Subtypes of Depression: Latent Class Analysis in Spanish Old People with Depressive Symptoms

Abstract

Major depressive disorder (MDD) is one of the most disabling disorders and the one that most contributes to disability. When it occurs in older people, it is an additional burden to their potential physical and cognitive deficiencies, making MDD an important public health problem that supposes a large investment in health. There is a clear lack of consistency between the subtypes of depression found in the literature, ranging from two to seven classes, with three being the most commonly found non-melancholic, melancholic and psychotic, or putative psychotics. The aim of this research is to add knowledge to the profiles of depressive symptoms in a representative sample of older Spanish people, and to study the possible relationship of these symptom profiles with variables that have traditionally been related to depression. Spanish data from the sixth wave of SHARE were used, with 612 Spanish older adults living in Spain. A routine of several LCAs with a different number of classes was performed to answer this first aim to classify Spanish adults with depression symptoms. The results pointed out the presence of three different classes among the participants in the study: psychosomatic (11.12%), melancholic (14.21%), and anhedonic (74.67%). This work represents a step forward to understand the heterogeneity of major depressive disorder, facilitating the diagnosis, and subsequent treatment of older adults.

Approaching person‐centered long‐term care: The trajectories of intrinsic capacity and functional decline in Taiwan

“…Conventionally, the number of latent classes can be determined based on the Akaike information criterion, the Bayesian information criterion (BIC), the sample‐size‐adjusted BIC and entropy. Smaller BIC and sample‐size‐adjusted BIC values suggest better model fitting, 22 whereas greater entropy (>0.7) shows a better degree of separation among latent classes 23 . In Table 1, the BIC and sample‐size‐adjusted BIC suggest a five‐class model, and the entropy method suggests a four‐class model.…”

“…Smaller BIC and sample-size-adjusted BIC values suggest better model fitting, 22 whereas greater entropy (>0.7) shows a better degree of separation among latent classes. 23 In Table 1, the BIC and sample-size-adjusted BIC suggest a five-class model, and the entropy method suggests a four-class model. Because the sample size of the five-class model is extremely imbalanced, we ultimately adopted the four-class model.…”

Special Issue “Mental Health Issues and Quality of Life in Older Individuals”

“…Pérez-Ros and Martínez-Arnau [ 5 ] evaluated the psychometric properties of the self-reported EQ-5D (an instrument to quantify quality of life) in nursing home residents with cognitive impairment to analyse its validity based on scales included in the comprehensive geriatric assessment, showing that it represent a good tool for this purpose in such clinical settings. Pérez-Belmonte et al [ 6 ] analysed major depressive disorder in older individuals from a representative Spanish sample. The results showed the presence of three different classes of major depressive disorder (e.g., psychosomatic, melancholic, and anhedonic (the most prevalent type)).…”

Erratum: Pérez-Belmonte, S., et al. Subtypes of Depression: Latent Class Analysis in Spanish Old People with Depressive Symptoms. Life 2020, 10, 70

“…The authors wish to make the following erratum to this paper [ 1 ]. The Funding is incorrect and must be replaced by the following:…”

“…The authors would like to apologize for any inconvenience caused to the readers by these changes. The Life editorial office has been asked to update the original manuscript [ 1 ] on the article webpage, with a reference to this erratum.…”