Retrospective Study
Copyright ©The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Psychiatry. Dec 19, 2023; 13(12): 1079-1086
Published online Dec 19, 2023. doi: 10.5498/wjp.v13.i12.1079
Analysis of influencing factors and the construction of predictive models for postpartum depression in older pregnant women
Lei Chen, Yun Shi
Lei Chen, Yun Shi, Department of Obstetrics, Suzhou Ninth People's Hospital, Suzhou 215200, Jiangsu Province, China
Author contributions: Chen L and Shi Y onceived and designed the study; Shi Y guided the study; Chen L collected the clinical date; Chen L and Shi Y analyzed the data; all authors drafted and revised the manuscript.
Institutional review board statement: This study was reviewed and approved by the Ethics Committee of Suzhou Ninth People's Hospital.
Informed consent statement: All study participants or their legal guardian provided informed written consent about personal and medical data collection prior to study enrolment.
Conflict-of-interest statement: We have no financial relationships to disclose.
Data sharing statement: No additional data are available.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Yun Shi, MM, Associate Chief Physician, Department of Obstetrics, Suzhou Ninth People's Hospital, No. 2666 Ludang Road, Taihu New Town, Wujiang District, Suzhou 215200, Jiangsu Province, China. shiy202381@163.com
Received: October 8, 2023
Peer-review started: October 8, 2023
First decision: October 24, 2023
Revised: November 2, 2023
Accepted: November 9, 2023
Article in press: November 9, 2023
Published online: December 19, 2023
Processing time: 72 Days and 9.5 Hours
Abstract
BACKGROUND

Changes in China's fertility policy have led to a significant increase in older pregnant women. At present, there is a lack of analysis of influencing factors and research on predictive models for postpartum depression (PPD) in older pregnant women.

AIM

To analysis the influencing factors and the construction of predictive models for PPD in older pregnant women.

METHODS

By adopting a cross-sectional survey research design, 239 older pregnant women (≥ 35 years old) who underwent obstetric examinations and gave birth at Suzhou Ninth People's Hospital from February 2022 to July 2023 were selected as the research subjects. When postpartum women of advanced maternal age came to the hospital for follow-up 42 d after birth, the Edinburgh PPD Scale (EPDS) was used to assess the presence of PPD symptoms. The women were divided into a PPD group and a no-PPD group. Two sets of data were collected for analysis, and a prediction model was constructed. The performance of the predictive model was evaluated using receiver operating characteristic (ROC) analysis and the Hosmer-Lemeshow goodness-of-fit test.

RESULTS

On the 42nd day after delivery, 51 of 239 older pregnant women were evaluated with the EPDS scale and found to have depressive symptoms. The incidence rate was 21.34% (51/239). There were statistically significant differences between the PPD group and the no-PPD group in terms of education level (P = 0.004), family relationships (P = 0.001), pregnancy complications (P = 0.019), and mother–infant separation after birth (P = 0.002). Multivariate logistic regression analysis showed that a high school education and below, poor family relationships, pregnancy complications, and the separation of the mother and baby after birth were influencing factors for PPD in older pregnant women (P < 0.05). Based on the influencing factors, the following model equation was developed: Logit (P) = 0.729 × education level + 0.942 × family relationship + 1.137 × pregnancy complications + 1.285 × separation of the mother and infant after birth -6.671. The area under the ROC curve of this prediction model was 0.873 (95%CI: 0.821-0.924), the sensitivity was 0.871, and the specificity was 0.815. The deviation between the value predicted by the model and the actual value through the Hosmer-Lemeshow goodness-of-fit test was not statistically significant (χ2 = 2.749, P = 0.638), indicating that the model did not show an overfitting phenomenon.

CONCLUSION

The risk of PPD among older pregnant women is influenced by educational level, family relationships, pregnancy complications, and the separation of the mother and baby after birth. A prediction model based on these factors can effectively predict the risk of PPD in older pregnant women.

Keywords: Older pregnant women; Postpartum depression; Influencing factors; Prediction model

Core Tip: Older pregnant women are more likely to develop postpartum depression (PPD) than younger pregnant women. PPD can harm the physical and mental health of pregnant women, offspring development, and family and social harmony. Here, we investigated the PPD status of 239 older pregnant women. Based on whether the older pregnant women experienced depression 42 d postpartum, we divided them into a PPD group and a no-PPD group. By conducting statistical analysis on two sets of data and constructing a prediction model, we examined the issue of how medical personnel can effectively assess the PPD risk of older pregnant women.