Year: 2023
Type: preprint
Study design: Observational Study
Abstract: and circadian function are leading candidate markers for early relapse identification in MDD. Consumer-grade wearable devices may offer opportunity for remote and real-time examination of dynamic changes in sleep. Objective: We used FitBit data from individuals with recurrent MDD to describe longitudinal associations of sleep duration, quality, and regularity with subsequent depressive relapse and depression severity.Design: Data were collected as part of a longitudinal remote measurement technologies (RMT) cohort study in people with recurrent MDD. Participants: A total of 623 people with MDD wore a FitBit and completed regular outcome assessments via email for a median follow-up of 541 days. Multivariable regression models tested for associations between sleep features and depression outcomes. We considered two samples of people with at least one assessment of relapse (n=213) or at least one assessment of depression severity (n=390). Results: Increased intra-individual variability in total sleep time, greater sleep fragmentation, and later sleep mid-points were associated with worse depression outcomes. Adjusted Population Attributable Fractions (PAFs) suggested that an intervention to increase sleep consistency in adults with MDD could reduce the population risk for depression by up to 18-37%. Conclusion: We found consistent associations between wearable-derived sleep features and the probability of depressive relapse and increased depressive symptom severity. Disordered sleep is prevalent and disruptive, and challenging to capture longitudinally via conventional laboratory sleep assessments. Our study demonstrates a role for consumer-grade activity trackers to predict relapse risk and depression severity in people with recurrent MDD.
Authors: Faith Matcham, Ewan Carr, Nicholas Meyer, Katie M White, Carolin Oetzmann, Daniel Leightley, Femke Lamers, Sara Siddi, Nick Cummins, Peter Annas, Giovanni de Girolamo, Josep Maria Haro, Grace Lavelle, Qingqin Li, Federica Lombardini, David C Mohr, Vaibhav Narayan, Brenda Penninx, Marta Coromina, Gemma Riquelme Alacid, Sara Simblett, Raluca Nica, Til Wykes, Jens Christian Brasen, Inez Myin-Germeys, Richard JB Dobson, Amos A Folarin, Yatharth Ranjan, Zulqarnain Rashid, Jude DIneley, Srinivasan Vairavan, Matthew Hotopf
Institutions: Centro de Investigación Biomédica en Red de Salud Mental, Parc Sanitari Sant Joan de Déu, Universitat de Barcelona, King's College London, University College London Hospitals NHS Foundation Trust, Amsterdam Public Health, Amsterdam University Medical Centers, Vrije Universiteit Amsterdam, Lundbeck (Denmark), Centro San Giovanni di Dio Fatebenefratelli, Northwestern University, KU Leuven, South London and Maudsley NHS Foundation Trust
Language: English
Topic: Sleep and related disorders
Subfield: Experimental and Cognitive Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: green
Funders: Eli Lilly and Company, Sanofi, NHS Blood and Transplant, South London and Maudsley NHS Foundation Trust, European Federation of Pharmaceutical Industries and Associations, Alzheimer's Society, National Institute for Health and Care Research, Department of Health and Social Care, King's College London, European Commission, ZonMw, King's Health Partners, Innovative Medicines Initiative, H. Lundbeck A/S, GIESKES-STRIJBIS FONDS, NIHR BioResource, NIHR Maudsley Biomedical Research Centre, Medical Research Council, Health Data Research UK
OpenAlex ID: W4360867574