Measuring successful aging: an exploratory factor analysis of the InCHIANTI Study into different health domains
Author(s) -
Sarah Mount,
Luigi Ferrucci,
Anke Wesselius,
Maurice P. Zeegers,
Annemie M.W.J. Schols
Publication year - 2019
Publication title -
aging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 90
ISSN - 1945-4589
DOI - 10.18632/aging.101957
Subject(s) - vitality , successful aging , exploratory factor analysis , socioeconomic status , gerontology , logistic regression , cognition , psychology , structural equation modeling , healthy aging , disease , clinical psychology , medicine , psychometrics , environmental health , psychiatry , computer science , philosophy , population , theology , pathology , machine learning
Advocating continued health into old age, so called successful aging, is a growing public health goal. However, the development of tools to measure aging is limited by the lack of appropriate outcome measures, and operational definitions of successful aging. Using exploratory factor analysis, we attempted to identify distinguishable health domains with representative variables of physical function, cognitive status, social interactions, psychological status, blood biomarkers, disease history, and socioeconomic status from the InCHIANTI study. We then used logistic and mixed effect regression models to determine whether the resulting domains predicted outcomes of successful aging over a nine-year follow-up. A four-domain health model was identified: neuro-sensory function, muscle function, cardio-metabolic function and adiposity. After adjustment for age and gender, all domains contributed to the prediction of walking speed (R 2 =0.73). Only the muscle function domain predicted dependency (R 2 =0.50). None of the domains were a strong, significant predictor of self-rated health (R 2 =0.18) and emotional vitality (R 2 =0.23). Cross-sectional findings were essentially replicated in the longitudinal analysis extended to nine-year follow-up. Our results suggest a multi-domain health model can predict objective but not subjective measures of successful aging.
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