Is Maternal Smoking During Pregnancy a Risk Factor for Cigarette Smoking in Offspring? A Longitudinal Controlled Study of ADHD Children Grown Up

Abstract

Objective: This study examined whether exposure to maternal smoking during pregnancy in children with and without ADHD is associated with smoking in offspring and whether this association is selective to ADHD children. Method: Ninety-six exposed and 400 unexposed participants were derived from two longitudinal studies of boys and girls with and without ADHD. Maternal smoking during pregnancy was defined by interviews with participants’ mothers. Results: A significant association was observed between exposure to maternal smoking in pregnancy and cigarette smoking in offspring (p = .02). Exposed offspring were also more likely to have higher rates of major depression (p = .04), bipolar disorder (p = .04), and conduct disorder (p = .04), and lower IQ (p = .01), lower Global Assessment of Functioning (GAF) score (p = .02), and more impaired Social Adjustment Inventory for Children and Adolescents (SAICA) scores versus unexposed offspring, adjusting for social class. Conclusion: Maternal smoking during pregnancy was found to increase the risk for smoking and a wide range of adverse psychiatric, cognitive, and functional outcomes in youth.

Keywords

ADHD smoking children risk

Introduction

Tobacco use among youth is a growing and alarming public health challenge. More than 3.5 million middle and high school students smoke cigarettes (U.S. Department of Health and Human Services, 2014), and 88% of adult smokers report that they started smoking by the age of 18 (U.S. Department of Health and Human Services, 2012). The annual public and private health care spending caused by smoking totals over US$132 billion (U.S. Department of Health and Human Services, 2014). Considering the known morbidity and mortality associated with smoking, efforts aimed at identifying risk factors for smoking in youth have large clinical, scientific, and public health significance.

In recent years, several investigative groups have documented a significant association between maternal smoking during pregnancy and ADHD (Banerjee, Middleton, & Faraone, 2007; Holz et al., 2014; Langley, Rice, van den Bree, & Thapar, 2005; Lindblad & Hjern, 2010; Linnet et al., 2003; Mick, Biederman, Faraone, Sayer, & Kleinman, 2002; Milberger, Biederman, Faraone, Chen, & Jones, 1996; Milberger, Biederman, Faraone, & Jones, 1998; Motlagh et al., 2011), conduct disorder (CD; Monuteaux, Blacker, Biederman, Fitzmaurice, & Buka, 2006), and bipolar disorder (Talati et al., 2013) in offspring. As these prevalent disorders have significantly increased risks for smoking themselves, it raises the possibility that maternal smoking during pregnancy may contribute to the risk for smoking in youth either directly or indirectly.

A better understanding as to whether maternal smoking during pregnancy is a risk factor for smoking in youth is an area of high clinic, scientific, and public health relevance. This is so considering that maternal smoking during pregnancy is a preventable risk that could be addressed with appropriate education and early intervention programs.

The main aim of this study was to evaluate whether exposure to maternal smoking during pregnancy contributes to the risk for smoking in youth. To this end, we examined the relationship between maternal smoking during pregnancy and offspring risk for smoking using data from a well characterized, longitudinal, and opportunistic sample of youth with and without ADHD of both sexes followed up prospectively and blindly onto young adult years. Because maternal smoking during pregnancy has also been associated with conduct (Monuteaux et al., 2006) and bipolar disorders (Talati et al., 2013), other substance use disorders (SUDs; Ekblad, Gissler, Lehtonen, & Korkeila, 2010), and cognitive deficits (Ernst, Moolchan, & Robinson, 2001), we also examined the association between these outcomes and maternal smoking during pregnancy.

Method

Detailed methodological information has been previously reported (Biederman et al., 1996; Biederman et al., 1992; Biederman et al., 1999; Biederman, Monuteaux, Mick, Spencer, Wilens, Klein, et al., 2006; Biederman, Monuteaux, Mick, Spencer, Wilens, Silva, et al., 2006; Biederman et al., 2010). Briefly, participants were derived from two identically designed, longitudinal case–control family studies of children with and without ADHD of both sexes ascertained from pediatric and psychiatric sources. These studies recruited male and female participants aged 6 to 17 years with (n = 140 boys, n = 140 girls and their first-degree relatives) and without (n = 120 boys, n = 122 girls and their first-degree relatives) Diagnostic and Statistical Manual of Mental Disorders (3rd ed., rev.; DSM-III-R; American Psychiatric Association [APA], 1987) ADHD. Male participants were assessed at baseline, 1-, 4-, and 10-year follow-ups whereas female participants were assessed at baseline, 5-, and 11-year follow-ups. The current sample includes information through the 10- and 11-year follow-ups for the boys and girls studies, respectively.

We excluded potential participants if they had major sensorimotor handicaps (paralysis, deafness, blindness), psychosis, autism, inadequate command of the English language, a Full Scale IQ less than 80, if their nuclear family was not available for study or if they were adopted. All of the ADHD participants met full DSM-III-R diagnostic criteria for ADHD at the time of the clinic referral; at the time of recruitment, they all had active symptoms of the disorder. At all assessment periods, parents and adult offspring provided written informed consent to participate, and parents also provided consent for offspring below the age of 18. Children and adolescents provided written assent to participate. The human research committee at Massachusetts General Hospital (MGH) approved the initial assessments as well as all aspects of the follow-up study.

Follow-Up Assessment Procedures

All assessments at all waves were conducted by highly selected, highly trained, and highly supervised psychometricians with undergraduate degrees in psychology. Lifetime psychiatric assessment at the 10- to 11-year follow-ups relied on the Schedule for Affective Disorder and Schizophrenia for Children (KSADS-E; Orvaschel, 1994) for participants younger than 18 years of age and the Structured Clinical Interview for the Diagnostic and Statistical Manual of Mental Disorders (4th ed.; DSM-IV; APA, 1994; SCID; First, Spitzer, Gibbon, & Williams, 1997; Spitzer, Williams, Gibbon, & First, 1990) supplemented with modules from the K-SADS-E to assess childhood diagnoses for participants 18 years of age and older. We conducted indirect interviews with participant’s mothers and direct interviews with participants >12 years. Both structured interviews had specific modules to assess smoking abuse and dependence. We combined data from indirect and direct interviews by considering a diagnostic criterion positive if it was endorsed in either interview.

Board-certified child and adult psychiatrists who were blind to the participant’s ADHD status, referral source and all other data resolved diagnostic uncertainties. We estimated the reliability of the diagnostic review process by computing kappa coefficients of agreement for clinician reviewers. For these diagnoses in children and adults, the median reliability between individual clinicians and the review committee assigned diagnoses was 0.87. To assess the reliability of our overall diagnostic procedures, we computed kappa coefficients of agreement by having experienced, blinded, board-certified child and adult psychiatrists diagnose participants from audiotaped interviews made by the assessment staff. Based on 500 assessments from interviews of children and adults, the median kappa coefficient was 0.98. Kappa coefficients for individual diagnoses included major depression (1.0), mania (0.95), ADHD (0.88), CD (1.0), oppositional defiant disorder (ODD; 0.90), antisocial personality disorder (ASPD; 0.80), major depression (1.0), and SUD (1.0).

Interviewers assessed the degree of impairment on daily functioning associated with each disorder that participants endorsed on a three-level ordinal scale: minimal (e.g., little to no impairment), moderate (e.g., difficulties in daily life tasks), or severe (e.g., unable to perform essential daily tasks). Consistent with our prior work, we considered major depression only if the depressive episode was associated with severe impairment, to avoid false positive diagnoses. As there is not a similar precedent for bipolar or SUDs, we adopted a less stringent approach and made the diagnosis only when associated with at least moderate impairment.

As previously described (Biederman et al., 1996; Biederman et al., 1992; Biederman et al., 1999; Biederman, Monuteaux, Mick, Spencer, Wilens, Klein, et al., 2006; Biederman, Monuteaux, Mick, Spencer, Wilens, Silva, et al., 2006; Biederman et al., 2010), participants were also assessed with a battery of neurocognitive tests measuring IQ, neuropsychological functioning to include measures of sustained attention/vigilance, planning and organization, interference control, set shifting and categorization, selective attention and visual scanning, verbal and visual learning, and memory, learning disability in math and reading, school functioning, and psychosocial functioning (Social Adjustment Inventory for Children and Adolescents [SAICA], John, Gammon, Prusoff, & Warner, 1987; and Global Assessment of Functioning [GAF] scales). Specifically, we estimated Full Scale IQ using the methods of Sattler (1988), from the vocabulary and block design subtests of Wechsler Intelligence Scales for Children–Revised (WISC-R; Wechsler, 1974) for participants younger than 17 and the Wechsler Adult Intelligence Scales–Revised (WAIS-R; Wechsler, 1981) for participants older than 17. Academic achievement was estimated using the Arithmetic Subtest of the Wide Range Achievement Test–Revised (Jastak & Jastak, 1985) and the Reading Subtest of the Wide Range Achievement Test–Revised (Jastak & Jastak, 1985). Participants in the study of boys with ADHD were administered the Gilmore Oral Reading test (Gilmore & Gilmore, 1968) at the baseline assessment. At baseline, the neuropsychological battery included (a) Rey–Osterrieth Complex Figure (Osterrieth, 1944; Rey, 1941; Bernstein & Waber, 1996), (b) The auditory Continuous Performance Test (CPT; Weintraub & Mesulam, 1985), (c) the computerized Wisconsin Card Sorting Test (WCST; Heaton, Chelune, Talley, Kay, & Curtiss, 1993), (d) the Wide Range Achievement test of Memory and Learning (WRAML) list learning test for children <17 (Adams & Sheslow, 1990) or the California Verbal Learning Test (CVLT) in children ≥17 years of age (Delis, Kramer, Kaplan, & Ober, 1987), (e) the Stroop test (Golden, 1978), and (f) The Freedom From Distractibility index (Wechsler, 1974, 1981), which included Coding, Arithmetic, and Digit Span. To estimate IQ at their respective 10-year follow-ups, the battery of the boys study consisted of the Wechsler Adult Intelligence Scales–III (WAIS-III) Vocabulary and Block Design, and the battery of the girls study used the Wechsler Abbreviated Scale of Intelligence (WASI) Vocabulary subtest and Matrix Reasoning subtests (Wechsler, 1999). Subtests from the WAIS-III were used to assess Working Memory, including the Arithmetic and Digit Span as well as Symbol Search and Coding subtests to assess processing speed in the boys study, and the Trail Making, Tower, and Color Word Interference Tests of the Delis–Kaplan Executive Functions Scale (D-KEFS; Delis, Kaplan, & Kraemer, 2001) in the girls study. For achievement, we used the arithmetic and reading subtests of the Wide Range Achievement Test–III and Test of Word Reading Efficiency (TOWRE) in the girls study. Social class was measured using the 5-point Hollingshead scale (Hollingshead, 1975).

Measurement of exposure to maternal smoking during pregnancy

Maternal smoking during pregnancy was coded positive if the mother answered “yes” to the following question during the indirect structured interview: “Did you smoke as much as a pack a day for at least 3 months while pregnant with this child?” Maternal smoking during pregnancy was also coded positive if during the direct structured interview the mother met criteria for nicotine abuse or dependence during the time she was pregnant with the child (utilizing the reported onset and offset of nicotine abuse/dependence and the date-of-birth of the child). Nicotine abuse cases were defined as the endorsement of smoking any amount of cigarettes 4 to 6 days per week. We included abuse cases to capture regular smoking habits that, while not as serious as dependence, still represent a potential risk to the fetus. This second definition was only used in the Girls ADHD study, as the Boys ADHD study did not assess nicotine abuse/dependence in the mothers’ structured interview.

Statistical Analysis

To assess the effects of maternal smoking in pregnancy on children, we compared the demographic characteristics between exposed and unexposed participants using t tests for normal outcomes, the Wilcoxon rank-sum test for socioeconomic status (SES), and the Pearson χ² tests for binary outcomes. We used the Cox proportional hazards model to assess the risk of SUDs and cigarette smoking. We used logistic regression to examine differences between risks for lifetime comorbid disorders as well as academic, cognitive, and global functioning. We also used linear regression to compare the SAICA scores between those exposed to maternal smoking and those unexposed. To determine whether risk for smoking among offspring was affected by an interaction between ADHD and exposure, we included the interaction term, ADHD status-by-maternal smoking exposure, across all models. Data are expressed as mean ± SD unless otherwise specified. All tests were two-tailed, and our alpha level was set at .05 for all analyses, unless otherwise noted. We calculated all statistics using STATA, version 12.0.

Results

Our final sample included 96 exposed and 400 unexposed participants. As seen in Table 1, we found no significant difference between the groups in age, gender, or race. We did find, however, significant associations between the groups for SES and ADHD, with the exposed group having a lower SES and a higher proportion of ADHD. We found that the interaction term, ADHD status-by-maternal smoking exposure, was not significant across all models and we subsequently removed it from the analyses (all p values > .05).

Table 1.

Demographic Characteristics (N = 496) at 10-Year Follow-Up.

	Unexposed (n = 400)	Exposed (n = 96)	Statistic
Age (years)	21.2 ± 4.4	21.1 ± 4.1	t = 0.12, p = .91
% male	210 (53)	42 (44)	χ²(1) = 2.4, p = .12
SES	1.6 ± 0.8	2.2 ± 1.03	z = −5.0, p < .0001
Race/ethnicity
Caucasian	383 (96)	93 (97)	χ²(3) = 4.3, p = .23
African American	12 (3)	1 (1)
Asian American	3 (0.5)	0 (0)
Unknown	2 (0.5)	2 (2)
ADHD status	204 (51)	63 (66)	χ²(1) = 6.7, p = .01

Note. SES = socioeconomic status.

Risk for Cigarette Smoking in Exposed and Unexposed Youth

When adjusting for both ADHD and SES, a significant association was observed between being exposed to maternal smoking in pregnancy and cigarette smoking in the participants (Figure 1, p = .02). This association lost significance when additionally adjusting for major depression, bipolar disorder, and CD (p = .89). We did not find any significant differences between the groups for any SUD, any alcohol abuse, alcohol dependence, substance abuse, or substance dependence (all p values > .05; see Figure 1).

Figure 1.

Exposure to maternal cigarette smoking and endorsement of offspring substance use disorders and cigarette smoking (N = 496).

As seen in Table 2, while adjusting for SES, exposed participants were more likely to have higher rates of most comorbid disorders, particularly major depression (p = .04), bipolar disorder (p = .04), and CD (p = .04) when compared with unexposed ones. However, when adjusting for both ADHD and SES, the association for major depression was the only association that remained statistically significant (p = .04), most likely due to limited statistical power.

Table 2.

Psychiatric Disorders (Lifetime).

	Unexposed (n = 400)	Exposed (n = 96)	Statistics (adjusted for SES)		Statistics (adjusted for ADHD and SES)
	Unexposed (n = 400)	Exposed (n = 96)	OR (95% CI)	p	OR (95% CI)	p
Major depression	206 (52)	66 (69)	1.87 [1.15, 3.04]	.04	1.71 [1.02, 2.87]	.04
Bipolar disorder	57 (14)	26 (27)	1.78 [1.02, 3.09]	.04	1.56 [0.87, 2.81]	.14
Psychosis	21 (5)	6 (6)	0.92 [0.35, 2.45]	.87	0.78 [0.29, 2.09]	.61
Disruptive disorders
Conduct disorder	82 (21)	33 (34)	1.69 [1.02, 2.80]	.04	1.51 [0.89, 2.58]	.13
Oppositional defiant disorder	161 (40)	50 (52)	1.38 [0.87, 2.19]	.18	1.14 [0.66, 1.96]	.63
Anxiety disorders
Multiple anxiety disorders (≥2)	122 (31)	36 (38)	1.22 [0.75, 1.97]	.42	1.01 [0.65, 1.78]	.78
Avoidance disorder	16 (4)	6 (6)	1.16 [0.42, 3.19]	.77	1.14 [0.41, 3.14]	.81
Separation anxiety disorder	96 (24)	29 (30)	1.22 [0.73, 2.03]	.45	1.08 [0.64, 1.83]	.78
Posttraumatic stress disorder	11 (3)	7 (7)	2.06 [0.74, 5.72]	.16	1.89 [0.68, 5.31]	.22
Agoraphobia	74 (19)	27 (28)	1.62 [0.95, 2.74]	.07	1.46 [0.84, 2.52]	.18
Simple phobia	121 (30)	34 (35)	1.16 [0.72, 1.89]	.54	1.06 [0.64, 1.74]	.82
Social phobia	95 (24)	36 (38)	1.61 [0.99, 2.64]	.06	1.49 [0.90, 2.46]	.12
Panic disorder	63 (16)	14 (15)	0.91 [0.48, 1.74]	.79	0.85 [0.44, 1.64]	.63
Generalized anxiety disorder	54 (14)	18 (19)	1.34 [0.73, 2.49]	.35	1.34 [0.73, 2.49]	.35

Note. SES = socioeconomic status; OR = odds ratio; CI = confidence interval.

Risks for Cognitive, School, and Interpersonal Functioning

Adjusting for SES, exposed participants were more likely to have required placement in special class (Table 3; p = .01). We also found that exposed participants had a lower vocabulary scaled score (p = .02), a lower IQ (p = .01), and a lower GAF score (p = .02), compared with unexposed participants. All other associations were not statistically significant (p > .05). When we adjusted for both ADHD and SES, the association between unexposed and exposed participants for GAF scores lost significance (p = .15). For the SAICA scores, when adjusting for SES,we found that those exposed to maternal smoking during pregnancy were more likely to have problems with their peers (Figure 2; β = 0.34; 95% confidence interval [CI] = [−0.16, −0.53]; p < .001), and their siblings (β = 0.21; 95% CI = [0.02, 0.41]; p = .03), and had a worse relationship with their fathers (β = 0.20; 95% CI = [0.01, 0.39]; p = .04). We found no other significant associations (all p values > .05). When we adjusted for both ADHD and SES, only the associations spare time activities (β = −0.14; 95% CI = [−0.28, −0.009]; p = .04) and problems with their peers (β = 0.26; 95% CI = [0.10, 0.43]; p = .002) remained significant. All other associations lost significance (p > .05). No significant interactions with ADHD were identified.

Table 3.

Academic, Cognitive, and Global Functioning.

	Unexposed (n = 400)	Exposed (n = 96)	Statistics (adjusting for SES)		Statistics (adjusting for ADHD and SES)
	Unexposed (n = 400)	Exposed (n = 96)	OR/β (95% CI)	p	OR/β (95% CI)	p
Academic function
Repeated grade	89 (22)	33 (34)	OR = 1.45 [0.87, 2.40]	.15	OR = 1.29 [0.76, 2.19]	.34
Special class	81 (20)	38 (40)	OR = 2.01 [1.22, 3.31]	.01	OR = 1.83 [1.03, 3.22]	.04
Extra help	264 (66)	70 (73)	OR = 1.26 [0.76, 2.10]	.37	OR = 1.01 [0.57, 1.81]	.97
Cognitive functioning
Vocabulary SS	13.30 ± 2.96	11.79 ± 2.94	β = −0.77 [−1.39, −0.15]	.02	β = −0.63 [−1.24, −0.03]	.04
Digit span SS	11.59 ± 3.06	10.52 ± 2.96	β = −0.55 [−1.22, 0.12]	.11	β = −0.39 [−1.03, 0.26]	.24
Oral arithmetic SS	12.39 ± 3.03	11.72 ± 2.93	β = −0.08 [−0.74, 0.57]	.80	β = 0.11 [−0.52, 0.73]	.73
Digit symbol SS	12.10 ± 2.92	11.66 ± 3.17	β = −0.05 [0.72, 0.62]	.88	β = 0.12 [−0.53, 0.77]	.71
Full scale IQ	112.0 ± 13.10	108.8 ± 14.14	β = −3.70 [−6.47, −0.93]	.01	β = −2.94 [−5.6, −0.28]	.03
Global functioning
GAF score	64.06 ± 9.82	60.36 ± 9.76	β = −2.60 [−4.82, −0.38]	.02	β = −1.07 [−2.53, 0.39]	.15

Note. SES = socioeconomic status; OR = odds ratio; CI = confidence interval; SS = scaled score; GAF = Global Assessment of Functioning.

Figure 2.

SAICA scores between those exposed and unexposed to maternal smoking.

Discussion

A significant association was observed between exposure to maternal smoking in pregnancy and cigarette smoking in the offspring. In addition, offspring exposed to maternal smoking during pregnancy were at increased risk for major depression, bipolar disorder, and CD. The ADHD status of the child did not affect this association. Taken together, these results support the hypothesis that maternal smoking during pregnancy may have both a direct and indirect contribution to the risk for smoking in the offspring independently of ADHD status.

The finding that children exposed to maternal smoking during pregnancy were more likely to have higher rates of smoking but not alcohol or drug abuse or dependence suggests that the effects of maternal smoking during pregnancy on substance abuse risk may be selective for smoking. However, other investigators reported an increased risk for SUDs in offspring of mothers exposed to smoking during pregnancy (Ekblad et al., 2010). Also, because nicotine has been shown to be a “gateway” drug for other SUDs (Biederman, Monuteaux, Mick, Wilens, et al., 2006; Biederman, Petty, Hammerness, Batchelder, & Faraone, 2012), a broader association of maternal smoking with SUD would be expected. More work is needed to resolve these discrepant findings.

The finding that exposure to maternal smoking during pregnancy increased the risks for conduct and mood disorders expands the previously reported association between exposure to maternal smoking during pregnancy and risk for ADHD (Banerjee et al., 2007; Holz et al., 2014; Langley et al., 2005; Linnet et al., 2003; Mick et al., 2002; Milberger et al., 1996; Milberger et al., 1998). For example, Ekblad et al. (2010) using data from the Finnish Medical Birth Register (n = 175,869), reported that the risk of psychiatric morbidity was significantly higher in the exposed children than in unexposed ones for most of the psychiatric diagnoses, particularly for behavioral and emotional disorders. Because the association between maternal and child smoking lost significance after controlling for mood, and CD, these disorders may mediate the association.

The association between exposure to maternal smoking during pregnancy and risk for CD in the offspring has been well documented in the literature. Early studies by Wakschlag et al. (1997) and Weissman, Warner, Wickramaratne, and Kandel (1999) reported that mothers who smoked during pregnancy were significantly more likely to have a child with CD than mothers who did not smoke during pregnancy even when controlling for a wide range of potential confounders including SES, maternal age, parental antisocial personality, substance abuse during pregnancy, and maladaptive parenting; these results suggest that maternal smoking during pregnancy is a robust independent risk factor for CD in offspring despite the difficulty in disaggregating prenatal environmental influences from genetic and postnatal environmental influences.

This association was recently confirmed in a study by Gaysina et al. (2013), using data from three independent studies that reported a significant association between maternal smoking during pregnancy and offspring conduct problems. Findings across these three studies using a complement of genetically sensitive research designs strongly suggest that smoking during pregnancy is a prenatal risk factor for offspring conduct problems even when controlling for specific perinatal and postnatal confounding factors.

Also consistent with the literature is the finding that exposure to maternal smoking during pregnancy increased the risk for bipolar disorders. Recently, Talati et al. (2013) reported that offspring exposed in utero to maternal smoking exhibited a twofold greater risk for bipolar disorder (odds ratio [OR] = 2.014, 95% CI = [1.48, 2.53], p = 0.01) even after adjusting for potential confounders. Likewise, El Marroun et al. (2014) showed that young children of mothers who smoked during pregnancy had worse affective scores than unexposed children, even after controlling for numerous confounders including alcohol ingestion, mothers’ education level, and socioeconomic factors. In addition, cortical thinning in precentral and superior frontal cortices was associated with worse affective outcomes. Although other familial and psychosocial factors cannot be ruled out, these findings suggest that prenatal tobacco exposure during pregnancy may contribute to the risk for bipolar disorder.

As ADHD, conduct and mood disorders can also increase the risk for smoking in youth (Biederman et al., 2008; Hammerness et al., 2013; Wilens et al., 2008; Wilens et al., 2009), taken together these findings support the hypothesis that exposure to maternal smoking during pregnancy could contribute to the risk for smoking in these disorders. They also suggest that, through these disorders, exposure to maternal smoking during pregnancy indirectly contributes to the risk of smoking in youth in general.

The finding that offspring exposed to maternal smoking during pregnancy have lower IQ than unexposed ones is also consistent with literature. Ernst et al. (2001) reported a dose–response relationship between maternal smoking during pregnancy and low birth weight, potentially associated with lower cognitive ability. In a recent study, El Marroun et al. (2014) reported that young primary-grade children of mothers who smoked during pregnancy had smaller total brain volume, decreased gray-matter volumes, and cortical thinning even after controlling for numerous factors, including alcohol ingestion, mothers’ education level, and socioeconomic factors. Consistent with these deleterious effects on the brain are our findings showing that offspring exposed to maternal smoking during pregnancy were more likely to have required placement in special classes, to have lower GAF scores, and more impaired interpersonal functioning as assessed through the SAICA when compared with unexposed offspring.

The reasons why exposure to maternal smoking during pregnancy increases the risk for smoking and psychopathology in the offspring are not entirely clear. Disturbances in neuronal pathfinding, abnormalities in cell proliferation and differentiation, and disruptions in the development of the cholinergic and catecholaminergic systems all have been reported in molecular animal studies of in utero exposure to nicotine (Ernst et al., 2001). These data suggest that prenatal exposure to nicotine dysregulates neurodevelopment leading to a higher risk for psychiatric problems in the offspring (Ernst et al., 2001). Theoretical considerations also suggest that the pharmacologic effects of nicotine in the brain could disrupt the mesolimbic dopaminergic pathway, which is prominent in the neurobiology of addictions (Levin & Kleber, 1995), including nicotine addiction, as well as disorders such as ADHD, CD, and mood disorders (Charney, Sklar, Buxbaum, & Nestler, 2013).

Our findings need to be viewed in light of methodological limitations. Our sample size did not allow for the adequate control of all risk factors for smoking in youth (D’Onofrio, Van Hulle, Goodnight, Rathouz, & Lahey, 2012). While we corrected for social class, when we simultaneously controlled for both ADHD and SES, many of the findings lost statistical significance. Thus, we cannot rule out the possibility that confounders, such as ADHD, SES, or other factors that we did not assess, could account for the observed findings. As indicated by Ellingson, Rickert, Lichtenstein, Langstrom, and D’Onofrio (2012), maternal smoking during pregnancy is associated with an increase in other risk factors. Of the variance associated with smoking during pregnancy, 45% could be attributed to genetic factors while 53% was attributed to unshared environmental factors suggesting that the intergenerational transmission of genes conferring risk for antisocial behavior and substance misuse in the mother influences the associations between maternal smoking during pregnancy and adverse offspring outcomes (Ellingson et al., 2012). Thapar and Rutter (2009) argued that caution is required in assuming causation as associations with prenatal risk factors may arise because of postnatal risk or through confounders, including inherited ones. Although mothers and offspring older than 12 years were directly interviewed, we cannot rule out the possibility of recall bias in general and whether recall bias affected differentially mothers of children with ADHD and ADHD children. Furthermore, as all information collected relied on self-report, including information on smoking, it is possible that the rates identified may be an underrepresentation of the true rate of smoking in mothers and offspring. Future studies may benefit from more objective assessments of smoking including biological assays. We lacked details regarding in utero cigarette exposure precluding our ability to assess dose–response relationships between cigarette exposure and offspring outcomes. In addition, as we did not assess smoking in the postnatal environment, we could not assess the independent effects of postnatal smoke exposure on the same kinds of outcomes reported in this manuscript. Although we did not conduct mediation/moderation analyses, we did covary by ADHD and sociodemographic variables. Nevertheless, future studies could benefit from more specific mediator/moderator approaches. As we relied for this analysis in an opportunistic, large, and well characterized sample of children with and without ADHD of both sexes, we do not know whether these findings will generalize to other samples. Furthermore, as this sample was acquired in the past, we also do not know whether our findings would differ in a newly acquired sample given changes in policy and known changes in patterns of youth smoking and maternal smoking during pregnancy over the past 10 to 15 years. As the participating families were largely Caucasian and referred, the findings may not generalize to community samples and other ethnic groups.

Although preliminary and in need of replication, our findings suggest that exposure to maternal smoking in pregnancy can increase the risk for a wide range of adverse outcomes in the offspring including an increased risk for cigarette smoking, conduct and mood disorders, low IQ, and functional impairments. Findings suggest that maternal smoking during pregnancy may have both a direct and indirect effect on the risk for smoking in the offspring, which is worthy of further investigation.

Despite the difficulty of separating exposure to maternal smoking during pregnancy from other genetic and environmental factors (Ernst et al., 2001), knowledge of prenatal exposure to nicotine should prompt clinicians in any medical discipline to closely monitor at-risk children. Findings should also encourage the development of programs aimed at educating and providing tobacco cessation interventions to women of childbearing age for preventing the potential wide ranging risks to the offspring associated with smoking during pregnancy. In addition, as smoking is far more prevalent among psychiatric patients than in the general population, these findings are especially relevant to mental health professionals (El Marroun et al., 2014).

Footnotes

Authors’ Note

The study sponsors did not have any role in study design, data collection, analysis, interpretation, or writing of the manuscript. Also, they did not have a role in the decision to submit the manuscript for publication.

Declaration of Conflicting Interests

The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: Dr. Joseph Biederman is currently receiving research support from the following sources: The Department of Defense, Army Aboriginal Community Assistance Program (AACAP), Alcobra, Forest Research Institute, Ironshore, Lundbeck, Magceutics, Inc., Merck, PamLab, Pfizer, Shire Pharmaceuticals, Inc., SPRITES, Sunovion, Vaya Pharma/Enzymotec, and National Institute of Health (NIH). In 2014, Dr. Joseph Biederman received honoraria from the Massachusetts General Hospital (MGH) Psychiatry Academy for tuition-funded continuing medical education (CME) courses. He has a U.S. Patent Application pending (Provisional Number 61/233,686) through MGH corporate licensing, on a method to prevent stimulant abuse. Dr. Biederman received departmental royalties from a copyrighted rating scale used for ADHD diagnoses, paid by Ingenix, Prophase, Shire, Bracket Global, Sunovion, and Theravance; these royalties were paid to the Department of Psychiatry at MGH. In 2013, Dr. Joseph Biederman received an honorarium from the MGH Psychiatry Academy for a tuition-funded CME course. He received research support from American Professional Society of ADHD and Related Disorders (APSARD), ElMindA, McNeil, and Shire. Dr. Biederman received departmental royalties from a copyrighted rating scale used for ADHD diagnoses, paid by Shire and Sunovion; these royalties were paid to the Department of Psychiatry at MGH. In 2012, Dr. Joseph Biederman received an honorarium from the MGH Psychiatry Academy and The Children’s Hospital of Southwest Florida/Lee Memorial Health System for tuition-funded CME courses. In 2011, Dr. Joseph Biederman gave a single unpaid talk for Juste Pharmaceutical Spain, received honoraria from the MGH Psychiatry Academy for a tuition-funded CME course, and received honoraria for presenting at international scientific conference on ADHD. He also received an honorarium from Cambridge University Press for a chapter publication. Dr. Biederman received departmental royalties from a copyrighted rating scale used for ADHD diagnoses, paid by Eli Lilly, Shire and AstraZeneca; these royalties were paid to the Department of Psychiatry at MGH. In previous years, Dr. Joseph Biederman received research support, consultation fees, or speaker’s fees for/from the following additional sources: Abbott, Alza, AstraZeneca, Boston University, Bristol Myers Squibb, Celltech, Cephalon, Cipher Pharmaceuticals, Inc., Eli Lilly and Co., Esai, Fundacion Areces (Spain), Forest, Fundación Dr. Manuel Camelo A.C., Glaxo, Gliatech, Hastings Center, Janssen, McNeil, Medice Pharmaceuticals (Germany), Merck, MGH Psychiatry Academy, Maine Medical Center (MMC) Pediatric, National Alliance for Research on Schizophrenia and Depression (NARSAD), National Institute on Drug Abuse (NIDA), New River, National Institute of Child Health and Human Development (NICHD), National Institute of Mental Health (NIMH), Novartis, Noven, Neurosearch, Organon, Otsuka, Pfizer, Pharmacia, Phase V Communications, Physicians Academy, The Prechter Foundation, Quantia Communications, Reed Exhibitions, Shionogi Pharma, Inc., Shire, the Spanish Child Psychiatry Association, The Stanley Foundation, UCB Pharma, Inc., Veritas, and Wyeth. Dr. Spencer has received research support from, has been a speaker for or on a speaker bureau or has been an Advisor or on an Advisory Board of the following sources: Alcobra, Cephalon, Inc., Eli Lilly & Company, Glaxo-Smith Kline, Heptares, Impax, Ironshore, Janssen Pharmaceutical, Lundbeck, Inc., McNeil Pharmaceutical, Novartis Pharmaceuticals, Pfizer, Shire Laboratories, Sunovion, VayaPharma, Enzymotec, Ltd., the NIMH and the Department of Defense. He receives research support from Royalties and Licensing fees on copyrighted ADHD scales through MGH Corporate Sponsored Research and Licensing. He has a U.S. Patent Application pending (Provisional Number 61/233,686), through MGH corporate licensing, on a method to prevent stimulant abuse. Dr. Faraone received income, travel expenses, and/or research support from and/or has been on an Advisory Board for Pfizer, Ironshore, Shire, Akili Interactive Labs, CogCubed, Alcobra, VAYA Pharma, Neurovance, Impax, NeuroLifeSciences, and research support from the National Institutes of Health (NIH). His institution is seeking a patent for the use of sodium-hydrogen exchange inhibitors in the treatment of ADHD. In previous years, he received consulting fees or was on Advisory Boards or participated in CME programs sponsored by Shire, Alcobra, Otsuka, McNeil, Janssen, Novartis, Pfizer, and Eli Lilly. Dr. Faraone receives royalties from books published by Guilford Press: Straight Talk about Your Child’s Mental Health and Oxford University Press: Schizophrenia: The Facts. Ms. Martelon and Ms. Woodworth report no conflicts of interest.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This manuscript was supported, in part, by grants to J. Biederman from the National Institutes of Health (R01 HD36317, R01 MH50657) and the Pediatric Psychopharmacology Research Council Fund.

Author Biographies

Joseph Biederman, MD, is the chief of the Clinical and Research Programs in pediatric psychopharmacology and adult ADHD, and director of the Alan and Lorraine Bressler Clinical and Research Program for Autism Spectrum Disorders, at Massachusetts General Hospital (MGH), Boston, MA. He is a professor of psychiatry at Harvard Medical School, Boston, MA.

MaryKate Martelon, MPH, is a statistician in the pediatric psychopharmacology and Adult ADHD Clinical and Research Programs at MGH.

K. Yvonne Woodworth, BA, is the administrative and scientific assistant to Dr. Joseph Biederman in the pediatric psychopharmacology and Adult ADHD Clinical and Research Programs at MGH.

Thomas J. Spencer, MD, is the assistant chief of the Clinical and Research Programs in pediatric psychopharmacology and adult ADHD at MGH, Boston, MA. He is also an associate professor at Harvard Medical School, Boston, MA.

Stephen V. Faraone, PhD, is the director of the Medical Genetics Research Center and distinguished professor of psychiatry and neuroscience and physiology at State University of New York (SUNY) Upstate Medical University, Syracuse, NY. He is also senior scientific advisor to the pediatric psychopharmacology and adult ADHD program at MGH and a lecturer at Harvard Medical School, Boston, MA.

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