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Validation of an a priori, index model of successful aging in a population-based cohort study: the successful aging index

Published online by Cambridge University Press:  20 May 2015

Theodore D. Cosco*
Affiliation:
Cambridge Institute of Public Health, Department of Public Health and Primary Care, University of Cambridge, Forvie Site, Robinson Way, Cambridge, CB20SR, UK
Blossom C. M. Stephan
Affiliation:
Institute of Health and Society, Newcastle University, The Baddiley-Clark Building, Richardson Road, Newcastle upon Tyne, NE24AX, UK
Carol Brayne
Affiliation:
Cambridge Institute of Public Health, Department of Public Health and Primary Care, University of Cambridge, Forvie Site, Robinson Way, Cambridge, CB20SR, UK
*
Correspondence should be addressed to: Theodore D. Cosco, Forvie Site, Robinson Way, Cambridge, CB20SR, UK. Phone: 07414983921. Email: tdc33@medschl.cam.ac.uk.

Abstract

Background:

Many definitions of successful aging (SA) exist in the absence of an established consensus definition. There are few examples of a priori application of SA models in real world contexts using external validation procedures. The current study aims to establish the predictive validity of an a priori, continuous model of SA with respect to service utilization.

Methods:

Individuals (n = 740; 64.2% female) aged 65 years and over (mean 75.9; SD 6.2), randomly selected from general practitioner registries in five sites across the United Kingdom included in the second and third combined screen and assessment waves of the Medical Research Council Cognitive Function and Aging Study (MRC CFAS; a longitudinal population-based cohort study) comprised the baseline and two-year follow-up in the current study. A Successful Aging Index (SAI) was created using items identified by systematic reviews of operational definitions and lay perspectives of SA, capturing physiological and psychosocial components. Demographic data and SAI components were collected at baseline. Outcome measures, i.e. health service use, informal care use, and functional service, were captured at two years follow-up.

Results:

Logistic regression revealed significant relationships between the SAI and six of eight service use outcomes in models adjusted for age, sex, education, and socio-economic status. Analysis of the area under the receiver operating characteristic (ROC) curve demonstrated sufficient predictive capabilities for all models, (range 0.65–0.86).

Conclusions:

The SAI demonstrated a strong association, and predictive accuracy, with respect to service use, providing preliminary support for the practical utility and usefulness of this measure.

Type
Research Article
Copyright
Copyright © International Psychogeriatric Association 2015 

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