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Institute of Medicine (US) Committee on Assessing Interactions Among Social, Behavioral, and Genetic Factors in Health; Hernandez LM, Blazer DG, editors. Genes, Behavior, and the Social Environment: Moving Beyond the Nature/Nurture Debate. Washington (DC): National Academies Press (US); 2006.

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Genes, Behavior, and the Social Environment: Moving Beyond the Nature/Nurture Debate.

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5Sex/Gender, Race/Ethnicity, and Health

In the search for a better understanding of genetic and environmental interactions as determinants of health, certain fundamental aspects of human identity pose both a challenge and an opportunity for clarification. Sex/gender and race/ethnicity are complex traits that are particularly useful and important because each includes the social dimensions necessary for understanding its impact on health and each has genetic underpinnings, to varying degrees.

Although there have been numerous genetic studies of sex and gender—and more recently race and ethnicity—over the past several decades, detailed information about the extent of our genetic similarities and differences did not reach the public’s attention until the completion of the Human Genome Project. With base pair comparisons possible across the individuals sequenced, the estimate that any two humans are 99.9 percent the same has raised our awareness that all humans are incredibly similar at the genetic level. Paradoxically, the evidence of vast numbers of DNA base pairs at which humans differ also became known at this time. It is estimated currently that any two people will differ at approximately 3 million positions along their genomes. Although there is some evidence that information about an individual’s sex or ancestry would provide information about the likelihood that he/she carries one allele versus another, it is typically a matter of probability—not a discrete or absolute determinant (even for the Y chromosome). While there is growing evidence of a number of significant differences between males and females in terms of health and health outcomes (IOM, 2001), “considerable controversy remains about the existence and importance of racial differences in genetic effects, particularly for complex diseases” (Ioannidis et al., 2004).

Previous chapters have discussed the contributions of the social environment, behavior, psychological factors, physiological mechanisms, and genetic variation to health. This chapter highlights the fact that the contributions of these variables are not monolithic and that fundamental individual traits, such as sex/gender and race/ethnicity, can change their meaning and health impact in different contexts. These complex traits are multifaceted, and the goal is to tease apart the facets at different levels of organization in order to identify which of them directly modulate health. This is a reciprocal process, because these various domains in turn inform our understanding of sex/gender and race/ethnicity. Failing to distinguish these different facets, both in the aggregate and within each level of analysis, will compromise the ability to obtain a more fine-grained understanding of how the different aspects of these fundamental individual traits interact to influence health.


Although the terms sex and gender are often used interchangeably, they, in fact, have distinct meanings. Sex is a classification based on biological differences—for example, differences between males and females rooted in their anatomy or physiology. By contrast, gender is a classification based on the social construction (and maintenance) of cultural distinctions between males and females. Gender refers to “a social construct regarding culture-bound conventions, roles, and behaviors for, as well as relations between and among, women and men, boys and girls” (Krieger, 2003).

Differences in the health of males and females often reflect the simultaneous influence of both sex and gender. Not only can gender relations influence the expression of biological traits, but also sex-associated biological characteristics can contribute to amplify gender differentials in health (Krieger, 2003). The relative contributions of gender relations and sex-linked biology to health differences between males and females depend on the specific health outcome under consideration. In some instances, sex-linked biology is the sole determinant of a health outcome—for example gonadal digenesis among women with Turner’s syndrome (due to X-monosomy). In other instances, gender relations account substantially for observed gender differentials for a given health outcome—for example the higher prevalence of needle-stick injuries among female compared to male health care workers, which is in turn attributed to the gender segregation of the health care workforce. The prevalence of HIV infection through needle-stick injury is higher among female health care workers because the majority of doctors are men, the majority of nurses and phlebotomists are women, and drawing blood is relegated to nurses and phlebotomists (who are mostly women) (Ippolito et al., 1999).

In yet other instances, gender relations can act synergistically with sex-linked biology to produce a health outcome. For example, the risk of hypospadias is higher among male infants born to women exposed to potential endocrine-disrupting agents at work. In this example, maternal exposure to the endocrine-disrupting agent (e.g., phthalates) arises because of gender segregation in the labor market (e.g., exposure among hair-dressers who are mainly women). Once exposure occurs, the risk of the outcome is predicated on sex-linked biology and is different for women and men, as well as for female and male fetuses, because only women can be pregnant, and exposure can lead to the outcome (hypospadias) only among male fetuses (all examples cited in Krieger, 2003).

Finally, in some instances, sex-linked biology can be obscured by the influence of gender relations in producing health differentials between women and men. For example, women’s lower risk of coronary heart disease (CHD) prior to menopause often has been ascribed to the cardioprotective effects of endogenous estrogens (a sex difference), but at the same time, the male/ female differential in heart disease also may reflect a diagnostic artifact; that is, the underdetection of heart disease among women caused by an unconscious bias among physicians to ascribe the symptoms of a real heart attack among premenopausal women to some other disorder (a gender difference) (McKinlay, 1996). Arber and colleagues (2006) demonstrated the presence of such bias in a randomized experimental study involving video-vignettes of a scripted consultation in which patients presented with standardized symptoms of CHD. The videotaped consultations were identical in terms of symptoms, but the patients’ gender, age (55 versus 75), class, and race varied. A probability sample of 256 primary care doctors from the United States and the United Kingdom viewed these video-vignettes and the results demonstrated that the diagnosis and patient management decisions were significantly affected by the patient’s gender. Women were asked fewer questions and received fewer diagnostic tests compared to men. The authors found evidence of “gendered ageism,” in which middle-aged women presenting with classic symptoms of CHD were asked the least amount of questions and prescribed the fewest CHD-related medications (Arber et al., 2006).

Besides the behavior of health care providers, a number of other social processes are recognized as contributing to gender inequalities in health. At the macro (or societal) level, these include the gender segregation of the labor force (alluded to above) and gender discrimination. Gender segregation of the workforce and gender discrimination together contribute to the persistence of the gender wage gap—that is the fact that women earn less than men in paid employment (Reskin and Padavic, 1994). The gender wage gap in turn contributes to the feminization of poverty. Women— particularly female heads of households—are over-represented among poor households in virtually every society. The adverse health effects of poverty (see Chapter 2 of this report) therefore fall disproportionately on women and their children. At the societal level, indicators of women’s economic autonomy or lack thereof (e.g., rates of poverty among women, the size of the gender wage gap, and the proportion of women in managerial and technical professions) have been shown to closely mirror women’s health status (mortality and rates of disability) (Kawachi et al., 1999).

Within households, gender relations also are characterized by the unequal division of labor (e.g., care giving roles are more often assumed by women), as well as by the unequal exercise of authority and power. Women with paid work are more likely than men to engage in the “second shift” (Hochschild, 1989), taking on responsibilities for childcare, housework, and care giving. The stresses associated with care giving, particularly providing care for ill spouses, have been linked to adverse health outcomes, such as cardiovascular disease (Lee et al., 2003).

Men and women differ biologically because their primary reproductive hormones are different. Less well recognized are the sex differences in certain aspects of immune function that stem from the fact that women and men face different immune challenges. In women, but not in men, successful reproduction requires the support of “foreign bodies”—sperm and a developing fetus. Moreover, as is the case for many other mammalian species, other aspects of male and female biology also may differ because they have different roles in caring for offspring or function in different ecological niches, thus reducing parental competition. For example, a brief stressor mimicking a burrow collapse results in a more pronounced long-term innate inflammatory response in female rats than in male rats exposed to the same stressor (Hermes et al., 2006). Given that females become aggressive during lactation and may likely suffer from wounding, selection would favor those who can mount an inflammatory response that is effective enough to enable them to survive at least long enough to wean their nursing pups. Given that males do not behave paternally in this species, a selection pressure at this juncture of the reproductive lifespan would not be as strong.

The central point is that sex differences in health and risk for disease are not simply minor correlates of differences in reproductive hormones. They also result from deeply embedded highly coordinated physiological systems that have evolved to serve sex-specific functions. For example, women must have sufficient energy reserves to sustain the huge metabolic demands of pregnancy and lactation. Thus, it is not surprising to see sex differences in energy metabolism. In men, insulin functions as a negative feedback signal in the regulation of fat metabolism, reducing body fat, but this does not occur in women, where it serves to conserve women’s fat stores (Hallschmid et al., 2004). Sex hormones have both genomic and nongenomic effects on the accumulation, distribution, and metabolism of adipose tissue, including the regulation of leptin (Mayes and Watson, 2004). Leptin has long-term effects on the regulation of body weight, mediated through appetite, energy expenditure and body temperature. Marked sex differences can be seen in levels of leptin, which in men (but not women) are associated with hypertension (Sheu et al., 1999). Moreover, leptin stimulates cellular components of innate immunity, stimulating T-cells, macrophages, and neutrophils, as well as preventing the programmed cell death of neutrophils (apoptosis) (Bruno et al., 2005). Indeed, leptin is increased during infections. Thus, fat metabolism and immune functions are differentially controlled in men and women, and the implications for disease risk and treatment are only now beginning to be explored.

In recent years, there has been an increased focus on understanding the differences and similarities between females and males at the societal level (i.e., behaviors, lifestyles, environment), at the level of the whole organism, and at the cellular and molecular levels (IOM, 2001) (see Table 5-1). There is, of course, huge variation in the degree of overlap in the physical traits of men and women. Sexual dimorphism is typically reserved for traits for which the difference is relatively large, such as height (population overlap of one standard deviation—10 percent of men are smaller than the average woman), while smaller differences are typically termed as sexually differentiated, such as hand shape (Williams et al., 2000).

TABLE 5-1. The Independent Dimensions of Sex/Gender in Humans.


The Independent Dimensions of Sex/Gender in Humans.

A significant number of studies have documented the differences between sexes across the lifespan. Genetic and physiological make up, in addition to an individual’s personal experiences and interactions with the environment, can play a large part in observed sex differences such as varying incidence and severity of disease. This may be the result of differences in exposure to the risk factors, the routes of exposure and processing of a foreign agent, and cellular responses to the body. Differences cannot simply be attributed to hormones. Sex affects behavior, perception, and health in multiple complex ways. Differences in the sex chromosomes are but one factor, although a significant one for a small number of diseases influenced by gene dosage (i.e., specific to the X chromosome), or for genes found only on the Y chromosome (IOM, 2001).

In order to understand the impact of sex/gender on health, it will be necessary to deeply appreciate that it is not a simple categorical variable, ultimately definable by the presence or absence of the Y chromosome. Rather, it is a multifaceted variable, biologically, psychologically and socially, with each facet having different effects on health and risk for disease. Each facet is oriented along dimensions that typically covary so strongly that many assume that they are inseparable (see the typical phenotypes of sex/gender in Table 5-1). However, there can be variance, if not sex reversals, along a given dimen sion without comparable variation in the others. This disassociation clearly demonstrates their independence. Thus, future research on the impact of interactions among social, behavioral, and genetic factors on health must determine which of these facets and dimensions contribute directly to sex differences in health and which are merely correlates.

An example helps to illustrate human variation. There are XY individuals with a genetic variant of the androgen receptor who are unambiguously heterosexual women and who are engaged in feminine social roles ranging from actresses to Olympic athletes. They have testes and hormone levels higher than those of pubertal boys. But, because their androgen receptors do not bind androgen, their genitalia, secondary sex characteristics, and musculature are fully differentiated as women. Until the Olympic committee changed its definition of sex from genetic to hormonal sex, such women had to compete as men. These women share the health risk of gonadal cancer, and typically their testes—their source of estrogens—are removed. However, their social roles—as actresses or Olympic athletes, for example— are better predictors of cardiovascular health and risk for muscle injury.

Moreover, sex/gender differences in health represent another arena that demonstrates powerfully that taking only a statistical approach to the problem of gene-environment interactions, and simply dividing variance in health into main effects and interactions, blinds researchers to the multitude of inseparable gene-environment interactions that have co-evolved to enable survival and successful reproduction. An excellent model for conducting research on development in dynamic terms was put forth in the National Research Council/Institute of Medicine (NRC/IOM) report entitled From Neurons to Neighborhoods: The Science of Early Childhood Development (2000).

The constructs of race and ethnicity, which have similar limitations and complexity as sex and gender, are explored in the following section.


Unlike sex, race is not firmly biologically based but rather is a “construct of human variability based on perceived differences in biology, physical appearance, and behavior” (IOM, 1999). According to Shields and colleagues (2005),

with the exception of the health disparities context, in which self-identified race remains a socially important metric, race should be avoided or used with caution and clarification, as its meaning encompasses both ancestry … and ethnicity …

Both race and ethnicity can be potent predictors for disease risk; however, it is important to emphasize the distinction between correlation and causation and to explore interactions among factors, while rejecting a unidirectional model that moves from genotype to phenotype.

With the increased attention being given to racial disparities in health, the definition of race has come under increased scientific scrutiny. Race continues to be one of the most politically charged subjects in American life, because its associated sociocultural component often has led to categorizations that have been misleading and inappropriately used (Kittles and Weiss, 2003). Definitions of race involve descriptions that are embedded in cultural as well as biological factors, and a careful distinction must be made between race as a statistical risk factor and as causal genetic variables (Kittles and Weiss, 2003). Thus, genetics cannot provide a single all-purpose human classification scheme that will be adequate for addressing all of the multifaceted dimensions of health differentials. It may be found that some alleles associated with destructive or protective factors related to disease and health are created, modified, or triggered by cultural and contextual factors.

Race also is notoriously difficult to define and is inconsistently reported in the literature and in self-reports. Self-report has been the classic measure for race and is still reliable in some cases given certain caveats. The usefulness of the data derived from self-reports of race in health research, however, has been the subject of much debate (Risch et al., 2002; Cooper et al., 2003; Burchard et al., 2003). In 2003, Burchard and colleagues wrote the following:

Excessive focus on racial or ethnic differences runs the risk of undervaluing the great diversity that exists among persons within groups. However, this risk needs to be weighed against the fact that in epidemiologic and clinical research, racial and ethnic categories are useful for generating and exploring hypotheses about environmental and genetic risk factors, as well as interactions between risk factors, for important medical outcomes. Erecting barriers to the collection of information such as race and ethnic background may provide protection against the aforementioned risks; however, it will simultaneously retard progress in biomedical research and limit the effectiveness of clinical decision-making.

Although there are requirements for reporting race in specific categories in federally sponsored research, the Office of Management and Budget directive that set out this requirement notes that these are not scientific categories. The National Institutes of Health (NIH) has reiterated that researchers should collect any additional data that would be more useful or appropriate for their specific projects. Researchers would advance our understanding of race and ethnicity by addressing factors that are related to race such as geographic area of ancestry or by providing greater detail about ancestors. In the 2000 Census, less than 3 percent (6.8 million) of the total population reported being of mixed race, and 7 percent of these 6.8 million people reported a heritage that included 3 or more races (Grieco and Cassidy, 2001). However, even those who report one race may have very complex backgrounds in terms of geography. For example, a black American could have origins in East Africa, West Africa, North Africa, or the Caribbean.

NIH has prescribed that all research projects will involve a good faith effort to include minorities when appropriate. By requiring funded research to make appropriate accommodations for minority subject recruitment, NIH has encouraged scientists to begin to consider issues of race, ethnicity, and culture in research as never before. Some of the emphasis on learning more about minority populations arises from the acknowledgement of the stark disparities in health when comparisons are made across racial groups.

Health Disparities and Race

Disadvantages in health exist for many groups such as Pacific Islanders, Hispanics, and Native Americans, when compared to Caucasians. Asians on many accounts are found to have more positive health profiles but are not without disadvantages in comparison with Caucasians (Whitfield et al., 2002). Literature on health disparities has documented African American/ Caucasian differences in major causes of death such as hypertension, diabetes, fatal stroke, and heart disease. The gap in health seems to be greatest between the ages of 51 and 63 (Hayward et al., 2000). Despite the 30-year trend toward convergence, the age-adjusted mortality rate from all causes of death for African Americans remains 1.3 times greater than that of Caucasians. This differential produces a life expectancy gap between African Americans and Caucasians of 5.3 years for men and 4.4 years for women (Hoyert et al., 2006). Furthermore, it also appears that African Americans are less likely to survive to middle age, and if they do, they are more likely to have health problems (Hayward et al., 2000).

Health disparities are a major public health concern and are a major emphasis of research across the country and across many disciplines. Genetic, social, and behavioral studies have shown that there are a large number of correlated differences across ethnic groups at the genetic, cultural, and environmental levels. From a methodological point of view, any comparison across ethnic groups from a single disciplinary vantage point will have a tremendous confounding issue. It is only by studying the multiple levels and risk factors simultaneously within subgroups (defined by ethnicity, geography, genetic backgrounds, and exposures to the environment) that we will begin to understand how specific combinations of environmental factors combine with specific combinations of genetic factors to give rise to health differences.

Race and Genetic Variation

Geographic origin, patterns of migration, selection, and historic events can lead to development of populations with very different genetic allele frequencies. Historically, to the extent that barriers such as large deserts or bodies of water, high mountains, or major cultural factors impeded communication and interaction of people, mating was restricted within group, producing genetic marker differences and thus, differences in the presence of specific disease-related alleles (see Box 5-1) (Kittles and Weiss, 2003). In line with this, Burchard and colleagues (2003) found that population genetic research of the last 20 years shows that the largest genetic differences occur between groups separated by continents. However, an analysis of 134 meta-analyses of genetic association studies by Ioannidis et al. (2004) found “at least 85% of genetic variation is accounted for by within-population interindividual differences, not by differences between groups.”

Box Icon

BOX 5-1

The Importance of Ancestral Origin. Despite the complexities and care that must be taken in attributing phenotypic differences to genetic differences among races, much may be gained by focusing on disorders that occur more frequently within a well-defined (more...)

Claims about correlations among genetic variation and race vary widely. Self-identified race/ethnicity corresponds highly to genetic cluster categories according to Tang and colleagues (2005); of the 3,636 individuals studied, less than 1 percent exhibited differences between their self-identified race/ ethnicity and genetic cluster membership. However Bamshad (2005) in his review of the literature suggests that while genetic ancestry and geographic ancestry are correlated, race and genetic ancestry is only modestly related.

Research into differences among population groups often uses single nucleotide polymorphism (SNP) markers to identify phenotypic variation. SNPs may affect a given phenotype at multiple levels so that a given protein is altered in its sequence, in its proper place in the organism, and in its proper development time. A codon may be altered that leads to protein with an altered amino acid sequence which results in either an inactive or a hyperactive form of the protein in every cell where the protein is expressed. A part of the promoter may be altered such that a protein is absent in some of its normal tissues but not in others or is present in the wrong tissue or at the wrong time. An mRNA splice site may be altered such that protein isoforms are inappropriately expressed in a given tissue. A target sequence may be altered leading to aberrant targeting of the protein to cellular compartments. An untranslated sequence in the 3′-end of the gene may be altered to give a longer or shorter period of existence for a given mRNA. Finally, an epigenetic mechanism may be altered leading to changes in developmental timing of a particular protein.

Due to evolutionary history, sequence is more highly conserved in cod ing regions when compared to noncoding regions. This feature creates the following situation in the genetic research of traits of great importance for public health: the interactions of SNPs with environment will be subtle and so will require large studies comprised of large cohorts carefully phenotyped for large numbers of environmental factors and genotyped for thousands of SNPs. Yet another challenge facing investigation using SNPs is that the bulk of SNPs found are not located in the conserved coding regions. Coordination of researchers involved in studies of humans, of other mammalian systems, of protein biochemistry and site-directed mutagenesis, and of cellular biology will be required to understand the interaction of genes and environment required to make an impact on public health in the United States.1

The use of SNPs also may aid in understanding variations in health outcomes among racial/ethnic groups. Using a sample that included a small number (less than 50 each) of African Americans, Hispanics, Asians, and Europeans, Smith et al. (2001) found that distribution of genetic variants showed a median difference of 15 to 20 percent at both the microsatellite and SNP markers. Additionally, 10 percent of all markers showed a difference of 40 percent or more. To the extent that findings from this study reflect the larger population, one would hypothesize that an allele with 20 percent or greater frequency in one racial group would also be found in another racial group, while those with a frequency below 20 percent would most likely be race-specific.

According to Burchard (2003), “race-specificity of variants is particularly common among Africans, who display greater genetic variability than other racial groups and have a larger number of low-frequency alleles.” Burchard concludes that variation among racial groups in the occurrence of variant alleles underlying disease or normal phenotypes may lead to differences in occurrence of the phenotypes themselves. For example, in some studies of hypertension, variation of SNPs at different allelic frequencies from one population to another suggest that higher rates of hypertension found in African Americans may be related to the alternations in DNA that vary by group (Cui et al., 2003; Erlich et al., 2003). Prior to drawing conclusions, however, one must consider alternative explanations that include gene-environment interactions as possible contributors to observed disparities (Whitfield and McClearn, 2005).

Arguments that genetic factors cannot be a major cause of health disparities arise out of a paradigm of genetic research that focuses on independent effects of genetics. Research on health disparities is an important opportunity to integrate biological knowledge with social and behavioral knowledge in order to better understand the determinants of disease. Social factors are certainly key contributors, but there is evidence that those factors do not account for all health differences (Braun, 2002). Conversely, solely focusing on molecular genetics ignores the dynamic nature of populations of DNA and the complex relationships among genes, organisms, and environment.

Considerable literature exists concerning how environmental processes, events, and circumstances contribute to development and behavior in ways that influence health as well. Some of these environmental factors are negative and are found to be more prevalent in the development of minorities. Some research suggests that African Americans may experience events and circumstances that have sociocultural origins that significantly influence development over the life course (Levine, 1982; Spencer et al., 1985; McLoyd and Randolph, 1985; Jackson, 1985; Jackson and Chatters, 1986). These sociocultural influences contribute to differences between racial groups as well as to differences between individuals within groups (Krauss, 1980; Levine, 1982; Jackson and Chatters, 1986). Sources of individual differences in health and behavior in African Americans have implications for the quality of late life as well as quantity of late life (years of life remaining). The multiple jeopardy hypothesis, for example, holds that negative environmental, social, and economic conditions during the early years of life for African Americans detrimentally affect social, psychological, and biological conditions in late life (Jackson, 1989). Although this hypothesis attempts to explain health differentials experienced by African Americans relative to Caucasians, it is critical to remember that there is considerable individual variability in these conditions within the African American population and within other minority populations.

In the search for the environmental origins of health differentials among ethnic groups, much of the earlier research focused on behaviors and social structures (NRC, 2001). The complexity of variables within racial groups presents challenges to identifying single, simple causes for poor health among racial/ethnic minorities. For example, environmental and behavioral variability among Hispanics evinces similarities and differences among its subgroups. This racial/ethnic (Hispanic) category consists of people from more than 20 different origins, but the people share a common language. Conversely, the groups within the Hispanic category significantly differ in their regional concentrations in the United States (e.g., Mexicans in the Southwest, Puerto Ricans in the Northeast, and Cubans in the Southeast) (NRC, 2001). In the United States, a significant relationship between race/ ethnicity and foreign birth status also is found (NRC, 2001). Contrasts between immigrants and their U.S.-born peers suggest an advantage in health status to those who are foreign born (Singh and Yu, 1996; Hummer et al., 1999), at least until they become oriented to American culture. Then the advantage decreases (Vega and Amaro, 1994).

Perhaps the most studied social variable in the search for environmental origins of health differentials is socioeconomic status (SES) (see Chapter 2). For example, substantial differences exist between African Americans and Caucasian Americans with regard to their socioeconomic position. Thus, according to the U.S. Census Bureau’s Current Population Survey (DeNavas et al., 2005), the median income for African American households was $30,134 in 2004 (the latest year for which data are available), compared to $48,977 among non-Hispanic Caucasian Americans. Poverty rates among African American households are nearly three times as high (24.7 percent in 2004), compared to Caucasian households (8.6 percent). Comparing households reporting similar levels of income, African American households report substantially lower levels of net wealth compared to Caucasian Americans (Conley, 1999). These differences in income and wealth are partly attributable to differences in average educational attainment when comparing African Americans (17.6 percent of whom reported having bachelor’s degree or higher in 2004) to Caucasian Americans (30.6 percent of whom had a bachelor’s degree or higher) (U.S. Census Bureau, 2005). Racial differences in intergenerational transfers of wealth, the growth of home equity over time, and access to federal programs that facilitated home ownership after World War II have played an even larger role in racial disparities in wealth over time (Oliver and Shapiro, 1997). African Americans also report higher levels of uninsurance (19.7 percent in 2004) compared to Caucasian Americans (11.3 percent) (DeNavas et al., 2005).

Research reveals that these socioeconomic differences between races account for a substantial portion of the racial disparity in health outcomes (IOM, 2000). At the same time, adjusting for socioeconomic differences does not completely eliminate racial disparities for all health outcomes (e.g., infant mortality). In other words, there is an independent contribution of racial/ethnic status to disparities in specific health outcomes. These residual health differences may result from the adverse health consequences of perceived discrimination for African Americans (IOM, 2000), from potential differences in biological susceptibility to disease, and/or from gene-environment interactions.

A universal finding is that people with higher indices of SES (education, income, and occupational grade) have lower mortality rates and lower rates of most diseases. However, more research is needed on how particular markers of SES show linear or nonlinear effects on health status (NRC, 2001). These gradients will be critical to understand in examining how genetic influences vary in social environments.

One of the future and formidable challenges to using the information ascertained from adding genetic information to examinations of health differentials is to gain an understanding of the underlying effect genes have on health within these complex environments. It may be found that the polymorphisms that occur in genotypes are destructive or protective factors related to disease and health that are created, modified, or triggered by cultural and contextual factors (Whitfield, 2005; Whitfield and McClearn, 2005).


Sex-linked biology and gender relations, as well as the concepts of race and ethnicity, require conceptual clarity in order to determine the interactive influences of each in giving rise to health differentials. To narrowly focus on such concepts impedes an appreciation of the rich variety among humans, however attention must be given to these and other categories in order to conduct meaningful research assessing the impact on health of interactions among social, behavioral, and genetic factors. For example, although a consistent genetic effect across racial groups can result in genetic variants with a common biological effect, that effect can be modified by both environmental exposures and the overall admixture of the population. The challenge is to parse out how health outcomes are influenced by genetic variations, behavioral and cultural practices, and social environments independently and as they interact with each others, while recognizing that sex, gender, race, and ethnicity may play important roles in their own right and because of their social meanings.


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The committee would like to thank Kent Taylor, Ph.D., Associate Director, Genotyping Laboratory, Medical Genetics Institute at Cedars Sinai Medical Center for his explication of SNP variation.

Copyright © 2006, National Academy of Sciences.
Bookshelf ID: NBK19934


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