“二胎”产妇产后抑郁影响因素及列线图预测模型构建

The influencing factors of postpartum depression in “second-child” women and the prediction model of line chart are constructed

目的 探讨影响“二胎”产妇产后抑郁的危险因素,构建预测产后抑郁的列线图模型,并评估模型的区分度和一致性。方法 选取2017年1月至2020年6月上海市第一人民医院医学心理科门诊收治的“二胎”产妇606例作为研究对象。并根据爱丁堡抑郁量表(EPDS)评估产后抑郁情绪,分为抑郁组109例和正常组497例。收集临床资料,采用单因素及多因素Logistic回归分析筛选影响“二胎”产妇产后抑郁的影响因素,构建列线图预测模型,采用ROC曲线、校准曲线验证模型的一致性及区分度。结果 “二胎”产妇产后抑郁发生率为17.99%(109/606)。抑郁组患者年龄≥35岁、高危妊娠、无职业、睡眠不好、产前焦虑、产前抑郁、没有陪伴分娩、婴儿出现健康问题、居住情况一般、家庭月收入(2000~8000元)、与公婆关系不好、产褥期照顾(婆家人为主)、婴儿性别不满意、一孩年龄<6岁、一孩对二孩的态度不是非常喜欢比例均明显高于正常组,支持利用度、客观支持、社会支持水平明显低于正常组(P<0.05)。多因素Logistic回归分析结果显示,年龄≥35岁、无职业、睡眠不好、产前抑郁、婴儿出现健康问题、与公婆关系差、婆家人照顾产褥期是影响“二胎”产妇产后抑郁的危险因素,一孩年龄≥6岁、社会支持水平、月子中心照顾产褥期是影响“二胎”产妇产后抑郁的保护因素(P<0.05)。构建的列线图预测模型具有较好的区分度(ROC曲线下面积为0.882,95%CI=0.841~0.924)和一致性(Hosmer-Lemeshow拟合优度检验χ^(2)=7.450,P=0.489)。结论 本研究构建的预测“二胎”产妇产后抑郁发生风险的列线图模型,具有较好的区分度和一致性。

Objective To explore the risk factors of postpartum depression in “second child” mothers, to construct a nomogram model for predicting postpartum depression, and to evaluate the discrimination and consistency of the model. Methods From January 2017 to June 2020, 606 “second-child” mothers who were admitted to the outpatient department of medical psychology of Shanghai General Hospital were gathered as the research objects. Postpartum depression was assessed according to the Edinburgh postnatal depression scale(EPDS), and they were grouped into a depression group of 109 cases and a normal group of 497 cases. The clinical data were collected, univariate and multivariate Logistic regression analyses were performed to screen the influencing factors of postpartum depression in “second child” mothers, a nomogram prediction model was built, and ROC curve and calibration curve were performed to verify the consistency and discrimination of the model. Results The incidence rate of postpartum depression among “second child” mothers was 17.99%(109/606). The proportions of age ≥35 years, high-risk pregnancy, no occupation, poor sleep, prenatal anxiety, prenatal depression, unaccompanied delivery, infant health problems, general living conditions, family monthly income of(2000-8000 yuan), poor relationship with in-laws, puerperium care of(mainly in-laws), dissatisfaction with baby gender, first child <6 years old, first child who did not like the second child very much in the depression group were higher than those in the normal group, while the levels of support utilization, objective support and social support were significantly lower than those in the normal group(P<0.05). The results of multivariate Logistic regression analysis showed that age ≥35 years old, no occupation, poor sleep, prenatal depression, infant health problems, poor relationship with in-laws, and in-law’s care during puerperium were the risk factors for postpartum depression in “second child” mothers, the first child ≥6 years old, the level of social support, and confinement center care during the puerperium were the protective factors affecting the postpartum depression of the “second child” mothers(P<0.05). The constructed nomogram prediction model had good discrimination(area under the ROC curve was 0.882, 95%CI=0.841-0.924) and consistency(Hosmer-Lemeshow goodness of fit test χ^(2) =7.450, P=0.489). Conclusion The nomogram model constructed in this study to predict the risk of postpartum depression in “second-child” mothers has good discrimination and consistency.