Background The Stopping Elderly Accidents, Deaths and Injuries (STEADI) screening algorithm aligns with current fall prevention guidelines and is easy to administer within clinical practice. However, the stratification into low, moderate and high risk categories limits the meaningful interpretation of the fall-related risk factors.
Methods Baseline measures from a modified STEADI were used to predict self-reported falls over 4 years in 3170 respondents who participated in the 2011–2015 National Health and Aging Trends Study. A point method was then applied to find coefficient-based integers and 4-year fall risk estimates from the predictive model. Sensitivity and specificity estimates from the point method and the combined moderate and high fall risk STEADI categories were compared.
Results There were 886 (27.95%) and 387 (12.21%) respondents who were classified as moderate and high risk, respectively, when applying the stratification method. Falls in the past year (OR: 2.16; 95% CI: 1.61 to 2.89), multiple falls (OR: 2.94; 95% CI: 1.89 to 4.55) and a fear of falling (OR: 1.77; 95% CI: 1.45 to 2.16) were among the significant predictors of 4-year falls in older adults. The point method revealed integers that ranged from 0 (risk: 27.21%) to 44 (risk: 99.71%) and a score of 10 points had comparable discriminatory capacity to the combined moderate and high STEADI categories.
Conclusion Coefficient-based integers and their risk estimates can provide an alternative interpretation of a predictive model that may be useful in determining fall risk within a clinical setting, tracking changes longitudinally and defining the effectiveness of an intervention.
- hip facture
- older people
Data availability statement
Data are available in a public, open access repository at https://www.nhats.org/.
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Contributors BCH—conceptualised the research idea and study design, conducted the analysis, interpreted the data and wrote the first draft of the manuscript. KAK—assisted with the development of the research questions and completed multiple reviews of the manuscript. JEW—advised on and supported the study design and research questions, conceptualised the theory supporting the research and completed multiple reviews of the manuscript. KT—helped come up with the statistical approach for each study objective, supported the study design and research questions, and completed multiple reviews of the manuscript. MVP—assisted with the development of the research questions, advised on and supported the study design, and completed multiple reviews of the manuscript.
Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
Competing interests None declared.
Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
Provenance and peer review Not commissioned; externally peer reviewed.
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