Abstract
Objective
To examine which 24-hour rest-activity rhythm (RAR) characteristics are associated
with depression symptoms in stroke survivors.
Design
Cross-sectional observational study examining associations of RAR characteristics
with the presence of depression symptoms adjusting for age, sex, race, and medical
comorbidity.
Setting
Community setting.
Participants
Stroke survivors: (1) recruited locally (N women=35, N men=28) and (2) a nationally
representative probability sample (the National Health and Nutrition Examination Survey
[NHANES]; N women=156, N men=124).
Interventions
None.
Measurements
Objective RAR characteristics derived from accelerometer recordings including activity
onset/offset times and non-parametric measures of RAR strength (relative amplitude),
stability (interdaily stability), and fragmentation (intradaily variability). The
presence of depression symptoms was categorized using Patient Health Questionnaire
scores.
Results
In both samples, the only RAR characteristic associated with depression symptoms was
intradaily variability (fragmentation): local sample, odds ratio=1.96 [95% confidence
interval=1.05-3.63]; NHANES sample, odds ratio=1.34, [95% confidence interval=1.01-1.78]).
In the NHANES sample, which included both mild and moderate/severe depression, the
association between 24-hour sleep-wake fragmentation and depression symptoms was driven
by moderate-to-severe cases.
Conclusions
Stroke survivors with higher levels of RAR fragmentation were more likely to have
depression symptoms in both samples. These findings have implications, given prior
studies in general samples linking RAR fragmentation with future depression and dementia
risk. Research is needed to establish the potential consequences, mechanisms, and
modifiability of RAR fragmentation in stroke survivors.
Keywords
List of abbreviations:
NHANES (National Health and Nutrition Examination Survey), PHQ-9 (Patient Health Questionnaire-9), PSD (poststroke depression), RAR (rest-activity rhythm)To read this article in full you will need to make a payment
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Article info
Publication history
Published online: February 01, 2023
Accepted:
January 12,
2023
Received in revised form:
January 11,
2023
Received:
August 10,
2022
Publication stage
In Press Journal Pre-ProofFootnotes
This research was supported by research funding from the National Institutes of Health (UL1TR001857), the Pittsburgh Foundation, and the University of Pittsburgh School of Health and Rehabilitation Sciences Doctoral Student Award.
Disclosures: S.F.S. is owner/CEO of Activity Rhythm Solutions Corporation, which is developing activity pattern monitoring technology with support from an NIH award (R41AG069596) and was not involved with the work reported here. None of the sources of support or relations listed here were involved in any aspect of the design, analysis, or interpretations in this paper. The remaining authors have no conflicts to disclose.
Identification
Copyright
© 2023 by the American Congress of Rehabilitation Medicine.
