Feminist scientists have offered clear frameworks and research methods for empirically investigating sex/gender within the biological sciences (Schiebinger 2008; Springer, Stellman, and Jordan-Young 2012; Ritz 2014; Singh and Klinge 2015; Kreiger 2003). Yet many scientists continue to struggle to operationalize gender in research design (Ruiz-Cantero et al. 2007; Jahn et al. 2017). In a review of epidemiological research conducted between 2006 and 2014, Jahn et al. found that researchers frequently discuss sex/gender in the introduction and discussion sections of a publication, but rarely actually incorporate sex/gender theory into study design or statistical analysis.
Recent policies by elite bioscience funders and journals that require documentation of sex differences in preclinical research exemplify and amplify this disconnect. For example, a 2016 National Institutes of Health (NIH) guidance and infographic (figure 1) released in tandem with its new mandate for analyzing sex in basic research included but one example of how gender may influence a biological trait: the simplistic and highly stereotyped scenario of the effects of wearing high heels on knee joints. The NIH’s guidance is a high-profile example of how the influence of gender on biological traits and health outcomes is frequently poorly understood or downplayed among biomedical researchers. Despite the routine inclusion of the concept of gender alongside that of sex in NIH literature, in practice the NIH assumes that biological differences between men and women stem primarily from intrinsic sex differences, and the NIH’s policy mandates only the consideration of sex, not gender, in research.
Feminist critics argue that new policies that require the study of sex as a biological variable reify sex differences and contribute to ideological conceptions of sex differences as binary, pervasive, and biologically fixed across human populations and organismic phylogenies. In overlooking gender, such calls to study sex are unlikely to redress urgent sex/gender health inequities. But such policies are also conceptually flawed. Though we may understand sex and gender as analytically distinct concepts, materially sex and gender are always interacting; human biology, including cells and biochemistry, should be understood as emerging in concert with the environment and experience broadly defined, rather than as a product of innate sex (Ruiz-Cantero et al. 2007; Jahn et al. 2017; Richardson et al. 2015; Joel et al. 2015).
The interaction of gender and biology goes much further than high heels. It is intimately entwined even with such seemingly basic molecular aspects of sex-biology as testosterone and estrogen levels. For instance, testosterone levels in men respond to childcare-giving, with men who provide care and live in close proximity to their infants exhibiting lower testosterone than men who do not (Gray et al. 2002; Fleming et al. 2002). This is not because men with low testosterone are more likely to become parents or engage in fathering; in a longitudinal study, men who became parents and lived with their children experienced decreases in testosterone (Gettler et al. 2011). A controlled experiment demonstrating that men who respond in a caring way to comfort a realistic crying baby doll show decreases in testosterone offers further support for a causal relationship between nurturance and testosterone levels in men (van Anders et al. 2012). Cultural or gender beliefs that influence parenting behavior would therefore be expected to influence testosterone levels, perhaps with attendant effects on downstream biological and health indicators. Women, too, experience shifts in testosterone levels in relation to parenting behavior (Kuzawa et al. 2010). Other research suggests that testosterone in women may respond to the experience of wielding power (van Anders, Steiger, and Goldey 2015).
Estrogen is also not solely a sex-related human biological variable. Women in calorie-replete, low-activity, post-industrial environments often have higher estrogen levels than women in more nutritionally limited environments (Ellison 2009); such women are also more likely to consume exogenous estrogen. Relatedly, because adipose tissue can aromatize hormones (aromatization is the process by which androgens are converted into estrogens), the global rise in obesity is theorized to be accompanied by heightened estrogen levels in men (Cohen 1999). While factors like the nutritional environment may not at first seem related to gender, in fact diet, obesity, weight-loss, and health-conscious behaviors are all strongly influenced by gender constructs (Wardle et al. 2004; Wardle, Haase, and Steptoe 2006, 644; Wells et al. 2012).
In this paper, we pose the biosocial turn – what Dorothy Roberts (2016) calls “the new biosocial science” – as an opportunity to creatively expand the range of empirical inquiries into gender as a biosocial variable and to newly articulate the importance of attending to gender in biological science. The Russell Sage Foundation’s new Integrating Biology and Social Science Knowledge initiative, introduced in 2016, refers to the biosocial turn as “a paradigm shift in the life sciences, spurred by the realization that many biological processes, rather than being fixed, immutable mechanisms that consign people to particular life outcomes, are instead fluid, dynamic responses to features of the social and physical environments humans inhabit.” This shift, the foundation writes, has “led researchers to launch interdisciplinary studies that seek to integrate approaches from the social and biological sciences, recognizing the potential for a deeper understanding of how social inequalities are initiated, maintained, and transmitted” (Russel Sage Foundation 2016).
In its call for proposals, the foundation highlights research on biological plasticity in relation to racial, ethnic, and socioeconomic variables in neuroscience, endocrinology, immunology, and epigenetics as exemplary of the biosocial turn. Here, as elsewhere, gender analysis and gender-related variables are largely absent in the burgeoning streams of research and theory that characterize the biosocial turn. Feminist scientists and science theorists, we argue, would do well to engage the reservoir of innovative new biosocial research as a resource for developing methods and theories for the study of sex/gender. Similarly, we call on biosocial scientists to attend as assiduously to gender as they have to other intersecting foci of analysis, such as racial discrimination and socioeconomic disadvantage.
Starting Frameworks: Racism, Poverty, and Biosocial Science
Studies of relationships among poverty, race, and biology provide a worthy model for building biosocial approaches to gender, body, and biology. Such studies have shifted in remarkable ways over the last several decades, from a frame of biological determinism to one in which the social and physical environment is recognized to have lifelong (and at times intergenerational) biological effects (Williams and Mohammed 2013; Kreiger 2014; Massey 2015). This unification of social science and biology has generated novel hypotheses and provided insight into biological phenomena. Research in this domain is broad, and ranges from examining how Jim Crow laws created disparities in health outcomes among US populations to unpacking the relationships between poverty and the developing brain. For example, researchers have shown, in large longitudinal datasets, that lower income is associated with reduced hippocampus volume and prefrontal cortex volume in growing children, perhaps due to stress (Hanson et al. 2012), and that race-based discrimination is related to blunted cortisol profiles in African American adolescents and adults, a sign of an exhausted hypothalamic-pituitary-adrenal system (DeSantis 2007).
A central claim of biosocial research on race is that social inequality has physiological outcomes. Stress hormones, immunological markers of inflammation, and chronic disease indicators like glucose are frequent targets of investigation. Recent years have seen a proliferation of methods for measuring discrimination, analyzing the factors that contribute to resilience, and examining how constructs such as neighborhood segregation may reflect structural racism. Presently, at least twenty-seven scales are available to assess how experiences of racism and discrimination relate to health (Bastos 2010). Newer methods, including measurements of telomere length and variation in methylation patterns among populations, are now being extended to studies of the biosocial dimensions of poverty and racial discrimination (Chae et al. 2014; McGuinness et al. 2012).
Based on this body of research, some suggest that many adult diseases might be considered developmental disorders due to the relationship between health and biology in later life and social conditions across the life course. In their description of the relationship between structural poverty and biology, Shonkoff and Garner state, “In simple terms, the process of development is now understood as a function of ‘nature dancing with nurture over time’ … That is to say, beginning prenatally, continuing through infancy, and extending into childhood and beyond, development is driven by an ongoing, inextricable interaction between biology (as defined by genetic predispositions) and ecology (as defined by the social and physical environment)” (Shonkoff et al. 2012, 234).
This, of course, sounds strikingly similar to longstanding feminist theoretical frameworks for understanding sex/gender as a dynamic developmental process. Fausto-Sterling eloquently describes how bones “imbibe culture” and develop in concert with environmental influences over the life course (Fausto-Sterling 2005). As Jordan-Young (2010, 286) writes, “Very few developmental endpoints are truly ‘final’; instead, they are interim states, with the possibility of growth and change until death. This is the meaning of plasticity. In this ongoing process, the interaction of physiological and experiential variables is iterative.”
Yet the full potential of gender as an organizing aspect of human experience across the life course still needs to be adequately recognized by biosocial scientists and in the human biological sciences in general. Some of this oversight may be the perception that racism and poverty are more profound, or more tractable, determinates of stratified health outcomes than gender. Some may be due the now-widespread appreciation of race as primarily a human social construct, leading researchers to eliminate biological hypotheses in favor of research programs that explore the social dimensions of racial variation. In contrast, while gender, like race and class, is a complex variable with pervasive influence across the life course, the alternative hypothesis of innate biological drivers of sex/gender differences remains robust, if not hegemonic, among biomedical researchers.
The widespread operationalization of racism and poverty as complex biosocial variables could provide a model for how researchers and funders might move to more rigorously study gender. Reigning biosocial models developed for research on race and social class, however, cannot be simply cross-applied to capture the interactions between sex, gender, and biology. For example, whereas inquiries into the influence of race and poverty in biological variation have focused on cumulative effects of stress, stress and discrimination may not be the most appropriate constructs with which to appreciate how gender contributes to human biological variation and health outcomes. Though gendered social and belief structures bestow women with lower social status than men, men often have worse health outcomes than women. Gender-based physiological stress may not be primarily related to discrimination; competition or safety concerns may be more appropriate constructs. Moreover, although the effects of gender will be pervasive across the life course, such effects may not be primarily stress-related.
Appreciation of the rich complexity and specificity of gender as a biosocial variable, we believe, is essential to efforts to integrate gender as a variable in all research – biosocial and beyond – and to the intellectual excitement and promise of sex/gender research. Despite the pleas of feminist theorists (Springer, Hankivsky, and Bates 2012), gender remains too-often portrayed in mainstream health science research as a unidimensional and independent causal factor that is either present or absent in a dataset: is gender at work, or not? Instead, gender must be conceptualized as a contextual theoretical construct that is pervasively intersectional and relationally multidimensional, in ways that we elaborate below.
Gender as Intersectional
Intersectionality is a key contribution of feminist theory that emerged from the critical insights of Black feminists regarding the influence of social location on experiences and perceptions. Any individual’s experiences lie at the intersections of multiple categories; gender is a constitutive part of our experiences of race, class, sexual orientation, ability, and immigration status, and our membership in these other social groupings influences our experience of gender (hooks 1984; Crenshaw 1991). Intersectional research recognizes and seeks to understand the variation within and between social categories (McCall 2005). For bioscientists who aim to better discern the effects of gender, and for feminist theorists who aim to support them, understanding gender as intersectional is essential in research design, choice of methodology, and analysis and interpretation of data.
Intersectional theory originated in cultural and legal studies and is now widely applied within the social sciences. But recognition of how social categories interact to create distinct experiences is also important in understanding human biology. For instance, the higher rate of allergic dermatitis in women compared with men is known to be a result of gender-linked differences in exposure and contact factors (Leyden and Kligman 1977; Modjtahedi, Modjtahedi, and Maibach 2004). But environmental factors, like chemical exposure at home and in the workplace or the tendency to wear jewelry made of certain metals, vary according to class, race, and gender, all of which interact to influence who develops dermatitis. Societal definitions of femininity and masculinity, which vary across class and cultural background, will influence the distress the dermatitis causes and the willingness to report to a medical provider. Class and immigrant status will affect access to medical care, and therefore affect measured dermatitis rates.
An intersectional perspective that includes gender is essential in scientific research design. In the broadest sense, intersectionality may be considered an epistemological starting point that influences how scientists approach the entire research process (Shields 2008; Hankivsky 2012). An intersectional perspective can provoke scientists to question their own location within the research process, in particular how their own social position may influence their background assumptions, hypotheses, methodology, and data interpretation. In this way, intersectionality shares common ground with other bodies of feminist theory, such as standpoint theory, in encouraging scientists to better understand how their own social location influences the research process.
Fundamentally, intersectionality theory helps researchers determine which variables may be relevant when exploring a topic and conceptualize how such variables may interact to influence a measured outcome. Intersectionality may be particularly useful in focusing attention on how effects may shift through time or vary across populations. Krieger’s recent analysis of breast cancer rates among Black and white women in the Jim Crow south exemplifies how an intersectional perspective can motivate temporal research hypotheses. Black women often have higher rates of estrogen receptor-negative (ER-) breast cancer than white women, a difference often proposed to have genetic roots. However, Krieger shows that Black women who were born and raised in the Jim Crow south have higher rates of ER- tumors than Black women born outside Jim Crow, indicating that cancer subtype is susceptible to social and environmental influences (Krieger, Jahn, and Waterman 2017).
To demonstrate how an intersectional perspective could motivate investigations of intra-population variation, consider research that accidentally uncovered how a race- and gender-related stressor affected African American college students (Richman and Jonassaint 2008). In 2006, researchers at Duke University conducted a project to understand the relationships between social stress and cortisol when an African American woman charged several Duke lacrosse players with rape. The case was highly publicized in the media and the campus atmosphere was charged. During this time, African American women, but not African American men, were found to have extremely high cortisol levels – so high, in fact, that they were unaffected by the study’s stress test. This research suggests that acute social context can manifest as stress experienced on the individual level and that gender, race, and other aspects of social location, such as being a Duke student, may all intersect to influence how our biology relates to our social circumstances.
An intersectional perspective allows scientists to hone hypotheses and predictions, or reexamine existing data, to better understand how race, gender, social class, and other factors interact to influence human physiology. Intersectionality must not be reduced to addition or multiplication. In an “additive model,” for example, race + gender + class = disadvantage (Bowleg 2008). Instead, categories intersect in dynamic, complex, and surprising ways depending on context, posing new questions for research (Choo and Ferree 2010). Interaction is an area in which many quantitative scientists excel. Scientists standardly use statistical techniques to consider how effect sizes vary in relation to other variables – techniques that, when critically deployed with awareness of the assumptions involved, are well-suited to exploring intersectional hypotheses (Else-Quest and Hyde 2016).
Consider, for instance, a study that uncovered an interaction between obesity and reports of race-based discrimination. McClure and colleagues set out to examine how ethnic discrimination interacts with health outcomes. They found no differences in levels of self-reported discrimination between obese and nonobese men. But obese Hispanic women reported higher levels of race-based discrimination than nonobese Hispanic women, and that discrimination was associated with higher fasting glucose in women (discrimination did not correlate with fasting glucose in men) (McClure et al. 2010). This finding suggests that obese women may be subject to race-based discrimination at higher rates than nonobese women, and that it has biological effects. Using these data, an intersectional perspective can provoke explorations of how glucose levels are partly an embodiment of racial discrimination and gender-based body norms. There is some evidence that weight stigma itself is associated with cortisol levels, independent of adiposity (Tomiyama et al. 2014), and experimental work demonstrates that exposure to weight-based discrimination elicits cortisol responses in women (Schvey, Puhl, and Brownell 2014). In the McClure et al. study, any physiological stress associated with race-based discrimination (including activation of the hypothalamic-pituitary-adrenal axis), must be also viewed as rooted in gender-based body norms. Hispanic women who violate the dominant culture’s body norms are subject to multiple, overlapping forms of discrimination and social stress, all of which impact their physiology. There are many similar examples of how an intersectional perspective can help to explain scientific research results that are accidentally uncovered – but rarely is intersectional gender theory explicitly sourced to motivate biological and biosocial hypotheses, research design, and interpretation.
Gender as Relationally Multidimensional
A relationally multidimensional perspective recognizes that gender is pervasive and that individuals experience gender at several different levels (Connell 2012). Understanding these multiple dimensions of gender is essential for biosocial scientists who seek to conceptualize how gender’s developmental effects may unfold. As gender theory classically holds, gender can be a set of prescribed social norms and mores imparted through interpersonal relationships and enculturation throughout life. Gender can also act structurally, through large-scale societal institutions, to limit individuals’ resources and choices. Finally, gender is composed of internal beliefs that orient individuals to the world and mediate their experiences within it. These different levels or dimensions of gender influence human health and biology in complex ways.
At one level, individuals biologically experience gender as societal norms that influence environmental exposures, behaviors, social interactions, diet, and a plethora of other factors. Take body size and diet, for example. While young boys do not tend to report body dissatisfaction, young girls begin to report a desire to be thinner around age six (Lowes and Tiggemann 2003). Body dissatisfaction in young girls is correlated with how girls describe their mother’s body image. Dominant cultural messages around body size and shape are internalized through home relationships, peer relationships, and media exposure (Sands and Wardle 2003). In a Swedish longitudinal study that followed children and adolescents for five years, girls who wished they were thinner at the beginning of the study were more likely to develop disordered eating habits, including repeat dieting, eating alone, skipping meals, and reporting that being thinner would improve their relationships and lives (Westerberg‐Jacobson, Ghaderi, and Edlund 2012). Nutrition and dieting behavior has biochemical effects, including on glucose metabolism, immunological factors, hormones, and neuropeptides. Through such mediators, social pressures that result in behavioral modifications to diet and body size will have inevitable effects on neurological pathways related to hunger, satiety, reward, and motivation, not to mention the associated mental health effects of monitoring food and body size. Dieting for weight loss is associated with reduced scores on cognitive function tests (Green 1994), and even moderate dieting in healthy subjects is well-known to impact amino acids in the brain and serotonin function (Anderson et al. 1990; Cowen et al. 1996). A fuller consideration of how gender relates to diet and body size would include understanding how eating disorders have recently risen among boys, how food choice can be conflated with gendered behavior (do “real men” eat salad?), and the societal pressure for boys and men to increase their body size, among other topics. In diet and nutrition, gender becomes biology, including neurological function and propensity for mental health disorders, via social norms, media messages, and relationships that impart ideology around ideal body types, which then influence individuals’ behavior. These sorts of socially influenced diet and body-monitoring patterns can create different developmental conditions across the life course according to sex/gender.
At another level, gender is experienced as a set of structural forces and patterns, reflected in employment options, economic class mobility, criminal sentencing, and other outcomes. Disparities in prison sentencing are an example of how structural forces impact human biology. An analysis of nearly 80,000 US criminal cases revealed that women receive shorter prison sentences than men do, even when controlling for the type of crime, prior record, income, and education (Mustard 2001). Controlling for the same factors, Black people receive longer sentences than white people. Due to these compounding structural forces, which embed gender- and race-based discrimination into our criminal justice system, Black men receive much longer prison sentences and are much less likely to receive no prison term than Black or white women or white men. Incarceration functions as both an acute and chronic stressor, and prison has a variety of health effects on inmates, including exposure to disease, violence, stress, isolation, and poor nutrition (Baillargeon et al. 2000; Massoglia 2008). Prison is associated with an increase in hypervigilance, social withdrawal, and psychological distancing, and many inmates develop post-traumatic stress disorders related to the prison experience (Haney 2003, 66). After release, formerly incarcerated individuals face poor job prospects and social stigma, which lead to lasting effects on mental health (Schnittker and John 2007). The prison system and the differential sentencing of Black men also impacts the biology of inmates’ families. Women with a family member in prison have poorer mental health and a higher risk of depression, obesity, cardiovascular disease, and stroke, even controlling for potentially confounding associated factors like early life events, income, or education level (Wildeman, Schnittker, and Turney 2012; Hedwig et al. 2014). The direct stress effects of having a family member imprisoned are compounded by loss of economic input into the family and high fees associated with incarceration. Understanding structural aspects of gender, in this case interacting with race to disproportionately distribute severe prison sentences to Black men, can help researchers to understand health effects that radiate through imprisoned men and their families.
A third dimension of gender is as a set of internal beliefs that orients how individuals interpret and experience the world, including gender roles and structural forces. An individual’s gender beliefs mediate their experience of the world, meaning the same event can carry different emotional and physiological valence depending on an individual’s gender beliefs (figure 2). For example, gender beliefs, including awareness of sexism, can influence cardiovascular and cortisol responses to laboratory stress tests, with experimental exposure to sexism eliciting different physiological responses depending on an individual’s beliefs (Eliezer, Major, and Mendes 2010; Townsend et al. 2011). Gender also mediates the effects of unemployment on psychological well-being, with marital status, gender, and broader societal beliefs around gender, such as who should be the household breadwinner, all acting to influence perceived distress (Artazcoz et al. 2004; Strandh et al. 2013). Such gender beliefs can be a part of cultural beliefs – for instance, there is a strong, positive relationship between beliefs in traditional gender roles and ethnic pride in some immigrant communities and, in turn, ethnic pride appears to protect against depression (Mahalingam and Haritatos 2008).
Through these multiple pathways, and others, gender organizes an individual’s experiences over their lifetime, interacting with other aspects of an individual’s social location throughout. To grasp the full picture of the relationally multidimensional character of gender as a component of body and biology ultimately requires a developmental and longitudinal framework. In recent research, Fausto-Sterling works to map and integrate current evidence for how sex/gender influences the first three years of life (Fausto-Sterling, Coll, and Lamarre 2012a, 2012b). Applying developmental systems theory to this critical developmental timeframe, Fausto-Sterling demonstrates how gendered interactions with parents and environments may intertwine with early and slight sex-linked differences to allow sex/gender to become embodied, leading to sex-differentiated behavioral and biological outcomes in young children. Such rigorous theoretical and hypothesis-building work lays the foundation for empirical research into how gender influences human health and biology across the life course.
Conclusion
Gender is a profound dimension of variation in human health and biology. As such, in contrast to the NIH’s exclusive emphasis on sex as a biological variable, when considering sex differences in human biology and health research, pervasive sex/gender interaction should be the default, null hypothesis (Springer, Stellman, and Jordan-Young 2012). Outside of sex research, we are experiencing a widespread shift in the scientific embrace of models of biological plasticity in relation to dynamic environments. We hope that sex and gender researchers will recognize the biosocial turn as an exciting opportunity to innovate, test, and sharpen sex/gender hypotheses. As in the case of biosocial research on racism, poverty, and biology, collaborations between social scientists familiar with gender theory and scientists schooled in quantitative research in large datasets will be essential to the development of methods and models for understanding gender as a biosocial variable.
We strongly suspect that gender is a lurking, underexplored variable in public health data sets, ripe for the picking. Feminist researchers should look to these datasets as resources for exploring challenging and novel hypotheses. For instance, recent work by Gettler et al. uses publicly available National Health and Nutrition Examination Survey (a large sample study designed to be representative of the US population) data to gain insight into how variation in social circumstances (such as residing with children) may be associated with hormone levels, which may in turn influence the development of adiposity and downstream health metrics (Gettler et al. 2017). Krieger similarly uses large data sets to demonstrate the health effect of Jim Crow laws on Black Americans (Kreiger et al. 2013). Other promising options include the National Survey of American Life- Adolescents, which has produced excellent analyses of how gender and ethnicity intersect with mental health and perceived discrimination in African Americans and Caribbean immigrant Black youth (Assari and Caldwell 2015; 2017, 14). In the modern funding environment, such large, open-access datasets combining biological, health, and social metrics represent a relatively untapped resource for quantitative work that explores explicitly gender-based biosocial hypotheses.
In rendering gender as a biosocial variable, researchers should take care not to occlude its multidimensionality. This may be particularly difficult because some dimensions of gender are better-studied than others. It is well-known that gender bias in occupations influences exposure rates to occupational hazards, and we increasingly recognize that broadly held societal beliefs about gender influence diagnosis rates and treatment recommendations (Messing et al. 2003).1 Less is known about how gender enculturation over the lifespan and internalized gender beliefs influence factors such as stress, health and disease risk, and willingness to seek treatment. Some of these factors may be easier to incorporate into existing research than others. For instance, occupational hazard exposure rates are currently available through data on employment categories and consumer data. In contrast, internal gender beliefs are rarely included in studies. All of this points to a need for better methodological tools to measure gender beliefs, gender-based stress, and similar concepts. Scientists must begin to include metrics and analyses of gender automatically within research, and funders should begin to support experimental pilots designed to develop better metrics for gender (Sharman and Johnson 2012).
Biosocial researchers have modeled interpretational and methodological boldness in forging new research on the biological markers of racism and poverty. Will gender, too, find its place at the forefront of the biosocial moment? Gender is hard to capture and operationalize, but so is any biosocial variable. The key, we have argued, is a rigorous understanding of gender as an intersectional and relationally multidimensional construct. Starting from this theoretical perspective, social and biological researchers can forge innovative hypotheses and pinpoint causal relationships between gender, other biosocial variables such as racism and poverty, and biology.
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- Chronic obstructive pulmonary disease (COPD) is one example of a disease that is underdiagnosed in women. In a random sample of physicians given a hypothetical case, COPD was diagnosed correctly for 58 per cent of men, but only 42 per cent of women (Chapman, Tashkin, and Pye 2001). [↩]
