Hostname: page-component-cd9895bd7-fscjk Total loading time: 0 Render date: 2024-12-23T15:29:38.855Z Has data issue: false hasContentIssue false

The association between history of prenatal loss and maternal psychological state in a subsequent pregnancy: an ecological momentary assessment (EMA) study

Published online by Cambridge University Press:  15 June 2021

Claudia Lazarides
Affiliation:
Institute of Medical Psychology, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
Nora K. Moog
Affiliation:
Institute of Medical Psychology, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
Glenn Verner
Affiliation:
Institute of Medical Psychology, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
Manuel C. Voelkle
Affiliation:
Faculty of Life Science, Department of Psychology, Psychological Research Methods, Humboldt-University of Berlin, Berlin, Germany
Wolfgang Henrich
Affiliation:
Department of Obstetrics, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
Christine M. Heim
Affiliation:
Institute of Medical Psychology, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
Thorsten Braun
Affiliation:
Department of Obstetrics, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
Pathik D. Wadhwa
Affiliation:
Development, Health and Disease Research Program, University of California, Irvine, CA, USA
Claudia Buss
Affiliation:
Institute of Medical Psychology, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany Development, Health and Disease Research Program, University of California, Irvine, CA, USA Department of Pediatrics, University of California, Irvine, CA, USA
Sonja Entringer*
Affiliation:
Institute of Medical Psychology, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany Development, Health and Disease Research Program, University of California, Irvine, CA, USA Department of Pediatrics, University of California, Irvine, CA, USA
*
Author for correspondence: Sonja Entringer, E-mail: [email protected]
Rights & Permissions [Opens in a new window]

Abstract

Background

Prenatal loss which occurs in approximately 20% of pregnancies represents a well-established risk factor for anxiety and affective disorders. In the current study, we examined whether a history of prenatal loss is associated with a subsequent pregnancy with maternal psychological state using ecological momentary assessment (EMA)-based measures of pregnancy-specific distress and mood in everyday life.

Method

This study was conducted in a cohort of N = 155 healthy pregnant women, of which N = 40 had a history of prenatal loss. An EMA protocol was used in early and late pregnancy to collect repeated measures of maternal stress and mood, on average eight times per day over a consecutive 4-day period. The association between a history of prenatal loss and psychological state was estimated using linear mixed models.

Results

Compared to women who had not experienced a prior prenatal loss, women with a history of prenatal loss reported higher levels of pregnancy-specific distress in early as well as late pregnancy and also were more nervous and tired. Furthermore, in the comparison group pregnancy-specific distress decreased and mood improved from early to late pregnancy, whereas these changes across pregnancy were not evident in women in the prenatal loss group.

Conclusion

Our findings suggest that prenatal loss in a prior pregnancy is associated with a subsequent pregnancy with significantly higher stress and impaired mood levels in everyday life across gestation. These findings have important implications for designing EMA-based ambulatory, personalized interventions to reduce stress during pregnancy in this high-risk group.

Type
Original Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re- use, distribution and reproduction, provided the original article is properly cited.
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press

Background

The prevalence among women of childbearing age of prenatal loss, the loss of an unborn child during pregnancy through miscarriage or stillbirth, is substantial, with one out of five women experiencing a miscarriage (loss of an embryo or fetus before the 20th week of gestation), and one out of 160 women experiencing a stillbirth (loss of a fetus occurring after the 20th week of gestation and a weight above 500 g) (Blencowe et al., Reference Blencowe, Cousens, Jassir, Say, Chou, Mathers and Hogan2016; El Hachem et al., Reference El Hachem, Crepaux, May-Panloup, Descamps, Legendre and & Bouet2017; Lawn et al., Reference Lawn, Blencowe, Waiswa, Amouzou, Mathers, Hogan and Flenady2016; MacDorman, Kirmeyer, & Wilson, Reference MacDorman, Kirmeyer and Wilson2012; Murphy et al., Reference Murphy, Mathews and Martin2017; Price, Reference Price2006). The negative consequences on women's mental health of losing an unborn child have been reported in several studies: prenatal loss is related to a higher risk for psychiatric disorders such as post-traumatic stress disorder, anxiety disorders, and major depression (reviewed in Engelhard, van den Hout, & Arntz, Reference Engelhard, van den Hout and Arntz2001; Farren et al., Reference Farren, Jalmbrant, Ameye, Joash, Mitchell-Jones, Tapp and Timmerman2016, Reference Farren, Mitchell-Jones, Verbakel, Timmerman, Jalmbrant and Bourne2018, Reference Farren, Jalmbrant, Falconieri, Mitchell-Jones, Bobdiwala, Al-Memar and Tapp2020; Horesh, Nukrian, & Bialik, Reference Horesh, Nukrian and Bialik2018; Hughes, Turton, & Evans, Reference Hughes, Turton and Evans1999; Jacob, Polly, Kalder, & Kostev, Reference Jacob, Polly, Kalder and Kostev2017; Turton, Evans, & Hughes, Reference Turton, Evans and Hughes2009). Over 80% of women who experience prenatal loss become pregnant within the subsequent 12-month period (Regan et al., Reference Regan, Gissler, Magnus, Håberg, Ball, Malacova and Nassar2019; Sundermann, Hartmann, Jones, Torstenson, & Velez Edwards, Reference Sundermann, Hartmann, Jones, Torstenson and Velez Edwards2017), and it is therefore likely that the negative effects of prenatal loss on maternal psychological well-being may extend to the subsequent pregnancy. Given the prominent role of maternal psychological state during pregnancy in many critical pregnancy, birth and offspring developmental and health outcomes (Bale et al., Reference Bale, Baram, Brown, Goldstein, Insel, McCarthy and Nemeroff2010; Buss, Entringer, & Wadhwa, Reference Buss, Entringer and Wadhwa2012; Entringer, Reference Entringer2013; Entringer, Buss, & Wadhwa, Reference Entringer, Buss and Wadhwa2012; Entringer, de Punder, Buss, & Wadhwa, Reference Entringer, de Punder, Buss and Wadhwa2018; Giannandrea, Cerulli, Anson, & Chaudron, Reference Giannandrea, Cerulli, Anson and Chaudron2013; Heim, Entringer, & Buss, Reference Heim, Entringer and Buss2019; Wadhwa, Entringer, Buss, & Lu, Reference Wadhwa, Entringer, Buss and Lu2011), it is crucially important to determine the relationship of a previous prenatal loss on maternal psychological well-being during a subsequent pregnancy.

Previous studies on the association between prenatal loss and maternal psychological state in a subsequent pregnancy have focused primarily on maternal anxiety and depression (Hughes et al., Reference Hughes, Turton and Evans1999; Hunter, Tussis, & MacBeth, Reference Hunter, Tussis and MacBeth2017; Turton et al., Reference Turton, Evans and Hughes2009). These previous studies have several limitations. First, the majority of these studies have focused on clinical diagnoses of psychiatric disorders (Blackmore et al., Reference Blackmore, Cote-Arsenault, Tang, Glover, Evans, Golding and O'Connor2011; Gong et al., Reference Gong, Hao, Tao, Zhang, Wang and Xu2013; Turton, Hughes, Evans, & Fainman, Reference Turton, Hughes, Evans and Fainman2001), thereby precluding the ascertainment of whether this relationship is evident with variation in maternal psychosocial distress and affective state along a continuum, potentially below clinical thresholds. The clinical relevance of maternal psychological state in pregnancy is not restricted to psychopathology but is evident along a continuum (reviewed in Burgueno, Juarez, Genaro, & Tellechea, Reference Burgueno, Juarez, Genaro and Tellechea2020; Graignic-Philippe, Dayan, Chokron, Jacquet, and Tordjman, Reference Graignic-Philippe, Dayan, Chokron, Jacquet and Tordjman2014; Lautarescu, Craig, & Glover, Reference Lautarescu, Craig, Glover, Clow and Smyth2020; Tarabulsy et al. Reference Tarabulsy, Pearson, Vaillancourt-Morel, Bussieres, Madigan, Lemelin and Duchesneau2014; Wadhwa et al. Reference Wadhwa, Entringer, Buss and Lu2011; Walsh et al. Reference Walsh, McCormack, Webster, Pinto, Lee, Feng and Krakovsky2019).

Second, previous study on the association of prenatal loss with maternal psychological well-being has relied exclusively on the use of traditional, retrospective recall-based measures to characterize maternal psychological state (for a meta-analytic overview, refer Campbell-Jackson & Horsch, Reference Campbell-Jackson and Horsch2014; Hunter et al. Reference Hunter, Tussis and MacBeth2017). Respondents are typically asked to rate how stressed, anxious, or depressed they have felt over the past week/month/since the beginning of their pregnancy. These traditional measures are prone to retrospective recall bias (Podsakoff, MacKenzie, & Podsakoff, Reference Podsakoff, MacKenzie and Podsakoff2012), thereby limiting their validity. In addition, most participants are asked to fill out the questionnaires in either a clinical or research laboratory setting, thereby potentially limiting their generalizability (ecological validity) to everyday real-life situations and circumstances.

Third, the majority of previous studies have incorporated only one measurement time point, in either early or late pregnancy; only 4 of 19 previous studies have used a longitudinal study design (Hunfeld, Agterberg, Wladimiroff, & Passchier, Reference Hunfeld, Agterberg, Wladimiroff and Passchier1996; Robertson-Blackmore et al., Reference Robertson-Blackmore, Putnam, Rubinow, Matthieu, Hunn, Putnam and Moynihan2013; Tsartsara & Johnson, Reference Tsartsara and Johnson2006; Woods-Giscombe, Lobel, & Crandell, Reference Woods-Giscombe, Lobel and Crandell2010; refer recent meta-analysis by Hunter et al., Reference Hunter, Tussis and MacBeth2017). It may be particularly important to assess maternal psychological state longitudinally across pregnancy because the association between history of prenatal loss and maternal psychological state may change across the course of gestation. Once the critical hallmark of 20th week of gestation is passed the risk for prenatal loss decreases significantly (ACOG, 2018; Ammon Avalos, Galindo, & Li, Reference Ammon Avalos, Galindo and Li2012; Mukherjee, Velez Edwards, Baird, Savitz, & Hartmann, Reference Mukherjee, Velez Edwards, Baird, Savitz and Hartmann2013), potentially contributing to improvements in maternal well-being in the second half of pregnancy. This issue may have clinical relevance because studies of the effects of maternal stress during pregnancy have reported differential effects depending on the gestational time window of its occurrence (Buss et al., Reference Buss, Entringer, Reyes, Chicz-DeMet, Sandman, Waffarn and Wadhwa2009, Reference Buss, Davis, Shahbaba, Pruessner, Head and Sandman2012a, Reference Buss, Entringer and Wadhwa2012b; Davis, Head, Buss, & Sandman, Reference Davis, Head, Buss and Sandman2017; Entringer et al., Reference Entringer, Buss, Rasmussen, Lindsay, Gillen, Cooper and Wadhwa2016).

Fourth, several of the previous studies are limited in terms of study design, particularly the lack of appropriate comparison groups. For example, some studies have included in the comparison group a combination of women who were pregnant for the first time and also women who were pregnant at least one time before the current (index) pregnancy, whereas the group of women with a history of prenatal loss include, obviously, only multigravida (women who were pregnant at least once before), and these studies did not adjust for gravida or parity status (Abbaspoor, Razmju, & Hekmat, Reference Abbaspoor, Razmju and Hekmat2016; Bicking Kinsey, Baptiste-Roberts, Zhu, & Kjerulff, Reference Bicking Kinsey, Baptiste-Roberts, Zhu and Kjerulff2015; Cumming et al., Reference Cumming, Klein, Bolsover, Lee, Alexander, Maclean and Jurgens2007; Farren et al., Reference Farren, Jalmbrant, Ameye, Joash, Mitchell-Jones, Tapp and Timmerman2016, Reference Farren, Mitchell-Jones, Verbakel, Timmerman, Jalmbrant and Bourne2018; Volgsten, Jansson, Svanberg, Darj, & Stavreus-Evers, Reference Volgsten, Jansson, Svanberg, Darj and Stavreus-Evers2018). Because the event/experience of a prior pregnancy might be associated with biological and psychological changes (Armstrong, Hutti, & Myers, Reference Armstrong, Hutti and Myers2009), this could potentially confound the association between history of prenatal loss and psychological state in a subsequent pregnancy. We note that in the current study we addressed this issue by including parity status as a covariate in all analysis. In addition, we conducted a sensitivity analysis by examining the effect of prenatal loss on our study outcomes in the study's subpopulation of multigravid women.

Fifth, several studies have failed to account for other important potential confounders associated with both risk for prenatal loss and impairments in mental well-being, such as sociodemographic factors (e.g. income, maternal age) and obstetric characteristics (e.g. obstetric risk factors; Blackmore et al., Reference Blackmore, Cote-Arsenault, Tang, Glover, Evans, Golding and O'Connor2011) EMA methods can address several of these above-discussed limitations by employing repeated real-time measurements of psychological states in participants' natural daily environments, thereby minimize biases associated with retrospective recall measures to provide more accurate and ecologically valid measures of psychological/behavioral states (Smyth & Stone, Reference Smyth and Stone2003). Thus, the aim of the current study was to examine the association of history of prenatal loss with assessments during a subsequent pregnancy in early as well as late gestation of maternal psychological state (maternal momentary pregnancy-specific distress and mood) using EMA methods.

Materials and methods

Participants

The study was conducted at the Institute of Medical Psychology and the Department of Obstetrics at the Charité Universtitaetsmedizin Berlin, Germany. Women with a singleton, intrauterine pregnancy were recruited prior to 16 weeks gestation. Exclusion criteria were twin pregnancies, uterine, placental/cord anomalies, fetal congenital malformations, and systemic corticosteroid intake. The study protocol included two study visits at the laboratory during early (T1: 12–16 weeks gestation) and late pregnancy (T2: 30–34 weeks gestation), followed by a 4-day EMA period, as described below. The Charité Institutional Review Board approved the study, and all participants provided written, informed consent.

The characteristics of the study participants are presented in Table 1. Miscarriage was defined as the loss of an unborn child during a recognized pregnancy before the 20th week of gestation, and if gestational age (GA) is not available, fetal weight equal or below 500 g (Farquharson, Jauniaux, Exalto, & Pregnancy, Reference Farquharson, Jauniaux, Exalto and Pregnancy2005). Prenatal losses occurring after the 20th week of gestation and a weight above 500 g were termed stillbirths (Tavares Da Silva et al., Reference Tavares Da Silva, Gonik, McMillan, Keech, Dellicour, Bhange and Tila2016). In total, 25.8% of the participating women reported the experience of prenatal loss, either miscarriage or stillbirth, in a previous pregnancy (N = 40). 5.8% reported two prenatal losses, and 1.9% reported more than two prenatal losses (N = 3) in their reproductive history. The prevalence of obstetric complications during pregnancy was low in our study population (5.8%).

Table 1. Maternal sociodemographic and obstetric characteristics

Note: Due to rounding, some totals may not correspond with the sum of the separate figures.

a income ranges based on KIGGs study's sociodemographic index (Lampert, Hoebel, & Kuntz, Reference Lampert, Hoebel and Kuntz2018).

Measures

Maternal characteristics

At each visit, trained study personnel conducted structured interviews to obtain information on sociodemographic characteristics and reproductive history (e.g. gravidity, parity, number of previous pregnancy losses), and estimated date of conception. GA at visit was computed based on early ultrasound measurements. Data on obstetric risk factors were abstracted from the medical record.

EMA-based measures of maternal psychological state

We assessed momentary maternal pregnancy-specific distress and mood using an EMA protocol for ambulatory, real-time measurement of affective states. The EMA protocol was delivered through the mobile phone application movisensXS (movisensXS; movisens, Reference movisens2020). The 4-day EMA protocol spanned two consecutive weekdays and a weekend (Thursday–Sunday, or Saturday–Tuesday). Participants were provided a smartphone with an electronic diary application. Throughout the EMA period, participants were prompted on average eight times per day (prompts were between 30 and 90 min apart between the hours of 8AM and 8PM).

Pregnancy-specific distress (PSD_mean; Rini, Dunkel-Schetter, Wadhwa, & Sandman, Reference Rini, Dunkel-Schetter, Wadhwa and Sandman1999) was assessed by inquiring about the woman's feelings (happiness and ambivalence) about being pregnant, her concerns about the baby's health, bodily discomfort due to pregnancy-related changes, and concerns about giving birth. Women rated these items on a Likert scale ranging from 0 to 5 (‘not at all’ to ‘completely’). Participants' ratings at each prompt were aggregated across all items and average scores were computed. The measure of pregnancy-specific stress was chosen for this study because measures that assess distress in a specific area of life may better reflect individual responses to these conditions than global stress questionnaires (Bussières et al., Reference Bussières, Tarabulsy, Pearson, Tessier, Forest and Giguère2015; Stanton, Lobel, Sears, & DeLuca, Reference Stanton, Lobel, Sears and DeLuca2002). This pregnancy-specific distress measure has previously been linked to pregnancy and offspring outcomes (e.g. Buss, Davis, Muftuler, Head, & Sandman, Reference Buss, Davis, Muftuler, Head and Sandman2010; Glynn, Schetter, Hobel, & Sandman, Reference Glynn, Schetter, Hobel and Sandman2008).

Maternal momentary mood was measured by the multidimensional mood questionnaire (MDBF) developed for daily diary research and validated for EMA studies (Courvoisier, Eid, & Lischetzke, Reference Courvoisier, Eid and Lischetzke2012; Courvoisier, Eid, Lischetzke, & Schreiber, Reference Courvoisier, Eid, Lischetzke and Schreiber2010; Hinz, Daig, Petrowski, & Brahler, Reference Hinz, Daig, Petrowski and Brahler2012; Steyer, Schwenkmezger, Notz, & Eid, Reference Steyer, Schwenkmezger, Notz and Eid1994). Participants rated their momentary mood along three dimensions: valence (good–bad mood, GB), arousal (calmness–nervousness, CN), and tiredness (alertness–tiredness, AT) on 12 items, four items for each dimension, with a balanced number of negatively worded and positively worded items. Items were rated on a 6-point Likert scale ranging from 0 to 5 (‘not at all’ to ‘completely’). Positively worded items were reversed before aggregating answers to derive an average score for each dimension (good–bad mood: GB_mean, calm–nervous: CN_mean, alert–tired: AT_mean) for each prompt. The derived original scores were reversed to ease the interpretation of the results such that higher average scores for each dimension indicate an unfavorable affective state (bad mood, nervous, tired), and lower average scores indicate favorable affective states (good mood, calm, alert).

Statistical analysis

We performed all statistical analyses in R version 3.5.1 (R Development Core Team, 2018). The R-package nlme version 3.1-137 was used for linear mixed model analyses (Pinheiro, Bates, DebRoy, Sarkar, & R Core Team, Reference Pinheiro, Bates, DebRoy, Sarkar and Core Team2018).

Variance decomposition of momentary measures

We used linear mixed(-effect) models (LMMs; cf. multilevel models) to identify the proportion of variance at the different levels of the data (momentary, day, stage of pregnancy and participant level; Snijders & Bosker, Reference Snijders and Bosker2012) with regard to pregnancy-specific distress and the three mood dimensions (valence, arousal, and tiredness). The applied analytical procedure has been described in detail elsewhere (Lazarides et al., Reference Lazarides, Ward, Buss, Chen, Voelkle, Gillen and Wadhwa2020). In four separate 4-level random intercept LMMs, the percentage of total variance for pregnancy-specific distress, valence, arousal, and tiredness was computed at the level of the momentary measurements (level 1), days (level 2), stages of pregnancy (level 3), and participants (level 4). To account for the unequal spacing of the auto-correlated measurements across a day a continuous time-autoregressive covariance structure of order one was specified using time since wake in minutes (Goldstein, Healy, & Rasbash, Reference Goldstein, Healy and Rasbash1994; Jones, Reference Jones1993; Littell, Milliken, Stroup, Wolfinger, & Oliver, Reference Littell, Milliken, Stroup, Wolfinger and Oliver2006). Restricted maximum likelihood was used for parameter estimation (for R code, see online Supplement A1).

Linear mixed models

EMA-based measures. To examine the effect of history of prenatal loss on pregnancy-specific distress and momentary maternal mood along the three dimensions valence, arousal, and tiredness, four separate 4-level LMMs were fitted to the nested data with the same random effect structure as described for the variance decomposition of EMA-based measures. We used the same continuous-autoregressive covariance structure to account for unequal temporal spacing of the momentary measurements. The exemplary R code is provided in online Supplement A2. Prenatal loss status (history of prenatal loss yes/no) was used as a dichotomous predictor. Relevant covariates (described below) were included as fixed effects in all models.

Moderation by stage of pregnancy. To explore how potential differences in psychological state between women with and without a history of prenatal loss may change with advancing gestation, we included the interaction term between stage of pregnancy (i.e. visit number, T1 and T2) and prenatal loss status in the linear mixed models described above (R code, see online Supplement A3).

Sensitivity analysis. The control group included women who were pregnant for the first time and women who were pregnant at least one time before the current pregnancy, whereas the group of women with a history of prenatal loss included only multigravida (multigravida = women that were pregnant at least once before). Because the experience of prior pregnancy may be associated with biological and psychological changes (Armstrong et al., Reference Armstrong, Hutti and Myers2009), this could introduce heterogeneity in the control group and limit the validity of reported differences in psychological well-being between women with and without prenatal loss. We therefore conducted a sensitivity analysis by testing our hypothesis in only multi-gravid women.

Covariates

All analyses were adjusted for the effects of potential confounders that have previously been associated with the risk for prenatal loss and impaired psychological well-being, including maternal age, parity (not included as a covariate in the sensitivity analyses), obstetric risk factors, and income (Magnus, Wilcox, Morken, Weinberg, & Haberg, Reference Magnus, Wilcox, Morken, Weinberg and Haberg2019). The following covariates were included as fixed effects in all described LMMs (R code, see online Supplement A1): stage of pregnancy (early – T1 v. late pregnancy – T2), maternal age at first visit, income, parity category (0 – nulliparous, 1 – multiparous; not included in sensitivity analyses described above), obstetric risk factor (presence of any of the following conditions during the current pregnancy: preeclampsia, hypertension, gestational diabetes coded with ‘1’, no obstetric risk factors present coded with ‘0’).

Compliance and handling of missing data

Given the EMA protocol, each time a participant refrained from answering a prompt, declined to answer, ignored a prompt or did not conclude the entire survey, the smartphone application recorded a missing value. To assess compliance, we calculated the percent of missing prompts of the total number of prompts. In the statistical analyses, missing data were accounted for by use of full information restricted maximum likelihood estimation (Little & Rubin, Reference Little and Rubin2002; Raudenbush & Bryk, Reference Raudenbush and Bryk2002). Thus, LMMs make use of all available data.

Results

EMA-based measures of maternal psychological state

Compliance

Compliance with the EMA protocol (number of missing prompts relative to the total number of prompts) was 86.3%, which is above the recommended 80% for EMA-studies, and also above average compliance of 75–78% previously reported in two meta-analyses comprised of 168 EMA studies (Jones et al., Reference Jones, Remmerswaal, Verveer, Robinson, Franken, Wen and Field2019; Wen, Schneider, Stone, & Spruijt-Metz, Reference Wen, Schneider, Stone and Spruijt-Metz2017).

Variance decomposition

The variance decomposition indicates the amount of the total variation in pregnancy-specific distress, valence, arousal, and tiredness that is derived from the different levels of the data (i.e. variation between individuals as well as within individuals, across the stages of pregnancy, across a day, and across moments; de Haan-Rietdijk, Kuppens, and Hamaker, Reference de Haan-Rietdijk, Kuppens and Hamaker2016; Schmiedek, Lovden, and Lindenberger, Reference Schmiedek, Lovden and Lindenberger2013). Based on the LMM, pregnancy-specific distress scores varied largely between individuals (68.4%) and to a lesser extent from moment to moment (12.1%), and from early to late pregnancy (16.9%), as well as to a small degree from day to day (5.1%; summary of results is given in online Supplementary Table S1, detailed results in online Supplementary Table S2). For the mood scales, GB_mean, CN_mean, and AT_mean, predominantly showed variation at the momentary level (48.8–54.3%) and between individuals (27.6–38.9%) rather than from day to day (7.1–10.2%) or from early to late pregnancy (3.7–5.9%; summary of results is given in online Supplementary Table S1, detailed results in online Supplementary Tables S3–S5). Intraclass correlation coefficients reflected this pattern of variation (online Supplementary Table S1).

Descriptive statistics

Summary statistics for pregnancy-specific distress and for each MDBF scale (valence, arousal, tiredness) are displayed separately for each time point (stage of pregnancy) in Table 2. Pregnancy-specific distress decreased slightly from early to late pregnancy in the whole sample. In general, mood improved from early to late gestation, as suggested by a decrease in mood valence (GB_mean), arousal (CN_mean) and level of tiredness (AT_mean) in the whole sample. The observed average and variation of mood scores are comparable with published norms for women in reproductive age (Hinz et al., Reference Hinz, Daig, Petrowski and Brahler2012; Steyer et al., Reference Steyer, Schwenkmezger, Notz and Eid1994; Steyer, Schwenkmezger, Notz, & Eid, Reference Steyer, Schwenkmezger, Notz and Eid1997).

Table 2. Summary statistics on valence (good – bad mood: GB_mean), arousal (calm – nervous: CN_mean), tiredness (alert – tired: AT_mean), and pregnancy-specific distress (PSD_mean), separately for each time point, T1 and T2

M, Mean; s.d., Standard deviation; N, Sample size at measurement time point.

History of prenatal loss and EMA measures of psychological state during pregnancy

An overview of the results of the linear mixed-effects model analysis is displayed in Table 3. More detailed results for each outcome are presented in online Supplementary Tables S6–S9.

Table 3. Results of linear mixed models predicting EMA-based pregnancy-specific distress (PSD_mean), and affective states (valence, GB_mean; arousal, CN_mean, tiredness, AT_mean) by stage of pregnancy and prenatal loss status

Note: Significance codes: p > 0.01 ‘ ’, p < 0.10 ‘.’, p < 0.05 ‘*’, p < 0.01 ‘**’, p < 0.001 ‘***’. Results displayed for log-transformed cortisol. Transformation did not change magnitude, direction nor significance level of the reported effects. For fit indices see online Supplementary Table S10.

Pregnancy-specific distress

There was a significant effect of history of prenatal loss on pregnancy-specific distress: women with a history of prenatal loss reported significantly higher levels of pregnancy-specific distress assessed at a momentary level, in early as well as in late gestation (B = 0.465, p = 0.004, online Supplementary Table S6). On average, women with a history of prenatal loss reported 0.465-unit higher levels of pregnancy-specific distress on a scale from to those without a history of prenatal loss.

Mood valence, arousal, and tiredness

There was no significant main effect of prenatal loss status on mood valence (GB_mean) albeit mood was slightly impaired in women with a history of prenatal loss compared to those without across the course of pregnancy (B = 0.214, p = 0.070, online Supplementary Table S7). Arousal was positively associated with prenatal loss status (CN_mean: B = 0.247, p = 0.047, online Supplementary Table S8): across gestation, women with a history of prenatal loss showed increased arousal compared to women without prenatal loss, and were more tired (AT_mean: B = 0.293, p = 0.026, online Supplementary Table S9). Women with prenatal loss showed on average a 0.247-unit higher level of arousal and a 0.270-unit higher level of tiredness.

Moderation of the association between history of prenatal loss and EMA measures of psychological state by stage of pregnancy

There was no main effect of stage of pregnancy on levels of pregnancy-specific distress (PSD_mean: B = −0.0002, p = 0.997, online Supplementary Table S6). However, the moderation analysis revealed a significant positive interaction effect between stage of pregnancy and prenatal loss status (PSD_mean: B = 0.314, p = 0.012). As displayed in Fig. 1, pregnancy-specific distress decreased from early to late gestation in women without a history of prenatal loss, whereas it increased in women with a history of prenatal loss.

Fig. 1. Grouped bar plot of EMA-based pregnancy-specific distress by history of prenatal loss in previous pregnancy and stage of pregnancy (mean ± 2 standard error bars).

Across the whole sample, momentary maternal mood including valence (impaired mood), arousal, and tiredness decreased significantly across pregnancy (GB_mean: B = −0.110, p = 0.003; CN_mean: B = −0.118, p = 0.003; AT_mean: B = −0.100, p = 0.042; online Supplementary Tables S7–S9), indicating a general improvement of mood across the whole sample. We therefore conducted a moderation analysis to test if the effect of prenatal loss on mood dimensions was moderated by the stage of pregnancy. The moderation analysis revealed a significant interaction effect of stage of pregnancy and prenatal loss status on arousal (CN_mean: B = 0.184, p = 0.045, Fig. 2). Women without a history of prenatal loss reported lower levels of arousal in late compared to early gestation, while levels did not decrease in women with a history of prenatal loss. There was no significant interaction effect of stage of pregnancy and prenatal loss status on mood valence and tiredness (GB_mean: B = 0.142, p = 0.090; AT_mean: B = 0.116, p = 0.317).

Fig. 2. Grouped bar plot displaying EMA-based arousal by history of prenatal loss in previous pregnancy and stage of pregnancy (mean ± 2 standard error bars).

Sensitivity analysis

When considering only women who were pregnant at least one time before the current pregnancy (40 women with and 39 without a history of prenatal loss), most of the previously reported effects remained unchanged in direction, magnitude, and significance level. Specifically, women with a history of prenatal loss reported higher levels of pregnancy-specific distress (PSD_mean: B = 0.482, p = 0.039), and were more nervous (CN_mean: B = 0.359, p = 0.037), more tired (AT_mean: B = 0.494, p = 0.003), across pregnancy compared to women without prenatal loss. Furthermore, there was a trend for an effect of prenatal loss status on mood valence when only including multigravid women. Women with a history of prenatal loss reported impaired mood compared to women without prenatal loss (GB_mean: B = 0.294, p = 0.081).

Discussion

To the best of our knowledge, this is the first study to use the EMA approach to comprehensively (i.e. serially, at a momentary level, across everyday life situations) quantify and compare stress and mood levels and trajectories in pregnancy in women with and without a prior history of prenatal loss. Our findings indicate that women with a prior history of prenatal loss experienced significantly more pregnancy-related stress and felt significantly more nervous and tired compared to those who have not previously experienced a prenatal loss. Moreover, our results suggest that these differences persisted and even grew or became amplified as pregnancy progressed. Maternal levels of stress and negative affect progressively decreased over the course of pregnancy in women without a history of prenatal loss, whereas they did not change or even increased in women with a prior history of prenatal loss. The magnitude of this observed difference is striking. Women in the prior prenatal loss group exhibited, on average, 38.6% more pregnancy-specific stress, 18.3% more arousal, and 15.5% more exhaustion than those in the comparison groupFootnote Footnote 1. The present study was not designed to address the clinical relevance of observed findings. Because the vast majority of studies of the effects of maternal stress in pregnancy have relied on the more traditional retrospective recall approach to quantify stress, as opposed to the EMA approach used in the current study, it is difficult to directly extrapolate clinical significance. We note, nevertheless, that several previous studies have reported that differences of comparable or even smaller magnitude in maternal stress during and/or across pregnancy have been independently associated with a range of adverse maternal, birth and child developmental and health outcomes, including premature birth, newborn and infant adiposity, neurodevelopmental deficits, and even cellular measures of aging (telomere length) (Buss et al., Reference Buss, Entringer and Wadhwa2012b; Entringer et al., Reference Entringer, de Punder, Buss and Wadhwa2018; Gyllenhammer, Entringer, Buss, & Wadhwa, Reference Gyllenhammer, Entringer, Buss and Wadhwa2020; Lindsay, Buss, Wadhwa, & Entringer, Reference Lindsay, Buss, Wadhwa and Entringer2018; Wadhwa et al., Reference Wadhwa, Entringer, Buss and Lu2011). Based on this observation we submit it is likely that the magnitude of the observed difference in maternal stress in the current study may portend clinical significance.

Our results are consistent with those of previous studies that find women report increased levels of post-traumatic stress, anxiety, and depression following pregnancy loss (Farren et al., Reference Farren, Jalmbrant, Ameye, Joash, Mitchell-Jones, Tapp and Timmerman2016, Reference Farren, Jalmbrant, Falconieri, Mitchell-Jones, Bobdiwala, Al-Memar and Tapp2020; Hughes et al., Reference Hughes, Turton and Evans1999; Turton et al., Reference Turton, Evans and Hughes2009). Across time, grief subsides and psychiatric disorders possibly remit, although, the emotional perturbations related to the experience of pregnancy loss remain (Kersting et al., Reference Kersting, Kroker, Steinhard, Ludorff, Wesselmann, Ohrmann and Arolt2007; Krosch & Shakespeare-Finch, Reference Krosch and Shakespeare-Finch2017; Volgsten et al., Reference Volgsten, Jansson, Svanberg, Darj and Stavreus-Evers2018). A subsequent pregnancy has the potential to reactivate the affective memories associated with the past prenatal loss (Haas & Canli, Reference Haas and Canli2008). The current study highlights the relevance of history of prenatal loss as a risk factor for increased prenatal stress in pregnancy and thus the potential negative consequences on pregnancy, birth and child development, and health outcomes.

In the current study, we observed an overall improvement across pregnancy in psychological well-being. This observation is consistent with recent evidence from a clinical population of pregnant women, who reported a decrease in psychopathological symptoms from early to late pregnancy (Asselmann, Kunas, Wittchen, & Martini, Reference Asselmann, Kunas, Wittchen and Martini2020). This general improvement of well-being and decrease in psychological stress may be associated with the attenuation of maternal biological stress responsivity across pregnancy (Entringer et al., Reference Entringer, Buss, Shirtcliff, Cammack, Yim, Chicz-DeMet and Sandman2010). However, in our study, women with a history of prenatal loss did not exhibit this decrease in stress and improvement in mood across pregnancy, which may be a consequence of their prior traumatic experience of losing a pregnancy and the resultant general feeling of uncontrollability. We have previously reported that the lack of stress attenuation across pregnancy is related to adverse pregnancy outcomes (Buss et al., Reference Buss, Entringer, Reyes, Chicz-DeMet, Sandman, Waffarn and Wadhwa2009).

We suggest that our study has several strengths. As of our knowledge, this is the first study to assess the effect of a history of prenatal loss on maternal psychological state in early and late pregnancy. We use EMA methods to assess maternal stress in women's everyday life in natural settings in contrast to previous research that exclusively relied on traditional retrospective questionnaires. Participants of the current study showed a high compliance with the EMA protocol. We assessed psychological state on a continuum, and relied on measures of mood and stress rather than focusing on clinical symptom categories or psychiatric diagnoses. We adjusted our analyses for the effect of important potential confounders, including sociodemographic factors, obstetric characteristics and number of previous pregnancies. By means of a sensitivity analysis within multigravida women only, we confirm the robustness of our results.

Some limitations of the current study need to be acknowledged. First, data on psychological state was available only for the current pregnancy, measures of psychological state prior to the initial prenatal loss were not available. Stress has been discussed as a risk factor for prenatal loss. However, previous studies investigating whether maternal psychological stress predicts prenatal loss have produced mixed results (Klebanoff, Shiono, & Rhoads, Reference Klebanoff, Shiono and Rhoads1990; Milad, Klock, Moses, & Chatterton, Reference Milad, Klock, Moses and Chatterton1998; Nelson et al., Reference Nelson, Grisso, Joffe, Brensinger, Shaw and Datner2003; Qu et al., Reference Qu, Wu, Zhu, Barry, Ding, Baio and Muscat2017). All our analyses were adjusted for covariates potentially associated with both risk for prenatal loss and maternal psychological state, including maternal age, parity, obstetric risk, and household income. Second, we were unable to test the effect of the number of previous prenatal losses on psychological state during pregnancy due to the relatively small number of women who miscarried more than once. Previous large cohort studies suggest that with increasing number of prenatal losses women report even higher levels of depression and anxiety (Blackmore et al., Reference Blackmore, Cote-Arsenault, Tang, Glover, Evans, Golding and O'Connor2011; Toffol, Koponen, & Partonen, Reference Toffol, Koponen and Partonen2013). We therefore submit that our findings may represent a conservative estimate of the true effect of history of prenatal loss on psychological state during pregnancy. Third, data on the length of inter-pregnancy intervals as well as on a whether or not women gave birth to a living child between the pregnancy loss and the current pregnancy were not available, and we were therefore unable to test the moderating effects of these variables. Previous studies suggest that the length of the inter-pregnancy interval does not affect the association between history of prenatal loss and depression and/or anxiety during a subsequent pregnancy or in the postpartum period (Gravensteen et al., Reference Gravensteen, Jacobsen, Sandset, Helgadottir, Radestad, Sandvik and Ekeberg2018; Schetter, Saxbe, Cheadle, & Guardino, Reference Schetter, Saxbe, Cheadle and Guardino2016). A large longitudinal cohort study reports a robust association between history of prenatal loss with increased levels of anxiety and depression during a subsequent pregnancy, which remained stable across the pre- and postnatal period of the index pregnancy, thereby indicating that the psychological impairment associated with previous prenatal loss might not attenuate significantly following the birth of a living child (Blackmore et al., Reference Blackmore, Cote-Arsenault, Tang, Glover, Evans, Golding and O'Connor2011). Fourth, EMA studies assess the participants' psychological state repeatedly across multiple days raising the issue of measurement reactivity. However, previous EMA studies have provided no evidence for measurement reactivity with regard to mood, craving, body image, and suicidal thoughts (Coppersmith, Reference Coppersmith2020; De Vuyst, Dejonckheere, Van der Gucht, & Kuppens, Reference De Vuyst, Dejonckheere, Van der Gucht and Kuppens2019; Heron & Smyth, Reference Heron and Smyth2013; Hufford, Shields, Shiffman, Paty, & Balabanis, Reference Hufford, Shields, Shiffman, Paty and Balabanis2002; Rowan et al., Reference Rowan, Cofta-Woerpel, Mazas, Vidrine, Reitzel, Cinciripini and Wetter2007).

The findings of our study suggest that women with a history of prenatal loss are at increased risk for experiencing higher levels of stress during pregnancy. Although, obstetric guidelines issued by the American College of Obstetricians and Gynecologists advice perinatal care providers to screen for postpartum depression, recommendations to not include screening for psychological stress (American Academy of Pediatrics & American College of Obstetricians and Gynecologists, 2017). Our results imply that pregnancy-specific distress might be a good screening tool for this purpose, since the effect on pregnancy loss on pregnancy specific distress in our study was substantial, and it primarily varied between individuals and may not have to be measured that frequently.

The current study underscores the importance of using EMA methods in assessing stress and mood in the context of pregnancy, which then could be used to design personalized interventions to reduce maternal stress. EMA-based measures of psychological states can be used to estimate subject-specific ‘moments at risk’, such as the deviation from the individual average stress level in a given moment, that have a higher predictive value for maternal cortisol levels during pregnancy than traditional approaches (Lazarides et al., Reference Lazarides, Ward, Buss, Chen, Voelkle, Gillen and Wadhwa2020). Future studies could test the efficacy of EMA-based targeted interventions in women with a history of prenatal loss. Given its substantial burden on maternal and offspring health, reducing stress during pregnancy in this high risk group could yield considerable public health benefit.

Supplementary material

The supplementary material for this article can be found at https://doi.org/10.1017/S0033291721002221

Financial support

This work was supported by European Research Council grants ERC-Stg 678073 and ERC-Stg 639766, and by NIH grants R01 HD-060628, R01 AG-050455, R01 HD-065825, UH3 OD-023349.

Conflict of interest

None.

Footnotes

The notes appear after the main text.

1 The reported percentages are based on the group means of the respective outcomes across measurement time points. These effect quantifications do not account for the nesting of the data, group sizes, variation within groups, and potential effect of covariates which were rather small in this sample. Therefore, these approximate effect sizes should be interpreted under these limitations.

References

Abbaspoor, Z., Razmju, P. S., & Hekmat, K. (2016). Relation between quality of life and mental health in pregnant women with prior pregnancy loss. The Journal of Obstetrics and Gynaecology Research, 42(10), 12901296. doi:10.1111/jog.13061.CrossRefGoogle ScholarPubMed
ACOG, C. (2018). Early pregnancy loss. American College of Obstetricians and Gynecologists, 132, e197–e207.Google Scholar
Kilpatrick, S. J., Papile, L.-A. & Macones, G. A. (Eds.). American Academy of Pediatrics – Committee on Fetus and Newborn & American College of Obstetricians and Gynecologists – Committee on Obstretric Practice: Guidelines for PERINATAL CARE 2017Google Scholar
Ammon Avalos, L., Galindo, C., & Li, D. K. (2012). A systematic review to calculate background miscarriage rates using life table analysis. Birth Defects Research (Part A): Clinical and Molecular Teratology, 94(6), 417423. doi:10.1002/bdra.23014.CrossRefGoogle ScholarPubMed
Armstrong, D. S., Hutti, M. H., & Myers, J. (2009). The influence of prior perinatal loss on parents’ psychological distress after the birth of a subsequent healthy infant. Journal of Obstetric, Gynecologic, and Neonatal Nursing, 38(6), 654666. doi:10.1111/j.1552-6909.2009.01069.x.CrossRefGoogle ScholarPubMed
Asselmann, E., Kunas, S. L., Wittchen, H. U., & Martini, J. (2020). Maternal personality, social support, and changes in depressive, anxiety, and stress symptoms during pregnancy and after delivery: A prospective-longitudinal study. PLoS One, 15(8), e0237609. doi:10.1371/journal.pone.0237609.CrossRefGoogle ScholarPubMed
Bale, T. L., Baram, T. Z., Brown, A. S., Goldstein, J. M., Insel, T. R., McCarthy, M. M., & Nemeroff, C. B. (2010). Early life programming and neurodevelopmental disorders. Biological Psychiatry, 68(4), 314319. doi:10.1016/j.biopsych.2010.05.028.CrossRefGoogle ScholarPubMed
Bicking Kinsey, C., Baptiste-Roberts, K., Zhu, J., & Kjerulff, K. H. (2015). Effect of previous miscarriage on depressive symptoms during subsequent pregnancy and postpartum in the first baby study. Maternal and Child Health Journal, 19(2), 391400. doi:10.1007/s10995-014-1521-0.CrossRefGoogle ScholarPubMed
Blackmore, E. R., Cote-Arsenault, D., Tang, W., Glover, V., Evans, J., Golding, J., & O'Connor, T. G. (2011). Previous prenatal loss as a predictor of perinatal depression and anxiety. The British Journal of Psychiatry, 198(5), 373378. doi:10.1192/bjp.bp.110.083105.CrossRefGoogle Scholar
Blencowe, H., Cousens, S., Jassir, F. B., Say, L., Chou, D., Mathers, C., & Hogan, D. (2016). National, regional, and worldwide estimates of stillbirth rates in 2015, with trends from 2000: A systematic analysis. The Lancet Global Health, 4(2), e98e108. doi:10.1016/s2214-109x(15)00275-2.CrossRefGoogle ScholarPubMed
Burgueno, A. L., Juarez, Y. R., Genaro, A. M., & Tellechea, M. L. (2020). Systematic review and meta-analysis on the relationship between prenatal stress and metabolic syndrome intermediate phenotypes. International Journal of Obesity, 44(1), 112. doi:10.1038/s41366-019-0423-z.CrossRefGoogle ScholarPubMed
Buss, C., Davis, E. P., Muftuler, L. T., Head, K., & Sandman, C. A. (2010). High pregnancy anxiety during mid-gestation is associated with decreased gray matter density in 6–9-year-old children. Psychoneuroendocrinology, 35(1), 141153. doi:10.1016/j.psyneuen.2009.07.010.CrossRefGoogle ScholarPubMed
Buss, C., Davis, E. P., Shahbaba, B., Pruessner, J. C., Head, K., & Sandman, C. A. (2012a). Maternal cortisol over the course of pregnancy and subsequent child amygdala and hippocampus volumes and affective problems. Proceedings of the National Academy of Sciences of the USA, 109(20), E1312E1319. doi:10.1073/pnas.1201295109.CrossRefGoogle ScholarPubMed
Buss, C., Entringer, S., Reyes, J. F., Chicz-DeMet, A., Sandman, C. A., Waffarn, F., & Wadhwa, P. D. (2009). The maternal cortisol awakening response in human pregnancy is associated with the length of gestation. American Journal of Obstetrics and Gynecology, 201(4), 398 e391398. doi:10.1016/j.ajog.2009.06.063.CrossRefGoogle ScholarPubMed
Buss, C., Entringer, S., & Wadhwa, P. D. (2012b). Fetal programming of brain development: Intrauterine stress and susceptibility to psychopathology. Science Signaling, 5(245), pt7. doi:10.1126/scisignal.2003406.Google ScholarPubMed
Bussières, E.-L., Tarabulsy, G. M., Pearson, J., Tessier, R., Forest, J.-C., & Giguère, Y. (2015). Maternal prenatal stress and infant birth weight and gestational age: A meta-analysis of prospective studies. Developmental Review, 36, 179199. doi:10.1016/j.dr.2015.04.001.CrossRefGoogle Scholar
Campbell-Jackson, L., & Horsch, A. (2014). The psychological impact of stillbirth on women: A systematic review. Illness, Crisis & Loss, 22(3), 237256. doi:10.2190/IL.22.3.d.CrossRefGoogle Scholar
Coppersmith, D. D. L. (2020). Frequent assessment of suicidal thinking does not increase suicidal thinking: Evidence from a high-resolution real-time monitoring study. Preprint from PsyArXiv. doi:10.31234/osf.io/6bh82.Google Scholar
Courvoisier, D. S., Eid, M., & Lischetzke, T. (2012). Compliance to a cell phone-based ecological momentary assessment study: The effect of time and personality characteristics. Psychological Assessment, 24(3), 713720. doi:10.1037/aO026733.CrossRefGoogle Scholar
Courvoisier, D. S., Eid, M., Lischetzke, T., & Schreiber, W. H. (2010). Psychometric properties of a computerized mobile phone method for assessing mood in daily life. Emotion (Washington, D.C.), 10(1), 115124. doi:10.1037/a0017813.CrossRefGoogle ScholarPubMed
Cumming, G. P., Klein, S., Bolsover, D., Lee, A. J., Alexander, D. A., Maclean, M., & Jurgens, J. D. (2007). The emotional burden of miscarriage for women and their partners: Trajectories of anxiety and depression over 13 months. BJOG An International Journal of Obstetrics and Gynaecology, 114(9), 11381145. doi:10.1111/j.1471-0528.2007.01452.x.CrossRefGoogle ScholarPubMed
Davis, E. P., Head, K., Buss, C., & Sandman, C. A. (2017). Prenatal maternal cortisol concentrations predict neurodevelopment in middle childhood. Psychoneuroendocrinology, 75, 5663. doi:10.1016/j.psyneuen.2016.10.005.CrossRefGoogle ScholarPubMed
de Haan-Rietdijk, S., Kuppens, P., & Hamaker, E. L. (2016). What's in a day? A guide to decomposing the variance in intensive longitudinal data. Frontiers in Psychology, 7, 891. doi:10.3389/fpsyg.2016.00891.CrossRefGoogle Scholar
De Vuyst, H. J., Dejonckheere, E., Van der Gucht, K., & Kuppens, P. (2019). Does repeatedly reporting positive or negative emotions in daily life have an impact on the level of emotional experiences and depressive symptoms over time? PLoS One, 14(6), e0219121. doi:10.1371/journal.pone.0219121.CrossRefGoogle ScholarPubMed
El Hachem, H., Crepaux, V., May-Panloup, P., Descamps, P., Legendre, G., & & Bouet, P.-E. (2017). Recurrent pregnancy loss: Current perspectives. International Journal of Women's Health, 9, 331345. doi:10.2147/ijwh.S100817.CrossRefGoogle ScholarPubMed
Engelhard, I. M., van den Hout, M. A., & Arntz, A. (2001). Posttraumatic stress disorder after pregnancy loss. General Hospital Psychiatry, 23(2), 6266. doi:10.1016/s0163-8343(01)00124-4.CrossRefGoogle ScholarPubMed
Entringer, S. (2013). Impact of stress and stress physiology during pregnancy on child metabolic function and obesity risk. Current Opinion in Clinical Nutrition and Metabolic Care, 16(3), 320327. doi:10.1097/MCO.0b013e32835e8d80.CrossRefGoogle ScholarPubMed
Entringer, S., Buss, C., Rasmussen, J. M., Lindsay, K., Gillen, D. L., Cooper, D. M., … Wadhwa, P. D. (2016). Maternal cortisol during pregnancy and infant adiposity: A prospective investigation. The Journal of Clinical Endocrinology & Metabolism, 102(4), 1366–1374. doi:10.1210/jc.2016-3025.CrossRefGoogle Scholar
Entringer, S., Buss, C., Shirtcliff, E. A., Cammack, A. L., Yim, I. S., Chicz-DeMet, A., & Sandman, C. A. (2010). Attenuation of maternal psychophysiological stress responses and the maternal cortisol awakening response over the course of human pregnancy. Stress (Amsterdam, Netherlands), 13(3), 258268. doi:10.3109/10253890903349501.CrossRefGoogle ScholarPubMed
Entringer, S., Buss, C., & Wadhwa, P. (2012). Prenatal stress, telomere biology, and fetal programming of health and disease risk. Science Signaling. 5(248), pt12. doi: 10.1126/scisignal.2003580.Google ScholarPubMed
Entringer, S., de Punder, K., Buss, C., & Wadhwa, P. D. (2018). The fetal programming of telomere biology hypothesis: An update. Philosophical Transactions of the Royal Society B: Biological Sciences, 373(1741), 1–15. doi:10.1098/rstb.2017.0151.CrossRefGoogle ScholarPubMed
Farquharson, R. G., Jauniaux, E., Exalto, N., & Pregnancy, E. S. I. G. f. E. (2005). Updated and revised nomenclature for description of early pregnancy events. Human Reproduction, 20(11), 30083011. doi:10.1093/humrep/dei167.CrossRefGoogle ScholarPubMed
Farren, J., Jalmbrant, M., Ameye, L., Joash, K., Mitchell-Jones, N., Tapp, S., & Timmerman, D. (2016). Post-traumatic stress, anxiety and depression following miscarriage or ectopic pregnancy: A prospective cohort study. British Medical Journal Open, 6(11), e011864. doi:10.1136/bmjopen-2016-011864.Google ScholarPubMed
Farren, J., Jalmbrant, M., Falconieri, N., Mitchell-Jones, N., Bobdiwala, S., Al-Memar, M., & Tapp, S. (2020). Posttraumatic stress, anxiety and depression following miscarriage and ectopic pregnancy: A multicenter, prospective, cohort study. American Journal of Obstetrics & Gynecology, 222(4), 367 e361367 e322. doi:10.1016/j.ajog.2019.10.102.CrossRefGoogle ScholarPubMed
Farren, J., Mitchell-Jones, N., Verbakel, J. Y., Timmerman, D., Jalmbrant, M., & Bourne, T. (2018). The psychological impact of early pregnancy loss. Human Reproduction Update, 24(6), 731749. doi:10.1093/humupd/dmy025.CrossRefGoogle ScholarPubMed
Giannandrea, S. A., Cerulli, C., Anson, E., & Chaudron, L. H. (2013). Increased risk for postpartum psychiatric disorders among women with past pregnancy loss. Journal of Women's Health, 22(9), 760768. doi:10.1089/jwh.2012.4011.CrossRefGoogle ScholarPubMed
Glynn, L. M., Schetter, C. D., Hobel, C. J., & Sandman, C. A. (2008). Pattern of perceived stress and anxiety in pregnancy predicts preterm birth. Health Psychology, 27(1), 4351. doi:10.1037/0278-6133.27.1.43.CrossRefGoogle ScholarPubMed
Goldstein, H., Healy, M. J., & Rasbash, J. (1994). Multilevel time series models with applications to repeated measures data. Statistics in Medicine, 13(16), 16431655. doi:10.1002/sim.4780131605.CrossRefGoogle ScholarPubMed
Gong, X., Hao, J., Tao, F., Zhang, J., Wang, H., & Xu, R. (2013). Pregnancy loss and anxiety and depression during subsequent pregnancies: Data from the C-ABC study. European Journal of Obstetrics & Gynecology and Reproductive Biology, 166(1), 3036. doi:10.1016/j.ejogrb.2012.09.024.CrossRefGoogle ScholarPubMed
Graignic-Philippe, R., Dayan, J., Chokron, S., Jacquet, A. Y., & Tordjman, S. (2014). Effects of prenatal stress on fetal and child development: A critical literature review. Neuroscience and Biobehavioral Reviews, 43, 137162. doi:10.1016/j.neubiorev.2014.03.022.CrossRefGoogle ScholarPubMed
Gravensteen, I. K., Jacobsen, E. M., Sandset, P. M., Helgadottir, L. B., Radestad, I., Sandvik, L., & Ekeberg, O. (2018). Anxiety, depression and relationship satisfaction in the pregnancy following stillbirth and after the birth of a live-born baby: A prospective study. BMC Pregnancy and Childbirth, 18(1), 41. doi:10.1186/s12884-018-1666-8.CrossRefGoogle ScholarPubMed
Gyllenhammer, L. E., Entringer, S., Buss, C., & Wadhwa, P. D. (2020). Developmental programming of mitochondrial biology: A conceptual framework and review. Philosophical Transactions of the Royal Society B: Biological Sciences, 287(1926), 20192713. doi:10.1098/rspb.2019.2713.Google ScholarPubMed
Haas, B. W., & Canli, T. (2008). Emotional memory function, personality structure and psychopathology: A neural system approach to the identification of vulnerability markers. Brain Research Reviews, 58(1), 7184. doi:10.1016/j.brainresrev.2007.10.014.CrossRefGoogle Scholar
Heim, C. M., Entringer, S., & Buss, C. (2019). Translating basic research knowledge on the biological embedding of early-life stress into novel approaches for the developmental programming of lifelong health. Psychoneuroendocrinology, 105, 123137. doi:10.1016/j.psyneuen.2018.12.011.CrossRefGoogle ScholarPubMed
Heron, K. E., & Smyth, J. M. (2013). Is intensive measurement of body image reactive? A two-study evaluation using ecological momentary assessment suggests not. Body Image, 10(1), 3544. doi:10.1016/j.bodyim.2012.08.006.CrossRefGoogle ScholarPubMed
Hinz, A., Daig, I., Petrowski, K., & Brahler, E. (2012). Mood in the German population: Norms of the multidimensional mood questionnaire MDBF. Psychotherapie Psychosomatik Medizinische Psychologie, 62(2), 5257. doi:10.1055/s-0031-1297960.Google ScholarPubMed
Horesh, D., Nukrian, M., & Bialik, Y. (2018). To lose an unborn child: Post-traumatic stress disorder and major depressive disorder following pregnancy loss among Israeli women. General Hospital Psychiatry, 53, 95100. doi:10.1016/j.genhosppsych.2018.02.003.CrossRefGoogle ScholarPubMed
Hufford, M. R., Shields, A. L., Shiffman, S., Paty, J., & Balabanis, M. (2002). Reactivity to ecological momentary assessment: An example using undergraduate problem drinkers. Psychology of Addictive Behaviors, 16(3), 205211. doi:10.1037/0893-164x.16.3.205.CrossRefGoogle ScholarPubMed
Hughes, P. M., Turton, P., & Evans, C. D. H. (1999). Stillbirth as risk factor for depression and anxiety in the subsequent pregnancy: Cohort study. British Medical Journal, 318(7200), 17211724. doi:10.1136/bmj.318.7200.1721.CrossRefGoogle ScholarPubMed
Hunfeld, J. A., Agterberg, G., Wladimiroff, J. W., & Passchier, J. (1996). Quality of life and anxiety in pregnancies after late pregnancy loss: A case-control study. Prenatal Diagnosis, 16(9), 783790. doi: 10.1002/(SICI)1097-0223(199609)16:9<783::AID-PD943>3.0.CO;2-7.3.0.CO;2-7>CrossRefGoogle ScholarPubMed
Hunter, A., Tussis, L., & MacBeth, A. (2017). The presence of anxiety, depression and stress in women and their partners during pregnancies following perinatal loss: A meta-analysis. Journal of Affective Disorders, 223, 153164. doi:10.1016/j.jad.2017.07.004.CrossRefGoogle ScholarPubMed
Jacob, L., Polly, I., Kalder, M., & Kostev, K. (2017). Prevalence of depression, anxiety, and adjustment disorders in women with spontaneous abortion in Germany – A retrospective cohort study. Psychiatry Research, 258, 382386. doi:10.1016/j.psychres.2017.08.064.CrossRefGoogle ScholarPubMed
Jones, R. H. (1993). Longitudinal data with serial correlation: A state-space approach. Boca Raton Florida US: Chapman and Hall/CRC Press.CrossRefGoogle Scholar
Jones, A., Remmerswaal, D., Verveer, I., Robinson, E., Franken, I. H. A., Wen, C. K. F., & Field, M. (2019). Compliance with ecological momentary assessment protocols in substance users: A meta-analysis. Addiction, 114(4), 609619. doi:10.1111/add.14503.CrossRefGoogle ScholarPubMed
Kersting, A., Kroker, K., Steinhard, J., Ludorff, K., Wesselmann, U., Ohrmann, P., & Arolt, V. (2007). Complicated grief after traumatic loss: A 14-month follow up study. European Archives of Psychiatry and Clinical Neuroscience, 257(8), 437443. doi:10.1007/s00406-007-0743-1.CrossRefGoogle Scholar
Klebanoff, M. A., Shiono, P. H., & Rhoads, G. G. (1990). Outcomes of pregnancy in a national sample of resident physicians. New England Journal of Medicine, 323(15), 10401045. doi:10.1056/NEJM199010113231506.CrossRefGoogle Scholar
Krosch, D. J., & Shakespeare-Finch, J. (2017). Grief, traumatic stress, and posttraumatic growth in women who have experienced pregnancy loss. Psychological Trauma: Theory, Research, Practice, and Policy, 9(4), 425433. doi:10.1037/tra0000183.CrossRefGoogle ScholarPubMed
Lampert, T., Hoebel, J., & Kuntz, B. (2018). Socioeconomic status and subjective social status measurement in KiGGS wave 2. Journal of Health Monitoring, 3(1), 108–125. doi:10.17886/RKI-GBE-2018-033.Google ScholarPubMed
Lautarescu, A., Craig, M. C., & Glover, V. (2020). Prenatal stress: Effects on fetal and child brain development. In Clow, A. & Smyth, N. (Eds.), Stress and brain health: Across the life course (2020/03/25 ed., Vol. 150, pp. 1740). doi:10.1016/bs.irn.2019.11.002.CrossRefGoogle Scholar
Lawn, J. E., Blencowe, H., Waiswa, P., Amouzou, A., Mathers, C., Hogan, D., & Flenady, V. (2016). Stillbirths: Rates, risk factors, and acceleration towards 2030. The Lancet, 387(10018), 587603. doi:10.1016/s0140-6736(15)00837-5.CrossRefGoogle ScholarPubMed
Lazarides, C., Ward, E. B., Buss, C., Chen, W. P., Voelkle, M. C., Gillen, D. L., & Wadhwa, P. D. (2020). Psychological stress and cortisol during pregnancy: An ecological momentary assessment (EMA)-Based within- and between-person analysis. Psychoneuroendocrinology, 121, 104848. doi:10.1016/j.psyneuen.2020.104848.CrossRefGoogle ScholarPubMed
Lindsay, K. L., Buss, C., Wadhwa, P. D., & Entringer, S. (2018). The interplay between nutrition and stress in pregnancy: Implications for fetal programming of brain development. Biological Psychiatry, 85(2), 135–149. doi:10.1016/j.biopsych.2018.06.021.Google ScholarPubMed
Littell, R. C., Milliken, G. A., Stroup, W. W., Wolfinger, R. D., & Oliver, S. (2006). SAS For mixed models. Cary North Carolina US: SAS Publishing.Google Scholar
Little, R. J., & Rubin, D. B. (2002). Bayes and multiple imputation. Statistical analysis with missing data, pp. 200220.CrossRefGoogle Scholar
MacDorman, M. F., Kirmeyer, S. E., & Wilson, E. C. (2012). Fetal and perinatal mortality, United States, 2006. National Vital Statistics Reports, 60(8), 122. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/24979970.Google Scholar
Magnus, M. C., Wilcox, A. J., Morken, N. H., Weinberg, C. R., & Haberg, S. E. (2019). Role of maternal age and pregnancy history in risk of miscarriage: Prospective register based study. BMJ – British Medical Journal, 364, l869. doi:10.1136/bmj.l869.CrossRefGoogle ScholarPubMed
Milad, M. P., Klock, S. C., Moses, S., & Chatterton, R. (1998). Stress and anxiety do not result in pregnancy wastage. Human Reproduction, 13(8), 2296–2300.CrossRefGoogle Scholar
movisens, G. (2020). movisensXS (Version 1.5.2). Karlsruhe, Germany.Google Scholar
Mukherjee, S., Velez Edwards, D. R., Baird, D. D., Savitz, D. A., & Hartmann, K. E. (2013). Risk of miscarriage among black women and white women in a U.S. Prospective Cohort Study. American Journal of Epidemiology, 177(11), 12711278. doi:10.1093/aje/kws393.CrossRefGoogle Scholar
Murphy, S. L., Mathews, T. J., Martin, J. A., … Strobino, D. M. (2017). Annual summary of vital statistics: 2013–2014. Pediatrics, 139(6), 102–110.CrossRefGoogle ScholarPubMed
Nelson, D. B., Grisso, J. A., Joffe, M. M., Brensinger, C., Shaw, L., & Datner, E. (2003). Does stress influence early pregnancy loss? Annals of Epidemiology, 13(4), 223–229.CrossRefGoogle ScholarPubMed
Pinheiro, J., Bates, D., DebRoy, S., Sarkar, D., & Core Team, R. (2018). _nlme: Linear and Nonlinear Mixed Effects Models_. R package version 3. pp. 1–137. Retrieved from https://CRAN.R-project.org/package=nlme>..>Google Scholar
Podsakoff, P. M., MacKenzie, S. B., & Podsakoff, N. P. (2012). Sources of method bias in social science research and recommendations on how to control it. Annual Review of Psychology, 63, 539569. doi:10.1146/annurev-psych-120710-100452.CrossRefGoogle ScholarPubMed
Price, S. K. (2006). Prevalence and correlates of pregnancy loss history in a national sample of children and families. Maternal and Child Health Journal, 10(6), 489500. doi:10.1007/s10995-006-0123-x.CrossRefGoogle Scholar
Qu, F., Wu, Y., Zhu, Y. H., Barry, J., Ding, T., Baio, G., & Muscat, R. (2017). The association between psychological stress and miscarriage: A systematic review and meta-analysis. Scientific Reports, 7(1), 1731. doi:10.1038/s41598-017-01792-3.CrossRefGoogle ScholarPubMed
Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear models: Applications and data analysis methods (Vol. 1). Thousand Oaks California US: Sage Publications.Google Scholar
R Development Core Team. (2018). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. Retrieved from https://www.R-project.org/.Google Scholar
Regan, A. K., Gissler, M., Magnus, M. C., Håberg, S. E., Ball, S., Malacova, E., & Nassar, N. (2019). Association between interpregnancy interval and adverse birth outcomes in women with a previous stillbirth: An international cohort study. The Lancet, 393(10180), 15271535. doi:10.1016/s0140-6736(18)32266-9.CrossRefGoogle ScholarPubMed
Rini, C. K., Dunkel-Schetter, C., Wadhwa, P. D., & Sandman, C. A. (1999). Psychological adaptation and birth outcomes: The role of personal resources, stress, and sociocultural context in pregnancy. Health Psychology, 18(4), 333345. doi:10.1037//0278-6133.18.4.333.CrossRefGoogle ScholarPubMed
Robertson-Blackmore, E., Putnam, F. W., Rubinow, D. R., Matthieu, M., Hunn, J. E., Putnam, K. T., & Moynihan, J. A. (2013). Antecedent trauma exposure and risk of depression in the perinatal period. Journal of Clinical Psychiatry, 74(10), e942e948. doi:10.4088/JCP.13m08364.CrossRefGoogle ScholarPubMed
Rowan, P. J., Cofta-Woerpel, L., Mazas, C. A., Vidrine, J. I., Reitzel, L. R., Cinciripini, P. M., & Wetter, D. W. (2007). Evaluating reactivity to ecological momentary assessment during smoking cessation. Experimental and Clinical Psychopharmacology, 15(4), 382389. doi:10.1037/1064-1297.15.4.382.CrossRefGoogle ScholarPubMed
Schetter, C. D., Saxbe, D., Cheadle, A., & Guardino, C. (2016). Postpartum depressive symptoms following consecutive pregnancies: Stability, change, and mechanisms. Clinical Psychological Science, 4(5), 909918. doi:10.1177/2167702616644894.CrossRefGoogle ScholarPubMed
Schmiedek, F., Lovden, M., & Lindenberger, U. (2013). Keeping it steady: Older adults perform more consistently on cognitive tasks than younger adults. Psychological Science, 24(9), 17471754. doi:10.1177/0956797613479611.CrossRefGoogle ScholarPubMed
Smyth, J. M., & Stone, A. A. (2003). Ecological momentary assessment research in behaviroal medicine. Journal of Happiness Studies, 4(1), 3552. doi:10.1023/A:1023657221954.CrossRefGoogle Scholar
Snijders, T. A. B., & Bosker, R. J. (2012). Multilevel analysis: An introduction to basic and advanced multilevel modeling (2 ed.). London: Sage Publishers.Google Scholar
Stanton, A. L., Lobel, M., Sears, S., & DeLuca, R. S. (2002). Psychosocial aspects of selected issues in women's reproductive health: Current status and future directions. Journal of Consulting and Clinical Psychology, 70(3), 751770. doi:10.1037/0022-006x.70.3.751.CrossRefGoogle Scholar
Steyer, R., Schwenkmezger, P., Notz, P., & Eid, M. (1994). Testtheoretische Analysen des Mehrdimensionalen Befindlichkeitsfragebogen (MDBF). Diagnostica.Google Scholar
Steyer, R., Schwenkmezger, P., Notz, P., & Eid, M. (1997). Multidimensional Mood State Questionnaire (MDBF). In. Göttingen: Hogrefe – Verlag für Psychologie.Google Scholar
Sundermann, A. C., Hartmann, K. E., Jones, S. H., Torstenson, E. S., & Velez Edwards, D. R. (2017). Interpregnancy interval after pregnancy loss and risk of repeat miscarriage. Obstetrics & Gynecology, 130(6), 13121318. doi:10.1097/AOG.0000000000002318.CrossRefGoogle ScholarPubMed
Tarabulsy, G. M., Pearson, J., Vaillancourt-Morel, M. P., Bussieres, E. L., Madigan, S., Lemelin, J. P., & Duchesneau, A. A. (2014). Meta-Analytic findings of the relation between maternal prenatal stress and anxiety and child cognitive outcome. Journal of Developmental and Behavioral Pediatrics, 35(1), 3843. doi:10.1097/Dbp.0000000000000003.CrossRefGoogle ScholarPubMed
Tavares Da Silva, F., Gonik, B., McMillan, M., Keech, C., Dellicour, S., Bhange, S., & Tila, M. (2016). Stillbirth: Case definition and guidelines for data collection, analysis, and presentation of maternal immunization safety data. Vaccine, 34(49), 60576068. doi:10.1016/j.vaccine.2016.03.044.CrossRefGoogle ScholarPubMed
Toffol, E., Koponen, P., & Partonen, T. (2013). Miscarriage and mental health: Results of two population-based studies. Psychiatry Research, 205(1–2), 151158. doi:10.1016/j.psychres.2012.08.029.CrossRefGoogle ScholarPubMed
Tsartsara, E., & Johnson, M. P. (2006). The impact of miscarriage on women's pregnancy-specific anxiety and feelings of prenatal maternal-fetal attachment during the course of a subsequent pregnancy: An exploratory follow-up study. Journal of Psychosomatic Obstetrics & Gynecology, 27(3), 173182. doi:10.1080/01674820600646198.CrossRefGoogle ScholarPubMed
Turton, P., Evans, C., & Hughes, P. (2009). Long-term psychosocial sequelae of stillbirth: Phase II of a nested case-control cohort study. Archives of Women's Mental Health, 12(1), 3541. doi:10.1007/s00737-008-0040-7.CrossRefGoogle ScholarPubMed
Turton, P., Hughes, P., Evans, C. D., & Fainman, D. (2001). Incidence, correlates and predictors of post-traumatic stress disorder in the pregnancy after stillbirth. British Journal of Psychiatry, 178, 556560. doi:10.1192/bjp.178.6.556.CrossRefGoogle ScholarPubMed
Volgsten, H., Jansson, C., Svanberg, A. S., Darj, E., & Stavreus-Evers, A. (2018). Longitudinal study of emotional experiences, grief and depressive symptoms in women and men after miscarriage. Midwifery, 64, 2328. doi:10.1016/j.midw.2018.05.003.CrossRefGoogle ScholarPubMed
Wadhwa, P. D., Entringer, S., Buss, C., & Lu, M. C. (2011). The contribution of maternal stress to preterm birth: Issues and considerations. Clinics in Perinatology, 38(3), 351384. doi:10.1016/j.clp.2011.06.007.CrossRefGoogle ScholarPubMed
Walsh, K., McCormack, C. A., Webster, R., Pinto, A., Lee, S., Feng, T., & Krakovsky, H. S. (2019). Maternal prenatal stress phenotypes associate with fetal neurodevelopment and birth outcomes. Proceedings of the National Academy of Sciences of the USA, 116(48), 2399624005. doi:10.1073/pnas.1905890116.CrossRefGoogle Scholar
Wen, C. K. F., Schneider, S., Stone, A. A., & Spruijt-Metz, D. (2017). Compliance with mobile ecological momentary assessment protocols in children and adolescents: A systematic review and meta-analysis. Journal of Internet Research 19(4), e132. doi:10.2196/jmir.6641.CrossRefGoogle ScholarPubMed
Woods-Giscombe, C. L., Lobel, M., & Crandell, J. L. (2010). The impact of miscarriage and parity on patterns of maternal distress in pregnancy. Research in Nursing & Health, 33(4), 316328. doi:10.1002/nur.20389.CrossRefGoogle ScholarPubMed
Figure 0

Table 1. Maternal sociodemographic and obstetric characteristics

Figure 1

Table 2. Summary statistics on valence (good – bad mood: GB_mean), arousal (calm – nervous: CN_mean), tiredness (alert – tired: AT_mean), and pregnancy-specific distress (PSD_mean), separately for each time point, T1 and T2

Figure 2

Table 3. Results of linear mixed models predicting EMA-based pregnancy-specific distress (PSD_mean), and affective states (valence, GB_mean; arousal, CN_mean, tiredness, AT_mean) by stage of pregnancy and prenatal loss status

Figure 3

Fig. 1. Grouped bar plot of EMA-based pregnancy-specific distress by history of prenatal loss in previous pregnancy and stage of pregnancy (mean ± 2 standard error bars).

Figure 4

Fig. 2. Grouped bar plot displaying EMA-based arousal by history of prenatal loss in previous pregnancy and stage of pregnancy (mean ± 2 standard error bars).

Supplementary material: File

Lazarides et al. supplementary material

Lazarides et al. supplementary material

Download Lazarides et al. supplementary material(File)
File 46.6 KB