Background and Purpose. The objective of this retrospective case-control study was to develop a model for predicting the likelihood of falls among community-dwelling older adults. Subjects. Forty-four community-dwelling adults (≥65 years of age) with and without a history of falls participated. Methods. Subjects completed a health status questionnaire and underwent a clinical evaluation of balance and mobility function. Variables that differed between fallers and nonfallers were identified, using t tests and cross tabulation with chi-square tests. A forward stepwise regression analysis was carried out to identify a combination of variables that effectively predicted fall status. Results. Five variables were found to be associated with fall history. These variables were analyzed using logistic regression. The final model combined the score on the Berg Balance Scale with a self-reported history of imbalance to predict fall risk. Sensitivity was 91%, and specificity was 82%. Conclusion and Discussion. A simple predictive model based on two risk factors can be used by physical therapists to quantify fall risk in community-dwelling older adults. Identification of patients with a high fall risk can lead to an appropriate referral into a fall prevention program. In addition, fall risk can be used to calculate change resulting from intervention.

Predicting the Probability for Falls in Community-Dwelling Older Adults

Objectives To identify the characteristics of elderly persons who develop a fear of falling after experiencing a fall and to investigate the association of this fear with changes in health status over time. Design A prospective study of falls over a 2-year period (1991-92). Falls were ascertained using bimonthly postcards plus telephone interview with a standardized (World Health Organisation) questionnaire for circumstances, fear of falling and consequences of each reported fall. Each participant underwent a physical exam and subjective health assessment each year form 1990 to 1993. Setting New-Mexico Aging Process Study, USA. Subjects 487 elderly subjects (> 60 years) living independently in the community. Main outcome measures Fear of falling after experiencing a fall. Results 70 (32%) of 219 subjects who experienced a fall during the 2 year study period reported a fear of falling. Women were more likely than men to report fear of falling (74% vs 26%). Fallers who were afraid of falling again had significantly ore balance (31.9% vs 12.8%) and gait disorders (31.9% vs 7.4%) at entry in the study in 1990. Among sex, age, mental status, balance and gait abnormalities, economic resource and physical health, logistic regression analysis show gait abnormalities and poor self-perception of physical health, cognitive status and economic resources to be significantly associated with fear of falling. Subjects who reported a fear of falling experienced a greater increase in balance (P = 0.08), gait (P Conclusion The study indicated that about one-third of elderly people develop a fear of falling after an incident fall and this issue should be specifically addressed in any rehabilitation programme.

Fear of falling and restriction of mobility in elderly fallers

Background. The aim of this study was to assess the impact of fear of falling on the health of older people. Methods. A total of 528 subjects (mean age 77 years) were recruited from two hospitals in Sydney, Australia, and followed for approximately 12 months. Eighty-five subjects died during follow-up, and 31 were admitted to an aged care institution. Tinetti’s Falls Efficacy Scale (FES) was successfully administered to 418 subjects as part of the baseline assessment. Among those with baseline FES scores, ability to perform 10 activities of daily living (ADLs) was assessed at baseline and follow-up in 307 subjects, and SF-36 scores were assessed at baseline and follow-up in 90 subjects recruited during the latter part of the study. Falls during follow-up were identified using a monthly falls calendar. Results. Compared with those with a high fall-related self-efficacy (FES score 5 100), those with a low fall-related self-efficacy (FES score # 75) had an increased risk of falling (adjusted relative risk 2.09, 95% confidence interval [CI] 1.31‐3.33). Those with poorer fall-related self-efficacy had greater declines in ability to perform ADLs ( p , .001): the total ADL score decreased by 0.69 activities among persons with low FES scores ( # 75) but decreased by only 0.04 activities among persons with FES scores of 100. Decline in ADLs was not explained by the higher frequency of falls among persons with low FES scores. SF-36 scores (particularly scores on the Physical Function and Bodily Pain subscales) tended to decline more among persons with poor fall-related self-efficacy. Nonfallers who said they were afraid of falling had an increased risk of admission to an aged care institution. Conclusions. Fear of falling has serious consequences for older people. Interventions that successfully reduce fear of falling and improve fall-related self-efficacy are likely to have major health benefits.

/pdf/prospective-study-of-the-impact-of-fear-of-falling-on-1coxl04ko3.pdf

Prospective Study of the Impact of Fear of Falling on Activities of Daily Living, SF-36 Scores, and Nursing Home Admission

Misclassification of seat belt use In a recent article, Robertson commented on our study of seat belts and death in a crash. Robertson wrote: “What is not explained adequately by the theory [about misclassification of seat belt use] is the sudden gap in police reported use by the dead and survivors that appeared in the mid-1980s”. Robertson’s criticism seems misplaced, as we offered no theory to explain changes in the prevalence of belt use. We reported that among front seat occupant pairs in which one or both died, the prevalence of belt use decreased from 12% in 1975 to 4% in 1980, and then rose to 40% in 1998. Explaining these changes, however, was not the focus of our paper. Using matched cohort methods, we noted that the risk ratio for death, comparing belted with unbelted occupants, was 0.59 using data from 1975–83, and 0.39 using data from 1986–98. We examined theories that might explain why these risk ratio estimates changed over time. We presented evidence against the theory that seat belts have become truly more effective and against the theory that estimates changed because of changes in crash characteristics. The observed change in risk ratio estimates could be explained by either, or both, of two theories: (1) Differential misclassification. Seat belt misclassification is differential when the proportion misclassified is related to the outcome (death). Risk ratio estimates could move away from their true value and toward 0 if, over time, an increasing proportion of crash survivors were classified as belted, when they were not, or an increasing proportion of those who died were classified as unbelted, when they were: this possible mechanism is illustrated with hypothetical data in the top half of table 1. (For simplicity, the table ignores the matching used in our published analysis.) (2) Non-differential misclassification. Without regard to death or survival, some belt users could be classified as not belted, or some nonusers as belted, or both. Non-differential misclassification of a binary variable tends to bias risk ratio estimates toward 1. If nondifferential error decreased over time, more recent risk ratio estimates could be less subject to this bias; they could move away from 1 toward their true value. However, even if non-differential error was constant over time, more recent risk ratios might also tend to be less biased, because of the influence of changing seat belt prevalence: bottom half of table 1. For both differential and non-differential misclassification, the size and direction of any change over time in risk ratio estimates will be related to the size and direction of the errors and changes in the prevalence of seat belt use. The observed changes in risk ratio estimates alone cannot tell us which estimates are least subject to bias. One of us has reported that there is some degree of both differential and nondifferential misclassification of belt use; but the amount of error in recent data suitable for a matched-cohort analysis was so trivial, and biases toward 1 and toward 0 so balanced, that the misclassification did not appreciably influence the risk ratio estimate. Robertson interpreted these results as showing only that trained crash investigators were as prone to differential misclassification as police investigators. Whatever the correct interpretation, we and Robertson agree that additional measures of seat belt use would be useful. We hope that information from electronic crash recorders will be added to publicly available data, such as the Crashworthiness Data System (CDS). It might be feasible for the CDS to assess some crashes with a second investigator assigned to determine belt use only by vehicle inspection, without knowledge of occupant outcomes or the police report. To minimize costs, this additional investigation could be reserved for those crashes with front seat occupant pairs among whom at least one died. This would allow a matched cohort analysis to compare risk ratio estimates using three sources of belt information: (1) police reports; (2) the usual CDS investigation; and (3) an investigator who could not be biased by knowledge of the outcome.

Falls in older people: risk factors and strategies for prevention.

Objectives: To identify clinical characteristics of elderly inpatients that predict their chance of falling (phase 1) and to use these characteristics to derive a risk assessment tool and to evaluate its power in predicting falls (phases 2 and 3). Design: Phase 1: a prospective case-control study. Phases 2 and 3: prospective evaluations of the derived risk assessment tool in predicting falls in two cohorts. Setting: Elderly care units of St Thomas9s Hospital (phase 1 and 2) and Kent and Canterbury Hospital (phase 3). Subjects: Elderly hospital inpatients (aged 65 years): 116 cases and 116 controls in phase 1, 217 patients in phase 2, and 331 in phase 3. Main outcome measures: 21 separate clinical characteristics were assessed in phase 1, including the abbreviated mental test score, modified Barthel index, a transfer and mobility score obtained by combining the transfer and mobility sections of the Barthel index, and several nursing judgments. Results: In phase 1 five factors were independently associated with a higher risk of falls: fall as a presenting complaint (odds ratio 4.64 (95% confidence interval 2.59 to 8.33); a transfer and mobility score of 3 or 4 (2.10 (1.22 to 3.61)); and primary nurses9 judgment that a patient was agitated (20.9 (9.62 to 45.62)), needed frequent toileting (2.48 (1.08 to 5.70)), and was visually impaired (3.56 (1.26 to 10.05)). A risk assessment score (range 0-5) was derived by scoring one point for each of these five factors. In phases 2 and 3 a risk assessment score >2 was used to define high risk: the sensitivity and specificity of the score to predict falls during the following week was 93% and 88% respectively in phase 2 and 92% and 68% respectively in phase 3. Conclusion: This simple risk assessment tool predicted with clinically useful sensitivity and specificity a high percentage of falls among elderly hospital inpatients.

/pdf/development-and-evaluation-of-evidence-based-risk-assessment-4pvq7o0dvk.pdf

Development and evaluation of evidence based risk assessment tool (STRATIFY) to predict which elderly inpatients will fall: case-control and cohort studies

Foundations of a Policy for the Aged in the 1980s and Beyond

36 patients aged 65 and over who were admitted to hospital after suffering a fall were examined soon after admission and followed for 4 months. 10 patients developed a severe tendency to clutch and grab and were unable to walk unsupported; 9 of these died or were still in hospital 4 months later. 16 patients showed similar signs but were able to walk independently; 5 of these died or were still in hospital after 4 months. 10 patients had no features of the post-fall syndrome; only 1 of these died within 4 months, and one of the survivors remained in hospital. The syndrome may represent the end result of a positive feed-back relationship between disturbed balance and falls.

The post-fall syndrome. A study of 36 elderly patients.

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Foundations of a Policy for the Aged in the 1980s and Beyond

The post-fall syndrome. A study of 36 elderly patients.