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The Gene–Culture Interaction Framework and Implications for Health
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The Gene–Culture Interaction Framework and
Implications for Health
Joni Y. Sasaki, Jessica LeClair, Alexandria West, and Heejung S. Kim
The Oxford Handbook of Cultural Neuroscience
Edited by Joan Y. Chiao, Shu-Chen Li, Rebecca Seligman, and Robert Turner
Abstract and Keywords
Based on the framework of gene–environment interactions (G E), the gene–culture
interaction framework demonstrates that a more complete understanding of thoughts and
behaviors relevant to health may come from incorporating both genetic and cultural
factors. Genes may interact with culture such that genetic predispositions lead to
different outcomes depending on culture, and cultural differences on a given outcome
may vary depending on genetic predispositions. We provide an overview of G E
research and some of the underlying biological mechanisms of these interactions. We
explain the gene–culture interaction framework and discuss how culture is an important
form of environment to consider that makes theoretical contributions unique from other
forms of environment typically studied in G E research. We discuss theoretical
questions raised by gene–culture interaction research and specify how the gene–culture
interaction framework can be applied to certain health issues.
Keywords: Gene–environment interaction, gene–culture interaction, determinants of health, framework, culture
Imagine two wine grape varieties across two different climates. Whereas the Cabernet
Sauvignon variety may thrive in warm climates, the ideal climate for Riesling is relatively
cooler. Knowing when and why grapes produce optimal fruit for good wine requires
understanding the interaction of a number of factors, such as grape variety based on
genes and climatic aspects of the environment: These grape varieties thrive in either
warm or cool climates, depending on their particular variety. Similarly, variation in
human thought and behavior relies on both genetic and environmental factors, as well as
the interaction between the two. Focusing only on genetics as a source of variation
ignores the reality that the same genetic tendency can lead to different outcomes
according to the environment. Likewise, focusing on the environment as the sole
Print Publication Date: Dec 2015
Subject: Psychology, Cognitive Neuroscience, Personality and Social Psychology
Online Publication Date: Apr 2016 DOI: 10.1093/oxfordhb/9780199357376.013.20
Oxford Handbooks Online
The Gene–Culture Interaction Framework and Implications for Health
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explanatory force overlooks the fact that the same environment can have different
consequences for people depending on their genetic tendencies. In order to make
predictions about when or why people think and behave the way they do, it is useful to
consider their biological predispositions together with the particular environmental
context in which they exist.
Among the many ways in which environments vary, culture—the part of the environment
created and shared among social beings and passed down over generations (de Waal,
2001; Geertz, 1973; Herskovits, 1948; Triandis, 2007)—is one important aspect of
environmental variation that has only recently been considered together with genes.
Cultural psychology is a field that investigates cultural variation in systematic ways and
has grown considerably in its breadth of topics and scientific approaches during the past
25 years. Recently, the emerging field of cultural neuroscience has built on cultural
psychology, tackling questions on culture, mind, and the brain by integrating cultural
psychological research with cutting-edge techniques and perspectives from neuroscience
(for review (p. 280) and proposed framework of cultural neuroscience, see Kim & Sasaki,
2014). Using cultural psychology and cultural neuroscience as foundations, our research
has examined gene–culture interactions, or the dynamic interplay of genes and culture as
they jointly influence psychological outcomes (Kim, Sherman, Sasaki, et al., 2010; Kim,
Sherman, Taylor, et al., 2010; Kim et al., 2011). Our perspective is that not only do both
genes and culture act as independent sources of influence, but also, importantly, they
interact to predict various outcomes. Therefore, the gene–culture interaction framework
examines how culture can shape the way genetic tendencies are expressed and also how
cultural influences may change depending on genetic predispositions.
Because the gene–culture interaction framework considers the sociocultural context as
one source of psychological variation that interacts with biological predispositions, this
framework may be important for understanding the complexities surrounding health
within and across diverse societies. In particular, many issues relevant to physical and
psychological health, including the determinants of health outcomes, treatments for
health problems, and intervention strategies, may vary across cultures. Within any
society, there exist groups of people that differ along multiple dimensions. In addition to
ethnicity or nationality, which are the most commonly studied dimensions of culture,
there are many other forms of culture (Cohen, 2009) that have important health
implications, such as religion (Koenig & Larson, 2001; McCullough, Hoyt, Larson, Koenig,
& Thoresen, 2000), region (Plaut, Markus, & Lachman, 2002), and social class (Adler,
Epel, Castellazzo, & Ickovics, 2000; Adler & Stewart, 2010; Plaut, Markus, Treadway, &
Fu, 2012). These different forms of culture vary not only within but also across societies,
and therefore, a cultural perspective can help broaden understandings of health beyond
the populations that tend to be studied most (i.e., “WEIRD” participants who are Western,
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educated, industrialized, rich, and democratic; Henrich, Heine, & Norenzayan, 2010a,
2010b). At the same time, there are important individual differences in genetic
predispositions, and these predispositions may predict health outcomes differently
depending on the cultural context. Given that genes interact with environmental factors
to influence health-related outcomes (e.g., Caspi et al., 2003; Johnson & Krueger, 2005;
Kim-Cohen et al., 2006; Larsen et al., 2010; Miller et al., 2009; Schmid et al., 2010; Taylor
et al., 2006) and that there are cultural differences in how people strive for and achieve a
healthful life (Oishi & Diener, 2001; Plaut et al., 2012), the gene–culture interaction
framework has great potential for predicting and explaining the complexity that
surrounds health issues for diverse groups.
In this chapter, we first provide an overview of research on gene–environment
interactions (gene × environment, or G × E) and the biological mechanisms underlying
these interactions. Second, we explain the framework of gene–culture interactions (gene
× culture, or G × C), including how this framework builds on gene–environment research
and makes unique theoretical contributions. We also discuss some potential mechanisms
of gene–culture interactions, review empirical evidence supporting the G × C framework,
and bridge the framework with a prominent theory in the study of genes and culture—
that of gene–culture coevolution. In the next section, we discuss theoretical issues and
questions raised by G × C research, including implications for findings in cultural
psychology and issues surrounding covariation of cultural and genetic differences.
Finally, we specify how the G × C framework can be applied to health research. In so
doing, we explain the theoretical value of taking a cultural perspective in issues of health,
suggest future areas of research relevant to health, and offer insight on how this research
has implications for public health policy.
Gene–Environment Interactions and
Underlying Biological Mechanisms
The framework of gene–environment interactions (G × E) is one that should seem familiar
to many psychologists, particularly in social and personality disciplines, and it also has
certain advantages compared to other interactionist models of behavior. The idea that
something about the person (in this case, genes) interacts with something in the
environment (e.g., the social context) is reminiscent of classic work from person ×
situation theory (Mischel, 1990; Mischel & Shoda, 1995), which addresses how
personality can interact with situational contexts to influence behavior. Consideration of
genetics from a similar perspective raises a number of novel questions and potential
implications for psychology. Some of the underlying biological mechanisms of G × E
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interactions, for example, may potentially be incorporated into theories of psychological
phenomena. Genetics research also offers a particularly promising way to contribute to
an understanding of cultural differences in basic (p. 281) psychological processes,
including health-related outcomes.
The long-standing nature–nurture debate focuses on distinguishing the distinct influences
of genes versus environment. Rather than treating the two factors separately, the G × E
interaction framework describes the phenotypic effects of interactions between individual
genetic variation and the environment. The framework proposes that environmental
conditions may moderate the psychological outcome of a particular genetic sequence or
that genetic predispositions may moderate the relationship between the environment and
an outcome (Caspi et al., 2002, 2003). In other words, an individual could be genetically
predisposed toward a particular psychological outcome, but that outcome may only occur
given specific environmental pressures. For example, Caspi and colleagues (2003) found
that carrying the short (s) allele of the 5-HTTLPR polymorphism of the serotonin
transporter (SLC6A4) gene promoter region increases the likelihood of showing
depressive symptoms compared to carrying the long (l) allele, but only when coupled with
exposure to life stress (for recent meta-analytic support of this G × E finding, see Karg,
Burmeister, Shedden, & Sen, 2011; but see also Risch et al., 2009).
Originally studied in the context of disease susceptibility, genes implicated in
environmental sensitivity, such as the s allele of 5-HTTLPR, have been referred to as
“risk” genes (e.g., Caspi et al., 2003). Recently, however, such genes have been
reconceptualized as “plasticity” genes, rather than as linked to mostly positive or mostly
negative outcomes, in order to highlight the malleability rather than valence of particular
genetic predispositions (Belsky et al., 2009). In addition to 5-HTTLPR (Caspi et al., 2003;
Cheon, Livingston, Hong, & Chiao, 2014; see also Chapter 17, this volume), G × E
interactions have been reported for various other genes, including the gene encoding
monoamine oxidase A (MAOA) (Caspi et al., 2002; Foley et al., 2004; Kim-Cohen et al.,
2006) and the dopamine D4 receptor (DRD4) gene (Bakermans-Kranenburg & van
IJzendoorn, 2011; Sasaki et al., 2013). In a study of intervention effects on child behavior,
a repeat polymorphism in DRD4 moderated the effectiveness of the intervention
(Bakermans-Kranenburg & van IJzendoorn, 2011), suggesting a differential susceptibility
to environmental inputs dependent on genetic differences. Another study investigating
the interaction between the environment and variants of the DRD4 gene found G × E
interactions on even short-term exposure to environmental conditions: Participants
carrying 2- or 7-repeat allele variants of DRD4 were more susceptible to the influence of
religion priming on prosocial behavior compared to participants without these variants
(Sasaki et al., 2013). Across multiple genes and investigations, there is evidence that
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people with certain genetic variants of “plasticity genes” may be more susceptible to
environmental influence in particular domains.
At the molecular level, environmental factors may interact with genes by influencing the
regulation of gene expression, which is a crucial link between genes and their
phenotypes. Gene expression is the process of synthesizing a biologically functional
molecule from DNA, and the capacity to adapt gene expression in response to
physiological changes or environmental conditions is a basic biological mechanism. For
instance, in response to being wounded, an injured organism might upregulate the
expression of genes relevant to wound recovery (Slavich & Cole, 2013). Similarly,
external social factors could activate biological pathways to regulate gene expression.
Stress and social isolation, for instance, have long been associated with poorer immune
system functioning (Seeman, 1996), and a study examining white blood cells provided
evidence linking social to biological factors at the level of gene expression (Cole et al.,
2007). In particular, among adults who felt less socially connected, pro-inflammatory
genes were upregulated, whereas anti-inflammatory genes were downregulated,
providing molecular evidence for the relation between social isolation and elevated risk
for inflammatory disease.
Social signal transduction, first studied in the context of animal models (Robinson,
Ferald, & Clayton, 2008), is a process explaining how social conditions might alter gene
expression through transcription factors, which are proteins that regulate the
transcription of DNA into mRNA (Slavich & Cole, 2013). Specifically, social signal
transduction emphasizes that subjectively perceived social environment threats may
affect hormone and transmitter levels, leading to changes in the activity of transcription
factors. For instance, feelings of loneliness or social isolation have been linked to the
activation of inflammatory genes and inhibition of antiviral genes (Slavich et al., 2010),
and even the mere threat of social loss appears sufficient to alter gene transcription
dynamics (Miller et al., 2008). The process of social signal transduction underscores the
point that an individual’s subjective perception (p. 282) of social conditions as either
threatening or nonthreatening may at times be more influential than what is objectively
the case (see also Chapter 17, this volume).
Individuals may also vary in their signal-transducing potential depending on differences
in their genes. For example, a study on the link between environmental adversity and
health outcomes examined a single nucleotide polymorphism (SNP) in the promoter
region of the human interleukin-6 (IL-6) gene, which is involved in the inflammatory
response (Cole et al., 2010). Particularly within the promoter and enhancer region of
genes, genetic sequence variations such as SNPs may alter the binding affinity of
transcription factors. This SNP of IL-6 inhibits binding of the transcription factor GATA1,
which typically activates in response to environmental adversity, and thus, people
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carrying the low-binding-affinity variant of the IL-6 gene show an inflammatory response
that is unrelated to exposure to environmental adversity.
Behavioral and health outcomes may also be influenced by epigenetics, which are
processes that can affect gene expression without altering the underlying genetic
sequence (Ledón-Rettig & Pfennig, 2012). Molecular-level processes, such as
methylation, or the addition of methyl groups, may prevent transcription factors from
accessing DNA, possibly preventing the synthesis of gene products. A key finding on how
epigenetic processes contribute to behavioral variation showed that maternal care in rats
is associated with differential methylation of the glucocorticoid receptor (GR) promoter
region in the brain hippocampi (Weaver et al., 2004, 2005). The offspring of rat mothers
who naturally exhibited greater pup licking and grooming behavior showed decreased
methylation of the GR promoter region in the hippocampi. Greater methylation of the GR
promoter has been found to reduce gene expression and to lead to a greater disposition
for anxiety (Meaney, 2001; Weaver et al., 2004).
In humans, there is evidence that epigenetic regulation of genes may be involved in
various social processes and mental health outcomes. For example, in a study
investigating methylation status of a regulator region (CpG island) of the oxytocin
receptor gene (OXTR) in peripheral blood cells and temporal cortex, individuals with
autism showed increases in methylation compared to controls (Gregory et al., 2009). The
increased methylation of this regulator region was specifically associated with decreased
OXTR transcription in an area of the temporal cortex adjacent to the temporal parietal
cortex and near the superior temporal sulcus (STS), a brain region implicated in social
cognition (Allison, Puce, & McCarthy, 2000; Pelphrey & Morris, 2006). DNA methylation
of OXTR may also play a role in individual variation in social information processing. The
DNA methylation status of OXTR was found to predict neural activation of areas of the
brain implicated in social processing in response to ambiguous social stimuli (Jack,
Connelly, & Morris, 2012).
Unlike sequence variations, which are relatively stable across an individual’s lifetime,
there is emerging evidence that epigenetic modifications may occur dynamically in
response to situational conditions. Immediately following a stressful experimental task,
for instance, the methylation status of the stress-associated gene OXTR first increases,
and then once the stressor ends, methylation status decreases below baseline
(Unternaehrer et al., 2012). Epigenetic mechanisms may play an important role not only
for long-term influences of environmental conditions on gene expression but also for
short-term, rapid changes in gene expression in response to situational social stressors.
Basic molecular mechanisms that underlie gene expression thus provide a biological
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pathway for environmental influences to penetrate deeply, altering patterns of gene
regulation and expression.
Advances in molecular biology have greatly increased scientific understandings of the
mechanisms through which different social environments lead to changes in gene
expression and thus behavior. In addition to investigating potential mechanisms more on
the genetic side of the G × E equation, our perspective is that incorporating a cultural
approach in the G × E framework adds the richness of cultural content to the
environment side of the equation and may ultimately elucidate some of the psychological
processes underlying G × E effects.
Gene–Culture Interaction Framework
Building on the gene–environment framework, the gene–culture interaction (G × C)
approach provides one possible way of reconceptualizing the environment to include the
cultural context (Kim, Sherman, Sasaki, et al., 2010; Kim, Sherman, Taylor, et al., 2010;
Kim et al., 2011). The “environment” in the G × E framework is a broad concept that can
include anything from resource availability and weather variability to social environments
in the family and the local society. Types of social (p. 283) environments can then be
meaningfully partitioned into the personal environment, or individual variation in
experiences and events, such as stress in the home setting (e.g., Taylor et al., 2006), and
the cultural environment, or beliefs, values, practices, and products that constitute a
shared system of meaning, such as the Western emphasis on independence and personal
choice (e.g., Markus & Kitayama, 1991). Although there are many ways to potentially
parse the environmental component of G × E, we argue that focusing on the cultural part
of the environment, as in the gene–culture interaction framework, is particularly
important both theoretically and practically.
Although no one definition of culture is uniformly agreed upon, there are key components
that many scientists are likely to endorse. Most would agree that culture is nonbiological
—that is, nongenetic. Via evolutionary processes, social organisms may be biologically
prepared with the capacity to develop culture (Tooby & Cosmides, 1992), and genes and
culture may interact (Dressler, Balieiro, Ribeiro, & Dos Santos, 2009; Kim, Sherman,
Sasaki, et al., 2010; Kim, Sherman, Taylor, et al., 2010; Kim et al., 2011; Kitayama et al.,
2014; Sasaki, Kim, & Xu, 2011) and mutually influence each other in processes of gene–
culture coevolution (Chiao & Blizinsky, 2010; Feldman & Laland, 1996; or dual
inheritance: Boyd & Richerson, 1985; see also Cavalli-Sforza & Feldman, 1981; Durham,
1990, 1991; Fincher, Thornhill, Murray, & Schaller, 2008; Lumsden & Wilson, 1981) to
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ultimately shape the neural processes underlying thought and behavior (see Chiao &
Immordino-Yang, 2013). At the same time, however, culture can be separated from
genes. Although culture influences and is influenced by biological processes, culture itself
can be understood as beliefs, values, practices, and products that are socially created
rather than genetically inherited by living beings (de Waal, 2001). Once socially created,
these environmental features must then be socially transmitted to others and passed
down over multiple generations such that they are maintained well beyond the lives of
their original creators (Berger & Luckman, 1966). These characteristics, some have
argued, are among the hallmarks of culture (de Waal, 2001; Geertz, 1973; Herskovits,
1948; Triandis, 2007).
Culture exists not only outside the self in the form of cultural products, or tangible, public
representations such as art and media, but also inside the mind (Cohen, 2009; Kim &
Markus, 1999; Shweder, 1995). In our approach, the G × C interaction framework
incorporates both aspects of the cultural environment. Thus, consideration of culture as a
form of environment provides an understanding of how an individual’s own beliefs and
values are shared with others and how these mutually shared meanings allow people to
interpret events and understand their experiences. Shared meaning constitutes an
important part of culture that is unique from other forms of environment and is one of the
main strengths of considering cultural and psychological factors in G × E research.
Mechanisms of the Gene–Culture Interaction
Framework
Although the biological mechanisms of G × C interactions have yet to be clearly
elucidated, some of the known biological mechanisms of G × E interactions may suggest
possible mechanisms linking the cultural environment to genes. One way of
conceptualizing culture is as socially shared patterns of mental processes and
psychological responses, which can be applied to the process of social signal
transduction. Just as the subjective perception of social conditions can affect patterns of
gene expression (Slavich & Cole, 2013), differences in cultural expectations and norms
could potentially affect perceptions of social situations and thus the way genes are
expressed. For example, in the case of seeking social support, European Americans are
more likely to confide in close others in distressing situations and directly ask for help
compared to Asian Americans, who may be relatively more concerned about burdening
their social networks (Kim, Sherman, & Taylor, 2008; Taylor et al., 2004). Thus, the same
social situation—seeking social support—could be perceived as more or less threatening
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depending on the cultural context (Taylor, Welch, Kim, & Sherman, 2007). One possibility
is that such cultural variation in subjective experience could manifest in cultural
differences in the activity of gene expression.
Cultural meanings, practices, and patterns of interactions could also have implications for
epigenetic processes. Epigenetic differences in the genomes of monozygotic twins, for
instance, can occur as a function of accumulated exposure to divergent life experiences
(Fraga et al., 2005). Such epigenetic modifications result in different behavioral and
health outcomes—in this case, differences between twins in disease onset. Similarly,
individuals engaged in different cultural contexts may be systematically exposed to
varying experiences that contribute to epigenetic change. For instance, a study
comparing (p. 284) Asia and North America found that the cultural environment of the
United States offered more frequent and potent opportunities to exert influence on one’s
surroundings compared to Japanese cultural environments, which provided more
opportunities for adjusting to the situation (Morling, Kitayama, & Miyamoto, 2002). A
lifetime of exposure to varying experiences could potentially result in culturally differing
patterns of methylation, epigenetic modifications that in some cases may be transmitted
across generations, providing an inheritance mechanism for the impact of environmental
factors (see Franklin & Mansuy, 2010).
From the perspective of differential susceptibility, individuals may exhibit differences in
their genetic predisposition to methylation and thus be more or less sensitive to
environmental influences (e.g., Huang, Perry, & Laux, 1999). In a study of adults with
traumatic experiences, increased methylation leading to decreased gene expression was
found to moderate the association between serotonin transporter gene polymorphisms
and depressive symptoms (van IJzendoorn, Caspers, Bakermans-Kranenburg, Beach, &
Phillbert, 2010). The short variant of the 5-HTTLPR gene predicted more feelings of
unresolved loss but only when methylation levels were low. Thus, epigenetic processes,
such as methylation, may operate at the interface of environmental exposure and
psychological outcomes.
Evidence for Gene–Culture Interactions
Evidence for G × C interactions relevant to health outcomes derives from studies
investigating a variety of genes and psychological processes. Building on the idea of
environmental susceptibility, G × C interaction research focuses on genes that have been
implicated in environmental sensitivity and predicts that particular genetic variations will
alter an individual’s susceptibility to environmental influence. In a study of the
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interaction between variants of the 2A serotonin receptor (5-HT2A) and depressive
symptoms, the perception of one’s family as a prototypically “good family” in Brazil
negatively correlated with depressive symptoms (Dressler et al., 2009). The effect was
enhanced for those individuals carrying the AA variant of 5-HT2A compared to individuals
with AG or GG variants. Another study, which investigated G × C interactive effects on
psychological well-being, found that religiosity was associated with greater well-being for
those genetically predisposed to be environmentally sensitive (i.e., those carrying the GG
variant of a particular oxytocin receptor gene polymorphism), but only for those from a
cultural context in which religion tended to provide more frequent opportunities for
affiliation (Sasaki et al., 2011).
Gene–culture interactions have also been shown for health-relevant behaviors, such as
emotion regulation. Kim and colleagues (2011) compared emotion regulation approaches
between the United States, where expressivity is more highly valued, and Korea, where
suppression is valued more. Koreans with the environmentally sensitive variant (GG
genotype) of the oxytocin receptor gene (OXTR) reported using more emotion
suppression than those with the AA genotype, whereas European Americans showed the
opposite pattern. Overall, it seems that through engagement in different cultural systems,
individuals genetically predisposed to environmental sensitivity are the ones to most
strongly adopt the particular psychological and behavioral patterns supported by a
culture for certain psychological phenomena (Kim & Sasaki, 2012, 2014). Likewise, when
comparing across multiple cultures, the most culturally divergent patterns of behavior
relevant to a gene of interest appear to emerge among people with environmentally
sensitive predispositions.
Bridging Gene × Culture with Gene–Culture
Coevolution
Although the gene–culture interaction and gene–culture coevolution perspectives both
investigate the relationship between biological and cultural variation, they address
different aspects of this relationship, and there are some interesting points that arise
from comparing these perspectives. Gene–culture coevolution theory (also known as dual
inheritance theory) provides an explanation for the macro-level interactions between
culture and genes by applying a Darwinian selection framework to culture. The theory
proposes that similar to genetic variants, features of a culture could increase individual
fitness and be transmitted through social learning in a system of inheritance not unlike
genetic inheritance (Boyd & Richerson, 1985; Chiao & Blizinsky, 2010; Feldman &
Laland, 1996). Thus, cultural features, which serve as adaptations to local environments
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and conditions, could evolve much like genes evolve. Such cultural evolution may have
been particularly important in the history of human evolution because cultural practices
could have allowed for adaption to environments at a pace much faster than allowed by
genetic evolution alone.
(p. 285) According to gene–culture coevolution, cultural systems contribute to creating
environmental pressures under which genetic evolution occurs. One classic example is
the coevolution of dairy farming practices and the lactase gene. The ability to digest milk
proteins usually disappears after childhood. However, there is an association between a
history of dairy farming and the frequency of genetic variants related to lactose tolerance
in a population (Beja-Pereira et al., 2003; Myles et al., 2005), suggesting that the
development of cultural practices supporting dairy farming and milk consumption
contributed to evolutionary selection favoring alleles for adult lactose tolerance. Another
example derives from research investigating the association between individualism–
collectivism tendencies and the serotonin transporter gene polymorphism 5-HTTLPR
(Chiao & Blizinsky, 2010; for gene–culture coevolution evidence of cultural tightness vs.
looseness and 5-HTTLPR as explained by historical ecological threat, see Mrazek, Chiao,
Blizinsky, Lun, & Gelfand, 2015). Previous studies have demonstrated that regions with
historically greater pathogen prevalence tend to be more collectivistic (Fincher et al.,
2008). Chiao and Blizinsky (2010) report that the cultural value of collectivism, which
enhances social connectedness, is associated with a higher frequency of the s allele of 5-
HTTLPR, which has been linked to anxiety and mood disorders in certain populations.
The development of collectivistic practices may have evolved to reduce exposure to
environmental pathogens and thus may have also strengthened selection pressures for
the s allele of 5-HTTLPR if it buffers susceptible populations against genetic
predispositions for affective disorders (see also Way & Lieberman, 2010).
The theory of gene–culture coevolution is complementary with the gene–culture
interaction framework in that the two approaches operate at different levels of analysis.
Gene–culture coevolution focuses on the macro-level evolutionary processes shaping
cultural norms and genetic variants. In contrast, the gene–culture interaction framework
addresses how culture and genetics interact to influence behavioral and psychological
outcomes at the individual level. Through gene–culture coevolution processes, a
particular adaptive cultural value may become common within a population, creating
selective pressures for a particular genetic variant. However, genetic variation will still
exist in the population. The gene–environment interaction framework explains how
individuals within the same cultural context might think and behave differently
depending on their genetic predispositions. For example, there may be a region-level
correlation between the prevalence of the s allele of 5-HTTLPR and collectivistic values
(Chiao & Blizinsky, 2010), whereas at the individual level, s allele carriers versus l allele
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carriers may be influenced by cultural norms differently, as predicted within the gene–
culture interaction framework.
Research on gene–culture interactions is new, yet the perspective holds great promise for
illuminating the processes underlying genetic and environmental influences on behavior.
Investigations in molecular biology may inform understandings of underlying biological
mechanisms, whereas cultural research may contribute to predictions about underlying
psychological mechanisms. By bringing these two perspectives together, gene × culture
research may offer a more complete picture of the process through which cultural
information, both inside and outside the head, can interact with genetic information to
lead to different outcomes.
Theoretical Issues and Questions Raised by
Gene × Culture Research
As an emerging area of research, gene–culture interactions raise a number of important
issues with theoretical relevance. First, there are some general patterns of results from
gene × culture research that may have implications for cultural psychology. Second,
research on genes and culture raises interesting questions about genetic frequencies in
different populations. Especially for addressing issues related to health, the combination
of both genetic and cultural considerations holds great potential. Yet at the same time,
the gene × culture framework represents a departure from more classic cultural
perspectives in some ways and raises important questions to be addressed.
Implications for Cultural Psychology
Gene–culture interactions offer a way of understanding not only how genetic
predispositions may manifest themselves differently depending on the cultural context
but also how cultural factors may influence people differently according to individual
differences at the level of genes. This framework captures how the content of culture can
inform research in the realm of biology and behavioral genetics. However, that is not to
say that the influence of culture is unvaried. Genes may constrain the effects of culture
by providing people with a range of possible traits or behaviors, and the environment,
(p. 286) including culture, can then select from that range of possibilities to lead to a
particular outcome.
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Gene × culture findings have shown that some well-known cultural effects seem to occur
more for people with certain genetic predispositions than others. Cultural differences in
emotional support seeking (Kim, Sherman, Sasaki, et al., 2010) and emotion regulation
(Kim et al., 2011), for instance, emerge among people with GG and AG genotypes of
OXTR but not AA genotypes. In addition, previously found cultural differences in locus of
attention (Choi, Koo, & Choi, 2007; Masuda & Nisbett, 2001) appeared only for GG and
CG genotypes of 5-HTR1A and not for CC genotypes (Kim, Sherman, Taylor, et al., 2010).
This general pattern of results may have implications for cultural psychology more
broadly because it is possible that many previously discovered cultural differences are
stronger for those with certain genetic predispositions than others. Although it is
probably not the case that a single gene leads people to be more or less culturally
normative across all traits and behaviors, one possibility given our G × C findings and
other G × E research is that sets of genes (e.g., oxytocin-related genes) may be related to
culturally normative responses for specific outcomes (e.g., socioemotional sensitivity).
This means that cultural differences on these outcomes may be more pronounced for
people with certain genetic predispositions than others, but across outcomes, there
should be no relationship between cultural normativity in general and any one set of
genes, consistent with insights on why cultural differences are not always reducible to
individual differences (Na et al., 2010).
Covariation of Cultural and Genetic Differences
One intriguing question derives from observations combining cultural differences in
psychological and behavioral tendencies with differences found in the distribution of
specific genotypes across ethnic groups, such as people of East Asian versus European
ancestry. Interestingly, many of the genes that have been commonly studied in
psychology, such as 5-HTTLPR, OXTR, and DRD4, have drastically different genotype
distributions across ethnic groups. Sometimes these divergent genotype frequency
distributions correlate with documented differences in cultural norms (Chiao & Blizinsky,
2010; Mrazek et al., 2015). However, when one considers the general set of psychological
tendencies associated with any given polymorphism, the way in which genotype
distributions within a cultural group align with their documented psychological
tendencies varies considerably.
For instance, compared to groups with European ancestry, East Asian samples tend to
have a much higher frequency of the 5-HTTLPR polymorphism s allele, which is
associated with stress reactivity (e.g., Caspi et al., 2003). East Asians are also known to
be more avoidance oriented than North Americans with European cultural backgrounds
(Heine et al., 2001; Lee, Aaker, & Gardner, 2000). Thus, the fact that the environmental
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susceptibility genotype of 5-HTTLPR is more common among people from East Asian
cultures, which emphasize interpersonal influence (Morling, Kitayama, & Miyamoto,
2003) and the value of group harmony (Kim & Markus, 1999), seems to make sense
intuitively.
At the same time, the G allele of OXTR rs53576 polymorphism is far more common among
European Americans than among East Asians (e.g., Kim, Sherman, Taylor, et al., 2010;
Kim et al., 2011). Given the association of the OXTR G allele with social bonding and
affiliation (e.g., Bakermans-Kranenburg & van IJzendoorn, 2008; Rodrigues, Saslow,
Garcia, John, & Keltner, 2009; but see Bakermans-Kranenburg & van IJzendoorn, 2014),
as well as with greater environment susceptibility (Belsky, Bakermans-Kranenburg, & van
IJzendoorn, 2007), it may seem counterintuitive to find a higher frequency of G alleles
among European Americans, who are from cultural contexts that tend to emphasize
independence and individualism, than among East Asians, who are from cultural contexts
in which interdependence and collectivism are fostered.
To further complicate the matter, different variants of DRD4 polymorphism (i.e., 2-repeat
and 7-repeat alleles) in different ethnic groups are associated with similar functional and
psychological characteristics (Reist et al., 2007; Wang et al., 2004), but the frequencies of
these respective environment susceptibility genotypes are roughly compatible between
European Americans and Asians (e.g., Kitayama et al., 2014; Sasaki et al., 2013).
Genetic profiles of different ethnic groups are no doubt the result of natural selection
processes and specific challenges posed by the regional environment, but it is beyond the
scope of this chapter to address how particular genes come to be more frequent in one
ethnic group than another. In this chapter, we focus on what we can learn from the
observation of diversity in genetic distributions among different ethnic groups and future
research questions that may be inspired by these observations.
(p. 287) Given that the frequencies of genotypes for these susceptibility genes differ
greatly, and sometimes against what seems to be the intuitive association with cultural
tendencies, one can reasonably infer that cultural tendencies cannot be simply explained
as averages of phenotypic tendencies of populations. That is, the frequency distribution of
OXTR genotypes (Kim, Sherman, Sasaki, et al., 2010; Kim et al., 2011) probably does not
explain why East Asians are more interdependent than European Americans. To the
extent that there is any relationship between genotypic distributions and cultural
tendencies, the relationships will be considerably more complicated, as proposed by
other theoretical models such as gene–culture coevolution and gene–culture interaction.
For example, there is evidence that the DRD4 variant may moderate the cultural
difference in independent versus interdependent social orientations such that 2- or 7-
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repeat allele carriers tend to have greater independence for European Americans but
greater interdependence for East Asians (Kitayama et al., 2014).
An additional point is that it is not always clear how specific the associations are between
a gene and its psychological correlate. For example, stress reactivity is often discussed in
relation to 5-HTTLPR, although it is by no means the only gene that is associated with
stress reactivity. There are other genes, such as OXTR (Rodrigues et al., 2009) and MAOA
(Caspi et al., 2002), that influence one’s sensitivity to environmental distress. Thus,
although there seems to be some genetic specificity in the associations with different
social behaviors, strongly inferring conceptually distinct and exclusive psychological
outcomes from specific genes should be done with caution. Rather, there may be sets of
genes with distinguishable but overlapping functions that predispose individuals to
certain domains of sociocultural influence. It will be useful to adopt more reliable ways of
investigating genetic influence, such as a polygenic approach examining the link between
a trait and multiple genes and a pleiotropic approach examining how a single gene may
be linked to multiple traits.
Moreover, considering gene–culture interactions in the context of genotypic distribution
differences in ethnic groups raises the question of why sometimes only a small genetic
minority in a cultural group seems to embody culturally normative tendencies. For
example, the s allele of 5-HTTLPR is relatively rare among European Americans, and the
G allele of OXTR rs53576 is relatively rare among East Asians, yet both the 5-HTTLPR s
allele and the OXTR G allele seem to predispose people to be more susceptible to cultural
influences. For this question, we propose that there are at least two possible answers.
One possibility is that the maintenance of culturally normative tendencies may be shaped
by multiple genes in conjunction with each other. Examination of multiple polymorphisms
in combination, including genes that are more or less common in a given population (e.g.,
G allele of OXTR or s allele of 5-HTTLPR among East Asians), is likely to yield a more
normally distributed genetic profile at the cultural group level (cf. Belsky et al., 2013),
evening out skewed distributions of each polymorphism. In other words, the genetic basis
of cultural susceptibility itself is probably similarly and normally distributed among many
cultural groups. Given that, it would be unwise to infer that any single gene is responsible
for a broad range of cultural differences or that a gene or even a group of genes are
responsible for a broad category of social behaviors, such a cultural conformity, without
further specifying the exact processes. It is more likely that a particular gene or set of
genes predispose each individual to be sensitive to a small aspect of cultural
environment, and only as a whole, we may be able to see cultural patterns.
This issue of single gene research is not limited to research in cultural genetics. The
single gene approach has been fruitful in leading the initial examination of the
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excruciatingly complex process of genetic influence, allowing investigators to formulate
theory-driven predictions in a relatively parsimonious manner. However, the field is
moving toward examining how multiple genes together influence psychological and
behavioral tendencies. Yet, there is currently no clear model to examine multiple genes in
conjunction with each other. It is unclear if the genes function in additive, interactive, or
compensatory ways, although there are some notable efforts to deal with this issue. For
example, Belsky and colleagues (2013) selected multiple genes based on results of
genome-wide association studies (GWAS) and examined how they predict particular
health-related behaviors, such as smoking and obesity, using an additive model. Also,
genome-wide complex trait analysis (Yang, Lee, Goddard, & Visscher, 2011) was
developed to address the “missing heritability” problem as a way to utilize GWAS data for
estimating and partitioning complex trait variation. Although these models offer promise,
to date there has not been a compelling study using multiple genes along with
environmental input to predict social behaviors. (p. 288) As the field moves forward,
there will no doubt be empirically and biologically informed ways to examine multiple
genes to further uncover the role of genes and environment in shaping social and cultural
behaviors, and researchers will then be able to answer questions with greater certainty.
An additional possibility is that much of the culture-specific norms have not been stable
for long enough to be reflected directly by a set of genes. The time frame for genetic
divergence among ethnic groups is more than 40,000 years (Bowcock et al., 1991). Thus,
much of the genetic composition of each ethnic group seems to predate certain
components of the established culture, at least in terms of cultural values, institutions,
and assumptions based on specific historical antecedents. Of course, as research on
gene–culture coevolution shows, cultural practices may have a detectable influence on
genetic distribution in specific cases (e.g., Beja-Pereira et al., 2003) within a relatively
brief evolutionary time frame. Nevertheless, it is likely that changes in thoughts and
behaviors at the individual level, and even cultural practices and norms at the group
level, are much more malleable and quick-paced than changes in genetic characteristics
of populations. Given that, the link between genetic profiles of a particular ethnic group
and their cultural characteristics may be fairly unstable, and this is an important
possibility to keep in mind.
The ways in which genes and culture are related with each other are numerous, as shown
in this very brief review. Currently, much remains unknown in terms of how genes work
to eventually lead to traits, and there are a number of caveats to consider in formulating
new theories. The field will benefit in the future from combining multiple perspectives,
including psychology, behavioral genetics, population genetics, and anthropology, to
address questions about the mind and behavior.
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How Can the Gene × Culture Framework Be
Applied to Health Research?
Due to the growth of cultural psychology, there is now a relatively large body of research
to draw upon for investigations of health using a gene–culture interaction perspective. In
this final section, we discuss cultural research relevant to health, promising avenues of
future research, and implications for public health policy.
Culture and Health
Cultural differences exist even in basic psychological phenomena, many of which have
important implications for understanding what people consider healthful and how they
ultimately achieve positive health outcomes. For instance, it is well-known that social
relationships have strong implications for health (Cohen, 2004), and this general link may
be true in every culture. The meanings embedded in relationship contexts, however, may
vary across cultures and thus have relevance for understanding a range of health-related
issues, from the way people draw on their social networks to cope with difficulties (Kim et
al., 2008) to the extent to which one’s well-being is contingent on others (Plaut et al.,
2012). In addition, given that certain genes or sets of genes may be linked to social
sensitivity in particular contexts (e.g., Bartz, Zaki, Bolger, & Ochsner, 2011), it may be
especially useful for gene–health research to consider the cultural contexts that shape
norms and expectations in social relationships.
Research from a cultural perspective has also shown more directly that there are cultural
differences in health outcomes, the willingness to seek different kinds of treatment, and
the effectiveness of different treatments. Given that perceived discrimination contributes
to health disparities (Major, Mendes, & Dovidio, 2013; Pascoe & Smart Richman, 2009;
Williams & Mohammed, 2009), it is important to consider intergroup dynamics for
investigations on culture and health. For instance, it is well documented that people from
lower social class contexts tend to fare worse than those from a higher social class on
certain health outcomes, in part due to greater exposure to stress and other health-
debilitating risks (Williams & Collins, 1995; for review, see Matthews & Gallo, 2011). In
addition, minorities may seek mental health treatment less often compared to majority
group members, even after acculturating to a new culture (B. Kim, 2007; Mills, 2012),
and for those who do seek medical care, there is evidence that ethnic minorities tend to
receive lower-quality treatment on average (Williams & Sternthal, 2010). Some minority
groups, such as Black Americans, continue to face lower average life expectancies
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compared to White Americans, even after taking social class into account (Williams &
Sternthal, 2010), raising the possibility that minorities may face greater health risks due
to perceived discrimination. However, some immigrant groups, such as those with
Mexican backgrounds, tend to have equivalent or better health outcomes than the
mainstream White population, despite the fact that they face greater risk of poverty and
low-quality health care (p. 289) (a phenomenon termed the “Hispanic paradox”; Markides
& Eschbach, 2005).
People from different cultures may also show different symptomatology for mental health
problems and have different beliefs about treatment (Ryder, Ban, & Chentsova-Dutton,
2011). Studies of people with depression across cultures have found that the Chinese
tend to somaticize depression symptoms more than do Westerners (Chang, 1985; Tsai,
Simeonova, & Watanabe, 2004). Also, European Americans who are depressed tend to
show decreased emotional reactivity, whereas East Asians who are depressed show
heightened emotional reactivity (Chentsova-Dutton et al., 2007). With regard to support
seeking, people from Japan tend to be less likely to seek support from close relationships
and from professional services compared to Americans, and this difference may be
explained by cultural differences in willingness to disclose problems (Mojaverian,
Hashimoto, & Kim, 2013) and relationship concerns, such as disrupting harmony or
saving face (Taylor et al., 2004). In addition, a longitudinal study of pregnant women
found that the Japanese, compared to Americans, are more likely to experience certain
positive pregnancy outcomes when they believe that close others have control over
decisions surrounding their pregnancy (Morling et al., 2003). These findings emphasize
the importance of understanding how culture may shape the expression or presentation
of certain health conditions, as well as how beliefs about appropriate treatment may have
consequence for health outcomes.
From the perspective of cultural neuroscience, a more complete picture of how people
conceptualize health, make decisions regarding their health, and ultimately achieve
positive health outcomes may come from examining the interaction of cultural and
biological factors (e.g., Chiao, Cheon, Pornpattananangkul, Mrazek, & Blizinsky, 2013).
Gene–culture interactions may be a particularly promising area of research within
cultural neuroscience that explains diverse psychological responses (Sasaki, 2013). For
example, research suggests that situating the individual within an intergroup context may
potentially have implications for health and that people with certain genotypes may be
more sensitive to stressful features of this context than others. Specifically, research by
Cheon and colleagues (2014) found that people who had prior negative contact with out-
groups and perceived that the social world is dangerous were more likely to report
intergroup biases, but this relationship was stronger for carriers of the more stress- or
threat-sensitive s allele of 5-HTTLPR compared to those homozygous for the l allele. This
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research highlights the importance of considering how an individual perceives the self in
relation to other groups in an intergroup context, as well as one’s genetic predispositions
to be sensitive to stress in this context.
Genes represent one component of biology but are certainly not the only important factor
to consider for questions surrounding health. As a field, cultural neuroscience examines
the complex ways in which culture and biology interact (Chiao & Ambady, 2007), and it is
crucial to consider specific findings of gene–culture interactions within the context of
cultural neuroscientific frameworks more broadly in order to understand health
disparities (Cheon, Mrazek, Pornpattananangkul, Blizinsky, & Chiao, 2013; Chiao et al.,
2013). A recent review of cultural neuroscience (Kim & Sasaki, 2014) proposes a
framework for understanding how genetic and environmental inputs affect psychology via
neural processes and how culture shapes these processes at multiple levels and is
constrained by the processes of evolution. Because it is clear that culture plays a role in
health outcomes in multiple ways, the next challenge for future research is to incorporate
a cultural approach while anchoring findings within a broader theoretical framework.
Future Research on Gene–Culture Interactions
There are many ways to conceptualize culture (Cohen, 2009), and future research on
gene–culture interactions should thus explore other methods of examining culture in
addition to using cultural group comparisons. For instance, measures of subjective
experience may be one way to consider culture in investigations. As previously described,
a G × C study of cultural consonance, or the degree of match between one’s own life and
the broader shared culture, found that lower cultural consonance was associated with
greater depressive symptoms, and this was especially the case for people with a potential
genetic link to depression-related conditions (Dressler et al., 2009). This study raised the
important point that disparities between subjective experiences and the norms
prescribed by the broader culture can have implications for health outcomes.
Other cultural psychological approaches include cultural task analysis to test implicit
indicators of cultural differences (Kitayama, Park, Sevincer, (p. 290) Karasawa, & Uskul,
2009), continuous measures of educational attainment to measure social class as culture
(Grossmann & Varnum, 2011), and cultural priming to test causal effects of cultural
information on psychological outcomes (Hong, Morris, Chiu, & Benet-Martínez, 2000;
Oyserman & Lee, 2008). Cultural priming may present an especially promising future
direction for gene–culture interaction research because it allows for causal inferences
about the relationship between cultural information and an outcome for people with
different genetic predispositions (for a G × E example of environmental priming in a
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laboratory setting, see Sasaki et al., 2013). All these examples of cultural approaches
could potentially be used in conjunction with the G × C framework.
Future research should also examine the mechanisms through which gene–culture
interactions occur, and the G × C framework may provide good opportunities to address
this issue. The framework of G × C, like that of G × E, makes predictions about
moderation by formalizing how the same genetic predisposition can be linked to different
outcomes depending on one’s culture and also how the same cultural background may
predict different outcomes depending on one’s genetic predisposition. As Baron and
Kenny (1986) explained, the best moderators are those that suggest possible mediators,
revealing something about the underlying mechanisms involved in a psychological
phenomenon. Culture is a moderator with such potential because numerous cultural
psychological studies have revealed mediating processes. In research on culture and
motivation, for instance, Heine and colleagues (2001) initially established an interaction
between a situation (receiving success vs. failure feedback) and culture (Japan vs. North
America) on task persistence and additionally showed that the interaction seemed to
suggest motivation as a potential mediator. Specifically, they showed that North
Americans seemed to experience greater motivation following success (vs. failure)
feedback, allowing them to persist more on a task compared with Japanese participants.
On the other hand, Japanese participants seemed to be more motivated by failure than
success compared with North Americans. Furthermore, cultural differences in motivation
were explained by between-group differences in lay theories about the utility of effort.
Because cultural differences in a given outcome (e.g., task persistence) pointed to
differences in an underlying process (e.g., motivation) and revealed potential
explanations for cultural differences (e.g., lay theories), this example illustrates how a
cultural approach can be useful for elucidating basic psychological processes.
A similar approach can be used in the context of health for G × C research. For example,
one of our previous G × C studies described previously found that culture moderates the
link between OXTR and emotional seeking among those who experience greater distress
(Kim, Sherman, Sasaki, et al., 2010). This finding of cultural moderation could potentially
illuminate social processes in relation to oxytocin more broadly because it suggests that
people who may be predisposed to be more socially sensitive only directly seek more
emotional social support in cultural environments that endorse this behavior as
appropriate. Although initial oxytocin findings seemed to suggest that higher levels of
oxytocin generally encourage people to socially connect with others in positive ways
(Kosfeld, Heinrichs, Zak, Fischbacher, & Fehr, 2005), later research has demonstrated
that oxytocin can also have negative effects, particularly in the context of in-group–out-
group competition (De Dreu, Greer, Van Kleef, Shalvi, & Handgraaf, 2010; Declerck,
Boone, & Kiyonari, 2010) or for individuals lacking optimal resources to deal with social
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stressors (Bartz, Zaki, Bolger, et al., 2010; Bartz, Zaki, Ochsner, et al., 2010; Bartz,
Simeon, et al., 2011). In reality, the influence of oxytocin is complicated and should
therefore be applied with caution (Miller, 2013). The social effects of oxytocin appear to
be highly dependent on aspects of the context and the individual (for review, see Bartz,
Zaki, et al, 2011); in addition, our research suggests that oxytocin may lead people to
interact with others in ways that are sanctioned by the sociocultural context (Kim,
Sherman, Sasaki, et al., 2010; Kim et al., 2011; Sasaki et al., 2011).
These G × C findings further support theories about how social support processes may
not function in the same way across cultures, and more broadly, they demonstrate that
genetic predispositions may manifest themselves in different ways according to what is
normative in the cultural context. As in the case of the culture, OXTR, and emotional
support-seeking study described previously (Kim, Sherman, Sasaki, et al., 2010), the act
of seeking emotional social support can have different meanings depending on the
cultural context (for review of culture and social support processes, see Kim et al., 2008).
G × C research demonstrates that the relationship between genetic predispositions and
behaviors may depend on the cultural (p. 291) meanings of behaviors rather than on
actual behaviors per se.
Implications of Gene × Culture Research for Public Health Policy
The utility of G × C research goes beyond the advancement of theory and development of
new methodology; it also has practical applicability to health issues, particularly in its
ability to inform public health policy. Here, we explore how G × C research can be
applied to the policy areas of defining health and developing goals for public health policy
and providing effective care in a targeted, cost-efficient manner. In so doing, we also
discuss implications and potential recommendations based on past studies and identify
questions for future research to address.
Defining and Delivering Health
Before developing policy, public health policymakers throughout the world should
address the following questions: What constitutes optimal health? How is it best fostered
in a given population? Answering these questions is far from straightforward, and much
research on cultural differences strongly suggests that peoples’ responses to these
questions can vary in important ways. The World Health Organization’s (WHO) recent
emphasis on addressing “social determinants of health,” or social factors that contribute
to health inequities throughout the world (Commission on Social Determinants of Health,
2008), is consistent with this idea that effective public health policy must take the
sociocultural context into account. WHO also defines health as “a state of complete
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physical, mental, and social well-being and not merely the absence of disease or
infirmity” (World Health Organization, 2003), but across cultures, the meaning of well-
being might vary greatly. For example, a study of conceptions of health in New Mexico
and Colorado found that Hispanic villagers highly emphasized fulfilling role obligations
according to one’s age and sex, and the primary repercussion of illness was that it
interfered with the ability to fulfill one’s obligations, not that it affected the sick
individual (Schulman & Smith, 1963). When addressing the concept of health among First
Nations or Aboriginal North Americans, a common model is the medicine wheel, which
depicts health as a holistic balance among social, mental, physical, and spiritual elements
—the latter being a factor that does not commonly appear in Western concepts of health
(Roberts, Harper, Tuttle-Eagle Bull, & Heideman-Provost, 1998; Waldram, 2006).
Furthermore, cultural variation also exists in the conception of a specific component of
health—that is, mental or subjective well-being (Fulmer et al., 2010; Oishi & Diener,
2003; Uchida & Kitayama, 2009). Lay concepts of subjective well-being in Western
cultures often tend to center on the “pursuit of happiness” and avoidance of unhappiness
for oneself (Diener & Diener, 1995; Suh, Diener, Oishi, & Triandis, 1998). In some
Eastern cultures, however, subjective well-being is achieved through fulfilling role
obligations and finding a balance between happiness and unhappiness (Lu, 2005; Suh et
al., 1998; Uchida & Kitayama, 2009). These findings suggest that public health policy
aimed at highly maximizing the population’s happiness may increase the psychological
well-being of a Western population, but it may not have the same effects in an Eastern
population, where such policy may be less appropriate.
Beyond considerations of the definitional components of health, cultural psychological
research also sheds light on differences in the ways to achieve optimal health. For
example, Eastern cultures’ emphasis on balance and dialecticism might apply to attitudes
toward health and the desired goals of public health. In research on topics such as
emotional experience (Uchida & Kitayama, 2009), reasoning and logic (Ji, Nisbett, & Su,
2001; Peng & Nisbett, 1999), and self-concept (Heine & Lehman, 1997; Spencer-Rodgers,
Williams, & Peng, 2010), it has been shown that Asians tend to be more tolerant of
contradiction, think of events in terms of cycles rather than linearly, and place
importance on the balance of opposing forces that are viewed as mutually dependent. It
is possible, then, that learning to accept illness and disability when they occur is an
important part of achieving health in some Asian populations. The issue of achieving
optimal health is further complicated by the possibility that cultural differences in certain
phenomena may be moderated by genetic predispositions (Kim & Sasaki, 2014). Thus,
policy aimed solely at eradicating illness and disability may be incomplete, missing
important differences in cultural attitudes and beliefs and the possibility that these
cultural differences could potentially vary by genes.
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However, it is also important to consider the individual differences that exist between
people within a culture. People may have certain predispositions in terms of their biology,
personality, and behavior; thus, it will be important for public policy to allow for flexibility
in accommodating (p. 292) within-group variation. For example, individual differences in
extraversion versus introversion have been linked to a dopamine receptor gene, DRD2,
with carriers of the A1 allele being significantly more extraverted than noncarriers
(Smillie, Cooper, Proitsi, Powell, & Pickering, 2010). People who vary on levels of
extraversion would likely also differ in the types of situations and behaviors that best
foster social and mental well-being (Diener, Oishi, & Lucas, 2003; Moscowitz & Coté,
1995). In terms of health policy, what may contribute to optimal health for a more
extraverted A1 allele carrier, for instance, may not work as well for someone without this
allele. It is a further possibility that genes may express themselves differently depending
on a person’s cultural environment (e.g., Kim, Sherman, Sasak, et al., 2010); thus, a
thorough understanding of how best to promote the health of a population may require
policy that takes both individual predispositions and cultural influences into account.
Providing Effective, Efficient Care
Whether implemented at the local, regional, or national level by governments and
institutions, public health policy aims to promote health and prevent disease and illness
in a population. Due to the spread of health-related ideas and tools throughout the world,
people are sometimes faced with the challenge of adapting policy that has been imported
from other populations. However, effective policy involves far more than finding a one-
size-fits-all prescription for well-being. Policy must be tailored to fit various types of
populations, within which there will be differences in genetic predispositions and cultural
backgrounds. Although a highly personalized care system may be ideal for allowing each
person in a society to strive for better health in his or her own way, the reality is that
public health policy is bound by limited resources and is therefore under pressure to
maximize its efficiency. Negotiating a balance between the ideal of effective, personalized
care and the limitations surrounding its provision is a difficult challenge for public health
policymakers, but helping to do so may be one of the greatest promises of G × C
research.
There is much public interest in genetics as a potential tool to identify health risk factors.
Although such an approach has much promise, G × C findings caution against the
assumption that genetic associations with health outcomes are uniform. The findings of G
× C research provide a more nuanced understanding of how multiple factors interact in
relation to health outcomes, and this knowledge can be used to create more streamlined
policy that delivers effective care while limiting the waste of resources. By its mandate, G
× C research investigates micro- and macro-level influences on the individual in order to
predict outcomes. However, it goes beyond an additive model of these influences,
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demonstrating how one level moderates the other and uncovering information about
potential mediators. In doing so, this research clarifies when predictions based solely on
genes or culture are likely to be qualified due to an existing interaction. In terms of
health policy, this means preventing the misappropriation of resources that can occur
when genes and culture are considered in isolation. To give a hypothetical example,
imagine that Japanese policy based on genetic studies conducted in Germany led to
individuals with a particular gene being identified as at-risk and given an intervention,
when in actuality, that gene was not a risk factor given the cultural environment in Japan.
Another example is a scenario in which certain cultural elements in the United States
were found to account for a higher prevalence of a disorder in that country, so an
intervention policy aimed at widespread change was enacted, even though only people
with certain genetic predispositions would be negatively affected. In both situations, the
efficiency and effectiveness of policy are compromised by considering genes and culture
separately rather than adopting a G × C perspective. Of course, there will certainly be
cases in which a person’s genes or culture alone may predict a large portion of the
variance in certain health outcomes, but G × C research can help predict when any
particular association is qualified due to the interaction of genes and culture.
Utilizing a G × C framework can be effective for addressing health issues related to
etiology, course, and outcome in different cultures. Clinical depression has been
associated with certain genetic precursors, such as the presence of an s versus an l allele
of the 5-HTTLPR polymorphism, depending on the environment: Having an s allele puts
one at higher risk of depression if coupled with environmental risk factors, such as loss,
interpersonal conflict, or a stressful childhood environment (Caspi et al., 2003; Taylor et
al., 2006). As Maselko (see Chapter 23, this volume) explains, various risk factors in the
early environment may biologically calibrate a person in a way that can prove
maladaptive and increase risk of neuropsychiatric disorders in later life. However, the
prevalence and manifestation of depression and other mental health disorders (p. 293)
show considerable variability between nations and between groups within nations,
suggesting that cultural factors may also play a role in a person’s susceptibility (Chiao &
Blizinsky, 2010; Kleinman, 1982; Maselko, Chapter 23, this volume; Tsai & Chentsova-
Dutton, 2002; see also Chapter 22, this volume). In fact, as Yang and Benson (Chapter 22,
this volume) note, clinical diagnoses based on culture-specific symptoms may be more
appropriate for determining the actual prevalence of certain disorders. Yet it is not
enough to know about the genetic and cultural influences on depression independently if
one hopes to predict its occurrence. As discussed in this chapter, genes and culture
sometimes interact and therefore should be considered in concert. This has been shown
to be the case in depression, as the presence of the s allele of 5-HTTLPR is actually
associated with lower prevalence of the disorder in more collectivistic cultures, perhaps
due to the buffering effect of collectivistic cultural values (Chiao & Blizinsky, 2010). Thus,
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a thorough understanding of how and when not only genetic and cultural factors but also
their interactions predict health outcomes can be instrumental in developing effective,
efficient policy.
Conclusions on Gene × Culture Research and Public Health Policy
Genes play an important role in determining health risks and outcomes. As such, in
matters of how to protect and promote the health of a population, genetic research
provides indispensable recommendations about how to create good policy. However, it is
important to realize that public health policy is a part of culture—it is an institutional
force that shapes and is shaped by the values, norms, and beliefs of a people. Changes
made to public health policy change the cultural context in which a population lives.
Given that cultural research investigates how the cultural context affects health, it is
clear that cultural research on health may have important recommendations for effective
public health policy. However, it is not enough to consider genetic and cultural influences
on health in isolation and then utilize the information in an additive manner to create
policy. In many cases, it is likely that genes and culture interact with each other to
influence a person’s health, and only future research will be able to determine when this
should be expected. Therefore, the G × C framework promises to provide a richer
understanding of health for people across diverse societies.
Acknowledgment
Preparation of the manuscript was supported by National Science Foundation grant
BCS-1124552 to Heejung S. Kim.
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Joni Y. Sasaki
Joni Y. Sasaki Department of Psychology, York University, Toronto, Ontario
Jessica LeClair
Jessica LeClair Department of Psychology, University of California Santa Barbara,
Santa Barbara, California
Alexandria West
Alexandria West Department of Psychology, York University, Toronto, Ontario
Heejung S. Kim
Heejung S. Kim Department of Psychology University of California Santa Barbara
Santa Barbara, California
