E-Thesis 420 views
Investigating the Measurement of Physical Activity and Associated Factors in Youth and Adults with Cystic Fibrosis / MAYARA BIANCHIM
Swansea University Author: MAYARA BIANCHIM
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DOI (Published version): 10.23889/SUthesis.58596
Abstract
Cystic Fibrosis (CF) is a multisystemic condition that affects almost every organ in the body, but especially the lungs. Regular physical activity (PA) can significantly slow disease progression and has become a crucial part of CF care. Previous research evaluating PA in CF has been hindered by the...
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Swansea
2021
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| Institution: | Swansea University |
| Degree level: | Doctoral |
| Degree name: | Ph.D |
| Supervisor: | Mackintosh, Kelly ; McNarry, Melitta |
| URI: | https://cronfa.swan.ac.uk/Record/cronfa58596 |
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| Abstract: |
Cystic Fibrosis (CF) is a multisystemic condition that affects almost every organ in the body, but especially the lungs. Regular physical activity (PA) can significantly slow disease progression and has become a crucial part of CF care. Previous research evaluating PA in CF has been hindered by the use of cut-points developed for healthy populations and the investigation of collinear movement behaviours as independent entities, both of which are likely to have confounded their findings and any subsequent inferences regarding associated health outcomes. Therefore, the overall aim of this thesis was to investigate the measurement and analysis of PA in those with CF. An initial systematic review provided recommendations for research calibrating accelerometry in paediatric clinical populations, highlighting that the pathophysiology of the condition must be accounted for and that the protocol should include a broad range of activities varying in intensity (Chapter 4). Subsequently, Chapter 5 developed and cross-validated raw acceleration CF-specific cut-points in youth which were then further assessed in Chapter 6, demonstrating that the CF-specific thresholds were associated with higher levels of moderate-to-vigorous physical activity (MVPA) and sedentary time (SED) and lower levels of light PA compared to generic cut-points. Furthermore, lung function was associated with light PA when using condition-specific thresholds. Further investigation of the relationship between PA and health in Chapter 7 found that reallocating time from sedentary to any other behaviour was beneficial for lung function, with the greatest improvements observed when SED was reallocated to sleep or MVPA. Finally, Chapter 8 developed and validated machine learning algorithms that achieved excellent accuracy to classify PA types and intensities in youth with CF. In conclusion, these findings significantly advance the assessment of PA, enhancing our understanding of the relationship between PA and health in CF and informing future condition-specific PA guidelines, care strategies and interventions. |
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| Keywords: |
Physical Activity, Cystic Fibrosis, Lung Function, Accelerometry, Machine Learning, Compositional Analysis |
| College: |
Faculty of Science and Engineering |