Liao Yujia,Chen Siyu,Deng Xiangyu,Gan Yanqiong,Han Shulei,Tan Xinlin,Huang Yue,Construction and validation of a simple model for predicting the risk of prenatal depression[J].SICHUAN MENTAL HEALTH,2023,36(5):466-472
Construction and validation of a simple model for predicting the risk of prenatal depression
DOI:10.11886/scjsws20230303001
English keywords:Prenatal depression  Risk factor  Prediction model
Fund projects:南充市社会科学研究“十四五”规划2021年度项目(项目名称:南充市育龄妇女产前抑郁规范化管理策略研究,项目编号:NC21B165)
Author NameAffiliationPostcode
Liao Yujia Nanchong Psychosomatic Hospital Nanchong 637770 China 637770
Chen Siyu* Nanchong Psychosomatic Hospital Nanchong 637770 China 637770
Deng Xiangyu China West Normal University Nanchong 637001 China 637001
Gan Yanqiong Affiliated Hospital of North Sichuan Medical College Nanchong 637002 China 637002
Han Shulei Beijing Renxin Changhe Medical Technology Co. LTD Beijing 102600 China 102600
Tan Xinlin Affiliated Hospital of North Sichuan Medical College Nanchong 637002 China 637002
Huang Yue Affiliated Hospital of North Sichuan Medical College Nanchong 637002 China 637002
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English abstract:
      Background Mental illness during pregnancy has become a major public health problem in China over the recent years, and depression is the most common psychological symptom during pregnancy. Current research efforts are directed towards the therapy on prenatal depression, whereas the construction of prediction model for prenatal depression risk has been little studied.Objective To construct a simple model for predicting the risk of prenatal depression, thus providing a valuable reference for the prevention of maternal depression during pregnancy.Methods A total of 803 pregnant women attending three hospitals in Nanchong city were consecutively recruited from May 2021 to February 2022. A self-administered questionnaire was developed for the assessment of social demographic variables, obstetrical and general medical indexes and psychological status of all participants, and Self-rating Depression Scale (SDS) was utilized to screen for the presence of maternal depression. Subjects were randomly assigned into modelling group (n=635) and validation group (n=168) at the ratio of 8∶2 under simple random sampling with replacement. The candidate risk factors of maternal depression during pregnancy were screened using binary Logistic regression analysis, and the predictive model was constructed. Then the performance of the predictive model was validated using receiver operating characteristics (ROC) curve.Results ① Lack of companionship (β=-0.692, OR=0.501, 95% CI: 0.289~0.868), low mood during the last menstrual period (β=-1.510, OR=0.221, 95% CI: 0.074~0.656), emotional stress during the last menstrual period (β=-1.082, OR=0.339, 95% CI: 0.135~0.853), unsatisfactory relationship between mother-in-law and daughter-in-law (β=-1.228, OR=0.293, 95% CI: 0.141~0.609), and indifferent generally relationship between mother-in-law and daughter-in-law (β=-0.831, OR=0.436, 95% CI: 0.260~0.730) were risk factors for prenatal depression in pregnant women (P<0.05 or 0.01). ② Model for predicting the prenatal depression risk yielded an area under curve (AUC) of 0.698 (95% CI 0.646~0.749), the maximum Youden index was 0.357 in modelling group with the sensitivity and specificity was 0.606 and 0.751, and an AUC of 0.672 (95% CI: 0.576~0.767) and maximum Youden index of 0.263 in validation group with the sensitivity and specificity of 0.556 and 0.707.Conclusion The simple model constructed in this study has good discriminant validity in predicting of the risk of prenatal depression. [Funded by Nanchong Social Science Research Project of the 14th Five-Year Plan (number, NC21B165)]
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