NOMURA, GILMAN, AND BUKA 199
Maternal Smoking During Pregnancy and Risk of Alcohol
Use Disorders Among Adult Offspring*
YOKO NOMURA, PH.D., M.P.H.,† STEPHEN E. GILMAN, SC.D.,† AND STEPHEN L. BUKA, SC.D.†
Department of Psychology, Queens College, The City University of New York, 65-30 Kissena Boulevard, Flushing, New York, 11367
ABSTRACT. Objective: The aim of this study was to evaluate the asso-
ciation between maternal smoking during pregnancy (MSP) and lifetime
risk for alcohol use disorder (AUD) and to explore possible mechanisms
through which MSP may be related to neurobehavioral conditions during
infancy and childhood, which could, in turn, lead to increased risk for
AUD. Method: A sample of 1,625 individuals was followed from preg-
nancy for more than 40 years. Capitalizing on the long follow-up time,
we used survival analysis to examine lifetime risks of AUD (diagnosed
according to the Diagnostic and Statistical Manual of Mental Disorders,
Fourth Edition) in relation to levels of MSP (none, <20 cigarettes/day,
and ≥20 cigarettes/day). We then used structural equation modeling to
test hypotheses regarding potential mechanisms, including lower birth
weight, neurological abnormalities, poorer academic functioning, and
behavioral dysregulation. Results: Relative to unexposed offspring,
offspring of mothers who smoked 20 cigarettes per day or more exhib-
ited greater risks for AUD (hazard ratio = 1.31, 95% CI [1.08, 1.59]).
However, no differences were observed among offspring exposed to
fewer than 20 cigarettes per day. In structural equation models, MSP was
associated with neurobehavioral problems during infancy and childhood,
which, in turn, were associated with an increased risk for adult AUD.
Conclusions: MSP was associated with an increased lifetime risk for
AUD. Adverse consequences were evident from birth to adulthood. A
two-pronged remedial intervention targeted at both the mother (to reduce
smoking during pregnancy) and child (to improve academic functioning)
may reduce the risk for subsequent AUD. (J. Stud. Alcohol Drugs, 72,
plinary Tobacco Use Research Center award P50 CA084719; an American
Beverage and Medical Research Grant award; and grants from the National
Cancer Institute, the National Institute on Drug Abuse, the Robert Wood
Johnson Foundation, the National Institute of Aging (AG023397), and the
National Institute of Mental Health grant (K01MH080062).
via email at: email@example.com. Yoko Nomura is also with the De-
partment of Psychiatry, Division of Child and Adolescent Psychiatry, Mount
Sinai School of Medicine, New York, NY. Stephen E. Gilman is with the
Department of Society, Human Development, and Health, and Department
of Epidemiology, Harvard School of Public Health, Boston, MA. Stephen
L. Buka is with the Department of Community Health, Brown University,
Received: September 11, 2009. Revision: August 19, 2010.
*This work was supported by National Institutes of Health Transdisci-
†Correspondence may be sent to Yoko Nomura at the above address or
cause of death in the United States, with approximately
79,000 deaths annually attributable to excessive alcohol use
(Centers for Disease Control and Prevention, 2004). Chronic
drinking causes a variety of functional impairments and has
many harmful health consequences. These include liver dis-
ease (Heron, 2007; Schiff, 1997); cancer (Baan et al., 2007);
cardiovascular disease (Rehm et al., 2003); neurological
damage (Corrao et al., 2002, 2004); HIV infection (Rosen-
bloom et al., 2007; Windle, 1997); and psychiatric problems
such as depression, anxiety, and antisocial personality disor-
der (Castaneda et al., 1996; Kessler et al., 1997; Rosenthal
and Westreich, 1999). Chronic drinking is also associated
with an elevated risk for unintended accidents such as falls
(Goodman et al., 1991), drowning (Cummings and Quan,
1999), burns (Hingson and Howland, 1993; McGill et al.,
CCORDING TO THE Centers for Disease Control and
Prevention, alcohol is the third highest lifestyle-related
1995), fatal motor vehicle crashes (National Highway Traf-
fi c Safety Administration, 2008), and interpersonal violence
(Bushman, 1997; Caetano et al., 2000).
Various biological and psychological risk factors for
alcohol use disorder (AUD) have been identifi ed, including
alcohol metabolism, genetic risks, and psychosocial risks
(i.e., lack of parental monitoring, severe and recurrent fam-
ily confl ict, and poor parent–child relationships) (Quete-
mont, 2004; Wall et al., 2007). However, to the best of our
knowledge, maternal smoking during pregnancy (MSP)
has never been found to be a potential distal risk factor
for alcohol use problems and AUD despite its association
with a variety of adverse outcomes, including substance
use disorders, in later life. For instance, the adverse effect
of MSP on birth outcomes is well established, including an
approximately 150-250 g decrement in birth weight (Sub-
stance Abuse and Mental Health Services Administration,
2005; Visscher et al., 2003) and a higher neonatal mortality
rate (Duncan et al., 2008; Fleming and Blair, 2007). Infants
exposed to MSP also displayed an elevated risk for sud-
den infant death syndrome (Edner et al., 2007; Markowitz,
2007; Weese-Mayer et al., 2007), neurological and lan-
guage problems (Fried, 1993; Fried et al., 1992a, 1992b),
diffi cult temperaments (Brook et al., 1998), aggression
(Tremblay et al., 2004), behavioral problems (Maughan et
al., 2004; Monuteaux et al., 2006; Orlebeke et al., 1997),
cognitive function defi cits (Keeping et al., 1989; Naeye and
Peters, 1984; Nomura et al., 2008), attention defi cits and
hyperactivity (Button et al., 2005; Linnet et al., 2005; Wak-
schlag et al., 1997), early onset of delinquency and antiso-
cial behavioral problems (Nomura et al., 2009; Piquero et
200 JOURNAL OF STUDIES ON ALCOHOL AND DRUGS / MARCH 2011
al., 2002; Wakschlag et al., 2003; Weitzman et al., 1992),
cigarette smoking in adolescence and adulthood (Buka
et al., 2003; Cornelius et al., 2000, 2005; Griesler et al.,
1998), and drug use (Ekblad et al., 2010) Fergusson et al.,
1998; Weissman et al., 1999). These fi ndings all indicate
that MSP may indeed impair the development of the fetal
central nervous system in a fashion that may predispose
the offspring to a wide array of neurobehavioral problems.
To date, few studies have tried to systematically elucidate
potential mechanisms by which MSP may impair the child’s
central nervous system early in life and the subsequent in-
creased risk for AUD. Furthermore, we are unaware of prior
studies that have examined whether there is a direct link
between MSP and AUD in adulthood or if their association
can, at least in part, be explained by problems in the preced-
ing stages of life. Approximately 10-20% of women smokers
who become pregnant continue to smoke during pregnancy
(DiFranza and Lew, 1995; Maughan et al., 2004), and MSP
is one of the early modifi able risk factors that could poten-
tially reduce the incidence of adverse outcomes throughout
the life course (Ringel and Evans, 2001; Shiono and Beh-
In this study, we used data from a population-based
sample of children who have been followed more than 40
years to address two aims: (a) to evaluate the lifetime risk
for Diagnostic and Statistical Manual of Mental Disorders,
Fourth Edition (DSM-IV; American Psychiatric Associa-
tion, 1994), AUD associated with exposure to MSP and (b)
to elucidate possible mechanisms through which MSP af-
fects neurobehavioral conditions during early infancy and
childhood (i.e., birth weight, neurological abnormalities,
academic functioning, and behavioral regulation), which
may lead to an increased risk for AUD. We hypothesized
that there will be a greater risk for AUD among offspring
exposed to MSP than those unexposed. We also hypothesized
that MSP is associated with increased risk for AUD, and that
this association will be mediated in part through problems in
infancy and childhood.
ect (CPP), consisting of prospective data collected from
a representative sample of pregnant women who received
prenatal care and delivered their babies during 1960-1966
(Niswander and Gordon, 1972). The CPP used a single study
design across all 12 sites. The sites participated in a system-
atic data collection from pregnancy to the fi rst 7 years to
identify perinatal and early childhood factors that adversely
affect subsequent child development (Buka et al., 1993).
Reports from the CPP have been summarized elsewhere
(Nicholas and Chan, 1981).
Data were derived from the Collaborative Perinatal Proj-
was established to locate and interview a sample of the adult
CPP offspring at the Providence, RI, and Boston, MA, sites.
Participants were selected through a multistage sampling
procedure, which involved a core assessment interview and
three component studies. Screening questionnaires were
mailed to 4,579 of the 15,721 Providence and Boston CPP
offspring who lived beyond 7 years of age. Of the 3,121
questionnaires that were returned (68.2%), 2,271 were eligi-
ble for participation based on the combined inclusion criteria
of the three component studies. Those who enrolled had a
somewhat higher level of education (e.g., 64.1% with at least
some college education) than participants who were eligible
but not enrolled (e.g., 51.8% with at least some college
education). Data from 49 of the individuals were excluded
from the fi nal sample either because of their participation in
a pilot version of the survey (n = 4) or because of problems
with the interview administration (n = 45). This resulted in
1,625 completed adult assessments (Gilman et al., 2008a,
2008b). As part of the study design, siblings were over-
sampled. The fi nal sample included these 1,625 offspring
of 1,254 mothers; analyses were conducted to account for
these sibling sets.
Between 2001 and 2004, the New England Family Study
visit, women reported whether they were currently smoking
and, if so, the number of cigarettes they smoked per day.
These questions were repeated at each subsequent prena-
tal visit up until the time of delivery. From these repeated
measurements, we determined the maximum number of
cigarettes smoked per day at any point during pregnancy.
Women were then classifi ed into three levels of smoking:
never smoked during any pregnancy day (coded 0), smoked
fewer than 20 cigarettes during any pregnancy day (coded
1), and smoked 20 cigarettes or more during any pregnancy
day (coded 2). This categorical smoking variable was used
in this article.
Birth weight. Birth weight was recorded in grams by a
nurse observer at the time of delivery.
Neurological abnormality at age 1. A trained pediatrician
or pediatric neurologist performed a neurological evaluation
of the child and screened for a variety of potential develop-
mental abnormalities when the child was approximately 1
year old (50-56 weeks). There were 116 items that were used
to characterize the child’s neurological status. Neurological
abnormality at age 1 was defi ned as the number of abnor-
malities coded either abnormal or suspect.
Academic functioning at age 7. The Wide Range Achieve-
ment Test measured learning (dis)abilities (i.e., reading,
arithmetic, and spelling; Jastak and Jastak, 1965). We used
the standardized scores for this analysis. The mean (SD)
scores for the three areas were the following: reading, 104.75
Maternal smoking during pregnancy. At the fi rst prenatal
NOMURA, GILMAN, AND BUKA 209
Shiono, P. H., & Behrman, R. (1995). Low birth weight: Analysis and rec-
ommendations. Future Child, 5, 35-51.
Substance Abuse and Mental Health Services Administration (Offi ce of
Applied Studies). (2005). Results from the 2004 National Survey on
Drug Use and Health: National fi ndings (NSDUH Series H-28, DHHS
Publication No. SMA 05-4062) Rockville, MD: Author.
Tremblay, R., Nagin, D., Séguin, J., Zoccolillo, M., Zelazo, P., Boivin, M.,
. . . Japel, C. (2004). Physical aggression during early childhood: Tra-
jectories and predictors. Pediatrics, 114, e43-e50.
Tucker, L. R., & Lewis, C. (1973). A reliability coeffi cient for maximum
likelihood factor analysis. Psychometrika, 38, 1-10.
Van Horn, M. L., Jaki, T., Masyn, K., Ramey, S. L., Smith, J. A., & An-
taramian, S. (2009). Assessing differential effects: Applying regres-
sion mixture models to identify variations in the infl uence of family
resources on academic achievement. Developmental Psychology, 45,
Visscher, W., Feder, M., Burns, A., Brady, T., & Bray, R. (2003). The impact
of smoking and other substance use by urban women on the birthweight
of their infants. Substance Use and Misuse, 38, 1063-1098.
Vuijk, P., van Lier, P. A., Huizink, A. C., Verhulst, F. C., & Crijnen, A. A.
(2006). Prenatal smoking predicts non-responsiveness to an intervention
targeting attention-defi cit/hyperactivity symptoms in elementary school
children. Journal of Child Psychology and Psychiatry, 47, 891-901.
Wakschlag, L., Lahey, B., Loeber, R., Green, S., Gordon, R., & Leventhal,
B. (1997). Maternal smoking during pregnancy and the risk of conduct
disorder in boys. Archives of General Psychiatry, 54, 579-580.
Wakschlag, L., Pickett, K., Middlecamp, M., Walton, L., Tenzer, P., &
Leventhal, B. (2003). Pregnant smokers who quit, pregnant smokers
who don’t: Does history of problem behavior make a difference? Social
Science & Medicine, 56, 2449-2460.
Wall, T. L., Schoedel, K., Ring, H. Z., Luczak, S. E., Katsuyoshi, D. M., &
Tyndale, R. F. (2007) Differences in pharmacogenetics of nicotine and
alcohol metabolism: Review and recommendations for future research.
Nicotine and Tobacco Research, 9 (Suppl. 3), S459-S474.
Weese-Mayer, D., Ackerman, M., Marazita, M., & Berry-Kravis, E. (2007).
Sudden Infant Death Syndrome: Review of implicated genetic factors.
American Journal of Medical Genetics, 143, 771-788.
Weissman, M. M., Warner, V ., Wickramaratne, P. J., & Kandel, D. B. (1999).
Maternal smoking during pregnancy and psychopathology in offspring
followed to adulthood. Journal of the American Academy of Child &
Adolescent Psychiatry, 38, 892-899.
Weitzman, M., Gortmaker, S., & Sobol, A. (1992). Maternal smoking and
behavior problems of children. Pediatrics, 90, 342-349.
World Health Organization. (1993). The ICD-10 classifi cation of mental and
behavioural disorders. Geneva, Switzerland: Author.
World Health Organization, (1997) Composite International Diagnostic
Interview, Version 2.1. Geneva, Switzerland: Author.
Williams, R. (1995). Product-limit survival functions with correlated sur-
vival times. Lifetime Data Analysis, 1, 171-186.
Windle, M. (1997). The trading of sex for money or drugs, sexually trans-
mitted diseases (STDs), and HIV-related risk behaviors among multi-
substance using alcoholic inpatients. Drug and Alcohol Dependence,