A systematic review of growth curve mixture modelling literature investigating trajectories of perinatal depressive symptoms and associated risk factors

Emily Baron, Judith Bass, Sarah M. Murray, Marguerite Schneider, Crick Lund

Research output: Contribution to journalReview article

Abstract

Background The aim of this study was to review the growth curve mixture modelling (GCMM) literature investigating trajectories of perinatal maternal depressive symptoms and associated risk factors. Methods A systematic search of peer-reviewed articles published until November 2015 was conducted in seven databases. Articles using GCMM to identify trajectories of perinatal depressive symptoms were considered. Symptoms had to be assessed at least three times, anytime from pregnancy to two years postpartum (PROSPERO; 2016:CRD42016032600). Results Eleven studies met inclusion criteria. All reported a low risk trajectory, characterised by stable low depressive symptoms throughout the perinatal period. A stable moderate-high or high symptom trajectory was reported in eight of 11 studies, suggesting a high-risk group with persistent depressive symptoms. Six studies also reported transient trajectories, with either increasing, decreasing or episodic depressive symptoms. None of the demographic, personality or clinical characteristics investigated systematically differentiated groups of women with different symptom trajectories, within or across studies. Thus, it is difficult to differentiate women at high or low risk of specific perinatal depression trajectories. Limitations A meta-analysis was not possible. The studies’ settings and inclusion criteria limit the generalisability of the findings to low-risk, middle- to high-income women. Conclusions Relatively similar trajectories of perinatal depressive symptoms were identified across studies. Evidence on factors differentiating women assigned to different trajectories was inconsistent. Research with larger samples and in more diverse settings is needed to inform services and policies on how and when to effectively identify subgroups of women at high risk of perinatal depression.

Original languageEnglish (US)
Pages (from-to)194-208
Number of pages15
JournalJournal of Affective Disorders
Volume223
DOIs
StatePublished - Dec 1 2017

Keywords

  • Depressive symptoms
  • Growth mixture modelling
  • Postpartum
  • Pregnancy
  • Risk factors
  • Trajectory

ASJC Scopus subject areas

  • Clinical Psychology
  • Psychiatry and Mental health

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