Epigenetics of the Developing Brain: How Early Experiences Shape Gene Expression

Epigenetics of the Developing Brain
Frances A. Cham pagne
Columbia University
ABSTRACT
Advances in understanding of the dynamic molecular interplay
between DNA and its
surrounding proteins suggest that epigenetic mechanisms are a
critical link between early
life experiences (e.g., prenatal stress, parent-offspring
interactions) and long-term changes
in brain and behavior. Although much of this evidence comes
from animal studies, there
is increasing converging evidence of these epigenetic processes
in humans. These new
insights into epigenetic pathways highlight the integration of
nature and nurture during
development and the potential for heritable changes that persist
across generations.
E
arly experiences create the foundations of individual
differences and how each person interacts with the world.
Though debate about the relative contributions of nature
versus nurture to personality, behavior, and risk of disease has
dominated discussions within psychology, biology, and
neurosci-
ence, the science is now poised to move beyond this dichotomy.
Advances in molecular biology have provided insights into both
nature and nurture and suggest that development is a process

involving complex interactions between these two inseparable
factors. This newfound understanding of gene-environment
interplay has significant implications for conceptualizations
o f the developing brain. Even before birth, brains are chang-
ing and refining in response to experiences. At first, these are
shared experiences between the mother and fetus, and there is a
growing sense that what a mother eats, drinks, or breathes and
certainly how she feels during pregnancy can affect the fetus.
This sensitivity to the environment continues from birth into
childhood and beyond. Both the sensory and the social world
around a developing child can have a lasting impact on the
brain. The question raised by this phenomenon of developmen-
tal and neural plasticity is regarding mechanism: How does this
dynamic process take place? Answering this question unites
both
the classic notions of nature versus nurture with the new and
emerging science of epigenetics.
From Genetics to Epigenetics
Each human’s genetic make-up is predictive of both physical
and psychological characteristics, and the current ability to
sequence genomes and provide individuals with a detailed
description o f their DNA is truly astounding. In experimental
studies in animals, manipulating DNA, even a single gene, can
have profound consequences. However, exclusive focus on
genetic
make-up as an account of an individual’s identity has always
been at odds with the sense that environments, particularly
those
experienced during childhood, shape development. Moreover,
decades o f research has confirmed that “nurture” in the very
broad
sense, consisting of sensory, social, nutritional, and
toxicological
experiences, has a profound effect on brain function and

behavior.
This uncomfortable dichotomy between the role o f DNA and
the role of the environment as developmental influences may be
resolved by taking a closer look at DNA.
Within the DNA sequence is encoded the instructions for
creating the building blocks of human anatomy, hence often
earning the description “the book of life” However, like all
books,
the biological book of life must be read for the knowledge
within to be realized. This reading is an active process
involving
the collective efforts of numerous proteins and enzymes that
either interact directly with DNA or with the proteins around
which DNA is wrapped (Peterson & Laniel, 2004; Razin, 1998).
The dilemma of biology is in the compact storage of sufficient
DNA to encode all the information needed to create a complex
organism; which in the case of humans involves over 20,000
protein-encoding genes and more than 3 billion nucleotide base
pairs (adenine, thymine, cytosine, guanine). This is ultimately
a space issue. In order to fit this much biological material into
each cell, a compact structure is imposed on DNA consisting
of a network of histone proteins (see Figure 1). Much like the
towering apartment complexes in Manhattan that permit a
population density of 70,000 people per square mile, these
histones interact directly with the DNA and allow for the dense
packaging observed in the nucleus of cells (Peterson & Laniel,
2004; Razin, 1998). However, solving this space issue creates a
2 Zero to Three • Ja nuary 2015
FIGURE 1 Schematic Illustration of Epigenetic Mechanisms
DNA is wrapped around clusters of histone proteins to promote

compact storage of the genome. (A) The DNA can become
methylated, by addition of a methyl chemical directly to the
DNA
sequence. This epigenetic modification typically reduces gene
activity. (B)The histones can also be chemically modified, with
consequences for gene activity.
Collectively, these epigenetic marks influence the accessibility
of
DNA to transcription.
second problem. The readability of DNA is entirely dependent
on the accessibility of DNA. When DNA is compactly stored
it is not readable; much like a book located far from reach or
obscured by an adjacent bookshelf. Thus, gene activation, the
transcription of DNA, involves significant rearrangements in
the
architecture of DNA and its surrounding histone proteins (see
Figure 1). Once DNA is unwrapped from histones and
associated
chemicals and proteins, the reading can commence and a chain
o f events is initiated that can lead to biological changes in the
organism. The chemicals and proteins that control gene activity
without altering the DNA sequence are collectively referred to
as
epigenetic. These factors can promote both gene expression and
gene silencing, with both of these processes being essential for
normal development (Taylor & Jones, 1985).
Epigenetic factors create a secondary layer of information
within
the genome. The elegant DNA sequence provides the
instructions
of “what” to make, while epigenetics instructs as to the “when”
and “how much.” Both layers of information are needed for
normal development to proceed. Epigenetics also accounts for

the
diversity of cells that emerge in an organism. Within an
individual,
each cell has a specific role to play, and there are multiple cell
types (e.g., muscle, blood, neurons) that have distinct physical
and functional characteristics. However, each of these cells has
the same DNA sequence. The unique characteristics of cells are
generated from their unique epigenetic patterns (Taylor &
Jones,
1985). Thus, in neurons, genes that are needed in muscle cells
may be epigenetically silenced and genes that promote neuronal
function are epigenetically active. It is important to note that
these
epigenetic patterns can be highly stable. Cells must “remember”
and maintain their characteristics over the lifespan.
Understanding of the importance o f epigenetics in controlling
the activity of genes emerged in the 1980s, and these molecular
mechanisms have been studied extensively within certain
disease states, particularly cancer (Jones & Laird, 1999). The
new
perspective that has emerged in the past decade is regarding
the role of these mechanisms in gene-environment interplay.
Epigenetic factors, particularly chemical modifications directly
to the DNA itself, were initially thought to be resistant to
change beyond early embryogenesis. However, in the past 10
years, evidence has emerged supporting the malleability of
epigenetic variation in response to a diverse range of
experiences
occurring across the lifespan. These experiences include classic
biological exposures, such as food, toxins, and hormones as
well
as the quality of the socio-emotional environment, conveyed
primarily through parent-infant interactions (Champagne,
2010). Environmentally induced epigenetic variation may be a

common mechanism for all aspects of environmental experience
to shape and control the genome. The implications of this
perspective are profound. While DNA sequence is the result of a
slow and methodical evolution, the capacity of the environment
to create epigenetic variation suggests that dynamic functional
consequences for the genome can arise during development and
dramatically alter the characteristics o f an individual.
Moreover,
this epigenetic plasticity may be particularly evident in
response
to experiences occurring during sensitive periods (i.e., prenatal
through to childhood).
Prenatal Programming
During fetal development, the rapid pace of biological change
creates a window of vulnerability to developmental disruption.
Prenatal exposure to famine is associated with increased met-
abolic dysfunction, neurodevelopmental disorder, and schizo-
phrenia in adulthood (Susser, Hoek, & Brown, 1998). Mothers
exposed to stress during pregnancy are more likely to
experience
birth complications and pre-term birth (Coussons-Read et al.,
2012). Stress programming is also observed—where the stress
response of offspring is heightened when the mother is prena-
tally stressed (Glover, O’Connor, & O’Donnell, 2010). These
correlational findings are complemented by studies examining
The current ability to sequence genomes and provide
individuals with a detailed description of their DNA is truly
astounding.
Zero to Three • January 2015 3
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Prenatal exposure may directly im pact fetal tissues
through physiological changes in the m other during
pregnancy.
childhood outcomes following in vitro fertilization where the
fetus is genetically related or unrelated to the mother. This
study
design suggests that there are unique developmental outcomes

associated with genetic risk and the environmental risk
conferred
by maternal prenatal distress. For example, reduced birth
weight,
reduced gestational length, and antisocial behavior emerge as
out-
comes of prenatal stress even when there is no genetic
relatedness
between mother and child (Rice et al., 2009).
An increasing appreciation of the plasticity of epigenetic factors
in
response to the environment has led to a particular focus on
these
mechanisms in the context of prenatal adversity. In longitudinal
studies of the impact of famine, individuals exposed during the
earliest stages of fetal development carry a lasting epigenetic
signature. In particular, there is altered DNA methylation—an
epigenetic modification directly to DNA that is associated with
gene silencing (see Figure 1)—in genes controlling growth and
metabolism among individuals exposed in utero to famine
(Heijmans et al., 2008). Although famine involves nutritional
restriction, this exposure is also a significant physiological and
emotional stressor, and there is increasing evidence of
epigenetic
outcomes as a consequence of prenatal stress. In a recent study,
more than 900 genes were found to be altered in their DNA
methylation levels in children born to prenatally stressed
mothers, with many of these genes being involved in immune
function (Cao-Lei et al., 2014). One gene that has emerged in
many studies of prenatal stress and distress encodes for the
glucocorticoid receptor (Nr3cl)—a protein that plays a role in
the stress response system. Epigenetic variation that reduces the
activity of the glucocorticoid receptor gene can render
individuals
hypersensitive to stressors and puts them at risk of numerous

neurodevelopmental and physical disorders (Champagne, 2013).
Maternal depression and anxiety during pregnancy and exposure
to stress are associated with epigenetic suppression of Nr3cl in
infants and children with some indication that these epigenetic
shifts are programming the stress response of affected infants
(Hompes et al., 2013; Oberlander et al., 2008).
Human studies of prenatal programming are compelling but
are necessarily correlational. However, experiments in animals
have been used to establish “cause and effect” to examine
the impact of prenatal adversity on the brain, and provide
support for an epigenetic hypothesis. In mice, offspring of
prenatally stressed mothers manifest behavioral, physiological,
and neurobiological changes consistent with heightened
stress reactivity and anxiety. Within the hippocampus, a brain
structure implicated in both the neuroendocrine response to
stress and with learning and memory, this early life stress
results
in decreased expression of glucocorticoid receptors (reduced
gene activity) and elevations in DNA methylation within the
Nr3cl gene (Mueller & Bale, 2008). The observation that these
epigenetic changes associated with prenatal experiences are
sustained into adulthood speaks to the enduring nature of
these biological mechanisms. This sustained molecular impact
is likewise observed following prenatal exposure to dietary
manipulations and exposure to toxins (Champagne, 2010).
A critical question that remains is how these epigenetic marks
are triggered. What is it about these prenatal experiences that
are capable o f inducing an epigenetic change? There are at
least
three possible routes to consider, which may work in combi-
nation to achieve these effects (Monk, Spicer, & Champagne,
2012). First, the prenatal exposure may directly impact fetal
tissues through physiological changes in the mother during
pregnancy. In the case of prenatal stress, it is hypothesized that

the stress the mother experiences increases her release of stress
hormones (glucocorticoids) and these hormones either directly
or indirectly (i.e., through other physiological pathways like the
immune system) act at a molecular level to alter epigenetic pat-
terns within the genome. This explanation certainly makes intu-
itive sense and there are studies that (a) confirm that increases
in maternal glucocorticoids are associated with increases in the
levels of these hormones in amniotic fluids, (b) illustrate the
epigenetic variation induced by glucocorticoids, and (c) illus-
trate that maternal glucocorticoid levels are predictive of stress
responses in offspring. A second pathway involves prenatal epi-
genetic disruption to the placenta. The placenta is the interface
between the mother and fetus during pregnancy and is essential
to growth and development during this period. Epigenetic dis-
ruption in the placenta is associated with birth complications
and neurodevelopmental problems, and maternal exposure
to stress, nutritional variation, and toxins is associated with
altered DNA methylation levels in the placenta. Finally, the
impact o f prenatal environmental conditions may be achieved
through alterations in the quality of postnatal mother-infant
interactions. For example, stress can trigger depressed mood
and reduce the amount of positive affect and physical contact
that mothers engage in with the newborn (Monk et al., 2012).
Disruptions to the mother-infant relationship as a consequence
of prenatal stress have been observed in both humans and
animals and may set the stage for long-term developmental
disruption in infants. The quality of this relationship can also
moderate the impact o f prenatal stress. For example, although
high maternal glucocorticoid levels during pregnancy can
predict deficits in cognitive ability among infants, this effect
4 Zero to Three • January 2015
is attenuated when there is a secure m other-infant attachment

(Bergman, Sarkar, Glover, & O’Connor, 2010).
Mothering the Newborn Brain
The newborn brain is a biologically sensitive structure that is
rapidly changing and refining in response to the sights, sounds,
and feelings o f the surrounding world. In mammals, this
world is dominated by interactions with parents, particularly
mothers. Although it is generally accepted that the quality of
the m other-infant relationship can exert a profound influence
on development, much of the direct evidence confirming
this influence comes from animal studies. Classic studies in
monkeys conducted by Harry Harlow in the 1950s and 1960s
demonstrated that infants deprived of maternal contact during
infancy had a heightened reactivity to stress and were impaired
in
social behavior in later life (Harlow, Dodsworth, 8t Harlow,
1965).
More recent applications of this experimental design indicated
that these long-term effects are associated with neurobiological
and molecular changes, including decreased brain serotonin
neurotransmitter receptors and enlargement in the volume of
stress-sensitive brain regions (Spinelli et ah, 2010; Spinelli et
al.,
2009). These detrimental effects of parental deprivation are
similarly observed in humans, such as when infants are reared
in
orphanages and have limited physical or social interactions with
caregivers. This form of institutional rearing leads to social and
emotional problems in childhood and adolescence, cognitive
impairment, decreased total brain volume, and increases in the
volume o f the amygdala (Hostinar, Stellern, Schaefer, Carlson,
&
Gunnar, 2012; O’Connor, Rutter, Beckett, Keaveney, &
Kreppner,
2000; Tottenham et ah, 2010). The amygdala is involved in the
processing of fearful stimuli, and enlargement in the size of the

amygdala likely contributes to the increased activation of this
brain region in response to threat cues that has been observed
in institutional-reared children. The serotonin system, which is
altered in response to maternal deprivation in primates, may
also
moderate the effects o f maternal deprivation in humans. Among
adolescents with a genetic variant of the serotonin transporter,
there is a heightened level o f emotional impairment observed
following institutional rearing, particularly amongst those
individuals who experience subsequent stressful life
experiences
(Kumsta et al., 2010). These gene-environment interactions play
a critical role in the development of psychiatric outcomes in
response to early life adversity.
Laboratory rodents can also be used to illustrate the effect of
maternal deprivation, prolonged separation, and disruption
to the quality of mother-infant interactions. These models
confirm and expand on what has been learned from humans
and non-human primates. Heightened neuroendocrine response
to stress, disruptions to the serotonin system, and alterations in
brain architecture are all hallmarks of the experience during
neonatal development o f reduced maternal care (Curley,
Jensen,
Mashoodh, & Champagne, 2011). However, one does not have
to invoke these extreme forms of early life experience to
observe
neurobiological and behavioral consequences. In all species,
there
are naturally occurring variations in parental care. In humans,
The impact of prenatal environmental conditions may be
achieved through alterations in the quality of postnatal
mother-infant interactions.
variation exists in how sensitive and responsive mothers are

to infant cues o f distress (Hane 8c Fox, 2006). In non-human
primates, mothers differ in the frequency with which they hold
infants (Fairbanks 8c McGuire, 1988). Even in laboratory
rodents,
mothers display significant variation in the frequency with
which they provide physical contact to offspring. A particular
form of contact that is characteristic of maternal rodents is pup
licking and grooming. This behavior serves, as the name
implies,
to groom and clean the pups and is also a source of sensory
experience that shapes the developing brain. Offspring that
receive more of this form o f maternal care during the first week
of life are less stress sensitive and perform better on cognitive
tasks, and these functional consequences are associated with
morphological and molecular changes in the brain that can be
observed into adulthood (Meaney, 2001). It is the lasting nature
of these changes that suggested the possible involvement of
epigenetic variation.
The early assumption that epigenetic variation could be
induced only during embryogenesis hindered the application
of epigenetic analyses to studies o f postnatal environmental
influence. However, there is now strong support for the
involvement of epigenetic pathways in explaining the long-term
impact of maternal care. In rodents, high levels of maternal care
lead to decreased DNA methylation within the Nr3cl gene
during infancy and, due to the lasting nature of this chemical
mark, reduced Nr3cl DNA methylation is sustained in these
offspring across the lifespan (Weaver et al., 2004). Consequent
to these epigenetic changes, offspring that receive high levels
of maternal care during infancy have increased levels of
glucocorticoid receptors in the hippocampus and are better able
to reduce their physiological and behavioral response to stress.
Cross-fostering studies, where offspring are transferred from a
high or low maternal care biological mother to a high or low
maternal care rearing environment confirm that these

epigenetic,
neuroendocrine, and behavioral effects of maternal care are
attributed to the experiences offspring have during development
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The newborn brain is a biologically sensitive structure that
is rapidly changing and refining in response to the sights,
sounds, and feelings of the surrounding world.
(Weaver et al., 2004). Moreover, these epigenetic changes are
reversible in adulthood using pharmacological treatments that
target DNA methylation (Weaver et al., 2004; Weaver et al.,
2005).
Because the experience o f high versus low levels of maternal
L e a r n M o r e
Psychobiology, Epigenetics, and Neuroscience Lab
http ://ch a m p a g n e la b .p sych .co lu m b ia .e d u
This website provides links to ongoing research publications
focused on basic and translational research on the
biological impact of early life experiences.
Columbia Center for Children's Environmental Health
h ttp ://c c c e h .o rg
This website provides information for researchers, health
professionals, communities, and families on the impact of
environmental exposures during development.

Brain Facts
w w w .b ra in fa c ts .o rg
The Brain Facts website is a public information initiative
developed by global nonprofit organizations working to
advance brain research.This site includes descriptions of
researchers' current understanding of brain development
and epigenetics.
Ghost in Your Genes
w w w .p b s .o rg /w g b h /n o v a /g e n e s /
NOVA documentary describing key findings that have
contributed to researchers' understanding of the role of
epigenetics in gene-environment interplay.
Evolution in Four Dimensions: Genetic, Epigenetic,
Behavioral, and Symbolic Variation in the History of Life
E. Jablonka and M. J. Lamb (2005). Cambridge, MA: MIT
Press
Nature Via Nurture: Genes, Experience, and What Makes Us
Human
M. Ridley (2003). NewYork, NY: Harper.
care lead to changes in the transcription of hundreds of genes
within the brain, it is likely that early rearing experiences lead
to
significant shifts in the epigenetic profile of the entire
genome—
the epigenome.
Evidence for the involvement of epigenetic pathways in the

effects
of naturally occurring variations in maternal care in rodents
has been complemented by many subsequent studies exploring
these mechanisms in response to disruptions to mother-infant
interactions. Prolonged periods of maternal separation in
rodents induces epigenetic variation in the brain of offspring,
particularly in genes in involved in the stress response, such as
vasopressin, corticotrophin releasing factor receptor (Crfr2),
and Nr3cl (Franklin et al., 2010; Kundakovic, Lim, Gudsnuk,
& Champagne, 2013; Murgatroyd et al., 2009). Rodents can
also engage in abusive caregiving behavior, and the experience
of these interactions during postnatal development can lead to
epigenetic changes within the brain-derived neurotrophic factor
(Bdnf) gene (Roth, Lubin, Funk, & Sweatt, 2009). Epigenetic
silencing o f Bdnf can impair neural plasticity and may lead to
an
increased risk of mood disorder in adulthood. In primates that
are deprived of maternal care, epigenetic disruption is observed
in both the brain and the blood, suggesting that the blood may
carry an epigenetic signature of this early life adversity
(Provencal
et al., 2012). The translation of animal studies to humans is
highly dependent on researchers’ ability to measure experience-
dependent epigenetic changes in the blood, saliva, or buccal
cells.
In humans, postmortem brain analyses suggest that increased
Nr3cl DNA methylation is observed in individuals with a
history
o f childhood abuse (McGowan et al., 2009) and this epigenetic
shift can similarly be observed in the blood (Perroud et al.,
2014).
However, it is important to note that genome-wide epigenetic
shifts are likely occurring in response to disruption to the
quality
of the early life social environment, and it is unclear what the
brain-blood relationship will be for all genes.

From One Generation to the Next
The lasting epigenetic impact o f mother-infant interactions that
occur prenatally or postnatally may account for the emergence
of neurobiological and behavioral disruption that has been
observed consequent to early life adversity. A question that has
emerged is whether these changes could persist to subsequent
generations. It is well-established in both humans and animals
that patterns o f maternal care can be transmitted from mother
to daughter and from fathers to sons (in species where males
participate in caregiving). In rodents, the experience of high
levels of maternal care by female offspring leads to shifts in the
developing neuroendocrine circuits that regulated maternal
care itself. Consequently, if a rat pup has received high levels
of
maternal care, it will bestow high levels of maternal care toward
its own offspring. This transmission of maternal behavior is
associated with epigenetic changes within the gene encoding
the estrogen receptor (Esrl; Champagne, 2008). High maternal
care leads to decreased DNA methylation and other changes to
the histones surrounding the Esrl gene. These effects emerge
during postnatal development and persist into adulthood (Pena,
6 Zero to Time * January 2015
Neugut, & Champagne, 2013). A similar epigenetic transmission
is observed following the experience of abusive caregiving. Rat
pups that have experienced abuse are more likely to engage
in abusive caregiving themselves, and this shift in behavior is
accompanied by epigenetic changes in the Bdnf gene (Roth
et al., 2009). These examples provide support for the role of
epigenetic mechanisms in the experience-dependent
transmission
of variation in behavior across generations that may account for

the transgenerational impact of abuse, attachment security, and
parental care in humans.
Classic views o f inheritance focus on the transmission of
genetic
information—variation in DNA. Thus, increasing evidence of a
behavioral transmission o f epigenetic variation via parental
care
is typically viewed as an example o f developmental plasticity
rather than o f inheritance. However, epigenetic variation
may also be inherited in a similar way to the inheritance of
DNA—through the germline. The sperm and oocyte are the
carriers of an individual’s genetic make-up to its descendants.
Although these cells can be damaged or the DNA mutated
following exposure to radiation or toxins, it has been assumed
that these cells otherwise do not carry a lifetime accumulation
o f “baggage” to the next generation. At the time of conception,
there is significant epigenetic reprogramming that occurs.
During this time, the epigenome is reset (Feng, Jacobsen, &
Reik, 2010). However, there is emerging evidence that this
biological “clean slate” retains some remnants from its
ancestors.
Parental exposure to toxins, dietary extremes, and stress can
leave
an epigenetic mark within the germline that is inherited by
offspring. For example, altered DNA methylation in the Crfr2
gene is observed in the sperm of male mice that experience
maternal separation during the postnatal period. This same
epigenetic mark is present in the brains of offspring of these
males (Franklin et al., 2010). The observation o f this
inheritance
through males is important mechanistically, because male mice
do not have any contact with offspring. Although researchers
still have much to learn about the mechanisms that account for
paternal epigenetic inheritance, this is certainly a phenomenon

that challenges current views on the origins o f an individual’s
unique characteristics.
Future D irections
Epigenetics is in its infancy and will certainly grow and develop
as the field moves forward. There are critical questions that
have
yet to be addressed regarding the process by which the qualities
of the environment become encoded into the epigenome and
the degree of stability versus plasticity that can be expected
from
this molecular partner to DNA. However, regardless of where
the
pursuit of these questions leads, epigenetics has created a new
way
of thinking. Rather than being constrained by the conventions of
nature versus nurture, questions of development and inheritance
can be addressed from a truly integrative perspective. The
developing brain is the product of this integration, responding
and changing in response to variation in DNA sequence,
inherited
molecular marks, and epigenetic variation that arises through
life
experience. It is important to note that experience can also be
viewed in an integrated way through the lens of epigenetics.
What
individuals eat, drink, breathe, and how they feel can impact
their
biology through the same mechanism. The social environments
to which individuals are exposed, and perhaps even those of
their
parents, can shift the readability of their DNA just as
profoundly
as exposure to drugs, toxins, and pollutants. The implications
for

policy and practice of the elucidation of these biological
pathways
may be significant, particularly when considering the potential
heritability of environmentally induced epigenetic change.
When
adults nurture the developing brain they are nurturing the DNA
of generations to come—a realization that conjures a growing
sense of responsibility and hope.
Frances A. Champagne, PhD, is c u rre n tly an a s s o c ia te p
ro fe s s o r in
th e D e p a rtm e n t o f P sych o lo g y a t C o lu m b ia U n
iv e rs ity . H er re se a rch and
te a c h in g fo c u s on th e n e u ro b io lo g ic a l a nd e p ig
e n e tic im p a c t o f e a rly
life e x p e rie n c e s a nd th e c ritic a l ro le o f m o th e rs
and fa th e r s in sh a p in g
d e v e lo p m e n ta l o u tco m e s.
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Discussion: Defining and Measuring Quality in Health Care
Organizations
Quality is never an accident. It is always the result of intelligent
effort.
—John Ruskin
Quality is multidimensional and involves the perspectives of
various stakeholders, including patients and families. As noted
in this week’s Learning Resources, defining quality is not a
simple, straightforward task. Yet, it provides an essential
foundation for being able to measure and assess quality, and,
ultimately, to improve it.
In this Discussion, you consider definitions and measurements
of quality. As you proceed, think about why it is important for
organizations to be able to quantify quality and compare current
performance to previous performance, to a set of standards,
and/or to performance in other organizations.
To prepare:
· Review the information in the Learning Resources, especially
the chapters in the Sadeghi, Brazi, Mikhail, and Shabot course
text, focusing on how quality is or could be defined and
measured.
· Think about a health care organization with which you are
familiar. It may be the same organization you are focusing on
for your Course Project, or a different one. How do you think
various stakeholders in this organization would define quality?
How would you define quality as it relates to this organization?
· Review the information on quality standards and / or aims in
the Learning Resources, and consider the following:
· Which outcomes related to quality are currently being
monitored in the organization that you have selected?

· How is related data collected and evaluated?
· Does the organization use health information technology in
this regard? If so, how?
· How is quality-related information (e.g., data, needs for
improvement) communicated throughout the organization?
· What do you consider to be the strengths and weaknesses of
the current approach to quality in this organization.
ORIGINAL ARTICLE
Maternal Alcohol Use during Pregnancy, Birth Weight and
Early Behavioral Outcomes
Jen-Hao Chen*
University of Chicago, 1155 East 60th Street, Chicago, IL
60637, USA
*Corresponding author: Tel: +1-773-834-7829; E-mail:
[email protected]
(Received 29 February 2012; first review notified 12 April
2012; in revised form 28 June 2012; accepted 11 July 2012)
Abstract — Aims: To examine the effect of maternal alcohol use
during pregnancy on infant behavioral outcomes and birth
weight,
and to investigate the differential susceptibility of infant
behavioral outcomes and birth weight to prenatal alcohol
exposure.
Methods: Data on children born to women taking part in the
United States National Longitudinal Survey of Youth (NLSY)
(n = 1618) were analyzed using the sibling fixed-effects model,
which helps adjust for maternal, genetic and social confounders
when examining effects of pre-natal exposure to possible toxins

such as alcohol. Mothers were classified as non-drinkers, light-
to-
moderate drinkers and heavy drinkers according to their
frequency of alcohol use during pregnancy. Infants’ behavioral
outcomes
were assessed using the modified Rothbart Infant Behavior
Questionnaire in the NLSY, which measures three dimensions
of behav-
ioral outcomes: positive mood, fearfulness and difficultness.
Results: Estimates from the model indicated that drinking
during preg-
nancy was positively associated with infant difficultness, but
not with positive mood or fearfulness. Further analysis by
frequency of
alcohol use suggested that both light-to-moderate and heavy
drinking were associated with an increase in infant
difficultness.
Additionally, while low-to-moderate drinking during pregnancy
was associated with infant difficultness, drinking at this level
was
not associated with low birth weight. Conclusion: The findings
suggest that maternal alcohol use during pregnancy is a risk
factor
for infant behavioral outcomes, after taking into account many
confounding factors. Infant behavioral outcomes appear to be
more
vulnerable to light-to-moderate levels of alcohol use during
pregnancy than birth weight is.
Drinking during pregnancy represents a major public health
problem and generates much public attention in many coun-
tries (O’Leary et al., 2007). In the USA, the Centers for
Disease Control and Prevention (CDC) showed that in 2005
approximately one in every eight pregnant women reported
that they had consumed alcohol during their pregnancy.
Furthermore, this high rate of alcohol use during pregnancy

has remained relatively unchanged in the USA since the
1990s (Centers for Disease Control and Prevention, 2009).
Accordingly, approximately half a million infants are
exposed prenatally to alcohol each year. Understanding the
consequences of prenatal alcohol exposure on children is not
only of academic interest, but is also important for those de-
termining policy.
Prenatal alcohol exposure has been associated with
various behavioral problems in children, including conduct
problems (D’Onofrio et al., 2007), attention problems
(Streissguth et al., 1984; Knopik et al., 2005) and criminal
and delinquent behaviors (Streissguth et al., 1999; Fast and
Conry, 2004). While these studies provide the best evidence,
more methodologically rigorous studies are definitely needed
in order to develop a comprehensive understanding of the
impact of prenatal alcohol exposure on children’s behavioral
development, particularly the developmental consequences
associated with low-to-moderate levels of alcohol exposure
(Jacobson and Jacobson, 1999; Huizink and Mulder, 2005).
Results from animal experiments show that light-to-moderate
alcohol consumption during pregnancy may cause mental
health and behavioral problems in offspring (Schneider et al.,
1997; Kraemer et al., 2007; Cuzon et al., 2008).
Additionally, experimental evidence further suggests that
prenatal alcohol use has a greater influence on the behavioral
outcomes of offspring than it does on infant birth weight. In
two randomized experiments on rhesus monkeys, Schneider
et al. (1997, 2001) found that moderate alcohol consumption
throughout pregnancy was associated with irritability, atten-
tion problems and poor neurological functioning in offspring,
in spite of the fact that the baby monkeys born during the
study showed no significant difference in birth weight
between the control and the experiment groups (Schneider
et al., 1997). Animal experiments thus suggest a ‘differential

susceptibility hypothesis,’ in which infant behavioral out-
comes are more vulnerable to prenatal alcohol exposure than
physical growth is.
Extant findings from observational studies of the conse-
quences of low-to-moderate levels of alcohol consumption
during pregnancy, however, remain somewhat contradictory.
Several studies found that low-to-moderate levels of alcohol
exposure were positively associated with children’s problem
behaviors (Streissguth, 1980, 1999; Olson et al., 1997; Sood
et al., 2001). In contrast, two recent analyses showed that
low-to-moderate drinking was not independently associated
with an increased risk of either attention deficit hyperactivity
disorder or behavioral problems in children (Knopik et al.,
2006; Kelly et al., 2009). The mixed results of these studies
may be due to the problem of identifying the causal effect of
prenatal alcohol exposure (Linnet et al., 2003; Testa et al.,
2003; Huizink and Mulder, 2005). In particular, many prior
evaluations did not adequately control for confounders, such
as family processes and maternal characteristics, which may
correlate with both child behavioral outcomes and maternal
alcohol use. The causal inference problem is further compli-
cated by study design and the type of data collected. Many
studies have relied on small, selective, clinical samples
where measures of family processes and parental characteris-
tics were often unavailable. Consequently, many prior
studies involve a risk of confounding resulting from simple
comparisons between children born to drinking mothers and
children born to non-drinking mothers without controlling
for unobserved differences between the subjects.
Quasi-experimental designs are useful alternatives to
account for potential confounders, including factors that are
not measured (Duncan et al., 2004; D’Onofrio et al., 2007).
For studies where randomized trials are not feasible,

Alcohol and Alcoholism Vol. 47, No. 6, pp. 649–656, 2012 doi:
10.1093/alcalc/ags089
Advance Access Publication 14 August 2012
© The Author 2012. Medical Council on Alcohol and Oxford
University Press. All rights reserved
quasi-experimental designs rely on natural experiments that
pull apart processes that are typically confounded and
provide better evidence for causal inference. One class of
quasi-experimental designs draws inferences from siblings or
children-of-twins comparisons (often referred to as a
fixed-effects model in the social science literature) and is
particularly useful for studies in human development. By
contrasting children exposed to prenatal alcohol with their
siblings or cousins who were exposed to less, this approach
controls for the mothers’ characteristics, including genetic li-
abilities that are shared by mothers and offspring. However,
only a few recent studies have adopted such a design in
examining the behavioral consequences of prenatal alcohol
consumption (for example, Knopik et al., 2006; D’Onofrio
et al., 2007; Knopik et al., 2009). Results from these studies
suggest that while many of the prior associations may be
spurious, maternal alcohol use during pregnancy may remain
a risk factor for certain behavioral problems. More import-
antly, these studies demonstrate the potential of the sibling
approach in studying the impact of low-to-moderate alcohol
use while pregnant. Furthermore, the differential susceptibil-
ity hypothesis suggested by the animal model has not been
adequately examined with observational data in humans.
According to this hypothesis, it would be expected that
low-to-moderate alcohol use would have a stronger negative
effect on child behavioral outcomes than on infant birth
weight. An empirical test of this hypothesis might also

inform theories about the neurological development and
physical growth of the fetus.
The present study was designed to address the methodo-
logical limitations and research gaps in the literature.
Specifically, this study investigated the association between
maternal drinking during pregnancy and infant behavioral
outcomes as related to the level of alcohol use. The study
employed a sibling fixed-effects model to account for unob-
served heterogeneity among the mothers of the children in
the sample. In addition, the study tested the differential sus-
ceptibility hypothesis with observational data. Finally, add-
itional analyses were performed to check the fixed-effects
identification assumption and to investigate whether the asso-
ciations between prenatal drinking and infant behavioral out-
comes, if any, were moderated by social status. Given that
the majority of women who drink while pregnant are consid-
ered light or moderate drinkers (Centers for Disease Control
and Prevention, 2009), the findings from this study have sig-
nificant implications for public health campaigns and pre-
natal problem prevention efforts that promote healthy
pregnancies and child well-being.
The focus on infant behavioral outcomes is further driven
by two reasons. First, studying infant outcomes provides add-
itional opportunities to identify the causal effects of prenatal
alcohol exposure. As children grow up, they are increasingly
subjected to the influence of environmental forces (Shonkoff
and Philips, 2000). Studies that focus on child outcomes that
investigate children at older ages may not be able to isolate
the effects of prenatal alcohol use from the child’s changing
environment. By examining behavioral outcomes during the
very first periods of life, the present study minimizes the in-
fluence of potential confounders from postpartum environ-
mental factors. Second, recent interdisciplinary evidence has
shown that early behavioral outcomes, which have often been

referred to as non-cognitive skills in economic and socio-
logical literature (e.g. Farkas, 2003; Cunha et al., 2010), are
strong predictors of later psychological well-being (Caspi
et al., 2003), problem behaviors (Caspi et al., 1995) and labor
market success (Caspi et al., 1998). At the same time, re-
search suggests that the investments made in interventions
later in life appear to be less efficient than earlier investments
(Carneiro and Heckman, 2003; Coneus et al., 2012). In order
to safeguard children’s development, policies should empha-
size early intervention, and, if possible, beginning during
pregnancy (Doyle et al., 2009). Inferences about the relation-
ship between alcohol use while pregnant and the behavioral
development of offspring in early life may thus shed light on
the origins of social inequality and future policy solutions for
reducing social inequality.
METHODS
Sample
The current study investigated children born to women who
participated in the National Longitudinal Survey of Youth
(NLSY). The NLSY is a nationally representative sample of
12,686 participants, who were between 14 and 21-year-old at
the start of the survey in 1979. Since 1986, the NLSY has
biennially interviewed and gathered information on the chil-
dren of the women in the original NLSY sample. However,
the NLSY stopped collecting information on infant behavior-
al outcomes for children born after 2000. The following stat-
istical analyses were thus restricted to children born between
1986 and 2000. The NLSY data include extensive informa-
tion on maternal behaviors during pregnancy for every birth
since 1986. Moreover, further data on the mothers can be
obtained from the NLSY master files and linked to the corre-
sponding child records on a year-by-year basis.

In the NLSY data, there were ~6700 children born to the
participating women between 1986 and 2000. The final ana-
lytical sample included only children aged 23 months to 4
years who had at least one sibling born between 1986 and
2000, thereby eliminating very young infants, whose beha-
viors are more difficult to assess (Rothbart, 1981; Shonkoff
and Philips, 2000). This left 2132 children. Cases with
missing values for infant behavioral outcomes and prenatal
alcohol use (n = 371) and time-varying covariates were
excluded (n = 143), producing a sample of 1618 children.
Most of the sibling groups in the sample included only two
children; however, sibling groups that included three or four
children were not uncommon. The maximum number of chil-
dren in a sibling group was five.
Outcome measures
The measures of the infant behavioral outcomes were
derived from the NLSY child temperament instruments,
which were a modified version of the Rothbart Infant
Behavior Questionnaire (Center for Human Resources
Research, 2006). Children of different ages received different
sets of temperament items. The present study used 11 items
administered to all of the children under 23 months to con-
struct infant behavioral scales. In addition to these common
items, six other items were administered to children under
650 Chen
11 months. These items were excluded from the scale con-
struction, because they focused more on measuring very
young children’s activity levels and behavioral routines (i.e.
sleepy and hungry at the same time), which are not the

primary interest of this study and were administered only to
part of the age range of the children in the sample.
For each of the 11 items, the mothers rated their infant’s
behavior using a 5-point scale, where a higher value indi-
cated a higher frequency of occurrence (i.e. 1, almost never,
2, less than ½ the time, 3, about ½ of the time, and so on).
To construct the infant behavioral scales, this study followed
the procedures described in previous studies and the guide-
lines from the NLSY User’s Guide (Center for Human
Resources Research, 2006; Lahey et al., 2008), which recom-
mend that researchers differentiate three dimensions of infant
behavioral outcomes: (a) positive mood (i.e. the child’s fre-
quency of smiling or laughter in any situation); (b) fearful-
ness (i.e. the child’s level of distress for novel people and
situations) and (c) difficultness (i.e. the child’s level of fussi-
ness and ability to be comforted). A total score was obtained
by summing across all the items in each dimension. These
totals were then standardized to facilitate interpretation and
comparison across different behavioral ratings.
Maternal drinking during pregnancy
The NLSY asked every woman to report her drinking behav-
ior during each pregnancy between 1986 and 2000 retro-
spectively. The mothers were first asked whether they had
consumed any alcohol in the 12 months before the birth of
the child. Next, if the answer was ‘yes,’ they were asked to
report the frequency of alcohol consumption during the preg-
nancy: never (33.8%), less than once a month (32.0%),
about once a month (17.3%), 3 or 4 days a month (7.8%), 1
or 2 days a week (6.6%), 3 or 4 days a week (1.5%), nearly
every day (0.7%) and every day (<0.1%).
This information was coded in two ways. First, this study
created a dummy variable to indicate whether a mother

drank any alcohol during each pregnancy. Second, the fre-
quency of prenatal drinking was separated into three levels:
no drinking, light-to-moderate drinking (defined as less than
3 or 4 days a month) and heavy drinking (defined as more
than 1 or 2 days a week). These two variables were the key
explanatory variables in the following statistical analyses.
Control variables
In contrast to studies relying on clinical samples involving
the local recruitment of subjects, the NLSY database
includes rich information on maternal characteristics, demo-
graphic variables and family socioeconomic status.
Time-invariant control variables include race and ethnicity,
maternal education and grandmother and grandfather’s edu-
cation. This study also controlled for several time-varying
variables that are known to be related to child outcomes, in-
cluding maternal characteristics, such as poverty, marital
status, age and the use of prenatal visits in the first trimester
of the pregnancy, as well as child characteristics, such as
gender, birth order and the child’s age at the time of assess-
ment. Finally, with the availability of extensive measures of
maternal cognitive and behavioral skills in the NLSY, this
study also included the mothers’ Armed Force Qualification
Test (AFQT) test scores, locus of control (from the Rotter
Locus of Control Scale), self-esteem (from the Rosenberg
Self-Esteem Scale) and self-rated sociability as covariates.
Statistical analyses
To estimate the relationship between maternal alcohol use
and infant behavioral outcomes, this study first evaluated the
data using ordinary least squares (OLS) regressions, and con-
trolled for a wide range of maternal characteristics, including
measures of maternal cognitive and behavioral skills.

Nonetheless, the incidence of women who participated in
drinking during pregnancy was not randomly distributed in
the population of pregnant women. The impact of maternal
alcohol use during pregnancy on an infant’s behavioral out-
comes could reflect characteristics not often measured in
surveys. Traditional OLS regression, however, cannot account
for such unobserved variable bias; a sibling fixed-effects
model is a better alternative to deal with this unobserved vari-
able bias. A sibling fixed-effects model compares siblings with
the ‘treatment’ of interest with siblings without the treatment
in the same family. This strategy allows anything that is shared
across births to be factored out. If, among otherwise similar
families, children who were exposed to prenatal drinking show
higher levels of behavioral problems than those with no expos-
ure to alcohol, a causal relationship between prenatal drinking
and behavioral outcomes is plausible. The rationale of sibling
fixed-effects can be expressed in the following equations:
Yij ¼ bDij þ
Xn
k¼1
gkXkij þ mj þ 1ij ð1Þ
ðYij � YijÞ ¼ bðDji � DijÞ
þ
Xn
k¼1
gkðXkij � XkijÞ þ ð1ij � 1ijÞ ð2Þ
Here, the subscript i refers to a child and subscript j refers to
the family (mother) of the child. Y is the outcome of interest.
D represents maternal drinking while pregnant. Xk is the vector
of n covariates, which serve as control variables. In addition, µ

refers to the family-level, time-invariant unobserved factors. If
these unobservable factors are simultaneously correlated with
infant behavioral outcomes and prenatal drinking, traditional
OLS estimates (as presented in the first equation) would yield
a biased estimate of β. The sibling fixed-effects estimator
removes bias from the time-invariant maternal and family com-
ponents of µ by subtracting the average for all siblings in a
given family from each child’s value (represented in the
second equation) and provides better estimates of the effects of
maternal alcohol use during pregnancy on infant behavioral
outcomes.
RESULTS
Descriptive statistics
Descriptive statistics are presented in Table 1. These statistics
are reported at the maternal and child levels, because each
mother in the sample had multiple children. Less than half of
Maternal alcohol use during pregnancy 651
the sample was non-drinking mothers, while mothers who
drank during all of their pregnancies and mothers who drank
during at least one pregnancy constituted 17% and 29% of
the sample, respectively. The mean age of the mothers in
1986 was 24.5 years, and, on average, each had two children.
Mothers who drank during their pregnancies were more
likely to be white and better educated, and they were less
likely to be poor. In contrast, mothers who did not drink at
all or who drank only during some of their pregnancies
tended to be African-American and Hispanic, with lower
levels of education. Furthermore, drinking mothers showed
higher levels of marital stability, but were more likely to

smoke while pregnant. Mothers who changed their drinking
behavior were less likely to live in a stable environment and
were more likely to have experienced short-term poverty, and
24% had a change in marital status between pregnancies.
The bottom half of Table 1 shows selected characteristics
of the children. Infant behavioral outcomes varied with ma-
ternal drinking behavior during pregnancy. Mothers who
drank while pregnant tended to have children with slightly
lower levels of positive mood and higher levels of difficult-
ness. Children born to non-drinking mothers showed higher
levels of fearfulness compared with children born to mothers
who drank while pregnant.
Effects of maternal alcohol use on infant behavioral
outcomes
Estimates of the effects of alcohol use on infant behaviors
are reported in Table 2. Table 2 shows the estimates of the
overall effects of maternal drinking during pregnancy, re-
gardless of the level of alcohol used. In the basic OLS
model (Model 1), drinking while pregnant was associated
with a lower level of positive mood of 0.25 standard devia-
tions (P < 0.001). Children whose mothers drank while preg-
nant scored 0.20 standard deviations higher (P < 0.001) on
the difficultness rating. Prenatal drinking appeared to have
no effect on children’s fearfulness. None of the maternal
demographic variables significantly correlated with any
infant behavioral outcomes examined. However, some mater-
nal cognitive and behavioral skills were strong predictors of
infant behavioral outcomes. For example, maternal self-
esteem had a significant positive effect on the children’s dif-
ficultness. An additional unit increase in the maternal self-
esteem rating was associated with an increase of 0.02

Table 1. Weighted descriptive statistics for samples of children
of the NLSY born between 1986 and 2000
Total sample
mean or %
By maternal alcohol use status across pregnancies
Drinkers
mean or %
Non-drinkers
mean or %
Change behavior
mean or %
Selected maternal characteristics
Demographic characteristics
Hispanic 6.0 2.0 8.4 7.1
African-American 11.3 7.8 11.8 10.1
Mother less than high school 7.3 6.5 8.5 7.4
Mother high school 38.9 34.3 38.0 44.6
Mother some college 20.4 19.8 18.0 22.2
Mother college 21.8 24.1 21.9 20.2
Mother more than college 11.6 15.3 13.7 5.7
Mother’s age at baseline (1986) 24.5 24.9 24.2 24.5
Number of children 2.4 2.3 2.4 2.4
Maternal cognitive and behavioral skills
Mother’s AFQT Score
(Percentile)
53.6 64.0 51.7 51.6
Mother’s self-esteem (10–40) 32.5 33.3 32.6 31.7

Mother’s Locus of Control (4–16) 8.6 8.1 8.7 8.7
Mother’s sociability (1–4) 2.9 3.1 2.8 2.9
Prenatal smoking
Smoking for all births 17.5 17.0 11.9 26.9
Non-smoking for all births 72.9 75.1 80.0 60.0
Change behavior 9.6 7.9 8.1 13.1
Marital status
No change of marital status 82.2 90.4 82.5 76.3
Get married 12.2 8.0 11.9 15.4
Divorced 5.6 1.6 5.6 8.3
Poverty status
Poor for all births 6.0 6.5 6.7 4.3
Non-poor for all births 81.4 89.2 80.5 77.8
Change poverty status 12.6 4.3 12.8 17.9
Child characteristics
Infant behavioral outcomes
Positive mooda 13.5 13.1 13.6 13.5
Fearfulnessb 10.6 10.3 10.9 10.4
Difficultnessc 5.8 6.1 5.8 5.7
First born 30.1 39.2 28.6 29.4
Sample size 1618 265 856 497
Sample size (fixed-effects) 725 124 389 212
aPositive mood score ranges from 3 to 15.
bFearfulness score ranges from 5 to 25.
cDifficultness score ranges from 3 to 15.
652 Chen

standard deviations (P < 0.001) in children’s positive mood
and with a decrease of 0.03 standard deviations (P < 0.001)
in child difficultness. The mother’s sociability was also nega-
tively correlated with fearfulness among children.
Model 2 in Table 2 employed the sibling fixed-effects
model. Compared with the estimates obtained from Model 1,
the negative effect on positive mood disappeared. This sug-
gests that the previously identified negative relationship
between prenatal drinking and children’s positive mood
might be spurious (i.e. the result of other unobserved vari-
ables). With respect to difficultness, the negative effect
remained sizable. The results showed that drinking while
pregnant is positively associated with an infant’s level of dif-
ficultness. Infants whose mothers drank while pregnant
scored 0.26 standard deviations higher (P < 0.001) on the dif-
ficultness rating compared with infants whose mothers did
not drink. In contrast, maternal alcohol use during pregnancy
appeared to have no effect on the positive mood or fearful-
ness of the infants.
Table 3 shows the sibling fixed-effects estimates by levels
of alcohol use. As Table 3 suggested, infants’ positive mood
and fearfulness were not affected by heavy drinking during
pregnancy. However, there were some interesting findings
regarding infant difficultness. Estimates suggested that the
negative effects of prenatal drinking on infant difficultness
were not limited to women who drank heavily during preg-
nancy. Although infants whose mothers drank heavily while
pregnant scored 0.36 standard deviations higher (P < 0.05)
on the difficultness rating than infants of non-drinkers,
light-to-moderate drinking also increased infants’ difficult-
ness ratings by 0.20 standard deviations (P < 0.01). Thus, it
appears that the adverse behavioral consequences of
light-to-moderate drinking are not trivial. In addition, the

estimates from Table 3 provided suggestive evidence that the
negative impact of prenatal drinking increased linearly with
the amount of alcohol consumed. Further explorative analysis
by using the original categories of frequency of alcohol use
found partial support for the hypothesis. However, the data
do not allow a closer examination of this linear relationship
among heavy drinkers, because the sample size in each
heavy drinking category was too small to render significant
results. Finally, the association between heavy drinking and
child fearfulness was sizable. Even though the association
was not statistically significant, the sizable effect suggested
that heavy drinking may be a risk factor for fearfulness as
well. More studies are definitely needed to investigate the re-
lationship between prenatal drinking and fearfulness.
To provide further evidence of the effect of alcohol and
infant difficultness and test the sensitivity of behavioral de-
velopment over physical growth as it relates to prenatal
drinking, the subsequent analysis expanded the previous
sibling fixed-effects model to include another important
outcome resulting from prenatal consumption of alcohol: low
birth weight. The fourth column of Table 3 shows these
results. The estimates showed no association between
light-to-moderate drinking and low birth weight, but mothers
who drank heavily during pregnancy had an increased
chance of 10% (P < 0.05) of giving birth to a child with a
low birth weight. Maternal smoking during pregnancy was
also associated with a higher chance of having a child with a
low birth weight. These findings are consistent with the con-
clusions of prior research: smoking is a strong risk factor for
Table 2. Effects of maternal alcohol use on infant behavioral
outcomes (n = 1618)a
Positive mood Fearfulness Difficultness

OLS
coefficient (SE)
Fixed-effects
coefficient (SE)
OLS
coefficient (SE)
Fixed-effects
coefficient (SE)
OLS
coefficient (SE)
Fixed-effects
coefficient (SE)
Prenatal behaviors and maternal demographic characteristics
Prenatal drinking −0.25*** (0.06) −0.07 (0.08) 0.02 (0.05) 0.10
(0.08) 0.20*** (0.05) 0.26*** (0.08)
Prenatal smoking 0.08 (0.08) 0.08 (0.14) 0.11 (0.08) 0.28*
(0.13) −0.01 (0.08) 0.16 (0.13)
In poverty status 0.00 (0.09) 0.10 (0.11) 0.07 (0.08) −0.10
(0.11) 0.11 (0.08) −0.03 (0.11)
Non-married during pregnancy
(married omitted)
0.02 (0.09) 0.05 (0.15) 0.01 (0.08) −0.01 (0.14) 0.03 (0.08) 0.14
(0.14)
Divorced/separated during
pregnancy
0.07 (0.10) 0.04 (0.14) −0.01 (0.09) 0.07 (0.14) −0.03 (0.09)
0.00 (0.14)

Mother years of education 0.00 (0.02) — 0.01 (0.01) — −0.01
(0.01) —
Grandmother years of education −0.00 (0.01) — 0.01 (0.01) —
−0.01 (0.01) —
Grandfather years of education 0.01 (0.01) — −0.00 (0.00) —
0.00 (0.03) —
Prenatal care in first trimester 0.04 (0.07) 0.05 (0.08) −0.01
(0.07) 0.01 (0.08) −0.01 (0.07) −0.03 (0.08)
First born −0.02 (0.06) −0.03 (0.07) −0.24*** (0.06) −0.15*
(0.07) −0.19** (0.06) −0.14* (0.07)
Male −0.00 (0.05) 0.04 (0.06) −0.10* (0.05) −0.09† (0.05)
0.09† (0.05) −0.01 (0.05)
Hispanic 0.03 (0.08) — 0.08 (0.08) — −0.04 (0.08) —
African-American 0.01 (0.08) — 0.28*** (0.08) — 0.32***
(0.08) —
Maternal cognitive and behavioral skills
Mother’s AFQT score (tenth
percentile)
−0.01 (0.01) — −0.03** (0.01) — −0.00 (0.01) —
Mother’s self-esteem 0.02*** (0.00) — −0.00 (0.01) —
−0.03*** (0.01) —
Mother’s locus of control 0.00 (0.01) — −0.02* (0.01) — −0.02
(0.01) —
Mother’s sociability 0.03 (0.04) — −0.11** (0.04) — −0.05
(0.04) —
aAll regressions also control for child age at the time of
assessment, maternal age and a series of dummy variables of
child’s year of birth. Coefficients of
these variables are not reported for brevity.

†P < 0.1; *P < 0.05; **P < 0.01; ***P < 0.001.
low birth weight. Heavy drinking seems to reduce children’s
birth weights as well, whereas low-to-moderate levels of
alcohol use appear to show no effect on birth weight.
Results from these tests, therefore, offer a more compre-
hensive picture of the impact of prenatal drinking on child
development. These results suggest that light-to-moderate
drinking may convey little harm to an infant in terms of
birth weight. By contrast, light-to-moderate drinking while
pregnant has a substantial negative impact on a child’s diffi-
cultness. These findings suggest that infant difficultness is
more susceptible to the influence of maternal alcohol con-
sumption during pregnancy. Results from Table 3 thus
provide partial support for the differential susceptibility hy-
pothesis that has been suggested in previous animal studies.
Finally, this study performed two additional sets of ana-
lyses in order to check the robustness of these findings. First,
this study estimated models that included interaction terms
for maternal alcohol use and gender, birth order, race and
maternal education. This was done in order to examine
whether the negative consequences of alcohol use on infant
difficultness differed by child and/or maternal characteristics.
The results are presented in Table 4. Interestingly, none of these
interaction terms was statistically significant. Therefore, there
was no strong evidence that the impact of prenatal drinking
on infant mental health differs across gender, birth order,
race or maternal education status. Second, this study exam-
ined whether the results were altered by the use of different
selection criteria in sampling. The sibling fixed-effects

model relies on the assumption that unobserved characteris-
tics are time invariant. Intuitively, however, it seems that the
longer the time between births, the more likely it is that this
assumption may fail. To deal with this issue, the new ana-
lysis excluded children who were born >60 months apart.
Results are presented in Table 5. Although the magnitudes
of the estimated coefficients did change slightly, the patterns
were quite similar to those in the previous analyses. Prenatal
drinking remained positively correlated with the infants’ dif-
ficultness, and the harmful effects of light-to-moderate
alcohol consumption remained sizable and statistically sig-
nificant. Thus, the results held, regardless of the potential
problems implicit in the assumptions of fixed-effects
modeling.
DISCUSSION
The present study provides additional evidence for the
impact of prenatal alcohol exposure on early developmental
outcomes using data from the NLSY. The results show a
negative effect of maternal alcohol use on infant difficult-
ness, even for light-to-moderate drinking. By contrast, there
is no significant association between prenatal alcohol expos-
ure and positive mood and fearfulness in children.
Furthermore, this study suggests that prenatal alcohol expos-
ure has a greater effect on infant difficultness than it does on
outcomes by
subgroup (n = 1618)a
Positive mood
coefficient (SE)
Fearfulness
coefficient (SE)

Difficultness
coefficient (SE)
Panel A: By gender
Male −0.08 (0.13) 0.10 (0.14) 0.31* (0.14)
Female −0.04 (0.11) 0.11 (0.10) 0.24* (0.10)
P (Male = female) 0.69 0.88 0.53
Panel B: By birth order
First-born −0.06 (0.14) 0.05 (0.15) 0.39** (0.15)
Non-first-born −0.07 (0.09) 0.12 (0.09) 0.23** (0.09)
P (first-born =
non-first-born)
0.92 0.55 0.16
Panel C: By race
Black 0.18 (0.17) 0.12 (0.16) 0.33* (0.16)
Hispanic −0.33 (0.18) 0.26 (0.17) 0.30† (0.17)
White −0.07 (0.11) 0.03 (0.10) 0.26* (0.10)
P (Black = white) 0.20 0.62 0.72
P (Hispanic =
white)
0.20 0.22 0.84
Panel D: By maternal education
Less than high
school
−0.12 (0.20) 0.08 (0.18) 0.39* (0.19)
High school or
more

−0.06 (0.09) 0.10 (0.08) 0.26** (0.08)
P (Less than high
school = high
school or more)
0.77 0.92 0.47
aAll results are reported using the specification including
sibling fixed-
effects, and, all pre-treatment covariates. Subgroup estimates
are obtained by
interacting the prenatal drinking effect with a full set of dummy
variables for
each subgroup. Standard errors are in parentheses.
†P < 0.1; *P < 0.05; **P < 0.01; ***P < 0.001.
outcomes and birth weight by levels of alcohol use using sibling
fixed-effects model (n = 1618)a
Positive mood
coefficient (SE)
Fearfulness
coefficient (SE)
Difficultness
coefficient (SE)
Low birth weightb
marginal effect (SE)
No drinking (omitted category) — — — —
Light-to-moderate drinking −0.09 (0.09) 0.08 (0.08) 0.20**

(0.06) −0.02 (0.02)
Heavy drinking 0.05 (0.18) 0.27 (0.16) 0.36* (0.18) 0.10*
(0.05)
Prenatal smoking 0.08 (0.14) 0.28* (0.13) 0.15 (0.14) 0.08*
(0.04)
In poverty status 0.10 (0.11) −0.10 (0.11) −0.03 (0.11) −0.04
(0.03)
Non-married during pregnancy (married omitted) 0.05 (0.15)
−0.02 (0.14) 0.13 (0.14) 0.01 (0.04)
Divorced/separated during pregnancy 0.03 (0.14) 0.06 (0.13)
−0.00 (0.14) −0.04 (0.04)
Prenatal care in first trimester 0.05 (0.08) 0.01 (0.08) 0.04
(0.08) 0.01 (0.02)
First born −0.03 (0.07) −0.16* (0.07) −0.14* (0.07) 0.01 (0.02)
Male 0.04 (0.06) −0.09† (0.05) 0.01 (0.05) −0.01 (0.02)
aAll regressions also control for child age at the time of
assessment, maternal age and a series of dummy variables of
child’s year of birth. Coefficients of
these variables are not reported for brevity.
bResults were estimated by using the linear probability model
(LPM) in the fixed-effects context. Results using fixed-effects
logistic regressions show similar
patterns. For ease of comparison and interpretations, I report
results from the linear probability model.
†P < 0.1; *P < 0.05; **P < 0.01; ***P < 0.001.
654 Chen
infant birth weight. Although occasional drinking during
pregnancy does not have an adverse effect on birth weight,
infrequent alcohol consumption produces a statistically sig-
nificant positive association with infant difficultness.

The present study has several limitations. First, by restrict-
ing the study subjects to children born between 1986 and
2000, the sample consists of infants born to relatively older
mothers. Women that have more education and come from
relatively higher socioeconomic strata tend to give birth at
older ages (Rindfuss and John, 1983). As a result, this sam-
pling strategy may provide a more conservative estimate of
the impact of maternal drinking during pregnancy than many
epidemiological surveys that sampled high-risk populations.
Second, results from the sibling-based analyses may not gen-
eralize to children without siblings. However, families with a
single child may not be the contemporary norm in the USA.
The total fertility rate per woman in the USA is approximate-
ly two and the predominant ideal family size in the USA is
made up of two to three children (Hagewen and Morgan,
2005). Results from sibling comparison are therefore still
relevant with regard to a large portion of the US population.
Third, the results from these analyses may not generalize to
different countries and societies. Fourth, the assessment of
maternal alcohol use during pregnancy in the NLSY was
based on frequency, which did not include information on
the amount of alcohol consumed on each occasion.
However, the magnitude of the association and the results
are consistent with previous research. Furthermore, explora-
tive analysis of the NLSY substance use data measured
during the non-pregnant period suggested a strong positive
association between frequency of alcohol use and amount of
alcohol consumption on each occasion. In fact, binge drin-
kers are among the most frequent drinkers. Prior episodes of
binge drinking also strongly relate to frequent alcohol con-
sumption while pregnant. Therefore, frequency of alcohol
use remains a meaningful indicator of the levels of maternal
alcohol use during pregnancy. Finally, maternal ratings of
infant behaviors are subjective, and thus may vary from
mother to mother. However, the sibling fixed-effects model

compared siblings’ behaviors that were rated by the same
mother, and therefore eliminated (or at least minimized) the
problem of different evaluative standards. Furthermore, some
child psychologists argue that maternal reports generally
provide valid and reliable measures of infant behaviors in
everyday life, and this may capture the infant’s behaviors
better than lab assessments that measure only a snapshot of
the child’s behaviors in a contrived environment (Fox and
Henderson, 2000).
Limitations notwithstanding, this study makes several sig-
nificant contributions to the literature. Most importantly, the
sibling fixed-effects modeling technique removed potential
biases due to unmeasured time-invariant family-specific
characteristics. While the sibling model cannot fully account
for all unobserved heterogeneities, it provided better esti-
mates on the relationship between prenatal alcohol exposure
and temperamental outcomes than the traditional OLS
model. In addition, this study examined infant behavioral
outcomes. Longitudinal evidence has demonstrated a strong
link between difficultness and childhood problem behaviors,
which suggests a continuity of early problem behaviors. For
example, using data from a prospective longitudinal study,
Guerin et al. (1997) found that infants who scored high on
difficultness when they were 1.5 years old had higher ratings
of aggressive behaviors during school age, as rated by
parents and teachers. Another study by Keenan et al. (1998)
also found that a high level of difficultness measured
between 1 and 2 years of age was significantly associated
with boys’ internalizing problem behaviors and externalizing
problem behaviors by age 3. Thus, infant difficultness is a
strong predictor of behavioral problems in childhood, and
recent reviews of the literature show that infant difficultness
is an indicator of early behavioral problems, which can be
used to identify children at high risk for problem behaviors
(Bates et al., 1985; Frick and Morris, 2004). Findings from

this study thus broaden the scope of those obtained from
prior studies, and provide further evidence of a link between
prenatal drinking and offspring behavioral problems in early
periods of life. Moreover, this study investigated the differen-
tial susceptibility of prenatal drinking in infant behavioral
outcomes and birth weight. Results provide the very first evi-
dence, and partial support, of the relative sensitivity of infant
behavioral outcomes over birth weight using observational
data involving humans. Finally, this study’s findings are
more generalizable than those obtained in prior clinical
studies, because the present results are based on a sample of
the offspring of women in a large national study, including
women from diverse social and economic backgrounds. In
terms of public health practices, the present study also pro-
vides information that may have significant implications for
public policy. Findings imply that interventions that aim to
reduce maternal drinking while pregnant may generate
improvements on children’s behavioral well-being. In add-
ition, given that a substantial proportion of Americans do not
consider light drinking during pregnancy to be hazardous
(MacKinnon et al., 1995), these findings also send an im-
portant message to the general public. Nevertheless, add-
itional studies are definitely needed to inform theories about
the etiology of child behavioral problems and provide neces-
sary information for public health campaigns.
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