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

Journal: Journal of affective disorders

Volume: 223

Issue: 

Year of Publication: 2018

Affiliated Institutions:  Alan J Flisher Centre for Public Mental Health, Department of Psychiatry and Mental Health, University of Cape Town, South Africa. Electronic address: emily.baron@uct.ac.za. Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, United States. Alan J Flisher Centre for Public Mental Health, Department of Psychiatry and Mental Health, University of Cape Town, South Africa. Alan J Flisher Centre for Public Mental Health, Department of Psychiatry and Mental Health, University of Cape Town, South Africa; Center for Global Mental Health, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.

Abstract summary 

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.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).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.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.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.

Authors & Co-authors:  Baron Emily E Bass Judith J Murray Sarah M SM Schneider Marguerite M Lund Crick C

Study Outcome 

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Statistics
Citations :  Bauer DJ, Curran PJ. Distributional assumptions of growth mixture models: implications for overextraction of latent trajectory classes. Psychol Methods. 2003;8:338–363.
Authors :  5
Identifiers
Doi : 10.1016/j.jad.2017.07.046
SSN : 1573-2517
Study Population
Women
Mesh Terms
Depression, Postpartum
Other Terms
Depressive symptoms;Growth mixture modelling;Postpartum;Pregnancy;Risk factors;Trajectory
Study Design
Cross Sectional Study
Study Approach
Systemic Review
Country of Study
Publication Country
Netherlands