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Loprinzi PD, Frith E. Association Between Perceived Physical Activity and Cognitive Function in Older Adults. Psychol Rep 2018; 122:108-116. [PMID: 29307247 DOI: 10.1177/0033294117750632] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
There is irrefutable evidence that regular participation in physical activity is favorably associated with numerous positive health outcomes, including cognitive function. Emerging work suggests that perceived physical activity, independent of actual physical activity behavior, is inversely associated with mortality risk. In this study, we evaluate whether perceived physical activity, independent of actual physical activity, is associated with cognitive function, a robust indicator of mortality risk. Data from the cross-sectional 1999-2002 National Health and Nutrition Examination Survey were employed ( N = 2352; 60+ years of age). Actual physical activity was assessed via a validated survey. Perceived physical activity was assessed using the following question: "Compared with others of the same age, would you say that you are: more active, less active, or about the same?" Cognitive function was assessed from the Digit Symbol Substitution Test. When examined in separate models, both actual and perceived physical activity were positively and statistically significantly associated with cognitive function. However, when considered in the same model, actual physical activity was no longer statistically significantly associated with cognitive function, but perceived physical activity was. Perceived physical activity, independent of actual physical activity, is independently associated with cognitive function. If these findings are replicated, future work should consider evaluating perceived physical activity when examining the effects of actual physical activity behavior on cognitive function.
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Affiliation(s)
- Paul D Loprinzi
- Exercise Psychology Laboratory, Physical Activity Epidemiology Laboratory, School of Applied Sciences, Department of Health, Exercise Science and Recreation Management, The University of Mississippi, Oxford, MS, USA
| | - Emily Frith
- Exercise Psychology Laboratory, Physical Activity Epidemiology Laboratory, School of Applied Sciences, Department of Health, Exercise Science and Recreation Management, The University of Mississippi, Oxford, MS, USA
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Chen Y, Wang W, Zhao X, Sha M, Liu Y, Zhang X, Ma J, Ni H, Ming D. Age-Related Decline in the Variation of Dynamic Functional Connectivity: A Resting State Analysis. Front Aging Neurosci 2017; 9:203. [PMID: 28713261 PMCID: PMC5491557 DOI: 10.3389/fnagi.2017.00203] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2016] [Accepted: 06/06/2017] [Indexed: 11/23/2022] Open
Abstract
Normal aging is typically characterized by abnormal resting-state functional connectivity (FC), including decreasing connectivity within networks and increasing connectivity between networks, under the assumption that the FC over the scan time was stationary. In fact, the resting-state FC has been shown in recent years to vary over time even within minutes, thus showing the great potential of intrinsic interactions and organization of the brain. In this article, we assumed that the dynamic FC consisted of an intrinsic dynamic balance in the resting brain and was altered with increasing age. Two groups of individuals (N = 36, ages 20–25 for the young group; N = 32, ages 60–85 for the senior group) were recruited from the public data of the Nathan Kline Institute. Phase randomization was first used to examine the reliability of the dynamic FC. Next, the variation in the dynamic FC and the energy ratio of the dynamic FC fluctuations within a higher frequency band were calculated and further checked for differences between groups by non-parametric permutation tests. The results robustly showed modularization of the dynamic FC variation, which declined with aging; moreover, the FC variation of the inter-network connections, which mainly consisted of the frontal-parietal network-associated and occipital-associated connections, decreased. In addition, a higher energy ratio in the higher FC fluctuation frequency band was observed in the senior group, which indicated the frequency interactions in the FC fluctuations. These results highly supported the basis of abnormality and compensation in the aging brain and might provide new insights into both aging and relevant compensatory mechanisms.
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Affiliation(s)
- Yuanyuan Chen
- College of Microelectronics, Tianjin UniversityTianjin, China.,Tianjin International Joint Research Center for Neural Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin UniversityTianjin, China
| | - Weiwei Wang
- Tianjin International Joint Research Center for Neural Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin UniversityTianjin, China.,Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin UniversityTianjin, China
| | - Xin Zhao
- Tianjin International Joint Research Center for Neural Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin UniversityTianjin, China.,Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin UniversityTianjin, China
| | - Miao Sha
- Tianjin International Joint Research Center for Neural Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin UniversityTianjin, China.,Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin UniversityTianjin, China
| | - Ya'nan Liu
- Tianjin International Joint Research Center for Neural Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin UniversityTianjin, China.,Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin UniversityTianjin, China
| | - Xiong Zhang
- Tianjin International Joint Research Center for Neural Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin UniversityTianjin, China.,Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin UniversityTianjin, China
| | - Jianguo Ma
- College of Microelectronics, Tianjin UniversityTianjin, China
| | - Hongyan Ni
- Department of Radiology, Tianjin First Center HospitalTianjin, China
| | - Dong Ming
- Tianjin International Joint Research Center for Neural Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin UniversityTianjin, China.,Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin UniversityTianjin, China
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