Risk factors of postpartum depression and depressive symptoms: umbrella review of current evidence from systematic reviews and meta-analyses of observational studies

Background: Evidence on risk factors for postpartum depression (PPD) are fragmented and inconsistent. Aims: To assess the strength and credibility of evidence on risk factors of PPD, ranking them based on the umbrella review methodology. Method: Databases were searched until 1 December 2020, for systematic reviews and meta-analyses of observational studies. Two reviewers assessed quality, credibility of associations according to umbrella review criteria (URC) and evidence certainty according to Grading of Recommendations-Assessment-Development-Evaluations criteria. Results: Including 185 observational studies (n = 3 272 093) from 11 systematic reviews, the association between premenstrual syndrome and PPD was the strongest (highly suggestive: odds ratio 2.20, 95%CI 1.81-2.68), followed by violent experiences (highly suggestive: odds ratio (OR) = 2.07, 95%CI 1.70-2.50) and unintended pregnancy (highly suggestive: OR=1.53, 95%CI 1.35-1.75). Following URC, the association was suggestive for Caesarean section (OR = 1.29, 95%CI 1.17-1.43), gestational diabetes (OR = 1.60, 95%CI 1.25-2.06) and 5-HTTPRL polymorphism (OR = 0.70, 95%CI 0.57-0.86); and weak for preterm delivery (OR = 2.12, 95%CI 1.43-3.14), anaemia during pregnancy (OR = 1.47, 95%CI 1.17-1.84), vitamin D deficiency (OR = 3.67, 95%CI 1.72-7.85) and postpartum anaemia (OR = 1.75, 95%CI 1.18-2.60). No significant associations were found for medically assisted conception and intra-labour epidural analgesia. No association was rated as 'convincing evidence'. According to GRADE, the certainty of the evidence was low for Caesarean section, preterm delivery, 5-HTTLPR polymorphism and anaemia during pregnancy, and 'very low' for remaining factors. Conclusions: The most robust risk factors of PDD were premenstrual syndrome, violent experiences and unintended pregnancy. These results should be integrated in clinical algorithms to assess the risk of PPD