Gender bias in medical research refers to the systematic exclusion or differential treatment of individuals based on biological sex or gender. This historical pattern often resulted in male biology being considered the default standard, leading to gaps in knowledge regarding the health of all people. The consequences of this approach permeate medical and health research, affecting foundational biological studies, the design of clinical trials, and the development of treatment guidelines. Addressing this bias requires a fundamental re-evaluation of how scientific investigation is conducted to ensure that health interventions are safe and effective for the entire population.
Bias in Research Methodology and Participation
Historically, women have been significantly underrepresented in clinical trials for many conditions and therapeutic drugs. This imbalance stems partly from a 1977 U.S. Food and Drug Administration (FDA) guideline that discouraged the inclusion of women of childbearing age in early-phase clinical trials due to concerns about potential fetal harm. Although this guideline was later revoked, the legacy of exclusion continues to affect study design and population diversity. For example, in cardiovascular studies, only about 38% of participants, on average, have been women, despite heart disease being the leading cause of death for women globally.
This systematic underrepresentation begins at the level of basic science research. Preclinical studies often rely disproportionately on male cell lines and male animal models; in some cases, over 80% of studies assessing drug safety and efficacy have been conducted solely using male mice. Researchers traditionally favored male models because they were perceived as having fewer hormonal fluctuations than females, simplifying the experimental design by presenting less biological variability.
The assumption that male biology serves as a universal standard means that data collected from these single-sex models may not accurately predict outcomes in females. When studies fail to include sufficient numbers of female subjects, or when data from both sexes are pooled without separate analysis, the resulting findings are skewed. This creates fundamental knowledge deficits about diseases and treatments in female bodies. The lack of diversity also extends to other groups, including transgender and nonbinary individuals, whose health data is often missing or incomplete in research.
Conceptual Confusion: Sex Versus Gender in Health
A persistent challenge in medical research is the conflation or interchangeable use of the terms “sex” and “gender” by researchers and in scientific literature. Biological sex refers to the physiological differences between individuals, typically categorized as male or female, based on chromosomal makeup, anatomy, and hormonal profiles. These factors directly influence biological processes such as metabolism, immune response, and drug pharmacokinetics.
In contrast, gender refers to the socially constructed roles, behaviors, expressions, and identities that a society considers appropriate for people. Gender influences health outcomes through social context, including access to care, exposure to environmental risk factors, and the experience of chronic stress. A failure to analyze data based on both sex (biology) and gender (social context) leads to incomplete or inaccurate scientific findings.
Researchers frequently use the term “gender” when they are actually referring to “sex,” blurring the distinction between biological and social determinants of health. This analytical oversight means that when a difference in health outcomes is observed, it is often unclear whether the cause is hormonal and genetic (sex) or related to societal roles and behavioral norms (gender). Recognizing and separating these two variables is necessary for developing targeted interventions that address the specific biological needs and social realities of diverse populations.
Consequences for Diagnosis and Treatment
The systemic biases in research design have consequences for patient health, particularly in the diagnosis and treatment of diseases that affect men and women differently. Heart disease offers a stark example, as women often experience symptoms that differ from the classic presentation established through male-centric research. While men frequently report crushing chest pain, women are more likely to present with atypical symptoms like shortness of breath, nausea, or pain in the jaw, neck, or back. This difference contributes to women being underdiagnosed for cardiovascular disease and receiving fewer diagnostic tests.
The problem also extends to drug efficacy and safety. Because drugs have historically been tested primarily on men, dosing recommendations often lead to reduced efficacy or increased adverse drug reactions in women. Women, on average, have different body compositions, lower body weight, and distinct hormonal influences that affect how drugs are absorbed, metabolized, and cleared from the body. For example, women taking certain cardiovascular drugs, such as beta-blockers, may experience more adverse effects like fatigue and bradycardia.
In the context of pain and mental health, gender stereotypes can lead to symptoms being dismissed or attributed to emotional factors, delaying accurate diagnosis and appropriate treatment. Furthermore, the application of one-size-fits-all guidelines, such as using the same measurement thresholds for heart valve size in both male and female patients despite smaller average heart size in women, can lead to misclassification of disease severity.
Mandates for Inclusive Research and Reporting
In response to the documented harms of gender bias, several institutional and governmental requirements have been implemented to promote inclusivity and precision in medical research. The National Institutes of Health (NIH) policy mandates the inclusion of women and minority groups in all NIH-funded clinical research unless a clear scientific justification for exclusion is provided. This policy specifically states that women of childbearing potential should not be routinely excluded from participation.
The NIH policy also requires that researchers design studies with sufficient statistical power to enable a valid analysis of intervention effects by sex. Investigators must report enrollment numbers stratified by sex, race, and ethnicity annually. The NIH also requires that grant proposals detail how sex will be incorporated as a biological variable in preclinical and basic science studies, pushing for the use of both male and female animal models and cell lines.
Scientific journals and publishing organizations have adopted standards to address reporting bias, such as the Sex and Gender Equity in Research (SAGER) guidelines. These guidelines encourage authors to use the terms sex and gender accurately and to report data disaggregated by sex and/or gender where appropriate. These requirements from funding agencies and major publications are driving a systemic shift toward more rigorous and representative research practices.