Considerations for collecting and analyzing longitudinal data in observational cohort studies of transgender, non-binary, and gender diverse people.

Autor:	Bailey S; The Matilda Centre for Research in Mental Health and Substance Use, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia., Newton N; The Matilda Centre for Research in Mental Health and Substance Use, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia., Perry Y; Telethon Kids Institute, University of Western Australia, Perth, WA, Australia., Grummitt L; The Matilda Centre for Research in Mental Health and Substance Use, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia., Smout S; The Matilda Centre for Research in Mental Health and Substance Use, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia., 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.
Jazyk:	angličtina
Zdroj:	International journal of transgender health [Int J Transgend Health] 2023 Nov 21; Vol. 25 (4), pp. 998-1003. Date of Electronic Publication: 2023 Nov 21 (Print Publication: 2024).
DOI:	10.1080/26895269.2023.2281527
Abstrakt:	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. Competing Interests: No potential conflict of interest was reported by the authors. (© 2023 The Author(s). Published with license by Taylor & Francis Group, LLC.)
Databáze:	MEDLINE
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