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Objective: To explore the independent and combined effects of smoking and passive smoking during pregnancy on maternal depression, anxiety and depressive anxiety comorbidities., Methods: From August 2020 to February 2022, women who underwent 42-day postpartum examination in Changfeng Women's Center and Shuangfeng Hospital of Hefei were recruited. Their depression and anxiety symptoms were assessed using EPDS Scale and GAD Scale, respectively, and smoking and passive smoking status during pregnancy were collected. Multivariate Logistic regression was used to analyze the independent and combined effects of smoking and passive smoking during pregnancy on postpartum depression, anxiety and depression and anxiety comorbidities., Results: A total of 2 447 parturients were included, whose mean age was(29.23±4.20) years old.58.6% of parturients lived in urban areas.97.2% parturients had unassisted reproduction and 73.5% pregnancy intention was spontaneous. Among them, 362(14.8%) had depression, 523(21.4%) had anxiety, and 270(11.0%) had depression and anxiety comorbidities. In an independent analysis of effects, maternal smoking during pregnancy was statistically associated with postpartum depression(OR=3.86, 95%CI 2.37-6.28), anxiety(OR =2.58, 95%CI 1.60-4.17) and depressive anxiety comorbidity(OR = 3.34, 95%CI 2.00-5.71). Maternal passive smoking during pregnancy was also positively associated with the risk of postpartum depression(OR = 1.56, 95%CI 2.00-5.71), anxiety(OR=1.71, 95%CI 1.24-2.37) and depression and anxiety comorbidities(OR = 1.52, 95%CI 1.02-2.28), and the higher the frequency of exposure to passive smoking, the higher risk of depression, anxiety, and depressive and anxiety comorbidities. No interaction between smoking during pregnancy and passive smoking exposure on postpartum depression(RERI = 0.69, 95%CI-4.62-6.00; AP = 10.84, 95%CI-73.37-95.04; S= 0.58, 95%CI 0.02-15.18), anxiety(RERI=0.27, 95%CI 0.05-0.49; AP=4.02, 95%CI-0.52-8.57; S=0.78, 95%CI 0.64-0.94) and depression and anxiety comorbidities(RERI = 0.07, 95%CI-0.25-0.39; AP=1.74, 95%CI-6.03-9.52; S=0.93, 95%CI 0.68-1.27)was observed., Conclusion: Both smoking and passive smoking during pregnancy were positively associated with the risk of postpartum depression, anxiety and depressive anxiety comorbidity.

Objective: To explore the association between postpartum depression (PPD) and transforming growth factor-β (TGF-β) concentrations in human colostrum., Methods: Participants were recruited from a maternal and infant cohort established in a tertiary general hospital in Guangdong Province between December, 2020 and September, 2021. In the afternoon of the second postpartum day, the women were evaluated with Edinburgh Postnatal Depression Scale (EPDS) for screening PPD (defined as a score of 10 or higher). The women with PPD were matched at a 1:1 ratio with women without PPD with maternal age difference within 5 years and the same mode of delivery. Colostrum samples were collected in morning on the third postpartum day for measurement of TGF-β concentrations using enzyme-linked immunosorbent assay (ELISA), and the association between EPDS scores and TGF-β concentrations was analyzed in the two groups., Results: A total of 90 women were included in the final analysis. The mean concentrations of TGF-β1, TGF-β2 and TGF-β3 in the colostrum were 684.03 (321.22-859.25) pg/mL, 5116.50±1747.04 pg/mL and 147.84±48.68 pg/mL in women with PPD, respectively, as compared with 745.67 (596.00-964.22) pg/mL, 4912.40±1516.80 pg/mL, and 168.21±48.15 pg/mL in women without PPD, respectively. Compared with women without PPD, the women with PPD had significantly lower concentrations of TGF-β1 ( P =0.026) and TGF-β3 ( P =0.049) in the colostrum. Spearman correlation analysis revealed that the EPDS scores were negatively associated with the concentrations of TGF-β1 ( r =-0.23, P =0.03) and TGF-β3 ( r =-0.25, P =0.02) in the colostrum., Conclusion: PPD is associated with decreased concentrations of TGF-β1 and TGF-β3 in human colostrum, suggesting the need of early PPD screening and interventions during pregnancy and the perinatal period to minimize the impact of PPD on human milk compositions.

Objectives: Primary health workers are the first fine to identify postpartum depression, which is important for patients with this disease to get early specialist diagnosis and treatment. The smartphone-based virtual patient is economical, convenient and effective, and has been applied extensively to evaluate the competency to detect postpartum depression, but there is no relevant application in China. This study aims to use virtual patient to assess the current status on the competency of detecting postpartum depression among primary maternal and child health workers in Hunan Province, and to explore potential influencing factors., Methods: A total of 222 primary maternal and child health workers from 3 regions with low, medium, and high economic levels in Hunan Province were enrolled, and smartphone-based virtual patients with postpartum depression were used for the assessment from May to July in 2018, and a self-designed questionnaire was used to investigate their demographic characteristics. The competency to detect postpartum depression was measured by 2 indicators: diagnostic accuracy and treatment accuracy. Descriptive statistical methods were used to describe the competency to detect postpartum depression among them and their demographic characteristics. A logistic regression analysis was used to explore the possible influencing factors for the diagnostic accuracy and treatment accuracy., Results: The diagnostic accuracy rate was 64.0%. There was no significant difference between the demographic characteristics and diagnostic accuracy rate ( P >0.05). The treatment accuracy rate was 50.9%. The workers from the middle economic level area were more likely to make the correct treatment than those from the low economic level area (OR= 3.229, 95% CI 1.478 to 7.014).Apart from postpartum depression, the 3 most frequently diagnosed items were bipolar disorder (22.1%, 49/222), secondary depression disorder (13.5%, 30/222), and neurasthenia (5.4%, 12/222). Among the correctly diagnosed health workers, the proportion for correct treatment was 29.6% (42/142), and there was no significant difference between the diagnostic accuracy and treatment accuracy ( P >0.05)., Conclusions: About half of the primary maternal and child health workers in Hunan Province, China have basic competency to detect postpartum depression, but the overall results are not satisfactory. The regional economic level is correlated with the competency of detecting postpartum depression, and the competency of detecting postpartum depression is stronger in more developed areas. Moreover, for the patients who have been identified as postpartum depression, the rate of correct treatment is low, which warrants particular attention in the follow-up training.

Objectives: To explore the application of random forest algorithm in screening the risk factors and predictive values for postpartum depression., Methods: We recruited the participants from a tertiary hospital between June 2017 and June 2018 in Changsha City, and followed up from pregnancy up to 4-6 weeks postpartum.Demographic economics, psychosocial, biological, obstetric, and other factors were assessed at first trimesters with self-designed obstetric information questionnaire and the Chinese version of Edinburgh Postnatal Depression Scale (EPDS). During 4-6 weeks after delivery, the Chinese version of EPDS was used to score depression and self-designed questionnaire to collect data of delivery and postpartum. The data of subjects were randomly divided into the training data set and the verification data set according to the ratio of 3꞉1. The training data set was used to establish the random forest model of postpartum depression, and the verification data set was used to verify the predictive effects via the accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and AUC index., Results: A total of 406 participants were in final analysis. Among them, 150 of whom had EPDS score ≥9, and the incidence of postpartum depression was 36.9%. The predictive effects of random forest model in the verification data set were at accuracy of 80.10%, sensitivity of 61.40%, specificity of 89.10%, positive predictive value of 73.00%, negative predictive value of 82.80%, and AUC index of 0.833. The top 10 predictive influential factors that screening by the variable importance measure in random forest model was antenatal depression, economic worries after delivery, work worries after delivery, free triiodothyronine in first trimesters, high-density lipoprotein in third trimester, venting temper to infants, total serum cholesterol and serum triglyceride in first trimester, hematocrit and serum triglyceride in third trimester., Conclusions: Random forest has a great advantage in risk prediction for postpartum depression. Through comprehensive evaluation mechanism, it can identify the important influential factors for postpartum depression from complex multi-factors and conduct quantitative analysis, which is of great significance to identify the key factors for postpartum depression and carry out timely and effective intervention.

Objective: To investigate the association of genetic polymorphisms of norepinephrine metabolizing enzymes with postpartum depression and analyze the risk factors for postpartum depression in women following cesarean section., Methods: A total of 591 Chinese woman of Han Nationality undergoing caesarean section were enrolled in this study. The diagnosis of postpartum depression was established for an Edinburgh Postnatal Depression Scale (EPDS) score ≥9. For all the women without antepartum depression, the genotypes of catechol-O-methyltransferase (COMT; at 5 sites including rs2020917 and rs737865) and monoamine oxidase A (rs6323) were determined using Sequenom ? Mass Array single nucleotide polymorphism (SNP) analysis. We analyzed the contribution of the genetic factors (SNPs, linkage disequilibrium and haplotype) to postpartum depression and performed logistic regression analysis to identify all the potential risk factors for postpartum depression and define the interactions between the genetic and environmental factors., Results: The incidence of postpartum depression was 18.1% in this cohort. Univariate analysis suggested that COMT polymorphism at rs2020917 (TT genotype) and rs737865 (GG genotype) were significantly correlated with the occurrence of postpartum depression ( P < 0.05). Logistic regression analysis showed that COMT polymorphism at rs2020917 (TT genotype) and rs737865 (GG genotype), severe stress during pregnancy, and domestic violence were the risk factors for postpartum depression ( P < 0.05); no obvious interaction was found between the genetic polymorphisms and the environmental factors in the occurrence of postpartum depression., Conclusions: The rs2020917TT and rs737865GG genotypes of COMT, stress in pregnancy, and domestic violence are the risk factors for postpartum depression.

Postpartum depression (PPD) affects the health of women and is an important issue that impacts negatively on the happiness of affected families. Previous studies have demonstrated that PPD impairs the mother-child attachment, impacts the marital relationship, and may cause family dysfunction. Although PPD is a common phenomenon, the concept of PPD is easily confused with other similar concepts such as postpartum blues and postpartum psychosis, which may delay proper prevention and management. This paper identifies the definitions, characteristics, antecedents, and consequences of PPD as well as provides empirical screen measurements and examples of model, borderline, and contrary cases in order to differentiate between the concepts of PPD and other disorders using Walker and Avant's (2011) concept analysis methodology. Three defining characteristics of postpartum depression were identified. First, depression begins four to six weeks after delivery and continues for at least two weeks. Second, we benchmarked over 5 depressive symptoms. Third, postpartum depression may disrupt puerperal women's lives by making it difficult for them to care for their babies and to concentrate on daily tasks. We hope that this article enhances nurses' professional competences to detect PPD as early as possible and to promote the quality of care received by postpartum women and their family members.

Postpartum psychological health is an important issue in postpartum care. This article introduces postpartum depression and describes its assessment, treatment, and nursing care. Postpartum depression is a non-psychotic depression that often commences 4 to 6 weeks after childbirth. Postpartum depression requires the diagnosis of at least 5 depressive symptoms that last for a period of at least 2 weeks. Postpartum depression may occur within the first-year postpartum and, if not treated in a timely and appropriate manner, may adversely affect the health of the new mother, the child, and the family. Health professionals in regular contact with women during the perinatal period are encouraged to screen at-risk patients for postpartum depression and to assist postpartum-depressed patients adhere to prescribed treatment regimens to promote the health of the new family.

Objective: To study the related factors of postpartum depression (PPD) and the effects of intervening measures to PPD incidence., Methods: 1 597 pregnant women selected from our antenatal care clinic were investigated by using the hospital anxiety and depression questionnaire (HAD) during pregnancy and the Edinburgh postpartum depression scale (EPDS) after childbirth. All the enrolled women were randomly divided into control group and intervening group by the proportion of 1 to 2. Six intervening measures were used in the latter group., Results: (1) There were 49 women whose HAD >or= 11 score (anxiety-depression mood) with 28 cases (57.1%) had got postpartum depression in the control group. In the intervening group, however, there were 94 women whose HAD >or= 11 score with 24 cases (25.5%) had got postpartum depression. There is a significant difference between the two groups (P < 0.01). (2) There were 71 (13.0%) women whose EPDS >or= 13 score (postpartum depression) in the control group. In the intervening group, however, there were 63 (6.0%) women whose EPDS >or= 13 score. There had a significant difference between the two groups (P < 0.01). (3) PPD women had higher N and P scores than those of non-PPD women (P < 0.01)., Conclusion: (1) Prenatal anxiety, depression, negative personality and postpartum psychological and physiological changes were high risk factors to PPD. (2) Psychological personality play an important role in PPD. (3) Incidence of PPD was significantly reduced by social support.