| 摘要: |
| 目的 调查影响产后抑郁症（PPD）的社会心理因素，探究其对PPD的预测价值，构建并评价PPD的预测模型。方法 随机选取2014年9月-2016年6月在重庆医科大学附属第一医院、金山医院、大学城医院进行产前检查、孕周≥28周、拟在该院住院分娩的371例孕妇，采用社会人口学调查表（自定义）、艾森克人格问卷（EPQ）、90项症状自评量表（SCL-90）、汉密尔顿焦虑/抑郁量表（HAMA14/HAMD24）、贝克焦虑/抑郁量表（BAI/BDI）对所有孕妇进行产前社会心理因素调查；并在产后的第42天追踪随访完成爱丁堡产后抑郁量表（EPDS），同时进行PPD的评估诊断。分析预测影响PPD的社会心理因素，并采用多因素逐步logistic回归构建预测模型，运用ROC曲线评价该模型的预测价值。结果 根据PPD的评估结果，371例产妇中60例（PPD组）符合PPD的诊断标准，311例不符合（N-PPD组）；PPD的发生率为16.17%（60/371）。单因素分析两组孕妇产前社会心理因素，结果显示工作稳定与否、文化程度、情绪稳定性、HAMA14得分、HAMD24得分、BAI得分、BDI得分、SCL-90各单因子（除躯体化）得分的差异均有统计学意义（P<0.05），对上述指标进行多因素逐步logistic回归，建立了如下数学模型：Logit（PI）=0.042×total score of SCL-90+1.005×fixed work or not+2.498×relative company+0.108×BDI score-1.319×education-8.028。该模型的ROC曲线下面积为0.833（P<0.001，95%CI：0.772~0.894）。当以PI=0.141为界点时，约登指数最大，灵敏度为0.900，特异度为0.533。结论 SCL-90总分、产妇有无固定工作、家属陪伴情况、BDI得分是PPD的独立危险因素，文化程度低是PPD的保护因素；本研究建立的基于社会心理因素的PPD预测模型有较高的预测价值，值得进一步研究。 |
| 关键词: 产后抑郁症 发病率 社会因素 心理因素 预测模型 |
| DOI：10.16781/j.0258-879x.2017.04.0476 |
| 投稿时间：2016-12-15修订日期：2017-03-14 |
| 基金项目:重庆市渝中区科技计划项目（20120217）. |
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| Prediction model for postpartum depression based on social psychological factors: establishment and evaluation |
| CAI Fei-ya1,KUANG Li1*,WANG Wo1,LI Da-qi1,CAO Jun2,HUI Xiao1 |
(1. Department of Psychiatry, University-Town Hospital Affiliated to Chongqing Medical University, Chongqing 401331, China;
2. Department of Psychiatry, the First Hospital Affiliated to Chongqing Medical University, Chongqing 400016, China
*Corresponding author) |
| Abstract: |
| Objective To investigate the social psychological factors influencing postpartum depression (PPD), and to explore its predictive value for PPD, so as to establish and evaluate the prediction model of PPD. Methods We randomly selected 371 pregnant women (pregnancy≥28 weeks), who received antenatal examination and would be hospitalized for delivery in the First Hospital, Jinshan Hospital, and University-Town Hospital Affiliated to Chongqing Medical University from Sep. 2014 to Jun. 2016. The social demographic questionnaire (self-define), the Eysenck Personality Questionnaire (EPQ), the Symptom Checklist-90 (SCL-90), the Hamilton Anxiety Scale/Hamilton Depression Rating Scale (HAMA14/HAMD24), and the Beck Anxiety Inventory/Beck Depression Inventory (BAI/BDI) were used to assess the prenatal social psychological factors of pregnant women, and the Edinburgh postnatal depression scale (EPDS) was completed on the 42nd day after delivery. Then the evaluation of PPD was conducted to analyze and predict the social psychological factors influencing PPD. Multivariate stepwise logistic regression analysis was used to establish the prediction model, and receiver operating characteristic (ROC) curve was used to evaluate the predictive value of the model. Results Sixty of the 371 cases met the diagnostic criteria of PPD (PPD group) according to the assessment results of PPD, while 311 cases did not meet (N-PPD group); the incidence of PPD was 16.17% (60/371). Univariate analysis results showed that there were significant differences in having a fixed work or not, the degree of education, emotional stability, HAMA14 score, HAMD24 score, BAI score, BDI score, and each single factor score (except somatization) of the SCL-90 between the two groups (all P<0.05). The above indexes were selected for multivariate logistic regression analysis, and the following mathematical prediction model was established: Logit (PI)=0.042×total score of SCL-90+1.005×having a fixed work or not+2.498×relative company+0.108×BDI score-1.319×the degree of education-8.028, with the area under the ROC curve being 0.833 (P<0.001, 95%CI: 0.772-0.894). When PI=0.141 was selected as cut-off point, the Youden index of the model was maximum, the sensitivity was 0.900 and the specificity was 0.533. Conclusion The total score of SCL-90, having a fixed work or not, family company and BDI score are independent risk factors of PPD, while low degree of education is an independent protective factor. The prediction model for PPD based on social psychological factors has been successfully established, which has a great predictive value and is worthy of further study. |
| Key words: postpartum depression incidence social factors psychological factors predictive model |
