Important notice

The Office for Statistics Regulation confirmed on 12/09/2024 that the gender identity estimates from Census 2021 are no longer accredited official statistics and are classified as official statistics in development.

For further information please see: Sexual orientation and gender identity quality information for Census 2021

These datasets provide Census 2021 estimates that classify usual residents aged 16 years and over in England and Wales for gender identity by sex, gender identity by age and gender identity by sex and age.

Gender identity

Gender identity refers to a person's sense of their own gender, whether male, female or another category such as non-binary. This may or may not be the same as their sex registered at birth.

Non-binary

Someone who is non-binary does not identify with the binary categories of man and woman. In these results the category includes people who identified with the specific term "non-binary" or variants thereon. However, those who used other terms to describe an identity that was neither specifically man nor woman have been classed in "All other gender identities".

Sex

This is the sex recorded by the person completing the census. The options were "Female" and "Male".

Trans

An umbrella term used to refer to people whose gender identity is different from their sex registered at birth. This includes people who identify as a trans man, trans woman, non-binary or with another minority gender identity.

Trans man

A trans man is someone who was registered female at birth, but now identifies as a man.

Trans woman

A trans woman is someone who was registered male at birth, but now identifies as a woman.

Usual resident

A usual resident is anyone who on Census Day, 21 March 2021, was in the UK and had stayed or intended to stay in the UK for a period of 12 months or more, or had a permanent UK address and was outside the UK and intended to be outside the UK for less than 12 months.

Notes:

• To ensure that individuals cannot be identified in the data, population counts have been rounded to the nearest five and counts under 10 have been suppressed.

• Percentages have been calculated using rounded data.

Selected socioeconomic characteristics of the transgender or non-binary population aged 15 and older, by age group. Marital status, presence of children under age 12 in the household, education, employment, personal income, Indigenous identity, the visible minority population, immigrant status, language(s) spoken most often at home, place of residence (population centre/rural), self-rated general health, and self-rated mental health. Estimates are obtained from combined cycles of the Canadian Community Health Survey, 2019 to 2021.

This data set contains EIIHA populations who received services funded by Ryan White Part A Grant. EIIHA is Early Identification of Individuals with HIV/AIDS (EIIHA) The special populations (EIIHA) with HIV are: Black MSM = Black men and Black transgender women who have sex with men. Latinx MSM = Latinx men and Latinx Transgender women who have sex with men. Black Women - Black women Transgender - Transgender men and women. These populations have the biggest disparities of people living with HIV. Other data is the number of clients and units used in each service category in the Ryan White Part A, a grant that provides services for those with HIV.

Important notice

The Office for Statistics Regulation confirmed on 12/09/2024 that the gender identity estimates from Census 2021 are no longer accredited official statistics and are classified as official statistics in development.

For further information please see: Sexual orientation and gender identity quality information for Census 2021

These datasets provide Census 2021 estimates that classify usual residents aged 16 years and over in England and Wales for gender identity by sex, gender identity by age and gender identity by sex and age.

Gender identity

Gender identity refers to a person's sense of their own gender, whether male, female or another category such as non-binary. This may or may not be the same as their sex registered at birth.

Non-binary

Someone who is non-binary does not identify with the binary categories of man and woman. In these results the category includes people who identified with the specific term "non-binary" or variants thereon. However, those who used other terms to describe an identity that was neither specifically man nor woman have been classed in "All other gender identities".

Sex

This is the sex recorded by the person completing the census. The options were "Female" and "Male".

Trans

An umbrella term used to refer to people whose gender identity is different from their sex registered at birth. This includes people who identify as a trans man, trans woman, non-binary or with another minority gender identity.

Trans man

A trans man is someone who was registered female at birth, but now identifies as a man.

Trans woman

A trans woman is someone who was registered male at birth, but now identifies as a woman.

Usual resident

A usual resident is anyone who on Census Day, 21 March 2021, was in the UK and had stayed or intended to stay in the UK for a period of 12 months or more, or had a permanent UK address and was outside the UK and intended to be outside the UK for less than 12 months.

Notes:

• To ensure that individuals cannot be identified in the data, population counts have been rounded to the nearest five and counts under 10 have been suppressed.

• Percentages have been calculated using rounded data.

The TransPop study is the first national probability sample of transgender individuals in the United States (it also includes a comparative cisgender sample). A primary goal of this study was to provide researchers with a representative sample of transgender people in the United States. The study examines a variety of health-relevant domains including health outcomes and health behaviors, experiences with interpersonal and institutional discrimination, identity, transition-related experiences, and basic demographic characteristics (age, race/ethnicity, religion, political party affiliation, marital status, employment, income, location, sex, gender, and education). Co-investigators (in alphabetical order): Walter O. Bockting, Ph.D. (Columbia University); Jody L. Herman, Ph.D. (UCLA); Sari L. Reisner, Ph.D. (Harvard University and The Fenway Institute, Fenway Health).

This dataset provides Census 2022 estimates for Trans Status or History (7 Groups) in Scotland.

Scotland’s Census included a new question on trans status or history in 2022. This means there is not comparable data for previous censuses.

The question was “Do you consider yourself to be trans, or have a trans history?”. People were asked to tick “No” or “Yes”. People who ticked “Yes” were asked to describe their trans status (for example, non-binary, trans man, trans woman).

Transgender or trans is a term used to describe people whose gender is not the same as the sex they were assigned at birth.

This was a voluntary question for people aged 16 and over.

The quality assurance report can be found here

Background: The COVID-19 lockdown in Bangladesh has left hijra individuals at an increased risk of poverty and food insecurity due to the economic crisis. The lack of healthcare facilities and lack of awareness raises the looming fear of the budding influence of COVID-19 among the hijra population. COVID-19 challenges the fundamental foundation of the public health system, and now the hijra group is out of the system because of stigma and discrimination.Methods: This article features three Focus Group Discussions (FGDs) conducted by 23 respondents about their experience during the COVID-19 Pandemic.Objectives: The following research aimed to understand the health, mental stress, social and economic effects on the lives of deprived and marginalized hijra people in Bangladesh of the COVID-19 lockdown. However, in the aftermath of the pandemic, their disadvantaged and socially excluded status makes hijra population more vulnerable to being affected by the virus and facing the economic and social impacts.Results: The results reflect the effect of COVID-19 in terms of social, health care and mental health problems on the hijra community in Bangladesh.Conclusion: The conclusion also presents valuable recommendations for policy practitioners during the COVID-19 situation to support the hijra community. Hijra people are assumed to suffer under the severity of the pandemic even more than the general population due to the intersections between their status as a vulnerable social group, and their high amount of medical risk factors. The COVID-19 pandemic can potentiate these vulnerabilities, add new challenges for hijra individuals, leading to devastating consequences, like severe physical, and mental health issues.

A worldwide project started in April 2009 called the Transgender Murder Monitoring Project (TMM) reported that 180 killings occurred between November 2009 and November 2010. Since January 2008, a total of 487 transgender people have been reported murdered. The TMM 2010 report broke down the murders in 19 countries. The majority happened in Brazil (91), Guatemala (15), Mexico (14), and the USA (14). (Source: Transgender Murder Monitoring Project. Regionally, the Belizean transgendered community has been continuously overlooked; they are invisible in the National Strategic Plan of 2006-2011. Funding received by the country for HIV/AIDS and outreach programs rarely reaches the transgender community because the system does not see the population as sufficiently large enough to make investments.The purpose of the research is to create a profile of transgender needs in the Belizean context; this report will feed into a larger effort for a region-wide advocacy plan that will be implemented by CRTA. The significance of the effort may lead to future planning around resource mobilization, capacity building and advocacy.

This dataset contains surveillance study estimates for population size, HIV prevalence, and ART coverage among female sex workers (FSW), men who have sex with men (MSM), people who inject drugs (PWID), and transgender men and women (TGM/W) from 2010-2023. It was created to support the UNAIDS Estimates Key Population Workbook for use by HIV estimates teams in sub-Saharan Africa. Key population surveillance reports, including Ministry of Health-led biobehavioural surveys, mapping studies, and academic studies were used to populate the database.

The dataset was populated using existing key population size estimate databases including:

UNAIDS Key Population Atlas

US Centers for Disease Control and Prevention surveillance database

Global Fund against HIV/AIDS, TB, and Malaria surveillance database

Global.HIV database

Systematic review databases among MSM (Stannah et al, 2019 and Stannah et al., 2023) and PWID (Degenhardt et al., 2023)

and was additionally supplemented by a literature review of peer-reviewed and grey literature sources.

The data can be explored in this web application and the accompanying manuscript can be found here

The Excel book contains the original data, refined data, statistical analyses, and the tables including those for publication.

This data set includes tables on persons living with HIV/AIDS, newly diagnosed HIV cases and all cause deaths in HIV/AIDS cases by gender, age, race/ethnicity and transmission category.

In all tables, cases are reported as of December 31 of the given year, as reported by December 31, 2024, to allow a minimum of 12 months reporting delay.

Gender is determined by both current gender and sex at birth variables; transgender values are assigned when current gender is identified as "Transgender" or when a discrepancy is identified between a person's sex at birth and their current gender (e.g., cases where sex at birth is "Male" and current gender is "Female" will become Transgender: Male to Female.) Prior to 2003, Asian and Native Hawaiian/Pacific Islanders were classified as one combined group. In order to present these race/ethnicities separately, living cases recorded under this combined classification were split and redistributed according to their expected proportional population representation estimated from post-2003 data.

Dataset contains counts and measures for individuals from the 2013, 2018, and 2023 Censuses. Data is available by statistical area 2.

​

The variables included in this dataset are for the census usually resident population count (unless otherwise stated). All data is for level 1 of the classification (unless otherwise stated).

​

The variables for part 1 of the dataset are:

• Census usually resident population count
• Census night population count
• Age (5-year groups)
• Age (life cycle groups)
• Median age
• Birthplace (NZ born/overseas born)
• Birthplace (broad geographic areas)
• Ethnicity (total responses) for level 1 and ‘Other Ethnicity’ grouped by ‘New Zealander’ and ‘Other Ethnicity nec’
• Māori descent indicator
• Languages spoken (total responses)
• Official language indicator
• Gender
• Cisgender and transgender status – census usually resident population count aged 15 years and over
• Sex at birth
• Rainbow/LGBTIQ+ indicator for the census usually resident population count aged 15 years and over
• Sexual identity for the census usually resident population count aged 15 years and over
• Legally registered relationship status for the census usually resident population count aged 15 years and over
• Partnership status in current relationship for the census usually resident population count aged 15 years and over
• Number of children born for the sex at birth female census usually resident population count aged 15 years and over
• Average number of children born for the sex at birth female census usually resident population count aged 15 years and over
• Religious affiliation (total responses)
• Cigarette smoking behaviour for the census usually resident population count aged 15 years and over
• Disability indicator for the census usually resident population count aged 5 years and over
• Difficulty communicating for the census usually resident population count aged 5 years and over
• Difficulty hearing for the census usually resident population count aged 5 years and over
• Difficulty remembering or concentrating for the census usually resident population count aged 5 years and over
• Difficulty seeing for the census usually resident population count aged 5 years and over
• Difficulty walking for the census usually resident population count aged 5 years and over
• Difficulty washing for the census usually resident population count aged 5 years and over.

​

Download lookup file for part 1 from Stats NZ ArcGIS Online or embedded attachment in Stats NZ geographic data service. Download data table (excluding the geometry column for CSV files) using the instructions in the Koordinates help guide.

​

Footnotes

Te Whata

Under the Mana Ōrite Relationship Agreement, Te Kāhui Raraunga (TKR) will be publishing Māori descent and iwi affiliation data from the 2023 Census in partnership with Stats NZ. This will be available on Te Whata, a TKR platform.

​

Geographical boundaries

Statistical standard for geographic areas 2023 (updated December 2023) has information about geographic boundaries as of 1 January 2023. Address data from 2013 and 2018 Censuses was updated to be consistent with the 2023 areas. Due to the changes in area boundaries and coding methodologies, 2013 and 2018 counts published in 2023 may be slightly different to those published in 2013 or 2018.

​

Subnational census usually resident population

The census usually resident population count of an area (subnational count) is a count of all people who usually live in that area and were present in New Zealand on census night. It excludes visitors from overseas, visitors from elsewhere in New Zealand, and residents temporarily overseas on census night. For example, a person who usually lives in Christchurch city and is visiting Wellington city on census night will be included in the census usually resident population count of Christchurch city.

​

Population counts

Stats NZ publishes a number of different population counts, each using a different definition and methodology. Population statistics – user guide has more information about different counts.

​

Caution using time series

Time series data should be interpreted with care due to changes in census methodology and differences in response rates between censuses. The 2023 and 2018 Censuses used a combined census methodology (using census responses and administrative data), while the 2013 Census used a full-field enumeration methodology (with no use of administrative data).

​

Study participation time series

In the 2013 Census study participation was only collected for the census usually resident population count aged 15 years and over.

​

About the 2023 Census dataset

For information on the 2023 dataset see Using a combined census model for the 2023 Census. We combined data from the census forms with administrative data to create the 2023 Census dataset, which meets Stats NZ's quality criteria for population structure information. We added real data about real people to the dataset where we were confident the people who hadn’t completed a census form (which is known as admin enumeration) will be counted. We also used data from the 2018 and 2013 Censuses, administrative data sources, and statistical imputation methods to fill in some missing characteristics of people and dwellings.

​

Data quality

The quality of data in the 2023 Census is assessed using the quality rating scale and the quality assurance framework to determine whether data is fit for purpose and suitable for release. Data quality assurance in the 2023 Census has more information.

​

Concept descriptions and quality ratings

Data quality ratings for 2023 Census variables has additional details about variables found within totals by topic, for example, definitions and data quality.

​

Disability indicator

This data should not be used as an official measure of disability prevalence. Disability prevalence estimates are only available from the 2023 Household Disability Survey. Household Disability Survey 2023: Final content has more information about the survey.

Activity limitations are measured using the Washington Group Short Set (WGSS). The WGSS asks about six basic activities that a person might have difficulty with: seeing, hearing, walking or climbing stairs, remembering or concentrating, washing all over or dressing, and communicating. A person was classified as disabled in the 2023 Census if there was at least one of these activities that they had a lot of difficulty with or could not do at all.

​

Using data for good

Stats NZ expects that, when working with census data, it is done so with a positive purpose, as outlined in the Māori Data Governance Model (Data Iwi Leaders Group, 2023). This model states that "data should support transformative outcomes and should uplift and strengthen our relationships with each other and with our environments. The avoidance of harm is the minimum expectation for data use. Māori data should also contribute to iwi and hapū tino rangatiratanga”.

​

Confidentiality

The 2023 Census confidentiality rules have been applied to 2013, 2018, and 2023 data. These rules protect the confidentiality of individuals, families, households, dwellings, and undertakings in 2023 Census data. Counts are calculated using fixed random rounding to base 3 (FRR3) and suppression of ‘sensitive’ counts less than six, where tables report multiple geographic variables and/or small populations. Individual figures may not always sum to stated totals. Applying confidentiality rules to 2023 Census data and summary of changes since 2018 and 2013 Censuses has more information about 2023 Census confidentiality rules.

​

Measures

Measures like averages, medians, and other quantiles are calculated from unrounded counts, with input noise added to or subtracted from each contributing value during measures calculations. Averages and medians based on less than six units (e.g. individuals, dwellings, households, families, or extended families) are suppressed. This suppression threshold changes for other quantiles. Where the cells have been suppressed, a placeholder value has been used.

​

Percentages

To calculate percentages, divide the figure for the category of interest by the figure for 'Total stated' where this applies.

​

Symbol

-997 Not available

-999 Confidential

​

Inconsistencies in definitions

Please note that there may be differences in definitions between census classifications and those used for other data collections.

IntroductionGender incongruence (GI) is characterized by a marked incongruence between an individual’s experienced/expressed gender and the assigned sex at birth. It includes strong displeasure about his or her sexual anatomy and secondary sex characteristics. In some people, this condition produces a strong distress with anxiety and depression named gender dysphoria (GD). This condition appears to be associated with genetic, epigenetics, hormonal as well as social factors. Given that L-glutamate is the major excitatory neurotransmitter in the central nervous system, also associated with male sexual behavior as well as depression, we aimed to determine whether metabotropic glutamate receptors are involved in GD.MethodsWe analyzed 74 single nucleotide polymorphisms located at the metabotropic glutamate receptors (mGluR1, mGluR3, mGluR4, mGluR5, mGluR7 and mGluR8) in 94 transgender versus 94 cisgender people. The allele and genotype frequencies were analyzed by c2 test contrasting male and female cisgender and transgender populations. The strength of the associations was measured by binary logistic regression, estimating the odds ratio (OR) for each genotype. Measurement of linkage disequilibrium, and subsequent measurement of haplotype frequencies were also performed considering three levels of significance: P ≤ 0.05, P ≤ 0.005 and P ≤ 0.0005. Furthermore, false positives were controlled with the Bonferroni correction (P ≤ 0.05/74 = 0.00067).ResultsAfter analysis of allele and genotypic frequencies, we found twenty-five polymorphisms with significant differences at level P ≤ 0.05, five at P ≤ 0.005 and two at P ≤ 0.0005. Furthermore, the only two polymorphisms (rs9838094 and rs1818033) that passed the Bonferroni correction were both related to the metabotropic glutamate receptor 7 (mGluR7) and showed significant differences for multiple patterns of inheritance. Moreover, the haplotype T/G [OR=0.34 (0.19–0.62); P

Police-reported hate crime, by type of motivation (race or ethnicity, religion, sexual orientation, language, disability, sex, age), selected regions and Canada (selected police services), 2014 to 2024.

The Population and Dwellings data from the 2021 Federal Census covers population in private households by age and gender. For questions, please contact socialresearch@calgary.ca. Please visit Data about Calgary's population for more information.

Population in private households refers to all persons or group of persons who occupy the same dwelling and do not have a usual place of residence elsewhere in Canada or abroad. For census purposes, households are classified into three groups: private households, collective households, and households outside Canada. Unless otherwise specified, all data in census products are for private households only. Population in private households includes Canadian citizens and landed immigrants whose usual place of residence is Canada. Also includes refugee claimants, holders of work and study permits, Canadian citizens and landed immigrants at sea or in port aboard merchant or government vessels, and Canadian citizens away from Canada on military or diplomatic business. Excludes government representatives and military members of other countries and residents of other countries visiting Canada.

Age refers to the age of a person (or subject) of interest at last birthday (or relative to a specified, well‑defined reference date).

Gender refers to an individual's personal and social identity as a man, woman, or non‑binary person (a person who is not exclusively a man or a woman). A person's gender may differ from their sex at birth, and from what is indicated on their current identification or legal documents such as their birth certificate, passport, or driver's licence. A person's gender may change over time. Statistics Canada collected data about transgender and non-binary populations for the first time on the 2021 Census. The category "Men+" includes men (and/or boys), as well as some non-binary persons. The category "Women+" also includes women (and/or girls), as well as some non-binary persons.

This is a one-time load of Statistics Canada federal census data from 2021 applied to the Communities, Wards, and City geographical boundaries current as of 2022 (so they will likely not match the current year's boundaries). Update frequency is every 5 years. Data Steward: Business Unit Community Strategies (Demographics and Evaluation). This dataset is for general public and internal City business groups.

Although South Africa is the global epicenter of the HIV epidemic, the uptake of HIV testing and treatment among young people remains low. Concerns about confidentiality impede the utilization of HIV prevention services, which signals the need for discrete HIV prevention measures that leverage youth-friendly platforms. This paper describes the process of developing a youth-friendly internet-enabled HIV risk calculator in collaboration with young people, including young key populations aged between 18 and 24 years old. Using qualitative research, we conducted an exploratory study with 40 young people including young key population (lesbian, gay, bisexual, transgender (LGBT) individuals, men who have sex with men (MSM), and female sex workers). Eligible participants were young people aged between 18–24 years old and living in Soweto. Data was collected through two peer group discussions with young people aged 18–24 years, a once-off group discussion with the [Name of clinic removed for confidentiality] adolescent community advisory board members and once off face-to-face in-depth interviews with young key population groups: LGBT individuals, MSM, and female sex workers. LGBT individuals are identified as key populations because they face increased vulnerability to HIV/AIDS and other health risks due to societal stigma, discrimination, and obstacles in accessing healthcare and support services. The measures used to collect data included a socio-demographic questionnaire, a questionnaire on mobile phone usage, an HIV and STI risk assessment questionnaire, and a semi-structured interview guide. Framework analysis was used to analyse qualitative data through a qualitative data analysis software called NVivo. Descriptive statistics were summarized using SPSS for participant socio-demographics and mobile phone usage. Of the 40 enrolled participants, 58% were male, the median age was 20 (interquartile range 19–22.75), and 86% had access to the internet. Participants’ recommendations were considered in developing the HIV risk calculator. They indicated a preference for an easy-to-use, interactive, real-time assessment offering discrete and private means to self-assess HIV risk. In addition to providing feedback on the language and wording of the risk assessment tool, participants recommended creating a colorful, interactive and informational app. A collaborative and user-driven process is crucial for designing and developing HIV prevention tools for targeted groups. Participants emphasized that privacy, confidentiality, and ease of use contribute to the acceptability and willingness to use internet-enabled HIV prevention methods.

Number of Times a Reason was Ticked (and Percentage of Participants that Selected the Reason) in the Dutch (NL) and United Kingdom (UK) Survey in Response to the Question:: “Have You Ever Been Discriminated Against for any of the Following Reasons:”.

BackgroundTransgender women (TGW) experience unique life traumas that may perpetuate negative sexual health outcomes, such as high rates of HIV and sexually transmitted infections. This is especially true in the US Deep South, where structural and cultural factors further marginalize gender minorities as well as people of color. Providing trauma informed care to TGW in sexual and reproductive health (SRH) settings is necessary, but strategies to measure traumatic experiences among this population are needed. We aimed to develop and psychometrically assess a multi-item survey instrument evaluating trauma-specific histories for use with TGW in SRH settings and assess differences in reported trauma histories between White and non-White TGW in the US Deep South.MethodsSurvey items were developed using three existing general trauma instruments (Life Events Checklist for DSM-5, Trauma History Questionnaire, Stressful Life Events Screening Questionnaire) and results from qualitative interviews with TGW. Survey items fell into five trauma subdomains: healthcare-related experiences, sexual/relationship experiences, crime-related/general trauma experiences, gender dysphoria experiences, and discrimination experiences. A computer-assisted self-interviewing instrument was administered to TGW. Descriptive statistics were calculated. Cronbach’s alpha coefficients (α) were calculated for each subdomain to determine internal consistency. Results were stratified by race (White versus non-White), and means of trauma subdomain results were compared.ResultsBetween April 2024–September 2024, 105 TGW enrolled and completed the instrument. Median participant age was 30 years (range 19–73), and most identified as White (n = 55) or Black/African American (n = 40). Mental health conditions such as depression (n = 64) and anxiety (n = 59) were common. Psychometric analyses revealed acceptable internal constancy for the subdomains of healthcare-related experiences (α = 0.787), crime-related/general trauma experiences (α = 0.870), and discrimination experiences (α = 0.870). Subdomains measuring sexual/relationship experiences and gender dysphoria had lower reliability (α = 0.597 and 0.499, respectively). Trauma in all subdomains was common among all participants, with traumatic sexual and relationship experiences (p = 0.004) and crime-related and general trauma experiences (p 

ImportanceTransgender and gender-diverse (TGD) individuals are at risk for discrimination and inequities across legal, social, and medical contexts. Population-level resources have rarely been used for TGD health research and, therefore, data is lacking about prevalences of a wide range of clinical conditions among TGD populations.ObjectiveTo leverage the Utah Population Database’s demographic, vital, and health records and examine population-level diagnostic prevalences in TGD individuals and an age-matched general cohort.Participants6,664 TGD individuals were identified using ICD codes for gender incongruence between 1995 and 2021; 64,124 age-matched individuals comprised the control cohort.DesignUsing Phecodes to collapse ICD codes, this study examined differences in the prevalence of medical, mental health, and neurodevelopmental clinical phenotypes in TGD and control cohorts using modified Poisson regression models.SettingAffiliated healthcare systems within the state of Utah.Main outcome and measureWe evaluated adjusted prevalence ratios of identified Phecodes.ResultsThe TGD cohort showed broadly higher documented prevalences of medical, mental health, and neurodevelopmental conditions compared to controls. Medical diagnoses more common in the TGD cohort included sleep disorders and chronic pain. Disparities in diagnoses such as “other endocrine disorders” and “need for hormone replacement therapy” likely reflect gender-affirming treatments. Mental health conditions including mood, depression, anxiety, and personality disorders were significantly more prevalent in the TGD cohort.Conclusions and RelevanceThis study highlights diagnostic disparities for TGD individuals across multiple clinical categories. Our findings may be driven by: 1) discrimination and over-medicalization of TGD individuals, 2) differences in accessing and interacting with the healthcare system, and 3) variation in the true incidence of medical and mental health outcomes in the TGD vs control cohorts.

Bivariable associations between negative indications of HIV testing engagement and socio-demographics, HIV knowledge, HIV stigma, social support, social cohesion, social acceptance, social participation, anti-trans stigma, and healthcare stigma among HIV-negative trans women, Tesoro Lingi, and people with other genders in Nepal (n = 173), 2019–2020.