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Operationalisation and validation of the Stopping Elderly Accidents, Deaths, and Injuries (STEADI) fall risk algorithm in a nationally representative sample
  1. Matthew C Lohman1,2,
  2. Rebecca S Crow2,3,4,
  3. Peter R DiMilia2,4,
  4. Emily J Nicklett5,
  5. Martha L Bruce1,2,
  6. John A Batsis1,2,3,4
  1. 1Department of Psychiatry, Dartmouth College Geisel School of Medicine, Hanover, New Hampshire, USA
  2. 2Dartmouth Centers for Health and Aging, Lebanon, New Hampshire, USA
  3. 3Dartmouth-Hitchcock Medical Center, Section of General Internal Medicine, Lebanon, New Hampshire, USA
  4. 4The Dartmouth Institute for Health Policy & Clinical Research, Lebanon, New Hampshire, USA
  5. 5University of Michigan School of Social Work, Ann Arbor, Michigan, USA
  1. Correspondence to Dr Matthew C Lohman, Department of Psychiatry, Geisel School of Medicine at Dartmouth, Lebanon, NH 03766, USA; matt.lohman{at}gmail.com

Abstract

Background Preventing 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.

Methods Data 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.

Results Participants 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.

Conclusion The 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.

  • falls
  • geriatrics
  • screening
  • measurement
  • injuries

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Footnotes

  • Contributors MCL led the study design, conceptualisation, analysis and interpretation of results. RSC assisted in study design, conceptualisation and interpretation of results. PRD assisted in analysis and interpretation of results. EN, MLB and JAB assisted in study design, conceptualisation and interpretation of results. MCL drafted the manuscript and all authors contributed to draft revisions and approval of the final manuscript.

  • Funding This work was supported by a grant from the National Institute of Mental Health at the National Institutes of Health (T32 MH073553). Dr Batsis’ research reported in this publication was supported in part by the National Institute on Aging at the National Institutes of Health (K23AG051681). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. This work was also supported by the Dartmouth Health Promotion and Disease Prevention Research Center (Cooperative Agreement Number U48DP005018) from the Centers for Disease Control and Prevention. The findings and conclusions in this journal article are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention. The National Health and Aging Trends Study (NHATS) is sponsored by the National Institute on Aging (grant number NIA U01AG032947) through a cooperative agreement with the Johns Hopkins Bloomberg School of Public Health.

  • Competing interests None declared.

  • Ethics approval This study was deemed exempt by the Dartmouth College Institutional Review Board because it is a secondary data analysis. The NHATS study, which produced the data, was approved by by the Johns Hopkins Bloomberg School of Public Health Institutional Review Board.

  • Provenance and peer review Not commissioned; externally peer reviewed.

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