Assessment of the association of heart rate variability and baroreflex sensitivity with depressive symptoms and stress experienced by women in pregnancy

Investigating heart rate variability measures during pregnancy as predictors of postpartum depression and anxiety: an exploratory study

Perinatal affective disorders are common, but standard screening measures reliant on subjective self-reports might not be sufficient to identify pregnant women at-risk for developing postpartum depression and anxiety. Lower heart rate variability (HRV) has been shown to be associated with affective disorders. The current exploratory study aimed to evaluate the predictive utility of late pregnancy HRV measurements of postpartum affective symptoms. A subset of participants from the BASIC study (Uppsala, Sweden) took part in a sub-study at pregnancy week 38 where HRV was measured before and after a mild stressor (n = 122). Outcome measures were 6-week postpartum depression and anxiety symptoms as quantified by the Edinburgh Postnatal Depression Scale (EPDS) and the Beck Anxiety Inventory (BAI). In total, 112 women were included in a depression outcome analysis and 106 women were included in an anxiety outcome analysis. Group comparisons indicated that lower pregnancy HRV was associated with depressive or anxious symptomatology at 6 weeks postpartum. Elastic net logistic regression analyses indicated that HRV indices alone were not predictive of postpartum depression or anxiety outcomes, but HRV indices were selected as predictors in a combined model with background and pregnancy variables. ROC curves for the combined models gave an area under the curve (AUC) of 0.93 for the depression outcome and an AUC of 0.83 for the anxiety outcome. HRV indices predictive of postpartum depression generally differed from those predictive of postpartum anxiety. HRV indices did not significantly improve prediction models comprised of psychological measures only in women with pregnancy depression or anxiety.

Predicting postpartum depressive symptoms by evaluating self-report autonomic nervous system reactivity during pregnancy

OBJECTIVE

Altered self-reported autonomic reactivity is associated with worse mental health in the general population. Although dysfunctional changes in ANS during pregnancy have been investigated in relation to depressive symptoms, no studies addressed the relationship between self-report autonomic reactivity during pregnancy and depressive symptoms after the delivery. The present study aimed to assess the impact of prepartum self-reported autonomic reactivity on the development of postpartum depressive symptoms.

METHODS

In this longitudinal study, 170 women were assessed during pregnancy (i.e., second or third trimester) and after childbirth (i.e., one month after the delivery). Self-reported autonomic reactivity was assessed through the Body Perception Questionnaire - Short Form that evaluates the autonomic functions related to organs above (i.e., supradiaphragmatic reactivity) and below (i.e., subdiaphragmatic reactivity) the diaphragm. In addition, prepartum and postpartum depressive symptoms were evaluated using the Patient Health Questionnaire - 9.

RESULTS

Findings showed that higher prepartum supradiaphragmatic reactivity predicted higher depressive symptoms in the postpartum period (β = 0.112, p = 0.009) after controlling for prepartum depressive symptomatology and other potential covariates.

CONCLUSIONS

Evaluation of self-reported autonomic activity may be a useful tool to identify antenatally women at risk of postpartum depressive symptoms. Future studies are needed to evaluate the effectiveness of interventions aimed at reducing the threat-responsive autonomic reactivity at rest and improving adaptive autonomic regulation to prevent postpartum depression.

Inflammation and decreased cardiovagal modulation are linked to stress and depression at 36th week of pregnancy in gestational diabetes mellitus

Stress and depression have been reported in gestational diabetes mellitus (GDM). Though inflammation and oxidative stress are associated with depression, there are no reports of link of cardiometabolic risks (CMR) to stress and depression in GDM. Normal pregnant women (control group, n = 164) and women with GDM (study group, n = 176) at 36th week of gestation were recruited for the study. Blood pressure (BP), body composition, heart rate variability (HRV), glycated hemoglobin (HbA1C), markers of insulin resistance, oxidative stress, inflammation and endothelial dysfunction, were assessed. Perceived stress score (PSS), quality of life (QoL) scale, Indian diabetic risk score (IDRS) and Edinburg postnatal depression score (EPDS) were assessed. Association of potential contributors to PSS and EDPS were assessed by correlation and regression analyses. There was significant increase in PSS, EPDS, IDRS scores, HbA1C, malondialdehyde (MDA) (oxidative stress marker) and high-sensitive C-reactive protein and interleukin-6 (inflammatory markers), and significant decrease in total power (TP) of HRV (marker of cardiovagal modulation), QoL and nitric oxide (endothelial dysfunction marker) in study group compared to control group. Though many cardiometabolic risk parameters were correlated with PSS and EPDS, the significant independent association was observed for TP, HbA1C, MDA and interleukin-6. However, interleukin-6 had maximum contribution to PSS (β = 0.550, p < 0.001) and EPDS (β = 0.393, p < 0.001) as demonstrated by multiple regression analysis. Inflammation, oxidative stress, glycation status and decreased cardiovagal modulation are associated with stress and depression at 36th week of gestation in GDM.

Comparing prenatal and postpartum stress among women with previous adverse pregnancy outcomes and normal obstetric histories: A longitudinal cohort study

OBJECTIVE

The aim of this study was to compare subjectively and objectively measured stress during pregnancy and the three months postpartum in women with previous adverse pregnancy outcomes and women with normal obstetric histories.

METHODS

We recruited two cohorts in southwestern Finland for this longitudinal study: (1) pregnant women (n = 32) with histories of preterm births or late miscarriages January-December 2019 and (2) pregnant women (n = 30) with histories of full-term births October 2019-March 2020. We continuously measured heart rate variability (HRV) using a smartwatch from 12 to 15 weeks of pregnancy until three months postpartum, and subjective stress was assessed with a smartphone application.

RESULTS

We recruited the women in both cohorts at a median of 14.2 weeks of pregnancy. The women with previous adverse pregnancy outcomes delivered earlier and more often through Caesarean section compared with the women with normal obstetric histories. We found differences in subjective stress between the cohorts in pregnancy weeks 29 and 34. The cohort of women with previous adverse pregnancy outcomes had a higher root mean square of successive differences between normal heartbeats (RMSSD), a well-known HRV parameter, compared with the other cohort in pregnancy weeks 26 (64.9 vs 55.0, p = 0.04) and 32 (63.0 vs 52.3, p = 0.04). Subjective stress did not correlate with HRV parameters.

CONCLUSIONS

Women with previous adverse pregnancy outcomes do not suffer from stress in subsequent pregnancies more than women with normal obstetric histories. Healthcare professionals need to be aware that interindividual variation in stress during pregnancy is considerable.

Pre-partum HRV as a predictor of postpartum depression: The potential use of a smartphone application for physiological recordings

BACKGROUND

This study aimed to investigate the role of a time-domain Heart Rate Variability index (the root mean square of successive difference between NN intervals, rMSSD) as a predictor of the onset of postpartum depression. HRV has been related to an increased risk of depression in the general population. However, its role in pregnant women is not clear, and the potential use of smartphone applications to evaluate HRV in this population has not been investigated.

METHODS

In study 1, simultaneous electrocardiogram and smartphone photoplethysmography were collected. The rMSSD was determined from each recording to evaluate the accuracy of a smartphone application in the measurement of HRV. In study 2, 135 pregnant women provided rMSSD values measured through a smartphone application in the prepartum (second or third trimester) and filled in the Edinburgh Postnatal Depression Scale in the postpartum (one month after the childbirth).

RESULTS

Study 1 showed the excellent accuracy of the smartphone application in the measurement of rMSSD. Study 2 indicated that lower prepartum rMSSD predicted higher depressive symptoms in the postpartum (β = -0.217, p = 0.010) after controlling for prepartum depressive symptoms and other potential covariates.

LIMITATIONS

Artefacts (e.g., hand movements) might have corrupted the physiological signal registered.

CONCLUSION

This study showed that a reduced vagal tone, indexed by lower rMSSD, during pregnancy was a predictor of depressive symptoms one month after childbirth. The prepartum period may offer an important timeframe to implement preventive intervention on vagal modulation in order to prevent depressive symptoms in the postpartum.

Prenatal stress assessment using heart rate variability and salivary cortisol: A machine learning-based approach

OBJECTIVE

To develop a machine learning algorithm utilizing heart rate variability (HRV) and salivary cortisol to detect the presence of acute stress among pregnant women that may be applied to future clinical research.

METHODS

ECG signals and salivary cortisol were analyzed from 29 pregnant women as part of a crossover study involving a standardized acute psychological stress exposure and a control non-stress condition. A filter-based features selection method was used to identify the importance of different features [heart rate (HR), time- and frequency-domain HRV parameters and salivary cortisol] for stress assessment and reduce the computational complexity. Five machine learning algorithms were implemented to assess the presence of stress with and without salivary cortisol values.

RESULTS

On graphical visualization, an obvious difference in heart rate (HR), HRV parameters and cortisol were evident among 17 participants between the two visits, which helped the stress assessment model to distinguish between stress and non-stress exposures with greater accuracy. Eight participants did not display a clear difference in HR and HRV parameters but displayed a large increase in cortisol following stress compared to the non-stress conditions. The remaining four participants did not demonstrate an obvious difference in any feature. Six out of nine features emerged from the feature selection method: cortisol, three time-domain HRV parameters, and two frequency-domain parameters. Cortisol was the strongest contributing feature, increasing the assessment accuracy by 10.3% on average across all five classifiers. The highest assessment accuracy achieved was 92.3%, and the highest average assessment accuracy was 76.5%.

CONCLUSION

Salivary cortisol contributed a significant increase in accuracy of the assessment model compared to using a range of HRV parameters alone. Our machine learning model demonstrates acceptable accuracy in detection of acute stress among pregnant women when combining salivary cortisol with HR and HRV parameters.

A Technology-Based Pregnancy Health and Wellness Intervention (Two Happy Hearts): Case Study

BACKGROUND

The physical and emotional well-being of women is critical for healthy pregnancy and birth outcomes. The Two Happy Hearts intervention is a personalized mind-body program coached by community health workers that includes monitoring and reflecting on personal health, as well as practicing stress management strategies such as mindful breathing and movement.

OBJECTIVE

The aims of this study are to (1) test the daily use of a wearable device to objectively measure physical and emotional well-being along with subjective assessments during pregnancy, and (2) explore the user's engagement with the Two Happy Hearts intervention prototype, as well as understand their experiences with various intervention components.

METHODS

A case study with a mixed design was used. We recruited a 29-year-old woman at 33 weeks of gestation with a singleton pregnancy. She had no medical complications or physical restrictions, and she was enrolled in the Medi-Cal public health insurance plan. The participant engaged in the Two Happy Hearts intervention prototype from her third trimester until delivery. The Oura smart ring was used to continuously monitor objective physical and emotional states, such as resting heart rate, resting heart rate variability, sleep, and physical activity. In addition, the participant self-reported her physical and emotional health using the Two Happy Hearts mobile app-based 24-hour recall surveys (sleep quality and level of physical activity) and ecological momentary assessment (positive and negative emotions), as well as the Perceived Stress Scale, Center for Epidemiologic Studies Depression Scale, and State-Trait Anxiety Inventory. Engagement with the Two Happy Hearts intervention was recorded via both the smart ring and phone app, and user experiences were collected via Research Electronic Data Capture satisfaction surveys. Objective data from the Oura ring and subjective data on physical and emotional health were described. Regression plots and Pearson correlations between the objective and subjective data were presented, and content analysis was performed for the qualitative data.

RESULTS

Decreased resting heart rate was significantly correlated with increased heart rate variability (r=-0.92, P<.001). We found significant associations between self-reported responses and Oura ring measures: (1) positive emotions and heart rate variability (r=0.54, P<.001), (2) sleep quality and sleep score (r=0.52, P<.001), and (3) physical activity and step count (r=0.77, P<.001). In addition, deep sleep appeared to increase as light and rapid eye movement sleep decreased. The psychological measures of stress, depression, and anxiety appeared to decrease from baseline to post intervention. Furthermore, the participant had a high completion rate of the components of the Two Happy Hearts intervention prototype and shared several positive experiences, such as an increased self-efficacy and a normal delivery.

CONCLUSIONS

The Two Happy Hearts intervention prototype shows promise for potential use by underserved pregnant women.