Risk Of Perinatal Depression Research Articles

Association between inflammatory biomarkers before pregnancy and risk of perinatal depression: A prospective cohort study of 4483 women in Sweden

AimPerinatal depression (PND) is a global health concern, affecting millions of childbearing women. Emerging data suggest that inflammation may play a role in the development of PND. Peripheral blood inflammatory biomarkers before pregnancy are widely tested in clinical practice at minimum cost, yet their potential role in PND risk remains unknown. MethodsWe conducted a prospective cohort study of 4483 birthing women during 2009–2021 within the LifeGene study with linkage to Swedish registers. Peripheral blood inflammatory biomarkers were profiled at baseline. Cases of PND were identified using validated tools or clinical diagnosis from subsequent pregnancies and postpartum periods. Logistic regression models were employed to assess the associations of each inflammatory biomarker (z scored) with PND. ResultsWe identified 495 (11.0 %) PND cases with an average age of 29.2 years. Pre-pregnancy platelet-to-lymphocyte ratio (PLR) was positively associated [OR, 95 % CI:1.14(1.01,1.27)], while lymphocyte count was inversely associated [OR, 95 % CI: 0.89(0.80,0.98)] with PND. A dose-response relationship was indicated for both PLR and lymphocytes when analyzed in categories based on tertile distribution. These associations appeared more pronounced for postpartum depression than antepartum depression and were independent of psychiatric comorbidities. ConclusionWith implications for future mechanistic research, these findings suggest that blood levels of lymphocytes and PLR before pregnancy are associated with subsequent risk of PND in a dose-response manner.

Predicting Prenatal Depression and Assessing Model Bias Using Machine Learning Models

BackgroundPerinatal depression is one of the most common medical complications during pregnancy and postpartum period, affecting 10% to 20% of pregnant individuals, with higher rates among Black and Latina women who are also less likely to be diagnosed and treated. Machine learning (ML) models based on electronic medical records (EMRs) have effectively predicted postpartum depression in middle-class White women but have rarely included sufficient proportions of racial/ethnic minorities, which has contributed to biases in ML models. Our goal is to determine whether ML models could predict depression in early pregnancy in racial/ethnic minority women by leveraging EMR data. MethodsWe extracted EMRs from a large U.S. urban hospital serving mostly low-income Black and Hispanic women (n = 5875). Depressive symptom severity was assessed using the Patient Health Questionnaire-9 self-report questionnaire. We investigated multiple ML classifiers using Shapley additive explanations for model interpretation and determined prediction bias with 4 metrics: disparate impact, equal opportunity difference, and equalized odds (standard deviations of true positives and false positives). ResultsAlthough the best-performing ML model's (elastic net) performance was low (area under the receiver operating characteristic curve = 0.61), we identified known perinatal depression risk factors such as unplanned pregnancy and being single and underexplored factors such as self-reported pain, lower prenatal vitamin intake, asthma, carrying a male fetus, and lower platelet levels. Despite the sample comprising mostly low-income minority women (54% Black, 27% Latina), the model performed worse for these communities (area under the receiver operating characteristic curve: 57% Black, 59% Latina women vs. 64% White women). ConclusionsEMR-based ML models could moderately predict early pregnancy depression but exhibited biased performance against low-income minority women.

Dlaczego i jak monitorować ryzyko depresji okołoporodowej - algorytmy postępowania.

Dlaczego i jak monitorować ryzyko depresji okołoporodowej - algorytmy postępowania.

A machine learning model to predict the risk of perinatal depression: Psychosocial and sleep-related factors in the Life-ON study cohort

Perinatal depression (PND) is a common complication of pregnancy associated with serious health consequences for both mothers and their babies. Identifying risk factors for PND is key to early detect women at increased risk of developing this condition. We applied a machine learning (ML) approach to data from a multicenter cohort study on sleep and mood changes during the perinatal period (“Life-ON”) to derive models for PND risk prediction in a cross-validation setting. A wide range of sociodemographic variables, blood-based biomarkers, sleep, medical, and psychological data collected from 439 pregnant women, as well as polysomnographic parameters recorded from 353 women, were considered for model building. These covariates were correlated with the risk of future depression, as assessed by regularly administering the Edinburgh Postnatal Depression Scale across the perinatal period. The ML model indicated the mood status of pregnant women in the first trimester, previous depressive episodes and marital status, as the most important predictors of PND. Sleep quality, insomnia symptoms, age, previous miscarriages, and stressful life events also added to the model performance. Besides other predictors, sleep changes during early pregnancy should therefore assessed to identify women at higher risk of PND and support them with appropriate therapeutic strategies.

Characteristics of mothers at risk for perinatal depression in industrial areas

Expectant mothers susceptible to emotional shifts during pregnancy, such as depression, underwent a perinatal phase. Within the first year after giving birth, 10-15% of women experienced specific depressive symptoms. This situation could harm the mother-child relationship. The purpose of this study was to characterize the traits of mothers who might have experienced prenatal depression at Muhammadiyah Gresik Hospital. Purposive sampling and Spearman's rank test analytics were applied to pregnant women between 20 weeks gestation and one month postpartum. Pregnant women with a history of acute medical problems and mental or psychological disorders were excluded. Out of 47 respondents, 59.6% were at risk of perinatal depression. The characteristics studied included religion, ethnicity, maternal age, educational level, employment status, family income, number of children, mode of delivery, complications during delivery, and depression history. Maternal age (r=-0.314, p=0.032*), employment status (r=0.346, p=0.016*), parity (r=-0.410, p=0.004*), and most recent delivery (r=-0.329, p=0.024*) showed significant correlations with the likelihood of perinatal depression. Maternal age, parity, and mode of delivery had negative correlations, while employment status had a positive correlation. The results of this study can be used as screening tools to identify mothers at risk of perinatal depression. Additionally, it proposes a prenatal and delivery counseling intervention program for both expectant mothers and unemployed women.

Mortalité maternelle par suicide et autres causes psychiatriques en France 2016–2018

This report, covering the period 2016–2018, confirms that psychiatric causes (largely dominated by suicides) are the leading cause of maternal mortality up to 1year after childbirth, a finding already made in the previous 2013–2015 report. There were 47 deaths from psychiatric causes in 3years, including 45 maternal suicides, giving a maternal mortality ratio (MMR) of 2.1 per 100,000 live births (NV) (95% CI: 1.4–2.6). The median time to suicide was 138days postpartum. This group represents 17.3% (16.5% for suicides) of all maternal deaths for the period. Maternal suicide is linked to an interaction of several risk factors, including a history of personal and family psychiatric disorders not always known to the obstetric team (53% of women), socioeconomic disparities (29% present social vulnerability, and 14% domestic violence), stressful events, and inadequate access to healthcare services. Psychiatric causes are among those in which the proportion of sub-optimal care and preventable deaths, i.e. 79% of cases, are the highest. An analysis of all the women who died in France of psychiatric causes during pregnancy reveals a number of recurring elements that point to the need for improvement, both in terms of the quality and organization of care, and in terms of women's interaction with the healthcare system. Screening for a history of psychiatric disorders and ongoing psychiatric pathologies must be carried out systematically at all stages of pregnancy and postpartum by all those involved, with communication with future parents on the not inconsiderable risk of perinatal depression. Finally, it is important to develop an adapted and graduated response across the country, according to resources, and to strengthen city–hospital collaboration and training for all those involved.

Bidirectional association between autoimmune disease and perinatal depression: a nationwide study with sibling comparison

Although major depression, characterized by a pro-inflammatory profile, genetically overlap with autoimmune disease (AD) and the perinatal period involve immune system adaptations and AD symptom alterations, the bidirectional link between perinatal depression (PND) and AD is largely unexplored. Hence, the objective of this study was to investigate the bidirectional association between PND and AD. Using nationwide Swedish population and health registers, we conducted a nested case-control study and a matched cohort study. From 1,347,901 pregnancies during 2001–2013, we included 55,299 incident PND, their unaffected full sisters, and 10 unaffected matched women per PND case. We identified 41 subtypes of AD diagnoses recorded in the registers and compared PND with unaffected population-matched women and full sisters, using multivariable regressions. Women with an AD had a 30% higher risk of subsequent PND (95% CI 1.2–1.5) and women exposed to PND had a 30% higher risk of a subsequent AD (95% CI 1.3–1.4). Comparable associations were found when comparing exposed women with their unaffected sisters (nested case-control OR: 1.3, 95% CI 1.2–1.5, matched cohort HR: 1.3, 95% CI 1.1–1.6), and when studying antepartum and postpartum depression. The bidirectional association was more pronounced among women without psychiatric comorbidities (nested case-control OR: 1.5, 95% CI 1.4–1.6, matched cohort HR: 1.4, 95% CI 1.4–1.5) and strongest for multiple sclerosis (nested case-control OR: 2.0, 95% CI 1.6–2.3, matched cohort HR: 1.8, 95% CI 1.0–3.1). These findings demonstrate a bidirectional association between AD and PND independent of psychiatric comorbidities, suggesting possibly shared biological mechanisms. If future translational science confirms the underlying mechanisms, healthcare providers need to be aware of the increased risk of PND among women with ADs and vice versa.

406 Cost-effectiveness of virtual Mindfulness Based Cognitive Therapy on pregnancies at high risk of perinatal depression

406 Cost-effectiveness of virtual Mindfulness Based Cognitive Therapy on pregnancies at high risk of perinatal depression

The predictive effect of mid-pregnancy sleep disorders on perinatal depression within women with or without depression in early pregnancy: A prospective cohort study

BackgroundTo investigate the relationship between depression in early pregnancy and sleep quality in mid-pregnancy, and explore whether sleep disorders independently predicts depression across the perinatal period within women with or without depression in early pregnancy. MethodsData were collected at 7 time points from 12 weeks of pregnancy to 6 weeks postpartum. Multiple logistic regression and survival analysis were used to explore the relationship between sleep quality in mid-pregnancy and perinatal depression within women with or without depression in early pregnancy. Results390 women were included. Women with depression in early pregnancy were more likely to have sleep disorders and perinatal depression. Women with sleep disorders had a higher risk of perinatal depression compared to women without sleep disorders in mid-pregnancy. Stratified analysis based on whether depressed at 12 weeks of pregnancy found that among women without depression, those with sleep disorders in mid-pregnancy were more likely to have subsequent perinatal depression and appeared earlier; whereas, among women with depression, mid-pregnancy sleep disorders was not a predictor of subsequent perinatal depression. LimitationHigh rates of missed visits may lead to sample bias, with depression and sleep quality being assessed by self-report. ConclusionsWomen with depression in early pregnancy are more likely to have sleep disorders in mid-pregnancy. There is a strong correlation between sleep quality in mid-pregnancy and perinatal depression among women without depression in early pregnancy. Routine screening and intervention for sleep disorders should be a priority in perinatal care to reduce the incidence of perinatal depression.

Equitable reach: Patient and professional recommendations for interventions to prevent perinatal depression and anxiety

ObjectivePerinatal depression and anxiety are the most common complications in the perinatal period and disproportionately affect those experiencing economic marginalization. Fewer than 15% of individuals at risk for perinatal depression are referred for preventative counseling. The goal of this study was to elicit patient and perinatal care professionals' perspectives on how to increase the reach of interventions to prevent perinatal depression and anxiety among economically marginalized individuals. MethodsWe conducted qualitative interviews with perinatal individuals with lived experience of perinatal depression and/or anxiety who were experiencing economic marginalization (n = 12) and perinatal care professionals and paraprofessionals (e.g., obstetrician/gynecologists, midwives, doulas; n = 12) serving this population. Three study team members engaged a “a coding consensus, co-occurrence, and comparison,” approach to code interviews. ResultsPerinatal individuals and professionals identified prevention intervention delivery approaches and content to facilitate equitable reach for individuals who are economically marginalized. Factors influential included availability of mental health counselors, facilitation of prevention interventions by a trusted professional, digital health options, and options for mental health intervention delivery approaches. Content that was perceived as increasing equitable intervention reach included emphasizing stigma reduction, using cultural humility and inclusive materials, and content personalization. ConclusionsLeveraging varied options for mental health intervention delivery approaches and content could reach perinatal individuals experiencing economic marginalization and address resource considerations associated with preventative interventions.

Sleep quality and perinatal depression in pregnant women treated in a primary care centre in Lima, Peru

ObjectiveThe aim is to evaluate the association between sleep quality and perinatal depression in pregnant women between the 12th week of gestation and the 36th week of gestation in a maternity and child centre in Lima. MethodsAnalytical cross-sectional study in pregnant women cared for in a primary care centre between August and December 2019. The data were collected through a self-administered survey. The Pittsburgh Sleep Quality Index (PSQI) was used to assess sleep quality. The evaluation of perinatal depression was performed with the Edinburgh Postnatal Depression Scale (EPDS). For the multivariate analysis, Poisson regression with robust variances was used to calculate the crude and adjusted prevalence ratios and their respective confidence intervals. ResultsThe sample was composed of 200 participants. The median [IQR] age was 26 [22–32] years, and 111 (55.5%) pregnancies were unplanned. 52% presented a poor quality of sleep and the risk of perinatal depression was 31.5%. Poor quality of sleep was associated with a significantly higher frequency of perinatal depression (aPR = 4.8 for those with poor quality of sleep warranting medical attention, and aPR = 6.6 for those with poor quality of sleep warranting medical attention and treatment). ConclusionsThere is a possible association between poor sleep quality and perinatal depression in pregnant women between weeks 12 and 36 of gestation. Operational research should be promoted to assess whether interventions to improve sleep quality could have a positive impact on reducing perinatal depression.

Fetal Anomaly: Family Experiences and Preferences for Care: An Integrative Review.

The prenatal diagnosis of a fetal anomaly is unexpected, creating a family crisis. Expectant parents are at an increased risk for perinatal depression and traumatic stress. Prior reviews examined parents' experiences when terminating but not continuing the pregnancy. This review synthesized qualitative research to describe the experiences, emotional responses, and needs of families continuing their pregnancy. An integrative review was performed using the Whitemore and Knafl methodology and PRISMA guidelines. A systematic review of peer-reviewed articles published between 2000 and 2200 on the experiences of fetal anomaly was performed using 5 databases. Eligible articles included qualitative studies describing families' experiences with a fetal anomaly diagnosis who elected to continue their pregnancy. Methodological quality was evaluated using the Critical Skills Appraisal Program checklist. Of the 678 article results, 16 met inclusion criteria. There were 298 participants from 5 countries. The major overarching theme of Response to the Diagnosis of Fetal Anomaly was identified. The major categories were emotional response, coping strategies, influences, health care experiences, and family needs. Uncertainty and grief were the most common emotions. Parents choosing to continue pregnancy benefit from compassionate, sensitive care, and accurate, concise information, provided in tailored instruction using multiple styles.

Preventing Perinatal Depression: Cultural Adaptation of the Mothers and Babies Course in Kenya and Tanzania.

Pregnant women and mothers in sub-Saharan Africa are at high risk for perinatal depression, warranting a need to develop culturally tailored interventions to prevent perinatal depression. This paper documents the process of adapting an evidence-based preventive intervention developed in the United States, the Mothers and Babies Course (MBC), to fit the contexts of rural pregnant women and mothers of young children in Kenya and Tanzania using the updated Framework for Reporting Adaptations and Modifications-Enhanced (FRAME). Data from informant interviews and field observations from the planning and implementation phases were used to make adaptations and modifications of the MBC for perinatal women through the eight aspects of FRAME. Follow-up field visits and reflection meetings with case managers and intervention participants indicated that the adapted version of the MBC was well accepted, but fidelity was limited due to various implementation barriers. The FRAME provided an optimal structure to outline the key adaptations and modifications of a preventive intervention intended to maximize engagement, delivery, and outcomes for high-risk perinatal women in rural settings.

Association between adverse childhood experiences and perinatal depressive symptoms: a cross-sectional analysis of 16,831 women in Iceland

Emerging data suggest that certain adverse childhood experiences (ACEs) are associated with perinatal depression (PND). However, few studies have comprehensively assessed the cumulative number and types of ACEs and their association to PND. We conducted a cross-sectional analysis among 16,831 female participants from the Stress-And-Gene-Analysis (SAGA) cohort in Iceland, 2018. ACEs were surveyed with the World Health Organization ACE—International questionnaire, while PND symptoms were assessed using the Edinburgh Postnatal Depression Scale (lifetime version). We, while adjusting for confounding factors, estimated the prevalence ratio (PR) of PND in relation to total number of ACEs using the Poisson quasi-likelihood model and further performed analyses for type-specific ACEs. At a mean age of 44 years (SD ± 11.1), 6,201 (36.8%) participants had experienced probable PND. Total number of ACEs was positively associated with PND (PR 1.11 per ACE, 95% CI: 1.10–1.11), also among women without any psychiatric comorbidities (PR 1.13, 95% CI: 1.11–1.14). PRs increased in a dose–response manner with the number of ACEs (P for trend < 0.001); women that endorsed 5 or more ACEs were twice as likely to have experienced PND (PR 2.24, 95% CI: 2.09–2.41). All ACE types (n = 13) were associated with PND, with most pronounced association for emotional neglect by a guardian (PR 1.53, 95% CI: 1.47–1.59). Our findings suggest a positive association between number of ACEs and PND symptoms. If our results are confirmed with prospective data, healthcare providers need to be alert of the risk of PND among expecting mothers with history of ACEs.

Perinatal depression: The use of the Edinburgh Postnatal Depression Scale to derive clinical subtypes.

Predicting the course and complications of perinatal depression through the identification of clinical subtypes has been previously undertaken using the Edinburgh Postnatal Depression Scale and has the potential to improve the precision of care and improve outcomes for women and their children. Edinburgh Postnatal Depression Scale scores were collected twice in pregnancy and twice in the postpartum in a sample of 360 women who met diagnostic criteria for perinatal depression using the Structured Clinical Interview for DSM disorder. These data were used to compare with previous, though conflicting, evidence from cross-sectional studies and extend this by undertaking longitudinal measurement invariance modelling to test the structural validity across the perinatal period. Latent profile and transition modelling was used to identify distinct subtypes of women and assess the utility of these subtypes and transition profiles to predict clinically meaningful outcomes. Although our data supported one of the previously reported three-factor Edinburgh Postnatal Depression Scale structures used to compute subfactor totals for depressed mood, anxiety and anhedonia at both early pregnancy and 6 months postpartum, there was little value in using these Edinburgh Postnatal Depression Scale subfactor scores to identify subtypes predictive of clinically meaningful postpartum symptom subtypes, or of general health, pregnancy and neonatal outcomes. Our study does not support the use of the Edinburgh Postnatal Depression Scale to distinguish perinatal depressive subtypes for the purposes of predicting course and complications associated with perinatal depression. However, the results give guidance on alternative ways to study the value of personalised management in improved outcomes for women living with or at risk for perinatal depression.

0621 A machine learning model to predict the risk of perinatal depression from sleep data in healthy pregnant women

Abstract Introduction Perinatal depression (PND) is a complication of pregnancy associated with serious health consequences for both mothers and their babies. Identifying predisposing factors for PND during early pregnancy is key to early detection of women who may be at greater risk of developing this condition. Machine Learning (ML) techniques have recently been applied in a few studies, mostly to predict postpartum depression. None of them, however, considered sleep data in model building, neither focused on PND. Methods By analyzing data from a multicenter, prospective cohort study on sleep and mood changes during the perinatal period (the “Life-ON” study), we constructed a ML model for PND risk prediction and tested it in a cross-validation setting. PND was assessed using an EPDS score &amp;gt;12 during 9 visits from early pregnancy until 6 months postpartum. In a bivariate analysis, 47 sociodemographic, psychological, blood-based, medical/gynecological, and subjective sleep variables, collected from 439 pregnant women (33.7±4.2 yrs.) during the first trimester of gestation, as well as 33 polysomnographic (PSG) parameters, recorded from 353 women (33.6±4.2 yrs.) during the second trimester, were correlated with PND. A support vector machine (SVM) model was then trained using the 10-features with the highest permutation importance to predict the individual risk of PND for each woman. Results Among all variables considered, sleep quality (PSQI) and insomnia symptoms (ISI) (p&amp;lt; 0.001), daytime sleepiness (ESS) and RLS severity (IRLS) (p&amp;lt; 0.05), as well as the PSG parameters Apnea Index (p=0.001), number of central hypopneas and percentage of sleep stage N2 (p&amp;lt; 0.05), were all positively correlated to PND. The PSQI and ISI scores were also selected by the SVM classifier, which achieved a mean AUROC of 0.777 and an AUPRC of 0.393, corresponding to a sensitivity of 54.3% and a specificity of 82.6% in identifying women at risk for PND. Conclusion In our data-driven ML model to predict the risk of PND during early pregnancy, subjective poor sleep quality and insomnia symptoms identified women at greater risk of developing PND, while none of the PSG variables improved model performance. Support (if any) Swiss National Science Foundation (grant: 320030_160250/1). The Italian Ministry of Health and Emilia-Romagna Region (grant: PE-2011-02348727).

Racial and ethnic differences in perinatal depression and anxiety

BackgroundFindings on racial and ethnic differences in perinatal depression/anxiety are mixed. MethodsWe assessed racial and ethnic differences in depression, anxiety, and comorbid depression/anxiety diagnoses in the year before, during, and the year after pregnancy (n = 116,449) and depression severity during (n = 72,475) and in the year after (n = 71,243) pregnancy among patients in a large, integrated healthcare delivery system. ResultsCompared to Non-Hispanic White individuals, Asian individuals had lower risk of perinatal depression and anxiety (e.g., depression during pregnancy relative risk [RR] = 0.35, 95 % confidence interval [CI]:0.33–0.38) and postpartum moderate/severe (RR = 0.63, 95 % CI:0.60–0.67) and severe (RR = 0.66, 95 CI:0.61–0.71) depression but higher risk of moderate/severe depression during pregnancy (RR = 1.18, 95 % CI:1.11–1.25). Non-Hispanic Black individuals had higher risk of perinatal depression, comorbid depression/anxiety, and moderate/severe and severe depression (e.g., depression diagnoses during pregnancy RR = 1.35, 95 % CI:1.26–1.44). Hispanic individuals had lower risk of depression during pregnancy and perinatal anxiety (e.g., depression during pregnancy RR = 0.86, 95 % CI:0.82–0.90) but higher risk of postpartum depression (RR = 1.14, 95 % CI:1.09–1.20) and moderate/severe and severe depression during and after pregnancy (e.g., severe depression during pregnancy RR = 1.59, 95 % CI:1.45–1.75). LimitationsInformation on depression severity was unavailable for some pregnancies. Findings may not generalize to individuals without insurance or outside of Northern California. ConclusionsNon-Hispanic Black individuals of reproductive age should be targeted with prevention and intervention efforts aimed at reducing and treating depression and anxiety. Asian and Hispanic individuals of reproductive age should be targeted with campaigns to destigmatize mental health disorders and demystify treatments and systematically screened for depression/anxiety.

Antenatal mobile-delivered mindfulness-based intervention to reduce perinatal depression risk and improve obstetric and neonatal outcomes: A randomized controlled trial

ObjectivesOne in five mothers will experience perinatal depression (PND) during pregnancy and within their first year following childbirth. Current evidence suggests the short-term efficacy of Mindfulness-based interventions (MBI) for perinatal women, but the extent to which this positive impact remains the early postpartum period is unclear. This study investigated the short- and maintenance efficacy of a mobile-delivered four-immeasurable MBI on PND, and obstetric and neonatal outcomes. MethodsSeventy-five adult pregnant women suffering from heightened distress were randomized to receive a mobile-delivered four-immeasurable MBI (n = 38) or a web-based perinatal education program (n = 37). PND was measured by Edinburgh Postnatal Depression Scale at baseline, post-intervention, 37th-week gestation, and 4–6 weeks postpartum. Outcomes also included obstetric and neonatal outcomes, trait mindfulness, self-compassion, and positive affect. ResultsParticipants reported an average age of 30.6 (SD = 3.1) years with a mean gestational age of 18.8 (SD = 4.6) weeks. In intention-to-treat analyses, women in the mindfulness group showed a significantly greater reduction in depression from baseline to post-intervention (adjusted mean change difference [β] = −3.9; 95%CI = [−6.05, −1.81]; d = −0.6), and the reduction sustained until 4–6 weeks postpartum (β = −6.3; 95%CI = [−8.43, −4.12]; d = −1.0), compared with control. They had a significantly reduced risk of emergent cesarean section (relative risk = 0.5) and gave birth to infants with higher Apgar scores (β = 0.6;p = .03; d = 0.7). Depression reduction before giving birth significantly mediated the intervention effect on lowering the emergency cesarean risk. ConclusionsWith a reasonably low dropout rate (13.2 %), the mobile-delivered MBI can be an acceptable and effective intervention for reducing depression throughout pregnancy and postpartum. Our study also suggests the potential benefits of early prevention for mitigating emergent cesarean section risk and enhancing neonatal health.

Research Priorities to Support Women Veterans' Reproductive Health and Health Care Within a Learning Health Care System.

Research Priorities to Support Women Veterans' Reproductive Health and Health Care Within a Learning Health Care System.

Autonomic function and inflammation in pregnant women participating in a randomized controlled study of Mindfulness Based Childbirth and Parenting

BackgroundPregnancy and childbirth are significant events in many women’s lives, and the prevalence of depressive symptoms increases during this vulnerable period. Apart from well documented cognitive, affective, and somatic symptoms, stress and depression are associated with physiological changes, such as reduced heart-rate variability (HRV) and activation of the inflammatory response system. Mindfulness Based Interventions may potentially have an effect on both HRV, inflammatory biomarkers, and self-assessed mental health. Therefore, the aim of this study was to assess the effects of a Mindfulness Childbirth and Parenting (MBCP) intervention on HRV, serum inflammatory marker levels, through an RCT study design with an active control group.MethodsThis study is a sub-study of a larger RCT, where significant intervention effects were found on perinatal depression (PND) and perceived stress. Participants were recruited through eight maternity health clinics in Stockholm, Sweden. In this sub-study, we included altogether 80 women with increased risk for PND, and blood samples and HRV measures were available from 60 of the participants (26 in the intervention and 34 in the control group).ResultsParticipants who received MBCP reported a significantly larger reduction in perceived stress and a significantly larger increase in mindfulness, compared to participants who received the active control treatment. However, in this sub-study, the intervention had no significant effect on PND, inflammatory serum markers or measures of HRV.ConclusionsNo significant differences were found regarding changes in HRV measures and biomarkers of inflammation, larger studies may be needed in the future.Trial registrationClinicalTrials.gov ID: NCT02441595. Registered 12 May 2015 - Retrospectively registered.