Cognitive and physical age gaps in relation to mild cognitive impairment and behavioral phenotypes
We can study how fast our biological aging clocks tick by calculating the difference (i.e., age gaps) between machine learning estimations of biological age and chronological age. While this approach has been increasingly used to study various aspects of aging, few had applied this approach to study...
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sg-ntu-dr.10356-1709672023-10-15T15:30:31Z Cognitive and physical age gaps in relation to mild cognitive impairment and behavioral phenotypes Yu Junhong Ng, Ted Kheng Siang Mahendran, Rathi School of Social Sciences Social sciences::Psychology Cognitive Aging Physical Fitness We can study how fast our biological aging clocks tick by calculating the difference (i.e., age gaps) between machine learning estimations of biological age and chronological age. While this approach has been increasingly used to study various aspects of aging, few had applied this approach to study cognitive and physical age gaps; not much is known about the behavioral and neurocognitive factors associated with these age gaps. In the present study, we examined these age gaps in relation to behavioral phenotypes and mild cognitive impairment (MCI) among community-dwelling older adults. Participants (N = 822, Agemean = 67.6) were partitioned into equally-sized training and testing samples. Cognitive and physical age-prediction models were fitted using nine cognitive and eight physical fitness test scores, respectively, within the training samples, and subsequently used to estimate cognitive and physical age gaps for each subject in the testing sample. These age gaps were then compared among those with and without MCI and correlated with 17 behavioral phenotypes in the domains of lifestyle, well-being, and attitudes. Across 5000 random train-test split iterations, we showed that older cognitive age gaps were significantly associated with MCI (versus cognitively normal) and worse outcomes across several well-being and attitude-related measures. Both age gaps were also significantly correlated with each other. These results suggest accelerated cognitive and physical aging were linked to worse well-being and more negative attitudes about the self and others and reinforce the link between cognitive and physical aging. Importantly, we have also validated the use of cognitive age gaps in the diagnosis of MCI. Submitted/Accepted version This work was supported by Research Donations from Kwan Im Thong Hood Cho Temple and Lee Kim Tah Holdings Pte Ltd., under the Mind Science Centre, Department of Psychological Medicine, National University of Singapore. 2023-10-09T08:08:23Z 2023-10-09T08:08:23Z 2023 Journal Article Yu Junhong, Ng, T. K. S. & Mahendran, R. (2023). Cognitive and physical age gaps in relation to mild cognitive impairment and behavioral phenotypes. GeroScience. https://dx.doi.org/10.1007/s11357-023-00864-9 2509-2715 https://hdl.handle.net/10356/170967 10.1007/s11357-023-00864-9 37428365 2-s2.0-85164484721 en GeroScience © 2023 The Author(s), under exclusive licence to American Aging Association. All rights reserved. This article may be downloaded for personal use only. Any other use requires prior permission of the copyright holder. The Version of Record is available online at http://doi.org/10.1007/s11357-023-00864-9. application/pdf |
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Social sciences::Psychology Cognitive Aging Physical Fitness Yu Junhong Ng, Ted Kheng Siang Mahendran, Rathi Cognitive and physical age gaps in relation to mild cognitive impairment and behavioral phenotypes |
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We can study how fast our biological aging clocks tick by calculating the difference (i.e., age gaps) between machine learning estimations of biological age and chronological age. While this approach has been increasingly used to study various aspects of aging, few had applied this approach to study cognitive and physical age gaps; not much is known about the behavioral and neurocognitive factors associated with these age gaps. In the present study, we examined these age gaps in relation to behavioral phenotypes and mild cognitive impairment (MCI) among community-dwelling older adults. Participants (N = 822, Agemean = 67.6) were partitioned into equally-sized training and testing samples. Cognitive and physical age-prediction models were fitted using nine cognitive and eight physical fitness test scores, respectively, within the training samples, and subsequently used to estimate cognitive and physical age gaps for each subject in the testing sample. These age gaps were then compared among those with and without MCI and correlated with 17 behavioral phenotypes in the domains of lifestyle, well-being, and attitudes. Across 5000 random train-test split iterations, we showed that older cognitive age gaps were significantly associated with MCI (versus cognitively normal) and worse outcomes across several well-being and attitude-related measures. Both age gaps were also significantly correlated with each other. These results suggest accelerated cognitive and physical aging were linked to worse well-being and more negative attitudes about the self and others and reinforce the link between cognitive and physical aging. Importantly, we have also validated the use of cognitive age gaps in the diagnosis of MCI. |
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School of Social Sciences |
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School of Social Sciences Yu Junhong Ng, Ted Kheng Siang Mahendran, Rathi |
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Yu Junhong Ng, Ted Kheng Siang Mahendran, Rathi |
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Yu Junhong |
title |
Cognitive and physical age gaps in relation to mild cognitive impairment and behavioral phenotypes |
title_short |
Cognitive and physical age gaps in relation to mild cognitive impairment and behavioral phenotypes |
title_full |
Cognitive and physical age gaps in relation to mild cognitive impairment and behavioral phenotypes |
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Cognitive and physical age gaps in relation to mild cognitive impairment and behavioral phenotypes |
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Cognitive and physical age gaps in relation to mild cognitive impairment and behavioral phenotypes |
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cognitive and physical age gaps in relation to mild cognitive impairment and behavioral phenotypes |
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2023 |
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https://hdl.handle.net/10356/170967 |
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