Wandschneider Lisa, Sauzet Odile, Razum Oliver, Miani Céline
Department of Epidemiology and International Public Health, School of Public Health, Bielefeld University, Bielefeld, Germany.
Center for Statistics, Bielefeld University, Bielefeld, Germany.
Front Epidemiol. 2022 Aug 24;2:914819. doi: 10.3389/fepid.2022.914819. eCollection 2022.
Gender as a relational concept is rarely considered in epidemiology. However, an in-depth reflection on gender conceptualisation and operationalisation can advance gender analysis in quantitative health research, allowing for more valid evidence to support public health interventions. We constructed a context-specific gender score to assess how its discriminatory power differed in sub-groups defined by social positions relevant to intersectional analyses, i.e., sex/gender, race, class, age and sexual attraction.
We created a gender score with the help of multivariable logistic regression models and conditional probabilities based on gendered social practices and expressed on a masculinity-femininity continuum, using data of the German Socioeconomic Panel. With density plots, we exploratively compared distributions of gendered social practices and their variation across social groups.
We included 13 gender-related variables to define a gender score in our sample ( = 20,767). Variables on family and household structures presented with the highest weight for the gender score. When comparing social groups, we saw that young individuals, those without children, not living with a partner or currently living in a same-sex/gender partnership, showed more overlap between feminine/masculine social practices among females and males.
The distribution of gendered social practices differs among social groups, which empirically backs up the theoretical notion of gender being a context-specific construct. Economic participation and household structures remain essential drivers of heterogeneity in practices among women and men in most social positions. The gender score can be used in epidemiology to support concerted efforts to overcome these gender (in)equalities-which are important determinants of health inequalities.
作为一种关系概念的性别在流行病学中很少被考虑。然而，对性别概念化和操作化进行深入思考可以推进定量健康研究中的性别分析，从而获得更有效的证据来支持公共卫生干预措施。我们构建了一个特定背景下的性别得分，以评估其在由与交叉性分析相关的社会地位所定义的亚组中的区分能力，即性别、种族、阶级、年龄和性取向。
我们借助多变量逻辑回归模型和基于性别化社会实践的条件概率，利用德国社会经济面板数据，创建了一个性别得分，该得分在男性气质 - 女性气质连续体上表示。通过密度图，我们探索性地比较了性别化社会实践的分布及其在社会群体中的差异。
我们纳入了13个与性别相关的变量来定义样本（n = 20,767）中的性别得分。家庭和家庭结构变量在性别得分中权重最高。在比较社会群体时，我们发现年轻人、没有孩子的人、不与伴侣同住或目前处于同性/同性别伴侣关系中的人，其女性和男性的女性化/男性化社会实践之间的重叠更多。
性别化社会实践的分布在社会群体中存在差异，这从经验上支持了性别是一个特定背景下的建构这一理论概念。经济参与和家庭结构仍然是大多数社会地位中男女实践异质性的重要驱动因素。性别得分可用于流行病学，以支持共同努力克服这些性别（不）平等——这些是健康不平等的重要决定因素。
