Original article
A risk model for the prediction of recurrent falls in community-dwelling elderly: A prospective cohort study

https://doi.org/10.1016/S0895-4356(02)00502-4Get rights and content

Abstract

The object of this article was to determine the predictive value of risk factors for recurrent falls and the construction of a fall risk model as a contribution to a mobility assessment for the identification of community-dwelling elderly at risk for recurrent falling in general practice. The design was a prospective cohort study (n = 311). There were four primary health care centers. A sample stratified on previous falls, age, and gender of community-dwelling elderly persons aged 70 years or over (n = 311) was taken from the respondents to a mail questionnaire (n = 1660). They were visited at home to assess physical and mental health, balance and gait, mobility and strength. A 36-week follow-up with telephone calls every 6 weeks was conducted. Falls and fall injuries were measured. During follow-up 197 falls were reported by 33% of the participants: one fall by 17% and two or more falls by 16%. Injury due to a fall was reported by 45% of the fallers: 2% hip fractures, 4% other fractures, and 39% minor injuries. A fall risk model for the prediction of recurrent falls with an area under the curve (AUC) of 0.79, based on logistic regression analysis, showed that the main determinants for recurrent falls were: an abnormal postural sway (OR 3.9; 95% Cl 1.3–12.1), two or more falls in the previous year (OR 3.1; 95% Cl 1.5–6.7), low scores for hand grip strength (OR 3.1; 95% Cl 1.5–6.6), and a depressive state of mind (OR 2.2; 95% CI 1.1–4.5). To facilitate the use of the model for clinical practice, the model was converted to a “desk model” with three risk categories: low risk (0–1 predictor), moderate risk (two predictors), and high risk (⩾3 predictors). A fall risk model converted to a “desk model,” consisting of the predictors postural sway, fall history, hand dynamometry, and depression, provides added value in the identification of community-dwelling elderly at risk for recurrent falling and facilitates the prediction of recurrent falls.

Introduction

Falls in the elderly represent a major problem in general practice, because of their high incidence, the involvement of many risk factors, and the considerable postfall morbidity and mortality 1, 2, 3, 4 . In community-dwelling elderly of 65 years or over lifetime cumulative incidence of falls ranges between 25 and 40% [5]. Major injury caused by falls accounts for about 10% of all falls, of which 1% concern hip fractures and 5% other fractures 1, 6. By far, most hip fractures are caused by falls 1, 4. Hip fractures have important consequences such as a high mortality in the first 3 months, a decline in the level of functioning, a threat to independence and the need for cost-consuming clinical care and rehabilitation facilities [6]. Psychosocial consequences of falls are fear of falling and social isolation, both also caused by mobility impairment [7]. Falls in the elderly are multifactorial events: intrinsic (patient-related), extrinsic (environment-related) and behavioral (activity-related) risk factors contribute to risk 1, 4. Particularly in recurrent falls, intrinsic risk factors have been reported to play a dominant role and extrinsic risk factors mainly an additional role 1, 2, 3, 4, 5. The main intrinsic risk factors for recurrent falling appear to be mobility problems 1, 2, 3, 4, 5.

Because of the high incidence and important consequences of falls, and the evidence that many recurrent falls are preventable, efforts to develop a strategy to prevent recurrent falls in primary care settings should be made [8]. In the past decade several randomized controlled studies have shown that multidimensional assessments and interventions in reducing falls and fall-related injury are effective 9, 10, 11, 12, 13, 14. From community surveys there is a consistent pattern showing that mobility risk factors have a great influence on falls, of which many are preventable 1, 2, 3, 4. Therefore, the focus on preventive efforts in primary care has to be directed on the improvement of mobilty. For the identification of elderly at risk for recurrent falls, a valid and feasible fall and mobility assessment protocol in primary health care is needed [15]. Several tests for the assessment of mobility problems have been recommended by many authors, but generally lack an evidence base and/or a sufficient feasibility in general practice 16, 17. Other authors have made efforts to construct a fall risk model to facilitate the risk assessment of falls in community-dwelling elderly, but these risk models are not easy to apply in clinical practice 18, 19.

Therefore, we set up a prospective study to answer the following questions:

  • - What is the predictive value of risk factors for recurrent falls in a community-based population?

Section snippets

Study population

Participants were randomly recruited from the respondents of a mail questionnaire in a prior retrospective study on the incidence of, risk factors for and consequences of falls sent to 2,744 of the 2,946 elderly persons aged 70 years or over, registered in four primary health care practices [20]. Subjects with wheelchair dependency (n = 18), serious cognitive impairment (n = 72), illiteracy (n = 3), severe somatic or psychiatric disease (n = 52), who were admitted into a nursing clinic or

Subjects

The baseline procedure was completed by 302 and the follow-up by 287 participants: 115 men (40%) and 172 women (60%) with a mean age of 77.2 (SD 4.9) and 78.5 (SD 5.2) years, respectively. About 37% were 80 years or over and 50% widowed or single.

Registered reasons for loss during baseline period and follow-up were: died (10), refused further participation for personal reasons (3), physically unable (3), cognitively unable (1), admitted into a hospital or nursing clinic (2), moved to another

Main results

This prospective study yielded a survey of risk factors for recurrent falls and a risk model for the prediction of recurrent falls, consisting of variables easy to assess in general practice. According to the converted scores in the the risk model, based on the regression coefficients, it appears that an abnormal postural sway, a history of two or more falls in the previous year, poor scores for handgrip dynamometry, and depression are the best predictors. The range of the scores of the model

Acknowledgements

This study was funded by a grant from Zorg Onderzoek Nederland (ZON) (Care Research in the Netherlands). Grant number: 28-2365.

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