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Influential factors for postpartum depression based on the structural equation model in Kaifu District in Changsha / 中南大学学报(医学版)
Journal of Central South University(Medical Sciences) ; (12): 1191-1197, 2017.
Article in Chinese | WPRIM | ID: wpr-669232
ABSTRACT

Objective:

To investigate the current status of the postpartum depression in Kaifu District in Changsha,and to explore the influential factors for postpartum depression.

Methods:

We selected the mothers,who had a delivery and met the inclusion criteria in Changsha during 2015,as the participants and established a prospective birth cohort study.The social demographic characteristics and health-related information for the mothers and their families were collected by using self-made questionnaire.The mothers' depression symptoms after one month postpartum were assessed by the Edinburgh Postnatal Depression Scale.We used the structural equation model to analyze the influential factors for postpartum depression.

Results:

A total of 961 cases were investigated.82 of them whose scores of EPDS were ≥ 9 points,and the incidence of PPD was 8.2%.The results of structural equation model revealed the influential factors and their correlations with postpartum depression.It has been shown that maternal age,maternal education level,per capita income of family,intention of pregnancy,pregnancy-related complications,mode of conception,mode of delivery,feeding patterns,birth weight,baby gender,and infant illness could exert effects on postpartum depression.

Conclusion:

The incidence of postpartum depression in Kaifu District is at a low level and the structural equation model can be applied to analyze the influential factors and their relations with postpartum depression.

Full text: Available Index: WPRIM (Western Pacific) Type of study: Observational study / Prognostic study Language: Chinese Journal: Journal of Central South University(Medical Sciences) Year: 2017 Type: Article

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Full text: Available Index: WPRIM (Western Pacific) Type of study: Observational study / Prognostic study Language: Chinese Journal: Journal of Central South University(Medical Sciences) Year: 2017 Type: Article