Transgender identity in young people and adults recorded in UK primary care electronic patient records: retrospective, dynamic, cohort study

Abstract

Objectives
To quantify the change in proportion of young people and adults identified as transgender in UK primary care records and to explore whether rates differ by age and socioeconomic deprivation.

Design
Retrospective, dynamic, cohort study.

Setting
IQVIA Medical Research Data, a database of electronic primary care records capturing data from 649 primary care practices in the UK between 1 January 2000 and 31 December 2018.

Participants
7 064 829 individuals aged 10-99 years, in all four UK countries.

Main outcome measures
Diagnostic codes indicative of transgender identity were used. Sex assigned at birth was estimated by use of masculinising or feminising medication and procedural/diagnostic codes.

Results
2462 (0.03%) individuals had a record code indicating a transgender identity. Direction of transition could be estimated for 1340 (54%) people, of which 923 were assigned male at birth, and 417 were assigned female at birth. Rates of recording in age groups diverged substantially after 2010. Rates of the first recording of codes were highest in ages 16-17 years (between 2010 and 2018: 24.51/100 000 person years (95% confidence interval 20.95 to 28.50)). Transgender codes were associated with deprivation: the rate of the first recording was 1.59 (95% confidence interval 1.31 to 1.92) in the most deprived group in comparison with the least deprived group. Additionally, the rate ratio of the proportion of people who identified as transgender was 2.45 (95% confidence interval 2.28 to 2.65) in the most deprived group compared with the least deprived group. Substantial increases were noted in newly recorded transgender codes over time in all age groups (1.45/100 000 person years in 2000 (95% confidence interval 0.96 to 2.10) to 7.81/100 000 person years in 2018 (6.57 to 9.22)). In 2018, the proportion of people with transgender identity codes was highest in the age groups 16-17 years (16.23 per 10 000 (95% confidence interval 12.60 to 20.57)) and 18-29 years (12.42 per 10 000 (11.06 to 13.90)).

Conclusion
The rate of transgender identity recorded in primary care records has increased fivefold from 2000 to 2018 and is highest in the 16-17 and 18-29 age groups. Transgender diagnostic coding is associated with socioeconomic deprivation and further work should investigate this association. Primary and specialist care should be commissioned accordingly to provide for the gender specific and general health needs of transgender people.

Full text

McKechnieDGJ,
etal
.
BMJMED
2023;2:e000499. doi:10.1136/bmjmed-2023-000499 1
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►Additional supplemental
material is published online
only. To view, please visit the
journal online (http:// dx. doi.
org/ 10. 1136/ bmjmed- 2023-
000499).
For numbered aliations see
end of article.
Correspondence to: Dr Douglas
Gordon John McKechnie,
University College London
Research Department of Primary
Care and Population Health,
London, London, UK;
douglas. mckechnie. 11@ ucl. ac. uk
Cite this as:
BMJMED
;:e. doi:./
bmjmed--
Received: 12 January 2023
Accepted:  June 
Transgender identity in young people and adults recorded in UK
primary care electronic patient records: retrospective, dynamic,
cohortstudy
Douglas Gordon John McKechnie ,1 Elizabeth O'Nions ,2 Julia Bailey ,1 Lorna Hobbs,3
Frank Gillespie,4 Irene Petersen1
WHAT IS ALREADY KNOWN ON THIS TOPIC
⇒Accurately determining the size and distribution of transgender populations
is challenging, but important for service planning, specialist healthcare
resource allocation, and clinician training
⇒The last study from the UK based on primary care records that attempted to
estimate this size and distribution of transgender populations was in 1998
⇒Few studies have examined the association between socioeconomic
deprivation and transgender identity at the population level
WHAT THIS STUDY ADDS
⇒Estimates of the rates and proportion of people with a record of transgender
identity in UK primary care health records during 2000- 18 were reported
⇒Rates of recorded transgender identity have increased in all age groups over
time, and are highest in ages 16- 29 years
⇒Recorded transgender identity was associated with living in areas of
socioeconomic deprivation
HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE, OR POLICY
⇒Sucient resources, support, and training must be provided to primary and
specialist care to adequately meet the healthcare needs (general and gender
specic) of transgender people
⇒Reasons for the association between socioeconomic deprivation (particularly
parental deprivation) and rates of recorded transgender identity are unclear;
further research should explore this association
⇒Recognition and recording of transgender identity in primary care records
provides opportunities for observational research (eg, comorbid physical and
mental health conditions, healthcare use, screening, and mortality)
ABSTRACT
OBJECTIVES To quantify the change in proportion of
young people and adults identied as transgender
in UK primary care records and to explore whether
rates dier by age and socioeconomic deprivation.
DESIGN Retrospective, dynamic, cohort study.
SETTING IQVIA Medical Research Data, a database
of electronic primary care records capturing data
from 649 primary care practices in the UK between 1
January 2000 and 31 December 2018.
PARTICIPANTS 7 064 829 individuals aged 10- 99
years, in all four UK countries.
MAIN OUTCOME MEASURES Diagnostic codes
indicative of transgender identity were used.
Sex assigned at birth was estimated by use of
masculinising or feminising medication and
procedural/diagnostic codes.
RESULTS 2462 (0.03%) individuals had a record
code indicating a transgender identity. Direction of
transition could be estimated for 1340 (54%) people,
of which 923 were assigned male at birth, and 417
were assigned female at birth. Rates of recording in
age groups diverged substantially aer 2010. Rates
of the rst recording of codes were highest in ages
16- 17 years (between 2010 and 2018: 24.51/100
000 person years (95% condence interval 20.95
to 28.50)). Transgender codes were associated
with deprivation: the rate of the rst recording was
1.59 (95% condence interval 1.31 to 1.92) in the
most deprived group in comparison with the least
deprived group. Additionally, the rate ratio of the
proportion of people who identied as transgender
was 2.45 (95% condence interval 2.28 to 2.65) in
the most deprived group compared with the least
deprived group. Substantial increases were noted
in newly recorded transgender codes over time in
all age groups (1.45/100 000 person years in 2000
(95% condence interval 0.96 to 2.10) to 7.81/100
000 person years in 2018 (6.57 to 9.22)). In 2018,
the proportion of people with transgender identity
codes was highest in the age groups 16- 17 years
(16.23 per 10 000 (95% condence interval 12.60 to
20.57)) and 18- 29 years (12.42 per 10 000 (11.06 to
13.90)).
CONCLUSION The rate of transgender identity
recorded in primary care records has increased
vefold from 2000 to 2018 and is highest in
the 16- 17 and 18- 29 age groups. Transgender
diagnostic coding is associated with socioeconomic
deprivation and further work should investigate this
association. Primary and specialist care should be
commissioned accordingly to provide for the gender
specic and general health needs of transgender
people.
Introduction
Transgender, or trans, is an umbrella term that
describes a diverse group of people whose gender
identity diers from their sex assigned at birth.1 Some
transgender people experience gender dysphoria—ie,
distress stemming from the dierence between their
gender identity and sex assigned at birth—and some
seek gender arming medical care, such as hormone
treatment and gender armation surgery.2 Some
individuals may also seek out psychological support
to help to explore their gender identity before (or
in the process of) making decisions about physical
interventions.
UK National Health Service (NHS) specialist gender
identity clinics have, historically, not accepted

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self- referrals, and so individuals seeking gender
arming specialist care must first be referred by an
NHS primary care clinician. Some clinics now do
allow self- referral, but still require that patients are
registered with an NHS primary care practice, with
whom the service will share care.3 Primary care clini-
cians are expected by the UK’s medical regulator to
refer such patients without delay and to work collab-
oratively with specialist gender services, including
prescribing and monitoring gender arming
hormones on the basis of specialist recommenda-
tions, where appropriate.4 The number of referrals to
specialist gender clinics has increased substantially
in recent years, among children, adolescents,5 and
adults.6 Waiting times for NHS gender clinics may
stretch to several years.7 As a consequence, some
people seek private gender care; although, the exact
number that do so is unclear.8 9 Self- medication
with hormone treatment, obtained from illicit or
quasi- legal sources, may also be widespread among
some groups of transgender people.10 Primary care
clinicians may still, however, be involved in gender
care for people accessing treatment outside of the
NHS. Shared care requests from the private sector
(for primary care to take over hormone prescribing)
are common4 11; and the UK's medical regulator has
suggested that clinicians might justifiably choose to
take over bridging prescribing as a harm reduction
measure for some people who are self- prescribing.4
Primary care also retains responsibility for providing
general physical and mental healthcare for their
transgender patients, and a need to take gender
identity into account to ensure appropriate access to
screening programmes, such as cervical screening
for trans men.12
Many transgender people experience diculties
accessing appropriate medical care, whether that be
gender care or general healthcare.2 13 Transgender
people experience stigma, discrimination, exclusion,
and harassment, including in healthcare settings.2
Transgender people may be reticent to disclose their
gender identity to clinicians due to fear of stigma-
tisation: transgender people report encountering
clinicians who deny the existence of transgender as a
legitimate identity or refuse to refer them to specialist
gender care.14
Estimates of the proportion of the population who
identify as transgender vary, depending on the defi-
nition and method used. Studies based on surveys
of general populations report much higher rates
of self- identification as transgender, non- binary,
gender diverse or gender questioning than those
examining diagnostic coding of transgender iden-
tity in healthcare records.15 Among people who are
transgender, only a subset will identify themselves
within primary care—eg, individuals with emotional
distress who seek support, those requesting gender
arming treatment, or those who otherwise believe
their primary care physicians should know that
they are transgender. A subset of this group will be
referred on for specialist gender care. The proportion
of people identified as having transgender identity is
therefore likely to be higher in primary care samples
than in secondary care samples, but lower than the
proportion of people identifying as transgender in
the general population.
Understanding the size and distribution of the
transgender population is critically important for
service design, resource allocation, and sta training,
but estimating these factors is challenging,15 and
high quality data are scarce.16 In 1998, Wilson and
colleagues, using a cross- sectional survey of general
practitioners in Scotland, estimated the proportion
of people with gender dysphoria among those older
than 15 years to be 0.82 per 10 000 individuals.17
No large scale, nationally representative, longitu-
dinal studies have estimated the rates and propor-
tion of transgender adolescents and adults identified
within the UK's national public primary care system.
We therefore aimed to report the proportion and
change over time in rates of transgender people
who presented to health care services based on UK
primary care records.
Method
Study design
This cohort study was population based and used
data from IQVIA Medical Research Data (IMRD), a
proprietary database of anonymised clinical record
data. IMRD incorporates data from The Health
Improvement Network, a Cegedim database. The
cohort study was dynamic; participants could enter
and leave the study throughout the time period of
interest.
Use of the terms incidence and prevalence have
been criticised in the context of transgender health:
firstly, for pathologising trans identity18 19; and
secondly, for implying that transgender identity has
an easily identifiable time of onset.15 In this article,
we use the terms rate of first recording and propor-
tion identified as transgender instead. From a statis-
tical perspective, these figures are calculated in the
same way as incidence and prevalence, and the rate
ratios for newly recorded transgender codes and
proportion identified as transgender are equivalent
to incidence rate ratios and prevalence rate ratios.
Setting
In the UK, almost all of the population are regis-
tered with an NHS primary care practice.20 Access
is free of charge. The database IMRD contains
de- identified data drawn from routinely collected
primary care records. Approximately 6% of the UK's
population are included in IMRD. This database
is generally representative of the UK primary care
population.21 Individuals can be registered at only
one NHS primary care practice at a time: registering

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with a new practice triggers de- registration from the
old practice. Diagnoses and observations are coded
using the Read system, which is a hierarchical coding
system including both diagnosis and symptoms.22
Social deprivation is estimated using the Townsend
score, a combined measure of unemployment, car
ownership, home ownership, and household over-
crowding.23 Scores are defined for areas of approxi-
mately 150 households and grouped into fifths. The
least deprived areas are slightly over- represented in
IMRD, and the most deprived areas slightly under-
represented: in 2009, 23.5% of patients active in the
database belonged to the least deprived fifth, and
14.6% to the most deprived fifth.21
Adjusting for deprivation status in the data anal-
ysis is therefore important for its generalisability to
the UK population. Townsend scores are calculated
based on 2001 UK census data; people living in resi-
dential areas built after 2001, therefore, do not have
data for deprivation in this dataset. We opted to use
a complete case analysis, excluding individuals and
practices with missing data for deprivation; use of
a missing indicator method was likely to bias any
analysis investigating a linear trend across the five
groups.24
Study population
We included data for individuals from 649 practices,
excluding practices with missing data on Townsend
deprivation (138 practices), and seven practices that
supplied less than full calendar year of data. Roughly
8200 NHS general practitioner (GP) practices were
recorded in the entire UK in 2021, although this
number has been falling as smaller practices have
tended to close over time.25–28
To determine the rate of first recording of trans-
gender identity over time, we included all indi-
viduals aged 10- 99 years who were permanently
registered at a participating GP practice between 1
January 2000 and 31 December 2018; 2018 were
the most recent data available at the time of the
study. Individuals were included if they did not
have a code suggestive of transgender identity on
their records prior to, or within three months of,
their registration at the practice (codes within three
months were more likely to reflect re- coding of trans-
gender identity already recorded at the individual's
previous practice, based on visual inspection of
Lewis plots29).
To determine the proportion of individuals with
transgender identity over time, we included all indi-
viduals aged 10- 99 years who were permanently
registered at a participating practice and provided
at least one full calendar year of data between 1
January 2000 and 31 December 2018. We consid-
ered individuals to be transgender from the date
that the first qualifying code was recorded from then
onwards.
Denition of main outcome
A list of Read codes indicating transgender identity
was developed using established methods30 and is
presented in the online supplemental table 1. The
presence of any of these codes in individuals' medical
records was the main outcome measure.
Identifying direction of transition
We sought to identify the direction of transition of
individuals (ie, transmasculine—assigned female at
birth and identifying as male, and transfeminine—
assigned male at birth and identifying as female).
The database, IMRD, contains a variable for
gender, coded as male or female. Whether this code
refers to sex assigned at birth or current gender is
not possible to determine; individuals can request
to change their gender in primary care records at
any time, and without any other requirements (such
as after obtaining a gender recognition certificate,
or having seen a specialist gender clinic).31 NHS
numbers (the unique patient identifier given to every
permanently registered NHS patient at a practice),
and the unique identifier by which individual patient
records are tracked within practices in the database,
can only be male or female and this gender categori-
sation cannot change. A patient wishing to change
their gender is, therefore, de- registered under the
old NHS number, and re- registered under a new NHS
number. Information from the old record should be
transferred into the new one. In IMRD, this process
would appear as a patient of one gender deregis-
tering and a new one of another gender registering
a similar time. However, distinguishing this change
from two dierent people of dierent genders leaving
and joining would be very dicult, particularly as
patient level data in the database are pseudonymised
(eg, birth dates are given by year only).
We opted instead to attempt to identify the direc-
tion of transition by examining related diagnostic
codes and prescribed medications. Lists of exami-
nation findings and procedures suggesting patients
who were assigned male at birth (eg, orchidectomy
or construction of vagina) or assigned female at
birth (eg, total abdominal hysterectomy or cervical
screening normal) were constructed. These codel-
ists are presented in the online supplemental
tables 2 and 3. Lists of masculinising (ie, testos-
terone) and feminising medications (ie, oestrogens,
GnRH (gonadotropin hormone- releasing hormone
analogues, finasteride, spironolactone, dutasteride,
and cyproterone) were also developed. Oestrogens
and cyproterone were only included as sole ingre-
dient formulations, that is, combined oral contracep-
tives containing oestrogens and progestogens were
not included.
Among individuals with a transgender code (as
defined above), presence of an assigned male at
birth suggesting code or any prescription of femi-
nising medication, or both, was taken to indicate

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transfeminine status. Presence of a code suggesting
assigned female at birth or any prescription of mascu-
linising medication, or both, was taken to indicate
transmasculine status. DGJM individually reviewed
and adjudicated for conflicted data (eg, individuals
with a record containing both assigned male at birth
and assigned female at birth codes).
Statistical analysis
Analyses were stratified by age group, Townsend
deprivation score, and calendar year.
The rate of new recording of transgender identity
was estimated per 100 000 person years as the total
number of people with newly recorded transgender
identity between 2000 and 2018, divided by the
total number of person years of follow- up. Person
time was calculated as the time between the latest
of: 10th birthday; three months after registration at
the practice; 1 January 2000; acceptable computer
usage date; acceptable mortality recording date (the
latter two are quality assurance measures32 33), and
the earliest of: date of first recorded transgender read
codes; date of death; date of leaving the practice;
date of last data collection from the practice; 99th
birthday; 31 December 2018.
The proportion of people with transgender Read
codes was determined by dividing the total number
of people with a qualifying code by the total number
of individuals in the eligible cohort (ie, all people
aged 10- 99, registered for at least one full calendar
year), over the time period of interest (eg, the entire
period, or for each calendar year when calculating
proportion by year). Individuals could contribute
data for more than one calendar year.
Poisson regression was done to obtain confidence
intervals for the rate of newly recorded transgender
identities and the proportion of people with trans-
gender identity.
Multivariable Poisson regression models, with (log)
person time as an oset, were used to determine rate
ratios for newly recorded transgender status and risk
ratios for proportions, adjusting for age, Townsend
deprivation scores, and calendar year. Multilevel
random intercept models were used to adjust for the
eect of clustering by GP practice. Wald tests were
used to examine for evidence of a linear relation
between increasing Townsend deprivation score and
transgender identity recording or proportion. Nested
models, incorporating an interaction term, and
a likelihood ratio test were used to examine for an
interaction between age (dichotomised as <18 years
and ≥18 years) and socioeconomic deprivation.
Visual inspection of the association between
calendar year, rate of new recording, and proportion
of people with trans identity, showed that rates and
proportions were similar between age groups from
2000 to 2009, but diverged hugely beyond that point.
Adding an interaction term ((2009 or earlier/2010 or
later)*(age group)) to the multivariable modelling
showed a highly significant interaction (P<0.0001)—
that is, the association between new trans recordings
or trans proportions and age group diered between
2000 and 2009 and 2010 and 2018. Rates of new
recordings or proportions by age group were there-
fore reported separately for those two time periods.
Statistical analysis was performed using Stata
17.0 (StataCorp, College Station, TX, USA).
Sensitivity analyses
To investigate the eect of excluding individuals and
practices with missing Townsend data, we performed
a sensitivity analysis to compare the point estimates
obtained for rate of recoding and proportion with
the full data set, versus the complete case analysis
used above. The point estimates did not substantially
dier. We therefore opted to retain the complete case
analysis method; not adjusting for deprivation status
leads to a slight bias towards least deprived areas,
which are over- represented in the database.
Patient and public involvement
Transgender and non- binary people were involved
in the conduct of this research. One coauthor is non-
binary, and another is transgender and has personal
experience of seeking and receiving gender arming
care in the UK. Both coauthors were involved from
the stage of interpretation and reporting of the find-
ings, including the writing and critical revision of
this paper, and have advised on appropriate methods
of dissemination of the findings.
The research findings cannot be sent directly to the
participants in the research because they are not indi-
vidually identifiable by the researchers. The results
will be disseminated to transgender and non- binary
people through traditional media, social media, and
communication with organisations supporting trans
and non- binary people.
Results
The absolute number of people identified as trans-
gender in primary care medical records was small. Of
7 064 829 individuals aged 10- 99 years, contributing
at least a year of data between 2000 and 2018, 2462
(0.03%) had a Read code indicating transgender
identity. Between 2000 and 2018, the overall rate
of first recording of transgender identity was 2.2 per
100 000 person years (95% confidence interval 2.1
to 2.3), and the overall proportion of people who
were transgender was 1.8 (95% confidence interval
1.8 to 1.9) per 10 000.
Transmasculine and transfeminine status
Of the 2462 individuals with transgender iden-
tity, 417 (17%) appeared to be transmasculine (ie,
prescribed testosterone, or had diagnostic or proce-
dure codes suggesting that they were assigned female
at birth, or both), and 923 (37%) appeared to be
transfeminine (ie, prescribed feminising medication,

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or had diagnostic or procedure codes suggesting
that they were assigned male at birth, or both). The
remaining 1122 (46%) individuals could not be
categorised: 1096 (45%) had no relevant codes or
prescriptions to indicate the direction of transition,
and 26 (1%) had conflicting data that could not be
reconciled on manual review (eg, prescriptions for
both masculinising and feminising medications).
Owing to the high rate of missing data for trans-
masculine and transfeminine status, we opted not to
stratify by this variable in further analyses.
Changes over time
The rate of first recordings of transgender identity
increased substantially for all age groups between
2000 and 2018 (figure 1; overall, from 1.45 (95%
confidence interval 0.96 to 2.10) per 100 000 person
years to 7.81 (6.57 to 9.22) per 100 000 person
years). The greatest proportional increase from 2000
to 2018 was in the 16- 17 years age group, where the
rate of first recording increased from zero (0 to 9.04)
and 4.01 (0.49 to 14.47) per 100 000 person years,
to 78.39 (54.60 to 109.02) per 100 000 person years.
The rates of first recording appeared to markedly
increase in the 10- 12, 13- 15, 16- 17, and 18- 29 age
groups from about 2013- 14 onwards (figure1).
Likewise, the proportion of people with a recorded
transgender identity in their records increased for
all age groups over time (figure 2) (overall, from
0.68 (95% confidence interval 0.55 to 0.83) per
10 000 in 2000, to 4.71 (4.38 to 5.05) per 10 000 in
2018). Again, individuals aged 16- 17 years showed
the greatest proportionate increase, from 0.19 (0 to
1.07) per 10 000 in 2002 to 16.23 (12.60 to 20.57)
per 10 000 in 2018, with a sharp increase from 2015
onwards. Similar changes in the rate of increase were
noted in the 18- 29 years age group and in the 13- 15
years group. In 2018, the proportion of people with
transgender identity codes had reached 16.23 per
10 000 (12.60 to 20.57) in the 16- 17 years group
and 12.42 per 10 000 (11.06 to 13.90) in the 18- 29
years groups. The proportion of people with recorded
transgender identity in the 30- 39, 40- 49, and 50
years and older groups increased over time in a more
gradual way.
The full data on which figures1 and 2 are based on
are given in online supplemental tables 4 & 5.
Age and deprivation
Overall, the rate of first recordings of transgender
identity was highest in the 16- 17 years age group
(12.8 new recordings per 100 000 person years
(95% confidence interval 11.0 to 14.7)). The overall
proportion of people with recorded transgender
identity was highest in the 16- 17 (2.31 per 10 000
(95% confidence interval 2.06 to 2.59)) and 18- 29
age groups (2.67 (2.56 to 2.79)). Table 1 contains
the rates of first recordings and proportions per age
Year
Rate of new recording of transgender
identity (per 100 000 person years)
0
40
60
80
20
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
All age groups
10-12
13-15
16-17
18-29
30-39
40-49
≥50
Figure  | Rates of newly recorded transgender identity during - , by age group
Year
Proportion with recorded
transgender identity (per 10 000)
0
10
15
20
5
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
All age groups
10-12
13-15
16-17
18-29
30-39
40-49
≥50
Figure  | Proportion of people with recorded transgender identity between  and , by age group

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group between 2010 and 2018, and online supple-
mental table 6 contains the rates and proportions per
age group between 2000 and 2009.
The rate of recording of new codes and the propor-
tion of people with transgender identity showed a
clear association with deprivation. People in the
most deprived areas were 59% more likely to have
a recorded transgender identity than people in the
least deprived areas (adjusted rate ratio for new
recording 1.59 (95% confidence interval 1.31 to
1.92), P for trend<0.0001). The association was
stronger for the proportions of transgender iden-
tity, with individuals in the most deprived area
being more than twice as likely to have a recorded
transgender identity than individuals in the least
deprived areas (adjusted rate ratio for proportion
with transgender identity 2.45 (95% confidence
interval 2.28 to 2.65), P for trend<0.0001) (table1,
figures3 and 4). Socioeconomic deprivation and age
showed no evidence of interaction (P=0.69 for like-
lihood ratio test).
Discussion
Principal ndings
We report the first estimates of the rate of first
recording and proportion of young people and
adults with transgender medical record codes in a
large primary care database that is nationally repre-
sentative of the UK. The absolute number of indi-
viduals with codes related to transgender was small
(0.03%). Transgender identity was most likely to be
recorded for the first time in 16- 17 year olds, and the
proportion of people with recorded transgender iden-
tity was greatest between the ages of 16 and 29 years.
The rates of newly recorded transgender identity and
the proportion of people with a transgender code
have increased markedly in all age groups between
2000 and 2018. A clear association between socioec-
onomic deprivation and recorded transgender iden-
tity was shown.
Table 1 | Rates of new recordings and proportions of transgender identity per age group (2010- 18) and Townsend
deprivation score group (2000- 18)
Rate of newly recorded codes, per
100 000 person years (95% CI)
Rate ratio of newly
recorded codes*
(95% CI)
Proportion of people with transgender
identity, per 10 000 (95% CI)
Rate ratio of
proportion with
transgender
identity*
(95% CI)
Age group (years):
-  . (. to .) . (. to .) . (. to .) . (. to
.)
-  . (. to .) . (. to .) . (. to .) . (. to
.)
-  . (. to .)  (ref) . (. to .)  (ref)
-  . (. to .) . (. to .) . (. to .) . (. to
.)
-  . (. to .) . (. to .) . (. to .) . (. to
.)
-  . (. to .) . (. to .) . (. to .) . (. to
.)
≥ . (. to .) . (. to .) . (. to .) . (. to
.)
Townsend depriva-
tion grouping:
First (least
deprived)
. (. to .)  (ref) . (. to .)  (ref)
Second . (. to .) . (. to .) . (. to .) . (. to
.)
Third . (. to .) . (. to .) . (. to .) . (. to
.)
Fourth . (. to .) . (. to .) . (. to .) . (. to
.)
Fih (most
deprived)
. (. to .) . (. to .) . (. to .) . (. to
.)
CI=condence interval.
*Adjusted for age group, Townsend deprivation score, and calendar year.
Townsend deprivation score group
Rate of new recording of transgender
identity (per 100 000 person year)
0
2
3
4
1
1st
(least
deprived)
5th
(most
deprived)
2nd 3rd 4th
Figure  | Rate of newly recorded transgender identity,
per Townsend deprivation score group

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Strengths and limitations
This study uses a very large dataset of real- world
primary care records, from a sample that is broadly
representative of the UK primary care population, to
provide estimates with high external validity.
The main limitation of this study is the reliance on
coding of transgender identity in clinical records. To
receive a code that indicates a transgender identity,
a transgender person would need to disclose their
transgender identity to their primary care physician,
the clinician would need to consider this relevant
information to include in the clinical notes, and also
they would need to code as such using one of the
specified read codes.
The Read codes available do not fully capture
the range of gender identity, such as non- binary or
gender diverse identities, and contain various terms
that are now outdated, or misapplied (eg, transsexu-
ality). A time lag might also happen between initial
presentation to primary care and coding of trans-
gender identity, if, for example, the code is only
applied after review by a gender identity clinic (for
which the waiting time may be years). Our study
cannot capture information from transgender people
who do not share this information with their GP
practice (where stigma may preclude disclosure34),
and will therefore underestimate the true proportion
of people with transgender identities in the popula-
tion. Our study estimates the proportion of people
for whom primary care clinicians are aware of their
transgender status. Transgender individuals might
also be receiving gender care solely in the private
sector, or be self- medicating with hormone therapy,
which primary care clinicians may not be aware of.16
We were only able to characterise the direction of
transition (transmasculine or transfeminine) in just
over half of transgender people. Data for the direc-
tion of transition should ideally be collected prospec-
tively (eg, by asking individuals their sex assigned at
birth and current gender identity35), but future work
might examine alternative approaches for classifying
transmasculine and transfeminine individuals, such
as the use of free text searches. Further work should
also attempt to collect data for non- binary and
gender diverse individuals.
Ethnic group is an important intersectional factor;
transgender people from ethnic minority back-
grounds experience additional discrimination.36
Sexual orientation is distinct from gender identity,
but sexuality and gender identity can change and
interact in complex ways throughout life.37 Although
ethnic group and sexual orientation may be recorded
for some individuals in primary care, they are not
routinely recorded and, therefore, we did not include
these characteristics in our study.
The most recent data presented here is from 2018;
recording rates of transgender identity in primary
care have likely changed in the years since. If the
trends in our study have remained, these rates have
likely continued to increase; however, future work
should extend this study to later timepoints.
Our study assumed that individuals retained a
transgender identity after having any diagnostic code
added; determining whether codes were later modi-
fied or removed was not possible. Gender identity is
fluid and some people will choose not to transition
to a dierent gender, and others may detransition.38
Our estimates therefore may include people who did
not retain a transgender identity.
Comparison with existing literature
Our overall proportion estimate for transgender iden-
tity of 1.8 per 10 000 is similar to those reported by
studies based on the US healthcare system.15 39–43
Likewise, our earliest proportion estimate of 0.68
per 10 000 (95% confidence interval 0.55 to 0.83)
in 2000 is similar to that of Wilson and colleagues’
estimate of 0.82 per 10 000 in 1998.17 Our find-
ings of substantial increases in both the rate of first
recording and the proportion of people with trans-
gender identity (in all age groups) is consistent
with similar studies in US healthcare system.15 Data
from the UK also indicate increasing referral rates to
gender identity clinics,5 44 and increases in applica-
tions for gender recognition certificates.45
Our method of identifying transgender individ-
uals was based on diagnostic record codes. Other
methods used elsewhere are of self- identified gender
status, which is a more valid measure of the construct
of transgender identity that is fundamentally self-
defined.46 However, doing so requires prospective
recording of self- defined gender status, which is not
present in most electronic health records,47 including
the one on which this study is based. Free- text
searches of uncoded clinical records can also identify
additional transgender individuals.48 Free text data,
however, is variably available in research databases,
and some ethical and privacy concerns surround
making these data more accessible for analysis.49
Increasing rates of transgender codes in records
may represent increasing numbers of people
presenting to primary care with gender related
concerns. Reasons for such may include increased
availability of information, support and resources
Townsend deprivation score group
0
2
3
4
1
1st
(least
deprived)
5th
(most
deprived)
2nd 3rd 4th
Proportion with recorded
transgender identity (per 10 000)
Figure  | Proportion of people with recorded transgender
identity, per Townsend deprivation score group

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OPEN ACCESSOPEN ACCESS
online, and increased societal awareness and accept-
ance, all of which have partially destigmatised
transgender identities and may make coming out as
transgender easier for individuals.15 These increases
may also have aected by individuals' self- labelling,
for example, leading them to conceptualise gender
dysphoria and distress as an expression of a trans-
gender identity. Changes in transgender identity
recording may also represent improved recognition,
knowledge, support, and coding by primary care
clinicians.
The UK's Oce for National Statistics has just
begun to release estimates on the size of the trans-
gender population in England and Wales, after a
question about gender identity was asked for the
first time in the 2021 Census. The Oce for National
Statistics data will be gradually released throughout
2023, but an initial report indicates that 0.5% of
respondents felt that their gender identity did not
match their sex registered at birth; the proportion
of respondents specifically identifying as trans male
or trans female was 0.1% in both cases.50 The 0.5%
estimate is three times higher than our largest (and
most recent) estimate of proportion, namely, 0.16%
among 16- 17 year olds in 2018. This is consistent
with the literature, where survey based estimates
of transgender identity are substantially higher
than those based on medical record studies.15 Some
people with transgender and gender questioning
identities likely do not feel the need to seek medical
treatment related to gender, or do not wish for their
gender to be added to their medical record. However,
if more people, whose gender care needs are hitherto
unknown, do come forward to seek gender treatment
in future, which seems probable, then the number
of transgender people identified within primary care
will continue to increase.
We found an association between socioeconomic
deprivation, rates of newly recorded transgender
identity, and the proportion of people with trans-
gender identity. Clinic based samples of trans-
gender people receiving specialist care have long
reported disproportionately high levels of depriva-
tion,51 52 along with stigma and isolation from family
members, diculties securing employment, and
challenges in personal relationships.
Although evidence is clear that transgender people
face discrimination in many forms,13 few population
based studies have assessed the association between
transgender status and socioeconomic deprivation.53
Two recent studies, one in Denmark,54 and one in the
US,53 reported lower household incomes and lower
employment rates in transgender people compared
with a cisgender comparison group.
The direction of causality between socioeconomic
status and transgender status is challenging to deter-
mine, and we cannot confidently explain the asso-
ciation from our data. Transgender individuals in
wealthier areas may be more able to aord specialist
gender care privately, which can be accessed entirely
independently of NHS primary care. This trend may be
increasing with longer NHS waiting lists. Therefore,
individuals from a wealthier background might
bypass NHS services entirely. However, primary care
might not be entirely unaware of registered patients
who are having gender arming care in the private
sector, especially as shared care requests from the
private sector are common—enough so that regional
and national NHS bodies have produced guidance on
how to handle such requests.4 11
Transgender adults might face discrimination
and stigma leading to exclusion from education,
employment, and family support, and therefore
become more likely to move to socioeconomically
deprived areas. Potentially, these areas might also
be more accepting of transgender individuals than
others. Transgender populations have higher rates of
substance abuse and mental illness compared with
cisgender peers,55 which may be partially explained
by the minority stress model56; therefore, the burden
of these health issues might aect income, employ-
ment, and societal integration. However, this expla-
nation would not account for the association between
transgender identity and deprivation seen in young
people, whose socioeconomic status is largely
determined by their parents' wealth, and therefore
predates the development of transgender identity.
Higher parental wealth may allow young people to
access care privately, independently of their NHS GP.
Conclusions
We have presented data for the rate of first recording,
and the proportion of people with diagnostic codes
for transgender identity in UK primary care records
between 2000 and 2018. Although the absolute
proportion of people identified as transgender in
primary care records is low, in relative terms, the
number increased substantially over this period.
As such, resources must be allocated to primary
and specialist care to meet the healthcare needs of
these individuals. Socioeconomic deprivation in
both adults and children is associated with a greater
proportion of people with codes suggesting trans-
gender identity; the reasons for this association are
unclear, and should be explored in future research.
AUTHOR AFFILIATIONS
1Department of Primary Care and Population Health, University
College London, London, UK
2Division of Psychology and Language Sciences, University College
London, London, UK
3Gender Identity Development Service, Tavistock and Portman NHS
Foundation Trust, London, UK
4Patient author, London, UK
Twitter Irene Petersen @i_petersen
Contributors DGJM was responsible for the conceptualisation,
method, soware, formal analysis, investigation, data curation,
writing (original dra), visualisation, and funding acquisition.
EO’N was responsible for the method, soware, data curation,
writing (review and editing). JB wrote, reviewed, and edited the

McKechnieDGJ,
etal
.
BMJMED
2023;2:e000499. doi:10.1136/bmjmed-2023-000499 9
OPEN ACCESSOPEN ACCESS
manuscript. LH and FG wrote, reviewed, and edited the manuscript.
IP was responsible for the method, soware, formal analysis,
data curation, writing, reviewing, editing, and supervision. The
corresponding author (DGJM) attests that all listed authors meet
authorship criteria and that no others meeting the criteria have
been omitted. DGJM is the guarantor. Transparency: The lead
author (the guarantor) arms that the manuscript is an honest,
accurate, and transparent account of the study being reported;
that no important aspects of the study have been omitted; and
that any discrepancies from the study as planned (and, if relevant,
registered) have been explained.
Funding DGJM is an NIHR In- Practice Fellow (grant ID NIHR301988).
The views expressed are those of the authors and not necessarily
those of the NHS, the NIHR, or the Department of Health and Social
Care. The funders had no role in the study design, collection, analysis,
interpretation of results, writing of the report or decision to submit for
publication.
Competing interests All authors have completed the ICMJE uniform
disclosure form at www. icmje. org/ disclosure- of- interest and declare:
DGJM was nancially supported by NIHR (grant ID NIHR301988) and
EON has received funding from the Dunhill Medical Trust in the last
three years; no nancial relationships with any organisations that
might have an interest in the submitted work in the previous three
years; no other relationships or activities that could have appear to
have influenced the submitted work.
Ethics approval IQVIA Medical Research Data holds ethical approval
to collect and supply data for research purposes from the NHS
London–South East Research Ethics Committee (ref 18/LO/0441).
This study was granted approval by this database's scientic review
committee in April 2022 (ref 22SRC013).
Provenance and peer review Not commissioned; externally peer
reviewed.
Data availability statement Data may be obtained from a third
party and are not publicly available. The data used in this study are
available from IQVIA Medical Research Data. Restrictions apply to the
availability of these data, which were used under licence for this study.
Supplemental material This content has been supplied by the
author(s). It has not been vetted by BMJ Publishing Group Limited
(BMJ) and may not have been peer- reviewed. Any opinions or
recommendations discussed are solely those of the author(s) and
are not endorsed by BMJ. BMJ disclaims all liability and responsibility
arising from any reliance placed on the content. Where the content
includes any translated material, BMJ does not warrant the accuracy
and reliability of the translations (including but not limited to local
regulations, clinical guidelines, terminology, drug names and drug
dosages), and is not responsible for any error and/or omissions
arising from translation and adaptation or otherwise.
Open access This is an open access article distributed in accordance
with the Creative Commons Attribution 4.0 Unported (CC BY 4.0)
license, which permits others to copy, redistribute, remix, transform
and build upon this work for any purpose, provided the original
work is properly cited, a link to the licence is given, and indication
of whether changes were made. See:https://creativecommons.org/
licenses/by/4.0/.
ORCID iDs
Douglas Gordon JohnMcKechnie http://orcid.org/0000-0002-3477-
1503
ElizabethO'Nions http://orcid.org/0000-0003-4427-0910
JuliaBailey http://orcid.org/0000-0002-5001-0122
REFERENCES
1 American Psychological Association. Guidelines for psychological
practice with Transgender and gender Nonconforming people.
American Psychologist 2015;70:832–64. 10.1037/a0039906
2 Crowley D, Cullen W, Van Hout MC. Transgender health care in
primary care. Br J Gen Pract 2021;71:377–8. 10.3399/bjgp21X716753
3 Self- referrals. Gender Identity Clinic – GIC, Available: https://gic.nhs.
uk/referrals/self-referrals/
4 General Medical Council. Trans Healthcare. n.d. Available: https://
www.gmc-uk.org/ethical-guidance/ethical-hub/trans-healthcare
5 Kaltiala R, Bergman H, Carmichael P, etal. Time trends in referrals
to child and adolescent gender identity services: a study in four
Nordic countries and in the UK. Nord J Psychiatry 2020;74:40–4.
10.1080/08039488.2019.1667429
6 Fielding J, Bass C. Individuals seeking gender Reassignment: marked
increase in demand for services. BJPsych Bull 2018;42:206–10.
10.1192/bjb.2018.30
7 Siddique H, correspondent HSL aairs. The Guardian. NHS England
waiting times for gender dysphoria patients unlawful, court hears,
Available: https://www.theguardian.com/world/2022/nov/29/nhs-
england-waiting-times-gender-dysphoria-patients-unlawful-court-
hears-trans-claimants-nhse
8 Wright T, Nicholls EJ, Rodger AJ, etal. Accessing and Utilising gender-
arming Healthcare in England and Wales: Trans and non- binary
people’s accounts of navigating gender identity clinics. BMC Health
Serv Res 2021;21:609. 10.1186/s12913-021-06661-4
9 Carlile A, Butteriss E, Sansfaçon AP. It’s like my kid came back
overnight”: experiences of Trans and non- binary young people and
their families seeking, nding and engaging with clinical care in
England. International Journal of Transgender Health 2021:1–17.
10.1080/26895269.2020.1870188
10 Mepham N, Bouman WP, Arcelus J, etal. People with gender
Dysphoria who Self‐Prescribe Cross‐Sex hormones: prevalence,
sources, and side eects knowledge. J Sex Med 2014;11:2995–3001.
10.1111/jsm.12691
11 NECS Medicines Optimisation. Gender Dysphoria private medical
providers. NECS Medicines Optimisation; 2018. Available: https://
medicines.necsu.nhs.uk/gender-dysphoria_private-medical-
providers_nhs-england-guidance/
12 Royal College of General Practitioners. The role of the GP in caring
for gender- questioning and transgender patient: RCGP Position
Statement, . 2019Available: https://www.rcgp.org.uk/policy/rcgp-
policy-areas/transgender-care.aspx
13 Winter S, Diamond M, Green J, etal. Transgender people: health at
the margins of society. Lancet 2016;388:390–400. 10.1016/S0140-
6736(16)00683-8
14 Berner AM, Connolly DJ, Pinnell I, etal. Attitudes of Transgender
men and non- binary people to Cervical screening: a cross- sectional
mixed- methods study in the UK. Br J Gen Pract 2021;71:e614–25.
10.3399/BJGP.2020.0905
15 Zhang Q, Goodman M, Adams N, etal. Epidemiological
considerations in Transgender health: A systematic review with
focus on higher quality data. Int J Transgend Health 2020;21:125–37.
10.1080/26895269.2020.1753136
16 Joseph A, Clie C, Hillyard M, etal. Gender identity and the
management of the Transgender patient: a guide for non- specialists.
J R Soc Med 2017;110:144–52. 10.1177/0141076817696054
17 Wilson P, Sharp C, Carr S. The prevalence of gender Dysphoria in
Scotland: a primary care study. Br J Gen Pract 1999;49:991–2.
18 Adams N, Pearce R, Veale J, etal. Guidance and ethical
considerations for undertaking Transgender health. Research and
Institutional Review Boards Adjudicating This Research Transgender
Health 2017:165–75. 10.1089/trgh.2017.0012
19 Bouman WP, Schwend AS, Motmans J, etal. Language and Trans
health. International Journal of Transgenderism 2017;18:1–6.
10.1080/15532739.2016.1262127
20 Patients Registered at a GP Practice. NHS Digital. 2022. Available:
https://digital.nhs.uk/data-and-information/publications/statistical/
patients-registered-at-a-gp-practice/july-2022
21 Blak BT, Thompson M, Dattani H, etal. Generalisability of the
health improvement network (THIN) database: demographics,
chronic disease prevalence and mortality rates. Inform Prim Care
2011;19:251–5. 10.14236/jhi.v19i4.820
22 Booth N. What are the read codes Health Libr Rev 1994;11:177–82.
10.1046/j.1365-2532.1994.1130177.x
23 Townsend Petal. Health and Deprivation: Inequality and the North.
London ; New York: Croom Helm, 1988.
24 Pedersen AB, Mikkelsen EM, Cronin- Fenton D, etal. Missing data
and multiple imputation in clinical Epidemiological research. Clin
Epidemiol 2017;9:157–66. 10.2147/CLEP.S129785
25 Welsh Government. General practice workforce: as at 30 September
2021. GOV.WALES, 2022. Available: https://www.gov.wales/general-
practice-workforce-30-september-2021
26 Public Health. General Practice - GP Workforce and practice list
sizes 2011, . 2021Available: https://publichealthscotland.scot/
publications/general-practice-gp-workforce-and-practice-list-
sizes/general-practice-gp-workforce-and-practice-list-sizes-2011-
2021/
27 Health and Social Care Board. Facts and gures on General
Practitioners (GPs) and Practices, Available: https://hscboard.hscni.
net/wp-content/themes/hscb
28 NHS. General Practice Workforce: ocial statistics, Available: https://
digital.nhs.uk/data-and-information/publications/statistical/
general-and-personal-medical-services
29 Lewis JD, Bilker WB, Weinstein RB, etal. The relationship between
time since registration and measured incidence rates in the
general practice research database. Pharmacoepidem Drug Safe
2005;14:443–51. 10.1002/pds.1115 Available: http://doi.wiley.com/
10.1002/pds.v14:7

McKechnieDGJ,
etal
.
BMJMED
2023;2:e000499. doi:10.1136/bmjmed-2023-00049910
OPEN ACCESSOPEN ACCESS
30 Davé S, Petersen I. Creating medical and drug code lists to identify
cases in primary care databases. Pharmacoepidemiol Drug Saf
2009;18:704–7. 10.1002/pds.1770
31 Primary Care Support England. Adoption and gender re- assignment
processes. n.d. Available: https://pcse.england.nhs.uk/help/patient-
registrations/adoption-and-gender-re-assignment-processes/
32 Maguire A, Blak BT, Thompson M. The importance of dening
periods of complete mortality reporting for research using
automated data from primary care. Pharmacoepidemiol Drug Saf
2009;18:76–83. 10.1002/pds.1688
33 Horsfall L, Walters K, Petersen I. Identifying periods of
acceptable computer usage in primary care research databases.
Pharmacoepidemiol Drug Saf 2013;22:64–9. 10.1002/pds.3368
34 Brooks H, Llewellyn CD, Nadarzynski T, etal. Sexual orientation
disclosure in health care: a systematic review. Br J Gen Pract
2018;68:e187–96. 10.3399/bjgp18X694841
35 Reisner SL, Biello K, Rosenberger JG, etal. Using a two- step method
to measure Transgender identity in Latin America/the Caribbean,
Portugal, and Spain. Arch Sex Behav 2014;43:1503–14. 10.1007/
s10508-014-0314-2
36 Howard SD, Lee KL, Nathan AG, etal. Healthcare experiences of
Transgender people of color. J Gen Intern Med 2019;34:2068–74.
10.1007/s11606-019-05179-0
37 Kuper LE, Nussbaum R, Mustanski B. Exploring the diversity
of gender and sexual orientation identities in an online
sample of Transgender individuals. J Sex Res 2012;49:244–54.
10.1080/00224499.2011.596954
38 Turban JL, Keuroghlian AS. “Dynamic gender presentations:
understanding transition and "de- transition" among Transgender
youth”. J Am Acad Child Adolesc Psychiatry 2018;57:451–3. 10.1016/j.
jaac.2018.03.016
39 Blosnich JR, Brown GR, Shipherd, PhD JC, etal. Prevalence of gender
identity disorder and suicide risk among Transgender veterans
utilizing veterans health administration care. Am J Public Health
2013;103:e27–32. 10.2105/AJPH.2013.301507
40 Kauth MR, Shipherd JC, Lindsay J, etal. Access to care for
Transgender veterans in the veterans health administration:
2006–2013. Am J Public Health 2014;104:S532–4. 10.2105/
AJPH.2014.302086
41 Quinn VP, Nash R, Hunkeler E, etal. Cohort prole: study of
transition, outcomes and gender (STRONG) to assess health
status of Transgender people. BMJ Open 2017;7:e018121. 10.1136/
bmjopen-2017-018121
42 Dragon CN, Guerino P, Ewald E, etal. Transgender Medicare
beneciaries and chronic conditions: exploring fee- for- service
claims data. LGBT Health 2017;4:404–11. 10.1089/lgbt.2016.0208
43 Ewald ER, Guerino P, Dragon C, etal. Identifying Medicare
beneciaries Accessing Transgender- related care in the era of ICD-
10. LGBT Health 2019;6:166–73. 10.1089/lgbt.2018.0175
44 Torjesen I. Trans health needs more and better services: increasing
capacity, expertise, and integration. BMJ 2018:k3371. 10.1136/bmj.
k3371
45 GOV.UK. Tribunal Statistics Quarterly: October to December 2021.
2022. Available: https://www.gov.uk/government/statistics/tribunal-
statistics-quarterly-october-to-december-2021/tribunal-statistics-
quarterly-october-to-december-2021
46 Kronk CA, Everhart AR, Ashley F, etal. Transgender data collection in
the electronic health record: Current concepts and issues. J Am Med
Inform Assoc 2022;29:271–84. 10.1093/jamia/ocab136
47 Donald C, Ehrenfeld JM. The opportunity for medical systems to
reduce health disparities among Lesbian, gay, Bisexual, Transgender
and Intersex patients. J Med Syst 2015;39:178. 10.1007/s10916-015-
0355-7
48 Roblin D, Barzilay J, Tolsma D, etal. A novel method for estimating
Transgender status using electronic medical records. Ann Epidemiol
2016;26:198–203. 10.1016/j.annepidem.2016.01.004
49 Ford E, Oswald M, Hassan L, etal. Should free- text data in
electronic medical records be shared for research? A citizens’
jury study in the UK. J Med Ethics 2020;46:367–77. 10.1136/
medethics-2019-105472
50 Oce for National Statistics. Gender identity, England and Wales:
census 2021. 2023. Available: https://www.ons.gov.uk/peoplepo
pulationandcommunity/culturalidentity/genderidentity/bulletins/
genderidentityenglandandwales/census2021
51 Hoenig J, Kenna J, Youd A. A follow- up study of Transsexualists:
social and economic aspects. Psychiatr Clin (Basel) 1970;3:85–100.
10.1159/000278595
52 Hoenig J, Kenna JC. The prevalence of Transsexualism in England
and Wales. Br J Psychiatry 1974;124:181–90. 10.1192/bjp.124.2.181
53 Carpenter CS, Eppink ST, Gonzales G. Transgender status, gender
identity, and socioeconomic outcomes in the United States. ILR
Review 2020;73:573–99. 10.1177/0019793920902776
54 Glintborg D, Rubin KH, Kristensen SBM, etal. Socioeconomic status
in Danish Transgender persons: a nationwide register- based cohort
study. Endocr Connect 2021;10:1155–66. 10.1530/EC-21-0119
55 Reisner SL, Poteat T, Keatley J, etal. Global health burden and needs
of Transgender populations: a review. The Lancet 2016;388:412–36.
10.1016/S0140-6736(16)00684-X
56 Hendricks ML, Testa RJ. A conceptual framework for clinical work
with Transgender and gender Nonconforming clients: an adaptation
of the minority stress model. Professional Psychology: Research and
Practice 2012;43:460–7. 10.1037/a0029597
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