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BackgroundIn this paper, we argue for Gender as a Sociocultural Variable (GASV) as a complement to Sex as a Biological Variable (SABV). Sex (biology) and gender (sociocultural behaviors and attitudes) interact to influence health and disease processes across the lifespan-which is currently playing out in the COVID-19 pandemic. This study develops a gender assessment tool-the Stanford Gender-Related Variables for Health Research-for use in clinical and population research, including large-scale health surveys involving diverse Western populations. While analyzing sex as a biological variable is widely mandated, gender as a sociocultural variable is not, largely because the field lacks quantitative tools for analyzing the influence of gender on health outcomes.MethodsWe conducted a comprehensive review of English-language measures of gender from 1975 to 2015 to identify variables across three domains: gender norms, gender-related traits, and gender relations. This yielded 11 variables tested with 44 items in three US cross-sectional survey populations: two internet-based (N = 2051; N = 2135) and a patient-research registry (N = 489), conducted between May 2017 and January 2018.ResultsExploratory and confirmatory factor analyses reduced 11 constructs to 7 gender-related variables: caregiver strain, work strain, independence, risk-taking, emotional intelligence, social support, and discrimination. Regression analyses, adjusted for age, ethnicity, income, education, sex assigned at birth, and self-reported gender identity, identified associations between these gender-related variables and self-rated general health, physical and mental health, and health-risk behaviors.ConclusionOur new instrument represents an important step toward developing more comprehensive and precise survey-based measures of gender in relation to health. Our questionnaire is designed to shed light on how specific gender-related behaviors and attitudes contribute to health and disease processes, irrespective of-or in addition to-biological sex and self-reported gender identity. Use of these gender-related variables in experimental studies, such as clinical trials, may also help us understand if gender factors play an important role as treatment-effect modifiers and would thus need to be further considered in treatment decision-making.

Sex and gender are distinct terms that must be used correctly. Data regarding sex and gender may be collected using a 2-step method that separates biological sex and self-reported gender identity. The PhenX Toolkit, funded by the National Institutes of Health (NIH), is one tool that provides investigators with recommended standard data-collection protocols. Another tool is the Diversity Minimal Item Set questionnaire. Importantly, sex and gender interact: for example, pain has both biological aspects (sex differences in electrical, ischemic, thermal, pressure, and muscle pain sensitivity) and cultural aspects (gender factors in how people report pain and how physicians understand and treat pain in patients). Gender norms, identity, and relations all impact patient care. Gender norms, for instance, may influence how a person experiences pain, gender identity may influence a person's willingness to report pain, and gender relations may influence a physician's gendered expectations in relation to a patient's gendered behaviors. Clinicians may perceive women's pain to be psychological; as a result, women may receive more nonspecific diagnoses, wait longer for treatment, and receive more antidepressants and fewer analgesics than men. Research on gender-diverse people and pain is just now emerging. Resources for methods of reporting include The Lancet, Nature, and the Sex and Gender Equity in Research (SAGER) Guidelines. We must consider all relevant factors intersecting with sex and gender, including age, disabilities, educational background, ethnicity, family configuration, geographic location, race, sexuality, social and economic status, sustainability, and more. [ABSTRACT FROM AUTHOR]

The goal of sex and gender analysis is to promote rigorous, reproducible and responsible science. Incorporating sex and gender analysis into experimental design has enabled advancements across many disciplines, such as improved treatment of heart disease and insights into the societal impact of algorithmic bias. Here we discuss the potential for sex and gender analysis to foster scientific discovery, improve experimental efficiency and enable social equality. We provide a roadmap for sex and gender analysis across scientific disciplines and call on researchers, funding agencies, peer-reviewed journals and universities to coordinate efforts to implement robust methods of sex and gender analysis. The authors discuss the potential for sex and gender analysis to foster scientific discovery, improve experimental efficiency and enable social equality., Author(s): Cara Tannenbaum [sup.1] , Robert P. Ellis [sup.2] , Friederike Eyssel [sup.3] , James Zou [sup.4] [sup.5] , Londa Schiebinger [sup.6] Author Affiliations: (1) Institute of Gender and Health, [...]

Scientists are likely not to be interested in thinking about housework. Housework is, however, related to the life of the mind. Scientists wear clean clothes to the lab, eat food procured and prepared by someone, and live in reasonably clean houses. This labor used to be done by stay-at-home wives. Now, housework is often done by wives and partners who are also full-time professionals--and the women the authors discuss in this study are scientists at thirteen of the top research universities in the United States. Findings from their study, based on data collected in 2006-2007, show that despite women's considerable gains in science in recent decades, female scientists do nearly twice as much housework as their male counterparts. Partnered women scientists at places like Stanford University do 54 percent of the cooking, cleaning, and laundry in their households; partnered men scientists do just 28 percent. This translates to more than ten hours a week for women--in addition to the nearly sixty hours a week they are already working as scientists--and to just five hours for men. These findings have important policy implications. Over the past three decades, governments, universities, and industries have dedicated often robust resources to efforts to increase the number of women scientists--and yet progress in attracting more women to science has stalled. In this study, the authors zero in on the obligation of household labor. They analyze the division of household labor in scientists' homes and their strategies to lighten the household load in order to maintain highly productive careers. They argue that work done in the home is very much an academic issue--not peripheral in any way to scientists' professional lives. Understanding how housework relates to women's careers is one new piece in the puzzle of how to attract more women to science. The authors' policy recommendation provides a new solution to one key aspect of balancing life and work. They propose that employers provide benefits to support housework. Many universities already offer retirement, health-care, and child-care supplements; some even support housing and tuition benefits. The authors recommend that institutions provide a package of flexible benefits that employees can customize to support aspects of their private lives in ways that save time and enhance professional productivity. Institutions need to think of housework benefits as part of the structural cost of doing business. With lab costs running into the millions of dollars, supporting the human resource involved--scientists' ability to be more productive--takes full advantage of investments in space and equipment. (Contains 4 figures and 1 note.)