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Updated: Jul 22, 2025

Assessment of Age-related Changes in Cognitive Functions Using EmoCogMeter, a Novel Tablet-computer Based Approach
Published on: February 14, 2014
Discordant Biological and Chronological Age: Implications for Cognitive Decline and Frailty
C Elizabeth Shaaban1, Caterina Rosano1, Xiaonan Zhu1
1Department of Epidemiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
Background:
Older adults with discordant biological and chronological ages (BA and CA) may vary in cognitive and physical function from those with concordant BA and CA.
Methods:
To make our approach clinically accessible, we created easy-to-interpret participant groups in the Health, Aging, and Body Composition Study (N = 2 458, 52% female participants, 65% White participants, age: 73.5 ± 2.8) based on medians of CA, and a previously validated BA index comprised of readily available clinical tests. Joint models estimated associations of BA-CA group with cognition (Modified Mini-Mental State Examination [3MS] and Digit Symbol Substitution Test [DSST]) and frailty over 10 years.
Results:
The sample included the following: 32%, Young group (BA and CA < median); 21%, Prematurely Aging group (BA ≥ median, CA < median), 27%, Old group (BA and CA ≥ median), and 20%, Resilient group (BA < median, CA ≥ median). In education-adjusted models of cognition, among those with CA < median, the Prematurely Aging group performed worse than the Young at baseline (3MS and DSST p < .0001), but among those with CA ≥ median, the Resilient group did not outperform the Old group (3MS p = .31; DSST p = .25). For frailty, the Prematurely Aging group performed worse than the Young group at baseline (p = .0001), and the Resilient group outperformed the Old group (p = .003). For all outcomes, groups did not differ on change over time based on the same pairwise comparisons (p ≥ .40).
Conclusions:
Discordant BA and CA identify groups who have greater cognitive and physical functional decline or are more protected than their CA would suggest. This information can be used for risk stratification.
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