Profiles and characteristics of clinical subtypes of perinatal depressive symptoms: A latent class analysis

Trajectories of sleep quality and depressive symptoms in women from pregnancy to 3 months postpartum: a prospective cohort study

Sleep quality and depression during pregnancy often affect women's adaptation to motherhood and are linked with adverse maternal and neonatal outcomes. Using a prospective cohort study comprising 190 pregnant women in central Taiwan, we investigated the trajectories of sleep quality and depressive symptoms and their associated predictors in perinatal women from pregnancy to postpartum. Sleep and depressive symptoms were assessed using the Pittsburgh Sleep Quality Index and the Edinburgh Postnatal Depression Scale, respectively, from mid-pregnancy to 3 months postpartum. We used group-based trajectory modelling and logistic regression modelling to analyse the data collected from the structured questionnaires. Pregnant women (50.5% primipara) with a mean (standard deviation) age of 32.3 (4.1) years were included. We identified three distinctive classes of sleep quality trajectories during the perinatal period: 'stable good' (18.4%), 'increasing poor' (48.9%), and 'stable poor' (32.6%). We further detected three stable trajectories of depressive symptoms: 'stable low' (36.3%), 'stable mild' (42.1%), and 'stable high' (21.6%). A significant association between sleep quality and depression trajectories was evident (p < 0.001). High fatigue symptoms and low social support predicted the high trajectories of poor sleep and depressive symptoms. Distinctive dynamic sleep quality and stable depression trajectories were characterised. Our findings revealed that both the sleep and depression trajectories were closely associated with one another, with common predictors of fatigue symptoms and social support. The early assessment of maternal sleep and depression status is important for identifying at-risk women and initiating interventions tailored to perinatal women to improve their sleep and mental health.

Exploring Heterogeneity in perinatal depression: a comprehensive review

Perinatal depression (PND) is a significant contributor to maternal morbidity globally. Recognized as a major cause of poor infant development, epidemiological and interventional research on it has increased over the last decade. Recently, studies have pointed out that PND is a heterogeneous condition, with variability in its phenotypes, rather than a homogenous latent entity and a concrete diagnosis, as previously conceptualized in psychometric literature and diagnostic systems. Therefore, it is pertinent that researchers recognize this to progress in elucidating its aetiology and developing efficacious interventions.This systematic review is conducted in accordance with the Meta-analysis of observational studies in epidemiology (MOOSE). It aims to provide an updated and comprehensive account of research on heterogeneity in phenotypes of PND and its implications in research, public health, and clinical practice. It provides a synthesis and quality assessment of studies reporting heterogeneity in PND using cutting-edge statistical techniques and machine learning algorithms. After reporting the phenotypes of PND, based on heterogeneous trajectories and symptom profiles, it also elucidates the risk factors associated with severe forms of PND, followed by robust evidence for adverse child outcomes. Furthermore, recommendations are made to improve public health and clinical practice in screening, diagnosis, and treatment of PND.

Increased risk of postpartum depression in women with lactational mastitis: a cross-sectional study

Background

A high incidence of lactational mastitis mainly occurs during the first month of breastfeeding. It may cause severe pain, frustration, fatigue, stress, and breastfeeding concerns. However, few studies investigated the effects of lactational mastitis on postpartum depression. This study investigated the potential association between lactational mastitis and postpartum depression.

Methods

We examined the associations of lactational mastitis with postpartum depression in 1,551 Chinese women. Lactational mastitis was diagnosed by breast specialists. The presence of depression symptoms was evaluated by the Edinburgh Postnatal Depression Scale (EPDS) and Patient Health Questionnaire 9 (PHQ9) at 6 weeks after delivery. Multiple linear regression analysis and multivariable log-binomial regression analysis were performed to estimate the association between lactational mastitis and postpartum depression.

Results

Among the 1,551 mothers, 147 (9.5%) experienced lactational mastitis diagnosed by breast specialists during the postpartum period. Compared with women without lactational mastitis, the proportion of women with depression symptoms was significantly higher (38.1% vs. 27.4%, p = 0.008), and the risk of postpartum depression increased by 68% (RR = 1.68, 95% CI, 1.18, 2.40) in women who had experienced lactational mastitis. In addition, the risk of self-harm or suicidal ideation increased by 89% (RR = 1.89, 95% CI, 1.08, 3.29) in women who experienced lactational mastitis. In stratified analysis, the associations of lactational mastitis with postpartum depression appeared stronger among women aged ≥35 years, with maternal comorbidities, and who delivered a female neonate.

Conclusion

The study results suggest that lactational mastitis is a risk factor for depression during the postpartum period. The impact of lactational mastitis on maternal mental health requires further attention.

Clinical trial registration

chictr.org.cn, ChiCTR2000041519.

Detection of differential depressive symptom patterns in a cohort of perinatal women: an exploratory factor analysis using a robust statistics approach

BACKGROUND

Postpartum depression can take many forms. Different symptom patterns could have divergent implications for how we screen, diagnose, and treat postpartum depression. We sought to utilise a recently developed robust estimation algorithm to automatically identify differential patterns in depressive symptoms and subsequently characterise the individuals who exhibit different patterns.

METHODS

Depressive symptom data (N = 548) were collected from women with neuropsychiatric illnesses at two U.S. urban sites participating in a longitudinal observational study of stress across the perinatal period. Data were collected from Emory University between 1994 and 2012 and from the University of Arkansas for Medical Sciences between 2012 and 2017. We conducted an exploratory factor analysis of Beck Depression Inventory (BDI) items using a robust expectation-maximization algorithm, rather than a conventional expectation-maximization algorithm. This recently developed method enabled automatic detection of differential symptom patterns. We described differences in symptom patterns and conducted unadjusted and adjusted analyses of associations of symptom patterns with demographics and psychiatric histories.

FINDINGS

53 (9.7%) participants were identified by the algorithm as having a different pattern of reported symptoms compared to other participants. This group had more severe symptoms across all items-especially items related to thoughts of self-harm and self-judgement-and differed in how their symptoms related to underlying psychological constructs. History of social anxiety disorder (OR: 4.0; 95% CI [1.9, 8.1]) and history of childhood trauma (for each 5-point increase, OR: 1.2; 95% CI [1.1, 1.3]) were significantly associated with this differential pattern after adjustment for other covariates.

INTERPRETATION

Social anxiety disorder and childhood trauma are associated with differential patterns of severe postpartum depressive symptoms, which might warrant tailored strategies for screening, diagnosis, and treatment to address these comorbid conditions.

FUNDING

There are no funding sources to declare.

Factors associated with the mental health status of pregnant women in China: A latent class analysis

Background

Prenatal mental health is a neglected public health issue that places pregnant women at a higher risk for mental disorders. The purpose of this study was to investigate the influencing factors of prenatal mental disorders and provide a scientific basis to guide and promote the mental health of pregnant women.

Methods

The study sample comprised 973 women in their first pregnancy, who were in their second trimester and third trimester, who underwent obstetric outpatient checkups at the Maternal and Child Health Hospital in Huai'an, who were recruited in the survey that was conducted from July to December 2017. The Chinese mental health scale (CMHS) was used to assess the mental health of pregnant women. The present study uses the chi-square test to compare the rates of class with different demographic variables, a latent class analysis to identify psychological symptoms, and multiple logistic regression analysis to examine whether the demographics predicted class membership.

Results

The chi-square test results showed that participants who reported feeling different in the perinatal period (χ² = 6.35, P = 0.04), having marital satisfaction (χ² = 15.8, P < 0.001), with an in-law relationship (χ² = 29.43, P < 0.001), with a friend relationship (χ² = 24.81, P < 0.001), with basic diseases (χ² = 8.04, P = 0.02), and taking birth control pills (χ² = 8.97, P = 0.01) have different probabilities of being classified. Three latent classes were identified: the high symptoms group (6.89%), the moderate symptoms group (20.56%), and the low symptoms group (72.56%). Pregnant women in the third trimester [odds ratio (OR) = 1.83, 95% confidence interval (CI): 1.04-3.25, P = 0.04], with a poor in-law relationship (OR = 2.82, 95% CI:1.45-5.51, P = 0.002), with a bad friend relationship (OR = 3.17, 95% CI: 1.31-7.71, P = 0.01), and who had basic diseases (OR = 1.70, 95% CI: 1.00-2.90, P = 0.04) tended to be classified under the high symptoms group than under the low symptoms group. Pregnant women with a bad friend relationship (OR = 2.15, 95% CI: 1.08-4.28, P = 0.03) and taking birth control pills (OR = 1.51, 95% CI: 1.08-2.11, P = 0.02) were more likely to be placed under the moderate symptoms group than under the low symptoms group.

Conclusions

A pregnant woman's mental health status factors include feeling different in the perinatal period, those with marital satisfaction, those with an in-law relationship, those with a friend relationship, those with basic diseases, and those taking birth control pills. To ensure a smooth progress of pregnancy and promote the physical and mental health of pregnant women, psychological screening and psychological intervention measures should be strengthened.

Profiles of women with postpartum depressive symptoms: A latent profile analysis using the Edinburgh Postnatal Depression Scale factors

OBJECTIVES

To examine the multidimensionality of symptoms assessed with the Edinburgh Postnatal Depression Scale (EPDS) and to identify and characterize the profiles of women with Postpartum Depression (PPD) symptoms.

METHODS

A sample of 487 Portuguese postpartum women with clinically relevant depressive symptoms participated in this cross-sectional online study. Confirmatory factor analysis was conducted to analyze the factor structure of the EPDS. A latent profile analysis based on the EPDS factors was conducted. Differences in sociodemographic characteristics and risk factors between profiles were explored.

RESULTS

Three EPDS factors were confirmed: depression, anxiety, and anhedonia. Based on these dimensions, three profiles with different symptom severities were found: mild anxious-depressive symptoms; severe PPD symptoms; and moderate anxious-depressive symptoms.

CONCLUSION

Identifying profiles of women with PPD symptoms according to the EPDS factors allows to understand the distinct paths of development of PPD and can inform the development of tailored interventions.

Distinct trajectories of perinatal depression in Chinese women: application of latent growth mixture modelling

BACKGROUND

Current research on perinatal depression rarely pays attention to the continuity and volatility of depression symptoms over time, which is very important for the early prediction and prognostic evaluation of perinatal depression. This study investigated the trajectories of perinatal depression symptoms and aimed to explore the factors related to these trajectories.

METHODS

The study recruited 550 women during late pregnancy (32 ± 4 weeks of gestation) and followed them up 1 and 6 weeks postpartum. Depressive symptoms were measured using the Edinburgh Postnatal Depression Scale (EPDS). Latent growth mixture modelling (LGMM) was used to identify trajectories of depressive symptoms during pregnancy.

RESULTS

Two trajectories of perinatal depressive symptoms were identified: "decreasing" (n = 524, 95.3%) and "increasing" (n = 26, 4.7%). History of smoking, alcohol use and gestational hypertension increased the chance of belonging to the increasing trajectories, and a high level of social support was a protective factor for maintaining a decreasing trajectory.

CONCLUSIONS

This study identified two trajectories of perinatal depression and the factors associated with each trajectory. Paying attention to these factors and providing necessary psychological support services during pregnancy would effectively reduce the incidence of perinatal depression and improve patient prognosis.

Symptom profiles of women at risk of mood disorders: A latent class analysis

BACKGROUND

Depression is the leading cause of disease burden among women worldwide. However, an understanding of symptom profiles among women at risk of mood disorders is limited. We determined distinct profiles of affective symptoms among high risk women, along with their distinguishing characteristics.

METHODS

Women were recruited from 17 clinical sites affiliated with the National Network of Depression Centers. They completed measures of depression (Patient Health Questionnaire - 9) and anxiety (Generalized Anxiety Disorder - 7) as well as questions regarding demographics, reproductive status, behavioral/mental health history, and life stress/adversity. Latent class analysis and multinomial logistic regression were used to identify and characterize symptom profiles.

RESULTS

5792 women participated, ages 18 to 90 (M = 38). Three latent classes were identified: generally asymptomatic (48%), elevated symptoms of comorbid anxiety and depression (16%), and somatic symptoms (36%). Financial security and greater social support were protective factors that distinguished asymptomatic women. The profile of the class with elevated anxiety/depressive symptoms constituted a complex mix of adverse social determinants and potentially heritable clinical features, including a diagnosis of Bipolar Disorder. Women in the 3rd latent class were characterized by menstrual irregularity and a stronger expression of neurovegetative symptoms, especially sleep disturbance and fatigue.

LIMITATIONS

Limitations included less than optimal racial diversity of our sample and reliance on self-report.

CONCLUSIONS

Different symptom profiles may reflect distinct subtypes of women at risk of mood disorders. Understanding the etiology and mechanisms underlying clinical and psychosocial features of these profiles can inform more precisely targeted interventions to address women's diverse needs.

Work-related potential traumatic events and job burnout among operating room nurses: Independent effect, cumulative risk, and latent class approaches

AIMS

The objective of this study is to explore and compare the strength of associations between work-related potential traumatic events and burnout among operating room nurses based on three different approaches.

DESIGN

The study followed a multisite cross-sectional design.

METHODS

A stratified sampling method was conducted. Cities in the Shandong Province were divided into four groups, and two tertiary hospitals were randomly selected from all tertiary hospitals in cities of each group. A total of 361 eligible operating room nurses provided valid questionnaires between June and November 2019. Work-related potential traumatic events questionnaire and the Chinese version of the Maslach Burnout Inventory were conducted. Associations between individual, cumulative potential traumatic events, as well as latent class analysis-derived patterns of potential traumatic experiences with burnout were examined using logistic regression analysis.

RESULTS

Specific traumatic events (e.g., patients' sudden death, bullying and ostracism from colleagues) were independently associated with an increased risk of burnout. Work-related potential traumatic events had a cumulative effect on burnout, whereby operating room nurses exposed to cumulative potential traumatic events carried a higher risk for burnout than others. The "multiple work-related potential traumatic events" pattern derived by latent class analysis was related to an increased risk of high depersonalization.

CONCLUSION

Operating room nurses who reported specific or multiple work-related potential traumatic events were at high risk for burnout. It is of great significance to provide qualified and timely counselling or support.

IMPACT

This study is the first to focus on work-related potential traumatic events among operating room nurses and examine their relationship with burnout based on three perspectives. The findings could help identify those operating room nurses who are at high risk of burnout in clinical practice. Hospital managers should develop targeted interventions to prevent or mitigate the harmful impact of potential traumatic events on occupational health.

Sleep heterogeneity in the third trimester of pregnancy: Correlations with depression, memory impairment, and fatigue

This study aimed to identify sleep subtypes during pregnancy using a person-centered method, explore the underlying factors of these subtypes, and investigate the associations of these subtypes with depression, memory impairment, and fatigue. Accordingly, self-report measures were administered to 1,825 pregnant women to assess demographics, prenatal factors, childhood trauma, personality traits, sleep problems, depression, memory impairment, and fatigue. Data were analyzed using latent class analysis, chi-squared tests, analysis of variance, multinomial logistical regression, and multivariate linear regression analyses. The profiles of "good sleep quality," "poor sleep efficiency," "daily disturbances," and "poor sleep quality" were identified. The results also revealed several factors underlying these subtypes that affect sleep quality: rumination, perinatal complications, high neuroticism, low resilience, history of abortion, and postgraduate education. Further, the "daily disturbances" and the "poor sleep quality" groups reported higher depression, memory impairment, and fatigue than the "good sleep quality" group. Thus, this study elucidated the heterogeneity of sleep subtypes during pregnancy in the Chinese population. Such findings may promote the development of tailored interventions for specific sleep subtypes in pregnant women.

The factor structure of major depressive symptoms in a sample of Chinese earthquake survivors

BACKGROUND

Experiencing natural disasters is associated with common mental disorders including major depressive disorder (MDD). However, the latent structure of MDD is widely debated, and few studies tested the MDD factor structure in Chinese natural disaster survivors. Therefore, the aim of the current study was to evaluate the factorial validity of the Patient Health Questionnaire-9 (PHQ-9) for DSM-5 major depressive disorder (MDD) symptoms in Chinese earthquake survivors.

METHOD

Participants were 1058 Chinese earthquake survivors. Self-reported measures included the PHQ-9 and the Short-Form Health Survey (SF-36). Confirmatory factor analysis (CFA) and structural equation modelling (SEM) was used to examine the latent structure of MDD and the associations between latent factors of MDD and different domains of health-related quality of life (HRQoL), respectively.

RESULTS

In the current sample, the model consisted of somatic and cognitive/affective (non-somatic) factors demonstrated significantly better fit than the other competing MDD models (χ² = 173.89, df = 26, CFI = 0.986, TLI = 0.981, RMSEA = 0.073, BIC = 18,091.13). Further SEM analyses indicated that the non-somatic factor was significantly related to both physical (β = - 0.362, p < .01) and psychosocial HRQoL (β = - 0.773, p < .01), while the somatic factor was a uniquely predictor of physical HRQoL (β = - 0.336, p < .01). Furthermore, we found the somatic factor partially mediated the relationship between the cognitive/affective factor and physical HRQoL (all ps < .05).

CONCLUSIONS

The MDD symptoms was best captured by a two-factor model comprised of somatic and cognitive/affective factors in Chinese natural disaster survivors. The two MDD factors were differentially associated with physical and psychosocial HRQoL, and the cognitive/affective factor associated physical HRQoL partially through the somatic factor. The current findings increase our understanding of latent structure of MDD symptoms, and carry implications for assessment and intervention of post-disaster mental health problems.

Health-related quality of life among Chinese primary care patients with different lower urinary tract symptoms: a latent class analysis

PURPOSE

No previous study has used a data-driven approach to explore symptom subclasses among patients with lower urinary tract symptoms (LUTS). The objectives of this study were to use latent class analysis (LCA) to identify distinct classes of LUTS among primary care patients and to assess the class differences in health-related quality of life (HRQOL).

METHODS

In this cross-sectional study, 500 patients were randomly recruited, and 18 symptoms according to the International Continence Society 2002 criteria were assessed. Classes were identified by LCA. Patient HRQOL was measured using the 12-item Short Form Health Survey (version 2), the modified Incontinence Impact Questionnaire-Short Form and the HRQOL item from the International Prostate Symptom Score.

RESULTS

Six distinct LUTS classes were identified: "asymptomatic" (26.0%), "mild symptoms" (22.6%), "moderate multiple symptoms" (17.0%), "urgency symptoms" (13.8%), "urinary incontinence" (12.0%) and "severe multiple symptoms" (8.6%). Multinomial regression analysis found differences in the gender distribution and prevalence of heart diseases across classes, and multiple linear regression found that patients with "severe multiple symptoms" and "urinary incontinence" had the poorest HRQOL.

CONCLUSION

Almost three quarters of the primary care patients in this study were suffering from varying degrees of LUTS. The poor HRQOL in "severe multiple symptoms" and "urinary incontinence" implies that patients in these classes require additional attention and treatments.

Maternal Prenatal Mood, Pregnancy-Specific Worries, and Early Child Psychopathology: Findings From the DREAM BIG Consortium

OBJECTIVE

Few studies have attempted to identify how distinct dimensions of maternal prenatal affective symptoms relate to offspring psychopathology. We defined latent dimensions of women's prenatal affective symptoms and pregnancy-specific worries to examine their association with early offspring psychopathology in three prenatal cohorts.

METHOD

Data were used from three cohorts of the DREAM-BIG consortium: Avon Longitudinal Study of Parents and Children (ALSPAC [N = 12,515]), Generation R (N = 6,803), and the Canadian prenatal cohort Maternal Adversity, Vulnerability, and Neurodevelopment (MAVAN [N = 578]). Maternal prenatal affective symptoms and pregnancy-specific worries were assessed using different measures in each cohort. Through confirmatory factor analyses, we determined whether comparable latent dimensions of prenatal maternal affective symptoms existed across the cohorts. We used structural equation models to examine cohort-specific associations between these dimensions and offspring psychopathology at 4 to 8 years of age (general psychopathology, specific internalizing and externalizing previously derived using confirmatory factor analyses). Cohort-based estimates were meta-analyzed using inverse variance-weighing.

RESULTS

Four prenatal maternal factors were similar in all cohorts: a general affective symptoms factor and three specific factors-an anxiety/depression factor, a somatic factor, and a pregnancy-specific worries factor. In meta-analyses, both the general affective symptoms factor and pregnancy-specific worries factor were independently associated with offspring general psychopathology. The general affective symptoms factor was further associated with offspring specific internalizing problems. There were no associations with specific externalizing problems.

CONCLUSION

These replicated findings of independent and adverse effects for prenatal general affective symptoms and pregnancy-specific worries on child mental health support the need for specific interventions in pregnancy.

Perinatal depression: Data-driven subtypes derived from life history and mindfulness and personality

BACKGROUND

Perinatal depression is the most prevalent mental disorder during the perinatal period, and research suggests that it presents heterogeneously. We aimed to explore how subtypes of perinatal depression present in terms of multivariate patterns of stable characteristics.

METHODS

A cohort study was conducted from March 2016 to March 2018 with Chinese women in the prenatal period (n = 3186). Of the participants, 682 (21.41%) women with Edinburgh Postnatal Depression Scale scores ≥10, indicating probable depression, were included, with the remaining 2504 (78.59%) representing the control group. We assessed mood distress, cognition, life history, emotional regulation, and personality, and used latent class analysis and latent transition analysis to identify perinatal depression subtypes. Of the 682 women with probable depression, only 598 were included in the full analyses, as they completed at least 10 questionnaires. A second, non-overlapping sample and a follow-up cohort were used.

RESULTS

We identified four subtypes: 1) a highly distressed type characterized by distress across all domains, high levels of rumination and neuroticism, and reduced trait mindfulness; 2) two moderately distressed types: one with high trauma and low perceived social support, and another with low trauma, high perceived social support, and expressive suppression; and 3) a slightly distressed subtype.

LIMITATIONS

We only collected cost and time spent in hospital from medical records. We only had a small follow-up sample.

CONCLUSIONS

This multidimensional subtyping of women with perinatal depression could help reduce the apparent heterogeneity of perinatal depression. Distinguishing the subtype characteristics facilitates identifying underlying causes of perinatal depression.

A transdiagnostic approach to conceptualizing depression across the perinatal period in a high-risk sample

Clinical guidelines recommend assessing depression during pregnancy and postpartum but often overlook potential changes in symptoms across this developmental period. Such changes contribute to difficulties in conceptualizing maternal depression. This study aimed to situate depressive symptoms and related concerns (anxiety, stress, sleep) across the perinatal period within a transdiagnostic framework and to use this framework to better understand how depressive symptoms change across the perinatal period. First, items from seven symptom scales were a priori categorized into six transdiagnostic factors: four based on Research Domain Criteria (loss, potential threat, frustrative nonreward, and sleep-wakefulness) and two based on the depression literature (somatic and coping symptoms). Second, using prospective data from women with a history of an affective disorder (n = 657) in an observational study of neuropsychiatric illness, factor analyses were performed in seven periods (three trimesters of pregnancy and four quarters of first year postpartum). For each period, a bifactor model with six transdiagnostic factors and a general factor fit data better than models that combined or dropped a factor (p < .003). Except around delivery, item loadings and intercepts could be fixed between consecutive periods and still adequately fit data from both periods. Means of sleep-wakefulness and somatic factors increased significantly from second to third trimester (p < .01), with trends reversing early postpartum. In conclusion, depressive symptoms and related concerns exhibit factor structures that are only partly congruent across the perinatal period. This conclusion suggests that greater attention to specific life phases is warranted in the conceptualization of depression during this time in women's lives. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Identify depressive phenotypes by applying RDOC domains to the PHQ-9

Major depression consists of multiple phenotypic traits. Our objective was to characterize depressive phenotypes in the patient health questionnaire (PHQ)-9 using the Research Domain Criteria (RDoC) research framework. Cross-sectional data were examined from the 2013-2014 (N = 5397) and 2015-2016 (N = 5164) National Health and Nutrition Examination Survey, a large, nationally representative U.S. sample. Using both factor analysis and qualitative analysis in mapping scale items along RDoC domains, a four factor model was found to be theoretically appropriate and had an excellent model fit for the PHQ-9. The factor structure consisted of phenotypes describing Negative Valence Systems and Externalizing (anhedonia and depression), Negative Valence Systems and Internalizing (depression, guilt and self-harm), Arousal and Regulatory Systems (sleep, fatigue and appetite) and Cognitive and Sensorimotor Systems (concentration and psychomotor). High correlation between these phenotypes did indicate screening and monitoring for depression study population using a single depression score is likely useful in most circumstances. In multiple indicator multiple cause analysis, differences in the means of the phenotypic traits were found by age, race/ethnicity, sex, and number of comorbidities. Future research should explore whether phenotype expression derived from readily available self-rated depression scales can help to inform more personalized care.