Email updates

Keep up to date with the latest news and content from BMC Geriatrics and BioMed Central.

Open Access Research article

Operationalizing frailty among older residents of assisted living facilities

Elizabeth A Freiheit1, David B Hogan12, Laurel A Strain3, Heidi N Schmaltz2, Scott B Patten1, Misha Eliasziw1 and Colleen J Maxwell12*

Author Affiliations

1 Department of Community Health Sciences, University of Calgary, 3rdFloor TRW, 3280 Hospital Drive NW, Calgary, Alberta, Canada

2 Department of Medicine, University of Calgary, HSC 3330 Hospital Drive NW, Calgary, Alberta, Canada

3 Department of Sociology, University of Alberta, 5-21 HM Tory Building, Edmonton, Alberta, Canada

For all author emails, please log on.

BMC Geriatrics 2011, 11:23  doi:10.1186/1471-2318-11-23

Published: 13 May 2011

Abstract

Background

Frailty in later life is viewed as a state of heightened vulnerability to poor outcomes. The utility of frailty as a measure of vulnerability in the assisted living (AL) population remains unexplored. We examined the feasibility and predictive accuracy of two different interpretations of the Cardiovascular Health Study (CHS) frailty criteria in a population-based sample of AL residents.

Methods

CHS frailty criteria were operationalized using two different approaches in 928 AL residents from the Alberta Continuing Care Epidemiological Studies (ACCES). Risks of one-year mortality and hospitalization were estimated for those categorized as frail or pre-frail (compared with non-frail). The prognostic significance of individual criteria was explored, and the area under the ROC curve (AUC) was calculated for select models to assess the utility of frailty in predicting one-year outcomes.

Results

Regarding feasibility, complete CHS criteria could not be assessed for 40% of the initial 1,067 residents. Consideration of supplementary items for select criteria reduced this to 12%. Using absolute (CHS-specified) cut-points, 48% of residents were categorized as frail and were at greater risk for death (adjusted risk ratio [RR] 1.75, 95% CI 1.08-2.83) and hospitalization (adjusted RR 1.54, 95% CI 1.20-1.96). Pre-frail residents defined by absolute cut-points (48.6%) showed no increased risk for mortality or hospitalization compared with non-frail residents. Using relative cut-points (derived from AL sample), 19% were defined as frail and 55% as pre-frail and the associated risks for mortality and hospitalization varied by sex. Frail (but not pre-frail) women were more likely to die (RR 1.58 95% CI 1.02-2.44) and be hospitalized (RR 1.53 95% CI 1.25-1.87). Frail and pre-frail men showed an increased mortality risk (RR 3.21 95% CI 1.71-6.00 and RR 2.61 95% CI 1.40-4.85, respectively) while only pre-frail men had an increased risk of hospitalization (RR 1.58 95% CI 1.15-2.17). Although incorporating either frailty measure improved the performance of predictive models, the best AUCs were 0.702 for mortality and 0.633 for hospitalization.

Conclusions

Application of the CHS criteria for frailty was problematic and only marginally improved the prediction of select adverse outcomes in AL residents. Development and validation of alternative approaches for detecting frailty in this population, including consideration of female/male differences, is warranted.