ECEESPE2025 ePoster Presentations Reproductive and Developmental Endocrinology (128 abstracts)
1Faculty of Medical Sciences, Medical University of Silesia, Department of Pediatrics and Pediatric Endocrinology, Katowice, Poland; 2Upper Silesian Child Health Center, Public Clinical Hospital No. 6 of the Silesian Medical University, Institute of Psychology, University of Silesia, Katowice, Poland; 3Pediatric Institute - Medical College, Jagiellonian University in Cracow, Department of Pediatric and Adolescent Endocrinology, Cracow, Poland; 4Institute of Psychology, University of Silesia, Katowice, Poland; 5Faculty of Law and Administration, University of Silesia, Katowice, Poland
JOINT3390
Introduction: The rise in referrals of transgender and gender diverse children and adolescents to clinical diagnosis is a widely discussed topic around the word. Similarly to adult population they are at risk for weight-related problems resulting from pathological eating behaviors, which in turn negatively influence the individuals metabolic health.
Aim: We assess the basic sociodemographic and metabolic profile of the youth population in the first clinical unit dedicated to transgender youth in our country.
Methods: This prospective study has examined a consecutive series of transgender and gender diverse children and adolescents (TGDC&A) based on WPATH SOC-8 between July/2017 and Sep/2024. Clinical and laboratory data was collected in unified medical records. Sociodemographic and TGDC&A history has been analysed alongside anthropometric and metabolic parameters. The population has been divided into registered female (RFAB) or male at birth (RMAB) groups.
Results: The population consists of 269 participants (230 RFAB, 39 RMAB), with increasing number of diagnosis in subsequent years 2017 (July-Dec) - 2/0, 2018 - 9/0 2019-16/3, 2020-18/4, 2021- 52/3, 2022- 68/22, 2023- 51/4, 2024 (Jan-Sep) 14/3 (RFAB/RMAB, respectively), with the mean/median age of diagnosis 15.8/16.1 years and the mean age of gender identity mismatch onset of 12 years. BMI distribution, fasting components of the metabolic syndrome and cortisol in circadian rhythm are presented in table.
Variables | all (n = 269) | RFAB (n = 230) | RMAB (n = 39) | |
BMI (centiles) | >97[n/%] | 61/22.7 | 56/24.3 | 5/12.8 |
90-97 [n/%] | 33/12.3 | 29/12.6 | 4/10.3 | |
10-90[n/%] | 150/55.8 | 126/54.8 | 24/61.5 | |
3-10 | 15/5.6 | 13/5.7 | 2/5.1 | |
<3 | 10/3.7 | 6/2.6 | 4/10.3 | |
z-score BMI (IOTF) [median, mean+/-SD] | 0.660.72+/-1.2 | 0.74 0.79+/-1.2 | 0.27 0.35+/-1.3 | |
Fasting blood | glucose = or >100 mg/dl | 16/5.9 | 14/6.1 | 2/5.1 |
HOMA-IR >2.5 | 94/34.9 | 80/34.8 | 14/35.9 | |
triglycerides >150 mg/dl | 20/7.4 | 20/8.7 | 0/0.0 | |
HDL-cholesterol <40 mg/dl | 26/9.7 | 18/7.8 | 8/20.5 | |
morning cortisol > 25mg/dl | 4/1.5 | 4/1.7 | 0/0.0 | |
midnight cortisol >5.7mg/dl | 17/6.3 | 15/6.5 | 2/5.1 |
Conclusions: Sociodemographic fluctuations in the proportion of RFAB/RMAB are visible, however difficult to explain now. The increased risk of abnormal BMI, mostly elevated in RFAB and decreased in RMAB, and higher risk of metabolic syndrome/complications are key issues to consider when preparing patients with GI/GD for medical transition.