nach oben

BMC Pregnancy and Childbirth

Erschienen in:

Open Access 01.12.2023 | Research

Adverse childhood experiences and prescription opioid use during pregnancy: an analysis of the North and South Dakota PRAMS, 2019–2020

verfasst von: Alexander Testa, Benjamin Jacobs, Lixia Zhang, Dylan B. Jackson, Kyle T. Ganson, Jason M. Nagata

Erschienen in: BMC Pregnancy and Childbirth | Ausgabe 1/2023

Abstract

Objectives

This study assesses the association between adverse childhood experiences (ACEs) and prescription opioid use during pregnancy.

Methods

This study uses data on 2,999 individuals from the 2019 and 2020 Pregnancy Risk Assessment Monitoring System (PRAMS) from North Dakota and South Dakota. The relationship between ACEs and prescription opioid use during pregnancy is examined using multiple logistic regression.

Results

The prevalence of prescription opioid use increases alongside more ACE exposure. Compared to those with no ACEs, recent mothers with three or more ACEs have a 2.4 greater odds of prescription opioid use during pregnancy (aOR [adjusted odds ratio] = 2.437; 95% CI [confidence interval] = 1.319, 4.503).

Conclusion

Exposure to three or more ACEs are associated with a higherrisk of prescription opioid use during pregnancy. Additional research is needed better understand the mechanisms that link ACEs and prescription opioid use during pregnancy, as well as how to best support those with ACEs exposure in a trauma-informed manner to reduce the risk of substance use.

Additional file 1. Methodological Appendix.

Additional file 2: Appendix A. Flowchart of Sample Selection Procedure. Appendix B. Definition of Adverse Childhood Experiences (ACEs). Appendix C. Results of Multiple Logistic Regression of Specific ACEs on Prescription Opioid Use During Pregnancy and Covariates (N = 2,999). Appendix D. Results of Multiple Logistic Regression of Number of ACEs on Prescription Opioid Use During Pregnancy and Covariates (N = 2,999). Appendix E. Patterns of Prescription Opioid Use During Pregnancy by ACEs (N = 2,999).

Supplementary Information

The online version contains supplementary material available at https://doi.org/10.1186/s12884-023-05925-7.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Introduction

From 2020 to 2021, over 107,000 drug overdoses occurred in the United States [1]. A substantial driver of overdose mortality is opioids, which accounted for approximately 76% of all drug overdose deaths in 2021 [1]. The opioid epidemic has touched many segments of the population over the past two decades. However, during the opioid epidemic crisis, pregnant women are a important population of focus [2].

Indeed, prior research demonstrates a relationship between prescription opioid analgesics use (i.e., butorphanol, buprenorphine for pain, codeine, fentanyl, hydrocodone, meperidine, methadone for pain, morphine, opium, oxycodone, pentazocine, tapentadol, and tramadol) and adverse infant birth outcomes including poor fetal growth, preterm birth, congenital disabilities, and neonatal abstinence syndrome [3‐7]. Despite the risk prescription opioids pose for maternal and infant health, estimates suggest that nearly seven percent of women have reported using a prescription opioid during pregnancy, and among these, 21.2% reported misuse (i.e., obtaining from a source other than a health care provider or using for a reason other than pain) [8]. Given the potential harms of prenatal prescription opioid exposure to offspring’s health and development, it is essential to identify the factors associated with prenatal prescription opioid use to inform policy and practice better. Of notable importance is the role of earlier stressful life events in contributing to the risk of prescription opioid use during pregnancy [9].

Adverse childhood experiences (ACEs) are experiences with abuse, neglect, and household dysfunction during childhood and adolescence [10]. Research on ACEs demonstrates that they are highly powerful, with exposure to ACEs increasing the chance of poor outcomes later in life, including negative physical and mental health [11, 12], diminished employment prospects [13], barriers to health care utilization [14], and premature mortality [15]. In particular, ACEs have a dose–response relationship with unwanted outcomes such that experiencing more ACEs—such as three or more—is associated with worse outcomes [16]. Prior research finds that ACEs are associated with substance use in adulthood [17‐20], including both prescription and illicit opioid use [21‐24]. However, limited research has investigated the relationship between ACEs and prescription opioid use during pregnancy, despite extant research documenting a connection between ACEs and other types of substance use during pregnancy, including various illicit drugs [25, 26], tobacco [26], alcohol [27], marijuana [28, 29]. One study on the relationship between ACEs and prescription opioid use in pregnancy uses an unrepresentative sample of 303 pregnant women in a psychosocial perinatal support program in a Southern urban medical clinic, finding no association between more ACEs exposure and prescription opioid use for nonmedical reasons during pregnancy [30], although certain ACEs subtypes such as being exposed to childhood maltreatment (i.e., emotional abuse, physical abuse sexual abuse, emotional neglect, and physical neglect) were associated with prescription opioid use during pregnancy.

Using data on representative samples of live births in two U.S. states, the current study extends prior literature by examining whether ACEs exposure is associated with prescription opioid use during pregnancy.

Methods

Data

Data are from the Pregnancy Risk Assessment Monitoring System (PRAMS). The PRAMS is an ongoing population surveillance system of live births in the United States conducted by the Centers for Disease Control and Prevention (CDC) and state health departments. Data are collected yearly via a stratified systematic sample of birth certificate records. The PRAMS data are from three separate sources: (1) birth certificate records, (2) vital record systems, and (3) responses to a PRAMS survey. The PRAMS survey is mailed to the home address of recent mothers approximately 2 to 4 months following their birth delivery. After up to three mailing attempts, telephone calls are made to non-responders. Survey weights enable adjustment for non-response and non-coverage, thereby making samples representative of live births in a given state [31].

While the entire PRAMS collects data from 46 states representing approximately 81% of all U.S. live births, a subset of states in specific years ask topic-specific questions. In 2019 and 2020, a supplemental survey was administered to a subset of jurisdictions asking about prescription opioid use during pregnancy [8]. In addition, select states include topic-specific questions asking mothers about various life experiences. Only two states—North Dakota and South Dakota—have questions asking about mothers’ adverse childhood experiences [32]. Accordingly, the current study uses data on 2,999 mothers from the 2019 and 2020 PRAMS surveys conducted in North and South Dakota. Additional file 2: Appendix A provides a flow chart describing the analytic sample section.

The study was performed in accordance with the Declaration of Helsinki. The study was approved by the Centers for Disease Control and Prevention in accordance with the data usage agreement for the Pregnancy Risk Assessment Monitoring System. All participants provided informed consent; for minors younger than 18 informed consent was waived by CDC. The general PRAMS methodology and protocol have been reviewed and approved by the CDC institutional review board, and state PRAMS projects undergo review by the local institutional review board of record for the health department. An informed consent document in each survey packet explains a participant’s rights in mail surveys. No written consent is required; consent is implied if the survey is completed and returned [31]. The informed consent document is read verbally for phone interviews, and the participant verbally agrees to proceed with the survey. Minors younger than 18 years who have given birth are considered emancipated for decisions about their children and do not require consent from parents or guardians to participate [31]. The PRAMS survey is administered in both English and Spanish. While an interviewer verbally administers phone-based surveys, mail surveys may depend on a women’s literacy levels and comfort in responding to the survey, neither of which are assessed in the PRAMS data collection process, and therefore consent is not requested from a parent or legal guardian in cases when an individual has low literacy levels [33].

Dependent variable

Consistent with prior research [8, 9, 34], any prescription opioid use is a dichotomous indicator of whether a respondent reported using any prescription opioids during their most recent pregnancy. Respondents were asked, “During your most recent pregnancy, did you use any of the following prescription pain relievers?”: (a) hydrocodone (like Vicodin®, Norco®, or Lortab®), (b) codeine (like Tylenol® #3 or #4, not regular Tylenol®), (c) oxycodone (like Percocet®, Percodan®, OxyContin®, or Ultracet®), (d) tramadol (like Ultram® or Ultracet®), (e) hydromorphone or morpheridine (like Demorol®, Exalgo®, or Dilaudid®), (f) oxymorphone (like Opana®), (g) morphine (like MS Contin®, Avinza® or Kadian®), or (h) fentanyl (like Duragesic®, Fentora®, or Actiq®). Respondents who answered affirmatively to using any of these prescription opioids during pregnancy were coded as a value of 1; those who did not indicate any use of these prescription opioids were coded as 0.

Independent variable

ACEs were measured using respondent self-report on ten types of childhood adversity before age 18. The ten questions used to classify ACEs closely approximate the measures from the CDC-Kaiser ACE Study [10]. Additional file 2: Appendix B presents the definitions and prevalence for the ten items. Consistent with prior research using PRAMS data, responses to the 10 ACE items are combined to create a cumulative score ranging from 0–10. The total ACEs scores were grouped into four categories: 0 ACE, 1 ACE, 2 ACEs, 3 or more ACEs [9, 32].

Control variables

Control variables include the mother’s age (< 24, 25–29, 30–34, and 35 or older), mother’s race/ethnicity (White, Hispanic, Black, Native American, Asian/Other, and mixed race), mother’s educational attainment (0 = less than college, 1 = college graduate), marital status (0 = not currently married, 1 = currently married), number of prior births (0, 1, 2, or 3 +), whether a mother reported being on Medicaid in the three months before pregnancy (1 = yes; 0 = no), household income (≤ $16,000, $16,000-$40,000, $40,001-$85,000, or > $85,000), state of residence, and year of birth.

Analytic approach

The bivariate association between the number of ACEs and prescription opioid use during pregnancy is assessed using a chi-square (χ²) test. Multivariable logistic regression is used to examine the associations between ACEs exposure (0, 1, 2, or 3 + ACEs) and prescription opioid use during pregnancy, net control variables. Analyses also assess the relationship between exposure to each specific type of ACE and prescription opioid use during pregnancy. All data analyses were conducted using the svypackage for weighted survey data in Stata/S.E. version 17. Variance inflation factors were under 2, indicating no significant issues with multicollinearity [35].

Results

Summary statistics are presented in Table 1. Overall, 4.7% of the sample reported prescription opioid use during pregnancy; 39.5% reported no ACEs, and 30% of the sample reported three or more ACEs. Figure 1 shows that the prevalence of prescription opioid use increased alongside higher ACEs score: 0 ACEs (2.3%), 1 ACE (4.7%), 2 ACEs (5.5%), and 3 or more ACEs (7.5%). A chi-square test reveals a statistically significant difference between the prevalence of prescription opioid use in different ACEs groups (χ² = 37.69, p < 0.001).

Table 1

Weighted summary statistics of analytic sample (N = 2,999)

Variable	%
Prescription Opioid Use	4.7%
Number of ACEs
0	39.5%
1	19.0%
2	11.5%
3 or More	30.0%
Mother’s Age
Less than 24	20.0%
25–29	34.3%
30–34	31.7%
35 or Older	13.9%
Mother’s Race/Ethnicity
White	75.1%
Hispanic	4.8%
Black	4.4%
Native American	9.7%
Asian/Other	2.5%
Mixed Race	3.4%
Mother’s Educational Attainment
Less than High School	9.2%
High School Graduate	20.7%
Some College	30.4%
College Graduate	39.8%
Currently Married	68.5%
Number of Prior Births
0	34.9%
1	31.2%
2	18.8%
3 +	15.0%
Medicaid	12.9%
Household Income
≤ $16,000	15.0%
$16,000-$40,000	17.7%
$40,001 – $85,000	36.5%
> $85,000	30.9%
State of Residence
North Dakota	43.4%
South Dakota	56.6%

Abbreviations: ACEs Adverse childhood experiences

The results of the multivariable logistic regression in Table 2 show that compared to those with no ACEs, recent mothers with three or more ACEs had approximately a 2.4 greater odds of prescription opioid use during pregnancy (aOR [adjusted odds ratio] = 2.437; 95% CI [confidence interval] = 1.319, 4.503). The multiple logistic regression analysis Additional file 2: Appendix C detail that eight of the 10 ACEs (except for parental separation and household violence) had a positive and statistically significant association with prescription opioid use during pregnancy.

Table 2

Results of multiple logistic regression of number of ACEs on prescription opioid use during pregnancy and covariates (N = 2,999)

Number of ACEs	OR	95% CI
0 (Reference)	—	—
1	1.884	(0.976—3.638)
2	1.986	(0.903—4.368)
3 or More	2.437**	(1.319—4.503)

Control variables include: mother’s age, mother’s race/ethnicity, mother’s educational attainment, currently married, number of prior births, Medicaid, income, state of residence, and year of birth

Abbreviations: OR Odds ratio, CI Confidence interval, ACEs Adverse childhood experiences

^**p < .01

Supplemental analysis

We conducted a few additional analyses to assess the overall findings. First, considering findings that the use of alcohol, tobacco, and marijuana is associated with prescription opioid use during pregnancy [36, 37], Additional file 2: Appendix D reassesses the main results while controlling for other types of substance use during pregnancy. This analysis includes variables for the average number of cigarettes a mother reported smoking per day across all three trimesters of pregnancy (0, less than 10, or 10 or more), the number of alcoholic drinks a mother reported consuming per week in the 3 months before becoming pregnancy (0 drinks, less than 1 drink, 1–3 drinks, 4–7 drinks, more than 7 drinks), and whether the mother reported using marijuana during pregnancy (1 = yes; 0 = no). After including these control variables, the results from the multiple regression model (n = 2,954) report similar results to the main analysis, as respondents with three or more ACEs have significantly higher odds of reporting prescription opioid use during pregnancy relative to respondents with no ACEs (OR = 2.221, 95% CI = 1.162, 4.245).

Next, we conducted a descriptive supplemental analysis using a measure of patterns of prescription opioid use, including no prescription opioid use, pain management, and prescription opioid misuse across ACEs exposure. A description of variable coding is provided in the methodological appendix. Additional file 2: Appendix E shows the percentage of respondents with no opioid use, opioid use for pain management, and opioid misuse by ACEs level. Overall, opioid use for pain management is lowest among respondents with 0 ACEs (2.2%) and raises alongside greater ACEs exposure: 1 ACE = 4.3%, 2 ACEs = 4.5%, 3 + ACEs = 5.6%. A similar pattern is found with pain management, which is reported by 2.1% of respondents with 0 ACE exposure compared to 5.6% with three or more ACEs. Likewise, opioid misuse occurs in 0.1% of individuals with 0 ACEs exposure but 1.9% of persons with three or more ACEs. Results from Fisher’s exact test for r X c tables determine that the difference between all three types of patterns of opioid use by ACEs level is statistically significant at the p< 0.001 level [38, 39]. However, small cell sizes prohibited multivariable analyses, and thus the differences should be interpreted cautiously.

Discussion

The core findings of this study reveal that ACEs—especially three or more ACEs—were associated with a 2.4-fold increase in the odds of prescription opioid use during pregnancy. These findings confirm earlier research that found a connection between ACEs and prescription opioid use among non-pregnant populations [23, 40, 41]. However, the results differ from recent work conducted by Osofsky et al. [30], which found no association between more ACEs and prescription opioid use for nonmedical reasons during pregnancy among a sample of 303 pregnant women embedded in a psychosocial perinatal support program in a Southern urban medical clinic. In addition, it is important to note that beyond the impact of cumulative ACEs, the current study found that eight out of the 10 ACEs were associated with prescription opioid use during pregnancy. Previous research by Osofsky et al. [30] found a relationship between indicators of child maltreatment and prescription opioid use for nonmedical reasons during pregnancy but no relationship with household dysfunction (i.e., parental separation or divorce, domestic violence, household substance abuse, family mental illness, and family member imprisonment). Somewhat consistent with this finding, our measures of abuse and neglect were consistently associated with prescription opioid use. In contrast, parental separation or divorce and domestic violence (i.e., indicators of household dysfunction) were not. Even so, our findings did indicate that measures related to household mental health, substance use, and incarceration were significantly associated with prescription opioid use. Still, due to differences in samples and because Osofsky et al. focused on prescription opioid use for nonmedical reasons, it is challenging to compare the results of the two studies directly. The findings of this study expand upon prior research by offering critical evidence that the relationship between ACEs and prescription opioid use in adulthood extends to the prenatal period. The finding of elevated patterns of prescription opioid use during pregnancy among women who experienced three or more ACEs offers an essential insight into the enduring role of early life adversity on health behaviors during pregnancy [42]. It is also important to note that most women—even in the face of ACEs exposure—did not use prescription opioids during pregnancy. For instance, while 7.5% of women with three or more ACEs used prescription opioids during pregnancy, over 90% of respondents with high ACEs exposure did not use prescription opioids during this period. Accordingly, while ACEs increased the risk of prenatal prescription opioid use, this was not the case for most pregnant women, suggesting that high levels of early life adversity increase the risk of, but do not guarantee, compromised behavioral health during pregnancy.

The findings from this study contribute to the existing literature regarding how ACEs are adverse outcomes in and of themselves. ACEs often contribute to downstream health effects due to allostatic load and stress and increase the risk of poor health behaviors such as substance use [10‐12]. Importantly, the findings in this study offer a key contribution to the literature’s understanding of the consequences of ACEs by demonstrating their connection to the use of prescription opioids during the critical period of pregnancy. The results suggest that even distal life events in childhood and adolescence can shape health behaviors during pregnancy by contributing to increased use of prescription opioids that potentially harm infant health [3‐7]. Accordingly, these findings reveal that the consequences of ACEs may be intergenerational, impacting not only the individual directly exposed to ACEs but also potentially harming the health of offspring from the earliest days of life.

While the current study established a connection between ACEs and prescription opioid use during pregnancy, future research should explore potential pathways to explain this relationship. For instance, many recent studies have documented that ACEs are strongly associated with chronic pain in children and adults [43‐47], which may lead to prescription opioid use for pain management but could also lead to patterns of opioid misuse. Likewise, ACEs can result in challenges with emotional regulation and a propensity for outlets to alleviate adverse emotional states [25, 48]. Given that pregnancy is an emotionally vulnerable period, such states may be heightened during times of pregnancy, thereby amplifying the risk of prescription opioid use. Uncovering the mechanisms of why ACE exposure leads to an increased risk of prescription opioid use during pregnancy for some women is crucial for developing programmatic interventions to provide support to ACEs exposed populations and promote positive health behaviors and healthy pregnancy.

The results also highlight the importance of detecting and mitigating ACEs’ negative repercussions on behavioral health. One means may be using clinical screenings during prenatal care and primary care visits to detect the presence of ACEs better and, when detected, provide trauma-informed care to help ensure a healthy pregnancy. For instance, recent evidence from two pilot studies in the Kaiser-Permanente system [49] found ACEs screenings can be feasibly conducted in a prenatal care setting without re-traumatization [50], and such practices can improve women’s health outcomes and children. Therefore, assessing the feasibility of such approaches to mitigate prescription opioid use during pregnancy is an important area for future research to consider carefully.

Limitations

There are limitations to the current analysis that can be expanded upon in future research. First, North Dakota and South Dakota were the only two states which asked questions about ACEs and prescription opioid use during pregnancy in the PRAMS study. Accordingly, the results may not be generalizable outside of these contexts, especially considering that these two states are unique in many regards, such as being more rural and having higher populations of White and Native American persons than the U.S. general population. Second, the questions about ACEs and prescription opioid use may be subject to recall or social desirability bias. Third, the study focused on various prescription opioids used during pregnancy. However, the findings of this study cannot be generalized to the use of illicit non-prescription opioids such as heroin. Fourth, because of sample limitations, we could not examine other questions about opioid use more granularly defined in multivariable analyses, such as whether opioids were used for pain management or nonmedical reasons, the frequency of prescription opioid use, and the timing in the pregnancy during which prescription opioids were used, and from where a respondent obtained the prescription opioids [9]. Larger-scale quantitative studies and qualitative research would be helpful to ascertain better the relationship between ACEs and specific reasons for and patterns of prescription opioid use during pregnancy. Finally, because the PRAMS data are cross-sectional, the findings should be interpreted as associations rather than causal relationships.

Conclusion

ACEs and prescription opioid uses are serious public health concerns that can influence maternal and infant health. The current study offered a novel insight into the relationship between ACEs and prescription opioid use during pregnancy. The findings suggest the need for additional research to understand better the mechanisms that lead to a link between ACEs and prescription opioid use during pregnancy, as well as how to support those with ACEs exposure in a trauma-informed manner to reduce the risk of subsequent substance use.

Acknowledgements

The authors wish to acknowledge the CDC PRAMS Working Group: Tammie Yelldell, MPH (AL), Kathy Perham-Hester, MS, MPH (AK), Letitia de Graft-Johnson, DrPH, MHSA (AR), Ashley Juhl, MSPH (CO), Jennifer Morin, MPH (CT), George Yocher, MS (DE), Tara Hylton, MPH (FL), Florence A. Kanu, PhD, MPH (GA), Matt Shim, PhD, MPH (HI), Julie Doetsch, MA (IL), Jennifer Pham (IA), Tracey D. Jewell, MPH (KY), Rosaria Trichilo, MPH (LA), Tom Patenaude, MPH (ME), Laurie Kettinger, MS (MD), Hafsatou Diop, MD, MPH (MA), Peterson Haak (MI), Mira Grice Sheff, PhD, MS (MN), Brenda Hughes, MPPA (MS), Venkata Garikapaty, PhD (MO), Emily Healy, MS (MT), Jessica Seberger (NE), David J. Laflamme, PhD, MPH (NH), Sharon Smith Cooley, MPH (NJ), Sarah Schrock, MPH (NM), Anne Radigan (NY), Pricila Mullachery, MPH (New York City), Kathleen Jones-Vessey, MS (NC), Grace Njau, MPH (ND), Ayesha Lampkins, MPH, CHES (OK), Cate Wilcox, MPH (OR), Sara Thuma, MPH (PA), Karine Tolentino Monteiro, MPH (RI), Kristin Simpson, MSW, MPA (SC), Ransom Wyse, MPH, CPH (TN), Tanya Guthrie, PhD (TX), Nicole Stone, MPH (UT), Peggy Brozicevic (VT), Kenesha Smith, MSPH (VA), Linda Lohdefinck (WA), Melissa Baker, MA (WV), Fiona Weeks, MSPH (WI), Lorie Chesnut, PhD (WY), CDC PRAMS Team, Women’s Health and Fertility Branch, Division of Reproductive Health.

Declarations

Not applicable.

Competing interests

The authors declare no competing interests.

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1. Methodological Appendix.

Centers for Disease Control and Prevention. U.S. Overdose Deaths In 2021 Increased Half as Much as in 2020 - But Are Still Up 15%. Published 2022. Accessed 10 Oct 2022. https://www.cdc.gov/nchs/pressroom/nchs_press_releases/2022/202205.htm.

Patrick SW, Schiff DM, Committee on substance use and prevention, et al. A public health response to opioid use in pregnancy. Pediatrics. 2017;139(3):e20164070. https://doi.org/10.1542/peds.2016-4070.CrossRefPubMed

Yazdy M, Desai R, Brogly S. Prescription opioids in pregnancy and birth outcomes: a review of the literature. J Pediatr Genet. 2015;04(02):056–70. https://doi.org/10.1055/s-0035-1556740.CrossRef

Patrick SW, Dudley J, Martin PR, et al. Prescription opioid epidemic and infant outcomes. Pediatrics. 2015;135(5):842–50. https://doi.org/10.1542/peds.2014-3299.CrossRefPubMedPubMedCentral

Ziedan E, Kaestner R. Effect of Prescription Opioids and Prescription Opioid Control Policies on Infant Health. National Bureau of Economic Research; 2020:w26749. https://doi.org/10.3386/w26749.

Brogly SB, Velez MP, Werler MM, Li W, Camden A, Guttmann A. Prenatal opioid analgesics and the risk of adverse birth outcomes. Epidemiology. 2021;32(3):448–56. https://doi.org/10.1097/EDE.0000000000001328.CrossRefPubMedPubMedCentral

Broussard CS, Rasmussen SA, Reefhuis J, et al. Maternal treatment with opioid analgesics and risk for birth defects. Am J Obstet Gynecol. 2011;204(4):314.e1-11. https://doi.org/10.1016/j.ajog.2010.12.039.CrossRefPubMed

Ko JY, D’Angelo DV, Haight SC, et al. Vital Signs: Prescription Opioid Pain Reliever Use During Pregnancy — 34 US Jurisdictions, 2019. MMWR Morb Mortal Wkly Rep. 2020;69(28):897–903. https://doi.org/10.15585/mmwr.mm6928a1.CrossRefPubMedPubMedCentral

Testa A, Crawford AD, Jackson DB, Gemmill A. Stressful life events and prescription opioid use during pregnancy: findings from the 2019 pregnancy risk assessment monitoring system. Soc Psychiatry Psychiatr Epidemiol. 2022. https://doi.org/10.1007/s00127-022-02349-0.

10.

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. Am J Prev Med. 1998;14(4):245–58. https://doi.org/10.1016/S0749-3797(98)00017-8.CrossRefPubMed

11.

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):e356–66. https://doi.org/10.1016/S2468-2667(17)30118-4.CrossRefPubMed

12.

Bellis MA, Hughes K, Ford K, Ramos Rodriguez G, Sethi D, Passmore J. Life course health consequences and associated annual costs of adverse childhood experiences across Europe and North America: a systematic review and meta-analysis. Lancet Public Health. 2019;4(10):e517–28. https://doi.org/10.1016/S2468-2667(19)30145-8.CrossRefPubMedPubMedCentral

13.

Liu Y, Croft JB, Chapman DP, et al. Relationship between adverse childhood experiences and unemployment among adults from five US states. Soc Psychiatry Psychiatr Epidemiol. 2013;48(3):357–69. https://doi.org/10.1007/s00127-012-0554-1.CrossRefPubMed

14.

Testa A, Jackson DB, Vaughn MG, Ganson KT, Nagata JM. Adverse Childhood Experiences, health insurance status, and health care utilization in middle adulthood. Soc Sci Med. 2022:115194. https://doi.org/10.1016/j.socscimed.2022.115194.

15.

Brown DW, Anda RF, Tiemeier H, et al. Adverse childhood experiences and the risk of premature mortality. Am J Prev Med. 2009;37(5):389–96. https://doi.org/10.1016/j.amepre.2009.06.021.CrossRefPubMed

16.

Sacks V, Murphey D, Moore K. Adverse Childhood Experiences: National and State-Level Prevalence. Child Trends. 2014:1–11.

17.

Leza L, Siria S, López-Goñi JJ, Fernández-Montalvo J. Adverse childhood experiences (ACEs) and substance use disorder (SUD): a scoping review. Drug Alcohol Depend. 2021;221:108563. https://doi.org/10.1016/j.drugalcdep.2021.108563.CrossRefPubMed

18.

Shin SH, McDonald SE, Conley D. Patterns of adverse childhood experiences and substance use among young adults: a latent class analysis. Addict Behav. 2018;78:187–92. https://doi.org/10.1016/j.addbeh.2017.11.020.CrossRefPubMed

19.

Rogers CJ, Pakdaman S, Forster M, et al. Effects of multiple adverse childhood experiences on substance use in young adults: A review of the literature. Drug Alcohol Depend. 2022;234:109407. https://doi.org/10.1016/j.drugalcdep.2022.109407.CrossRefPubMed

20.

Davis JP, Tucker JS, Stein BD, D’Amico EJ. Longitudinal effects of adverse childhood experiences on substance use transition patterns during young adulthood. Child Abuse Neglect. 2021;120:105201. https://doi.org/10.1016/j.chiabu.2021.105201.CrossRefPubMedPubMedCentral

21.

Meyer D, Siddiqui Z, Deol E, et al. Adverse childhood experiences and opioid use disorder: a systematic review. Psychoneuroendocrinology. 2023;153:106224. https://doi.org/10.1016/j.psyneuen.2023.106224.CrossRef

22.

Stein MD, Conti MT, Kenney S, et al. Adverse childhood experience effects on opioid use initiation, injection drug use, and overdose among persons with opioid use disorder. Drug Alcohol Depend. 2017;179:325–9. https://doi.org/10.1016/j.drugalcdep.2017.07.007.CrossRefPubMedPubMedCentral

23.

Merrick MT, Ford DC, Haegerich TM, Simon T. Adverse childhood experiences increase risk for prescription opioid misuse. J Prim Prev. 2020;41(2):139–52. https://doi.org/10.1007/s10935-020-00578-0.CrossRefPubMed

24.

Guarino H, Mateu-Gelabert P, Quinn K, et al. Adverse Childhood Experiences Predict Early Initiation of Opioid Use Behaviors. Front Sociol. 2021;6. Accessed 31 Jan 2023. https://www.frontiersin.org/articles/10.3389/fsoc.2021.620395.

25.

Currie CL, Tough SC. Adverse childhood experiences are associated with illicit drug use among pregnant women with middle to high socioeconomic status: findings from the All Our Families Cohort. BMC Pregnancy Childbirth. 2021;21(1):133. https://doi.org/10.1186/s12884-021-03591-1.CrossRefPubMedPubMedCentral

26.

Racine N, McDonald S, Chaput K, Tough S, Madigan S. Pathways from maternal adverse childhood experiences to substance use in pregnancy: findings from the all our families cohort. J Women’s Health. 2021;30(12):1795–803. https://doi.org/10.1089/jwh.2020.8632.CrossRef

27.

Frankenberger DJ, Clements-Nolle K, Yang W. The association between adverse childhood experiences and alcohol use during pregnancy in a representative sample of adult women. Women’s Health Issues. 2015;25(6):688–95. https://doi.org/10.1016/j.whi.2015.06.007.CrossRefPubMedPubMedCentral

28.

Testa A, Jackson DB, Boccio C, Ganson KT, Nagata JM. Adverse childhood experiences and marijuana use during pregnancy: Findings from the North Dakota and South Dakota PRAMS, 2017–2019. Drug Alcohol Depend. 2022;230:109197. https://doi.org/10.1016/j.drugalcdep.2021.109197.CrossRefPubMed

29.

Klasner C, Brown J, Gopalakrishnan M, Metwally DE, Besse M, Mark K. Effect of maternal adverse childhood experiences (ACE) and cannabis use on pregnancy outcomes. Arch Womens Ment Health. 2022;25(6):1097–104. https://doi.org/10.1007/s00737-022-01269-x.CrossRefPubMed

30.

Osofsky JD, Osofsky HJ, Frazer AL, et al. The importance of adverse childhood experiences during the perinatal period. Am Psychol. 2021;76(2):350–63. https://doi.org/10.1037/amp0000770.CrossRefPubMed

31.

Shulman HB, D’Angelo DV, Harrison L, Smith RA, Warner L. The Pregnancy Risk Assessment Monitoring System (PRAMS): overview of design and methodology. Am J Public Health. 2018;108(10):1305–13. https://doi.org/10.2105/AJPH.2018.304563.CrossRefPubMedPubMedCentral

32.

Testa A, Jackson DB, Ganson KT, Nagata JM. Maternal adverse childhood experiences and pregnancy intentions. Ann Epidemiol. 2021;64:47–52. https://doi.org/10.1016/j.annepidem.2021.09.011.CrossRefPubMed

33.

Ahluwalia IB, Helms K, Morrow B. Assessing the validity and reliability of three indicators self-reported on the pregnancy risk assessment monitoring system survey. Public Health Rep. 2013;128(6):527–36. https://doi.org/10.1177/003335491312800612.CrossRefPubMedPubMedCentral

34.

Testa A, Fahmy C, Jackson DB. Incarceration exposure and prescription opioid use during pregnancy. Drug Alcohol Depend. 2022;235:109434. https://doi.org/10.1016/j.drugalcdep.2022.109434.CrossRefPubMed

35.

Allison P. When Can You Safely Ignore Multicollinearity? Statistical Horizons. 2012. Accessed 6 Oct 2022. https://statisticalhorizons.com/multicollinearity/.

36.

Kozhimannil KB, Graves AJ, Levy R, Patrick SW. Nonmedical Use of Prescription Opioids among Pregnant U.S. Women. Women’s Health Issues. 2017;27(3):308–15. https://doi.org/10.1016/j.whi.2017.03.001.CrossRefPubMedPubMedCentral

37.

Smith MV, Costello D, Yonkers KA. Clinical correlates of prescription opioid analgesic use in pregnancy. Matern Child Health J. 2015;19(3):548–56. https://doi.org/10.1007/s10995-014-1536-6.CrossRefPubMedPubMedCentral

38.

Clarkson DB, Fan Y an, Joe H. A remark on algorithm 643: FEXACT: an algorithm for performing Fisher’s exact test in r x c contingency tables. ACM Trans Math Softw. 1993;19(4):484–8. https://doi.org/10.1145/168173.168412.CrossRef

39.

Mehta CR, Patel NR. A Network algorithm for performing fisher’s exact test in r × c contingency tables. J Am Stat Assoc. 1983;78(382):427–34. https://doi.org/10.1080/01621459.1983.10477989.CrossRef

40.

Quinn K, Frueh BC, Scheidell J, Schatz D, Scanlon F, Khan MR. Internalizing and externalizing factors on the pathway from adverse experiences in childhood to non-medical prescription opioid use in adulthood. Drug Alcohol Depend. 2019;197:212–9. https://doi.org/10.1016/j.drugalcdep.2018.12.029.CrossRefPubMedPubMedCentral

41.

Tang S, Ports KA, Zhang K, Lin HC. Adverse childhood experiences, internalizing/externalizing symptoms, and associated prescription opioid misuse: a mediation analysis. Prev Med. 2020;134:106034. https://doi.org/10.1016/j.ypmed.2020.106034.CrossRefPubMedPubMedCentral

42.

Duffy KA, McLaughlin KA, Green PA. Early life adversity and health-risk behaviors: proposed psychological and neural mechanisms. Ann N Y Acad Sci. 2018;1428(1):151–69. https://doi.org/10.1111/nyas.13928.CrossRefPubMedPubMedCentral

43.

Brown RC, Plener PL, Braehler E, Fegert JM, Huber-Lang M. Associations of adverse childhood experiences and bullying on physical pain in the general population of Germany. J Pain Res. 2018;11:3099–108. https://doi.org/10.2147/JPR.S169135.CrossRefPubMedPubMedCentral

44.

Groenewald CB, Murray CB, Palermo TM. Adverse childhood experiences and chronic pain among children and adolescents in the United States. Pain Rep. 2020;5(5):e839. https://doi.org/10.1097/PR9.0000000000000839.CrossRefPubMedPubMedCentral

45.

Nelson S, Simons LE, Logan D. The Incidence of Adverse Childhood Experiences (ACEs) and their association with pain-related and psychosocial impairment in youth with chronic pain. Clin J Pain. 2018;34(5):402–8. https://doi.org/10.1097/AJP.0000000000000549.CrossRefPubMed

46.

Nelson SM, Cunningham NR, Kashikar-Zuck S. A conceptual framework for understanding the role of adverse childhood experiences in pediatric chronic pain. Clin J Pain. 2017;33(3):264–70. https://doi.org/10.1097/AJP.0000000000000397.CrossRefPubMedPubMedCentral

47.

You DS, Albu S, Lisenbardt H, Meagher MW. Cumulative childhood adversity as a risk factor for common chronic pain conditions in young adults. Pain Med. 2019;20(3):486–94. https://doi.org/10.1093/pm/pny106.CrossRefPubMed

48.

Dennison MJ, Rosen ML, Sambrook KA, Jenness JL, Sheridan MA, McLaughlin KA. Differential associations of distinct forms of childhood adversity with neurobehavioral measures of reward processing: a developmental pathway to depression. Child Dev. 2019;90(1):e96–113. https://doi.org/10.1111/cdev.13011.CrossRefPubMed

49.

Watson C, Kathryn RK, Nancy G, Kelly YWC. Promising Practices for Implementing Adverse Childhood Experiences and Resilience Screening in Obstetric Care. J Womens Health (Larchmt). 2022. https://doi.org/10.1089/jwh.2022.0260.

50.

Racine N, Killam T, Madigan S. Trauma-informed care as a universal precaution: beyond the adverse childhood experiences questionnaire. JAMA Pediatr. 2020;174(1):5–6. https://doi.org/10.1001/jamapediatrics.2019.3866.CrossRefPubMed

Titel: Adverse childhood experiences and prescription opioid use during pregnancy: an analysis of the North and South Dakota PRAMS, 2019–2020
verfasst von: Alexander Testa
Benjamin Jacobs
Lixia Zhang
Dylan B. Jackson
Kyle T. Ganson
Jason M. Nagata
Publikationsdatum: 01.12.2023
Verlag: BioMed Central
Erschienen in: BMC Pregnancy and Childbirth / Ausgabe 1/2023
Elektronische ISSN: 1471-2393
DOI: https://doi.org/10.1186/s12884-023-05925-7

Update Gynäkologie

Bestellen Sie unseren Fach-Newsletter und bleiben Sie gut informiert – ganz bequem per eMail.

Newsletter bestellen

Die Highlights vom Kongress des American College of Cardiology 2024

Springer Medizin

Adverse childhood experiences and prescription opioid use during pregnancy: an analysis of the North and South Dakota PRAMS, 2019–2020