Beyond Sex and Gender Differences: The Case for Women’s Health Research
by Liisa A.M. Galea, Bonnie H. Lee, Romina Garcia de leon, M. Natasha Rajah, and Gillian Einstein:
Introduction
Sex and gender are acknowledged as important factors to consider in health. Sex refers to the biological and physiological differences between males, females and intersex individuals, such as chromosomes and hormones. Gender is a psychosocial construct, and is not only gender identity but how a given society treats, and how support systems differ, depending on gender identity. Worldwide, more attention is being paid to sex and gender differences in health outcomes, including during the COVID-19 pandemic. Females are more likely to be diagnosed with certain diseases such as auto-immune diseases and mood disorders, whereas males are more likely to be diagnosed with neurodevelopmental disorders such as autism and attention hyperactivity disorder.
Importantly, beyond disease risk, there are sex differences in manifestation of disease and in disease mechanisms. Shockingly, females are more likely to be diagnosed with the same disease later than males, they experience greater adverse effects from new therapeutics than males, and are often described as having “atypical” symptoms for a given disease even when that disease may be more prevalent in females. Although there is more research to be done, the reasons for these disparities are, in part, due to the fact that historically, males are more likely to be used in both animal (preclinical) and human (clinical) research.
In recognition of these discrepancies in health, many funders worldwide are mandating the incorporation of sex and gender in research and in clinical trials. The National Institutes for Health Research (NIH) was the first to mandate the inclusion of women in their sponsored clinical trials in 1993 and in all clinical research in 2001.
In 2016, NIH expanded this mandate to consider sex as a biological variable (SABV) in biomedical research. However, NIH has no strict guidelines to ensure appropriate incorporation or analyses of SABV in the published research. Analyses of published reports suggest that only 28% of clinical trials and only 15% of bio-medical data are reporting their data by sex and these percentages are not affected by NIH funding status. The Canadian Institutes for Health Research (CIHR) established more stringent guidelines, initiated in 2010, that called for sex and gender-based analysis (SGBA), which was eventually mandated in 2019.
Since 2002, the European Union has had various stages of requirements to include women and gender in research, such that in 2002, women needed to be considered in participation of research and in 2021 gender considerations in research were required in grant applications for Horizon Europe.
It is important to keep in mind that the mandates enacted by these countries were due to the underrepresentation of women in clinical trials and in the medical literature, which has resulted in an imbalance of our knowledge of men versus women’s health and perpetuated health inequities between the sexes and genders. However, even though funders and publishers are requiring researchers and authors to pay more attention to sex and gender in research, a number of implementation issues have arisen.
With the advent of funding mandates for inclusion of sex/gender in research in the United States, Canada and Europe, there has been a dramatic shift in the percentage of studies that use both males and females from 38% to approximately 70% of studies. On the face of things, this is great news, however, the published data are rarely disaggregated by sex and are even more rarely analyzed using sex as a discovery variable (~ 5%). During the COVID-19 pandemic, where sex differences in mortality, immune response, and vaccine efficacy are documented, only 4% to 24% of clinical trials included an analysis with data disaggregated by sex.
Clearly, more needs to be done to underscore the importance of studying, and not just accounting for, sex and gender differences in health outcomes. This chapter will explore implementation issues in the mandates for sex inclusion, the many types of sex differences, the history of how the lack of women’s health research converged with the need for sex and gender research, why sex and gender research will not fully address the lack of our understanding of women’s health, and finally, how female-unique experiences, such as menstruation, pregnancy and menopause influence female physiology.
Why the mandates don’t necessarily further women’s health
The mandates for NIH-sponsored clinical trials and SABV in biomedical research do not provide recommendations concerning either design or statistical analyses. This may be understandable, as there is not always consensus on best practices for incorporating sex and gender in the analysis of data. Moreover, we must recognize that NIH-sponsored trials account for only a small subset (~5%) of clinical trials and NIH-funded research only accounts for ~25% of published biomedical papers. Importantly, even with the mandates from NIH, CIHR, and the European Union, there has been little disaggregation by sex in clinical trial outcomes or in the basic literature.
As noted above, SABV and SGBA have been implemented in an effort to rectify the lack of females/women as research subjects and participants. But will the mandates do enough to move the dial for women’s health? Past data indicates that these mandates do not go far enough. Even though NIH-sponsored clinical trials have been mandated to include women since 1993, fewer than 30% analyzed their outcomes using sex as a factor (which includes using sex as a covariate rather than as a discovery variable).
Thus, although 75% of NIH funded randomized control trials included both males and females only 26% of those trials used sex/gender in the analyses of results. A similar situation is seen in a survey of research in Neuroscience and Psychiatry, as only 40% of studies over the last 10 years have analyzed their data using sex as a variable, which includes analyses uses a covariate (described below). Thus, despite the large uptake in the inclusion of males and females in studies in 2019 compared to 2009, the majority of studies do not assess the impact of sex or gender on their data and consequently there is no corresponding increase in our understanding of whether and how sex and gender affect study outcomes.
Moreover, of the 30% to 40% of studies that have included sex as a factor in their statistical analyses, most use it as a covariate. This is problematic because it removes the linear association in variability that is a result of sex/gender, effectively “controlling” for any possible differences. Furthermore, often in regression modeling, it is only the main effect of sex/gender that is controlled for and not the interaction of sex with other variables of interest.
Yet, it may well be the interaction of sex/gender with a treatment variable that is significant. An interaction effect is when the effects of one variable (drug treatment) depend on the other factor (sex). For example, one might note that a treatment is beneficial for one sex but detrimental for another indicating that a significant interaction of sex by treatment is present.
Thus, if the majority of researchers that do use sex/gender as a variable use it as a covariate to control for differences based on sex/gender or do not explore interaction effects with sex/gender, we will be no further ahead in our discovery of how the sexes/genders may mediate different manifestations/risk/mechanisms of disease and require different forms of treatment for that disease.
What history then tells us is that the increased use of both sexes will not necessarily translate to discovery of whether sex differences exist in the research conducted. It is possible that with more time, the overall percentages of papers examining sex/gender as discovery variables will improve. However despite the earlier adoption of mandated inclusion of both sexes by NIH in clinical research in 2001, this has not significantly improved analysis with sex as a discovery variable over the last 10 years in Psychiatry or Neuroscience which is currently at 5% of these studies. Importantly, when researchers examine the influence of sex as a discovery variable, they find sex differences in treatment efficacy for transplant, stroke, and glioblastomas, suggesting that this is an important variable to consider to improve lives.
Misconceptions in sex differences research
So what are the barriers researchers face to incorporating SABV and SGBA? Studies are beginning to investigate perceptions of animal researchers and these studies reveal two main misconceptions: (1) that studying sex differences is equivalent to sexism and (2) that sex differences research can be limited to the inclusion of males and females in the initial studies, as opposed to later phases of investigation.
The assumption that studying sex differences is sexist is misdirected. Simply because there is a sex difference in a trait does not mean that one sex is inferior to the other – or that one trait is better than the other. It means there is a difference between the sexes which may or may not translate into an important difference in health outcomes between the sexes. A smaller structural brain volume is often used as an example of inferiority. However, smaller brain volumes or cortical surface areas may in fact reflect greater efficiency in brain function.
Studies show that in females, decreases in the complexity of hippocampal dendritic arbors or reduced hippocampal volume during pregnancy, are not associated with reduced function, but rather, improvements in spatial memory and maternal attachment, respectively. We need to be careful to ensure that our implicit biases (e.g. bigger is better) do not imply biological inferiority in one sex over the other and do not prevent us from advancing knowledge.
Indeed, studies have reported sex differences in brain activation patterns in humans and rodents during specific memory tasks, even when there are no significant sex differences in memory performance. Such findings have been interpreted as reflecting sex/gender preferences in cognitive strategies utilized during the performance of cognitively demanding tasks, which may be influenced by biological differences or by the different sociocultural experiences of women and men. But one thing is clear, no matter what the reason for these differences, researchers will need to consider these differences in order for treatments to be equally effective across sexes and genders.
Thus, sex differences may be reflected in many ways (Fig. 45.1). If researchers assume that sex differences should only be tested in the trait of interest and not the neural or molecular mechanisms underlying that trait, they may miss important discoveries that may have implications for precision treatment.
Many instances in neuroscience exist in which there may be no apparent sex difference in a particular trait, but the underlying mechanisms driving it can be quite different between the sexes. For example, the levels of neurogenesis in the hippocampus of adult rodents is equivalent between the sexes but the temporal dynamics and maturation rate of those maturing neurons show large differences between the sexes. Furthermore, pain hypersensitivity is mediated by different mechanisms in males and females; microglia mediate pain hypersensitivity in males, whereas T-lymphocytes mediate pain hypersensitivity in females.
Each of these examples illustrate that an outcome (i.e., neurogenesis/memory performance, pain sensitivity) may not differ by sex, but the mechanisms driving the outcome can be quite different. These findings in turn suggest that treatments for increasing neurogenesis/memory and pain hypersensitivity will need to be different based on sex.
In addition, these findings may reflect a converging sex difference which de Vries (2004) suggests is when sex difference in neural representation/mechanism may reflect a compensation within the brain to ensure there is no sex difference in behavior.
Although the behavior may be the same, these converging sex differences may have significant implications for treatment efficacy between the sexes. Too often these potential sex differences are ignored in the literature, as once there is no difference between sexes in the original trait, researchers will not consistently use sex as a variable in future studies (estimates suggest this practice occurs 30% of the time). Converging sex differences may contribute to sex differences in disease susceptibility or treatment. However, to discover these sex differences, researchers, funders, and publishers need to ensure that the research is appropriately analyzing sex as a factor.
By focusing on studying sex differences have we missed the point?
In the race to redress sex and gender health inequities in knowledge, have we missed the main impetus of the SABV/SGBA mandates? These mandates were created precisely because we do not have enough information about women’s physiology and their experience of disease and obviously, if the data are not analyzed by sex/gender, we miss important information on how the sexes might differ. However, women’s health research cannot be addressed solely by SABV/SGBA work.
One must also consider how female-unique experiences such as hormonal contraceptive use, pregnancy, menstrual cycles, menopause, and gendered experiences in the health care system, may influence health and disease outcomes. Of course, the same is true for male/men and non-binary people’s health. Men’s health does not always need to be compared to women’s health, and nonbinary health is not just about how it compares to cis-normative health. Working exclusively in sex/gender differences mistakenly emphases that health research will always use males as the comparator group with a continued instance that women’s biology be measured against a “norm,” which is male. With the current focus on sex differences research, although females/women are at last included in the research, they are still not prioritized.
By failing to prioritize female health, we only learn about how females/women compare to a male standard and we also fail to correct the ignorance that exists about women’s biology in health and disease. Where women’s bodies have been the focus, we have learned that hormonal contraceptives, pregnancy and pregnancy-related disorders, hormone therapy type, and menopause can have both short and long-lasting effects on health.
History of women’s health research
The field of women’s health emerged from Second Wave Feminism and its emphasis on the fact that reproductive health is not pathological. It empowers women to determine the course of their reproductive health. The reclaiming of women’s bodies as being under their control, rather than simply being reproductive organisms, led to a critical paradigm shift. However, in its early years, women’s health was often translated into a concentration on their reproductive organs or, as Nanette Wenger put it, “bikini medicine.”
One of the pivotal moments in research for the need for women’s health came in the discovery that heart disease was the number one killer in women after menopause and with that the realization that heart disease was not a man’s disease. This led to the idea that women’s health was much more than, and not just confined to, reproductive health.
Groundbreaking work by Marianne Legato, Nanette Wenger, and Karin Schenck-Gustafsson ultimately led to the understanding that not only was heart disease the number one killer of women, but that women presented with different symptoms, received different treatment, and had different outcomes than men. In this sense, women’s health became about equity in health care.
Concurrently, the field of Hormones and Behavior, which concentrated on the effects of sex steroids (estradiol and testosterone) on behavior, mostly on sexual behavior, via effects in the brain was gaining momentum. Gorski was one of the first to examine the influence of gonadal hormones on sex differences and sexual differentiation in the brain. This early work concentrated on sexual differentiation of the brain during development and ofttimes used the term “sexual dimorphism.” With the publication of the Proceedings of the Work Session of the Neurosciences Research Program (1980) the field of Hormones and Behavior entered a Contemporary Period (1980–2006) in which sex differences in human behavior (and not just nonhuman animals) began to be correlated with brain differences – both anatomical and functional.
This period led to a ballooning of sex differences research and continued discussions and debates on the role of sex, gender, and social experiences on brain development across the lifespan, its association with behavior, cognition, experience and the environment, and health outcomes. Through sex and gender differences research, women’s health became about every body system and the Office for Research on Women’s Health (founded 1990), the Columbia University Partnership for Gender-Specific Medicine (founded 1997), The Society for Women’s Health Research (founded 1990) and the Canadian Centers for Excellence in Women’s Health (founded 1996) advocated for the health of all female health and equity in clinical trials, drug development, and research.
Thus, for the last 5 decades, the fields of women’s health and sex differences have developed side-by-side and have only recently been merged into a perspective on sex differences in health and disease1 with equity arguments being extended to sex differences research and combined with arguments for replicable science. However, is there value in keeping these fields separate?
What is women’s health and does it always need to be compared to men’s health? Is the emphasis on sex and gender differences stymieing progress in our understanding of women’s health, which has long been ignored in the literature? In the next few sections, we provide evidence that women’s health as a separate discipline is essential to make headway into erasure of health inequities.
Beyond sex/gender differences: What is women’s health?
What is women’s health? Research suggests that women’s health is affected by a number of female-specific and gendered factors. Theory suggests that we need to move beyond the reproductive body to understand women’s whole body health. The last part of our chapter is focused on the biological contributions on women’s health and outlines how female-specific biology, such as the menstrual cycle, hormonal contraceptives, pregnancy, and menopause, influence women’s corporeal, and not just reproductive, health. However, it is important to note that psychosocial factors such as access to education, occupational roles, and socioeconomic status – all factors which show a sex/gender bias – will also influence health, but is beyond the scope of the present chapter and the reader is directed to other reviews on this important topic.
Menstrual cycle, hormonal contraceptives, and health
The characteristics of menstrual cycles influence disease risk and may be a barometer for future health risks. Menstrual cycle irregularities, length of cycle, and age of first menarche can affect cardiovascular disease risk, inflammatory bowel disease epilepsy, and kidney disease. In addition, the phase of the menstrual cycle can influence the symptoms of schizophrenia and possibly outcomes following breast cancer surgery. Moreover, disorders can vary specifically with the menstrual cycle such as premenstrual dysphoric disorder (PMDD), migraines, and catamenial epilepsy.
Indeed, authors have postulated that female health is cyclical and follows changes in immune system function with the menstrual cycle. Perhaps not surprisingly, the menstrual cycle is also associated with fluctuations in functional brain connectivity, suggesting that the menstrual cycle has a far-reaching impact on female health.
Hormonal contraceptives that alter the menstrual cycle influence health risks. Depending on the type of hormonal contraception, it can affect bone density, arterial stiffness, thrombosis risk, with reductions in risk for ovarian and endometrial cancer but a controversial increased risk of breast cancer. Conflicting reports suggest that hormonal contraceptives are associated with either reduced levels of depression or an increased risk for depression indices. The age of the woman who uses contraception plays a factor in these disparate results, as there is an increased risk of antidepressant use in younger populations but no increased risk for depression symptoms in adult populations.
There seem to be little to no changes in frontal cortical dopamine-dependent cognition with hormonal contraceptive use, but so little research has been done that cognitive effects are still hard to pin down. Puberty/adolescence is a crucial time for gonadal hormone changes and neural development. Thus, the negative effects of hormonal contraceptives during adolescence may not be so surprising and indeed the negative effects on bone density may be limited to adolescent exposure and more pronounced in progestin-only formulations. There are many different formulations of hormonal contraceptives that range not only in different types of synthetic estrogens and progestins but also different time courses.
Studies in this area are scarce, and given the popularity of hormonal contraceptives, as approximately 100 million women worldwide or 65% of women in the United States alone are currently using some more of contraception, this should serve as a wakeup call to the community that hormonal contraceptive research is woefully lacking.118 Thus, hormonal contraceptives affect a number of health outcomes but attention to the type of contraceptive, age of use, and length of use are important variables to consider.
Reproductive experience and health
Pregnancy is associated with dramatic physiological changes in the cardiac, pulmonary, immune, and metabolic systems. The placenta releases large amounts of placental hormones, leading to progesterone levels that are 20 times higher, glucocorticoid levels that are 2 times higher, and 17β-estradiol levels 300 times higher than normal levels. These hormonal and physiological changes are necessary for maintenance of pregnancy, yet the long-term consequences of being exposed to sustained high levels of hormones and altered physiology have not been thoroughly addressed in the literature. This is an important consideration, as maternal physiology remains altered long past pregnancy, and is associated with both short- and long-term repercussions for women’s health. In the short term, there is an increased risk for neuropsychiatric disorders such as anxiety, depression, psychosis, and obsessive-compulsive disorder.
Indeed, the risk for first time admission to hospital for any mental disorder is 2–7 times more likely in the first postpartum month. However, autoimmune disorders such as multiple sclerosis and rheumatoid arthritis remit during pregnancy. In addition, disorders of pregnancy, such as hypertension and preeclampsia, can increase risk for cardiovascular disorders in the short-term such as myocardial infarction or stroke. Thus, there are short term implications of pregnancy on perinatal mental illness and hypertension that deserve attention.
Much less research is dedicated to understanding the long-term consequences of pregnancy on health, but there is evidence that previous pregnancy and/or pregnancy-related disorders influence both brain and cardiovascular health. Using a large human database, researchers found, using machine learning, that past reproductive experience was associated with a “younger brain age” relative to chronological age, with the more youthful brain areas including the hippocampus and nucleus accumbens. This is supported by similar findings in animals, as previously parous middle-aged rats exhibit enhanced levels of neuroplasticity, including hippocampal neurogenesis, compared to nulliparous rats.
Middle aged, previously parous, rats have less age-related cognitive decline and lower levels of neurodegeneration, suggesting less neural aging with a history of previous parity. Beyond brain health, gestational hypertension and/or gestational diabetes are associated with increased cardiovascular disease risk including hypertension and type 2 diabetes in mid-life. Previous parity is also associated with a reduced risk of endometrial and ovarian cancer. Evidently, reproductive experience and the presence of pregnancy-related disorders have long-lasting effects on health and is a critical area of research that deserves more attention.
Menopause, hormone therapy and health
Menopause is defined as 12 consecutive months of amenorrhea and is associated with a reduction in ovarian hormones. However, the ovaries are not quiescent post menopause as they produce a variety of androgens. Menopause is associated with increased vasomotor symptoms (hot flashes, night sweats), somatic symptoms (increased fat mass, redistribution of from subcutaneous to visceral fat), cognitive symptoms (reduced verbal memory), and increased white matter hyperintensities.
Indeed, cognitive symptoms and brain activation patterns are different following greater physiologically-monitored vasomotor symptoms. However, there are many types of menopauses, each of which can differentially affect health. Menopause can begin spontaneously or via surgical means, and early or later in the lifespan. These different menopause types involve distinct hormonal changes which lead to vastly different outcomes, especially in cognitive health.
Given that estrogens are thought to be neuroprotective in injury, normal aging, and pathological neurodegeneration, it is not surprising that reduced levels of ovarian hormones after menopause may contribute to reductions in various cognitive domains and increased risk for and severity of certain diseases, like late-onset sporadic Alzheimer’s disease (AD). Indeed, in surgical menopause, even in women younger than 50, changes in verbal episodic and spatial memory can occur within a year post-surgery.
Hormone therapy (HT) is prescribed to alleviate menopausal symptoms, such as hot flashes and headaches. Importantly, vasomotor symptoms of menopause have been implicated in cognitive and brain health. For example, a higher frequency of physiologically-monitored hot flashes, particularly during sleep, were associated with lower verbal memory performance and greater white matter hyperintensity burden. This is a critical finding, as white matter hyperintensity burden is considered a risk factor for ischemic stroke, AD, and dementia.
Although the exact mechanistic link remains to be elucidated, it is likely to involve cardiovascular disease risk factors, which are associated with both menopausal vasomotor symptoms and white matter hyperintensities. Given that menopausal vasomotor symptoms extend to affect the brain, treating these symptoms with HT, may also improve cognitive and brain health.
Indeed, there is evidence suggesting HT decreases risk and delays onset of AD. However, other studies show that HT may not have a beneficial effect on AD or cognitive function in older females. These seemingly conflicting findings from different studies may, at least in part, be attributed to differences in type, dose, and timing of HT as well as differences in genotype and reproductive experience. For example, using HT within 5 years of menopause reduced AD risk by 30%, whereas using HT for 5 or more years after menopause did not reduce AD risk, implicating a critical window during which HT use may be beneficial.
Further, a recent study showed that an earlier onset of HT was associated with more brain aging only in those carrying an APOEe4 allele, which accounts for the largest proportion of genetic risk factors for sporadic AD. This demonstrates that genotype can interact with HT use to alter outcomes. In addition, HT effects are influenced by past reproductive experience in animal models. Galea et al. found that in nulliparous rats, conjugated estrogens (Premarin: a commonly prescribed HT) enhanced spatial learning, whereas in primiparous rats, it impaired spatial learning. Together, these studies highlight the need to understand how different HTs affect women’s health depending on their genotype and reproductive experience. This greater attention to female-specific experiences across all health domains will enhance precision medicine for women.
In each of the sections above it is evident that multiple female-specific experiences influence health and disease risk (Fig. 45.2), but that more research is needed. Due to the scarcity of women’s health research, more information is needed to uncover whether the type of hormone therapies or contraceptives, age of first and last pregnancies, fetal sex may influence health and disease risk and have rarely been explored. Certainly, despite the numerous calls for action, the science of women’s health remains in its infancy.
What does it cost us when we ignore women’s health?
In this chapter, we have provided evidence that many female-unique factors (menstrual cycle, hormonal contraceptives, pregnancy history, and menopause) influence women’s health. Precision medicine must consider these factors to better understand the disparities in healthcare and how we can correct them. We must recognize and value the contribution of studies in women’s health and recognize they do not always need to be conducted in conjunction with examining males.
Indeed, female-specific traits critical to the health of women may be missed if researchers are not paying attention to the unique characteristics and needs of women. One example of this was during the early trials of COVID-19 vaccines. At first, pregnant people were not enrolled, thus a crucial opportunity to vaccinate this important population of individuals early in the pandemic was missed. We now know that pregnant females are at a 2.5 times greater risk of mortality following COVID-19 and vaccinations during either the second or third trimester of pregnancy confer a benefit not only to the pregnant person but to the fetus.
Furthermore, in the list of symptoms that were cataloged from the vaccine, women’s health indices were not queried. As a result, women were left to wonder about some menstrual and menopausal symptoms they were experiencing after the vaccine and it is likely that these fears led to the increased vaccine hesitancy that is threatening pandemic recovery. These fears could have been allayed if the original trials had included these symptoms and followed women to ensure the public that these were not serious concerns.
The lack of research on women’s health issues extends into the medical school curriculum in that physicians have been exposed to limited knowledge during their training. Indeed, studies find that in the United States and Canada, medical school curriculum often lacks sex and gender content and this has not changed in neurology and nephrology over the past 10 years. This likely contributes to the findings that women are more likely to receive a later diagnosis, be misdiagnosed or dismissed due to their symptom presentation. Clearly, the lack of women’s health research encourages reduced attention to sex as a variable during medical school, which can lead to inefficient clinical care for women.
The importance and benefits of studying women’s health, along with sex/gender differences, is not only limited to health outcomes. A study found that health expenditures increases were disproportionately related to improvements in longevity in men compared to women across the majority of the 27 countries examined. The reasons behind this are unknown, but it is hard not to consider that the lack of information on women’s health contributes to these disparities. Women form ~70% of the workforce globally, in addition to the extra unpaid caregiving duties they often perform.
Thus, healthier women will have less productivity loss that would result in reduced costs to the economy. The way forward is clear: investing in women’s health from fundamental science to clinical trials to medical practice will have a cascading effect to improve not only the health of women but also the health of our economies.
Conclusions
In this chapter, we have outlined how the underrepresentation of females in medical research has led to a lack of knowledge of women’s health. We underscored that studying sex/gender differences must involve the analysis of sex/gender as a discovery variable and not to simply control for these possible differences.
Despite over 20 years of mandates to include women in NIH-sponsored clinical research and clinical trials, progress has been slow partially due to the issues with analyses, an understanding of the many types of sex differences, and the lack of attention to female-specific variables that affect health and disease risk. To progress, the medial research field needs to study the various types of sex differences and not assume that if there is no sex/gender difference in a certain trait, there are no differences in the mechanisms driving the trait.
Despite years of recognition that females are understudied, under 5% of studies in biomedical fields are in females only, a far cry from the 27% to 40% that are in males only.2We provided evidence for the biological importance of studying female-unique experiences such as menstruation, hormonal contraceptives, pregnancy, and menopause that drive health outcomes and disease risk. However, it is also important to consider that gendered life experiences also greatly affect health outcomes. Indeed, acute coronary syndrome is linked to gendered and not sex-specific traits and allostatic load is linked not just to sexual orientation but other gendered factors as well. These and many other gendered experiences are rarely studied, though they certainly affect disease risk and resilience and deserve more attention. Along with the call for more research on women’s health, many have argued for the inclusion of gender-diverse people along with women’s health.
As noted above, this is an important and neglected topic. It is important in our collective considerations that researchers focus on being gender-inclusive. Thus, we would argue that researchers need to focus on women’s health, nonbinary health, and how sex and gendered differences may be contributing to different health outcomes. As we have seen in the literature, fruitful discoveries regarding sex and gender outcomes in medical research come from disaggregation of data and analyzing sex/gender as a discovery variable. But it is equally important to acknowledge that women’s health must not always need to be compared to men’s health.
After all, the goal of precision medicine is to improve health outcomes based on individual physiological profiles, which includes how these female-unique experiences can shape physiology.