BACKGROUND Perinatal depression is a major global public health problem, but the onset and progression of symptoms that give rise to perinatal depression are less clear in the scientific literature. METHODS This study followed 1210 Chinese pregnant (mean age = 29.52) women who completed the Edinburgh Postnatal Depression Scale at five time points: 13, 24, and 37 weeks of gestation (G13, G24, G37), and 1 and 6 weeks postpartum (W1, W6). Cross-lagged panel networks were used to analyze and compare networks from first to second trimester (G13 → G24), second to third trimester (G24 → G37), and one week to six weeks postpartum (W1 → W6). RESULTS Results showed that network structure did not differ significantly between the three networks, demonstrating continuity of depressive symptoms over the course of pregnancy and postpartum. Across the three periods, self-reported panic was identified as the symptom that had the largest influence on other symptoms at a following assessment, and self-reported worry was the symptom that was most strongly influenced by depressive symptoms at previous timepoints. Moreover, thoughts of self-harm showed a distinct feature where it could only trigger other symptoms in the postnatal, but not prenatal period. LIMITATIONS Self-reported questionnaires used in this study may be susceptible to bias. Items of perinatal depressive symptoms included in the network analysis are also not exhaustive. CONCLUSIONS Findings from this symptom-oriented psychopathology network shed light upon the developmental course of perinatal depressive symptoms, providing insights for tailored preventative intervention programs.
Unraveling the onset and continuity of depressive symptoms from early pregnancy to six weeks postpartum: A longitudinal network analysis.
Yijia Li,M. Gao,Sihan Liu,Li Yang,Ruimin Zheng
Published 2025 in Journal of Affective Disorders
ABSTRACT
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- Publication year
2025
- Venue
Journal of Affective Disorders
- Publication date
2025-03-01
- Fields of study
Medicine, Psychology
- Identifiers
- External record
- Source metadata
Semantic Scholar, PubMed
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