Pubertal Suppression, Bone Mass, and Body Composition in Youth With Gender Dysphoria
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES Puberty onset and development contribute substantially to adolescents’ bone mass and body composition. Our objective with this study was to examine the effects of gonadotropin-releasing hormone agonists (GnRHa) on these puberty-induced changes among youth with gender dysphoria (GD). METHODS Medical records of the endocrine diversity clinic in an academic children’s hospital were reviewed for youth with GD seen from January 2006 to April 2017 with at least 1 baseline dual-energy radiograph absorptiometry measurement. RESULTS At baseline, transgender females had lower lumbar spine (LS) and left total hip (LTH) areal bone mineral density (aBMD) and LS bone mineral apparent density (BMAD) z scores. Only 44.7% of transgender youth were vitamin D sufficient. Baseline vitamin D status was associated with LS, LTH aBMD, and LS BMAD z scores. Post-GnRHa assessments revealed a significant drop in LS and LTH aBMD z scores (transgender males and transgender females) without fractures and LS BMAD (transgender males), an increase in gynoid (fat percentage), and android (fat percentage) (transgender males and transgender females), and no changes in BMI z score. CONCLUSIONS GnRHa monotherapy negatively affected bone mineral density of youth with GD without evidence of fractures or changes in BMI z score. Transgender youth body fat redistribution (android versus gynoid) were in keeping with their affirmed gender. The majority of transgender youth had vitamin D insufficiency or deficiency with baseline status associated with bone mineral density. Vitamin D supplementation should be considered for all youth with GD.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".