Objectives. To develop computable phenotype algorithms to identify a transgender and gender-diverse (TGD) cohort by using diverse data sources in All of Us, a national community-engaged program to facilitate health equity in the United States by partnering with 1 million participants. Methods. We identified TGD individuals in All of Us by applying inclusion criteria based on conditions, laboratory measurements, or medications related to being TGD in electronic health record data or confirmed survey responses, using participant data collected between May 31, 2017, and July 1, 2022. Results. Of 413 457 participants, we identified 4781 (1.2%) as TGD. Participants aged 18 to 29 years (26.1% vs 8.2%), who were bisexual (20.7% vs 3.5%), with annual income of less than $25 000 (35.9% vs 24.7%), and with housing security concerns (31.9% vs 16.0%) accounted for a larger proportion of TGD individuals than non-TGD individuals. Conclusions. Combining survey and electronic health record data enables the identification of TGD individuals who have been missed by previous studies that used survey data alone in All of Us to explore health disparities in TGD people. (Am J Public Health. Published online ahead of print June 5, 2025:e1-e10. https://doi.org/10.2105/AJPH.2025.308129).

目的。 利用“全民参与”项目中多样化的数据来源开发可计算的表型算法，以识别美国促进健康公平的一百万参与者中的跨性别和性别多样性（TGD）群体。“全民参与”是一个全国性的社区参与计划。
方法。 我们通过应用基于条件、实验室检测结果或与跨性别身份相关的药物的纳入标准，在电子健康记录数据或确认的调查回复中识别“全民参与”项目中的 TGD 个体，使用了参与者在2017年5月31日至2022年7月1日之间收集的数据。
结果。 在413,457名参与者中，有4,781人（1.2%）被确定为 TGD。年龄在18至29岁之间的参与者（占TGD群体的26.1%，而非TGD群体的8.2%）、双性恋者（占TGD群体的20.7%，而非TGD群体的3.5%）、年收入低于 25,000 美元的人群（占 TGD 群体的35.9%，而非TGD群体的24.7%）以及有住房安全担忧的人群（占TGD群体的31.9%，而非TGD群体的16.0%），在TGD个体中所占比例高于非TGD个体。
结论。 结合调查数据和电子健康记录数据，能够识别出仅使用调查数据的研究之前未能发现的 TGD 个体，从而有助于“全民参与”项目探索跨性别人群中的健康差异。（Am J Public Health. 2025年6月5日在线发表。https://doi.org/10.2105/AJPH.2025.308129）。