Search

BACKGROUND AND OBJECTIVES: The effects of endocrinological treatment on cardiovascular risk abstract profile in transgender adolescents are unknown. In this retrospective cohort study, we aim to investigate these effects and assess obesity and dyslipidemia prevalence in transgender adolescents at 22 years compared with peers. METHODS: Changes in BMI, systolic blood pressure (SBP), diastolic blood pressure (DBP), glucose, homeostatic model assessment for insulin resistance (HOMA-IR), and lipid values during treatment, along with the prevalence of obesity and dyslipidemia at 22 years, were recorded in 71 transwomen and 121 transmen who started gonadotropin-releasing hormone agonists in their adolescence (15 years), with a subsequent addition of sex hormones (17 years). RESULTS: In transwomen, changes in BMI (13.0; 95% confidence interval [CI] 1.6 to 4.4), SBP (22 mmHg; 95% CI 27 to 3), DBP (110 mmHg; 95% CI 7 to 14), glucose (0.0 mmol/L; 95% CI 20.2 to 0.2), HOMA-IR (10.6; 95% CI 20.6 to 1.9), and lipid values were similar or more favorable compared with peers. The same was true for transmen regarding changes in BMI (12.3; 95% CI 1.7 to 2.9), SBP (17 mmHg; 95% CI 3 to 10), DBP (17 mmHg; 95% CI 5 to 10), glucose (10.1 mmol/L; 95% CI 20.1 to 0.3), HOMA-IR (20.2; 95% CI 20.8 to 0.3), and lipid values. At age 22, obesity prevalence was 9.9% in transwomen, 6.6% in transmen, 2.2% in ciswomen, and 3.0% in cismen. CONCLUSIONS: Generally, endocrinological treatment in transgender adolescents is safe regarding cardiovascular risk. Because obesity is more prevalent in transgender adolescents compared with peers, body weight management should be important during the medical trajectory. [ABSTRACT FROM AUTHOR]

Chapter 18 of the book "Handbook of Longitudinal Research: Design, Measurement, and Analysis," edited by Scott Menard is presented. It provides a distinction between studies with only one follow-up measurement and studies with more than one follow-up measurement in most Randomized controlled trials (RCTs). It explores on the different statistical techniques that can be used for the analysis of recurrent event data.