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Depressive subtypes in an elderly cohort identified using latent class analysis.

E M Veltman1, F Lamers2, H C Comijs2

  • 1Department of Psychiatry, Leiden University Medical Center, The Netherlands.

Journal of Affective Disorders
|May 5, 2017
PubMed
Summary

This study identified three distinct subtypes of late-life depression using data-driven methods. Key differences were observed in appetite, weight, and metabolic health, suggesting distinct pathways in older adults.

Keywords:
Atypical depressionDepression subtypesLatent class analysisMelancholic depressionMetabolic syndrome

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Area of Science:

  • Gerontology
  • Psychiatry
  • Computational Statistics

Background:

  • Depressive disorders exhibit heterogeneity, necessitating subtype identification for effective research and clinical practice.
  • Late-life depression subtypes are understudied, highlighting the need for empirical classification methods.
  • Data-driven approaches can enhance the classification of depression in older adults.

Purpose of the Study:

  • To identify distinct subtypes of major depressive disorder in older adults using latent class analysis.
  • To characterize these subtypes based on sociodemographic and clinical features.
  • To explore potential differences in metabolic and cardiovascular health among depression subtypes in the elderly.

Main Methods:

  • Latent class analysis (LCA) was applied to depression symptom data from 359 older adults (≥60 years) diagnosed with major depressive disorder.
  • Ten items from the Composite International Diagnostic Interview (CIDI) were used to define depression symptom profiles.
  • Identified classes were further analyzed using sociodemographic, clinical characteristics, and health data.

Main Results:

  • Three distinct depression subtypes were identified: moderate-severe (46.5%), severe melancholic (38.4%), and severe atypical (15.0%).
  • Appetite, weight changes, psychomotor symptoms, and loss of interest were key distinguishing features between subtypes.
  • The severe atypical subtype showed higher prevalence of females, lower mean age, higher BMI, and increased cardiovascular disease and metabolic syndrome compared to the melancholic subtype.

Conclusions:

  • Three empirically-derived subtypes of late-life depression were identified, mirroring patterns seen in younger adults.
  • Distinct differences in appetite, weight, and metabolic/cardiovascular health suggest varying underlying biological pathways.
  • These findings underscore the importance of considering metabolic pathways in the pathogenesis and treatment of depression in older individuals.