Epidemiological considerations in transgender health: A systematic review with focus on higher quality data
Why this work is in the frame
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Bibliographic record
Abstract
Background: High quality data pertaining to the size of the transgender and gender diverse (TGD) population are scant, however, several recently published studies may provide more reliable contemporary estimates.Aims: To summarize the estimated number and proportion of TGD individuals overall and across age groups, based on most accurate data.Methods: This systematic review focused on recent studies (published from 2009 through 2019) that utilized sound methodology in assessing the proportion of TGD people in the general population. Publications were included if they used clear definitions of TGD status, and calculated proportions based on a well-defined sampling frame. Nineteen eligible publications represented two broad categories of studies: those that used data from large health care systems; and those that identified TGD individuals from population surveys.Results: Among health system-based studies, TGD persons were identified using relevant diagnostic codes or clinical notes. The proportions of individuals with a TGD-relevant diagnosis or other recorded evidence ranged between 17 and 33 per 100,000 enrollees. In population surveys TGD status was ascertained based on self-report with either narrow or broad definitions. The survey-based estimates were orders of magnitude higher and consistent across studies using similar definitions. When the surveys specifically inquired about ‘transgender’ identity, the estimates ranged from 0.3% to 0.5% among adults, and from 1.2% to 2.7% among children and adolescents. When the definition was expanded to include broader manifestations of ‘gender diversity’, the corresponding proportions increased to 0.5-4.5% among adults and 2.5-8.4% among children and adolescents. Upward temporal trends in the proportion of TGD people were consistently observed.Conclusions: Current data indicate that people who self-identify as TGD represent a sizable and increasing proportion of the general population. This proportion may differ, depending on inclusion criteria, age, and geographic location, but well-conducted studies of similar type and design tend to produce comparable results.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it