Phenotyping stress exposures related to perinatal health disparities

Depression screening may not capture significant sources of prenatal stress for Black women

Exposure to stress during pregnancy, including depression, has a significant impact on maternal health. Black women experience varied stressors that impact pregnancy outcomes. Although the move to engage in universal screening of women for depression is a positive step toward improving women's health, it has been deployed without a comprehensive examination of its utility for capturing exposure to other stressors with known associations with perinatal and neonatal health problems for Black women such as discrimination stress. In the present study, we examine the overlap between several sources of stress and a positive screen on the Edinburgh Postnatal Depression Scale (EPDS) in Black pregnant women. Data were gathered from a study examining the effects of stress on prenatal health (N = 168). Discrimination stress, structural and systemic racism stress, perceived stress, and partner abuse were measured using standardized questionnaires during pregnancy. Using a score of ≥ 13 to indicate probable depression the sensitivity of the EPDS to identify women who experienced high levels of discrimination stress (41.7%), structural and systemic racism (39.5%), perceived stress (63.4%), and partner abuse (45.2%) was suboptimal. Lowering the threshold for a positive screen on the EPDS to a score of 10 improved sensitivity but did not solve the problem of under-identification of women whose health is at risk. The focus on depression screening for pregnant women should be re-considered. A screening toolkit that more rigorously and broadly assesses risk and need for support and intervention is needed to improve perinatal health outcomes for Black women.

Psychological Well-being across the Perinatal Period: Life Satisfaction and Flourishing in a Longitudinal Study of Black and White American Women

Psychological well-being (life satisfaction and flourishing) during the perinatal period has implications for both maternal and child health. However, few studies have investigated the extent to which psychological well-being changes from preconception to postpartum periods, particularly among diverse samples of women. Using prospectively collected data from an ongoing longitudinal study, we investigated changes in two dimensions of psychological well-being from preconception to postpartum among 173 Black and White American women. Results showed that changes in life satisfaction (i.e., global quality of life) and flourishing (e.g., self-acceptance, sense of purpose) over the perinatal period were moderated by race. For life satisfaction, White women reported an increase from preconception to pregnancy with increased life satisfaction levels remaining stable from pregnancy to postpartum. However, Black women reported no changes in life satisfaction across these timepoints. In contrast, both Black and White women reported an increase in flourishing levels across the perinatal period, although the timing of these changes differed. Findings highlight a need for greater clinical and empirical attention to the way in which psychological well-being changes during the perinatal period to optimize health and inform strengths-based intervention targets.

Preconception stress exposure from childhood to adolescence and birth outcomes: The impact of stress type, severity and consistency

The negative effects of prenatal stress on offspring health are well established, but there remains little understanding of the influence of stress prior to conception despite known effects on biological systems that are important for a healthy pregnancy. Furthermore, operational definitions of stress vary considerably, and exposure is often characterized via summed, ordinal scales of events. We hypothesized that type, severity, and consistency of preconception stress would be associated with birthweight and gestational age (GA) at birth. Data were drawn from a subsample of participants in the 21-year longitudinal Pittsburgh Girls Study (PGS, N = 2,450) that has followed women annually since childhood. Prior work in the PGS derived three domains of stress exposure between ages 7-17 years related to subsistence (e.g., resource strain, overcrowding), safety (e.g., community violence, inter-adult aggression), and caregiving (e.g., separation, maternal depression). We tested the effects of dimensions of preconception stress on birthweight and GA among offspring of 490 PGS participants who delivered at age 18 or older (n = 490; 76% Black, 20% White, 4% Multiracial). Our hypotheses were partially supported with results varying by stress type and severity and by infant sex. Severity of preconception exposure to subsistence stress was prospectively associated with lower offspring birthweight (B = -146.94, SE = 69.07, 95% CI = -282.66, -11.22). The association between severity of caregiving stress in childhood and adolescence and GA at birth was moderated by infant sex (B = 0.85, SE = .41, 95% CI = 0.04, 1.66), suggesting greater vulnerability to this type of stress for male compared to female infants. Exposure to safety stressors did not predict birth outcomes. Infants of Black compared with White mothers had lower birthweight in all models regardless of preconception stress type, severity or consistency. However, we observed no moderating effects of race on preconception stress-birth outcome associations. Demonstrating specificity of associations between preconception stress exposure and prenatal health has the potential to inform preventive interventions targeting profiles of exposure to optimize birth outcomes.

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.