Personality traits as a risk factor for postpartum depression: A systematic review and meta-analysis

Background: Certain personality traits increase vulnerability to depression, but the evidence linking personality and postpartum depression (PPD) is less robust. This systematic review aimed to identify personality traits that increase the risk of PPD. Methods: We systematically reviewed studies retrieved from PubMed/Medline, PsycINFO, Scopus, CINAHL, and Cochrane, following the PRISMA guidelines for reporting. We carried out a meta-analysis on the association between neuroticism and PPD. Results: A total of 34 studies were analyzed. Of these, 31 considered at least one trait associated with PPD; 10 studies considered at least one trait not associated with PPD. The meta -analysis included 13 studies, concluding that neuroticism was associated with PPD (OR: 1.37; 95%CI: 1.22-1.53; p<0.001). Limitations: Study design and approach to personality assessment influence results. Prospective longitudinal studies of persons with no prior history of mood disorder would provide stronger evidence about whether particular personality traits predict PPD. Most studies reviewed used self-report measures to assess personality. Study design and approach to personality assessment influence results, and indications of publication bias were found. Conclusions: Neuroticism is the personality trait most widely studied in relation to PPD. Our meta-analysis found this trait is strongly related with PPD. Moreover, vulnerable personality style and trait anxiety are also associated with PPD. Screening for these traits might help identify women at risk, improving prevention, early detection, and possibly treatment.

Automated summary

This systematic review found that neuroticism is the most widely studied personality trait in relation to postpartum depression (PPD). The meta-analysis showed a strong relationship between neuroticism and PPD, while vulnerable personality style and trait anxiety were also associated with PPD. Screening for these traits could help identify women at risk, improving early detection and potentially treatment.