
==== Front
Pediatr Rep
Pediatr Rep
pediatrrep
Pediatric Reports
2036-749X
2036-7503
MDPI

10.3390/pediatric16030062
pediatrrep-16-00062
Review
Prenatal Tobacco Exposure and Behavioral Disorders in Children and Adolescents: Systematic Review and Meta-Analysis
https://orcid.org/0000-0002-4798-7696
Godleski Stephanie 1*
Shisler Shannon 2
Colton Kassidy 3
Leising Meghan 2
Aricò Maurizio Academic Editor
1 Department of Psychology, College of Liberal Arts, Rochester Institute of Technology, Rochester, NY 14623, USA
2 Clinical and Research Institute on Addictions, State University of New York at Buffalo, Buffalo, NY 14203, USA; smcasey@buffalo.edu (S.S.); mlcasey@buffalo.edu (M.L.)
3 Department of Psychology, School of Arts and Sciences, University of Rochester, Rochester, NY 14627, USA; kcolton@ur.rochester.edu
* Correspondence: saggsh@rit.edu; Tel.: +1-585-475-2643
31 8 2024
9 2024
16 3 736752
01 7 2024
03 8 2024
27 8 2024
© 2024 by the authors.
2024
https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Prenatal tobacco exposure has been implicated in increased risk of the development of behavioral disorders in children and adolescents. The purpose of the current study was to systematically examine the association between prenatal tobacco exposure and diagnoses of Attention Deficit/Hyperactivity Disorder, Oppositional Defiant Disorder, and Conduct Disorder in childhood and adolescence. We searched Medline, Psychinfo, ERIC, Proquest, Academic Search Complete, PsychArticles, Psychology and Behavioral Sciences Collection, Web of Science, CINAHL Plus, and Google Scholar databases through October 2022. The authors screened studies and extracted data independently in duplicate. Ten clinical studies examining diagnoses of Attention Deficit/Hyperactivity Disorder, Oppositional Defiant Disorder, and Conduct Disorder between the ages of 4 and 18 years old were included. There was insufficient evidence to synthesize outcomes related to Conduct Disorder and Oppositional Defiant Disorder. The meta-analysis found a significant effect of prenatal tobacco exposure in increasing the likelihood of an Attention Deficit/Hyperactivity Disorder diagnosis in childhood and adolescence. Implications for future research are discussed.

prenatal tobacco exposure
attention deficit/hyperactivity disorder
oppositional defiant disorder
conduct disorder
This research received no external funding.
==== Body
pmc1. Introduction

Maternal smoking during pregnancy continues to be a public health concern, as tobacco is commonly used during pregnancy with rates of tobacco use during pregnancy remaining stable [1,2]. Indeed, 5.5% of infants born in 2020 were prenatally exposed to tobacco [3]. Therefore, understanding the risk that prenatal tobacco exposure poses for later developmental sequelae is critical. Prenatal tobacco exposure (PTE) is associated with a higher risk of a variety of negative physical, cognitive, and socio-behavioral health outcomes for children both early and later in development, including restricted fetal growth, poor self-regulation, learning and memory deficits, obesity, and aggressive behavior [4,5,6,7,8,9,10]. Indeed, prenatal tobacco exposure has been suggested to impact brain function, physiological dysregulation, and early neurobehavioral outcomes [11,12].

In particular, prenatal tobacco exposure is implicated in increased impulsivity, dis-inhibition, dysregulation, activity, and inattention [6,7,13,14] and, thus, a higher risk of the development of attentional, externalizing, and disruptive behavior disorders [15,16]. Specifically, prenatal tobacco exposure has been linked to behavioral disorders (BDs), including Attention Deficit/Hyperactivity Disorder (ADHD), Oppositional Defiant Disorder (ODD), and Conduct Disorder (CD) [17,18,19,20,21,22]. This suite of disorders is characterized by hyperactivity, inattention, impulsivity, and defiant behavior including noncompliance with limit-setting by adults or peers and hostile or aggressive physical behavior towards others.

Importantly, BDs can result in many challenges for affected children. They may have difficulty forming positive relationships with peers and adults and may be more likely to have problems with bullying and victimization in school [23,24]. Other adverse outcomes include poor academic achievement, higher odds of substance use disorders, unemployment, and criminal behavior [25]. In addition, BDs are often comorbid with other mental health disorders (e.g., anxiety) [26,27]. Diagnoses such as ADHD, ODD, and CD can also often bear considerable financial and emotional burdens for individuals, families and caregivers, agencies, and society as a whole. BD diagnoses are also associated with increased caregiver strain and diminished parental mental health [28,29,30,31]. Additionally, childhood BDs are estimated to produce expenses upwards of $52.4 billion a year, including costs associated with hospitalizations, outpatient visits, prescriptions, detention centers, medically related work absences for parents, and education [28,32,33,34,35]. Finally, CD and ADHD carry a significant global health burden, with estimates of 5.75 million years lived with disability (YLDs) for CD, and 491,500 YLDs for ADHD, accounting for 0.8% of YLDs globally [36]. YLDs reflect the extent to which a disability impacts quality of life with one YLD equivalent to one year of healthy life lost due to disability. Thus, it is important to understand the potential for increased risk of these disorders due to prenatal tobacco exposure.

The magnitude of the association between prenatal tobacco exposure and diagnosed BDs is unclear, as much research examines the symptoms or facets of disruptive behavior or externalizing behavior in general (e.g., hyperactivity, inattention, impulsivity) instead of clinical diagnoses, and the results are mixed [37,38,39,40,41,42]. Understanding the impact of prenatal tobacco exposure on symptomatology that meets the threshold for diagnoses is an important extension of past work and is likely to be especially informative for understanding clinically significant levels of BD rather than prenatal tobacco exposure’s impact on BD symptoms alone [43]. In order to receive a clinical diagnosis, individuals must present with both a number of symptoms and functional impairment [44]. Thus, a clinical diagnosis is naturally concomitant with functional impairment, whereas counts of BD symptoms may or may not reflect clinically significant levels of behavioral concerns or be associated with significant impaired functioning [45]. Indeed, to some extent, externalizing symptoms are not uncommon, particularly in younger children, such that these behaviors may be developmentally typical in early childhood. What is most worrying is when the persistence or severity of the symptoms impedes the ability of the child to function well in their environment. Therefore, in addition to past work that has examined the impact of prenatal tobacco exposure on BD symptomatology on a continuum, it is also important to understand the impact of exposure in predicting more severe, impairing levels of BD that meet a clinical threshold, given the significant wide-reaching impact of diagnosed BDs [36]. In examining prenatal tobacco exposure specifically regarding the likelihood of BD diagnoses, we may better understand how smoking during pregnancy impacts overall daily functioning in addition to symptomatology [46]. Therefore, the present systematic review and meta-analysis fills a critical gap in the literature regarding the relationship between prenatal tobacco exposure and disruptive, externalizing behavior that meets the threshold for BD diagnoses.

Most previous reviews have synthesized adjusted associations between prenatal to-bacco exposure and BD diagnoses or externalizing behavior problems; however, there is a lack of consistency across studies in what confounding variables are adjusted for analytically, which has been argued to make it difficult to interpret the summary estimates of prenatal exposure on outcomes such as ADHD [43,47,48]. Indeed, much of the previous research has adjusted for a variety of sociodemographic variables (e.g., socio-economic status, maternal age, maternal education) when examining the link between prenatal tobacco exposure and BDs; however, many studies also take into account other potential influences or confounding variables such as prenatal exposure to other substances or maternal mental health [47,48,49,50]. The constellation of influences that are adjusted for varies significantly from study to study (e.g., different sociodemographic risk factors, parental mental health concerns, pregnancy and birth outcomes) [50]. This lack of consistency in included potential covariates produces adjusted associations that are not comparable, impacting the ability to combine them via meta-analysis [51]. Thus, the current synthesis focused on investigating unadjusted associations between exposure and subsequent diagnoses, and expands on previous work by examining the unadjusted relationship between tobacco exposure and focusing on clinical diagnoses, which may reflect a greater degree of severity and impairment. Therefore, the purpose of the current study was to systematically examine the association between prenatal tobacco exposure and the BD diagnoses of ADHD, ODD, and CD between the ages of 4 and 18 years old. The age ranges were chosen to reflect pre-school or school-aged children and adolescents. Further, the validity of diagnoses of ADHD, ODD, and CD have been supported at preschool age and diagnoses of such disorders as early as the preschool period have shown stability into the school age years, whereas diagnoses prior to the preschool period may be less valid and stable [52,53].

2. Materials and Methods

2.1. Selection of Studies

Studies included in this synthesis were obtained from several sources. First, we completed electronic searches of Medline, Psychinfo, ERIC, Proquest, Academic Search Complete, PsychArticles, Psychology and Behavioral Sciences Collection, Web of Science, CINAHL Plus, and Google Scholar in October 2022. We imposed no date restrictions on our search. We searched for both published and unpublished manuscripts, such as dissertations and theses, in order to reduce the possibility of publication bias [54]. The first part of the search term indicated the developmental period and substance, thus included all iterations of the following: pregnancy or prenatal or maternal with smoking or nicotine or tobacco or cigarette. This was paired with a key word indicating our outcome of interest, for which we used attention, inattention, impulsivity, attention deficit hyperactivity disorder, attention deficit disorder, ADHD, externalizing behavior, conduct, conduct disorder, conduct problems, oppositional, oppositional defiant disorder, disruptive behavior disorder, disruptive behav*, or hyperactivity.

2.2. Data Analysis Plan

We fit a random-effects model to the data and estimated the amount of heterogeneity (i.e.,τ2), using the DerSimonian–Laird estimator [55]. In addition, we report the Q-test for heterogeneity and the I2 statistic [56,57]. We use studentized residuals and Cook’s distances to examine whether studies may be outliers and/or influential in the context of the model [58]. We consider studies potential outliers if they have a studentized residual larger than the 100 × (1 − 0.05/(2 × k))th percentile of a standard normal distribution (i.e., using a Bonferroni correction with two-sided α = 0.05 for k studies included in the meta-analysis). The analysis was carried out using R (version 4.0.0) and the metafor package (version 2.5.82) [59,60].

2.3. Publication Bias

Given that statistically significant results are more likely to be published than non-significant results, any meta-analysis should take the potential for publication bias into account [61]. We searched for both published and unpublished manuscripts (i.e., unpublished dissertations and theses) as one strategy to decrease the likelihood of finding publication bias. The rank correlation test and the regression test, using the standard error of the observed outcomes as a predictor, are used to check for funnel plot asymmetry, but it is necessary to have at least 10 studies in an analysis for tests of publication bias to be valid, so we were only able to assess publication bias for effects of prenatal exposure on ADHD diagnosis in the current review [62,63].

2.4. Quality Assessment

We assessed the risk of bias in the included studies by drawing on the signaling questions in the checklist for cohort studies appraisal tool from the Joanna Briggs Institute (JBI) [64]. The items in this checklist cover the methodological quality of the research to help determine if it was adequately protected from potential sources of bias. Two reviewers undertook the risk of bias assessment independently, and any disagreements were resolved by consensus, or by a third reviewer if necessary. We assessed the risk of bias at the paper level, coding each paper on the 11 criteria covered by the tool. Response options were “Yes”, “No”, “Unclear”, and “Not applicable”, with yes answers indicating the lowest risk of potential bias. We report the results of the assessment for each of the assessed criteria for each included study.

3. Results

3.1. Search Results, Quality Assessment, and Coding Features

3.1.1. Search Outcomes

Searches yielded 14,085 references for consideration. After removing duplicate references, a total of 3387 manuscripts remained from the initial literature search. The initial screening involved reviewing the titles and abstracts of all 3387 studies, and eliminated articles that were not quantitative, were conducted solely with animals, or did not include a measure of prenatal tobacco exposure and a diagnosed BD. This initial screening allowed for the direct exclusion of 2844 manuscripts, and the texts of the remaining 543 manuscripts were read in full (see Figure 1). Additional studies were collected by conducting a snowball search of the reference lists of included studies and relevant meta-analyses, which generated an additional 6 articles for consideration which were also read in full.

3.1.2. Study Inclusion Criteria

The studies that were selected for inclusion quantified the relationship between prenatal tobacco exposure and diagnosed BDs in children aged 4 to 18 years old. We excluded studies from the meta-analysis if they (a) were not written in English (e.g., [65,66]); (b) were not a quantitative study of the relationship between prenatal tobacco exposure and BDs (e.g., [67,68]); (c) did not include a clear measure of a clinically diagnosed BD (e.g., [37,69]); (d) did not include a non-exposed comparison/control group that did not smoke during pregnancy (e.g., [70,71,72,73]); (e) had samples that were either less than 4 years of age, or greater than 18 years of age or included children that were below 4 or above 18 (e.g., [74,75,76]) or did not report child age at the time of diagnosis [77]; (f) did not report an unadjusted odds ratio, or information that could be meaningfully converted to an unadjusted odds ratio, such as a 2 × 2 frequency table that included the number of exposed vs. non-exposed participants and number diagnosed and not diagnosed within those categories (e.g., [78,79,80,81,82]); (g) had a sample that was not clearly independent (e.g., twin sample, large national samples covering several years of births where siblings were not clearly excluded [83,84,85]).

3.1.3. Studies Sharing Common Data

One of the included studies reported on more than one BD [86]. Since we were underpowered for a robust variance analysis and only one study reported exclusively on ODD and CD diagnoses, we chose to run a separate analysis for ADHD, in order to create independence among the effects. Nigg and Breslau (2007) was the only study that reported across multiple waves and included diagnoses at several age ranges within the same longitudinal sample; we chose the timing of the wave (i.e., child age) based on examining a similar developmental period as the other included studies—to the closest approximation [86]. Therefore, for Nigg and Breslau (2007), we chose to include the effect sizes from the 6-year-old wave for analyses to be consistent with the majority of the other studies included [86]. Sagiv et al. (2013) was the only study to include maternal smoking categorized as a heavier use (i.e., >10 cigarettes/day), a lighter use (1–10 cigarettes/day), and a non-smoking group, and we chose to include the heavier use group in comparison to the non-smoking group [87]. Huang et al. (2019) reported on two independent samples with two independent effect sizes; therefore, both were included for the purposes of the current review [88]. In the end, we included a total of 10 studies with 11 independent samples in this review, contributing a total of 13 effect sizes (11 for ADHD, 1 for ODD, and 1 for CD).

The typical study in this review reported on the relationship between prenatal tobacco exposure and BDs in children using some form of data that allowed for calculation of an odds ratio. Most studies reported on a combination of ages or grade levels, most typically spanning from middle childhood through adolescence. In the typical study, prenatal tobacco exposure was maternally self-reported, and a standardized diagnostic interview was used to measure clinical diagnoses of BDs.

3.1.4. Risk of Bias Assessment

The risk of bias assessment for each domain for each included study is presented in Table 1. The most common source of potential bias was in the measurement of exposure. Most studies used retrospective self-reports of pregnancy smoking, which may be susceptible to both recall and social desirability bias. No studies used prospective biological assays of tobacco exposure, nor did any use well-validated methods for capturing daily substance use patterns (e.g., substance use assessment interview, biological assay during pregnancy). In addition, most authors did not explore the extent of potential selection bias. Only one study presented a balance table of differences between exposure groups on baseline measures of demographics. Finally, there was a general lack of clarity around attrition and missing data. Often, large portions of the target sample were missing from analyses with no explanation and no analysis of whether missing data were differential between exposure groups.

3.1.5. Coding Study Features

To ensure sufficient reliability of the data, two coders independently reviewed and coded all studies included in our synthesis. Inter-rater reliability was computed separately for each variable as the percentage of agreement between coders. These reliabilities ranged from 75% for socio-economic status to 100% for publication year. Low reliabilities for socio-economic status were the result of coders’ differing interpretations of the information presented on socio-economic status (i.e., whether the information was clear or if inferences could be drawn from the information provided), and these were resolved quickly. All coding disagreements were resolved through discussion and consensus prior to any data analyses.

We coded several variables to be considered as possible moderators of the relationship between prenatal tobacco exposure and BD diagnoses (e.g., sample recruitment, location, sample size; sample demographics, behavior measure used/reporter, method of assessing prenatal tobacco exposure). However, there was variability in the nature of the reporting practices in the primary studies, reducing our ability to consider all of the potential moderators in our analyses and, as detailed subsequently, there was no significant amount of heterogeneity in the true outcomes suggesting that moderator analyses were not appropriate. Therefore, potential sources of variation in study findings were not examined.

3.1.6. Prenatal Tobacco Exposure

Prenatal tobacco exposure was typically reported as a binary occurrence. For example, most studies reported whether or not mothers smoked during their pregnancy. Mothers self-reported their prenatal tobacco use in most of the studies.

3.1.7. Behavior Disorders

The assessment of BD used was coded for all studies (see Table 2). Five of the studies included assessed BD via clinical/hospital diagnoses based on criteria from the Diagnostic and Statistical Manual of Mental Disorders (Third Edition, Revised, DSM-III-R; [95]; Fourth Edition, DSM-IV-TR, [96]; e.g., [88,90]). An additional four studies in this analysis reported using some form of structured diagnostic interview, such as the Diagnostic Interview Schedule ([97,98]; e.g., [89]) or the Schedule for Affective Disorders and Schizophrenia for School-Age Children (K-SADS; [99,100]; e.g., [94]). The final study assessed for BD diagnoses using the Multimodal Treatment Study for Attention-Deficit/Hyperactivity Disorder version of the Swanson, Nolan, and Pelham, Version IV Questionnaire (MTA-SNAP-IV; [101]; e.g., [89]).

3.1.8. Effect Sizes

Effect sizes were recorded as unadjusted odds ratios. When odds ratios were not presented in the manuscript, the information from the 2 × 2 frequency table was inputted into the Campbell Effect Size Calculator [102]. Odds ratios were converted to log odds and the variance of the log odds were computed for use in the analysis (this is required to maintain symmetry in the analysis). The summary effect sizes were then converted back into odds ratios for interpretation.

3.2. Effects of Prenatal Tobacco Exposure on BD Diagnoses

3.2.1. Effects of Prenatal Tobacco Exposure on ADHD Diagnosis

We included a total of k = 11 independent effects in the analysis, including 1402 exposed children and 6383 non-exposed children (for a total of 7785). The observed outcomes expressed as log odds ranged from −0.18 to 0.69. The estimated average outcome based on the random-effects model was μ^ = 0.26 (95% CI: 0.12 to 0.41). Therefore, the average outcome differed significantly from zero (z = 3.49, p < 0.001), indicating that children prenatally exposed to tobacco were significantly more likely to be diagnosed with ADHD. A forest plot showing the observed outcomes and the estimate based on the random-effects model (converted from log odds to odds ratio) is shown in Figure 2. According to the Q-test, there was no significant amount of heterogeneity in the true outcomes (Q(10) = 4.75, p = 0.91, τ^2= 0.00, I2 = 0.00%); thus, moderator analyses were not appropriate. One study—Sagiv et al. (2013)—had a relatively large weight compared to the rest of the studies and could be considered overly influential [87]. However, if Sagiv et al. (2013) is removed from the analysis, the result is only slightly lower (OR = 1.24) and remains statistically significant (p = 0.01) [87]. An examination of the studentized residuals revealed that none of the studies had a value larger than ±2.84 and hence there was no indication of outliers in the context of this model. A funnel plot of the estimates is shown in Figure 3. Neither the rank correlation nor the regression test indicated any funnel plot asymmetry (p = 1.000 and p = 0.899), indicating that no publication bias is detected.

3.2.2. Effects of Prenatal Tobacco Exposure on ODD Diagnosis

One study (Nigg and Breslau, 2007) examined the relationship between prenatal tobacco exposure and ODD diagnosis [86]. Their study, conducted in the US, utilized a sample of 798 17-year-old children. They found that prenatally exposed children were 2.19 times more likely to be diagnosed with ODD than non-exposed children [95% CI: 1.40 to 3.45].

3.2.3. Effects of Prenatal Tobacco Exposure on CD Diagnosis

Nigg and Breslau (2007) were also the only authors to report on the relationship between prenatal tobacco exposure and diagnosis of conduct disorder [86]. They found that children prenatally exposed to tobacco were 2.19 times more likely to have been diagnosed with conduct disorder than unexposed children (OR 2.19, [95% CI: 1.21 to 3.97]).

4. Discussion

The current meta-analyses aimed to examine the association between prenatal tobacco exposure and diagnoses of ADHD, ODD, and CD in childhood and adolescence. Based on the 10 studies reviewed examining child and adolescent ADHD diagnoses, children prenatally exposed to tobacco were significantly more likely to be diagnosed with ADHD. These results are consistent with previous reviews demonstrating associations between prenatal tobacco exposure with disruptive behavior and externalizing symptoms [21,50,103,104,105] and adds by synthesizing the literature on tobacco exposure and specifically clinical diagnoses as an outcome. Only one study reviewed exclusively reports on ODD and CD diagnoses as an outcome (i.e., [86]). While Nigg and Breslau (2007) did find that children prenatally exposed to tobacco were significantly more likely to be diagnosed with both ODD and CD, in the absence of more evidence we cannot make strong conclusions regarding either relationship [86]. However, past work has suggested a particularly strong relationship between maternal smoking during pregnancy and CD symptomatology (e.g., [106]). The BDs are often comorbid, including approximately 50% of those diagnosed with ADHD within the study by Arnold et al. (2005) who were also diagnosed with ODD or CD [89]. Future research examining the direct association between prenatal tobacco exposure and diagnosed ODD and conduct problems, as well as those with comorbid diagnoses of more than one BD, would allow for further synthesis work. Despite differences in the ways the included studies approached examination of the relationship between prenatal tobacco exposure and BDs, there was no significant heterogeneity in the analyses for ADHD. Given the homogeneity, we did not examine potential sources of variation. The forest plot in Figure 1 illustrates the consistency of the effect sizes across the body of evidence for ADHD.

These findings help to clarify previous research focusing on symptoms or facets of behavioral disorders and demonstrate the impact of prenatal tobacco exposure for increasing the likelihood of diagnoses of ADHD, in particular. The current synthesis demonstrates the direct association between prenatal tobacco exposure and later clinically significant diagnoses of BD. Future research would benefit from examining the mechanisms driving the association between prenatal tobacco exposure and later diagnoses of attentional or behavioral problems. Prenatal tobacco exposure can have teratogenic effects on attention and regulation systems (e.g., atypical nervous system development; [5,15,107,108,109]), which is evident in more highly aroused and reactive neonatal behaviors [110,111] and is associated with the later development of behavioral problems (e.g., [112]). Therefore, one mechanism through which prenatal tobacco exposure may be associated with attentional and disruptive behavior disorders is through the teratological impact of the tobacco exposure itself (e.g., [106]). In addition, shared genetic risk between parents and offspring may be an important factor for BDs [21,113]; however, genetically informed studies have also suggested the important influence of family or the social environment in the association between prenatal tobacco exposure and behavior problems [114]. For example, maternal smoking during pregnancy is also associated with higher rates of maternal psychopathology (e.g., [115,116]) as well as with less effective parenting practices (e.g., harsh discipline, less nurturing and sensitive; [117,118,119,120]). Such parenting practices may increase the risk of disinhibition, dysregulation, and behavioral problems (e.g., [13,115]), while maternal responsiveness in the context of prenatal tobacco exposure may be protective (e.g., [13]). Therefore, parent–child interactions and parenting practices may also serve as a potential moderator of the association between prenatal tobacco exposure and BDs.

Limitations

The current synthesis included 10 studies with 11 total independent samples, with only 1 study examining ODD and CD, which limits the generalizability of our findings for those outcomes. In addition, although the results suggested that there was not a significant amount of heterogeneity in the true outcomes for ADHD, there may have been limited power to detect heterogeneity due to the small sample size of the studies. An age range encompassing preschool- or school-aged through adolescence was chosen to represent school-aged children and adolescents and reflected the age ranges within many of the reviewed studies that spanned from preschool and kindergarten ages (4 or 5 years old) to mid to late adolescence (12 to 18 years old). There can be significant changes across these developmental periods and although past research has supported the stability of diagnoses as early as preschool-aged (e.g., [53]), there is the possibility that diagnoses may not persist from earlier to later periods. Further, the dose and timing of exposure may be significant factors influencing child outcomes [47,50,82]. Importantly, there was variation across reviewed studies in the detail with which prenatal tobacco exposure was assessed, ranging from a dichotomized approach (i.e., yes/no) and categorizing prenatal tobacco exposure (e.g., exposed versus non-exposed) to considering the level or quantity of smoking [87]. However, exposure group statuses across the reviewed studies were based primarily on maternal self-report of use. Patterns of smoking can vary across pregnancy [106,121], and methodology for assessing tobacco exposure may be important to consider [106,122]. In particular, reliance on solely maternal self-report of use is a significant limitation of past research, especially when quantified as a dichotomy of either exposed vs. not exposed without consideration of dose and timing of prenatal tobacco exposure across the prenatal period.

Importantly, the current review adds to previous research by focusing on studies that reported unadjusted associations between prenatal tobacco exposure and BD diagnoses in order to pool across comparable associations of the direct relationship [51]. Given that much of the previous research has covaried for a wide variety of factors associated with smoking during pregnancy, unadjusted associations allow for a clearer synthesis of the direct relationship between prenatal tobacco exposure and BDs. Smoking during pregnancy may be a marker of other risks for children developing externalizing behavior problems, including lower-quality parent–child interactions (e.g., Eiden et al., 2023), or shared genetic vulnerability [123]. The findings of the current review demonstrated pooled associations of a similar magnitude between prenatal tobacco exposure and ADHD as previous reviews examining ADHD symptomatology (e.g., pooled adjusted associations ranging from 1.56 to 1.64, [47,48,49,50]; unadjusted associations of 1.76, [49]). Across these meta-analyses and the current meta-analysis, the direct influence of prenatal tobacco exposure on BDs regardless of consideration of covariates is apparent. Nevertheless, there may be an important role of potential covariates, such as parental BD diagnoses or other substance exposure. For example, prenatal tobacco smokers are more likely to also use other substances, such as cannabis [124]. This comorbidity was not examined in the current study as very few of the reviewed studies examined cannabis exposure, but it may be useful for future research to consider potential additive or multiplicative effects. Alcohol use may also be an important additional substance to consider given that past meta-analyses examining ADHD symptomatology have suggested the importance of considering the impact of maternal alcohol use [50]. Adjusting for parental ADHD, however, has produced comparable associations in comparison to studies that did not adjust for parental ADHD [50]. Finally, we completed a quality assessment and recognized that due to the phenomenon under study and the methods through which prenatal tobacco exposure was typically assessed (i.e., maternal self-report), no study was in the low risk of bias category due to potential selection and reporting biases.

5. Conclusions

Based on the studies reviewed in this meta-analysis, there was a significant effect of prenatal tobacco exposure in increasing the likelihood of an ADHD diagnosis in childhood and adolescence. Although prenatal tobacco exposure does appear to be a risk factor for later ADHD diagnoses, the causal pathways linking the two are unclear and require further examination, such as teratological and familial influences. It may also be important for future studies to adopt consistent criteria when measuring prenatal tobacco exposure and clinical diagnoses to provide a more conclusive inference. Finally, it would be beneficial for additional research to include diagnoses of a broader spectrum of BD diagnoses more consistently, such as ODD and CD, as well as the potential comorbidities of the BDs.

Acknowledgments

We would like to thank the many research assistants who contributed their support and assistance with this project. We would also like to thank the College of Liberal Arts Dean’s Office and the Francena Miller Research Fellowship at the Rochester Institute of Technology for their support.

Author Contributions

Conceptualization, S.G., S.S. and M.L.; methodology, S.G., S.S., K.C. and M.L.; validation, S.G., S.S., K.C. and M.L.; formal analysis, S.S.; investigation, S.G., S.S., K.C. and M.L.; data curation, S.G., S.S., K.C. and M.L.; writing—original draft preparation, S.G., S.S. and K.C.; writing—review and editing, S.G., S.S., K.C. and M.L.; visualization, S.G., S.S. and K.C.; project administration, S.G. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data are available upon reasonable request to the first author.

Conflicts of Interest

The authors declare no conflicts of interest.

Figure 1 Identification of studies via databases and registers.

Figure 2 Forest plot of the random effects model of the relationship between prenatal tobacco exposure and ADHD diagnosis [39,86,87,88,89,90,91,92,93,94].

Figure 3 Funnel plot for ADHD. Note. Dots represent the observed outcomes in the included studies.

pediatrrep-16-00062-t001_Table 1 Table 1 Quality Assessment Ratings.

Assessment
Domain	Groups Similar and from Same Population	Tobacco Exposure Measured Similarly	Tobacco Exposure Measure Valid and Reliable	Confounding Factors Identified	Strategies to Deal with Confounding Factors	Groups Free of BD at the Time of Exposure	BD Measure Valid and Reliable	Follow Up Time Reported and Sufficient	Follow Up Complete and Reasons for Loss to Follow Up Described/Explored	Strategies to Address Incomplete Follow Up Utilized	Appropriate Statistical Analysis Used	
Arnold et al. (2005) [89]	+	+	−	+	+	+	+	+	−	−	+	
Arruda et al. (2015) [39]	Unclear	+	−	+	Unclear	+	+	+	Unclear	−	+	
Huang et al. (2019) [88]	−	+	−	+	+	+	−	+	+	N/A	+	
Kim et al. (2013) [90]	−	+	−	+	+	+	−	+	+	N/A	+	
Lipinska et al. (2021) [91]	−	+	−	+	−	+	+	+	Unclear	−	+	
McIntosh et al. (1995) [92]	Unclear	+	−	+	+	+	+	+	+	N/A	+	
Nigg and Breslau (2007) [86]	Unclear	+	−	+	+	+	+	+	Unclear	+	+	
Nordström et al. (2017) [93]	Unclear	+	−	+	+	+	+	+	−	−	+	
Sagiv et al. (2013) [87]	−	+	−	+	+	+	−	+	−	−	+	
Wang et al. (2008) [94]	−	+	−	+	+	+	+	+	+	N/A	+	
Note. + = Yes; − = No; N/A = Not applicable.

pediatrrep-16-00062-t002_Table 2 Table 2 Characteristics of studies included on prenatal tobacco exposure and BD diagnoses.

Study	Site	Number Exposed/Total Participants	Age (Years)	Assessment of Prenatal Smoking	BD Diagnosis Outcome	Assessment of BD	
Arnold et al. (2005) [89]	United States and Canada	163/714	7–9.9	Baseline assessment asked mothers about smoking in gestational period (yes/no)	ADHD; 215/468 with ADHD had comorbid ODD/CD	Diagnostic Interview Schedule for Children (DISC-IV)	
Arruda et al. (2015) [39]	Brazil	495/1830	5–13	Parents completed a study questionnaire	ADHD	Parents and/or caregivers completed the MTA-SNAP-IV scale	
Huang et al. (2019) [88]	China	Discovery Sample:
56/1058
Stage One Sample:
26/674	6–18	Maternal questionnaire covering environmental risk factors including prenatal smoking (yes/no)	ADHD	Diagnosis of ADHD by psychiatrists using DSM-IV diagnostic criteria	
Kim et al. (2013) [90]	United States	39/129	5–12	Parents completed a questionnaire about prenatal smoke exposure (yes/no) and other covariates	ADHD	A previous diagnosis by a physician based on DSM-IV diagnostic criteria	
Lipinska et al. (2021) [91]	Poland	57/282	7–17	Mothers completed a pregnancy and perinatal history questionnaire, including prenatal smoking (yes/no)	ADHD	Diagnosis of ADHD using DSM-IV-TR or ICD-10 criteria, verified with a structured history questionnaire	
McIntosh et al. (1995) [92]	United States	41/265	6–13	Mothers reported on smoking during pregnancy with the Maternal Perinatal Scale	ADHD	Diagnosis by physicians and psychologists of ADHD using DSM-III criteria, verified with school health and testing records	
Nigg and Breslau (2007) [86]	United States	247/600 with prenatal exposure vs. never exposed	6–17	Mothers reported on their daily smoking habits during pregnancy during an interview (yes/no)	ADHD age 6; ODD age 6; ADHD age 11; ODD age 11; ODD age 17; CD age 17	Diagnostic Interview Schedule for Children (DISC; version 2.1) and Diagnostic Interview Schedule for Youth (DIS-Y)	
Nordström et al. (2017) [93]	Finland	97/316 with ADHD diagnosis data	15–16	Information was systematically collected at antenatal clinics and birth hospital via self-report questionnaires and the delivery records	ADHD and/or DBD	At 15–16, Schedule for Affective Disorders and Schizophrenia for School-age Children—present and lifetime version (K-SADS-PL)	
Sagiv et al. (2013) [87]	United States	166/560 with smoking data	8	Mothers reported on their prenatal smoking approximately two weeks after birth on a questionnaire	ADHD	Pediatric records were reviewed at the time of assessment for ADHD diagnoses	
Wang et al. (2008) [94]	China	15/1260	4–12	Covariates and confounder assessed via clinical records or questionnaires completed by interviewing parents	ADHD	Schedule for Affective Disorders and Schizophrenia for School-age Children (K-SADS-E) modified to assess DSM-IV-R criteria	

Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
==== Refs
References

1. Centers for Disease Control and Prevention Information for Health Care Providers and Public Health Professionals: Preventing Tobacco Use During Pregnancy Division of Reproductive Health, National Center for Chronic Disease Prevention and Health Promotion Atlanta, GA, USA 2014
2. National Survey on Drug Use and Health NSDUH Report: Substance Use During Pregnancy: 2002 and 2003 Update Office of Applied Studies, Substance Abuse and Mental Health Services Administration (SAMHSA) Rockville, MD, USA 2005
3. Centers for Disease Control and Prevention QuickStats: Percentage of Births to Mothers Who Reported Smoking Cigarettes at Any Time During Pregnancy, by Urbanization Level of County of Residence—United States, 2020 Morb. Mortal. Wkly. Rep. 2021 70 1652 10.15585/mmwr.mm7047a5
4. Banderali G. Martelli A. Landi M. Moretti F. Betti F. Radaelli G. Lassandro C. Verduci E. Short and long term health effects of parental tobacco smoking during pregnancy and lactation: A descriptive review J. Transl. Med. 2015 13 327 10.1186/s12967-015-0690-y 26472248
5. Coles C.D. Kable J.A. Lynch M.E. Examination of gender differences in effects of tobacco exposure Gender Differences in Prenatal Substance Exposure Lewis M. Kestler L. American Psychological Association Washington, DC, USA 2012 99 120
6. Cornelius M.D. Day N.L. The effects of tobacco use during and after pregnancy on exposed children: Relevance of findings for alcohol research Alcohol. Res. Health 2000 24 242 249 15986719
7. Cornelius M.D. Day N.L. Developmental consequences of prenatal tobacco exposure Curr. Opin. Neurol. 2009 22 121 125 10.1097/WCO.0b013e328326f6dc 19532034
8. Cornelius M.D. Ryan C.M. Day N.L. Goldschmidt L. Willford J.A. Prenatal tobacco effects on neuropsychological outcomes among preadolescents J. Dev. Behav. Pediatr. 2001 22 217 225 10.1097/00004703-200108000-00002 11530894
9. Day N.L. Richardson G.A. Goldschmidt L. Cornelius M.D. Effects of prenatal tobacco exposure on preschoolers’ behavior J. Dev. Behav. Pediatr. 2000 21 180 188 10883878
10. Wiebe S.A. Clark C.A.C. De Jong D.M. Chevalier N. Espy K.A. Wakschlag L. Prenatal tobacco exposure and self-regulation in early childhood: Implications for developmental psychopathology Dev. Psychopathol. 2015 27 397 409 10.1017/S095457941500005X 25997761
11. Eiden R.D. Perry K.J. Ivanova M.Y. Marcus R.C. Prenatal Substance Exposure Annu. Rev. Dev. Psychol. 2023 5 19 44 10.1146/annurev-devpsych-120621-043414
12. Froggatt S. Covey J. Reissland N. Infant neurobehavioural consequences of prenatal cigarette exposure: A systematic review and meta-analysis Acta Paediatr. 2020 109 1112 1124 10.1111/apa.15132 31821600
13. Clark C.A. Massey S.H. Wiebe S.A. Espy K.A. Wakschlag L.S. Does early maternal responsiveness buffer prenatal tobacco exposure effects on young children’s behavioral disinhibition? Dev. Psychopathol. 2019 31 1285 1298 10.1017/S0954579418000706 30428950
14. Espy K.A. Fang H. Johnson C. Stopp C. Wiebe S.A. Respass J. Prenatal tobacco exposure: Developmental outcomes in the neonatal period Dev. Psychol. 2011 47 153 169 10.1037/a0020724 21038943
15. Huizink A.C. Mulder E.J. Maternal smoking, drinking or cannabis use during pregnancy and neurobehavioral and cognitive functioning in human offspring Neurosci. Biobehav. Rev. 2006 30 24 41 10.1016/j.neubiorev.2005.04.005 16095697
16. Kotimaa A.J. Moilanen I. Taanila A. Ebeling H. Smalley S.L. Mcgough J.J. Hartikainen A.-L. Järvelin M.-R. Maternal smoking and hyperactivity in 8-year-old children J. Am. Acad. Child Adolesc. Psychiatry 2003 42 826 833 10.1097/01.CHI.0000046866.56865.A2 12819442
17. Braun J.M. Kahn R.S. Froehlich T. Auinger P. Lanphear B.P. Exposures to environmental toxicants and attention deficit hyperactivity disorder in U.S. children Environ. Health Perspect. 2006 114 1904 1909 10.1289/ehp.9478 17185283
18. Han J.-Y. Kwon H.-J. Ha M. Paik K.-C. Lim M.-H. Lee S.G. Yoo S.-J. Kim E.-J. The effects of prenatal exposure to alcohol and environmental tobacco smoke on risk for ADHD: A large population-based study Psychiatry Res. 2015 225 164 168 10.1016/j.psychres.2014.11.009 25481018
19. Dolan C.V. Geels L. Vink J.M. van Beijsterveldt C.E.M. Neale M.C. Bartels M. Boomsma D.I. Testing causal effects of maternal smoking during pregnancy on offspring’s externalizing and internalizing behavior Behav. Genet. 2016 46 378 388 10.1007/s10519-015-9738-2 26324285
20. Ellis L.C. Berg-Nielsen T.S. Lydersen S. Wichstrøm L. Smoking during pregnancy and psychiatric disorders in preschoolers Eur. Child Adolesc. Psychiatry 2012 21 635 644 10.1007/s00787-012-0300-y 22767183
21. Gaysina D. Fergusson D.M. Leve L.D. Horwood J. Reiss D. Shaw D.S. Elam K.K. Natsuaki M.N. Neiderhiser J.M. Harold G.T. Maternal smoking during pregnancy and offspring conduct problems: Evidence from 3 independent genetically sensitive research designs JAMA Psychiatry 2013 70 956 963 10.1001/jamapsychiatry.2013.127 23884431
22. Wakschlag L.S. Lahey B.B. Loeber R. Green S.M. Gordon R.A. Leventhal B.L. Maternal smoking during pregnancy and the risk of conduct disorder in boys Arch. Gen. Psychiatry 1997 54 670 676 10.1001/archpsyc.1997.01830190098010 9236551
23. Berchiatti M. Ferrer A. Badenes-Ribera L. Longobardi C. School adjustments in children with attention deficit hyperactivity disorder (ADHD): Peer relationships, the quality of the student-teacher relationship, and children’s academic and behavioral competencies J. Appl. Sch. Psychol. 2022 38 241 261 10.1080/15377903.2021.1941471
24. Cook C.R. Williams K.R. Guerra N.G. Kim T.E. Sadek S. Predictors of bullying and victimization in childhood and adolescence: A meta-analytic investigation Sch. Psychol. Q. 2010 25 65 83 10.1037/a0020149
25. Erskine H.E. Norman R.E. Ferrari A.J. Chan G.C. Copeland W.E. Whiteford H.A. Scott J.G. Long-term outcomes of attention-deficit/hyperactivity disorder and conduct disorder: A systematic review and meta-analysis J. Am. Acad. Child Adolesc. Psychiatry 2016 55 841 850 10.1016/j.jaac.2016.06.016 27663939
26. Boylan K. Vaillancourt T. Boyle M. Szatmari P. Comorbidity of internalizing disorders in children with oppositional defiant disorder Eur. Child Adolesc. Psychiatry 2007 16 484 494 10.1007/s00787-007-0624-1 17896121
27. Chen M.-H. Su T.-P. Chen Y.-S. Hsu J.-W. Huang K.-L. Chang W.-H. Chen T.-J. Bai Y.-M. Higher risk of developing mood disorders among adolescents with comorbidity of attention deficit hyperactivity disorder and disruptive behavior disorder: A nationwide prospective study J. Psychiatr. Res. 2013 47 1019 1023 10.1016/j.jpsychires.2013.04.005 23643104
28. Christenson J.D. Crane D.R. Malloy J. Parker S. The cost of oppositional defiant disorder and disruptive behavior: A review of the literature J. Child Fam. Stud. 2016 25 2649 2658 10.1007/s10826-016-0430-9
29. Matza L.S. Paramore C. Prasad M. A review of the economic burden of ADHD Cost Eff. Resour. Alloc. 2005 3 5 10.1186/1478-7547-3-5 15946385
30. Tsai K.H. Yeh M. Slymen D. Strain in caring for youths meeting diagnosis for disruptive behavior disorders J. Emot. Behav. Disord. 2015 23 40 51 10.1177/1063426613503498
31. Kashdan T.B. Jacob R.G. Pelham W.E. Lang A.R. Hoza B. Blumenthal J.D. Gnagy E.M. Depression and anxiety in parents of children with adhd and varying levels of oppositional defiant behaviors: Modeling relationships with family functioning J. Clin. Child Adolesc. Psychol. 2004 33 169 181 10.1207/S15374424JCCP3301_16 15028551
32. Foster E.M. Jones D.E. The Conduct Problems Prevention Research Group The high costs of aggression: Public expenditures resulting from conduct disorder Am. J. Public Health 2005 95 1767 1772 10.2105/AJPH.2004.061424 16131639
33. Guevara J.P. Mandell D.S. Rostain A.L. Zhao H. Hadley T.R. National estimates of health services expenditures for children with behavioral disorders: An analysis of the medical expenditure panel survey Pediatrics 2003 112 e440 e446 10.1542/peds.112.6.e440 14654642
34. Schein J. Adler L.A. Childress A. Cloutier M. Gagnon-Sanschagrin P. Davidson M. Kinkead F. Guerin A. Lefebvre P. Economic burden of attention-deficit/hyperactivity disorder among children and adolescents in the United States: A societal perspective J. Med. Econ. 2022 25 193 205 10.1080/13696998.2022.2032097 35068300
35. Pelham W.E. Foster E.M. Robb J.A. The economic impact of attention-deficit/hyperactivity disorder in children and adolescents J. Pediatr. Psychol. 2007 32 711 727 10.1093/jpepsy/jsm022 17556402
36. Erskine H.E. Ferrari A.J. Polanczyk G.V. Moffitt T.E. Murray C.J.L. Vos T. Whiteford H.A. Scott J.G. The global burden of conduct disorder and attention-deficit/hyperactivity disorder in 2010 J. Child Psychol. Psychiatry 2014 55 328 336 10.1111/jcpp.12186 24447211
37. Melchior M. Hersi R. van der Waerden J. Larroque B. Saurel-Cubizolles M.-J. Chollet A. Galéra C. Maternal tobacco smoking in pregnancy and children’s socio-emotional development at age 5: The EDEN mother-child birth cohort study Eur. Psychiatry 2015 30 562 568 10.1016/j.eurpsy.2015.03.005 25843027
38. Wang Y. Buckingham-Howes S. Nair P. Zhu S. Magder L.S. Black M.M. Prenatal drug exposure, behavioral problems, and drug experimentation among African-American urban adolescents J. Adolesc. Health 2014 55 423 431 10.1016/j.jadohealth.2014.02.021 24768161
39. Arruda M.A. Querido C.N. Bigal M.E. Polanczyk G.V. ADHD and mental health status in Brazilian school-age children J. Atten. Disord. 2015 19 11 17 10.1177/1087054712446811 22665924
40. Ball S.W. Gilman S.E. Mick E. Fitzmaurice G. Ganz M.L. Seidman L.J. Buka S.L. Revisiting the association between maternal smoking during pregnancy and ADHD J. Psychiatr. Res. 2010 44 1058 1062 10.1016/j.jpsychires.2010.03.009 20413131
41. Hill S.Y. Lowers L. Locke-Wellman J. Shen S.A. Maternal smoking and drinking during pregnancy and the risk for child and adolescent psychiatric disorders J. Stud. Alcohol 2000 61 661 668 10.15288/jsa.2000.61.661 11022804
42. Thapar A. Fowler T. Rice F. Scourfield J. van den Bree M. Thomas H. Harold G. Hay D. Maternal Smoking During Pregnancy and Attention Deficit Hyperactivity Disorder Symptoms in Offspring Am. J. Psychiatry 2003 160 1985 1989 10.1176/appi.ajp.160.11.1985 14594745
43. E Gilman S. Hornig M. Invited Commentary: The Disillusionment of Developmental Origins of Health and Disease (DOHaD) Epidemiology Am. J. Epidemiol. 2020 189 1 5 10.1093/aje/kwz214 31576401
44. American Psychiatric Association Diagnostic and Statistical manual of Mental Disorders 5th ed. American Psychiatric Association Washington, DC, USA 2013
45. Üstün B. Kennedy C. What is “functional impairment”? Disentangling disability from clinical significance World Psychiatry 2009 8 82 85 10.1002/j.2051-5545.2009.tb00219.x 19516924
46. Sciberras E. Mulraney M. Silva D. Coghill D. Prenatal risk factors and the etiology of ADHD—Review of existing evidence Curr. Psychiatry Rep. 2017 19 1 10.1007/s11920-017-0753-2 28091799
47. Haan E. Westmoreland K.E. Schellhas L. Sallis H.M. Taylor G. Zuccolo L. Munafò M.R. Prenatal smoking, alcohol and caffeine exposure and offspring externalizing disorders: A systematic review and meta-analysis Addiction 2022 117 2602 2613 10.1111/add.15858 35385887
48. He Y. Chen J. Zhu L.-H. Hua L.-L. Ke F.-F. Maternal Smoking During Pregnancy and ADHD: Results From a Systematic Review and Meta-Analysis of Prospective Cohort Studies J. Atten. Disord. 2020 24 1637 1647 10.1177/1087054717696766 29039728
49. Dong T. Hu W. Zhou X. Lin H. Lan L. Hang B. Lv W. Geng Q. Xia Y. Prenatal exposure to maternal smoking during pregnancy and attention-deficit/hyperactivity disorder in offspring: A meta-analysis Reprod. Toxicol. 2018 76 63 70 10.1016/j.reprotox.2017.12.010 29294364
50. Huang L. Wang Y. Zhang L. Zheng Z. Zhu T. Qu Y. Mu D. Maternal Smoking and Attention-Deficit/Hyperactivity Disorder in Offspring: A Meta-analysis Pediatrics 2018 141 e20172465 10.1542/peds.2017-2465 29288161
51. Chang B.-H.S. Hoaglin D.C. Meta-Analysis of Odds Ratios: Current Good Practices Med. Care 2017 55 328 335 10.1097/MLR.0000000000000696 28169977
52. Egger H.L. Angold A. Common emotional and behavioral disorders in preschool children: Presentation, nosology, and epidemiology J. Child Psychol. Psychiatry 2006 47 313 337 10.1111/j.1469-7610.2006.01618.x 16492262
53. Keenan K. Boeldt D. Chen D. Coyne C. Donald R. Duax J. Hart K. Perrott J. Strickland J. Danis B. Predictive validity of DSM-IV oppositional defiant and conduct disorders in clinically referred preschoolers J. Child Psychol. Psychiatry 2011 52 47 55 10.1111/j.1469-7610.2010.02290.x 20738448
54. Cooper H. Research Synthesis and Meta-Analysis: A Step-by-Step Approach 4th ed. Sage Publications, Inc. Thousand Oaks, CA, USA 2010
55. DerSimonian R. Laird N. Meta-analysis in clinical trials Control Clin. Trials 1986 7 177 188 10.1016/0197-2456(86)90046-2 3802833
56. Cochran W.G. The combination of estimates from different experiments Biometrics 1954 10 101 129 10.2307/3001666
57. Higgins J.P.T. Thompson S.G. Quantifying heterogeneity in a meta-analysis Stat. Med. 2002 21 1539 1558 10.1002/sim.1186 12111919
58. Viechtbauer W. Cheung M.W.-L. Outlier and influence diagnostics for meta-analysis Res. Synth. Methods 2010 1 112 125 10.1002/jrsm.11 26061377
59. R Core Team R: A Language and Environment for Statistical Computing R Foundation for Statistical Computing; R Core Team Vienna, Austria 2020 Available online: https://www.R-project.org/ (accessed on 21 May 2023)
60. Viechtbauer W. Conducting Meta-Analyses in R with the metafor Package J. Stat. Softw. 2010 36 1 48 10.18637/jss.v036.i03
61. Rothstein H.R. Sutton A.J. Borenstein M. Publication bias in meta-analysis Publication Bias in Meta-Analysis: Prevention, Assessment and Adjustments Rothstein H.R. Sutton A.J. Borenstein M. John Wiley & Sons Hoboken, NJ, USA 2006
62. Begg C.B. Mazumdar M. Operating characteristics of a rank correlation test for publication bias Biometrics 1994 50 1088 1101 10.2307/2533446 7786990
63. Sterne J.A. Egger M. Regression methods to detect publication and other bias in meta-analysis Publication Bias in Meta-Analysis: Prevention, Assessment and Adjustment Rothstein H.R. Sutton A.J. Borenstein M. Wiley Hoboken, NJ, USA 2005 99 110
64. Moola S. Munn Z. Tufanaru C. Aromataris E. Sears K. Sfetcu R. Currie M. Lisy K. Qureshi R. Mattis P. Chapter 7: Systematic Reviews of Effectiveness JBI Manual for Evidence Synthesis Aromataris E. Lockwood C. Porritt K. Pilla B. Jordan Z. JBI Adelaide, Australia 2020 Available online: https://synthesismanual.jbi.global (accessed on 23 January 2024)
65. Schlack R. Göbel K. Hölling H. Petermann F. Romanos M. Prädiktoren der Stabilität des Elternberichts über die ADHS-Lebenszeitprävalenz und Inzidenz der elternberichteten ADHS-Diagnose im Entwicklungsverlauf über sechs Jahre–Ergebnisse aus der KiGGS-Studie Z. Psychiatr. Psychol. Psychother. 2018 66 233 247 10.1024/1661-4747/a000361
66. Schmitz J.C. Cholemkery H. Medda J. Freitag C.M. Prä-und perinatale Risikofaktoren bei Autismus-Spektrum-Störung und Aktivitäts-und Aufmerksamkeitsstörung Z. Kinder. Jugendpsychiatr. Psychother. 2017 45 1 9 10.1024/1422-4917/a000507 28128013
67. Brinksma D.M. Hoekstra P.J. Hoofdakker B.v.D. de Bildt A. Buitelaar J.K. Hartman C.A. Dietrich A. Age-dependent role of pre- and perinatal factors in interaction with genes on ADHD symptoms across adolescence J. Psychiatr. Res. 2017 90 110 117 10.1016/j.jpsychires.2017.02.014 28259004
68. Slotkin T.A. If nicotine is a developmental neurotoxicant in animal studies, dare we recommend nicotine replacement therapy in pregnant women and adolescents? Neurotoxicol. Teratol. 2008 30 1 19 10.1016/j.ntt.2007.09.002 18380035
69. Zhu J.L. Olsen J. Liew Z. Li J. Niclasen J. Obel C. Parental smoking during pregnancy and ADHD in children: The Danish national birth cohort Pediatrics 2014 134 e382 e388 10.1542/peds.2014-0213 25049343
70. Mick E. Biederman J. Faraone S.V. Sayer J. Kleinman S. Case-control study of attention-deficit hyperactivity disorder and maternal smoking, alcohol use, and drug use during pregnancy J. Am. Acad. Child Adolesc. Psychiatry 2002 41 378 385 10.1097/00004583-200204000-00009 11931593
71. Owens E.B. Hinshaw S.P. Perinatal problems and psychiatric comorbidity among children with ADHD J. Clin. Child Adolesc. Psychol. 2013 42 762 768 10.1080/15374416.2013.785359 23581554
72. Russell G. Ford T. Rosenberg R. Kelly S. The association of attention deficit hyperactivity disorder with socioeconomic disadvantage: Alternative explanations and evidence J. Child Psychol. Psychiatry 2014 55 436 445 10.1111/jcpp.12170 24274762
73. Wakschlag L.S. Pickett K.E. Kasza K.E. Loeber R. Is prenatal smoking associated with a developmental pattern of conduct problems in young boys? J. Am. Acad. Child Adolesc. Psychiatry 2006 45 461 467 10.1097/01.chi.0000198597.53572.3e 16601651
74. Chen K. Budman C.L. Herrera L.D. Witkin J.E. Weiss N.T. Lowe T.L. Freimer N.B. Reus V.I. Mathews C.A. Prevalence and clinical correlates of explosive outbursts in Tourette Syndrome Psychiatry Res. 2013 205 269 275 10.1016/j.psychres.2012.09.029 23040794
75. Roigé-Castellví J. Morales-Hidalgo P. Voltas N. Hernández-Martínez C. van Ginkel G. Canals J. Prenatal and perinatal factors associated with ADHD risk in schoolchildren: EPINED epidemiological study Eur. Child Adolesc. Psychiatry 2020 30 347 358 10.1007/s00787-020-01519-2 32242248
76. Tatarka M.E. Neurobehavioral Characteristics of Infants Exposed to Cocaine University of Washington Washington, DC, USA 1997
77. Joelsson P. Chudal R. Talati A. Suominen A. Brown A.S. Sourander A. Prenatal smoking exposure and neuropsychiatric comorbidity of ADHD: A finnish nationwide population-based cohort study BMC Psychiatry 2016 16 306 10.1186/s12888-016-1007-2 27581195
78. Brander G. Rydell M. Kuja-Halkola R. de la Cruz L.F. Lichtenstein P. Serlachius E. Rück C. Almqvist C. D’Onofrio B.M. Larsson H. Perinatal risk factors in Tourette’s and chronic tic disorders: A total population sibling comparison study Mol. Psychiatry 2018 23 1189 1197 10.1038/mp.2017.31 28348386
79. Cochran D.M. Jensen E.T. Frazier J.A. Jalnapurkar I. Kim S. Roell K.R. Joseph R.M. Hooper S.R. Santos H.P. Kuban K.C.K. Association of prenatal modifiable risk factors with attention-deficit hyperactivity disorder outcomes at age 10 and 15 in an extremely low gestational age cohort Front. Hum. Neurosci. 2022 16 911098 10.3389/fnhum.2022.911098 36337853
80. Desrosiers C. Boucher O. Forget-Dubois N. Dewailly É. Ayotte P. Jacobson S.W. Jacobson J.L. Muckle G. Associations between prenatal cigarette smoke exposure and externalized behaviors at school age among Inuit children exposed to environmental contaminants Neurotoxicol. Teratol. 2013 39 84 90 10.1016/j.ntt.2013.07.010 23916943
81. Freitag C.M. Hänig S. Schneider A. Seitz C. Palmason H. Retz W. Meyer J. Biological and psychosocial environmental risk factors influence symptom severity and psychiatric comorbidity in children with ADHD J. Neural Transm. 2012 119 81 94 10.1007/s00702-011-0659-9 21626412
82. Sciberras E. Ukoumunne O.C. Efron D. Predictors of parent-reported attention-deficit/hyperactivity disorder in children aged 6–7 years: A national longitudinal study J. Abnorm. Child Psychol. 2011 39 1025 1034 10.1007/s10802-011-9504-8 21468666
83. Langley K. Heron J. Smith G.D. Thapar A. Maternal and paternal smoking during pregnancy and risk of ADHD symptoms in offspring: Testing for intrauterine effects Am. J. Epidemiol. 2012 176 261 268 10.1093/aje/kwr510 22791738
84. Palmer R.H.C. Bidwell L.C. Heath A.C. Brick L.A. Madden P.A.F. Knopik V.S. Effects of maternal smoking during pregnancy on offspring externalizing problems: Contextual effects in a sample of female twins Behav. Genet. 2016 46 403 415 10.1007/s10519-016-9779-1 26826031
85. Madley-Dowd P. Kalkbrenner A.E. Heuvelman H. Heron J. Zammit S. Rai D. Schendel D. Maternal smoking during pregnancy and offspring intellectual disability: Sibling analysis in an intergenerational Danish cohort Psychol. Med. 2022 52 1847 1856 10.1017/S0033291720003621 33050963
86. Nigg J.T. Breslau N. Prenatal smoking exposure, low birth weight, and disruptive behavior disorders J. Am. Acad. Child Adolesc. Psychiatry 2007 46 362 369 10.1097/01.chi.0000246054.76167.44 17314722
87. Sagiv S.K. Epstein J.N. Bellinger D.C. Korrick S.A. Pre- and postnatal risk factors for ADHD in a nonclinical pediatric population J. Atten. Disord. 2013 17 47 57 10.1177/1087054711427563 22298092
88. Huang X. Zhang Q. Gu X. Hou Y. Wang M. Chen X. Wu J. LPHN3 gene variations and susceptibility to ADHD in Chinese Han population: A two-stage case–control association study and gene–environment interactions Eur. Child Adolesc. Psychiatry 2019 28 861 873 10.1007/s00787-018-1251-8 30406846
89. Arnold L.E. Elliott M. Lindsay R.L. Molina B. Cornelius M.D. Vitiello B. Hechtman L. Elliott G.R. Newcorn J. Epstein J.N. Gestational and postnatal tobacco smoke exposure as predictor of ADHD, comorbid ODD/CD, and treatment response in the MTA Clin. Neurosci. Res. 2005 5 295 306 10.1016/j.cnr.2005.09.009
90. Kim S. Arora M. Fernandez C. Landero J. Caruso J. Chen A. Lead, mercury, and cadmium exposure and attention deficit hyperactivity disorder in children Environ. Res. 2013 126 105 110 10.1016/j.envres.2013.08.008 24034783
91. Lipińska E. Słopień A. Pytlińska N. Słopień R. Wolańczyk T. Bryńska A. The role of factors associated with the course of pregnancy and childbirth in attention deficit hyperactivity disorder (ADHD) Psychiatr. Polska 2021 55 659 673 10.12740/PP/OnlineFirst/110686 34460889
92. McIntosh D.E. Mulkins R.S. Dean R.S. Utilization of maternal perinatal risk indicators in the differential diagnosis of ADHD and UADD children Int. J. Neurosci. 1995 81 35 46 10.3109/00207459509015297 7775071
93. Nordström T. Hurtig T. Rodriguez A. Savolainen J. Rautio A. Moilanen I. Taanila A. Ebeling H. Different Risk Factors Between Disruptive Behavior Disorders and ADHD in Northern Finland Birth Cohort 1986 J. Atten. Disord. 2017 21 904 912 10.1177/1087054714538654 25001369
94. Wang H.-L. Chen X.-T. Yang B. Ma F.-L. Wang S. Tang M.-L. Hao M.-G. Ruan D.-Y. Case–control study of blood lead levels and attention deficit hyperactivity disorder in Chinese children Environ. Health Perspect. 2008 116 1401 1406 10.1289/ehp.11400 18941585
95. American Psychiatric Association Diagnostic and Statistical Manual of Mental Disorders 3rd ed. Text Revision; American Psychiatric Association Washington, DC, USA 1980
96. American Psychiatric Association Diagnostic and Statistical Manual of Mental Disorders 4th ed. Text Revision; American Psychiatric Association Washington, DC, USA 1994
97. Costello A. Edelbrock C. Kalas R. Kessler R. Klaric S. The Diagnostic Interview Schedule for Children, Parent Version (Revised) University of Massachusetts Medical Center Worcester, MA, USA 1982
98. Shaffer D. Fisher P. Piacentini J. Schwab-Stone M. Wicks J. Diagnostic Interview Schedule for Children Second Revision; New York State Psychiatric Institute New York, NY, USA 1989
99. Kaufman J. Birmaher B. Brent D. Rao U. Flynn C. Moreci P. Williamson D. Ryan N. Schedule for Affective Disorders and Schizophrenia for School-Age Children-Present and Lifetime Version (K-SADS-PL): Initial Reliability and Validity Data J. Am. Acad. Child Adolesc. Psychiatry 1997 36 980 988 10.1097/00004583-199707000-00021 9204677
100. Kaufman J. Birmaher B. Brent D.A. Ryan N.D. Rao U. K-SADS-PL J. Am. Acad. Child Adolesc. Psychiatry 2000 39 1208 10.1097/00004583-200010000-00002
101. Swanson J.M. Kraemer H.C. Hinshaw S.P. Arnold L.E. Conners C.K. Abikoff H.B. Clevenger W. Davies M. Elliott G.R. Greenhill L.L. Clinical relevance of the primary findings of the MTA: Success rates based on severity of ADHD and ODD symptoms at the end of treatment J. Am. Acad. Child Adolesc. Psychiatry 2001 40 168 179 10.1097/00004583-200102000-00011 11211365
102. Wilson D.B. Practical Meta-Analysis Effect Size Calculator [Online Calculator] Available online: https://campbellcollaboration.org/research-resources/effect-size-calculator.html (accessed on 1 May 2023)
103. Latimer K. Wilson P. Kemp J. Thompson L. Sim F. Gillberg C. Puckering C. Minnis H. Disruptive behaviour disorders: A systematic review of environmental antenatal and early years risk factors Child Care Health Dev. 2012 38 611 628 10.1111/j.1365-2214.2012.01366.x 22372737
104. Tien J. Lewis G.D. Liu J. Prenatal risk factors for internalizing and externalizing problems in childhood World J. Pediatr. 2020 16 341 355 10.1007/s12519-019-00319-2 31617077
105. Tiesler C.M.T. Heinrich J. Prenatal nicotine exposure and child behavioural problems Eur. Child Adolesc. Psychiatry 2014 23 913 929 10.1007/s00787-014-0615-y 25241028
106. Estabrook R. Massey S.H. Clark C.A.C. Burns J.L. Mustanski B.S. Cook E.H. O’Brien T.C. Makowski B. Espy K.A. Wakschlag L.S. Separating family-level and direct exposure effects of smoking during pregnancy on offspring externalizing symptoms: Bridging the behavior genetic and behavior teratologic divide Behav. Genet. 2016 46 389 402 10.1007/s10519-015-9762-2 26581695
107. Suzuki K. Minei L.J. Johnson E. Effect of nicotine upon uterine blood flow in the pregnant rhesus monkey Am. J. Obstet. Gynecol. 1980 136 1009 1013 10.1016/0002-9378(80)90628-6 6768293
108. Slotkin T.A. Fetal nicotine or cocaine exposure: Which one is worse? J. Pharmacol. Exp. Ther. 1998 285 931 945 9618392
109. Mamiya N. Buchanan R. Wallace T. Skinner R.D. Garcia-Rill E. Nicotine suppresses the P13 auditory evoked potential by acting on the pedunculopontine nucleus in the rat Exp. Brain Res. 2005 164 109 119 10.1007/s00221-005-2219-8 15754179
110. Law K.L. Stroud L.R. LaGasse L.L. Niaura R. Liu J. Lester B.M. Smoking during pregnancy and newborn neurobehavior Pediatrics 2003 111 1318 1323 10.1542/peds.111.6.1318 12777547
111. Stroud L.R. McCallum M. Salisbury A.L. Impact of maternal prenatal smoking on fetal to infant neurobehavioral development Dev. Psychopathol. 2018 30 1087 1105 10.1017/S0954579418000676 30068428
112. Shields A. Cicchetti D. Reactive aggression among maltreated children: The Contributions of attention and emotion dysregulation J. Clin. Child Psychol. 1998 27 381 395 10.1207/s15374424jccp2704_2 9866075
113. Kuja-Halkola R. D’onofrio B.M. Larsson H. Lichtenstein P. maternal smoking during pregnancy and adverse outcomes in offspring: Genetic and environmental sources of covariance Behav. Genet. 2014 44 456 467 10.1007/s10519-014-9668-4 25117564
114. D’Onofrio B.M. van Hulle C.A. Waldman I.D. Rodgers J.L. Harden K.P. Rathouz P.J. Lahey B.B. Smoking during pregnancy and offspring externalizing problems: An exploration of genetic and environmental confounds Dev. Psychopathol. 2008 20 139 164 10.1017/S0954579408000072 18211732
115. Eiden R.D. Schuetze P. Coles C.D. Maternal cocaine use and mother–infant interactions: Direct and moderated associations Neurotoxicol. Teratol. 2011 33 120 128 10.1016/j.ntt.2010.08.005 21256426
116. Scott T.J.L. Heil S.H. Higgins S.T. Badger G.J. Bernstein I.M. Depressive symptoms predict smoking status among pregnant women Addict. Behav. 2009 34 705 708 10.1016/j.addbeh.2009.04.003 19411145
117. Brook J.S. Brook D.W. Whiteman M. The Influence of Maternal Smoking During Pregnancy on the Toddler’s Negativity Arch. Pediatr. Adolesc. Med. 2000 154 381 385 10.1001/archpedi.154.4.381 10768677
118. Tandon M. Si X. Belden A. Spitznagel E. Wakschlag L.S. Luby J. Parenting practices in pregnancy smokers compared to non smokers J. Clin. Med. Res. 2013 5 84 91 10.4021/jocmr1283w 23519319
119. Fergusson D.M. Woodward L.J. Horwood L.J. Maternal smoking during pregnancy and psychiatric adjustment in late adolescence Arch. Gen. Psychiatry 1998 55 721 727 10.1001/archpsyc.55.8.721 9707383
120. Schuetze P. Eiden R.D. Dombkowski L. The association between cigarette smoking during pregnancy and maternal behavior during the neonatal period Infancy 2006 10 267 288 10.1207/s15327078in1003_4 36101896
121. Pickett K.E. Wakschlag L.S. Dai L. Leventhal B.L. Fluctuations of maternal smoking during pregnancy Obstet. Gynecol. 2003 101 140 147 10.1016/s0029-7844(02)02370-0 12517659
122. Massey S.H. Clark C.A. Sun M.Y. Burns J.L. Mroczek D.K. Espy K.A. Wakschlag L.S. Dimension- and context-specific expression of preschoolers’ disruptive behaviors associated with prenatal tobacco exposure Neurotoxicol. Teratol. 2020 81 106915 10.1016/j.ntt.2020.106915 32693011
123. El Marroun H. Bolhuis K. A Franken I.H. Jaddoe V.W.V. Hillegers M.H. Lahey B.B. Tiemeier H. Preconception and prenatal cannabis use and the risk of behavioural and emotional problems in the offspring; a multi-informant prospective longitudinal study Leuk. Res. 2019 48 287 296 10.1093/ije/dyy186
124. Oga E.A. Mark K. Coleman-Cowger V.H. Cigarette Smoking Status and Substance Use in Pregnancy Matern. Child Health J. 2018 22 1477 1483 10.1007/s10995-018-2543-9 29882032
