EQUITY Team,, CERPOP, INSERM, Batiment E, 1er Etage, 37 Allées Jules Guesde, 31062, Toulouse, France.
IHPST UMR 8590, CNRS, 13 rue du Four, 75006, Paris, France.
Biol Sex Differ. 2022 May 12;13(1):23. doi: 10.1186/s13293-022-00430-6.
Epidemiologists need tools to measure effects of gender, a complex concept originating in the social sciences which is not easily operationalized in the discipline. Our aim is to clarify useful concepts, measures, paths, effects, and analytical strategies to explore mechanisms of health difference between men and women.
We reviewed concepts to clarify their definitions and limitations for their translation into usable measures in Epidemiology. Then we conducted methodological research using a causal framework to propose methodologically appropriate strategies for measuring sex and gender effects in health.
(1) Concepts and measures. We define gender as a set of norms prescribed to individuals according to their attributed-at-birth sex. Gender pressure creates a systemic gap, at population level, in behaviors, activities, experiences, etc., between men and women. A pragmatic individual measure of gender would correspond to the level at which an individual complies with a set of elements constituting femininity or masculinity in a given population, place and time. (2) Main analytical strategy. Defining and measuring gender are not sufficient to distinguish the effects of sex and gender on a health outcome. We should also think in terms of mechanisms, i.e., how the variables are linked together, to define appropriate analytical strategies. A causal framework can help us to conceptualize "sex" as a "parent" of a gender or gendered variable. This implies that we cannot interpret sex effects as sexed mechanisms, and that we can explore gendered mechanisms of sex-differences by mediation analyses. (3) Alternative strategy. Gender could also be directly examined as a mechanism, rather than through a variable representing its realization in the individual, by approaching it as an interaction between sex and social environment.
Both analytical strategies have limitations relative to the impossibility of reducing a complex concept to a single or a few measures, and of capturing the entire effect of the phenomenon of gender. However, these strategies could lead to more accurate analyses of the mechanisms underlying health differences between men and women.
流行病学家需要工具来衡量性别因素的影响,而性别是一个源于社会科学的复杂概念,在该学科中不易操作化。我们的目的是阐明有用的概念、衡量标准、途径、效应和分析策略,以探索男女健康差异的机制。
我们回顾了概念,以澄清其定义和局限性,以便将其转化为流行病学中可用的衡量标准。然后,我们使用因果框架进行方法学研究,提出了在健康研究中衡量性别和性别效应的方法上适当的策略。
(1)概念和衡量标准。我们将性别定义为根据个体的出生性别赋予个体的一套规范。性别压力在人群层面上造成了男性和女性在行为、活动、经历等方面的系统性差距。个人性别衡量标准将对应于个人在特定人群、地点和时间内遵守构成女性气质或男性气质的一系列要素的水平。(2)主要分析策略。定义和衡量性别不足以区分性别对健康结果的影响。我们还应该考虑机制,即变量之间的联系方式,以确定适当的分析策略。因果框架可以帮助我们将“性别”概念化为性别或性别变量的“父母”。这意味着我们不能将性别效应解释为性别化机制,并且我们可以通过中介分析探索性别差异的性别化机制。(3)替代策略。也可以通过将性别视为性别与社会环境之间的相互作用,而不是通过代表其在个体中实现的变量来直接检验性别作为一种机制。
这两种分析策略都存在局限性,这是由于不可能将一个复杂的概念简化为一个或几个衡量标准,也不可能捕捉到性别的整个效应。然而,这些策略可以导致更准确地分析男女健康差异背后的机制。