The symptom network structure of depressive symptoms in late-life: Results from a European population study.


Journal

Molecular psychiatry
ISSN: 1476-5578
Titre abrégé: Mol Psychiatry
Pays: England
ID NLM: 9607835

Informations de publication

Date de publication:
07 2020
Historique:
received: 18 03 2018
accepted: 08 06 2018
revised: 09 05 2018
pubmed: 2 9 2018
medline: 18 3 2021
entrez: 2 9 2018
Statut: ppublish

Résumé

The network theory conceptualizes mental disorders as complex networks of symptoms influencing each other by creating feedback loops, leading to a self-sustained syndromic constellation. Symptoms central to the network have the greatest impact in sustaining the rest of symptoms. This analysis focused on the network structure of depressive symptoms in late-life because of their distinct etiologic factors, clinical presentation, and outcomes. We analyzed cross-sectional data from wave 2 of the 19 country Survey of Health, Ageing, and Retirement in Europe (SHARE) and included non-institutionalized adults aged 65 years or older (mean age 74 years, 59% females) endorsing at least one depressive symptom on the EURO-D scale for depression (N =8,557). We characterized the network structure of depressive symptoms in late-life and used indices of "strength", "betweenness", and "closeness" to identify symptoms central to the network. We used a case-dropping bootstrap procedure to assess network stability. Death wishes, depressed mood, loss of interest, and pessimism had the highest values of centrality. Insomnia, fatigue and appetite changes had lower centrality values. The identified network remained stable after dropping 74.5% of the sample. Sex or age did not significantly influence the network structure. In conclusion, death wishes, depressed mood, loss of interest, and pessimism constitute the "backbone" that sustains depressive symptoms in late-life. Symptoms central to the network of depressive symptoms may be used as targets for novel, focused interventions and in studies investigating neurobiological processes central to late-life depression.

Identifiants

pubmed: 30171210
doi: 10.1038/s41380-018-0232-0
pii: 10.1038/s41380-018-0232-0
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

1447-1456

Subventions

Organisme : NIMH NIH HHS
ID : P50 MH113838
Pays : United States
Organisme : NIA NIH HHS
ID : P01 AG005842
Pays : United States
Organisme : NIA NIH HHS
ID : R21 AG025169
Pays : United States
Organisme : NIA NIH HHS
ID : HHSN271201300071C
Pays : United States

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Auteurs

Martino Belvederi Murri (M)

Section of Psychiatry, Department of Neuroscience, Ophthalmology, Genetics and Infant-Maternal Science, University of Genoa, Genoa, Italy.
IRCCS Ospedale Policlinico San Martino, Genova, Italy.
Department of Psychological Medicine, King's College London, London, UK.

Mario Amore (M)

Section of Psychiatry, Department of Neuroscience, Ophthalmology, Genetics and Infant-Maternal Science, University of Genoa, Genoa, Italy.
IRCCS Ospedale Policlinico San Martino, Genova, Italy.

Matteo Respino (M)

Institute for Geriatric Psychiatry, Weill Cornell Medicine, White Plains, New York, NY, USA.

George S Alexopoulos (GS)

Institute for Geriatric Psychiatry, Weill Cornell Medicine, White Plains, New York, NY, USA. gsalexop@med.cornell.edu.

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