• Matthew C Lohman, Rebecca S Crow, Peter R DiMilia, Emily J Nicklett, Martha L Bruce, and John A Batsis.
• Department of Psychiatry, Dartmouth College Geisel School of Medicine, Hanover, New Hampshire, USA.
• J Epidemiol Community Health. 2017 Dec 1; 71 (12): 1191-1197.

BackgroundPreventing falls and fall-related injuries among older adults is a public health priority. The Stopping Elderly Accidents, Deaths, and Injuries (STEADI) tool was developed to promote fall risk screening and encourage coordination between clinical and community-based fall prevention resources; however, little is known about the tool's predictive validity or adaptability to survey data.MethodsData from five annual rounds (2011-2015) of the National Health and Aging Trends Study (NHATS), a representative cohort of adults age 65 years and older in the USA. Analytic sample respondents (n=7392) were categorised at baseline as having low, moderate or high fall risk according to the STEADI algorithm adapted for use with NHATS data. Logistic mixed-effects regression was used to estimate the association between baseline fall risk and subsequent falls and mortality. Analyses incorporated complex sampling and weighting elements to permit inferences at a national level.ResultsParticipants classified as having moderate and high fall risk had 2.62 (95% CI 2.29 to 2.99) and 4.76 (95% CI 3.51 to 6.47) times greater odds of falling during follow-up compared with those with low risk, respectively, controlling for sociodemographic and health-related risk factors for falls. High fall risk was also associated with greater likelihood of falling multiple times annually but not with greater risk of mortality.ConclusionThe adapted STEADI clinical fall risk screening tool is a valid measure for predicting future fall risk using survey cohort data. Further efforts to standardise screening for fall risk and to coordinate between clinical and community-based fall prevention initiatives are warranted.© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

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