0812 Sleep Health Changes in Transgender Adults Initiating Gender-Affirming Hormone Therapy: A Systematic Review

Abstract Introduction Transgender and gender diverse (TGD) adults are at elevated risk of poor sleep health. Gender-affirming hormone therapy (GAHT) is widely used to relieve gender dysphoria and increase quality of life in this population. Hormone-driven changes in thermoregulation, mood, and stress may plausibly either improve or disrupt sleep. However, the relationship between GAHT and sleep health has not been systematically reviewed. This review synthesizes evidence on how GAHT initiation influences sleep health in TGD adults. However, the relationship between GAHT and sleep health has not been systematically reviewed. We synthesized the evidence on GAHT initiation and sleep health in TGD adults and followed PRISMA guidelines. Methods Three reviewers systematically searched three databases (PubMed, PsycINFO, Web of Science) in January 2025. The search was limited to prospective studies of GAHT initiation in TGD adults that included sleep health outcomes (i.e., regularity, duration, quality, alertness, timing, and efficiency) and included at least one follow-up. We assessed risk of bias with the ROBINS-I and synthesized results by hormone type (i.e., testosterone or estrogen/anti-androgens) and sleep health outcome. Results Nine of 957 screened articles met inclusion criteria, representing samples of 6–262 TGD adults initiating GAHT. Follow-ups ranged from 3 to 12 months. Sleep outcomes included total sleep time, sleep efficiency, sleep onset latency, wake after sleep onset, sleep architecture, insomnia, fatigue, and chronotype. Outcomes assessed using polysomnography (n=1), EEG or single-channel EEG (n=2), and validated (n=3) or unvalidated (n=3) self-report measures. Initiating estrogen/anti-androgen was associated with modest increases in EEG-derived N1 sleep. Initiating testosterone was associated with temporary increases in fatigue at 3 months that returned to baseline by 9 and 12 months. Risk of bias ranged from moderate (n=1) to critical (n=8) due to the use of unvalidated measures and inadequate control of confounding variables. Conclusion Most observed changes in sleep health were small and not clinically significant. The use of overlapping datasets, measurement variability, and a high risk of bias across studies limit the ability to draw clear conclusions about GAHT’s effects on sleep health. Larger studies that address extraneous variables are needed to clarify these relationships. Support (if any)