Bailey S, Newton N, Perry Y, Grummitt L, Smout S, Barrett E
The Matilda Centre for Research in Mental Health and Substance Use, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia.
Telethon Kids Institute, University of Western Australia, Perth, WA, Australia.
Int J Transgend Health. 2023 Nov 21;25(4):998-1003. doi: 10.1080/26895269.2023.2281527. eCollection 2024.
The health and well-being of transgender, non-binary, and gender-diverse people is receiving increasing attention from epidemiologists and public health researchers, including those utilizing longitudinal observational cohort studies. These longitudinal studies are advantageous over cross-sectional observational study designs given their scope over several timepoints rather than one, and when exposures and outcomes are prospectively measured this improves validity of causal claims. However, within these longitudinal studies, gender is often collected inconsistently (e.g. only asked at a single timepoint), or inadequately (e.g. questions that use limiting notions of gender). Due to the temporal nature of gender, this introduces potential including misclassification error and may provide an incomplete picture of gender diversity in a sample. This article considers these methodological issues and offers evidence-based recommendations to ensure longitudinal data on trans, non-binary, and gender-diverse people is treated with epidemiological rigor, while maintaining inclusivity.
跨性别者、非二元性别者和性别多样化者的健康与福祉正受到流行病学家和公共卫生研究人员越来越多的关注，包括那些开展纵向观察队列研究的人员。这些纵向研究相较于横断面观察性研究设计具有优势，因为其涵盖多个时间点而非一个时间点，并且当对暴露因素和结果进行前瞻性测量时，这会提高因果关系主张的有效性。然而，在这些纵向研究中，性别信息的收集往往不一致（例如仅在单个时间点询问）或不充分（例如使用有限性别概念的问题）。由于性别的时间特性，这会带来包括错误分类误差在内的潜在问题，并且可能无法全面呈现样本中的性别多样性。本文探讨了这些方法学问题，并提供基于证据的建议，以确保在保持包容性的同时，严谨地运用流行病学方法处理有关跨性别者、非二元性别者和性别多样化者的纵向数据。
