We have located links that may give you full text access.
Clusters of functional domains to identify older persons at risk of disability.
AIM: To date, there is no consensus on which set of variables should be used to identify older persons at risk of disability in activities of daily living. The present study aimed to: (i) evaluate how different deficits cluster in a population of community-dwelling older persons; and (ii) investigate whether the discriminative capacity of physical performance measures towards the development of disability might be improved by adding psychological, social and environmental indicators.
METHODS: Data are from 709 non-disabled older persons participating in the "Invecchiare in Chianti" study. We carried out a cluster analysis of 12 deficits in multiple functional domains, selected from the available frailty assessment instruments. Then, participants were assigned to a group, based on the obtained clusters of variables. For each group, we measured the prognostic capacity and the predictive ability for 6-year disability.
RESULTS: The analysis showed a "physical" cluster (including weight loss, reduced grip strength/gait speed/physical activity, impaired balance, environmental barriers) and a "psychosocial" cluster (e.g. living alone, depression, low income). Thus, participants were classified into four groups according to the presence of a physical and/or psychosocial cluster. Compared with the "fit" group, the relative risks of becoming disabled in the "physical," "psychosocial" and "mixed" deficit groups were 2.23 (95% CI 0.71-7.00), 1.52 (95% CI 0.62-3.75) and 6.37 (95% CI 2.83-14.33), respectively. The positive and negative predictive values for the "physical," "psychosocial" and "mixed" deficit groups were, respectively, 9% and 87%, 6% and 83%, and 27% and 94%.
CONCLUSIONS: As expected, physical and psychosocial deficits cluster predominantly into different groups. Even when both are considered simultaneously, the ability to predict incident disability is still insufficient. Geriatr Gerontol Int 2018; 18: 685-691.
METHODS: Data are from 709 non-disabled older persons participating in the "Invecchiare in Chianti" study. We carried out a cluster analysis of 12 deficits in multiple functional domains, selected from the available frailty assessment instruments. Then, participants were assigned to a group, based on the obtained clusters of variables. For each group, we measured the prognostic capacity and the predictive ability for 6-year disability.
RESULTS: The analysis showed a "physical" cluster (including weight loss, reduced grip strength/gait speed/physical activity, impaired balance, environmental barriers) and a "psychosocial" cluster (e.g. living alone, depression, low income). Thus, participants were classified into four groups according to the presence of a physical and/or psychosocial cluster. Compared with the "fit" group, the relative risks of becoming disabled in the "physical," "psychosocial" and "mixed" deficit groups were 2.23 (95% CI 0.71-7.00), 1.52 (95% CI 0.62-3.75) and 6.37 (95% CI 2.83-14.33), respectively. The positive and negative predictive values for the "physical," "psychosocial" and "mixed" deficit groups were, respectively, 9% and 87%, 6% and 83%, and 27% and 94%.
CONCLUSIONS: As expected, physical and psychosocial deficits cluster predominantly into different groups. Even when both are considered simultaneously, the ability to predict incident disability is still insufficient. Geriatr Gerontol Int 2018; 18: 685-691.
Full text links
Related Resources
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app
All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.
By using this service, you agree to our terms of use and privacy policy.
Your Privacy Choices
You can now claim free CME credits for this literature searchClaim now
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app