Multiple measures of sleep patterns and sleep efficiency are associated with lifetime diagnoses of mental illness, according to a new study that used wrist accelerometer data to track sleep. The study is publishing today (October 12th, 2021) in the open-access journal PLOS Medicine by Shreejoy Tripathy of the University of Toronto and the Centre for Addiction and Mental Health (CAMH), Canada, and colleagues.
Sleep problems are known to be both symptoms of and modifiable risk factors for many psychiatric disorders. In the new study, researchers collected data on 89,205 individuals participating in the UK Biobank study who wore accelerometers on their wrist for 7 days between 2013 and 2015. The accelerometers were used to generate objective data on sleep timing, duration, efficiency, and variability. Data on psychiatric diagnoses – including schizophrenia spectrum disorders, bipolar disorder, major depressive disorder, and anxiety disorders – as well as other health and sociodemographic information was available for all participants, who ranged in age from 43 to 79 and were 56% female.
The researchers found striking trends when they examined the associations between the sleep measures and inpatient psychiatric diagnoses. Each diagnosis was associated with a mean of 8.5 of the 10 accelerometer-derived sleep measures. Measures of sleep quality, such as sleep efficiency, were generally more affected by psychiatric diagnosis than measures of sleep duration. Effect sizes were small; the largest magnitude effect was observed for the association between sleep efficiency and major depressive disorder. Associations were replicated across ancestries and sexes.
“Our findings provide a rich clinical portrait of the ways in which sleep can be disrupted across individuals with lifetime mental illness,” the authors say. “This work showcases the capacity of accelerometry to provide detailed, objective sleep measurements at scale, even across cohorts of tens of thousands of individuals.”
The authors add, “This work showcases the power of wearable devices to provide fine-grained information about how sleep is disrupted in mental illness.”
Reference: “Association of accelerometer-derived sleep measures with lifetime psychiatric diagnoses: A cross-sectional study of 89,205 participants from the UK Biobank” by Michael Wainberg, Samuel E. Jones, Lindsay Melhuish Beaupre, Sean L. Hill, Daniel Felsky, Manuel A. Rivas, Andrew S. P. Lim, Hanna M. Ollila and Shreejoy J. Tripathy, 12 October 2021, PLOS Medicine.
Funding: The authors acknowledge Milos Milic for data curation assistance. MW and SJT acknowledge support from the Kavli Foundation, Krembil Foundation, CAMH Discovery Fund, the McLaughlin Foundation, NSERC (RGPIN-2020-05834 and DGECR-2020-00048) and CIHR (NGN-171423). DF is supported by the Michael and Sonja Koerner Foundation New Scientist Program, Krembil Foundation, CAMH Discovery Fund, and the McLaughlin Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. This research was conducted under the auspices of UK Biobank application 61530, “Multimodal subtyping of mental illness across the adult lifespan through integration of multi-scale whole-person phenotypes.”
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