Case study 1: Formulation of research questions, analysis and reporting
In addition to the recruitment of different genders and groups of people, the subsequent gender-specific analysis and its systematic reporting is crucial in order to be able to interpret and transfer it. However, a study by Brady et al. showed that gender was insufficiently considered in clinical studies on COVID-19: only 4% of the registered studies planned a gender-specificsubgroup analysis, and only 17.8% of the published randomized controlled trials (RCTs) examined reported specific results (Brady et al. 2021)
For example, gender-specific aspects in infection courses, immune responses and therapy responses may remain undetected because they are not visible in aggregated evaluations and are not reported in a gender-specific manner.
Case study 2: Case study of basic research with tissue/cells
In pharmacology, crucial aspects of drug metabolism are overlooked due to the lack of information on the genetic sex of the tissue/cell. As a result, women experience adverse drug reactions almost twice as often as men (Zucker and Prendergast 2020)
. A striking example is the enzyme cytochrome P450 3A4 (CYP3A4), which plays a crucial role in drug metabolism. Numerous studies have shown that CYP3A4 expression and activity can differ between male and female cells, potentially leading to differences in drug efficacy and toxicity (Gogos et al. 2019)
. Research suggests that women often have higher CYP3A4 activity compared to men, resulting in faster metabolism of certain drugs. However, these gender differences are often overlooked in laboratory studies using cell cultures, as the genetic sex of the donor cells is often not taken into account (Shah et al. 2014)
Case study 3：Basic research with animal studies
For decades, pain research predominantly used male animals, as it was assumed that the hormonal cycles of female animals lead to fluctuations that complicate the results. However, this approach ignored crucial sex-specific variations in pain perception and response to pain medication. A benchmark study by Sorge et al. (2014) showed that male and female rodents use different immune pathways to process pain. This means that pain medication that was only tested on male animals may not be equally effective in female animals (Sorge et al. 2014).
This bias in animal studies has significant clinical implications. Numerous studies show that women are more likely to suffer from chronic pain disorders than men and often respond differently to pain treatments. The failure to include female animals in preclinical animal studies has contributed significantly to the ongoing gender pain gap, i.e. the under-diagnosis and under-treatment of pain in women.
Case study 4：Case study clinical trials
Historically, cardiovascular research has focused predominantly on white male subjects, which has led to a lack of understanding of the manifestation of heart disease in women and gender-diverse individuals, as well as blacks and POC. Regitz-Zagrosek et al. found in one study that only 35% of participants in large cardiology studies were women (Regitz-Zagrosek et al. 2016), despite heart disease being the leading cause of death in all genders (Safiri et al. 2022). This omission has contributed to misdiagnosis and delayed treatment of women with heart attacks, as their symptoms often differ from those of men. For example, women are more likely to experience symptoms such as nausea, dizziness, upper abdominal pain and back pain than the stereotypical left-sided chest pain that are considered "typical" heart attack symptoms. Prasanna et al. found in a study that 46% of the cardiology studies examined described a proportion of less than 25% of Black subjects, which means that they are still underrepresented and continue the data gap (Prasanna et al. 2021). This is particularly problematic as Black patients have a higher premature cardiovascular mortality rate.
Case study 5：Case study survey research
Existing gender biases in survey research contribute significantly to the gender data gap. One example is the Demographic and Health Surveys (DHS), which are used worldwide to collect population-related health data. While women are asked detailed questions about family planning and reproductive health, men are hardly asked any questions about this - the reverse is true for topics such as smoking or alcohol consumption (Weber et al. 2021). This gender-specific structuring of the surveys is based on traditional role models and leads to incomplete data sets and gender-specific biases (Weber et al. 2019). This has far-reaching consequences, as health strategies and policy measures are developed on the basis of this biased data and potentially gender-specific health risks are insufficiently taken into account (Shannon et al. 2019).
