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dc.contributor.advisorAlexander, Gene E.en_US
dc.contributor.authorHanson, Krista D.
dc.creatorHanson, Krista D.en_US
dc.date.accessioned2012-05-08T21:04:04Z
dc.date.available2012-05-08T21:04:04Z
dc.date.issued2012
dc.identifier.urihttp://hdl.handle.net/10150/222574
dc.description.abstractLevel of physical fitness may be an important factor influencing the effects of brain aging and age-related cognitive decline. Multiple measures of aerobic fitness were used in a cohort of healthy older adults 50-89 years of age to identify how individual differences in fitness relate to brain aging and age-associated cognitive decline. Healthy adults (n=123; 65 F and 58 M; mean ± sd age = 67.9 ± 10.0; Mini-Mental State Exam = 29.1 ± 1.2) were screened to exclude neurological, psychiatric, and medical illnesses that could affect cognitive function, including hypertension. The Scaled Subprofile Model (SSM) with voxel-based morphometry and Statistical Parametric Mapping version 8 (VBM; SPM8 Dartel) were performed on T1-weighted 3T volumetric magnetic resonance imaging (MRI) scans to identify a gray matter pattern associated with brain aging. Performance on aerobic fitness measures, assessed during a graded exercise treadmill test (GXT), was evaluated in relation to the age-associated MRI gray matter network pattern and indices of neuropsychological function. Multivariate SSM VBM network analysis identified a linear combination of patterns that predicted age (R² = 0.48, p = 8.71e-19). This combined pattern was characterized by reductions in bilateral lateral and medial frontal, parietal, lateral temporal, and cerebellar regions with relative preservations in thalamic, occipital, and medial temporal regions including the hippocampus. Higher expression of the age-related network pattern was associated with poorer performance on multiple fitness indices. The best combination of fitness measures in predicting brain aging included overall treadmill exercise time, ventilatory efficiency, and the difference between basal and maximal respiratory rate (p = 6.67e-7). A higher combined fitness index score related to brain aging was associated with better performance on measures of memory, executive function, and processing speed in this cohort (6.08e-9≤ p≤ 0.05). Those individuals with higher levels of aerobic fitness had lower expression of the gray matter brain aging pattern and better performance on measures of memory, executive function, and processing speed. Identifying those fitness indices that are the best predictors of brain aging and cognitive performance may aid efforts in developing and evaluating exercise based interventions for age-related cognitive decline.
dc.language.isoenen_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.subjectfitnessen_US
dc.subjectgray matteren_US
dc.subjectMRIen_US
dc.subjectmultivariateen_US
dc.subjectPsychologyen_US
dc.subjectagingen_US
dc.subjectcognitionen_US
dc.titleRelation of Physical Fitness to Brain Aging and Cognition in Older Adultsen_US
dc.typetexten_US
dc.typeElectronic Dissertationen_US
thesis.degree.grantorUniversity of Arizonaen_US
thesis.degree.leveldoctoralen_US
dc.contributor.committeememberLee, Ryanen_US
dc.contributor.committeememberGlisky, Elizbaeth L.en_US
dc.contributor.committeememberKaszniak, Alfred W.en_US
dc.contributor.committeememberAlexander, Gene E.en_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.disciplinePsychologyen_US
thesis.degree.namePh.D.en_US
refterms.dateFOA2018-07-18T00:55:19Z
html.description.abstractLevel of physical fitness may be an important factor influencing the effects of brain aging and age-related cognitive decline. Multiple measures of aerobic fitness were used in a cohort of healthy older adults 50-89 years of age to identify how individual differences in fitness relate to brain aging and age-associated cognitive decline. Healthy adults (n=123; 65 F and 58 M; mean ± sd age = 67.9 ± 10.0; Mini-Mental State Exam = 29.1 ± 1.2) were screened to exclude neurological, psychiatric, and medical illnesses that could affect cognitive function, including hypertension. The Scaled Subprofile Model (SSM) with voxel-based morphometry and Statistical Parametric Mapping version 8 (VBM; SPM8 Dartel) were performed on T1-weighted 3T volumetric magnetic resonance imaging (MRI) scans to identify a gray matter pattern associated with brain aging. Performance on aerobic fitness measures, assessed during a graded exercise treadmill test (GXT), was evaluated in relation to the age-associated MRI gray matter network pattern and indices of neuropsychological function. Multivariate SSM VBM network analysis identified a linear combination of patterns that predicted age (R² = 0.48, p = 8.71e-19). This combined pattern was characterized by reductions in bilateral lateral and medial frontal, parietal, lateral temporal, and cerebellar regions with relative preservations in thalamic, occipital, and medial temporal regions including the hippocampus. Higher expression of the age-related network pattern was associated with poorer performance on multiple fitness indices. The best combination of fitness measures in predicting brain aging included overall treadmill exercise time, ventilatory efficiency, and the difference between basal and maximal respiratory rate (p = 6.67e-7). A higher combined fitness index score related to brain aging was associated with better performance on measures of memory, executive function, and processing speed in this cohort (6.08e-9≤ p≤ 0.05). Those individuals with higher levels of aerobic fitness had lower expression of the gray matter brain aging pattern and better performance on measures of memory, executive function, and processing speed. Identifying those fitness indices that are the best predictors of brain aging and cognitive performance may aid efforts in developing and evaluating exercise based interventions for age-related cognitive decline.


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