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结构性别主义与人口健康研究方法:引入一种新的分析框架,以捕捉生命历程和交叉影响。

Methods for structural sexism and population health research: Introducing a novel analytic framework to capture life-course and intersectional effects.

机构信息

Division of Adolescent/Young Adult Medicine, Boston Children's Hospital, 333 Longwood Avenue, Boston, MA, 02115, USA; Department of Pediatrics, Harvard Medical School, Boston, MA, 02115, USA.

Department of Behavioral and Social Sciences, Brown University School of Public Health, Providence, RI, 02903, USA.

出版信息

Soc Sci Med. 2024 Jun;351(Suppl 1):116804. doi: 10.1016/j.socscimed.2024.116804. Epub 2024 May 31.

Abstract

Accumulating evidence links structural sexism to gendered health inequities, yet methodological challenges have precluded comprehensive examinations into life-course and/or intersectional effects. To help address this gap, we introduce an analytic framework that uses sequential conditional mean models (SCMMs) to jointly account for longitudinal exposure trajectories and moderation by multiple dimensions of social identity/position, which we then apply to study how early life-course exposure to U.S. state-level structural sexism shapes mental health outcomes within and between gender groups. Data came from the Growing Up Today Study, a cohort of 16,875 children aged 9-14 years in 1996 who we followed through 2016. Using a composite index of relevant public policies and societal conditions (e.g., abortion bans, wage gaps), we assigned each U.S. state a year-specific structural sexism score and calculated participants' cumulative exposure by averaging the scores associated with states they had lived in during the study period, weighted according to duration of time spent in each. We then fit a series of SCMMs to estimate overall and group-specific associations between cumulative exposure from baseline through a given study wave and subsequent depressive symptomology; we also fit models using simplified (i.e., non-cumulative) exposure variables for comparison purposes. Analyses revealed that cumulative exposure to structural sexism: (1) was associated with significantly increased odds of experiencing depressive symptoms by the subsequent wave; (2) disproportionately impacted multiply marginalized groups (e.g., sexual minority girls/women); and (3) was more strongly associated with depressive symptomology compared to static or point-in-time exposure operationalizations (e.g., exposure in a single year). Substantively, these findings suggest that long-term exposure to structural sexism may contribute to the inequitable social patterning of mental distress among young people living in the U.S. More broadly, the proposed analytic framework represents a promising approach to examining the complex links between structural sexism and health across the life course and for diverse social groups.

摘要

越来越多的证据表明,结构性性别歧视与性别健康不平等有关,但方法学上的挑战使得对生命历程和/或交叉影响的全面研究无法进行。为了帮助解决这一差距,我们引入了一个分析框架,该框架使用序贯条件均值模型(SCMM)来共同解释纵向暴露轨迹和多个社会身份/地位维度的调节作用,然后我们将其应用于研究美国州一级结构性性别歧视对性别群体内部和之间的心理健康结果的早期生命历程影响。数据来自于今日成长研究,这是一项对 1996 年 9-14 岁的 16875 名儿童进行的队列研究,我们对他们进行了 2016 年的随访。我们使用了相关公共政策和社会条件的综合指数(例如,堕胎禁令,工资差距),为每个美国州分配了一个特定年份的结构性性别歧视分数,并通过平均与研究期间居住在各州相关的分数来计算参与者的累积暴露量,根据在每个州居住的时间加权。然后,我们拟合了一系列 SCMM 来估计从基线到给定研究波的累积暴露与随后的抑郁症状之间的总体和群体特定关联;我们还拟合了使用简化(即非累积)暴露变量的模型用于比较目的。分析表明,累积暴露于结构性性别歧视:(1)与随后波次经历抑郁症状的几率显著增加有关;(2)不成比例地影响了多重边缘化群体(例如,性少数群体女孩/妇女);(3)与静态或时点暴露操作化(例如,一年中的暴露)相比,与抑郁症状的相关性更强。从实质上说,这些发现表明,长期暴露于结构性性别歧视可能导致美国年轻人中精神困扰的不平等社会模式。更广泛地说,所提出的分析框架代表了一种有前途的方法,可以研究生命历程中结构性性别歧视与健康之间的复杂联系,以及不同社会群体之间的联系。

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