https://orcid.org/0000-0002-5856-9350
Figures
Abstract
Background
Few studies have provided inconsistent findings on the neurodevelopmental impact of prescription prenatal opioid exposure (PPOE). In this study, we examined the association between PPOE and developmental vulnerability later in childhood.
Methods
This was a matched cohort study using the Manitoba Population Research Data Repository. This cohort included dyads with children born in Manitoba, Canada between 2005–2011 with follow up until 2016. Each exposed child was matched to up to four controls based on birthing parent’s age, gestational age, sex, kindergarten year, and income quintile. A sibling cohort was created to compare the outcomes between exposed and unexposed siblings. PPOE was defined as filling ≥ 2 prescriptions for opioids at any time during pregnancy. Of the 973 children with PPOE, the majority (94%) had low-potency opioid exposure, primarily codeine. The Early Development Instrument (EDI) was used to assess developmental vulnerability in kindergarten. Multivariable logistic regression models were used to adjust for confounders.
Results
Of the 103,905 eligible children, 51% of the exposed group (n = 973) were developmentally vulnerable in 1 or more domains, compared with 32% of the control group (n = 3,814) (Adjusted Odds Ratio [AOR] 1.46; 95% CI 1.23-1.71). Children in the exposed group had a significantly higher likelihood of being vulnerable in all domains: physical health and well-being (AOR 1.31; 95%CI 1.08-1.59), communication skills and general knowledge (AOR 1.53;95%CI 1.25-1.88), language and cognitive development (AOR 1.53;95%CI 1.25-1.86), social competence (AOR 1.60;95%CI 1.32-1.95); emotional maturity domain was the least affected (AOR 1.25;95%CI 1.01-1.55). There was a higher risk of developmental vulnerability in children exposed to opioids in early pregnancy, longer durations and higher opioid dose. In the sibling cohort, no significant differences were observed in the EDI outcomes between exposed and unexposed siblings (AOR 0.92; 95% CI 0.58-1.46).
Conclusion
In the matched cohort study, exposure to prescription opioids during pregnancy was associated with a higher risk of developmental vulnerability later in childhood. In the sibling analysis, no differences were observed. These data strongly suggest that families should be offered early and long-term developmental screening and family-centered support.
Citation: Abulannaz O, Ruth CA, Camden A, Brownell M, Ricci MF, Dragan R, et al. (2026) Teacher-reported kindergarten development among children exposed to prescription opioids during pregnancy. PLoS One 21(8): e0355101. https://doi.org/10.1371/journal.pone.0355101
Editor: Omid Beiki, Karolinska Institutet, SWEDEN
Received: September 3, 2025; Accepted: July 16, 2026; Published: August 6, 2026
Copyright: © 2026 Abulannaz et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: The raw data used in this study were obtained from provincial administrative and registry databases housed in the Manitoba Population Research Data Repository, Manitoba Centre for Health Policy, including the Hospital Discharge Abstract Database, Drug Program Information Network, Medical Services Manitoba Health Insurance Registry, Early Development Instrument database, Families First Screen, Child and Family Services, and Shared Health Diagnostic Services. These data are subject to strict privacy and ethical restrictions. Further information can be requested by contacting Manitoba Centre for Health Policy Repository Access Coordinator at mchp_access@cpe.umanitoba.ca.
Funding: This work was funded through a Children’s Hospital Research Institute of Manitoba Operating Grant to LEK.
Competing interests: The authors declare no conflicts of interest.
Abbreviations: POE, Prenatal Opioid Exposure; EDI, Early Development Instrument; NOWS, Neonatal Opioid Withdrawal Syndrome; MME, Morphine Milligram Equivalents; MCHP, Manitoba Center for Health Policy
Introduction
Opioid use has increased dramatically and presents a major public health concern in North America [1]. The majority of women misusing opioids are within childbearing age [2]. In Manitoba, administrative health data identified opioid prescriptions in 7.7% of pregnancies in 2013 [3]. The outcomes of neonates following prescription prenatal opioid exposure (PPOE) are well-recognized in the literature and include increased risk for prematurity, low birth weight and neonatal opioid withdrawal syndrome (NOWS) [4]. However, a recent systematic review has identified gaps in evidence evaluating the long-term neurodevelopmental outcomes following PPOE [5]. These include inadequate control over confounding factors such as environmental, social and genetic variables that can impact the long-term neurodevelopmental outcomes of PPOE, small sample sizes, heterogeneity among included studies emerging from variations in type of opioid exposure, study populations, and assessment tools hindering meta-analysis.
Few studies have provided inconsistent insights into the potential neurodevelopmental effects of PPOE. Studies yielded conflicting results regarding Bayley Scales of Infant and Toddler Development scores [5–9]. Developmental vulnerability scores are important indicators of children’s neurodevelopment and can signal areas for intervention with the potential to improve long-term outcomes [10]. A few recent studies evaluated the educational outcomes among children with NOWS and reported that neonatal withdrawal was strongly associated with poor and deteriorating school performance, and significantly increased the likelihood of developing a subsequent educational disability [11, 12]. Studies conducted in the United States and Australia assessed educational outcomes in children with NOWS; however, because not all infants with PPOE meet the diagnostic criteria for NOWS, the expected outcomes following PPOE are not well understood.
We hypothesize that children with PPOE are at a higher risk of having developmental vulnerability than children unexposed to prescription opioids during pregnancy. To answer this question, we conducted a retrospective matched cohort study to investigate the association between PPOE and neurodevelopmental outcomes at 6 years of age. Furthermore, we evaluated the effect of PPOE on developmental outcomes among siblings where one or more of the siblings were exposed and one or more were unexposed within the same family. By conducting a sibling analysis, we aimed to mitigate the influence of unmeasured confounding factors stemming from the complex interplay of biological, social, and environmental elements affecting children exposed to opioids in utero.
Methods
Design and subjects
This is a retrospective matched cohort study using the Population Research Data Repository at the Manitoba Center for Health Policy (MCHP), University of Manitoba, Canada. Data are de-identified, population-wide and linkable across the health, social, and educational sectors, allowing for robust pharmacoepidemiological research [13–15]. This study is STROBE-compliant, and ethics, privacy and access approvals were obtained from the University of Manitoba Health Research Ethics Board (H-REB). The ethics committee approved a waiver of informed consent. Because the data were fully anonymized before analysis. Data access was obtained on March 10, 2023.
The databases used in this study were the Hospital Discharge Abstract Database; Drug Program Information Network; Medical Services; Manitoba Health Insurance Registry; Early Development Instrument (EDI); Families First Screen; Child and Family Services; and Shared Health Diagnostic Services. Linkage across the datasets was completed using a scrambled personal health identification number. The repository data have been widely and extensively used for population health research and their validity of dyad linkages has been well-documented [16–19].
We included birthing parent-child dyads with live hospital births between January 1, 2005 and December 31, 2011, in Manitoba. Dyads were excluded for the following factors: birthing parent with no health coverage 9 months before birthdate, twin births, missing gestational age, or<34 weeks, birthing parent age < 14, missing income quintile data, birthing parent who had only one opioid prescription, those with NOWS diagnosis and no opioid prescriptions, children with no recorded EDI, and dyads that could not be matched.
Exposure
The exposure group includes birthing parents who have filled at least two outpatient prescriptions for an opioid any time during pregnancy. Opioid analgesics and Opioid Agonist Therapies (OAT) for the treatment of opioid use disorder were included. Each child in the exposure group was matched to up to four controls based on birthing parent’s age, gestational age, sex, kindergarten year, and income quintiles. Gestational age matching was categorized as moderate to late preterm (35–36 weeks), term (37–41 weeks) and post-term (42 + weeks). Birthing parent age was categorized as 14–19,20–24,25–29,30–34,35–39, and 40 + years. Out of the total cases, 927 were successfully matched with 1–4 controls, 22 cases were matched with 3 controls, 16 cases with 2 controls, and 8 cases with 1 control. Cumulative opioid dose was measured using morphine milligram equivalents (MME) to allow for meaningful comparison across different opioid medications. We converted the total opioid amount to MME using the morphine equivalent ratios [3]. For cumulative MME analysis, methadone was excluded because most methadone use was from compounded products for which MME cannot be determined.
Outcomes
The Early Developmental Instrument (EDI) was used to assess developmental health of the cohort. EDI is a well-validated 103-component kindergarten teacher-completed questionnaire, that encompasses five developmental domains: physical health and well-being, language and cognitive development, emotional maturity, communication skills and general knowledge, and social competence [20]. Kindergarten teachers complete EDI questionnaires for students enrolled in the public school system during the latter half of the year. EDI was first administrated in 2005 and data are available every second school year between the years 2006–2017. EDI has been used globally as a population-based indicator of children’s developmental health and has a high psychometric property [20–22]. EDI domain scores are represented as a numerical value ranging from 0-10, alongside a percentile ranking based on the Canadian population norms. If a child’s score ≤ the 10th percentile of the Canadian population norms for any one or more domains, they are classified as being developmentally vulnerable.
For the sibling cohort, we compared children with PPOE with their unexposed siblings living in the same home, and in an attempt to match the environments we excluded children who were taken ever into care. Birthing parents’ encrypted Personal Health Identification numbers were used to specify siblings.
Covariates
In the main analysis the models adjusted for birthing parent mental disorders, birthing parent diabetes, gestational age, sex and children’s receipt of child protective services. Data on prenatal alcohol use, substance use, and smoking were obtained from the Families First Screen (FFS) database. A large proportion of the cohort had missing data for these variables (50%); accordingly, they were not included in the main analysis. We explored these variables and other potential covariates (length of hospital stay, admission to the NICU, and breastfeeding initiation) in the sensitivity analysis. This was restricted to children with data on these variables. An additional model was run, including those with missing data and coded as such. Due to the small sample size of the siblings’ cohort, the model was adjusted for variables with substantial Standardized Mean differences (SMD), including birthing parent age at birth, birthing parent mental disorders, sex and admission to the NICU. A list of the definitions of the variables is included in (Table 1 in S1 File).
Statistical analysis
SMD was used to compare baseline demographic and clinical characteristics of the cohort (SMD > 0.1 was considered substantial) [23]. We used a 2-tailed t test for continuous variables and categorical and dichotomous variables were described as proportions. Multivariable logistic regression models were used for all outcome models. For the analysis of sibling cohort data, a conditional logistic regression model was used to control for clustering of siblings within the same family. Multicollinearity was assessed using the variance inflation factor, and none met the criteria of >10.
Secondary analysis
To better understand potential predictors of adverse developmental outcomes, we evaluated the association of the timing of opioid exposure, duration of exposure and cumulative opioid dose with developmental vulnerability. Firstly, we categorized children based on time of exposure into 3 groups: exposed during the first trimester, exposed during the second and/or third trimester and exposed throughout pregnancy. We estimated the last menstrual period (LMP) as the difference between birth date and gestational age. The first trimester included exposures between the LMP and 13 weeks of gestation, the second trimester included exposures between 14 and 27 weeks of gestation and the third trimester included exposures between 28 weeks of gestation and birth. Due to the limited number of exposures during the second and third trimester (5% and 7% of the exposure group, respectively), they were combined in the logistic regression model. Secondly, we dichotomized the duration of exposure into ‘acute’ < 30 days and ‘chronic’ ≥ 30days [24]. We further evaluated the association between cumulative MME and EDI outcomes. Exposed children were dichotomized by the median of the cumulative MME (<540 and ≥540) [25]. Finally, we calculated the E-value to examine the potential influence of unmeasured confounding [26].
A p-value < .05 was considered statistically significant. All statistical analyses were conducted using SAS, version 9.4 (SAS Institute Inc.).
Results
Description of study population
Of the 103,905 eligible children born in Manitoba during the study period, 973 were included in the exposure group and 3,814 in the matched control group (Fig 1). The matching variables were balanced between the exposed and control groups (Table 1). PPOE comprised codeine (94%), oxycodone (8%), methadone (3%), morphine (2%), phenylpiperidine derivatives (1.5%), and hydromorphone (0.6%). Most exposures occurred during the first trimester (23%) or throughout pregnancy (31%). The lowest income quintile accounted for 48% of the exposure group dyads. Higher proportions of the birthing parents in the exposure group had diabetes (5% vs 3% of controls) and mental disorder diagnoses (34% vs 9% of controls). Birthing parent smoking and alcohol use during pregnancy was higher in the exposure group 38% and 17% compared with 18% and 13% in the control group, respectively. Receipt of child protection services was substantially higher in the exposure group; 57% of children with PPOE received child protection services, compared with 17% and of children in the control group. Children in the exposure group had longer hospital and NICU stays (SMD > 0.1). Breastfeeding initiation in hospital was lower in the exposure group 58% compared with 83% in the control group. Among children with PPOE, 6% had a NOWS diagnosis.
Logistic regression models
EDI outcomes revealed that 51% of children with PPOE were developmentally vulnerable in one or more domains compared to 32% of the control group (AOR 1.46; 95% CI 1.23-1.71) (Table 2). PPOE increased the risk of developmental vulnerability in all EDI domains, emotional maturity domain was the least affected (AOR,1.25;95% CI 1.01-1.55). Table 2 in S1 File. Presents the multivariable logistic regression model for developmental vulnerability in any 1 or more EDI domains. All EDI domain scores mean differences were significant for the matched cohort (p < .0001) (Table 3 in S1 File).
Secondary analysis
The association between prescription prenatal opioid exposure (PPOE) and developmental vulnerability in one or more EDI domains was found to be significantly linked with exposure to opioids during both the first trimester (AOR 1.64;95% CI 1.23-2.19) and throughout pregnancy (AOR, 1.71;95% CI 1.30-2.24) (Table 3). Exposure during the second and third trimesters was significantly associated with vulnerability in the emotional maturity domain only. Compared with the unexposed group, the risk of developmental vulnerability increased depending on the duration of exposure (Table 4). Additionally, a gradient effect was observed for low vs high MME in all outcomes except physical health and well-being and emotional maturity domains (Table 5). Crude odds ratio for the effects of timing of exposure, duration of exposure, and cumulative opioid dose are provided in Table 4, Table 5, and Table 6 in S1 File respectively.
Sensitivity analysis
The association between PPOE and developmental vulnerability was retained in the sensitivity analysis based on a complete case analysis. The model adjusted for length of hospital stay, admission to the NICU, breastfeeding initiation, alcohol use, smoking, and substance use; in addition to the variables included in the main analysis (Table 7 in S1 File). Communication skills and general knowledge (AOR 1.36;95% CI 1.05-1.78), language and cognitive development (AOR 1.42;95% CI 1.09-1.84) and social competence domains (AOR 1.65;95% CI 1.29-2.12) were the most affected domains. However, there was no significant association between PPOE and emotional maturity domain (AOR 1.17;95% CI 0.88-1.54). Breastfeeding initiation at the hospital was associated with a reduced risk of developmental vulnerability (AOR 0.71;95% CI 0.59-0.87) (Table 8 in S1 File).
Sibling cohort
Of the 973 children born with PPOE, 161 had siblings without documented exposure to prescription opioids during pregnancy (unexposed, n = 188). Siblings were born within 1–11 years. In the sibling cohort, the median (IQR) age at delivery 27 (24 –31) years for the exposed siblings vs 24 (19 –28) years for the unexposed siblings. Adjusted analyses revealed no differences between exposed and unexposed siblings; EDI outcomes revealed that 44% of children with PPOE were developmentally vulnerable in one or more domains compared to 48% of the unexposed siblings (AOR 0.92;95%CI 0.58-1.46) (Table 6). None of the EDI domain scores’ mean differences were statistically significant between the exposed and unexposed siblings (Table 9 in S1 File).
Discussion
In this matched cohort study investigating teacher-reported kindergarten developmental outcomes among children exposed prenatally to prescription opioids, PPOE was associated with an increased risk of developmental vulnerability. PPOE‘s negative impact on developmental outcomes in this study has potential biological plausibility, given the significant association between PPOE during the first trimester and developmental vulnerability compared with exposures during later trimesters. While brain development occurs throughout pregnancy, the first trimester is a critical period for organogenesis and structural formation. Exposures in early pregnancy may disrupt these fundamental processes, potentially leading to a negative impact on long-term development [27]. This emphasizes the necessity for preconception counselling to mitigate the potential negative developmental impact. A gradient effect was observed with high MME and exposures to longer durations as well. The prevalence of NOWS in the cohort was low, which could be attributed to the exposure to low-potency opioids and the fact that some of the exposures occurred during the first trimester. NOWS develops in 5–20% of children exposed to prescription opioids [28].
The mechanisms underlying the impact of PPOE on long-term neurodevelopmental outcomes remain poorly understood. In animal models and human brain cell cultures in vitro, opioids have been shown to be associated with microglia and neuronal apoptosis [29–31], neurotransmitter dysregulation [32], decreased neurogenesis [33], altered myelination [34], and disrupted architecture of brain networks [31]. Furthermore, preclinical models have revealed impaired learning and memory in offspring exposed to opioids during pregnancy [35]. Opioid receptors are abundant in the brain, and it has been hypothesized that improper activation of opioid receptors can influence fetal brain development [36].
Our findings are consistent with Kang et al [37], who found that children exposed to prescription analgesic opioids are at risk of developing attention deficit hyperactivity disorder, autism spectrum disorder, intellectual disabilities and other neuropsychiatric disorders and the risk was mainly associated with high opioid dose, longer duration of exposure and opioid exposures during early pregnancy. No association between PPOE and developmental outcomes was observed in their sibling’s cohort. In our matched cohort most opioid exposures were analgesic opioids, a small number of children were exposed to OAT (3%), this precluded a stratified analysis to examine the impact of analgesic opioids versus OAT exposures. In a Norwegian population-based cohort study, of 64, 256 fifth-grade children, prescription analgesic prenatal opioid exposure, mainly codeine (90.5%), was associated with small reductions in literacy and numeracy scores in the first trimester and with chronic exposures [38]. These results align with our findings in a comparable cohort with mainly codeine exposures. In contrast, Wen et al [25] found no association between overall birthing parent analgesic opioid use and increased risk of neurodevelopmental disorders in early childhood. However, increased risk of neurodevelopmental disorders was observed in children exposed to opioids for longer duration and at higher doses.
To address unmeasured social, genetic, and other environmental factors, we explored this association using a sibling cohort design. In the sibling cohort, we did not observe differences in neurodevelopmental outcomes between exposed and unexposed siblings. This could be explained by unmeasured confounding. The E-value that measures unmeasured confounding was 1.71. This indicates that an unmeasured confounder associated with PPOE and neurodevelopmental outcomes with an odds ratio of 1.71 could theoretically shift the lower 95% CI to include the null value; however, a weaker confounder could not. It is important to note that the sibling cohort had a small sample size which limits the interpretation of our findings. These findings support the assumption that the increased risk of negative developmental impacts in cases of PPOE may not be due to opioid exposure alone. Several social determinants of health including socioeconomic status, caregiver education, housing and food security, parental mental health, and access to prenatal and pediatric healthcare services can all independently affect developmental outcomes [6,39,40]. Growing evidence indicates that children with PPOE are more likely to be raised in adverse social conditions, which can heighten the developmental risk beyond the direct biological effect of PPOE [6]. Therefore, our findings should be interpreted in light of both impact of PPOE and the boarder social context in which these children and their siblings are raised.
In our study design, we included a matched control group and the multivariable logistic regression model adjusted for potential confounders. Detangling social determinants of health from risks related to opioid use during pregnancy, however, remains challenging. The benefits of opioid use, particularly opioid agonist therapies, in reducing birthing parent mortality, preventing relapse and spread of infectious diseases, and optimizing pregnancy and infant outcomes [41] must be considered within these discussions alongside variables that are challenging to capture using administrative health data. For instance, genetic and epigenetic factors and other factors (i.e., parenting behaviour, birthing parent stress, and emotional dysregulation) [42,43] have been associated with childhood developmental outcomes; however, we could not control for such factors using administrative data.
Children with PPOE are often exposed to a plethora of risk factors that need to be approached through a family-centred harm reduction lens to mitigate the long-term negative sequelae of PPOE and concomitant confounders. Several interventions have been shown to ameliorate adverse developmental outcomes at the population level, such as home-visiting programs [44], food supplement programs in schools and low-income families [45], comprehensive/integrated care [46] and family-centered approaches [43]. Educational challenges may not be apparent until the children attend school. The effectiveness of support and intervention measures are less effective when applied later in the child’s academic journey [47]. Incorporating the life experiences, needs, and perceptions of these parents and children while creating interventions will promote the development of programs that are effective, practical, and tailored to their needs. Our study strongly underscores the need for an increase in capacity for early developmental screening by family physicians and pediatricians, and assessment and coordinated intervention by certified child & adolescent clinical health psychologists and developmental pediatricians for children with PPOE in Manitoba [48]. Additionally, it emphasises the need of an updated comprehensive Clinical Practice Guidelines for managing children with PPOE to enhance the overall health and well-being of families and children affected by opioid use during pregnancy [46].
Strengths
This is the first Canadian study evaluating the long-term neurodevelopmental impact of PPOE using EDI data. We used a matched control study design and we adjusted for several confounders that have been associated with negative developmental outcomes in this population. The utilization of thoroughly validated and well-recognized international measures of educational performance enhances the generalizability of the results. The use of MCHP data enables long-term follow-up and minimizes attrition and detection bias while also enabling inclusion of various confounders.
Limitations
The use of administrative data does not allow the capture of illicit or diverted opioid use or an in-depth assessment of the concomitant social determinants of health. We cannot guarantee that birthing parents who filled an opioid prescription took the medication, which may lead to exposure misclassification and an over-estimation of prenatal opioid exposure. Despite using a matched cohort and adjusting for covariates, we are unable to consider all unmeasured or residual confounding due to the unavailability of environmental and genetic factors in the data repository as well as high missingness in variables related to alcohol use, smoking and substance use during pregnancy. This limitation precluded adjusting for these variables in all models. The sibling cohort had a small sample size, and we only had data on prescription opioids. Unexposed siblings may have been exposed to non-prescription opioids. The EDI is administered throughout Manitoba’s public education system; students enrolled in private schools and some schools in Indigenous communities were not included. Furthermore, assessment of educational outcomes by teachers could potentially introduce bias. However, teachers were unaware of the exposure status. Therefore, any errors stemming from this bias would be random and non-differential. Finally, these findings may not be relevant to newer OAT medications as they were not captured in this dataset. Most exposures involved prescription codeine, these findings may not generalize to illicit opioids or opioid agonist therapy used for opioid use disorder.
Conclusion
In this matched cohort study, PPOE was associated with an increased risk of developmental vulnerability. The impact of PPOE has been previously shown to not only related to the direct impact on the exposure of the brain to opioids, but also a combination of other biological, social, and environmental factors. Considering the simultaneous presence of these risk factors, it is of utmost importance to provide children with PPOE and their families early and long-term developmental screening and family-centered support to help ameliorate later educational challenges.
Supporting information
S1 File. Supplementary Content.
Table 1. Demographic and Clinical Variables’ Definition. Table 2. Multivariable Logistic Regression Model Results for vulnerability in EDI in 1 or more domains: Exposed Versus Matched Control. Table 3. EDI Domain Scores for the Exposed and Matched Control Group. Table 4. EDI Vulnerability results: Effect of Timing of Opioid Exposure. Table 5. EDI Vulnerability results: Acute vs chronic exposure. Table 6. EDI Vulnerability results: Cumulative MME high vs low categories. Table 7. EDI Vulnerability results: Exposed Versus Matched Control (sensitivity analysis).Table 8. Multivariable Logistic Regression Model Results for vulnerability in EDI in 1 or more domains: Exposed Versus Matched Control – sensitivity analysis (complete case).Table 9. EDI Domain Scores for the Sibling Cohort.
https://doi.org/10.1371/journal.pone.0355101.s001
(DOCX)
S1 Table. STROBE statement—checklist of items that should be included in reports of cohort studies.
https://doi.org/10.1371/journal.pone.0355101.s002
(DOCX)
Acknowledgments
We acknowledge the MCHP for the use of data contained in the Population Research Data Repository under project # 2018/2019–49 registered with the Provincial Health Research Privacy Committee. The results and conclusions are those of the authors, and no official endorsement by the MCHP, Manitoba Health, or other data providers is intended or should be inferred.
References
- 1. Jayasinha R, Nairn S, Conrod P. A Dangerous “Cocktail”: The COVID-19 Pandemic and the Youth Opioid Crisis in North America: A Response to Vigo et al. Can J Psychiatry. 2020:070674372094382.
- 2. Krans EE, Patrick SW. Opioid use disorder in pregnancy: Health policy and practice in the midst of an epidemic. Obstet Gynecol. 2016;128(1):4–10. pmid:27275812
- 3. Falk J, Dahl M, Raymond CB, Chateau D, Katz A, Leong C, et al. Opioid use during pregnancy: A population-based cohort study. CMAJ Open. 2017;5(2):E517–23. pmid:28655728
- 4. Gandhi KD, Schak KM, Vande JL, et al. The negative impact of maternal perinatal opioid use on neonatal outcomes. Prim Care Companion CNS Disord. 2021;23(3):20m02737.
- 5. Balalian AA, Graeve R, Richter M, Fink A, Kielstein H, Martins SS, et al. Prenatal exposure to opioids and neurodevelopment in infancy and childhood: A systematic review. Front Pediatr. 2023;11:1071889. pmid:36896405
- 6. Yeoh SL, Eastwood J, Wright IM, Morton R, Melhuish E, Ward M, et al. Cognitive and motor outcomes of children with prenatal opioid exposure: A systematic review and meta-analysis. JAMA Netw Open. 2019;2(7):e197025. pmid:31298718
- 7. Doberczak TM, Shanzer S, Cutler R, Senie RT, Loucopoulos JA, Kandall SR. One-year follow-up of infants with abstinence-associated seizures. Arch Neurol. 1988;45(6):649–53. pmid:3369972
- 8. Beckwith AM, Burke SA. Identification of early developmental deficits in infants with prenatal heroin, methadone, and other opioid exposure. Clin Pediatr (Phila). 2015;54(4):328–35. pmid:25189695
- 9. Robey A, Buckingham-Howes S, Salmeron BJ, Black MM, Riggins T. Relations among prospective memory, cognitive abilities, and brain structure in adolescents who vary in prenatal drug exposure. J Exp Child Psychol. 2014;127:144–62. pmid:24630759
- 10. Oberklaid F, Baird G, Blair M, Melhuish E, Hall D. Children’s health and development: Approaches to early identification and intervention. Arch Dis Child. 2013;98(12):1008–11. pmid:23968776
- 11. Fill M-MA, Miller AM, Wilkinson RH, Warren MD, Dunn JR, Schaffner W, et al. Educational Disabilities among children born with neonatal abstinence syndrome. Pediatrics. 2018;142(3):e20180562. pmid:30166364
- 12. Oei JL, Melhuish E, Uebel H, Azzam N, Breen C, Burns L, et al. Neonatal abstinence syndrome and high school performance. Pediatrics. 2017;139(2):e20162651. pmid:28093465
- 13. Jutte DP, Roos LL, Brownell MD. Administrative record linkage as a tool for public health research. Annu Rev Public Health. 2011;32:91–108. pmid:21219160
- 14. Roos LL, Gupta S, Soodeen R-A, Jebamani L. Data quality in an information-rich environment: Canada as an example. Can J Aging. 2005;24 Suppl 1:153–70. pmid:16080132
- 15. Robinson JR, Young TK, Roos LL, Gelskey DE. Estimating the burden of disease. Comparing administrative data and self-reports. Med Care. 1997;35(9):932–47. pmid:9298082
- 16. Smith M, Lix LM, Azimaee M, Enns JE, Orr J, Hong S, et al. Assessing the quality of administrative data for research: A framework from the Manitoba Centre for Health Policy. J Am Med Inform Assoc. 2018;25(3):224–9. pmid:29025002
- 17. Roos LL, Nicol JP. A research registry: Uses, development, and accuracy. J Clin Epidemiol. 1999;52(1):39–47. pmid:9973072
- 18. Brownell MD, Roos NP, Roos LL. Monitoring health reform: A report card approach. Soc Sci Med. 2001;52(5):657–70. pmid:11218171
- 19. Kozyrskyj AL, Mustard CA. Validation of an electronic, population-based prescription database. Ann Pharmacother. 1998;32(11):1152–7. pmid:9825079
- 20. Janus M, Brinkman SA, Duku EK. Validity and psychometric properties of the early development instrument in Canada, Australia, United States, and Jamaica. Soc Indic Res. 2011;103(2):283–97.
- 21. Janus M, Offord DR. Development and psychometric properties of the Early Development Instrument (EDI): A measure of children’s school readiness. Can J Behav Sci Rev Can Sci Comport. 2007;39:1–22.
- 22. Ip P, Li SL, Rao N, Ng SSN, Lau WWS, Chow CB. Validation study of the Chinese Early Development Instrument (CEDI). BMC Pediatr. 2013;13:146. pmid:24053538
- 23. Austin PC. Using the standardized difference to compare the prevalence of a binary variable between two groups in observational research. Communications in Statistics - Simulation and Computation. 2009;38(6):1228–34.
- 24. Desai RJ, Huybrechts KF, Hernandez-Diaz S, Mogun H, Patorno E, Kaltenbach K, et al. Exposure to prescription opioid analgesics in utero and risk of neonatal abstinence syndrome: Population based cohort study. BMJ. 2015;350:h2102. pmid:25975601
- 25. Wen X, Lawal OD, Belviso N, Matson KL, Wang S, Quilliam BJ, et al. Association between prenatal opioid exposure and neurodevelopmental outcomes in early childhood: A retrospective cohort study. Drug Saf. 2021;44(8):863–75. pmid:34100263
- 26. VanderWeele TJ, Ding P. Sensitivity analysis in observational research: Introducing the E-value. Ann Intern Med. 2017;167(4):268–74. pmid:28693043
- 27. Antoun S, Ellul P, Peyre H, Rosenzwajg M, Gressens P, Klatzmann D, et al. Fever during pregnancy as a risk factor for neurodevelopmental disorders: Results from a systematic review and meta-analysis. Mol Autism. 2021;12(1):60. pmid:34537069
- 28. Kocherlakota P. Neonatal abstinence syndrome. Pediatrics. 2014;134(2):e547-61. pmid:25070299
- 29. Slotkin TA, Whitmore WL, Salvaggio M, Seidler FJ. Perinatal methadone addiction affects brain synaptic development of biogenic amine systems in the rat. Life Sci. 1979;24(13):1223–9. pmid:571949
- 30. Hu S, Sheng WS, Lokensgard JR, Peterson PK. Morphine induces apoptosis of human microglia and neurons. Neuropharmacology. 2002;42(6):829–36. pmid:12015209
- 31. Merhar SL, Jiang W, Parikh NA, Yin W, Zhou Z, Tkach JA, et al. Effects of prenatal opioid exposure on functional networks in infancy. Dev Cogn Neurosci. 2021;51:100996. pmid:34388637
- 32. Wu VW, Mo Q, Yabe T, Schwartz JP, Robinson SE. Perinatal opioids reduce striatal nerve growth factor content in rat striatum. Eur J Pharmacol. 2001;414(2–3):211–4. pmid:11239921
- 33. Erbs E, Faget L, Ceredig RA, Matifas A, Vonesch J-L, Kieffer BL, et al. Impact of chronic morphine on delta opioid receptor-expressing neurons in the mouse hippocampus. Neuroscience. 2016;313:46–56. pmid:26480813
- 34. Sanchez ES, Bigbee JW, Fobbs W, Robinson SE, Sato-Bigbee C. Opioid addiction and pregnancy: Perinatal exposure to buprenorphine affects myelination in the developing brain. Glia. 2008;56(9):1017–27. pmid:18381654
- 35. Vestal-Laborde AA, Eschenroeder AC, Bigbee JW, Robinson SE, Sato-Bigbee C. The opioid system and brain development: Effects of methadone on the oligodendrocyte lineage and the early stages of myelination. Dev Neurosci. 2014;36(5):409–21. pmid:25138998
- 36. Vathy I. Prenatal opiate exposure: Long-term CNS consequences in the stress system of the offspring. Psychoneuroendocrinology. 2002;27(1–2):273–83. pmid:11750783
- 37. Prenatal opioid exposure and subsequent risk of neuropsychiatric disorders in children: Nationwide birth cohort study in South Korea | The BMJ. Accessed July 4, 2024. https://www.bmj.com/content/385/bmj-2023-077664
- 38. Trønnes JN, Lupattelli A, Ystrom E, Nordeng H. Analysis of prenatal exposure to opioid analgesics and scholastic skills in children in fifth grade in Norway. JAMA Netw Open. 2022;5(7):e2222425. pmid:35852803
- 39. Patrick SW, Faherty LJ, Dick AW, Scott TA, Dudley J, Stein BD. Association among county-level economic factors, clinician supply, metropolitan or rural location, and neonatal abstinence syndrome. JAMA. 2019;321(4):385.
- 40. Parolin M, Simonelli A, Mapelli D, Sacco M, Cristofalo P. Parental substance abuse as an early traumatic event. preliminary findings on neuropsychological and personality functioning in young drug addicts exposed to drugs early. Front Psychol. 2016;7:887. pmid:27378983
- 41. Tran EL, Kim SY, England LJ, Green C, Dang EP, Broussard CS, et al. The MATernaL and Infant NetworK to Understand Outcomes Associated with Treatment of Opioid Use Disorder During Pregnancy (MAT-LINK): Surveillance Opportunity. J Womens Health (Larchmt). 2020;29(12):1491–9. pmid:33227221
- 42. Thadani PV. The intersection of stress, drug abuse and development. Psychoneuroendocrinology. 2002;27(1–2):221–30. pmid:11750780
- 43. Larson JJ, Graham DL, Singer LT, Beckwith AM, Terplan M, Davis JM, et al. Cognitive and behavioral impact on children exposed to opioids during pregnancy. Pediatrics. 2019;144(2):e20190514. pmid:31320466
- 44. Peacock S, Konrad S, Watson E, Nickel D, Muhajarine N. Effectiveness of home visiting programs on child outcomes: A systematic review. BMC Public Health. 2013;13:17. pmid:23302300
- 45. Meyers AF, Sampson AE, Weitzman M, Rogers BL, Kayne H. School Breakfast Program and school performance. Am J Dis Child. 1989;143(10):1234–9. pmid:2801668
- 46. Society CP. Managing infants born to mothers who have used opioids during pregnancy | Canadian Paediatric Society. Accessed July 3, 2024. https://cps.ca/documents/position/opioids-during-pregnancy
- 47. Campbell FA, Pungello EP, Burchinal M, Kainz K, Pan Y, Wasik BH, et al. Adult outcomes as a function of an early childhood educational program: An Abecedarian Project follow-up. Dev Psychol. 2012;48(4):1033–43. pmid:22250997
- 48.
Posted KM. ‘Desperate’ shortage of psychologists causing critical delays in youth care. Winnipeg Free Press. 2023. Accessed March 19, 2024. https://www.winnipegfreepress.com/breakingnews/2023/05/03/desperate-shortage-of-psychologists-causing-critical-delays-in-youth-care