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流行病学研究中的性与性别多维性。

Sex and Gender Multidimensionality in Epidemiologic Research.

出版信息

Am J Epidemiol. 2023 Jan 6;192(1):122-132. doi: 10.1093/aje/kwac173.

Abstract

Along with age and race, sex has historically been a core stratification and control variable in epidemiologic research. While in recent decades research guidelines and institutionalized requirements have incorporated an approach differentiating biological sex from social gender, neither sex nor gender is itself a unidimensional construct. The conflation of dimensions within and between sex and gender presents a validity issue wherein proxy measures are used for dimensions of interest, often without explicit acknowledgement or evaluation. Here, individual-level dimensions of sex and gender are outlined as a guide for epidemiologists, and 2 case studies are presented. The first case study demonstrates how unacknowledged use of a sex/gender proxy for a sexed dimension of interest (uterine status) resulted in decades of cancer research misestimating risks, racial disparities, and age trends. The second illustrates how a multidimensional sex and gender framework may be applied to strengthen research on coronavirus disease 2019 incidence, diagnosis, morbidity, and mortality. Considerations are outlined, including: 1) addressing the match between measures and theory, and explicitly acknowledging and evaluating proxy use; 2) improving measurement across dimensions and social ecological levels; 3) incorporating multidimensionality into research objectives; and 4) interpreting sex, gender, and their effects as biopsychosocial.

摘要

性别与年龄和种族一样,历来是流行病学研究中的核心分层和控制变量。虽然近几十年来,研究指南和制度化要求已经将区分生物性别和社会性别纳入其中,但性别和性别本身都不是单一维度的结构。性别和性别的维度在内部和之间的混淆提出了有效性问题,其中常用代理措施来衡量感兴趣的维度,而通常没有明确的承认或评估。在这里,概述了性别和性别的个体层面维度,作为对流行病学家的指导,并提出了 2 个案例研究。第一个案例研究表明,在没有明确承认的情况下,将性别/性别代理用于感兴趣的性别维度(子宫状况),会导致数十年来癌症研究对风险、种族差异和年龄趋势的错误估计。第二个案例说明了如何应用多维性别和性别框架来加强对 2019 年冠状病毒病发病率、诊断、发病率和死亡率的研究。概述了需要考虑的因素,包括:1)解决措施与理论之间的匹配问题,并明确承认和评估代理使用;2)改善各个维度和社会生态层面的测量;3)将多维性纳入研究目标;4)将性别和性别及其影响解释为生物心理社会因素。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f2f/9825720/9b775835c8ba/kwac173f1.jpg

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