The exclusion of females from clinical trials as well as from many areas of basic research was a critical issue that harmed not only the health of women, but also the advance of science and medicine (Beery and Zucker, 2011). In order to correct this situation, the National Institutes of Health (NIH) and other funding agencies requested the inclusion of women in clinical trials (NIH revitalization Act, 1993), and later the consideration of sex as a biological variable in basic research (Clayton and Collins, 2014). While these actions were necessary, they also led to an excessive focus on the search for sex differences, in many cases without previously reflecting on why sex was relevant for the research topic being studied, and on what was the best approach to explore its potential influence.Importantly, several studies have shown that not only sex but also gender plays a determining role in health outcomes (Heise et al., 2019;Regitz-Zagrosek, 2012). In this line, the World Health Organization (WHO) assumed gender as one of the social determinants of population health and health inequalities in the Social Determinants of Health framework (World Health Organization, 2010). While sex generally refers to a set of biological attributes associated with physical and physiological features, gender refers to a multidimensional construct associated with social roles, behavior, lifestyle, and personal experiences (Heidari et al., 2016). Despite this differentiation, sex and gender are often inappropriately confused in the literature (Hammarström and Annandale, 2012), and gender is still rarely considered in health research, which could be due to the lack of quantitative tools to analyze its influence on health outcomes. Moreover, even when they are explored, comparisons are usually made within a rigid binary framework, performing simple male vs. female analyses that leave sex and gender-related sources of variability without explanation (Joel, 2021;Sanchis-Segura and Wilcox, 2024). But individuals experience gender-related norms differently, and thus we miss information when we classify them as something with two opposite, fixed poles (Saguy et al., 2021). A previous gender scale that has been widely used, the Bem Sex Role Inventory (BSRI; Bem, 1974), challenges the assumption of masculinity and femininity being two opposed ends of the same dimension, but it still focusses solely in the psychological and individual aspects of gender roles, and is based on outdated notions of femininity and masculinity. While these concepts may be addressing some individual aspects of gender that are relevant for health (such as personality traits), there are other relational and institutional aspects of gender that may also be critical for our health (Connell, 2012;Heise et al., 2019). In this regard, measuring and labelling genderrelated behaviors as such (e.g. caregiving or discrimination) could give richer information for individualized medicine than just sex or gender categories, or scores based on a single measure of masculinity/femininity based on individual traits.Due to this gap in the field, a new instrument was developed for the North American population for the study of gender using a multidimensional approach -the Stanford Gender-related Variables for Health Research (GVHR), after a thorough review of the literature regarding gender dimensions and gender-related variables (Nielsen et al., 2021). Importantly, considering that gender is a social construct that can vary from one culture to another, it is necessary to analyze if gender measures created in one cultural group are valid for a different culture. For example, the GVHR scale was recently adapted to the Spanish population (Díaz-Morales et al., 2023), and the authors found that a five-factor model was more tenable for that population than the original sevenfactor structure. Still, caregiver and work strain were the gender variables that predicted worse health-related quality of life, psychological health, and health-risk behaviors, in line with the findings from the original scale.In the current work, we aim to translate and validate the Stanford GVHR instrument to the Portuguese population, and analyze the impact of gender-related variables on health outcomes. Moreover, we intend to go beyond the original article and explore the potential impact of gender-related variables on stress. According to the WHO, stress can be defined as a state of worry or mental tension caused by a difficult situation (World Health Organization, 2023). Stress is a natural human response that is experienced by everyone when facing challenges and threats in their lives. However, when prolonged, stress can become pathological, impacting a person's physical and mental health (O'Connor et al., 2021). The impact of sex and gender on stress has been previously studied, using either a binary approach (Matud, 2004), or a dimensional approach but only considering physiological variables such as hormones (Kajantie and Phillips, 2006). Thus, exploring the impact of gender-related variables from a multidimensional perspective might help go one step beyond what is already known regarding sex/gender differences on stress.This project was conducted by the principles of the Declaration of Helsinki and was approved by the Ethical Subcommittee in Life and Health Sciences of the University of Minho (CEICVS 005/2022). Before completing the form, participants had to give their consent for data collection. All data was processed anonymously.First, the original English version of the GVHR was obtained from the authors and translated to Portuguese by two Portuguese native speakers. Then, after a consensus was reached, an independent bilingual translator back-translated the scale, which was sent for approval to the original authors.This project had a cross-sectional design, and data collection took place between July 2022 and November 2022. The data was collected and managed using REDCap electronic data capture tools hosted at the researcher's university (Harris et al., 2019(Harris et al., , 2009)). The questionnaire was shared through the university mailing lists with students, staff, and the general community. The time requested to complete the questionnaire was approximately 20 minutes. The only exclusion criteria applied was age less than 18 years or not giving consent to collect the data. The questionnaire was divided into four sections: social demographics information (16 questions), health information (ten questions), stress level information (Perceived Stress Scale -PSS-10), and gender-related variables information (GVHR).Social demographics information included, among others, age, sex, gender, sexual orientation, relationship status, education, last year's income, and professional status (for most variables we used the same questions and response options as in Nielsen et al. 2021).The Health Days Measures (CDC HRQOL-4; Centers for Disease Control and Prevention, 2000) was used to collect health information, including general health status, physical health, mental health, and recent activity limitations. Additionally, weight, height, and questions about monthly habits, such as binge drinking, smoking, and vaping, were included in this section.The Portuguese version of the PSS-10 (Trigo et al., 2010) was used to measure perceived stress. The PSS is a self-report measure designed to capture the degree to which situations in an individual's life are appraised as stressful. It is composed of a fivepoint Likert scale varying from zero (never) to four (very often), corresponding to the frequency of stress felt in the last month. Scores range from 0 to 40, with higher scores corresponding to higher stress levels. In the validation of this scale by Trigo et al. (2010), it showed good reliability with a Cronbach's alpha of 0.874.Finally, the GVHR captures critical aspects of three dimensions of gender: Gender Norms (cultural rules produced through social institutions and cultural products), Gender-Related Traits (how individuals or groups perceive and present themselves concerning gender norms), and Gender Relations (how gender shapes social interactions in romantic relationships, friendships, families, schools, workplaces, and public settings).These are represented in the original validation of the questionnaire with seven factors: caregiver and work strain (Gender Norms), independence, risk-taking and emotional intelligence (Gender-Related Traits), and social support and discrimination (Gender Relations).The complete instruments (in Portuguese) used for collecting the sociodemographic and health data, as well as the GVHR, can be found in the Supplementary Material, while the original English version of these instruments can be found in the Supplementary Material of Nielsen et al. (2021) publication.Statistical analysis was performed using SPSS (Version 28, Chicago, IL, USA), Amos (Version 7.0) and JASP (Version 0.17.2, JASP Team, University of Amsterdam, the Netherlands). The significance level for all tests (p-value) was set at 0.05. The minimum sample size needed to validate the questionnaire was 260 participants, considering that the GVHR scale has 26 items, and there is a general recommendation of 10 participants per item (Boateng et al., 2018). Also, that sample size would allow us to detect effect sizes as small as R 2 =0.097 in multiple regression models (type-I error = 5%, statistical power = 95%, 10 predictors; calculated with GPower 3.1.9.2).Before performing the statistical analysis, the database was appropriately prepared based on what was done in the original GVHR article. First, body mass index (BMI) was computed based on self-reported values on weight and height, and dichotomized for further analysis to reflect under or normal weight (BMI .90), goodness of fit index (GFI > .90), Tucker-Lewis index (TLI > .90) and root mean square error of approximation (RMSEA < .05). Cronbach's alpha coefficients were calculated for those measures composed by several items. Pearson correlation coefficients were also computed to analyze relationships between the seven GVHR factors.Finally, we used JASP to explore the association between the seven factors and healthrelated variables. Logistic or linear regression was used depending on whether the dependent variable was categorical or continuous, respectively. Thus, logistic regression was used for the BMI, general health, vaping, smoking, and binge drinking dichotomized variables. On the other hand, linear regression was used for the PSS-10, physical health, mental health, and activity limitations. Moreover, age and years of education were included as covariates, in addition to either sex or gender (each model was performed twice), following what was done in the original publication.The sample included 351 participants (which was over the 260 needed), 100 male (28.5%), and 251 female (71.5%), with an average age of 30.4 (Min=18 and Max=64).Descriptive statistics on all the relevant sociodemographic and health variables are shown in Table 1. The Shapiro-Wilk test showed that the only variable following a normal was the PSS-10, the mean and are shown for this while the and range are shown for the of GVHR with = χ²/df ratio = = = = and = Also, all factors showed Supplementary Table 1 for their Cronbach's alpha and to the factor most of the variables the factors, for the variable (which to the item many per which had a factor of a influence on the factor work The of was generally Supplementary Table and with the Still, there was a correlation between and work strain, and emotional work strain and and social support and emotional intelligence regression model was performed either with sex or with gender as a (in addition to the age and years of However, the were the only the models using sex as are in the while the models using gender can be found at Supplementary Moreover, a is shown in Supplementary Figure 1 higher levels of discrimination and risk-taking were associated with binge drinking, while lower social age, and male sex were associated with more likelihood of being overweight or obese Table 2 regression models of PSS-10 R 2 mental health R 2 and activity R 2 were while the model of physical health R 2 was PSS-10, discrimination and work strain were while higher social emotional intelligence and risk-taking were mental health, discrimination and work strain were predictors mental while social support was a Finally, for activity discrimination and work strain were predictors Figure to the sex found in our and the lack of of our age when with the general Portuguese population, we to the multiple regression models in two of the 1 included 100 females and 100 males on age and education level and 2 on a sample more of the population also regarding age, including females and males on age and education level be with due to the sample and are only to the sample and some into the potential of the lack of of our 1, the findings were the same as with the Logistic regression models of binge drinking, vaping, smoking, and general health were not while the model was with the lower social age, and male sex were associated with more likelihood of being overweight or obese Table linear regression those of PSS-10, mental health and activity were while the model of physical health was For PSS-10, discrimination and work strain were while higher social support was a mental health, work strain was a mental while social support was a Finally, for activity social support was a Table from on the other hand, from those from the which could be due to the of statistical in addition to the different of the of the logistic regression models were model could not even be performed due to only participants as vaping Table while the linear regression models of PSS-10, physical health and mental health were (for activity the of the model was social support was a of PSS-10 and mental health, while caregiver strain was a of physical health Table and to the values obtained in the we can that the factor structure of the original GVHR scale was in the Portuguese population (Boateng et al., 2018). factor were for all factors, with the of However, we this the of our sample than a general issue with the factor regarding the sample on professional status, there was a of participants not which is not of the general population the sample used in the original The sample included in the Spanish validation of the GVHR by et al. had a higher of people but they not the item in their work strain we their sample for In studies may to our findings on a more sample to if a more factor for is the association between gender-related variables and health as in the original higher risk-taking was associated with binge The study by et al. also showed that risk-taking was to in and women after for age, lifestyle, and stress our et al., potential explanation for this association is that individuals with a higher for risk-taking to in behaviors that including without considering health and 2012). which is to has been as a factor in behaviors and we found that gender discrimination was associated with binge with findings from a review by and on discrimination based on sexual orientation, and gender, which that discrimination to such as relationship can be through the which that individuals discrimination may as a to psychological In this line, previous studies have that mental health and can also be by of including gender which is to and et al., According to our gender discrimination as a of mental health and activity in line with the of Nielsen et al. 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Additionally, it was also associated with higher perceived when these analyses in which included participants and had an age more to that of the general Portuguese population, the discrimination factor was no associated with health could be that people are more about their gender discrimination this factor more relevant for their health outcomes to BMI, as in the original and the Spanish being male was associated with an likelihood of being while we found an association with lower social support and Social support has been well as a factor for health including weight due to its role in behaviors, and et al., et al., et al., 2021). weight has been in in line with our as and factors such as physical activity to et al., and et al., factor that was shown to be relevant for health outcomes was work strain, which was associated with higher perceived mental health and activity limitations. is with the findings from the Spanish validation of the GVHR scale (Díaz-Morales et al., 2023), and with previous literature that associated with higher strain and tension were to more psychological in and women, due to a higher psychological and the work strain factor included questions about and participants felt from their work which to and could be relevant in our which we may many of our we the study all the university and the general our research group is in the of which had an influence on studies have shown that experience stress levels their et al., et al., with of the the of Portuguese have stress et al., we that of our participants were students, we not collect information on the degree of studies on this population could the associated with the degree of the other hand, we found that social support had a influence on being a of perceived stress and mental health to be with those found in the Spanish validation of the scale, as well as with previous studies that social support and stress impact health in and that social of social is a factor for et al., and emotional intelligence also as a factor stress. intelligence to the to and and the of The relationship between this variable and the to with has been well in the literature and and and our go in with previous the between this study and the original as well as the Spanish we found no with the caregiver strain which was a of worse health outcomes in those lack of might be by the number of single participants in our sample the weight of the caregiver strain variable less in the original of our gender-related variables had an influence on physical The that we had a generally with an average age of may not reflect the impact on physical health that these variables could being at this in life only relevant for mental health and activity limitations. to be by our analyses performed in which had participants and included an age more to that of the general Portuguese population age = For that higher caregiver strain was associated with worse physical health, in line with the from Nielsen et al. 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