Background: Depressive symptoms are common in the peripartum period and pose a great risk to the well-being of the mother, the infant, and the entire family. Evidence from longitudinal studies suggests that affected women do not constitute one homogeneous group in terms of severity, chronicity, and onset of symptoms. To account for individual differences regarding the longitudinal course of depressive symptoms from pregnancy to the postpartum period, growth mixture models have proven to be useful.

Methods: We conducted a group-based trajectory modeling analysis to identify perinatal depressive symptom trajectories in a Swiss sample ( = 151). Depressive symptoms were assessed six times, covering nearly 6 months from the third trimester of pregnancy to 3 months postpartum. In addition to determining perinatal depressive symptom trajectories, we aimed to examine whether these trajectories are linked to psychopathological risk factors such as a history of premenstrual syndrome (PMS), anxiety, prenatal stress, and somatic symptoms after delivery that are associated with hormonal fluctuations.

Results: The findings revealed three trajectories of perinatal depressive symptoms that were relatively stable over time and differed in symptom load (low, medium, high), as well as one trajectory of decreasing symptoms, with a significant symptom reduction after giving birth. Women with a higher depressive symptom load experienced a greater degree of prior premenstrual symptoms, prenatal anxiety, and birth anxiety, as well as somatic symptoms after delivery.

Conclusion: Further research is needed to account for the distinct trajectories of perinatal depressive symptoms in order to provide appropriate care for affected women. A focus on somatic symptoms after delivery and their association with depressive mood is essential to better understand the potential shared etiopathology of reproductive transition phase mood disorders.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9909046PMC
http://dx.doi.org/10.1177/17455057221147391DOI Listing

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