Heterogeneity in long-term trajectories of depressive symptoms: Patterns, predictors and outcomes

Katherine L. Musliner, Trine Munk-Olsen, William W. Eaton, Peter P. Zandi

Research output: Contribution to journalReview articlepeer-review

95 Scopus citations

Abstract

Background Evidence suggests that long-term trajectories of depressive symptoms vary greatly throughout the population, with some individuals experiencing few or no symptoms, some experiencing transient symptoms and others experiencing chronic depression. The goal of this paper is to review studies that examined heterogeneity in long-term trajectories of depressive symptoms and summarize the current knowledge regarding (a) the number and patterns of trajectories and (b) antecedents and outcomes associated with different trajectory patterns. Methods We conducted a systematic review of literature in the Medline and PsychINFO databases. Articles were included if they (a) modeled trajectories of depressive symptoms, (b) used a group-based trajectory modeling approach, (c) followed participants for 5+ years and (d) had a sample size of at least 200. Results We identified 25 studies from 24 separate cohorts. Most of the studies identified either 3 or 4 distinct trajectory classes. Trajectories varied in terms of severity (low, medium, high) and stability (stable, increasing, decreasing). In most studies, the majority of participants had consistently few or no depressive symptoms, but a notable minority (usually <10%) reported persistent symptoms. Predictors of trajectories with greater symptom burden included female gender, lower income/education and non-white race. Other predictors were specific to different populations (e.g. mothers, older adults). High symptom burden trajectories were associated with poor psychiatric and social outcomes. Limitations Comparisons between studies were qualitative. Conclusions Trajectories of depression symptoms in the general population are heterogeneous, with most individuals showing minimal symptoms but a notable minority experiencing chronic high symptom burden.

Original languageEnglish (US)
Pages (from-to)199-211
Number of pages13
JournalJournal of Affective Disorders
Volume192
DOIs
StatePublished - Mar 1 2016

Keywords

  • Depressive symptoms
  • Group-based trajectory modeling
  • Growth mixture modeling
  • Latent class growth analysis
  • Review
  • Trajectories

ASJC Scopus subject areas

  • Clinical Psychology
  • Psychiatry and Mental health

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