The relationship between wearable-derived sleep features and relapse in Major Depressive Disorder.

Longitudinal Major Depressive Disorder Sleep Wearable technology

Journal

Journal of affective disorders
ISSN: 1573-2517
Titre abrégé: J Affect Disord
Pays: Netherlands
ID NLM: 7906073

Informations de publication

Date de publication:
20 Jul 2024
Historique:
received: 15 12 2023
revised: 09 07 2024
accepted: 16 07 2024
medline: 23 7 2024
pubmed: 23 7 2024
entrez: 22 7 2024
Statut: aheadofprint

Résumé

Changes in sleep and circadian function are leading candidate markers for the detection of relapse in Major Depressive Disorder (MDD). Consumer-grade wearable devices may enable remote and real-time examination of dynamic changes in sleep. Fitbit data from individuals with recurrent MDD were used to describe the longitudinal effects of sleep duration, quality, and regularity on subsequent depression relapse and severity. Data were collected as part of a longitudinal observational mobile Health (mHealth) cohort study in people with recurrent MDD. Participants wore a Fitbit device and completed regular outcome assessments via email for a median follow-up of 541 days. We used multivariable regression models to test the effects of sleep features on depression outcomes. We considered respondents with at least one assessment of relapse (n = 218) or at least one assessment of depression severity (n = 393). Increased intra-individual variability in total sleep time, greater sleep fragmentation, lower sleep efficiency, and more variable sleep midpoints were associated with worse depression outcomes. Adjusted Population Attributable Fractions suggested that an intervention to increase sleep consistency in adults with MDD could reduce the population risk for depression relapse by up to 22 %. Limitations include a potentially underpowered primary outcome due to the smaller number of relapses identified than expected. Our study demonstrates a role for consumer-grade activity trackers in estimating relapse risk and depression severity in people with recurrent MDD. Variability in sleep duration and midpoint may be useful targets for stratified interventions.

Sections du résumé

BACKGROUND BACKGROUND
Changes in sleep and circadian function are leading candidate markers for the detection of relapse in Major Depressive Disorder (MDD). Consumer-grade wearable devices may enable remote and real-time examination of dynamic changes in sleep. Fitbit data from individuals with recurrent MDD were used to describe the longitudinal effects of sleep duration, quality, and regularity on subsequent depression relapse and severity.
METHODS METHODS
Data were collected as part of a longitudinal observational mobile Health (mHealth) cohort study in people with recurrent MDD. Participants wore a Fitbit device and completed regular outcome assessments via email for a median follow-up of 541 days. We used multivariable regression models to test the effects of sleep features on depression outcomes. We considered respondents with at least one assessment of relapse (n = 218) or at least one assessment of depression severity (n = 393).
RESULTS RESULTS
Increased intra-individual variability in total sleep time, greater sleep fragmentation, lower sleep efficiency, and more variable sleep midpoints were associated with worse depression outcomes. Adjusted Population Attributable Fractions suggested that an intervention to increase sleep consistency in adults with MDD could reduce the population risk for depression relapse by up to 22 %.
LIMITATIONS CONCLUSIONS
Limitations include a potentially underpowered primary outcome due to the smaller number of relapses identified than expected.
CONCLUSION CONCLUSIONS
Our study demonstrates a role for consumer-grade activity trackers in estimating relapse risk and depression severity in people with recurrent MDD. Variability in sleep duration and midpoint may be useful targets for stratified interventions.

Identifiants

DOI: 10.1016/j.jad.2024.07.136 PMID: 39038618
pubmed: 39038618
pii: S0165-0327(24)01194-7
doi: 10.1016/j.jad.2024.07.136
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

Copyright © 2024. Published by Elsevier B.V.

Déclaration de conflit d'intérêts

Declaration of competing interest HE was a full-time employee of H. Lundbeck A/S and held stock and stock options in H. Lundbeck A/S at the time of study conduct. QL, SV and VN were employees of Janssen Research & Development, LLC and held company stocks/stock options at the time of study conduct. JMH has received economic compensation for participating in advisory boards or giving educational lectures from Eli Lilly & Co, Sanofi, Lundbeck, and Otsuka. No other authors have competing interests to declare.

Auteurs

F Matcham (F)

School of Psychology, University of Sussex, Falmer, UK; Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK. Electronic address: F.Matcham@sussex.ac.uk.

E Carr (E)

Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.

N Meyer (N)

Insomnia and Behavioural Sleep Medicine Clinic, University College London Hospitals NHS Foundation Trust, London, UK.

K M White (KM)

Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.

C Oetzmann (C)

Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.

D Leightley (D)

Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.

F Lamers (F)

Department of Psychiatry and Amsterdam Public Health Research Institute, Amsterdam UMC, Vrije Universiteit, Amsterdam, the Netherlands.

S Siddi (S)

Parc Sanitari Sant Joan de Déu, Fundació San Joan de Déu, CIBERSAM, Universitat de Barcelona, Barcelona, Spain.

N Cummins (N)

Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.

P Annas (P)

H. Lundbeck A/S, Valby, Denmark.

G de Girolamo (G)

IRCCS Instituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.

J M Haro (JM)

Parc Sanitari Sant Joan de Déu, Fundació San Joan de Déu, CIBERSAM, Universitat de Barcelona, Barcelona, Spain.

G Lavelle (G)

Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.

Q Li (Q)

H. Lundbeck A/S, Valby, Denmark.

F Lombardini (F)

Parc Sanitari Sant Joan de Déu, Fundació San Joan de Déu, CIBERSAM, Universitat de Barcelona, Barcelona, Spain.

D C Mohr (DC)

Center for Behavioral Intervention Technologies, Department of Preventative Medicine, Northwestern University, Chicago, IL, USA.

V A Narayan (VA)

Davos Alzheimer's Collaborative, Wayne, PA, USA.

B W H J Penninx (BWHJ)

Insomnia and Behavioural Sleep Medicine Clinic, University College London Hospitals NHS Foundation Trust, London, UK.

M Coromina (M)

Parc Sanitari Sant Joan de Déu, Fundació San Joan de Déu, CIBERSAM, Universitat de Barcelona, Barcelona, Spain.

G Riquelme Alacid (G)

Parc Sanitari Sant Joan de Déu, Fundació San Joan de Déu, CIBERSAM, Universitat de Barcelona, Barcelona, Spain.

S K Simblett (SK)

Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.

R Nica (R)

RADAR-CNS Patient Advisory Board, UK.

T Wykes (T)

Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK; South London and Maudsley NHS Foundation Trust, London, UK.

J C Brasen (JC)

H. Lundbeck A/S, Valby, Denmark.

I Myin-Germeys (I)

Center for Contextual Psychiatry, Department of Neurosciences, KU Leuven, Leuven, Belgium.

R J B Dobson (RJB)

Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.

A A Folarin (AA)

Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK; South London and Maudsley NHS Foundation Trust, London, UK.

Y Ranjan (Y)

Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.

Z Rashid (Z)

Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.

J Dineley (J)

Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.

S Vairavan (S)

Janssen Research and Development, LLC, Titusville, NJ, USA.

M Hotopf (M)

Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK; South London and Maudsley NHS Foundation Trust, London, UK.
Radar-cns.org, UK.

Classifications MeSH