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Identifying Patterns of Free-Living Physical Activity that are Related to Perceived Physical Fatigability

Graves, Jessica L (2021) Identifying Patterns of Free-Living Physical Activity that are Related to Perceived Physical Fatigability. Master's Thesis, University of Pittsburgh. (Unpublished)

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Abstract

Previous accelerometry studies have shown that lower levels of physical activity (PA) are associated higher perceived physical fatigability, a modifiable risk factor which plays an important role along the disablement pathway. However, none have explored how the size, shape, timing and variability of the entire 24-hour rest-activity rhythm (RAR) is associated with fatigability. We examined cross-sectional associations of accelerometry-derived RARs with perceived physical fatigability (Pittsburgh Fatigability Scale (PFS, 0-50)) in a sample of 181 older adults (71.3 + 6.7 years) from the Developmental Epidemiologic Cohort Study and the Mobility and Vitality Lifestyle Program. RAR features included parameter estimates from the anti-logistic extended cosine model, Intradaily Variability and Interdaily Stability, and 4-hour intervals of mean and standard deviation of PA across days. K-means clustering algorithm was applied to cosine model parameters to identify profiles of RAR features. Multivariate quantile and logistic regression were used to test the effects of each RAR feature and cluster on median PFS Physical scores and the odds of having greater perceived physical fatigability (PFS Physical score > 15), adjusting for age, sex, race, BMI, and depression symptomology. Later rise times (up mesor) and timing of midpoint of activity (acrophase) were associated with higher PFS Physical scores (β=1.38, p=0.01; β=1.29, p = 0.01, respectively), later rise times were also associated with 46% increased odds of greater fatigability (OR=1.46, p=0.01). Those with higher physical fatigability showed an overall dampened activity profile, with lower levels of PA between 4am and 8am significantly associated with higher PFS scores (β=-4.50, p=0.03). K-means clustering algorithm identified four RAR profiles: “Less Active/Robust”, “Earlier RAR”, “More Active/Robust” and “Later RAR”. Compared to “Earlier RAR” patterns, “Less Active/ Robust” and “Later RAR” patterns were associated with higher PFS Physical scores (β=6.14, p=0.01; β=3.53, p=0.01, respectively). Having either “Less Active/Robust” or “Later RAR” was associated with 2.26 times the odds of having greater fatigability (p=0.03). This study has public health significance because it is the first to identify classes of RARs which are associated with perceived physical fatigability, allowing future researchers and clinicians to develop interventions aimed at modifying RARs to prevent or delay functional decline.


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Details

Item Type: University of Pittsburgh ETD
Status: Unpublished
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Graves, Jessica Ljeg143@pitt.edu0000-0002-8227-1511
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairGlynn, Nancy Wepidnwg@pitt.edu
Committee MemberVenditti, Elizabeth Mvendittiem@upmc.edu
Committee MemberBoudreau, RobertM Mboudreaur@edc.pitt.edu
Date: 19 January 2021
Date Type: Publication
Defense Date: 4 December 2020
Approval Date: 19 January 2021
Submission Date: 7 December 2020
Access Restriction: 2 year -- Restrict access to University of Pittsburgh for a period of 2 years.
Number of Pages: 59
Institution: University of Pittsburgh
Schools and Programs: School of Public Health > Epidemiology
Degree: MS - Master of Science
Thesis Type: Master's Thesis
Refereed: Yes
Uncontrolled Keywords: accelerometry, rest-activity rhythms, cosine modeling, cluster analysis
Date Deposited: 19 Jan 2021 20:59
Last Modified: 19 Jan 2023 06:15
URI: http://d-scholarship.pitt.edu/id/eprint/40112

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