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

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Abstract

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.