measures (balance, gait, physical function, physical activity, dual task ability, strength, and range of motion) accounted for 40% of all relationships. Clinical tests of balance and physical function, cognition, specifically executive function (76% significant) and processing speed (100%), medications (58%), frailty (100%), and chronic conditions (83%) were all consistent predictors of falls. There was a paucity of evidence for psychosocial, environmental, and sociodemographic factors. Most reviews (54%) were rated as low risk of bias. CONCLUSIONS AND IMPLICATIONS: Mobility-related risk factors for falls are well established and can be addressed through interventions. Findings highlight the limited examination of psychosocial, sociodemographic, and environmental risk factors for falls, indicating areas for future 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 | 0.006 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.013 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".