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

Philip Zeyen; Lena Sannemann; Xiaochen Hu; Joseph Kambeitz; Christian Rietz; Michael Wagner; Christiane Woopen; Susanne Zank; Frank Jessen; Forugh S Dafsari

doi:10.1016/j.jad.2024.05.059

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

J Affect Disord. 2024 May 14:359:342-349. doi: 10.1016/j.jad.2024.05.059. Online ahead of print.

Authors

Affiliations

¹ Department of Psychiatry and Psychotherapy, University of Cologne, Faculty of Medicine, University Hospital Cologne, Cologne, Germany. Electronic address: philip.zeyen@uk-koeln.de.
² Department of Psychiatry and Psychotherapy, University of Cologne, Faculty of Medicine, University Hospital Cologne, Cologne, Germany.
³ 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.
⁴ 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.
⁵ Heinrich-Hertz-Chair, Center for Life Ethics, University of Bonn, Bonn, Germany.
⁶ 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.
⁷ 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.

PMID: 38754595
DOI: 10.1016/j.jad.2024.05.059

Abstract

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: 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: 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 R² = 0.228, p < .001) and in both clusters (cluster 1: Nagelkerke's R² = 0.171, p < .001; cluster 2: Nagelkerke's R² = 0.213, p < .001), respectively.

Limitations: The main limitations are the restriction to cognitively unimpaired individuals and the use of a self-rated questionnaire to assess depressive symptoms.

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.

Keywords: Geriatric depression; Late-life depression; Population-based cross-sectional study; Risk factors.