PURPOSE: This study explored the risk factors, cut-off points, sensitivity, specificity, positive predictive values, and negative predictive values of physical performance testing among community-dwelling frail elderly people in Taiwan. ORGANIZING CONSTRUCT: The empirical measurement of frailty is based on the following five indicators: weight loss, weakness, exhaustion, slow responses, and minimal physical activity. The frail phenotype is considered present if three or more of the indicators are observed. Meanwhile, a short battery of physical performance tests was conducted to assess the balance, mobility, and flexibility among elderly people. METHODS: A cross-sectional research design was executed. Participants were evaluated using a short battery of physical performance tests to assess their physical performance. Multivariate logistic regression and receiver operating characteristic (ROC) analyses were performed. FINDINGS: The logistic regression results showed that the factors significantly correlated to frailty included falls in the previous year, smoking, hypertension, and bone and joint disease. Physical performance test scores were analyzed using the ROC curves to discriminate frailty statuses. The analysis results showed that the areas under the ROC curves for the diagnostic accuracy of right-hand grip, left-hand grip, and the 8-foot up-and-go test reached 0.70, and the optimal cut-off points determined using Youden's index were 17.25 kg, 20.75 kg, and 8.13 s, respectively. CONCLUSIONS: The research findings suggest that physical performance variables can be used to effectively screen elderly people at risk for frailty in the community. CLINICAL RELEVANCE: The findings offer reference values for physical performance tests specific to community-dwelling frail elderly people. The information can enable health practitioners to achieve early identification of frailty among elderly people with anthropometric characteristics similar to those associated with people in Asian countries.
PURPOSE: This study explored the risk factors, cut-off points, sensitivity, specificity, positive predictive values, and negative predictive values of physical performance testing among community-dwelling frail elderly people in Taiwan. ORGANIZING CONSTRUCT: The empirical measurement of frailty is based on the following five indicators: weight loss, weakness, exhaustion, slow responses, and minimal physical activity. The frail phenotype is considered present if three or more of the indicators are observed. Meanwhile, a short battery of physical performance tests was conducted to assess the balance, mobility, and flexibility among elderly people. METHODS: A cross-sectional research design was executed. Participants were evaluated using a short battery of physical performance tests to assess their physical performance. Multivariate logistic regression and receiver operating characteristic (ROC) analyses were performed. FINDINGS: The logistic regression results showed that the factors significantly correlated to frailty included falls in the previous year, smoking, hypertension, and bone and joint disease. Physical performance test scores were analyzed using the ROC curves to discriminate frailty statuses. The analysis results showed that the areas under the ROC curves for the diagnostic accuracy of right-hand grip, left-hand grip, and the 8-foot up-and-go test reached 0.70, and the optimal cut-off points determined using Youden's index were 17.25 kg, 20.75 kg, and 8.13 s, respectively. CONCLUSIONS: The research findings suggest that physical performance variables can be used to effectively screen elderly people at risk for frailty in the community. CLINICAL RELEVANCE: The findings offer reference values for physical performance tests specific to community-dwelling frail elderly people. The information can enable health practitioners to achieve early identification of frailty among elderly people with anthropometric characteristics similar to those associated with people in Asian countries.
Authors: Jennifer L Sutton; Rebecca L Gould; Stephanie Daley; Mark C Coulson; Emma V Ward; Aine M Butler; Stephen P Nunn; Robert J Howard Journal: BMC Geriatr Date: 2016-02-29 Impact factor: 3.921
Authors: Xiaomeng Chen; Yi Liu; Valerie Thompson; Nadia M Chu; Elizabeth A King; Jeremy D Walston; Jon A Kobashigawa; Darshana M Dadhania; Dorry L Segev; Mara A McAdams-DeMarco Journal: BMC Geriatr Date: 2022-01-27 Impact factor: 3.921
Authors: David Navarrete-Villanueva; Alba Gómez-Cabello; Jorge Marín-Puyalto; Luis Alberto Moreno; Germán Vicente-Rodríguez; José Antonio Casajús Journal: Sports Med Date: 2021-01 Impact factor: 11.136