Prediction of depressive symptoms at high age (80+) by psychological, biological and functional factors.

Geriatric depression Late-life depression Population-based cross-sectional study Risk factors

Journal

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

Informations de publication

Date de publication:
14 May 2024
Historique:
received: 31 10 2023
revised: 18 04 2024
accepted: 12 05 2024
medline: 17 5 2024
pubmed: 17 5 2024
entrez: 16 5 2024
Statut: aheadofprint

Résumé

Late-life depression (LLD) is highly prevalent, especially in people aged 80 years and older. We aimed to investigate predictors and their influence on depressive symptoms in LLD. We analysed data from the NRW80+ study, a population-based cross-sectional study of individuals aged 80 years and older. Data from n = 926 cognitively unimpaired participants were included. We reduced 95 variables to 21 predictors of depressive symptoms by using a two-step cluster analysis (TSCA), which were assigned to one of four factors (function, values and lifestyle, autonomy and contentment, biological-somatic) according to a principal component analysis. A second TSCA with complete data sets (n = 879) was used to define clusters of participants. Using weighted mean composite scores (CS) for each factor group, binary logistic regression analyses were performed to predict depressive symptoms for each cluster and the total population. The second TSCA yielded two clusters (cluster 1 (n = 688), cluster 2 (n = 191)). The proportion of participants with depressive symptoms was significantly higher in cluster 2 compared to cluster 1 (39 % vs. 15 %; OR = 3.6; 95 % CI 2.5-5.1; p < .001). Participants in cluster 2 were significantly older (mean age 88 vs. 85 years; p < .001), with a higher proportion of women (56 % vs. 46 %; OR = 1.5; 95 % CI 1.1-2.0; p = .016), had a higher BMI (p = .017), lower financial resources (OR = 2.3; 95 % CI 1.6-3.5; p < .001), lower educational level (OR = 1.8; 95 % CI 1.2-2.5; p = .002), higher proportion of single, separated or widowed participants (OR = 1.9; 95 % CI 1.3-2.6; p < .001) and a smaller mean social network (p = .044) compared to cluster 1. Binary logistic regression analyses showed that the weighted mean CS including the autonomy and contentment predictors explained the largest proportion of variance (22.8 %) for depressive symptoms in the total population (Nagelkerke's R The main limitations are the restriction to cognitively unimpaired individuals and the use of a self-rated questionnaire to assess depressive symptoms. Psychological factors such as autonomy and contentment are critical for the occurrence of depressive symptoms at higher age, independent of the functional and somatic status and may serve as specific targets for psychotherapy.

Sections du résumé

BACKGROUND BACKGROUND
Late-life depression (LLD) is highly prevalent, especially in people aged 80 years and older. We aimed to investigate predictors and their influence on depressive symptoms in LLD.
METHODS METHODS
We analysed data from the NRW80+ study, a population-based cross-sectional study of individuals aged 80 years and older. Data from n = 926 cognitively unimpaired participants were included. We reduced 95 variables to 21 predictors of depressive symptoms by using a two-step cluster analysis (TSCA), which were assigned to one of four factors (function, values and lifestyle, autonomy and contentment, biological-somatic) according to a principal component analysis. A second TSCA with complete data sets (n = 879) was used to define clusters of participants. Using weighted mean composite scores (CS) for each factor group, binary logistic regression analyses were performed to predict depressive symptoms for each cluster and the total population.
RESULTS RESULTS
The second TSCA yielded two clusters (cluster 1 (n = 688), cluster 2 (n = 191)). The proportion of participants with depressive symptoms was significantly higher in cluster 2 compared to cluster 1 (39 % vs. 15 %; OR = 3.6; 95 % CI 2.5-5.1; p < .001). Participants in cluster 2 were significantly older (mean age 88 vs. 85 years; p < .001), with a higher proportion of women (56 % vs. 46 %; OR = 1.5; 95 % CI 1.1-2.0; p = .016), had a higher BMI (p = .017), lower financial resources (OR = 2.3; 95 % CI 1.6-3.5; p < .001), lower educational level (OR = 1.8; 95 % CI 1.2-2.5; p = .002), higher proportion of single, separated or widowed participants (OR = 1.9; 95 % CI 1.3-2.6; p < .001) and a smaller mean social network (p = .044) compared to cluster 1. Binary logistic regression analyses showed that the weighted mean CS including the autonomy and contentment predictors explained the largest proportion of variance (22.8 %) for depressive symptoms in the total population (Nagelkerke's R
LIMITATIONS CONCLUSIONS
The main limitations are the restriction to cognitively unimpaired individuals and the use of a self-rated questionnaire to assess depressive symptoms.
CONCLUSIONS CONCLUSIONS
Psychological factors such as autonomy and contentment are critical for the occurrence of depressive symptoms at higher age, independent of the functional and somatic status and may serve as specific targets for psychotherapy.

Identifiants

pubmed: 38754595
pii: S0165-0327(24)00796-1
doi: 10.1016/j.jad.2024.05.059
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest All authors disclosed no relevant relationships.

Auteurs

Philip Zeyen (P)

Department of Psychiatry and Psychotherapy, University of Cologne, Faculty of Medicine, University Hospital Cologne, Cologne, Germany. Electronic address: philip.zeyen@uk-koeln.de.

Lena Sannemann (L)

Department of Psychiatry and Psychotherapy, University of Cologne, Faculty of Medicine, University Hospital Cologne, Cologne, Germany.

Xiaochen Hu (X)

Department of Psychiatry and Psychotherapy, University of Cologne, Faculty of Medicine, University Hospital Cologne, Cologne, Germany.

Joseph Kambeitz (J)

Department of Psychiatry and Psychotherapy, University of Cologne, Faculty of Medicine, University Hospital Cologne, Cologne, Germany.

Christian Rietz (C)

CERES - Cologne Center for Ethics, Rights, Economics, and Social Sciences of Health, University of Cologne, Cologne, Germany; Institute for Educational Science, Heidelberg University of Education, Heidelberg, Germany.

Michael Wagner (M)

CERES - Cologne Center for Ethics, Rights, Economics, and Social Sciences of Health, University of Cologne, Cologne, Germany; Institute of Sociology and Social Psychology, University of Cologne, Cologne, Germany.

Christiane Woopen (C)

Heinrich-Hertz-Chair, Center for Life Ethics, University of Bonn, Bonn, Germany.

Susanne Zank (S)

CERES - Cologne Center for Ethics, Rights, Economics, and Social Sciences of Health, University of Cologne, Cologne, Germany; Department of Special Education and Rehabilitation Science, Faculty of Human Sciences, University of Cologne, Cologne, Germany.

Frank Jessen (F)

Department of Psychiatry and Psychotherapy, University of Cologne, Faculty of Medicine, University Hospital Cologne, Cologne, Germany; German Center for Neurodegenerative Disease (DZNE), Bonn, Cologne, Germany; Cellular Stress Response in Aging-Associated Diseases (CECAD) Cluster of Excellence, University of Cologne, Faculty of Medicine, University Hospital Cologne, Cologne, Germany.

Forugh S Dafsari (FS)

Department of Psychiatry and Psychotherapy, University of Cologne, Faculty of Medicine, University Hospital Cologne, Cologne, Germany.

Classifications MeSH