Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, USA.
Department of Sociomedical Sciences, Mailman School of Public Health, Columbia University, New York, USA.
Prev Sci. 2024 Jul;25(Suppl 3):459-473. doi: 10.1007/s11121-024-01646-1. Epub 2024 Feb 15.
Menstrual cycle characteristics are largely considered unmodifiable reproductive factors, a framing that prevents exploration of the ways structural factors interfere with menstrual health. Given the role of structural factors like healthy food and healthcare access on reproductive health and the grave need for structural interventions to known reproductive health disparities that disproportionately target cisgender women racialized as Black, it is imperative that science begin to examine how structural factors influence menstrual health. To explore such research, we employ critical race theory and intersectionality to illustrate what a structural intervention to improve menstrual cycle health could look like. Centering those with the greatest need, persons racialized as Black and/or LatinX living in food and healthcare deserts in Northern Manhattan, our illustrative sample includes four groups of persons who menstruate (e.g., cisgender girls and women) that are pre-menarche, pre-parous, postpartum, or perimenopausal. We describe a hypothetical, multilevel clustered-randomized control trial (cRCT) that provides psychoeducation on racism-related trauma and free delivered groceries to both treatment and control groups, while randomizing 30 clusters of housing associations to receive either sexual health clinics at their housing association or free vouchers for healthcare. We embed mixed methods (diaries, interviews, surveys, mobile apps, observation) into the design to evaluate the effectiveness of the 1-year intervention, in addition to determining the impact on participants through their perspectives. Through this illustration, we provide a novel example of how structural interventions can apply mixed methods to evaluate effectiveness while delivering services to populations impacted by multiple structural factors. We demonstrate how qualitative and quantitative approaches can be paired in clustered RCTs and how a living logic model can empirically incorporate the population perspective into more effective interventions. Lastly, we reveal how sensitive menstrual health is to structural factors and how upstream improvements will trickle down to potentially reduce health disparities in reproductive health.
月经周期特征在很大程度上被认为是不可改变的生殖因素，这种观点阻止了人们探索结构因素如何干扰月经健康。鉴于结构性因素（如健康食品和医疗保健的可及性）对生殖健康的影响，以及迫切需要针对以黑人为特征的顺性别女性的已知生殖健康差异采取结构性干预措施，科学界必须开始研究结构性因素如何影响月经健康。为了探索此类研究，我们运用批判种族理论和交叉性理论来说明改善月经周期健康的结构性干预措施可能是什么样子。以那些最需要帮助的人为中心，即居住在曼哈顿北部食品和医疗保健荒漠中的黑人和/或拉丁裔，我们的示例包括四个月经人群（例如，初潮前的顺性别女孩和女性、未生育过的女性、产后女性和围绝经期女性）。我们描述了一个假设的、多层次聚类随机对照试验（cRCT），该试验为治疗组和对照组提供与种族主义相关创伤有关的心理教育，并免费提供食品杂货，同时将 30 个住房协会集群随机分配到接受住房协会的性健康诊所或免费医疗保健代金券。我们将混合方法（日记、访谈、调查、移动应用程序、观察）嵌入设计中，以评估为期 1 年的干预措施的有效性，此外还通过参与者的观点来确定对他们的影响。通过这种说明，我们提供了一个如何通过混合方法来评估有效性的结构干预的新示例，同时为受多种结构因素影响的人群提供服务。我们展示了如何在聚类 RCT 中结合定性和定量方法，以及如何通过实证将人群观点纳入更有效的干预措施的活逻辑模型。最后，我们揭示了月经健康对结构因素的敏感性，以及上游的改善如何可能减少生殖健康中的健康差异。
