ArticleThe journals of gerontology. Series A, Biological sciences and medical sciences2024
Fall Trajectories in Older Men: Trajectories of Change by Age and Predictors for Future Fall Risk.
Article in The journals of gerontology. Series A, Biological sciences and medical sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Standalone commercial exergame training to improve balance in older adults in care facilities: a systematic review and meta-analysis of recent 10-year randomized controlled trials.BMC geriatrics · 2026Pooled it
- Dynamic transitions in falls and physical activity among older adults in Malaysia: a longitudinal multi-state analysis.BMC public health · 2025Article
Corrections and comments
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Authors and funding
5 authors.
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Abstract
backgroundVery little is known about specific trajectories or patterns of falls over time. Using the well-characterized cohort of the Osteoporotic Fractures in Men Study (MrOS), we classified individuals by fall trajectories across age and identified predictors of group assignment based on characteristics at baseline.
methodsUsing an analysis sample of 5 976 MrOS participants and 15 years of follow-up data on incident falls, we used group-based trajectory models (PROC TRAJ in SAS) to identify trajectories of change. We assessed the association of baseline characteristics with group assignment using 1-way analysis of variance and chi-square tests. Multivariable logistic regression was used to analyze the outcome of the high-risk fall trajectory groups compared to the low-risk groups.
resultsChanges in rates of falls were relatively constant or increasing with 5 distinct groups identified. Mean posterior probabilities for all 5 trajectories were similar and consistently above 0.8 indicating a reasonable model fit. Among the 5 fall trajectory groups, 2 were deemed high risk, those with steeply increasing fall risk and persistently high fall risk. Factors associated with fall risk included body mass index, use of central nervous agents, prior history of diabetes and Parkinson's disease, back pain, grip strength, and physical and mental health scores.
conclusionsTwo distinct groups of high fall risk individuals were identified among 5 trajectory groups, those with steeply increasing fall risk and persistently high fall risk. Statistically significant characteristics for group assignment suggest that future fall risk of older men may be predictable at baseline.
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