Postpartum depression in mothers and fathers: a structural equation model

Author:

Duan Zhizhou,Wang Yuanyuan,Jiang Ping,Wilson Amanda,Guo Yan,Lv Yongliang,Yang Xiaonan,Yu Renjie,Wang Shuilan,Wu Zhengyan,Xia Mengqing,Wang Guosheng,Tao Ye,Xiaohong L,Ma Ling,Shen Hong,Sun Jue,Deng Wei,Yang Yong,Chen Runsen

Abstract

Abstract Background Post-partum depression (PPD) is a growing mental health concern worldwide. There is little evidence in the Chinese context of the relationship between paternal PPD and maternal PPD. Given the growing global concerns this relationship requires further exploration. Methods A survey was conducted with 950 total couples from March 2017 to December 2018. The study was conducted using a standardized questionnaire that included basic demographic information, information on the relationship between the mother-in-law and daughter-in-law, marital satisfaction (both maternal and paternal), and PPD symptoms. Structural Equation Modelling (SEM) analysis was used to explore the underlying mechanism for PPD symptoms in mothers and fathers. Results In 4.4% of the couples both the wife and the husband showed depressive symptoms. Maternal marital satisfaction showed a significant mediating effect on paternal PPD (B = -0.114, p < 0.01), and there was a direct effect of maternal PPD on paternal PPD (B = 0.31, p < 0.001). Conclusions This is the first study to investigate the possible correlation between maternal PPD, mother-in-law and daughter-in-law relationship satisfaction, maternal marital satisfaction, paternal marital satisfaction, and paternal PPD. It is important for future PPD interventions to target both maternal and paternal mental health, as well as the mechanisms identified that can lead to PPD.

Funder

Young Medical Talent of Jiangsu Province

Suzhou Key Diagnosis and Treatment Program

Suzhou Key Medical Center for Psychiatric Diseases

Suzhou Municipal Sci-Tech Bureau Program

Health City “531” action plan of Suzhou Municipal and Suzhou Clinical Medicine Expert Team

Publisher

Springer Science and Business Media LLC

Subject

Obstetrics and Gynecology

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