Witt, Rachel
(2024)
Using Generalized Additive Models to Compare Age Trends in Actigraphy and Self-Report Sleep Measures Across the Life Span in Individuals with and without Psychiatric Disorders.
Master's Thesis, University of Pittsburgh.
(Unpublished)
This is the latest version of this item.
Abstract
As of 2016, over 1 billion people worldwide, or about 16% of the world’s population, were affected by mental and addictive disorders, causing a considerable burden of disease (Rehm & Shield, 2019). Sleep disturbances are present across mental disorders (Baglioni et al., 2016) and improving sleep quality significantly improves mental health (Scott et al., 2021). This is an area of public health interest due to the health impact of sleep and mental disorders as well as the fact that they show a strong relationship and are potentially modifiable factors for use in interventions.
A study examining age trends in actigraphy and self-report sleep across the lifespan using generalized additive models, found associations between sleep and age (Wallace et al., 2022). While these findings are interesting, their methods focused only on “healthy” people, excluding those with comorbid mental and sleep disorders. Given the association between sleep disturbances and mental disorders, I decided to repeat the analysis, but to include those with psychiatric conditions in the models, examining the association between sleep and mental disorders across the lifespan.
Using the Pittsburgh Lifespan Sleep Databank, a comprehensive databank which incorporates both actigraphy and self-report sleep data over most of the lifespan, I ran generalized additive models predicting selected actigraphy and self-report sleep outcomes from a smoothed age/psychiatric condition interaction and relevant covariates.
Within the healthy control, self-report sleep duration, sleep onset and offset decreased through middle age. Within those presenting with a psychiatric condition, self-report sleep duration decreased through middle age and then showed a large increase into old age. Actigraphy sleep onset showed a marginally significant linear decrease across the lifespan; self-report sleep onset showed a similar decrease, but did not present in a linear pattern. Sleep offset showed the most nonlinear pattern, oscillating over the lifespan with an overall neutral trend.
From these results, we can see that the association between age and sleep differs based on if an individual presents with mental illness, offering an opportunity for future study into why these differences exist and how treating sleep disturbances could lead to better mental health in the long run.
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Details
Item Type: |
University of Pittsburgh ETD
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Status: |
Unpublished |
Creators/Authors: |
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ETD Committee: |
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Date: |
18 December 2024 |
Date Type: |
Publication |
Defense Date: |
11 December 2024 |
Approval Date: |
18 December 2024 |
Submission Date: |
13 December 2024 |
Access Restriction: |
No restriction; Release the ETD for access worldwide immediately. |
Number of Pages: |
52 |
Institution: |
University of Pittsburgh |
Schools and Programs: |
School of Public Health > Biostatistics |
Degree: |
MS - Master of Science |
Thesis Type: |
Master's Thesis |
Refereed: |
Yes |
Uncontrolled Keywords: |
sleep, mental health, mental illness, mental disorder, psychiatric, age, lifespan |
Date Deposited: |
18 Dec 2024 20:04 |
Last Modified: |
18 Dec 2024 20:04 |
URI: |
http://d-scholarship.pitt.edu/id/eprint/47289 |
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Using Generalized Additive Models to Compare Age Trends in Actigraphy and Self-Report Sleep Measures Across the Life Span in Individuals with and without Psychiatric Disorders. (deposited 18 Dec 2024 20:04)
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