Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2022 Nov 1.
Published in final edited form as: Obstet Gynecol. 2021 Nov 1;138(5):770–776. doi: 10.1097/AOG.0000000000004570

Association Between Adverse Childhood Experiences and Adverse Pregnancy Outcomes

Emily S Miller 1,2,3, Oriana Fleming 4, Etoroabasi E Ekpe 1, William A Grobman 1,2, Nia Heard-Garris 5,6,7
PMCID: PMC8542582  NIHMSID: NIHMS1734449  PMID: 34619717

Abstract

Objective:

To examine the association between adverse childhood experiences and adverse pregnancy outcomes.

Methods:

This cohort study included individuals who enrolled in a perinatal collaborative mental healthcare program (COMPASS) between 2017–2021. Participants completed psychosocial self-assessments, including an adverse childhood experiences (ACE) screen. The primary exposure was adverse childhood experiences measured by the ACE score which was evaluated as a dichotomized variable, with a high ACE score defined as greater than three. Secondary analyses utilized the ACE score as a continuous variable. Adverse pregnancy outcomes including gestational diabetes, hypertensive disorders of pregnancy (HDP), preterm birth, and small-for-gestational-age (SGA) births were abstracted from the electronic health record. Bivariable and multivariable analyses were performed, including mediation analyses.

Results:

Of the 1,274 women with a completed ACE screen, 904 (71%) reported one or more adverse childhood experiences and 290 (23%) reported a high ACE score (more than three adverse childhood experiences). Adverse childhood experience scores were not associated with gestational diabetes or SGA births. After controlling for potential confounders, individuals with high ACE score had a 1.55-fold (95% CI 1.06–2.26) increased odds of having a HDP and a 2.03-fold (95% CI 1.38–2.99) increased odds of preterm birth. Each point increase in ACE score was not associated with a statistically increased odds of HDP (aOR 1.07, 95% CI 0.99–1.15); however, each additional point on the ACE screen was associated with increased odds of preterm birth (aOR 1.13, 95% CI 1.05–1.22). Mediation analyses demonstrated tobacco use, chronic medical problems, and obesity each partially mediated the observed association between high ACE scores and HDP. Having chronic medical comorbidities partially mediated the observed association between high ACE scores and preterm birth.

Conclusion:

One in four individuals referred to a perinatal mental health program who were pregnant or postpartum had a high ACE score. Having a high ACE score was associated with an increased risk of HDP and preterm birth. These results underscore how remote events may reverberate through the life course.

Precis:

In pregnant people with mental health conditions, adverse childhood experiences are associated with an increased risk of hypertensive disorders of pregnancy and preterm birth.

Introduction

Adverse childhood experiences, traumatic events that occur in childhood including exposures to abuse or neglect, parental separation or divorce, or parental mental health conditions or substance use disorder, are consistently associated with chronic health conditions later in life with a dose-response relationship.1,2 Adverse childhood experiences are common, with 62% of Americans reporting at least one, 25% at least three, and 16% at least four adverse childhood experiences.3,4 Moreover, adverse childhood experiences are disproportionally prevalent among those facing social adversity, including structural racism and poverty.5 As adverse childhood experiences may alter life trajectories, including educational attainment and employment status, primary prevention of adverse childhood experiences and mitigation of their effects are essential components of an equity-focused public health strategy.

There is biologic plausibility for a relationship between adverse childhood experiences and adverse pregnancy outcomes. Adverse childhood experiences are known to affect the long-term development of the neuroendocrine and immune systems; these alterations, in turn, have been associated with adverse pregnancy outcomes.6,7 One mechanism by which adverse childhood experiences affect lifelong health is by altering the internalization of perceived stress via increased cortisol production in the setting of a stress exposure.8 High levels of cortisol increase the release of pro-inflammatory cytokines9, which are, in turn, associated with gestational diabetes, hypertensive disorders of pregnancy, preterm birth, and small for gestational age births.10–15 In addition to these biologic pathways, social determinants, including education and income, likely mediate the observed relationship.15

Prior studies (Appendix 1, available online at http://links.lww.com/AOG/C460) that have examined this relationship are limited by small sample sizes13, populations with limited generalizability16,17, or significant concern for confounding bias.18–20 In order to fill this evidence gap, our objective was to examine the association between adverse childhood experiences and adverse perinatal outcomes using a diverse sample of individuals with perinatal mental health conditions. We hypothesized that having a high ACE score would be associated with an increased prevalence of adverse pregnancy outcomes.

Methods

This cohort study included all pregnant and postpartum individuals who enrolled in the Collaborative Care Model for Perinatal Depression Support Services (COMPASS) on or after its inception on January 23, 2017, through March 1, 2021, and who delivered after 20 weeks’ gestation. COMPASS is a perinatal mental health system embedded within all five of the Northwestern Medicine obstetrics clinics.21 Obstetric patients were eligible for enrollment if they had either a history of a mental health condition or current mental health symptoms. COMPASS provides mental health services, guided by collaborative care model principles22, during pregnancy and up to one year postpartum.

Upon enrollment in COMPASS, individuals were asked to complete self-reported psychosocial assessments, including ten types of adversity occurring before the age of 18 that are described in the Centers for Disease Control and Prevention’s (CDC’s) Kaiser ACE Study.1 These assessments were completed directly in a participant registry, housed in REDCap.23 Individuals who did not complete the adverse childhood experience (ACE) screen were excluded from these analyses. Sociodemographic characteristics including maternal age, insurance, self-reported race and ethnicity, marital status, medical history including tobacco use, medical conditions, body mass index at delivery, obstetric history including parity, and preganancy outcomes including gestational diabetes, hypertensive disorders of pregnancy, preterm birth, and small for gestational age births were abstracted from the electronic health record (EHR). Gestational diabetes was diagnosed by either a glucose challenge test of >200mg/dL or results from a glucose tolerance test that met the Carpenter-Coustan diagnostic criteria.24 Hypertensive disorders of pregnancy were diagnosed by the attending obstetric clinician, in accordance with criteria defined by the American College of Obstetricians and Gynecologists (ACOG).25 Gestational age at delivery was calculated from the estimated due date, derived using ACOG standards26 and preterm birth was defined as delivery prior to 37 weeks’ gestation. Infants were classified as small for gestational age if their birth weight was below the 10th percentile of normative birthweights for singletons.27

Adverse childhood experiences were evaluated as a categorical variable with a high ACE score defined as greater than three adverse childhood experiences in accordance with prior work.1 Secondary analyses evaluated ACE as a continuous variable. Bivariable analyses were conducted using Student’s t-tests or Mann Whitney U tests for continuous variables or chi squared or Fisher’s exact tests for categorical variables, as appropriate. Given the complex inter-relatedness of social determinants of health, a directed acyclic graph (DAG) (Figure 1) was generated to represent potential causal networks and inform covariate adjustment. Variables with plausible roles as confounders in the DAG that were significantly different in bivariable analyses were considered as potential confounders. While race and ethnicity have been associated with both adverse childhood experiences and adverse pregnancy outcomes8,28, their role as a surrogate for structural racism and discrimination was felt to be potentially antecedent to the adverse childhood experiences exposure; without metrics to ascribe temporality to these lived experiences, race and ethnicity were not included as confounders. Bivariable analyses were performed to evaluate associations between participant characteristics and missing data for the ACE screen. These associations were used to perform a sensitivity analysis using multiple imputation. Given the specific pregnancy risks faced by people in their first pregnancy, additional sensitivity analyses were performed including just those who were nulliparous.

Figure 1:

Figure 1:

Open in a new tab

Directed acyclic graph for the association between adverse childhood experiences and adverse pregnancy outcomes.

For adverse pregnancy outcomes with significant associations with ACE score in bivariable analyses, mediation analyses were performed to inform the underlying pathways of the association.29,30 Variables considered as potential mediators were identified using the DAG (Figure 1). The percentage of the total effect that was mediated by a given factor was calculated by dividing the beta coefficient of the indirect pathway by the summation of the beta coefficients of the indirect and direct pathways. As indirect effects are often non-parametric, standard errors and confidence intervals for each mediator were estimated using bootstrapping with 5000 replications and bias correction. STATA v15.0 was used for analyses. This study was approved by Northwestern University’s Institutional Review Board prior to its initiation.

Results

During the study period, 2,016 individuals were referred to COMPASS for mental health care and met eligibility criteria; 742 (37%) were excluded as they did not complete their ACE screen. ACE scores for the remaining 1,274 participants are shown in Figure 2. Of the individuals included, 904 (71%) reported one or more ACE and 290 (23%) reported a high ACE score (i.e., a score greater than three).

Figure 2:

Figure 2:

Open in a new tab

Distribution of adverse childhood experiences scores.

Sociodemographic and clinical characteristics of the sample, stratified by high ACE score, are shown in Table 1. Patients with high ACE scores (> 3 ACEs) were more likely to be younger at time of delivery, have government-supported insurance (e.g., Medicaid), use tobacco, have a chronic medical condition, and have a higher body mass index (BMI) at delivery. Patients with high ACE scores were less likely to be married. Self-identified race and ethnicity also differed by ACE exposure, with people identifying as White or Asian less likely to have a high ACE score than those who identified as Black.

Table 1:

Sociodemographic and clinical characteristics, stratified by high adverse childhood experiences score

ACE Score ≤ 3 ACE Score > 3 p value
n=984 (77%) n=290 (23%)
Maternal age (years) 33 ± 5 32 ± 6 <0.001
Public insurance (n=1225) 138 (14.6%) 106 (37.7%) <0.001
Race (n=1225) <0.001
 White 555 (58.8%) 112 (39.9%)
 African-American/Black 146 (15.5%) 104 (37.0%)
 Asian 58 (6.1%) 10 (3.6%)
 Other1 84 (8.9%) 30 (10.7%)
 Unknown 101 (10.7%) 25 (8.9%)
Latinx ethnicity (n=1146) 131 (14.8%) 56 (21.3%) 0.013
Married (n=1224) 692 (73.4%) 131 (46.6%) <0.001
Ever used tobacco (n=1216) 144 (15.4%) 84 (30.2%) <0.001
Any chronic medical condition (n=1215) 425 (45.4%) 154 (55.4%) 0.003
 Pre-existing diabetes 36 (3.7%) 14 (4.8%) 0.37
 Chronic hypertension 58 (5.9%) 21 (7.2%) 0.40
BMI at delivery (kg/m2) (n=1157) 32 ± 7 33 ± 7 0.002
 BMI > 30 kg/m2 at delivery 458 (51.4%) 164 (61.9%) 0.003
Nulliparous 538 (54.7%) 140 (48.3%) 0.055
Prior history of preterm birth (n=1219) 54 (5.7%) 31 (11.1%) 0.002
Open in a new tab

Data presented as mean ± standard deviation or n (%)

1

Includes individuals who self-identified as American Indian/Alaska Native, Native Hawaiian/Other Pacific Islander, or other

Associations between high ACE score and adverse pregnancy outcomes are described in Table 2. After controlling for potential confounders (including maternal age, insurance, marital status, tobacco use, chronic medical conditions, and obesity), individuals with high ACE score had a 1.6-fold increased odds of having a hypertensive disorder of pregnancy and a 2.0-fold increased odds of preterm birth. No differences were observed in gestational diabetes or small for gestational age births, though it should be noted that the point estimates for each of these outcomes were higher in those with high ACE scores compared to those without a high ACE score.

Table 2:

Bivariable and multivariable analyses of the associations between adverse childhood experiences and adverse pregnancy outcomes

ACE Score ≤ 3 ACE Score > 3 OR (95% CI) aOR (95% CI)
Gestational diabetes (n=1170) 60 (6.7%) 20 (7.4%) 1.11 (0.66–1.88) 1.21 (0.70–2.11)
Hypertensive disorder of pregnancy 126 (12.8%) 58 (20.0%) 1.58 (1.08–2.32) 1.55 (1.06–2.26)
Preterm birth (n=1271) 120 (12.2%) 67 (23.1%) 2.16 (1.54–3.01) 2.03 (1.38–2.99)
Small for gestational age (n=1149) 39 (4.4%) 14 (5.3%) 1.20 (0.64–2.25) ---1
Open in a new tab

Data presented as n (%)

ACE = adverse childhood experiences; OR = odds ratio; aOR = adjusted odds ratio

Multivariable analyses adjusted for maternal age, insurance, marital status, tobacco use, chronic medical conditions, and obesity

1

Cell count too small for multivariable analysis

As a secondary analysis, ACE score was analyzed as a continuous variable. Each additional point on the ACE screen was associated with a 10% increased odds of hypertensive disorders of pregnancy (OR 1.10, 95% CI 1.03–1.18); however, this finding did not remain significant in multivariable analyses (aOR 1.07, 95% CI 0.99–1.15). Each additional point on the ACE screen was also associated with 15% increased odds of preterm birth (OR 1.15, 95% CI 1.08–1.23); this association remained significant in multivariable analyses (aOR 1.13, 95% CI 1.05–1.22).

Review of missing data demonstrated that those with missing ACE data were younger [33 (IQR 30–36) vs. 33 (IQR 29–36), p<0.001]; were more likely to have public insurance (25% vs 20%, p=0.012), identify as Black (27% vs 20%, p=0.002), be married (60% vs 67%, p=0.002); and were less likely to be nulliparous (48% vs 53%, p=0.018). These identified associations were used to perform multiple imputation. Bivariable and multivariable analyses were conducted with these imputed data with results depicted in Appendix 2, available online at http://links.lww.com/AOG/C460. After multiple imputation, the associations between a high ACE score and preterm birth and between a high ACE score and hypertensive disorders of pregnancy were not changed. Analyses including only those who were nulliparous similarly did not change the results.

Mediation analyses were conducted for the outcomes of hypertensive disorders of pregnancy and preterm birth. Tobacco use, chronic medical problems, and obesity each partially mediated the observed association between high ACE scores and hypertensive disorders of pregnancy (Table 3). Having chronic medical comorbidities partially mediated the observed association between high ACE scores and preterm birth (Table 3). There was no other statistically significant mediation present.

Table 3:

Mediation analyses

Proportion of Total Effect Mediated 95% CI
Hypertensive disorder of pregnancy
 Tobacco use 5.3% 4.2–6.7%
 Any chronic medical comorbidity 11.5% 9.8–13.4%
 Obesity 17.4% 15.4–19.6%
Preterm birth
 Tobacco use 0.4% 0.2–1.0%
 Any chronic medical comorbidity 6.7% 5.3–8.2%
 Obesity 0.1% 0.0–0.4%
Open in a new tab

CI = confidence interval

Obesity was defined as a BMI > 30 kg/m2 at delivery

Discussion

In this study, one in four pregnant or postpartum individuals referred for perinatal mental health care had a high ACE score, consistent with national CDC and BRFSS estimates.4,5 We found a high ACE score was associated with hypertensive disorders of pregnancy and preterm birth. These data amplify the importance of the CDC’s campaign to prevent adverse childhood experiences to improve U.S. health31 and emphasize the potential of prevention to mitigate the intergenerational transmission of trauma. The association of adverse childhood experiences with hypertensive disorders of pregnancy was mediated by tobacco use, chronic medical comorbidities, and obesity whereas the association with preterm birth was partially associated with chronic medical comorbidities. These mediation analyses suggest avenues for secondary prevention when adverse childhood experiences are identified.

In Felitti’s study on adverse childhood experiences, seven categories of negative experiences occurring in childhood were associated with negative health outcomes later in life.1 Subsequently, many investigators expanded the understanding of health outcomes related to adverse childhood experiences, finding a dose-response relationship as well.1,32 Recently, maternal adverse childhood experiences were associated with abnormal development of their children through at least 4 years of age.33–36 Our findings underscore the potential intergenerational reverberation of adverse childhood experiences as infants born to individuals exposed to trauma were more likely to be born preterm.

Our study narrows the focus from childhood outcomes to birth outcomes, linking adverse childhood experiences to adverse pregnancy outcomes including preterm birth. Results from our study are consistent with prior results linking adverse childhood experiences to preterm birth.13,37 Less research has been conducted to evaluate the association between adverse childhood experiences and other adverse pregnancy outcomes (Table 1). Our study builds on the existing literature through its larger sample size, lessening the potential for type II error. In addition, the breadth of sociodemographic diversity of our study population improves external generalizability. Finally, the development of a DAG and use of mediation analysis provide insights into the pathways that contribute to observed associations.

The study is limited by recall bias inherent in detailing adverse childhood experiences. Underreporting of negative childhood experiences is common due to incomplete memories or stigma.38 This dynamic, however, would bias our results toward the null and may have masked relationships between adverse childhood experiences and other adverse pregnancy outcomes. In addition, this study included individuals with an identified history or current symptoms of a mental health condition. Whether the association between adverse childhood experiences and adverse perinatal outcomes is different in this population compared to a more general population remains unknown. Finally, while the DAG informed development of our model, we recognize that complex interactions across social and structural determinants of health exist and cannot be represented in any one model.

These data are particularly salient in the context of the COVID-19 pandemic, as rates of intimate partner violence and child neglect are rising.39 Health care professionals play an important role in identifying and intervening when abuse or neglect is suspected. In addition, the observed racial disparity in the prevalence of adverse childhood experiences emphasizes the importance of equity-focused research and programs designed to mitigate these risks.

Supplementary Material

Supplemental Digital Content_1
Supplemental Digital Content_2

Acknowledgments

This work was supported by the Friends of Prentice (philanthropic organization). N. Heard-Garris’s efforts were supported by the National Heart Lung and Blood Institute (5K01HL147995–02). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Footnotes

Financial Disclosure

Emily S Miller is a site PI for a COVID-19 in pregnancy clinical trial sponsored by Pfizer. Nia Heard-Garris is the co-owner of XNY Genes, LLC, a racial equity consulting group. Dr. Heard-Garris is also the co‐author of and receives royalties for a text in UpToDate, Inc on the developmental and behavioral implications for children of incarcerated parents. The other authors did not report any potential conflicts of interest.

Each author has confirmed compliance with the journal’s requirements for authorship.

References

  • 1.Felitti VJ, Anda RF, Nordenberg D, et al. Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults. The Adverse Childhood Experiences (ACE) Study. American journal of preventive medicine 1998;14(4):245–58. DOI: 10.1016/s0749-3797(98)00017-8. [DOI] [PubMed] [Google Scholar]
  • 2.Hughes K, Bellis MA, Hardcastle KA, et al. The effect of multiple adverse childhood experiences on health: a systematic review and meta-analysis. Lancet Public Health 2017;2(8):e356–e366. DOI: 10.1016/S2468-2667(17)30118-4. [DOI] [PubMed] [Google Scholar]
  • 3.Merrick MT, Ford DC, Ports KA, Guinn AS. Prevalence of Adverse Childhood Experiences From the 2011–2014 Behavioral Risk Factor Surveillance System in 23 States. JAMA Pediatr 2018;172(11):1038–1044. (In eng). DOI: 10.1001/jamapediatrics.2018.2537. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Merrick MT, Ford DC, Ports KA, et al. Vital Signs: Estimated Proportion of Adult Health Problems Attributable to Adverse Childhood Experiences and Implications for Prevention - 25 States, 2015–2017. MMWR Morbidity and mortality weekly report 2019;68(44):999–1005. (In eng). DOI: 10.15585/mmwr.mm6844e1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Crouch E, Probst JC, Radcliff E, Bennett KJ, McKinney SH. Prevalence of adverse childhood experiences (ACEs) among US children. Child Abuse Negl 2019;92:209–218. (In eng). DOI: 10.1016/j.chiabu.2019.04.010. [DOI] [PubMed] [Google Scholar]
  • 6.Coussons-Read ME, Lobel M, Carey JC, et al. The occurrence of preterm delivery is linked to pregnancy-specific distress and elevated inflammatory markers across gestation. Brain, behavior, and immunity 2012;26(4):650–9. (In eng). DOI: 10.1016/j.bbi.2012.02.009. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Johnson SB, Riley AW, Granger DA, Riis J. The science of early life toxic stress for pediatric practice and advocacy. Pediatrics 2013;131(2):319–27. (In eng). DOI: 10.1542/peds.2012-0469. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Bowers K, Ding L, Gregory S, et al. Maternal distress and hair cortisol in pregnancy among women with elevated adverse childhood experiences. Psychoneuroendocrinology 2018;95:145–148. (In eng). DOI: 10.1016/j.psyneuen.2018.05.024. [DOI] [PubMed] [Google Scholar]
  • 9.Giurgescu C Are maternal cortisol levels related to preterm birth? Journal of obstetric, gynecologic, and neonatal nursing : JOGNN / NAACOG 2009;38(4):377–90. DOI: 10.1111/j.1552-6909.2009.01034.x. [DOI] [PubMed] [Google Scholar]
  • 10.Villar J, Carroli G, Wojdyla D, et al. Preeclampsia, gestational hypertension and intrauterine growth restriction, related or independent conditions? American journal of obstetrics and gynecology 2006;194(4):921–31. (In eng). DOI: 10.1016/j.ajog.2005.10.813. [DOI] [PubMed] [Google Scholar]
  • 11.Poston L, Igosheva N, Mistry HD, et al. Role of oxidative stress and antioxidant supplementation in pregnancy disorders. The American journal of clinical nutrition 2011;94(6 Suppl):1980S–1985S. (In eng). DOI: 10.3945/ajcn.110.001156. [DOI] [PubMed] [Google Scholar]
  • 12.Osborne LM, Monk C. Perinatal depression--the fourth inflammatory morbidity of pregnancy?: Theory and literature review. Psychoneuroendocrinology 2013;38(10):1929–52. (In eng). DOI: 10.1016/j.psyneuen.2013.03.019. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Christiaens I, Hegadoren K, Olson DM. Adverse childhood experiences are associated with spontaneous preterm birth: a case-control study. BMC medicine 2015;13:124. (In eng). DOI: 10.1186/s12916-015-0353-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Walsh K, Basu A, Werner E, et al. Associations Among Child Abuse, Depression, and Interleukin-6 in Pregnant Adolescents: Paradoxical Findings. Psychosomatic medicine 2016;78(8):920–930. (In eng). DOI: 10.1097/psy.0000000000000344. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Weightman AL, Morgan HE, Shepherd MA, Kitcher H, Roberts C, Dunstan FD. Social inequality and infant health in the UK: systematic review and meta-analyses. BMJ Open 2012;2(3) (In eng). DOI: 10.1136/bmjopen-2012-000964. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Hillis SD, Anda RF, Dube SR, Felitti VJ, Marchbanks PA, Marks JS. The association between adverse childhood experiences and adolescent pregnancy, long-term psychosocial consequences, and fetal death. Pediatrics 2004;113(2):320–7. (In eng). DOI: 10.1542/peds.113.2.320. [DOI] [PubMed] [Google Scholar]
  • 17.Kerkar S, Shankar A, Boynton-Jarrett R, Harville EW. Adverse Childhood Experiences are Associated with Miscarriage in Adulthood: The GROWH Study. Maternal and child health journal 2021;25(3):479–486. (In eng). DOI: 10.1007/s10995-020-03079-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Mason SM, Tobias DK, Clark CJ, Zhang C, Hu FB, Rich-Edwards JW. Abuse in Childhood or Adolescence and Gestational Diabetes: A Retrospective Cohort Study. American journal of preventive medicine 2016;50(4):436–444. (In eng). DOI: 10.1016/j.amepre.2015.08.033. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Schoenaker D, Callaway LK, Mishra GD. The Role of Childhood Adversity in the Development of Gestational Diabetes. American journal of preventive medicine 2019;57(3):302–310. (In eng). DOI: 10.1016/j.amepre.2019.04.028. [DOI] [PubMed] [Google Scholar]
  • 20.Stanhope KK, Cammack AL, Perreira KM, et al. Adverse childhood experiences and lifetime adverse maternal outcomes (gestational diabetes and hypertensive disorders of pregnancy) in the Hispanic Community Health Study/Study of Latinos. Annals of epidemiology 2020;50:1–6. (In eng). DOI: 10.1016/j.annepidem.2020.08.004. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Miller ES, Jensen R, Hoffman MC, et al. Implementation of perinatal collaborative care: a health services approach to perinatal depression care. Primary health care research & development 2020;21:e30. DOI: 10.1017/S1463423620000110. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Archer J, Bower P, Gilbody S, et al. Collaborative care for depression and anxiety problems. The Cochrane database of systematic reviews 2012;10:CD006525. (In eng). DOI: 10.1002/14651858.CD006525.pub2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform 2009;42(2):377–81. DOI: 10.1016/j.jbi.2008.08.010. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Carpenter MW, Coustan DR. Criteria for screening tests for gestational diabetes. American journal of obstetrics and gynecology 1982;144(7):768–73. DOI: 10.1016/0002-9378(82)90349-0. [DOI] [PubMed] [Google Scholar]
  • 25.Gestational Hypertension and Preeclampsia: ACOG Practice Bulletin, Number 222. Obstetrics and gynecology 2020;135(6):e237–e260. DOI: 10.1097/AOG.0000000000003891. [DOI] [PubMed] [Google Scholar]
  • 26.Committee Opinion No 700: Methods for Estimating the Due Date. Obstetrics and gynecology 2017;129(5):e150–e154. (In eng). DOI: 10.1097/aog.0000000000002046. [DOI] [PubMed] [Google Scholar]
  • 27.Brenner WE, Edelman DA, Hendricks CH. A standard of fetal growth for the United States of America. American journal of obstetrics and gynecology 1976;126(5):555–64. (In eng). DOI: 10.1016/0002-9378(76)90748-1. [DOI] [PubMed] [Google Scholar]
  • 28.Giurgescu C, Misra DP. Psychosocial Factors and Preterm Birth Among Black Mothers and Fathers. MCN Am J Matern Child Nurs 2018;43(5):245–251. (In eng). DOI: 10.1097/nmc.0000000000000458. [DOI] [PubMed] [Google Scholar]
  • 29.Hayes AF, Preacher KJ. Statistical mediation analysis with a multicategorical independent variable. Br J Math Stat Psychol 2014;67(3):451–70. (In eng). DOI: 10.1111/bmsp.12028. [DOI] [PubMed] [Google Scholar]
  • 30.Preacher KJ, Hayes AF. Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behav Res Methods 2008;40(3):879–91. (In eng). DOI: 10.3758/brm.40.3.879. [DOI] [PubMed] [Google Scholar]
  • 31.Prevention CfDCa. Preventing Adverse Childhood Experiences (ACEs) to improve U.S. health. (https://www.cdc.gov/media/releases/2019/p1105-prevent-aces.html).
  • 32.Gilbert LK, Breiding MJ, Merrick MT, et al. Childhood adversity and adult chronic disease: an update from ten states and the District of Columbia, 2010. American journal of preventive medicine 2015;48(3):345–9. (In eng). DOI: 10.1016/j.amepre.2014.09.006. [DOI] [PubMed] [Google Scholar]
  • 33.Chang YT, Feng JY, Chang HY, Chang YC, Lee CK. The impacts of maternal childhood adversity, stress, and mental health on child development at 6 months in Taiwan: A follow-up study. Dev Psychopathol 2020:1–10. (In eng). DOI: 10.1017/s0954579420000267. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Eismann EA, Folger AT, Stephenson NB, et al. Parental Adverse Childhood Experiences and Pediatric Healthcare Use by 2 Years of Age. The Journal of pediatrics 2019;211:146–151. (In eng). DOI: 10.1016/j.jpeds.2019.04.025. [DOI] [PubMed] [Google Scholar]
  • 35.McDonald SW, Madigan S, Racine N, Benzies K, Tomfohr L, Tough S. Maternal adverse childhood experiences, mental health, and child behaviour at age 3: The all our families community cohort study. Prev Med 2019;118:286–294. (In eng). DOI: 10.1016/j.ypmed.2018.11.013. [DOI] [PubMed] [Google Scholar]
  • 36.Sun J, Patel F, Rose-Jacobs R, Frank DA, Black MM, Chilton M. Mothers’ Adverse Childhood Experiences and Their Young Children’s Development. American journal of preventive medicine 2017;53(6):882–891. (In eng). DOI: 10.1016/j.amepre.2017.07.015. [DOI] [PubMed] [Google Scholar]
  • 37.Mersky JP, Lee CP. Adverse childhood experiences and poor birth outcomes in a diverse, low-income sample. BMC Pregnancy Childbirth 2019;19(1):387. (In eng). DOI: 10.1186/s12884-019-2560-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Reuben A, Moffitt TE, Caspi A, et al. Lest we forget: comparing retrospective and prospective assessments of adverse childhood experiences in the prediction of adult health. Journal of child psychology and psychiatry, and allied disciplines 2016;57(10):1103–12. (In eng). DOI: 10.1111/jcpp.12621. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Chandan JS, Taylor J, Bradbury-Jones C, Nirantharakumar K, Kane E, Bandyopadhyay S. COVID-19: a public health approach to manage domestic violence is needed. Lancet Public Health 2020;5(6):e309. (In eng). DOI: 10.1016/s2468-2667(20)30112-2. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplemental Digital Content_1
NIHMS1734449-supplement-Supplemental_Digital_Content_1.pdf (371.5KB, pdf)
Supplemental Digital Content_2
NIHMS1734449-supplement-Supplemental_Digital_Content_2.pdf (81.3KB, pdf)

RESOURCES