Guidance note on the collection and use of data for LGBTIQ equality.
Date: 2024-01-23
Institutions: Directorate-General for Justice and Consumers
Subjects: EU strategy, action programme, application of the law, discrimination on the basis of sexual orientation, equal treatment, fundamental rights, gender mainstreaming

 
 
 
 
 
 
 
EUROPEAN COMMISSION 

Directorate-General for Justice and Consumers 
Directorate D –Equality and Non-Discrimination  
Unit D1 - Non-discrimination: LGBTIQ, Age, Horizontal Matters  
European Commission 
B-1049 Brussels 

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Guidance note 
on the collection and use of 
data for LGBTIQ equality  

This document has been produced by the Subgroup on Equality Data of the High-Level 
Group on Non-Discrimination, Equality and Diversity. 

The Subgroup on Equality Data is composed of representatives from EU Member States 
and Norway, the European Commission, Eurostat, Eurofound, EIGE and FRA. Member 
States representatives are experts from governmental departments dealing with non-
discrimination policies, national statistical institutes and equality bodies. It provides a 
forum  for  relevant  national  authorities  and  EU  institutions, to discuss  challenges  and 
opportunities in improving the collection and use of equality data. 

The Subgroup on Equality Data would like to express their gratitude to the EU Agency 
for Fundamental Rights (FRA) and two external experts, Joz Motmans and Aisa Burgwal, 
for  their  extensive  input  in  the  development  of  this  guidance  note,  drawing  on  their 
wide-ranging knowledge and expertise. 

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Manuscript completed in March 2023  

PDF 

ISBN 978-92-68-05054-5 

doi:10.2838/398439  DS-03-23-327-EN-N  

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© European Union, 2023 

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Table of contents 

Table of contents 

5 

7 
1.  Background to – and purpose of – this Guidance 
1.1.  Need for data for informed policy choices ....................................................... 8 
1.2.  What are ‘equality data’? ................................................................................ 9 
1.3.  Purpose and structure of this guidance note.................................................. 12 

2.  Challenges, data protection, and other ethical considerations in 
collecting and using equality data on SOGIESC 
16 
2.1.  Challenges in collecting and using SOGIESC data ............................................ 16 
2.2.  Data-protection rules do not prevent the collection of equality data on 
SOGIESC ................................................................................................................. 21 
2.3.  Ethical considerations in relation to data on SOGIESC .................................... 23 

3.  General principles for collecting equality data on SOGIESC 
3.1.  Carry out needs assessments of users and potential users of data 
disaggregated by SOGIESC ...................................................................................... 27 

27 

3.1.1.  Rationale ........................................................................................................................ 27 

3.1.2.  Guidance ........................................................................................................................ 27 
Identify existing data sources that provide information on SOGIESC .............. 28 
3.2. 

3.2.1.  Rationale ........................................................................................................................ 28 

3.2.2.  Guidance ........................................................................................................................ 29 
3.3.  Align definitions and categorisations related to SOGIESC ............................... 31 

3.3.1.  Rationale ........................................................................................................................ 31 

3.3.2.  Guidance ........................................................................................................................ 31 
3.4.  Mainstream information on SOGIESC in all national and EU surveys .............. 33 

3.4.1.  Rationale ........................................................................................................................ 34 

3.4.2.  Guidance ........................................................................................................................ 41 
3.5.  Mainstream an intersectional approach in the collection and use of 
SOGIESC data ......................................................................................................... 43 

3.5.1.  Rationale ........................................................................................................................ 45 

3.5.2.  Guidance ........................................................................................................................ 45 
3.6.  Provide sufficient budget for regular surveys to collect equality data 
on SOGIESC ............................................................................................................ 46 

3.6.1.  Rationale ........................................................................................................................ 46 

3.6.2.  Guidance ........................................................................................................................ 47 
3.7.  Facilitate the effective use of SOGIESC equality data to strengthen and 
improve LGBTIQ equality ........................................................................................ 48 

3.7.1.  Rationale ........................................................................................................................ 48 

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3.7.2.  Guidance ........................................................................................................................ 49 

4.  How to collect information on SOGIESC 
52 
4.1.  How to collect data on sexual orientation ..................................................... 53 

4.1.1.  Rationale ........................................................................................................................ 53 

4.1.2.  Guidance ........................................................................................................................ 56 

4.1.3.  Examples for measuring sexual orientation ................................................................... 57 
4.2.  How to collect data on sex and gender (identity) ........................................... 60 

4.2.1.  Rationale ........................................................................................................................ 60 

4.2.2.  Guidance ........................................................................................................................ 64 

4.2.3.  Examples on how to collect data on sex, gender, and gender identity ......................... 66 
4.3.  How to collect data on gender expression ..................................................... 71 

4.3.1.  Rationale ........................................................................................................................ 71 

4.3.2.  Guidance ........................................................................................................................ 72 

4.3.3.  Examples of measuring gender expression .................................................................... 73 
4.4.  How to collect data on sex characteristics ..................................................... 76 

4.4.1.  Rationale ........................................................................................................................ 76 

4.4.2.  Guidance ........................................................................................................................ 77 

4.4.3.  Examples of intersex measures ...................................................................................... 78 

Annex: Glossary 

82 

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1. 

Background to – and purpose of 
– this Guidance 

Equality and non-discrimination are founding values of the European Union (EU). These 
values are enshrined in the EU’s Treaties1 and in the Charter of Fundamental Rights of 
the  European  Union2.  They  are  also  an  integral  part  of  the  European  Pillar  of  Social 
Rights3.  

In recent decades, legislative developments and policy initiatives on the national and EU 
level  have  helped  build  more  inclusive  societies,  including  for  lesbian,  gay,  bisexual, 
asexual,  trans,  intersex  and  queer  (LGBTIQ)  people4.  Notably,  in  November  2020  the 
European Commission published its first ever LGBTIQ equality strategy 2020-20255. The 
strategy  delivers  on  the  European  Commission’s  commitment  to  building  a  union  of 
equality and marks a new era in efforts at the European level to promote equality for 
LGBTIQ people.  

Nevertheless, a recent survey by the European Union Agency for Fundamental Rights 
(FRA) on LGBTI people in the EU gives cause for concern. The survey was the largest of 
its kind providing information on the lived realities of LGBTI people in the EU. It points 
to  persistent  and  concerning  rates  of  discrimination,  bias-motivated  violence,  and 
harassment  against  LGBTIQ  people.  There  is  an  urgent  need  to  collect  robust  and 
comparable  data  so  we  can  measure  progress  in  promoting  equality  and  non-
discrimination. However, information about the lived realities of LGBTIQ people across 
the  EU  is  incomplete  and  fragmented.  Where  data  are  available,  they  are  often  not 
sufficiently comparable or of low quality.  

Acknowledging the need for more and better information related to sexual orientation, 
gender  identity,  gender  expression,  and  sex  characteristics  (SOGIESC),  the  European 

1 Article 10 TFEU and Article 2 TEU. 
2 Article 21. 
3 Principle 3. 
4 LGBTIQ people are people: (i) who are attracted to others of their own gender (lesbian, gay) or multiple 
genders (bisexual, pansexual), or who experience little or no sexual and/or emotional attraction (asexual, 
aromantic);  (ii)  whose  gender  identity  and/or  expression  does  not  correspond  to  the  sex  they  were 
assigned at birth (trans, non-binary); (iii) who are born with sex characteristics that do not fit the typical 
definition of male or female (intersex); and (iv) whose identity does not fit into a binary classification of 
sexuality and/or gender (queer). See European Commission (2020), LGBTIQ equality strategy 2020-2025, 
COM(2020) 698 final, Brussels, 12 November 2020, p. 3. 
5 The strategy builds on the list of actions to advance LGBTI equality for 2015-2019, which was the first 
policy framework specifically combating discrimination against LGBTI people. See: European Commission 
(2020),  Final  report  2015-2019  on  the  list  of  actions  to  advance  LGBTI  equality,  Publications  Office, 
Luxembourg of the European Union (Publications Office). 

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Commission  in  2020  invited  the  FRA  and  the  European  Institute  for  Gender  Equality 
(EIGE)  ‘[…]  to  continue  providing  Member  States  with  technical  assistance  and 
methodological support on the design and implementation of data-collection exercises 
on LGBTIQ people both on single and multiple grounds6’.  

1.1. 

Need for data for informed policy 
choices 

‘Reliable  and  comparable  equality  data  will  be  crucial  for  assessing  the  situation  of 
LGBTIQ people and effectively tackling inequalities’. 

 EU LGBTIQ Equality Strategy (2020-2025) 

A key purpose of any data-collection process is to gather information that can help to: 
(i) drive change; (ii) design evidence-based, targeted policies and programmes; and (iii) 
ensure  budgets  that  meet  the  needs  of  different  groups  of  people.  Data  reflect  the 
identities, experiences and needs of people and communities that have the right to be 
heard and respected. Everyone should be able to see themselves and their identities 
represented in surveys and other data-collection instruments7. However, the diversity 
of LGBTIQ people has traditionally not been visible in national surveys or administrative 
data sources8.  

This  general  lack  of  –  or  incomplete  –  statistical  evidence  about  LGBTIQ  peoples’ 
identities and experiences makes it difficult to assess the true magnitude/prevalence of 
discrimination, structural inequalities, bias-motivated crime, and harassment suffered 
by LGBTIQ people. A lack of equality data also makes it difficult to monitor and evaluate 
the  effectiveness  of  legislation  and  policies  in  tackling  LGBTIQ  inequality  and 
discrimination. Many surveys and research exercises used to inform policy do not ask: 
(i) questions about SOGIESC; or (ii) questions on experiences of discrimination based on 
SOGIESC.  This  can  make  LGBTIQ  people  invisible  within  national  and  international 
datasets and for monitoring efforts in relation to equal treatment. 

To make informed policy choices to counter discrimination and foster equal treatment, 
legislators  and  policymakers  need  data  on  people’s  social  positioning  and  on  their 

6 European Commission (2020), LGBTIQ equality strategy 2020–2025, COM(2020) 698 final, Brussels, 12 
November 2020, p. 24.  
7 National Academies of Sciences, Engineering, and Medicine (2022), Measuring Sex, Gender Identity, and 
Sexual Orientation, Washington, DC: The National Academies Press, p. 6.  
8  ‘Administrative  data’  refers  to  the  data  contained  in  such  records  that  are  collected  and  kept  by  a 
government agency.  

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experiences  of  discrimination  based  on  SOGIESC.  Thus  far,  there  has  been  little 
systematic and recurrent data collection  on LGBTIQ people across the EU, and where 
SOGIESC data exist, they vary greatly in scope and quality. Only a few Member States 
collect data on SOGIESC, while others deliberately refrain from doing so, as evidenced 
by  the  2017  Commission  report  on  data  collection  in  relation  to  LGBTIQ  people. 
Information  suggests  that,  although  the  availability  of  data  on  sexual  orientation  is 
generally  low,  it  is  still  considerably  greater  than  the  availability  of  data  on  gender 
identity, gender expression, or sex characteristics. As the EU LGBTIQ equality strategy 
emphasises, this shows that there is a need to improve the collection and use of data on 
LGBTIQ equality9. 

Box A 1 – Subgroup on Equality Data 

In 2018, the EU High Level Group on Non-Discrimination, Equality and Diversity set up 
a Subgroup on Equality Data (the Subgroup) to support Member States in their efforts 
to improve the collection and use of equality data. It tasked the FRA with facilitating 
the work of the Subgroup, in line with the Agency’s mandate to develop methods and 
standards to improve the comparability, objectivity and reliability of equality data at 
the European level10.  

To date, the Subgroup has developed: 

•  a set of non-binding guidelines on collecting and using equality data;  

•  a compendium of promising practices for the collection of equality data 

implemented at national level; 

•  a diagnostic mapping tool to help Member States identify existing sources of 

equality data and identify gaps in their data;  

•  practical guidance to Member States on improving the collection of data on 

racial or ethnic origin. 

1.2.  What are ‘equality data’? 

The European handbook on equality data and the Guidelines on improving the collection 
and use of equality data define ‘equality data’ as any piece of information that is useful 
for the purposes of describing, analysing, reasoning about, and making decisions on the 

9 European Commission (2020), LGBTIQ equality strategy 2020-2025, COM(2020) 698 final, Brussels, 12 

November 2020, p. 22. 

10 Council Regulation (EC) No 168/2007 of 15 February 2007 establishing a European Union Agency for 
Fundamental Rights, OJ L 53, 22.2.2007. 

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state of equality. This information may be quantitative or qualitative in nature. It can 
include aggregate data that reflect inequalities and their causes or effects in societies11. 

Equality  statistics  can  be  compiled  from  multiple  data  sources,  such  as  population 
censuses;  administrative  registers;  household  and  individual  surveys;  victimisation 
surveys;  and  attitudinal surveys.  Other  sources  include:  (i)  complaints data  (including 
aggregate  profiles  of  complainants  and  offenders);  (ii)  criminal  justice  data  (including 
court  statistics  and  data  on  the  outcomes  of  court  cases,  and  compensation 
offered/sanctions  applied);  and  (iii)  other  avenues  of  data  collection  (such  as 
discrimination testing and diversity monitoring by employers, civil-society organisations, 
and service providers).  

Data  disaggregated  by  certain  personal  characteristics  (including  age,  sex,  racial  or 
ethnic origin, religion or belief, disability, sexual orientation, gender identity, or being 
intersex/having a variation of sex characteristics) can be used to produce equality data, 
at  an  aggregated  level  for  statistical  purposes,  if  this  is  done  voluntarily  and  in  full 
compliance with legal provisions on data protection (see Section No 2.2 of this guidance 
document) 

Box A 2 – Artificial intelligence 

An important and relatively recent development concerns the use of data for creating 
algorithms  to  support  decision-making  and  artificial  intelligence  systems.  Such 
algorithms and artificial intelligence  systems are frequently based on complex data 
processing,  aiming  at  more  efficient  decision-making  and  sometimes  at  the  full 
automation of processes.  

These data-driven technologies need to make equality and non-discrimination a key 
consideration.  As  was  demonstrated  by  the  FRA’s  recent  report12,  algorithms  hold 
significant potential for discriminatory bias. Biases are often inherent in data that are 
frequently used to build algorithms and AI systems,  the so-called training data. For 
instance, the FRA’s simulation of algorithms to detect offensive speech used training 
data consisting of real social-media posts which had been labelled as offensive or not 

11 The United States National Science and Technology Council distinguishes between three types of data, 
all of which are essential for evidence-based policymaking: 
‘a) Data that helps us understand the quantity of people who have a particular experience or characteristic 
(“quantity”  or  “prevalence  data”);  b)  Data  that  helps  us  understand  how  people  experience  systems 
differently (“quality” or “difference data”); and c) Data  that helps us understand whether policies and 
interventions work for different populations (“understanding what works” or “assessment data”).’  
See Subcommittee on Sexual Orientation, Gender Identity, and Variations in Sex Characteristics (SOGI) 
Data and Subcommittee on Equitable Data of the National Science and Technology Council (2023), Federal 
Evidence Agenda on LGBTQI+ Equity, United States Government, p. 8. 
12  FRA  (2022),  Bias  in  algorithms  –  Artificial  intelligence  and  discrimination,  Publications  Office, 
Luxembourg. 

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offensive13. The instances of online hatred in the data were often directed towards 
LGBTIQ, Muslim and Jewish people. As a result, in the FRA’s simulation of algorithms 
to detect offensive speech, terms linked to sexual orientation such as ‘gay’ were more 
often incorrectly labelled as offensive, as were terms like ‘Muslim’ and ‘Jew’14. Over-
flagging  may  be  helpful  to  identify  and  counter  instances  of  hate  speech  towards 
these groups. However, it can have the adverse effect of members of these groups 
disproportionately  having  their  content  flagged  as  offensive15,  which  becomes 
particularly problematic if the flagged content is not subject to human review16. 

It is necessary to analyse algorithms for bias, including by checking training data for 
sources of bias and by checking the outputs of the algorithms themselves. Even when 
there is no direct information on protected characteristics included in the data, the 
use of algorithms can still lead to discrimination due to data that are highly correlated 
with  protected  characteristics  (proxies).  A  particularly  problematic  example  is 
algorithmic  profiling  used  by  law  enforcement,  which  uses  different  techniques  to 
profile people based on correlations and patterns in data17. Profiling that results in 
discrimination  based  on  protected  characteristics  is  unlawful18,  but  can  be  hard  to 
detect. Most algorithmic bias results in indirect discrimination through proxies (such 
as  neighbourhoods  or  names  as  a  proxy  for  ethnicity,  or  shoe  size  as  a  proxy  for 
gender). Given the potentially limitless number of proxies, whose correlation with a 
protected characteristic may not be evident, this is more difficult to counteract 19.  

Bias  can  also  be  introduced  if training data  are unrepresentative.  For  instance,  if a 
face-detection algorithm is mainly trained on male faces, its predictions may not be 
reliable  when  applied to  female faces20.  Bias  stemming  from poor data  quality can 
also  be  amplified  by  feedback  loops,  which  occur  when  predictions  of  algorithms 
become the basis for future training datasets, for example in predictive policing21. 

It is therefore important to also analyse the output of algorithms for bias. If the output 
of algorithms differs when only information on protected characteristics changes, this 

13  FRA  (2022),  Bias  in  algorithms  –  Artificial  intelligence  and  discrimination,  Publications  Office, 
Luxembourg, pp. 11-12, pp. 55-56. 
14  FRA  (2022),  Bias  in  algorithms  –  Artificial  intelligence  and  discrimination,  Publications  Office, 
Luxembourg, pp. 11-12, p. 62. 
15  FRA  (2022),  Bias  in  algorithms  –  Artificial  intelligence  and  discrimination,  Publications  Office, 
Luxembourg, p. 11. 
16  FRA  (2022),  Bias  in  algorithms  –  Artificial  intelligence  and  discrimination,  Publications  Office, 
Luxembourg, p. 77. 
17  FRA  (2018),  Preventing  unlawful  profiling  today  and  in  the  future:  a  guide,  Publications  Office, 
Luxembourg, p. 19. 
18 Article 11 (3) of the Police Directive. 
19  FRA  (2022),  Bias  in  algorithms  –  Artificial  intelligence  and  discrimination,  Publications  Office, 
Luxembourg, p. 24. 
20  FRA  (2022),  Bias  in  algorithms  –  Artificial  intelligence  and  discrimination,  Publications  Office, 
Luxembourg, p. 19. 
21  FRA  (2022),  Bias  in  algorithms  –  Artificial  intelligence  and  discrimination,  Publications  Office, 
Luxembourg, p. 77. 

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indicates a risk of discrimination22. For this purpose, it is necessary to collect data on 
protected characteristics, including SOGIESC. Currently, the legal basis for this may be 
unclear  for  users  of  algorithms,  since  detecting  algorithmic  discrimination  is  not 
specified as a justification for processing sensitive personal data in the General Data 
Protection Regulation (GDPR)23, although the EU’s proposed Artificial Intelligence Act 
may provide some clarity24. 

1.3. 

Purpose and structure of this guidance 
note 

Since SOGIESC categories can have different meanings in different societies and social 
contexts, there is no self-evident solution for measuring these categories. There is also 
no agreed-upon standard for how to best collect data on SOGIESC. This results in a lack 
of comparability between existing data-collection efforts at national level and across the 
EU. It also increases the time and cost of developing relevant categories and collecting 
data.  Improving  data-collection  efforts  and  the  quality  of  collected  data  will  help 
Member  States  and  the  EU  to  gather  more  exact  SOGIESC  data  to  support  their 
monitoring  and  reporting  activities.  It  will  also  help  to  increase  trust  among  LGBTIQ 
people in data-collection efforts by states and public institutions. 

Although it supports awareness-raising on the opportunities and challenges of collecting 
SOGIESC data, this guidance note serves as a starting point to help Member States to 
effectively  apply  and  monitor  EU  equality  law.  It  sets  out the  challenges  in  collecting 
data on SOGIESC, and highlights promising paths to a more standardised and consistent 
approach, while reflecting the different national contexts and the varying requirements 
for  the  collection  of  equality  data  based  on  SOGIESC.  Policymakers  and  other 
stakeholders may choose or prioritise actions set out in the guidelines that best meet 
the needs identified at the time in any given Member State.  

EU  Member  States  are  encouraged  to  use  these  guidelines  to:  (i)  inform  the 
development and effective implementation of national action plans on LGBTIQ equality; 
(ii)  inform  their  equality-data  strategies;  and  (iii)  monitor  the  outcomes  of  these 
strategies from an equality perspective.  

22  FRA  (2022),  Bias  in  algorithms  –  Artificial  intelligence  and  discrimination,  Publications  Office, 
Luxembourg, p. 25. 
23  FRA  (2022),  Bias  in  algorithms  –  Artificial  intelligence  and  discrimination,  Publications  Office, 
Luxembourg, p. 24. 
24  FRA  (2022),  Bias  in  algorithms  –  Artificial  intelligence  and  discrimination,  Publications  Office, 
Luxembourg, p. 10. 

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The target audience of these guidelines includes public and private entities involved in 
collecting and using data on equality for LGBTIQ people, such as: 

● 

● 

● 

● 

● 

● 

data producers in political and administrative bodies at national, regional, and 
local level; 

national statistical offices; 

private and public organisations; 

the justice system and the police; 

equality bodies and national human rights institutions; 

academia. 

The guidance note begins by setting out the challenges, data-protection rules, and key 
ethical  considerations  when  collecting  and  using  SOGIESC  data  (Section  2).  The  main 
body of this guidance summarises two sets of principles for collecting and using equality 
data based on SOGIESC. The first set of 7 principles are general/cross-cutting in nature, 
and are discussed in Section 3. The second set of 4 principles provide practical guidance 
on how to collect data on SOGIESC, and are discussed in Section 4. The second set of 
practical  principles  includes  several  examples  of  past  surveys  to  illustrate  possible 
approaches. However, these are not intended as examples of best practice to be directly 
adopted. Where examples contain problematic elements, these are highlighted in the 
notes for consideration under each example. 

Because  the  requirements  for  collecting  equality  data  on  SOGIESC  may  vary  across 
different data sources (e.g. administrative, census, or survey data), the applicability of 
the following guiding principles might be easier for some data sources than others. The 
principles do not follow any particular order of priority. Depending on the user’s needs, 
they  can  be  read  either  together  and  applied  as  a  whole,  or  they  can  be  applied 
individually or combined. 

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Figure 1 – Guiding principles for the collection and use of equality data 
on SOGIESC 

Alternative text: Figure laying out the structure of the guidance note. At the top is an 
arrow with the text ‘Data-protection rules (2.2) & Ethical considerations (2.3)’. Below are 
boxes with the general/cross-cutting principles and logos to illustrate them: ‘3.1 Carry 
out  needs  assessments  of  (potential)  users’,  ‘3.2  Identify  existing  data  sources  on 
SOGIESC  data’,  ‘3.3  Align  definitions/categorisations  related  to  SOGIESC’,  ‘3.4  Take 
information on SOGIESC into account in all policies’, ‘3.5 Take intersectional approach 
into account in all policies’, ‘3.6 Provide sufficient budget’ and ‘3.7 Facilitate effective 
use of SOGIESC data’. Below this are four boxes with the practical principles: ‘4.1. How 
to  collect  data  on  sexual  orientation’,  ‘4.2  How  to  collect  data  on  sex  and  gender 
(identity)’, ‘4.3 How to collect data on gender expression’, and ‘4.4. How to collect data 
on sex characteristics’. 

Type your caption here. 

© Type your Copyright information here. 

Source: Type your source here. 

The  guidance  note  is  complemented  by  a  compendium  of  promising  practices  for 
collecting  equality  data25,  which  compiles  a  range  of  practices  on  different 

25 FRA (2023), Compendium of practices for equality-data collection. 

14 

 
 
 
 
discrimination grounds, including SOGIESC, and aims to provide practical examples on 
how to implement the principles on collecting and using equality data.  

The Subgroup on Equality Data developed this guidance note with the support of the 
FRA and two leading experts in LGBTIQ equality. Before being finalised and endorsed by 
the  High-Level  Group  on  Non-Discrimination,  Equality  and  Diversity,  key  European 
LGBTIQ  representative26  organisations  and  the  Subgroup  on  LGBTIQ  Equality  were 
consulted.  

26 ILGA Europe, The Eurocentralasian Lesbian* Community (EL*C), OII Europe, 

Transgender Europe (TGEU), IGLYO. 

15 

 
 
 
2. 

Challenges, data protection, and 
other  ethical  considerations  in 
collecting  and  using  equality 
data on SOGIESC 

2.1. 

Challenges 
SOGIESC data 

in  collecting  and  using 

In addition to the common challenges and gaps in the collection and use of equality data 
more  broadly,  which  were  explored  in  the  first  guidance  note  developed  by  the 
Subgroup27, there are other and/or cumulative challenges to the collection and use of 
SOGIESC data. The 11 bullet points below discuss these additional challenges in more 
detail. 

● 

● 

Limited  reliable  information  on  the  composition  of  LGBTIQ  people  among  the 
population in the EU and a lack of sampling frames. So far, only Malta’s census28 
includes  questions  on  sexual  orientation  and  gender  identity,  and  no  national 
census  in  the  EU  asks  about  gender  expression  or  sex  characteristics.  There  is 
therefore a lack of reliable estimates of the percentage of LGBTIQ people in the 
population, and this restricts quantitative research and makes it difficult to develop 
reliable sampling frames29. 

The need for valid and reliable measures which reflect contemporary terminology 
and concepts. Definitions and categorisations need to be aligned across national 
data sources and between Member States to ensure comparability (see Guideline 
No  3.3  of  this  guidance  document).  Conceptions  of  LGBTIQ  identities  and 

27 Common challenges in collecting and using equality data include: the lack of a coordinated approach; 
the  lack  of  sufficient  resources;  insufficient  comparability  across  different  data  sources;  insufficient 
consultation  with  relevant  stakeholders;  an  imbalance  of  data  collection  on  different  grounds  of 
discrimination and across different areas of life; an over-reliance on proxies; and inaccurate interpretation 
of the data-protection frameworks. See: European High Level Group on Non-Discrimination, Subgroup on 
Equality Data (2018), Guidelines on improving the collection and use of equality data, Publications Office, 
Brussels, pp. 9-10. 
28 National Statistics Office – Malta, Census. 
29  Daly,  F.,  Crehan,  P.  R.,  Grzywnowicz,  M.  (2022),  The  LGBTI  Inclusion  Index:  An  Innovative  Tool  to 
Incentivize  Human  Rights  and  Development  Data. Journal  of  Human  Rights  Practice,  14(2),  600-621, 
p.614. 

16 

 
 
 
experiences are continuously evolving, so these concepts should be under periodic 
review while endeavouring to support comparability across time30. Differences in 
language,  culture  and  historical  understandings  should  also  be  considered  (see 
Section 4 of this guidance document). Moreover, terms commonly known within 
the  LGBTIQ  community  may  not  be  as  well-known  to  the  general  public,  so 
researchers  should  balance  the  use  of  precise  terminology  with  the  need  for 
accessible  questions,  particularly  when  the  survey  is  directed  at  the  general 
population31. In doing so, researchers should  avoid using terms which may be in 
common  use  but  are  considered  outdated  and/or  derogatory  (such  as 
‘hermaphrodite’ rather than ‘intersex’, or ‘transsexual’ as a term to refer to all trans 
people)32. 

● 

Small sample sizes that limit statistical power. In most population-based surveys, 
LGBTIQ people represent less than 10% of the sample. This can be a challenge for 
data  disaggregation  and  statistical  power.  It  may  result  in  LGBTIQ  people  being 
excluded  entirely  from  the  reported  findings  or  being  included  with  large 
confidence intervals. It can also limit any substantial intersectional analysis. This 
can be countered through increasing overall sample sizes, oversampling33 LGBTIQ 
people, using booster samples34, or conducting dedicated surveys, although these 
approaches all entail extra costs35. 

●  Methods  of  data  collection.  There  are  specific  challenges  in  surveying  LGBTIQ 
people  with  traditional  methods,  such  as  personal  interviews  conducted  either 
face-to-face or via telephone. Many LGBTIQ people are not ‘out’ in all aspects of 
their  life  and  may  not  be  willing  to  disclose  aspects  of  their  private  identity  or 
experiences, or may only be willing to do so anonymously. This can be countered 
through  a  self-completion  section  in  a  face-to-face  interview  (CASI  –  computer-
assisted  self-interviewing)  ensuring  confidentiality,  or  through  an  online  survey 

30 National Academies of Sciences, Engineering, and Medicine (2022),  Measuring Sex, Gender Identity, 
and Sexual Orientation, Washington, DC: The National Academies Press, p. 124.  
31 Center for American Progress (2022),  Collecting Data About LGBTQI+ and Other Sexual and Gender-
Diverse Communities – Best Practices and Key Considerations. 
32 Further information on terms to use and avoid can be found in European Parliament (2020), Glossary 
of  Sensitive  Language  for  Internal  and  External  Communications,  and  in  Ginicola,  M,  Smith,  C,  and 
Filmore, J. (Eds.) (2017), Affirmative Counseling with LGBTQI+ People, American Counseling Association, 
pp. 368-370. 
33 Oversampling is the practice of selecting respondents so that some groups make up a larger share of 
the survey sample than they do in the population. 
34  In  the  German  Socio-Economic  Panel  (SOEP),  a  ‘boost  sample’  of  sexual  and  gender  minority 
respondents was used to supplement the existing probability-based sample, see Fischer M., Kroh M., De 
Vries  L.,  Kasprowski  D.,  Kühne  S.,  Richter  D.  and  Zindel  Z.  (2022),  Sexual  and  Gender  Minority  (SGM) 
Research Meets Household Panel Surveys: Research Potentials of the German Socio-Economic Panel and 
Its Boost Sample of SGM Households, European Sociological Review, (38(2)). 
35 Sell, R. L. (2017), Challenges and Solutions to Collecting Sexual Orientation and Gender Identity Data. 
American Journal of Public Health, 107 (8), 1212-1214, pp. 1213-1214. 

17 

 
 
 
method (such as CAWI: computer-assisted web interviewing) ensuring anonymity. 
This might result in more respondents from different strata of the target population 
being willing to participate, including those who do not wish to disclose that they 
are LGBTIQ in a traditional survey conducted face-to-face or by telephone. Often, 
due to the lack of sampling frames,36 the preferred method of data collection is a 
self-selection online survey. However, this also comes with its own challenges, as 
the sample will tend to be biased towards people more active within the LGBTIQ 
community,  especially  if  it  is  not  combined  with  a  well-developed  outreach 
campaign. Online methods in general pose the challenge of excluding people who 
lack access to technology or digital literacy. 

●  Weighting  methods  depend  on  the  method  of  data  collection.  Where  data  are 
available for a representative sample (such as through the census in Malta37), it is 
possible to weight these data based on the proportion of the population and their 
composition.  When  a  non-probabilistic  approach  is  used,  post-stratification 
weighting can be applied to align the completed sample with estimated population 
totals. Weighting should also attempt to correct for potential exclusion, selection, 
and non-participation biases. This can include taking the channels used for survey 
promotion into account38.  

● 

● 

Lack of – or insufficient – participation/consultation of LGBTIQ people and their 
representative  organisations  in  the:  (i)  design  and  implementation  of  data 
collection; (ii) interpretation of results; and (iii) dissemination efforts. This lack of 
involvement  might  result  in  incorrect  categorisations  and  interpretations  of 
findings,  as  well  as  limited  outreach.  Considering  the  experience  and  expert 
knowledge  of  the  communities  is  important  in  developing  policy  measures  that 
reflect contemporary terminology and the situation at stake. Active consultation 
with LGBTIQ people/organisations at all stages of data collection, analysis, and use 
can be helpful for understanding the cultural context, the stigma LGBTIQ people 
might be facing, and other specific experiences.  

The need to build trust. Given the long history of persecution and criminalisation 
that  LGBTIQ  people  have  faced  and  continue  to  face,  they  may  be  reluctant  to 
provide information on their sexual orientation, their gender identity, or whether 
they are intersex/have a variation of sex characteristics. This is especially the case 
for people who belong to multiple marginalised groups. Therefore, it is important 

36 A sampling frame is a list of units/people from which a sample is drawn. 
37 National Statistics Office – Malta, Census. 
38  For  instance,  for  the  FRA  LGBTI  Survey  2019,  affiliation  weights  were  used  to  correct  for  over-
representation of affiliated respondents and respondents who had been reached through campaigns by 
LGBTIQ organisations. See FRA (2020), Technical report. A long way to go for LGBTI equality, Publications 
office of the European Union, Luxembourg. pp. 76-85. 

18 

 
 
 
to: (i) build trust by working together with civil-society groups; and (ii) clarify how 
the data are stored and used and for what purpose they are stored and used (see 
Section  No  2.3  of  this  guidance  document).  Where  possible,  anonymised  data 
should be made accessible to LGBTIQ communities and organisations for their own 
use. All public bodies should publish equality data that can readily be used by the 
public, civil-society organisations, and independent researchers. This should be in 
accessible formats for  people  who  are  not  experts  in the field.  Special  attention 
should be paid to making these data accessible for people with disabilities39. 

The  difficult  of  reaching  underrepresented  and  hard-to-reach  groups.  Data-
collection efforts need to be conscious of adopting sampling strategies that reach 
underrepresented  LGBTIQ  people.  These  efforts  should  consider,  among  other 
factors:  gender;  age;  disability;  racial  and  ethnic  background;  migration  and 
refugee status; class; social origin; languages spoken by potential respondents; the 
level of respondents’ involvement in the LGBTIQ community; access to housing (as 
LGBTIQ  people  disproportionately  experience  homelessness);  access 
to 
technology;  as  well  as  the  intersections  between  these  factors.  Survey  methods 
should  be  adapted  to  the  groups  to  be  reached,  and  methodological  limitations 
should  be  openly  acknowledged.  For  example,  a  survey  focused  on  LGBTIQ 
community centres would overwhelmingly reach people who are already actively 
engaged in the community and will be less likely to reach people who are ‘closeted’ 
(i.e. who do not publicly disclose that they are LGBTIQ)40. 

The need to improve outreach to LGBTIQ women. Within the LGBTIQ community, 
cisgender41, endosex42 gay men tend to be overrepresented in data collection43. A 
specific effort should  therefore be made: (i) to ensure the participation of other 
members  of  the  community,  specifically  targeting  the  women  of  the  LGBTIQ 
community; and (ii) to ensure that civil-society organisations led by – and focused 
on – LGBTIQ women are involved in all parts of the dissemination process.  

The need for explicit inclusion of trans and intersex people.  Often, research on 
LGBTIQ communities only considers sexual orientation (see Guideline No 3.4 of this 
guidance note), without asking about gender identity, gender expression, and sex 

● 

● 

● 

39 Measures can include using ‘simple English’ (or equivalent), sign-language interpretation, large-print 
text, alt text for images, and colourblind-accessible colours in data visualisations. 
40 Human Rights Campaign Foundation (2019), LGBTQ-Inclusive Data Collection: A Lifesaving Imperative. 
Washington, DC, Human Rights Campaign Foundation, p. 17. 
41 Cisgender people are people whose gender identity corresponds to their sex assigned at birth. 
42 An endosex person is someone whose sex characteristics fit the normative medical or social ideas for 
female and male bodies. 
43 For example, in the FRA LGBTI II Survey 2019, gay cisgender men represented 42% of the respondents. 
FRA (2020),  Technical report. A long way to go for LGBTI  equality, Publications  Office  of the European 
Union, Luxembourg. p. 63. 

19 

 
 
 
characteristics. It is important to ensure that all parts of the community are made 
visible within the data, and to account for multiple affiliations within the LGBTIQ 
categories (for example, someone may be trans, intersex, lesbian and a woman). 

●  Administrative data and the use of proxies (see Guideline No 3.4 of this guidance 
document). Member States are increasingly moving towards using administrative 
data to produce both population-related statistical information and their censuses. 
Since  administrative  data  sources  rarely  include  information  about  sexual 
orientation,  gender  identity,  or  about  being  intersex/having  a  variation  of  sex 
characteristics,  there  is  a  risk  that  LGBTIQ  people  will  increasingly  be  rendered 
invisible.  Collecting  SOGIESC  information  in  administrative  data  without  a  legal 
ground or rationale being provided may also raise questions about data protection 
and  the  validity  of  the  information  provided44.  Administrative  SOGIESC  data 
collection will always be limited to: (i) the legal ground determining its purpose; 
and  (ii)  complying  with  data-protection  rules.  Collecting  SOGIESC  information  in 
administrative data might also result in limiting comparability across data sources 
within and between countries. This is because the measurements in different data 
sources  and  countries  might  be  based  on  differing  concepts.  Where  proxy 
information is used, it might not reflect how the person in question would have 
self-identified,  so  it  is  likely  to  result  in  undercounts.  Although  they  should  be 
approached with caution, such data can be helpful, for instance where they provide 
the basis for further research that makes self-identification possible45.  

Box A 3 – Willingness to share SOGIESC information 

Findings  of  the  Special  Eurobarometer  437  point  to  broad  support  for  providing 
sensitive personal information on an anonymous basis, especially among those who 
describe themselves as belonging to a minority group at risk of discrimination. Some 
83%  of  respondents  who  self-identified  as  belonging  to  a  sexual  minority  were  in 
favour  of  providing,  on  an  anonymous  basis,  information  about  their  sexual 
orientation46. 

44  Ashley,  F.  (2021),  Recommendations  for  Institutional  and  Governmental  Management  of  Gender 
Information. New York University Review of Law & Social Change, 44(4):489-528, pp. 504, 514-515. 
45  Ashley,  F.  (2021),  Recommendations  for  Institutional  and  Governmental  Management  of  Gender 
Information. New York University Review of Law & Social Change, 44(4):489-528, pp. 504, 514-515. 
46 European Commission (2015), Special Eurobarometer 437: Discrimination in the EU in 2015, European 
Union, p. 99. 

20 

 
 
 
2.2. 

Data-protection rules do not prevent 
the collection of equality data on 
SOGIESC 

‘Ensure that requirements for individuals to provide information on their sex or gender 
are relevant, reasonable and necessary as required by the law for a legitimate purpose 
in the circumstances where it is sought, and that such requirements respect all persons’ 
right to self-determination of gender’.  

-The Yogyakarta Principles plus 1047, Principle 6(G) 

In  the  EU,  the  collection  of  personal  data  disaggregated  by  sensitive  personal 
characteristics, such as SOGIESC, is protected by EU data-protection law and the Charter 
of Fundamental Rights of the EU. However, data-protection rules do not stand in the 
way of collecting equality data for statistical purposes. On the contrary, the rules allow 
data to be processed while ensuring the respect of fundamental rights48. 

The GDPR provides for a single set of data-protection rules across the EU, meaning that 
all collection and processing of data on equality should be carried out in full compliance 
with  the  principles  and  safeguards  set  out  under  it.  The  GDPR  requires  that  data 
collection  should  pursue  a  well-defined  goal,  such  as  measuring  and  documenting 
inequalities or meeting legal reporting requirements49. More restrictive conditions apply 
to processing sensitive data, as mentioned in the GDPR on ‘special categories of personal 
data’50. 

Furthermore, the principle of ‘data minimisation’ lies at the heart of the EU’s general 
data-protection regime, requiring that personal data should be ‘adequate, relevant, and 

47 In 2006, international human-rights experts adopted a set of international principles relating to sexual 
orientation and gender identity serving as a universal guide to human rights. These Yogyakarta principles 
affirm binding international legal standards with which all States must comply. In 2017, the Yogyakarta 
Principles plus 10 (YP+10) were adopted to complement the original Yogyakarta Principles. 
48 See FRA (2021), Equality in the EU 20 years on from the initial implementation of the equality directives, 
Publications Office, Brussels; European Commission (2021), Round table on Equality Data in September 
2021. 
49 Any organisation processing personal data must have a valid legal basis for that processing activity. The 
law provides six legal bases for processing: consent, performance of a contract, a legitimate interest, a 
vital interest, a legal requirement, and a public interest.  See Article 6, 253 Regulation (EU) 2016/679 of 
the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with 
regard  to  the  processing  of  personal  data  and  on  the  free  movement  of  such  data,  and  repealing 
Directive 95/46/EC, OJ 2016 L 119 (General Data Protection Regulation). 
50 Under Article 9 of the GDPR special categories of personal data comprise ‘personal data revealing racial 
or ethnic origin, political opinions, religious or philosophical beliefs, or trade union membership’, as well 
as ‘genetic data, biometric data for the purpose of uniquely identifying a natural person, data concerning 
health or data concerning a natural person’s sex life or sexual orientation’. 

21 

 
 
 
limited to what is necessary in relation to the purposes for which they are processed’51. 
This means that:  

● 

● 

● 

data processing should be limited to what is necessary to fulfil a legitimate purpose; 

personal-data  processing  should  only  take  place  when  its  purpose  cannot  be 
reasonably fulfilled by other means; 

data processing may not disproportionately interfere with the interests, rights, and 
freedoms at stake52; 

Article  9(2)  of  the  GDPR  clearly  stipulates  that  the  general  prohibition  on  processing 
special categories of personal data in line with the ‘data minimisation’ principle does not 
apply in several cases, including when:  

■ 

■ 

■ 

the data subject has given explicit consent; 

processing is necessary for reasons of substantial public interest, on the basis 
of EU or national law; 

processing is necessary for: (i) achieving purposes in the public interest; (ii) 
the purposes of scientific or historical research; or (iii) statistical purposes. 

In addition, Recital 26 of the GDPR clarifies that the principles of data protection apply 
to special categories of personal data that concern an identified or identifiable natural 
person. By contrast, they do not apply to anonymous information or to personal data 
rendered anonymous in such a manner that the data subject is not  identified or is no 
longer identifiable53. Given the sensitivity of the information, data anonymity should be 
guaranteed even when linking data sets. Measures should be taken to prevent any abuse 
or data leaks following the collection of the data. 

Data-collection efforts also need to ensure a balance between the benefits of the data 
collected  and  the  risks  associated  with  any  potential  misuse  or  unauthorised  data 
disclosure54. This ensures that data are only collected where the benefits of collecting 
the  information  outweigh  the  intrusion  of  privacy55.  Therefore,  data  should  not  be 

51 Article 5(1)(c) and Recital (39) of the General Data Protection Regulation. 
52  FRA,  Council  of  Europe  (2018  edition),  Handbook  on  European  data  protection  law,  Section  3.3. 
Publications Office, Luxembourg.  
53 For more information, see: (i) Guiding Principle No 4 of the Guidance Note on the collection and use of 
equality  data  based  on  racial  and  ethnic  origin;  (ii)  the  European  Commission’s  2017  report  on  data 
collection in relation to LGBTIQ people; (iii) the EDPS preliminary opinion on data protection and scientific 
research from 6 January 2020; and  (iv)  the upcoming EDPB guidance on data protection and scientific 
research. 
54 National Academies of Sciences, Engineering, and Medicine (2022),  Measuring Sex, Gender Identity, 
and Sexual Orientation, The National Academies Press, Washington DC, p. 61. 
55  Conference  of  European  Statisticians,  67th  plenary  session  (2019).  In-Depth  Review  of  Measuring 
Gender Identity. United Nations Economic and Social Council, Paris. 

22 

 
 
 
published or publicly accessible in a manner that allows individual data subjects to be 
identified, either directly or indirectly. 

2.3. 

Ethical  considerations  in  relation  to 
data on SOGIESC 

‘Recognise that the needs, characteristics and human-rights situations of populations of 
diverse  sexual  orientations,  gender 
identities,  gender  expressions  and  sex 
characteristics are distinct from each other, and ensure that data on each population is 
collected and managed in a manner consistent with ethical, scientific and human-rights 
standards and made available in a disaggregated form’.  

-  The Yogyakarta Principles plus 10, Principle 19. 

The  use  of  statistical  and  analytical  categories  for  any  data  collection  or  for  data 
disaggregation should always be guided by the overriding human-rights based principle 
of doing no harm. This principle was set out by the United Nations High Commissioner 
for Human Rights (OHCHR) in the Human Rights-Based Approach to Data.  

‘Doing no harm’ means: (i) that no data-collection activity should create or strengthen 
existing discrimination, bias, or stereotypes; and (ii) that the data collected should be 
used for the benefit of the groups they describe.  

This guidance note recognises and reaffirms the OHCHR set of six principles of a human 
rights-based  approach  to  data  collection:  participation,  data  disaggregation,  self-
identification, transparency, privacy, and accountability. 

In addition to the set of human-rights based principles for data collection, the ethical 
principles  set  out  in  the  bullet  points  below  should  underpin  and  guide  all  national 
efforts when collecting data on SOGIESC. 

●  Questions  on  SOGIESC  should be  voluntary:  that  is, nobody  should be forced to 
disclose their sexual orientation, gender identity, or whether they have a variation 
of sex characteristics if they do not want to. Respondents should therefore have 
the opportunity to respond to SOGIESC questions with ‘prefer not to say/disclose’ 
and ‘don’t know’ or ‘questioning’. 

23 

 
 
● 

Informed consent to take part is crucial56. This requires a clear affirmative act on 
the part of the data subject consenting to their data being processed. Consent must 
be  freely  given,  specific,  and  unambiguous.  It  must  cover  all  purposes  of  data 
processing, and all processing activities carried out for these purposes57. 

●  When the purpose for collecting special categories of personal data is not clear, it 
is recommended to inform the subject as to: (i) the legal ground for collecting the 
data; (ii) the purpose for which the data are collected; and (iii) how the data will 
be processed and protected. 

● 

● 

Civil-society  organisations,  including  LGBTIQ  organisations  and  survey  experts, 
should be involved as much as possible in all stages of developing a survey or data-
collection  instrument.  Whenever  possible,  they  should  also  be  involved  in 
interpreting  and  contextualising  results  in  line  with  the  underlying  principle  of 
doing  no  harm. During  any  consultation  process,  LGBTIQ  representatives  should 
not feel pressured to take part, and they should receive appropriate compensation 
for their contributions. 

Inconsistencies  in  SOGIESC  information  provided  by  respondents  to  different 
administrative  sources  should  not  automatically  be  interpreted  as  attempts  at 
falsification or as errors needing to be corrected or clarified. This is particularly 
important  for  situations  where  SOGIESC  information  is  collected  as  part  of 
administrative information to provide permits, services, benefits, or employment. 
Inconsistencies  may  be  due  to  various  reasons,  including:  (i)  changes  in  the 
respondents’  identities;  (ii)  changes  in  their  levels  of  comfort  in  disclosing  such 
information; or (iii) limited response options (such as the use of binary gender or 
sex categories). Forms collecting SOGIESC information should clarify explicitly that 
respondents will not be penalised for any discrepancies58. 

● 

Interviewers  may  affect  results  since  people  might  be  more  reluctant  to  reveal 
their  sexual  orientation,  gender  identity/expression,  or  the  fact  that  they  are 
intersex/have  a  variation  of  sex  characteristics  to  an  interviewer  (for  data-
collection modes, see Section 2.1 of this guidance document).  

56 IE SOGI – UN Independent Expert on protection against violence and discrimination based on Sexual 
Orientation  and  Gender  Identity  (2019),  Data  collection  and  management:  An  essential  component  in 
creating awareness and providing effective measures to address violence and discrimination based on 
SOGI, United Nations Human Rights Special Procedures.  
57 Recital (32) of the General Data Protection Regulation (GDPR). 
58 Subcommittee on Sexual Orientation, Gender Identity, and Variations in Sex Characteristics (SOGI) Data 
and  Subcommittee  on  Equitable  Data  of  the  National  Science  and  Technology  Council  (2023),  Federal 
Evidence Agenda on LGBTQI+ Equity, United States Government, pp. 39-40. 

24 

 
 
 
● 

● 

For  in-person  interviews,  it  is  important  to  create  a  safe  environment  where 
respondents can answer questions at their own pace, in privacy, and without fear 
of being overheard by other household members or passers-by59. The interviewer 
should consider that answering sensitive questions may be emotionally taxing and 
could be ‘triggering’ 60to some participants. 

The principles of avoiding harm should also be extended to cover the interviewers. 
Because  interviewers  may  visit  the  homes  of  people  unknown  to  them  during 
research projects, they put themselves under a certain degree of psychological and 
physical  risk.  In  such  cases,  interviewers  should  have  access  to  psychological 
support during fieldwork61. 

●  When a survey aims to assess sensitive topics such as violence, discrimination, and 
sexual abuse, content warnings and information on  specialised support services 
should be provided to respondents at the beginning and end of the survey. 

●  When the response category ‘other’ is included as a choice for a survey question, a 
write-in possibility should be available whenever possible. This allows respondents 
to elaborate in their own words on a particular issue/ground and reduces the risk 
of  producing  unreliable  data,  subsumed  under  a  closed  category  of  ‘other’. 
Including  the  option  ‘other’  can  also  inform  possible  changes  to  the  answer 
categories in subsequent iterations of the survey. Where the question is about a 
respondent’s identity, it might be preferable to use an alternative formulation such 
as ‘Please describe’ or ‘Prefer to self-describe’.  

●  When  conducting  qualitative  research,  researchers  should  be  aware  of  implicit 
bias, and they should therefore be trained in diversity and anti-discrimination to 
minimise  potential  discomfort  and  power  imbalances  when  engaging  with 
respondents. Interviewer matching (i.e. making sure the interviewer resembles the 
interviewee  in  some  way  such  as  in  gender,  language  spoken,  or  migration-
experience) can increase response rates and acceptance amongst respondents and 
thus  improve the  research  results62.  Interviewee transcript  review  (i.e.  allowing 
interviewees to listen to a recording of the interview they have given so they can 

59 European Commission (2021), Guidance note on the collection and use of equality data based on racial 
or ethnic origin. Publications Office, Luxembourg, p. 55. 
60 Triggering words can cause strong emotions (for example, frustration) because of previous experiences. 
61 European Commission (2021), Guidance note on the collection and use of equality data based on racial 
or ethnic origin. Publications Office, Luxembourg, p. 55. 
62 European Commission (2021) Guidance note on the collection and use of equality data based on racial 
or ethnic origin. Publications Office, Luxembourg, p. 55. 

25 

 
 
 
reflect  on  and  correct  the  account  they  give)  can  be  a  useful  tool  to  avoid 
misrepresentation or researcher bias when talking about SOGIESC topics63. 

Data-protection  rules  and  other  ethical  considerations  are  general/cross-cutting  in 
nature, and should be considered in the implementation of the guiding principles set 
out in this note. 

63 Hagens, V., Dobrow, M.J. and Chafe, R. (2009), Interviewee Transcript Review: assessing the impact on 
qualitative research. BMC Med Res Methodol 9, 47; Rowlands, J. (2021), Interviewee Transcript Review as 
a Tool to Improve Data Quality and Participant Confidence in Sensitive Research. International Journal of 
Qualitative Methods, 20. 

26 

 
 
 
3. 

3.1. 

General  principles  for  collecting 
equality data on SOGIESC 

Carry  out  needs  assessments  of  users 
and 
data 
users 
potential 
disaggregated by SOGIESC 

of 

3.1.1. 

Rationale 

A  needs  assessment  of  users  and  potential  users  of  data  disaggregated  by  SOGIESC 
should help to identify the type of equality data needed for both evidence-based policy 
making and monitoring the state of equality and human rights.  

The  needs  assessment  should  be  based  on:  (i)  relevant  EU  law;  (ii)  international  and 
national normative standards to which Member States are subject (such as the Charter 
of Fundamental Rights of the EU); (iii) EU equality legislation; (iv) international human-
rights  law;  and  (v)  national  legislation.  All  of  these  standards  and  bodies  of  law  may 
variously  address  equality  and  non-discrimination  in  relation  to  SOGIESC.  The 
assessment  should  also  reflect  relevant  policies  and  political  commitments,  including 
the  European  Pillar  of  Social  Rights,  the  LGBTIQ  equality  strategy  2020-2025  and  the 
United Nations (UN) Agenda for Sustainable Development.  

The  needs  assessment  could  be  facilitated  or  coordinated  by  a  national  statistical 
institute  or  a  relevant  ministry/governmental  department.  Alternatively,  a  specific 
mandate and dedicated resources to carry out the assessment could be provided to a 
national human-rights institution, equality body, or research institute.  

3.1.2. 

Guidance 

Member States are encouraged to: 

● 

undertake  a  comprehensive  needs  assessment  for  equality  data  in  relation  to 
SOGIESC, by considering all relevant policy and legislative developments, including 
international human-rights law and relevant policy and political commitments; 

27 

 
 
● 

● 

● 

conduct  a  user-needs  assessment  periodically,  for  example  every  4-5  years, 
considering new legislative and policy developments or evaluations of existing laws 
and policies; 

identify data-collection priorities based on the urgency of the user needs; 

communicate  the  findings  of  the  needs  assessments  through  different  channels 
and  in  different  formats  to  all  relevant  institutions,  bodies,  statistical  institutes, 
research institutes, civil-society organisations, etc. 

3.2. 

Identify existing data sources that 
provide information on SOGIESC 

3.2.1. 

Rationale 

Identifying  all  available  data  (including  data  from  administrative,  governmental, 
academic and civil-society sources) related to SOGIESC is necessary to both: (i) obtain a 
coordinated approach to data collection; and (ii) create uniform categories, concepts, 
and definitions. Identifying all these data would make it possible to lay the foundation 
for  a  more  systematic  approach  to  SOGIESC  data  collection.  It  would  also  make  it 
possible to provide a solid basis for necessary improvements by identifying the three 
important factors set out in the following bullet points. 

● 

● 

The first important factor is the  different data sources and providers of equality 
data  related  to  SOGIESC.  In  identifying  these,  it  is  important  to  also  consider 
sources and providers that are not specifically designed to collect equality data but 
that  still  have  variables  that  could  be  used  to  measure  existing  structural 
inequalities. 

The second important factor is the gaps and inconsistencies in the design of a study 
and in the methods, concepts, and measurements applied (these inconsistencies 
also include unnecessary duplicates in data collection). 

●  A  distinction  can  be  made  between  international/European  data  sources  and 
national data sources. There are relatively few international/European studies that 

28 

 
 
collect international data on the experiences of LGBTIQ people64. For national data 
sources,  a  further  distinction  can  be  made  between  the  collection  of  data  on  a 
specific  topic,  such  as  discrimination,  or  the  collection  of  data  in  general  on 
population and/or household characteristics (e.g. national censuses). The latter can 
provide insight into the quantitative presence of LGBTIQ people in society and can 
possibly also provide details about the social position of these LGBTIQ people when 
comparable with other information (e.g. in a comparable work or living situation)65.  

3.2.2. 

Guidance 

Member States and all other relevant institutions and actors involved in – or responsible 
for – the collection of SOGIESC data are encouraged to take the actions set out in the 
following bullet points.  

● 

● 

● 

● 

They should take due account of Guideline No 1 ‘Map existing sources of equality 
data and identify data gaps’ of the Guidelines on improving the collection and use 
of equality data. 

They  should  identify  and  authorise  an  institution/body/organisation  to  initiate, 
coordinate, and execute the mapping exercise. 

They  should  undertake  a  comprehensive  exercise  to  identify  all  existing  data 
sources66 that support the disaggregation of data by SOGIESC in statistical terms. 
They should also list all SOGIESC categories and proxy variables used in the different 
data sources, including their underlying concepts and definitions. 

They  should  use  the  results  of  the  identification/mapping  exercise  to  find 
similarities and discrepancies between data sources and over time on: 

■ 

the  policy  area/legislative  file  for  which  the  data  have  been  used  or  are 
needed;  

■ 

the data source (administrative register, survey data, complaint data, etc.); 

64 Some examples are: Out Now Global (2020), Out Now Global LGBT 2020 Study: International LGBT2020 
Homophobia Report, Out Now, Paris; FRA (2020), A long way to go for LGBTI equality, Publications Office, 
Luxembourg; European Commission (2019), Special Eurobarometer 493: Discrimination in the European 
Union, European Union; European Social Survey (2018), ESS Round 9 Source Questionnaire, University of 
London, London; GESIS (2016), European Values Study, GESIS, Cologne.  
65 For more information about international data sources and existing official and non-governmental data 
sources, see the report on data collection in relation to LGBTIQ people. 
66 Data sources collected and/or used by national authorities in areas covered by EU law regarding equality 
and non-discrimination in relation to SOGIESC – these may also refer to proxies (such as sex of the partner 
along with the sex of the respondent, etc.). 

29 

 
 
 
■ 

■ 

■ 

■ 

■ 

■ 

the  categories/classifications  used  for  the  disaggregation,  or  the  questions 
used  in  a  survey  to  measure  SOGIESC  and  the  concepts  and  definitions 
underlying these questions (and relevant changes in categories/classifications 
over time); 

the intersections between grounds of discrimination; 

the areas of life for which the data are collected, such as: work, access to work, 
housing,  access  to  housing,  education,  health,  access  to  justice,  access  to 
goods and services, etc. 

the methods of qualitative and quantitative data collection (e.g. face-to-face 
interview, online survey, mail survey, telephone interview, etc.), sample size, 
representativeness, and geographical coverage; 

public accessibility of data and analyses; 

the  frequency  with  which  the  data  were  collected  (i.e.  the  frequency  of 
updates and existing time series, as well as any interruptions or variations in 
frequency). 

● 

● 

● 

● 

They should review the results of the data mapping in conjunction with the findings 
of the user-needs  assessment  (see  Guideline  No  3.1  of this  guidance  document) 
and assess the current needs to collect data broken down by sexual orientation, 
gender identity/expression, and sex characteristics.  

They should ensure that aggregated statistical data based on SOGIESC enter the 
public domain in a transparent manner, especially in cases where such data can be 
used by the courts (Article 47 of the Charter of Fundamental Rights of the EU).  

They should set up a data hub (with a dedicated web page) to collate and display 
SOGIESC  data  identified through  the  identification/mapping  exercise  in  line with 
Guideline No 3 of the Guidelines on improving the collection and use of equality 
data. This hub can also be hosted by the institution/body authorised to perform 
the needs assessment (see Guideline No 3.1 of this guidance document). 

They  should  carry  out  a  periodic  exercise  to  identify  LGBTIQ  equality  data 
considering  both:  (i)  the  frequency  with  which  the  identified  data  sources  are 
updated,  for  example,  every  4-5  years;  and  (ii)  new  potential  data  sources  and 
suppliers. 

●  Member  States  that  do  not  collect  SOGIESC  data  in  official  statistics  or  through 
large-scale  surveys  should  consider  a  structured  dialogue  with  different 

30 

 
 
stakeholders  (e.g.  decision-makers,  public  authorities,  research  institutes,  civil-
society organisations, etc.) to reach a consensus on what kind of data should and 
may be collected and under what conditions. 

3.3. 

Align definitions and categorisations 
related to SOGIESC 

3.3.1. 

Rationale 

A  uniform  approach  in  data  collection  (including  aligning  the  applied  SOGIESC 
definitions)  would  support  the  harmonisation  of  the  collected  data:  (i)  over  time;  (ii) 
within different data sources; and (iii) across different data sources. Aligning definitions 
of  sexual  orientation,  sex,  gender,  gender  identity,  gender  expression,  and  sex 
characteristics  would  lead  to  better  measurement  and  therefore  maximise  the 
comparability, validity, and reliability of the data collected. It would also minimise data-
collection costs. Better measurement of sexual orientation, sex, gender, gender identity, 
gender  expression,  and  sex  characteristics  will  make  it  easier  to  identify  sexual  and 
gender minority populations and understand the challenges they face. The definitions 
from the Glossary of this guidance document may be taken as a starting point for such 
an alignment.  

In summary, a uniform approach in this area would help to: 

●  maximise comparability (at the national level and across the EU); 

● 

increase the validity and reliability of SOGIESC concepts; 

●  maximise the possibilities for linking different data sources for further analysis and 

equality reporting; 

●  minimise time, costs, and unnecessary duplication between data sources. 

3.3.2. 

Guidance 

Member  States  and  relevant  institutions/bodies  involved  in  –  or  responsible  for  – 
collecting data based on SOGIESC are encouraged to take the 12 measures set out in the 
following bullet points.  

31 

 
 
● 

● 

● 

● 

● 

They should build on the most recent findings from academic research in sociology 
and  social  psychology  on  SOGIESC  to  increase  the  awareness  of  potential  data 
collectors and data users about the social construction of the following terms: sex, 
gender,  gender 
identity,  gender  expression,  sexual  orientation,  and  sex 
characteristics. 

They should engage in structured consultations with representatives of all relevant 
LGBTIQ  communities  to:  (i) 
identify  the  most  appropriate  categories  for 
disaggregation/questions  on  self-identification  to  be  asked  in  a  survey;  and  (ii) 
agree  on  operational  definitions.  In  line  with  the  UN’s  human  rights-based 
approach to data, community consultation and participation should take place as 
much  as  possible  at  all  levels  of  research,  including  at  the  stage  when 
questionnaires and measurements are being developed. 

Building  on  the  results  of  the  community  consultations,  they  should  carry  out 
consultations with: (i) survey-methodology experts; (ii) survey-design experts; and 
(iii) data experts involved in collecting administrative data (e.g. national registers 
and  censuses).  In  these  consultations,  they  should  discuss  the  challenges  and 
problems  of  potential  categorisations  for  disaggregation/survey  questions 
(including proxy data on SOGIESC) in different data collections. These consultations 
should  seek  to  reach  agreement  about  the  most  effective,  valid,  and  reliable 
approaches  to  the  collection  and  use  of  data  on  LGBTIQ  people.  These 
consultations could also provide the basis for developing standards or promising 
practices in the measurement of relevant categorisations.  

They should improve response rates by adapting and revising  questions/categories 
(in  particular  ambiguous  questions  and  categories)  where  necessary.  These 
adaptations  and  revisions  could  be  based  on  insights  from  the  community 
consultations. 

They should use precise and bias-free terminology that reflects the constructs of 
interest. The questions they use should clearly specify which components are being 
measured  (e.g.  sex,  gender,  gender  identity,  sex  characteristics,  and  sexual 
orientation). They should make sure that one construct is not used as a proxy for 
another67. In relation to this, they should duly consider Guidelines No 4.1. to 4.4. of 
this guidance document. 

67 National Academies of Sciences, Engineering, and Medicine (2022),  Measuring Sex, Gender Identity, 
and Sexual Orientation, The National Academies Press, Washington DC, p. 6. 

32 

 
 
 
● 

● 

● 

● 

● 

● 

● 

They should duly consider differences in the requirements towards different data 
sources  (administrative  registers,  censuses,  survey  data,  etc.)  and  the  feasibility 
of/leeway for applying uniform categories in different data sources.  

They should: (i) document the basic criteria and classification procedures in relation 
to  SOGIESC;  (ii)  document  their  suggested  combination  of  these  criteria  and 
procedures;  and  (iii)  inform  data  users  about  the  concepts  these  criteria  and 
procedures are based on. 

They should take due account of Guideline No 9 ‘Enhance validity and reliability of 
equality data’ and Guideline No 11 ‘Improve comparability of equality data’ of the 
guidelines on improving the collection and use of equality data. 

They should build on the findings from the identification exercise (Guideline No 3.2. 
of this guidance document) to identify commonalities and discrepancies between 
the categories/definitions applied across data sources and time.  

They should take due consideration of Guideline No 3.4 of this guidance document 
on  taking  information  on  SOGIESC  into  account  in  all  policies  to  incorporate:  (i) 
agreed-upon SOGIESC definitions/categories for disaggregation and the necessary 
combinations  of  these  definitions/categories;  and  (ii)  questions  measuring 
discrimination/crime victimisation based on SOGIESC into EU and national surveys.  

They  should  strengthen  and  take  into  account  in  all  policies  the  regular  use  of 
agreed-upon  SOGIESC  categories  to  disaggregate  all  data  collected  for  the 
European Statistical System. 

They should strengthen cooperation between different national and international 
equality bodies to improve and coordinate their data collection based on SOGIESC. 

3.4.  Mainstream information on SOGIESC in 

all national and EU surveys 

Data collectors and data users need multiple and complementary sources of equality 
data to enable evidence-based policy making and assess the state of equality for LGBTIQ 
people.  A  proper  impact  assessment  of  policies  in  the  field  of  equality  and  non-
discrimination requires regular data collection on all grounds of discrimination and for 
all areas of life covered by the relevant legislation. However, effort spent collecting more 
and  better  equality  data  should  be  balanced  and  guided  by  the  EU’s  data-protection 
rules, requiring states to collect personal data only for ‘specified, explicit and legitimate 

33 

 
 
purposes’ and only ‘relevant and limited to what is necessary in relation to the purposes 
for which [personal data] are processed’68. 

3.4.1. 

Rationale 

3.4.1.1. 

Censuses 

Censuses, large-scale national and international surveys, and administrative data can be 
valuable  sources  of  equality  data.  However,  they  are  often  limited  in  the  data  they 
collect.  

Censuses provide information on the size, composition, and spatial distribution of the 
population, as well as on its socioeconomic and demographic characteristics. Censuses 
collect  data  on  each  person  of  the  general  population  based  on  registers, 
questionnaires, or mixed data sources. 

The collection of personal data broken down by personal characteristics is protected by 
constitutional standards, EU data-protection law, and the Charter of Fundamental Rights 
of the EU. Current EU legislation requires every census to collect and ask for information 
about sex. The question is mandatory and the response categories that are allowed are 
‘male’ or ‘female’69. This has created a problem for the LGBTIQ population, since some 
trans, gender-diverse, and intersex people do not fall within a binary framework of sex 
and/or gender. The limited options are thus exclusionary and will impact the validity of 
the  data.  Moreover,  where  countries  legally  provide  for  gender  markers  outside  the 
binary on official documents (as is the case in Austria70, Germany71, Denmark72, Italy73, 
Malta74, and the Netherlands75), binary options may require respondents to make a false 
statement  about  their  official  legal  status.  In  their  censuses,  Germany76  includes  the 
categories  ‘diverse’  and  ‘not  stated  in  birth  register’,  and  Malta77  includes  an  ‘other’ 

68 Article 5(1)(c) and Recital (39) of the General Data Protection Regulation (GDPR). 
69  Eurostat  (2019),  EU  legislation  on  the  2021  population  and  housing  censuses:  Explanatory  notes, 
Publications Office, Luxembourg, p. 66. 
70  Ministry  of  Finance  (2023),  Changing  Assigned  Sex.  Note  that  these  gender  markers  are  limited  to 
intersex people. 
71 Federal Anti-Discrimination Agency (Antidiskriminierungsstelle des Bundes) (2023),  Male  – Female – 
Diverse: The ‘third option’ and the General Act on Equal Treatment. Whether these gender markers are 
open to non-intersex non-binary people is unclear. 
72 TGEU (2014), Denmark: X in Passports and New Trans Law Works. 
73 Baska, M and Milton, J. (2022), Italian court recognises non-binary person’s gender identity in historic 
first, Pink News. 
74 Human Rights Directorate (2020), Legal Gender Recognition and Bodily Integrity. 
75 Government of the Netherlands (2022), Changing the registration of gender on official documents. 
76  Statistische  Ämter  des  Bundes  und  der  Länder  (2022),  https://www.zensus2022.de/DE/Wer-wird-
befragt/Musterfragebogen_Uebersicht/Fragebogen.html?nn=610864" \l "Haushaltebefragung 
77 National Statistics Office – Malta, Census. 

34 

 
 
 
category for the question on sex, but only insofar as this corresponds to the record on 
the  birth  register.  Austria,  Denmark  and  the  Netherlands  rely  on  administrative  data 
rather  than  conducting  population  censuses.  In  Italy,  however,  the  2022  census  only 
provided for ‘male’ and ‘female’78. 

Overall, censuses rarely collect information about ‘special categories of personal data’ 
such as those related to SOGIESC79. Not including questions on SOGIESC in censuses has 
wider implications, as censuses regularly build the sampling frame for different types of 
surveys. Therefore, it is important to reiterate that data-protection rules do not stand in 
the way of collecting equality data for statistical purposes, and that the principles of data 
protection  do  not  apply  to  anonymous  information  or  to  personal  data  made 
anonymous  in  such  a  manner  that  the  data  subject  is  not  identified  or  is  no  longer 
identifiable80.  So  far,  Malta  is  the  only  EU  Member  State  to  have  included  specific 
questions on sexual orientation and gender identity in its census81. Outside the EU, the 
United Kingdom, Canada and Australia have included a question on gender identity in 
their census, and Nepal, India and Pakistan have revised their censuses to include non-
binary sex or gender categories82. 

Where  there  are  no  specific  SOGIESC  questions,  some  idea  of  the  lived  realities  of 
LGBTIQ people can be gained by using proxy information, for example asking questions 
about: (i) the census respondent’s partner; (ii) the census respondent’s relationship to 
other  household  members;  (iii)  the  sex  of  the  partner/household  members  in  the 
census. Collecting such proxy information has increased in recent years, mainly because 
in an increasing number of countries same-sex couples can register their relationship or 
can  legally  marry.  The  EU  regulations  for  the  2021  census83  make  it  compulsory  for 
Member  States  to  provide  data  on  the  categories  ‘in  an  opposite-sex  marriage  or 
registered partnership’ or ‘in a same-sex marriage or registered partnership’. However, 
the regulations also abolish the distinction between opposite-sex partners and same-
sex partners for the category ‘partners in a consensual union84’, making it more difficult 

78 ISTAT (2022), Populazione e Abitazioni: Documentazione. 
79 Under Article 9 of the GDPR, special categories of personal data comprise ‘personal data revealing racial 
or ethnic origin, political opinions, religious or philosophical beliefs, or trade union membership’, as well 
as ‘genetic data, biometric data for the purpose of uniquely identifying a natural person, data concerning 
health or data concerning a natural person’s sex life or sexual orientation’. 
80 See European Commission (2021), Round table on Equality Data in September 2021 and Principle 4 of 
the Guidance note on the collection and use of equality data based on racial or ethnic origin. 
81 National Statistics Office – Malta, Census. 
82 National Academies of Sciences, Engineering, and Medicine (2022),  Measuring Sex, Gender Identity, 
and Sexual Orientation, The National Academies Press, Washington DC, p. 114. 
83 Regulation (EU) 2017/543. 
84  Eurostat  (2019),  EU  legislation  on  the  2021  population  and  housing  censuses  –  Explanatory  Notes, 
Publications Office, Luxembourg, pp. 66-67. 

35 

 
 
 
to gather information on the number of same-sex couples who are not married or in a 
registered partnership.  

Although data on same-sex partnerships are often used as a proxy for sexual orientation, 
the  information  they  provide  is  limited.  They  do  not  capture  people  who  are  not 
currently in a relationship or who are not willing to disclose – or comfortable disclosing 
–  their  relationship.  They  also  fail  to  capture  respondents  who  are  currently  in  an 
‘opposite-sex’ relationship, which will particularly lead to an undercount of bisexual and 
pansexual  people,  as  well  as  of  trans  people  who  have  not  had  their  gender  legally 
registered. 

Box A 4 – SOGIESC Questions in Malta’s Census 

Q5 

Indicate your registered sex (Mark one circle only) 

●  Male 
● 
●  Other 

Female 

Q7 

Is the gender you identify with the same as your registered sex? 

Yes (Go to Q9) 

● 
●  No 

Q8 

Specify the gender you identify with 

(Open text field) 

Q9 

Which of the following best describes your sexual orientation? (Mark one circle only) 

Straight/Heterosexual 

● 
●  Gay or Lesbian 
● 
Bisexual 
●  Other (Specify) 

Notes for consideration: 

The  census  has  some  limitations.  In  Q5,  the  ‘other’  category  refers  specifically  to 
registered sex, so this question should not be used to indicate the prevalence of non-

36 

 
 
 
binary or intersex people. Q7 asks whether the respondent’s gender differs from their 
registered sex instead of their sex assigned at birth. This question will therefore only 
capture trans respondents who have not had their gender legally recognised. Q9 is 
also limited in the options it presents, for instance by not capturing asexual people. 

3.4.1.2. 

Large-scale surveys 

Although SOGIESC data are still not collected through censuses in most countries, the 
situation appears to be changing for population-based surveys. Large-scale surveys are 
a powerful tool, which make it possible to collect a comprehensive set of equality data. 
General  population  surveys  are  based  on  a  sample  that  is  representative  of  the total 
population, for example the  Labour Force Survey, the EU Survey on Living Conditions 
(EU-SILC), or national health surveys.  

its  composition 

In  a  recently  published  report,  the  Organisation  for  Economic  Cooperation  and 
Development  (OECD)  states  that  it  is  important  to  collect  representative  data  on 
SOGIESC85.  Representativeness  shows  the  extent  to  which  the  characteristics  of  a 
sample  (such  as 
in  relation  to  SOGIESC)  corresponds  to  the 
characteristics  of  the  population  from  which  the  sample  has  been  drawn,  following 
established  rules.  As  stated  in  the  Guidelines  on  improving  the  collection  and  use  of 
equality data, ‘representativeness can be negatively affected if the sample size is too 
small – [that is], when it does not include a sufficient number of persons belonging to a 
targeted population group, or if specific subgroups of the population are systematically 
excluded  from  the  data  collection  in  the  first  place  (because  of  language  difficulties, 
impairments etc.)86.’ 

Several EU and European Economic Area countries have already included questions on 
SOGIESC  in  population-based  surveys87.  Belgium88,  Denmark89,  Finland90,  France91, 

85 OECD (2020), Over the Rainbow? The Road to LGBTI Inclusion, OECD Publishing, Paris, p. 29. 
86  European  Commission  (2018),  Guidelines  on  improving  the  collection  and  use  of  equality  data, 
Publications Office, Luxembourg, p. 21. 
87  A  full  list  of  nationally  representative  surveys  asking  about  sexual  orientation  and  gender  identity 
conducted by public institutions in OECD countries as of 2018 is available in the OECD (2019), Society at a 
Glance  2019:  OECD  Social  Indicators,  OECD  Publishing,  Paris,  pp.  52-56.  Further  information  on  data 
collected by Member States is also detailed in European Commission (2017), Data collection in relation to 
LGBTI People, Publications Office, Luxembourg. 
88 Institute for the Equality of Women and Men (Instituut voor de gelijkheid van vrouwen en mannen) 
(2022), Enquête #YouToo?. 
89 Statens Serum Insitut (2019), Projekt SEXUS. 
90 Finnish Institute for Health and Welfare (2021), School Health Promotion Study. 
91 Institut National D’Études Démographiques (2020), VIRAGE. 

37 

 
 
 
 
Ireland92, the Netherlands93, Sweden94 and Norway95 have conducted surveys which ask 
about  both  sexual  orientation  and  gender  identity.  Germany96,  Italy97,  Spain98  and 
Iceland99 have included questions on sexual orientation. Italy has implemented a pilot 
survey  on  discrimination  which  includes  questions  on  sexual  orientation  and  gender 
identity. Portugal also aims to include questions on sexual orientation, gender identity, 
and sex characteristics in an upcoming survey on gender-based violence100. The inclusion 
of sex characteristics would be particularly important since no general population survey 
asks about whether respondents are intersex/have a variation of sex characteristics101. 

3.4.1.3.  Administrative data 

Administrative data are distinct from data collected solely for statistical purposes (data 
collected  solely  for  statistical  purposes  include  census  data  and  survey  data). 
Administrative  data  are  any  data  collected  by  public  authorities.  Administrative  data 
primarily serve some purpose other than the production of statistics102, such as paying 
taxes, or registering births and deaths.  

Unlike  data  from  surveys,  administrative  data  often  cover  entire  populations  (e.g.  all 
taxpayers), and they might reveal information that otherwise would never have been 
collected.  Administrative  data  may  be  collected  more  often  than  data  collected  for 
statistical  purposes.  For  example,  on  the  situation  of  LGBTIQ  people  in  Europe,  it  is 
common to find administrative data from records on: (i) the number of people entering 
a legally recognised same-sex partnership (whether marriage or another status); and (ii) 
the  number  of  individuals  granted  permission  to  change  the  record  of  their  sex  as 
assigned by birth.  

While  they  can  be  useful,  administrative  data  present  many  challenges  and  can  be 
problematic as a source of SOGIESC data. Efforts to collect administrative data are not 
coordinated and tracked in the same way as efforts to collect statistical data. In some 

92 Central Statistics Office (2019), General Household Survey. 
93 Statistics Netherlands (2021), Safety Monitor. 
94 Public Health Agency of Sweden (2022), Public Health Survey. 
95 Statistics Norway (2021), Quality of Life in Norway. 
96 German Institute for Economic Research (DIW Berlin) (2022), Socio-Economic Panel. 
97  Istituto  Nazionale  di  Statistica  (2015),  Survey  on  discriminations  by  gender,  sexual  orientation  and 
ethnic origin. 
98 Instituto Nacional de Estadística (2006), Health and Sexual Behaviour Survey. 
99 Directorate of Health (2022), Health and Wellbeing Study. 
100 OHCHR (2018), Report of the Independent Expert on protection against violence and discrimination 
based on sexual orientation and gender identity: Responses by the Portuguese Authorities, p. 3. 
101 OECD (2019), Society at a Glance 2019: OECD Social Indicators, OECD Publishing, Paris, p. 15. 
102  European  Commission  (2016),  European  Handbook  on  Equality  Data  (2016  revision),  Publications 
Office, Luxembourg, Section 2.1.1. 

38 

 
 
 
cases, data at group level are not available at all103. The variables may also be limited, 
for instance where data on legal gender are collected but data on gender identity are 
not. In many cases, SOGIESC data are being collected without there being a legal ground 
or  rationale  to  do  so  (for  example,  when  applying  for  a  library  card),  which  may  be 
perceived as overly invasive and, in some cases, deter LGBTIQ people from accessing a 
particular service104.  

3.4.1.4.  Use of proxy variables 

A proxy variable is an indicator that is used to give an approximate representation of a 
phenomenon, related to the variable, but not directly measurable in a more objective 
way.  For  a  variable  to  be  a  valid  proxy,  it  must  be  closely  related  to  the  variable  it 
replaces. 

The OHCHR’s Human Rights-Based Approach to Data states that populations must be 
self-identifying, meaning that population parameters cannot be imposed by an outside 
party  or  assigned  through  imputation  or  proxy.  The  primary  concern  with  proxy 
reporting is that the resulting data will not reflect how a person would have identified if 
they could have responded for themselves105. Therefore, collecting information on the 
self-identification  of  individuals  in  terms  of  SOGIESC  takes  precedence  over  proxy 
information.  

Many Member States regularly collect population or census data that can be used as an 
imperfect proxy for SOGIESC data (for example in questions that ask about the sex of 
the  respondent  and  their  partner  as  a  proxy  for  LGBTIQ  relationships).  This  type  of 
information is likely to be inaccurate for several reasons. For example, it fails to account 
for  trans  people  who  have  not  legally  registered  their  gender,  or  for  bisexual  or 
pansexual people in a relationship with someone of a different sex. Such information 
should therefore only be used in the absence of any other means of collecting SOGIESC 
data. 

The use of proxy reporting can be necessary in some cases (such as when collecting data 
on infants) but is likely to result in ‘undercounts’. For example, if statistics are based only 
on prenatal screening (as a proxy for individuals with a variation of sex characteristics), 
they will miss those individuals whose variation of sex characteristics is revealed later in 

103 For instance, in health databases, intersex people are not specifically defined as such in health terms 
for statistical analysis, and are therefore not included in databases. See: Republic of Slovenia, Advocate 
of the Principle of Equality (2022), Special report. The Situation of Intersex People in Medical Procedures, 
Advocate of the Principle of Equality, Ljubljana. 
104  Ashley,  F.  (2021),  Recommendations  for  Institutional  and  Governmental  Management  of  Gender 
Information. New York University Review of Law & Social Change, 44(4):489-528. pp. 504, 514-515. 
105 National Academies of Sciences, Engineering, and Medicine (2022), Measuring Sex, Gender Identity, 
and Sexual Orientation, The National Academies Press, Washington DC, p. 50. 

39 

 
 
 
life. Similarly, standard binary measures of sex are an inadequate proxy for the primary 
measurement of gender and sex characteristics, especially among sexually diverse and 
gender-diverse  populations106.  If  data  on  the  number  of  changes  in  legal  gender 
registration are used as a proxy for the size of the trans population (or for the proportion 
of the population that is trans), this can lead to undercounts since not all trans people 
can or wish to change their legal gender registration. It could also lead to inaccuracies, 
since it may include intersex people who do not identify as trans. Weighting based on 
estimates from other countries on the proportion of trans people seeking legal gender 
recognition  (LGR)  could  improve  the  reliability  of  proxy  data.  However,  this  is  only 
possible if the countries have comparable legislation, since legal hurdles can significantly 
impact the number of people seeking LGR. 

Box A 5 – Use of proxies in the EU-SILC household survey 

The EU-SILC household survey contains a question about sex and a question about the 
marital status of all household members166. A note about same-sex couples is made to 
clarify that registered partnerships also count as a marital status. The combination of 
both  questions  could  assess  the  prevalence  of  same-sex  couples,  although  this 
information  will  only  capture  same-sex  couples  who  are  married  or  in  a  registered 
partnership. 

[Sex] (question repeats for all household members) 

●  Male  
● 

Female  

[NOTE: All current household members aged 16 and over.]  

[Marital Status] (question repeats for all household members) 

●  Never married  
●  Married  
● 
Separated  
●  Widowed 
●  Divorced  

[NOTE: All current household members aged 16 and over. Some countries have a legal 
framework  for  registering  partnerships  (in  most  countries  these  are  same-sex 
partnerships, and they have a legal status parallel to married couples). This information 
must  also  be  treated  in  a  harmonised  way  and  it  is  proposed  to  treat  these  legally 
recognised  partners  as  married  and  to  classify  them  under  code  2  when  the 
relationship still exists, or as 3-5 as appropriate (legal separation or death of one of the 
partners or so on).]  

106 National Academies of Sciences, Engineering, and Medicine (2022), Measuring Sex, Gender Identity, 
and Sexual Orientation, The National Academies Press, Washington DC, p. 44. 

40 

 
 
 
 
 
Eurostat  and  Member  States  often  do  not  disaggregate  these  data  to  estimate  the 
prevalence  of  same-sex  couples,  even  though  the  information  is  available.  In  the 
absence of better data being available, such disaggregation can be a useful tool. 

3.4.2. 

Guidance 

Member States and relevant institutions and bodies involved in – or responsible for – 
collecting data based on SOGIESC are encouraged to take information on SOGIESC into 
consideration  in  all  policies.  The  bullet  points  below  set  out  in  more  detail  some 
considerations that Member States should bear in mind. 

● 

If  censuses  do  not  provide  information  on  SOGIESC,  sample  surveys  should 
complement  the  censuses  and  include  questions/modules  capturing  SOGIESC 
characteristics on a regular basis. 

●  When  developing  surveys  or  when  collecting  data  as  part  of  the  European 
Statistical  System through the  Labour  Force  Survey  and  EU-SILC,  Member  States 
should, where it is appropriate, systematically incorporate information based on 
SOGIESC.  Adding  optional  questions  on  self-identification  is  also  a  possibility. 
Information  based  on  SOGIESC  could  also  be  incorporated  by  developing  and 
running  thematic  survey  modules  to  cover,  for  example:  (i)  experiences  of 
discrimination  in  different  areas  of  life;  (ii)  bias-motivated  harassment  and 
violence; (iii) rights awareness; and (iv) reporting incidents of discrimination.  

● 

To  capture  intersecting  inequalities,  Member  States  should  introduce  individual 
variables and survey questions that specifically relate to measuring inequalities and 
perceived discrimination on multiple grounds, including SOGIESC, in different areas 
of life. 

●  Where  relevant  and  possible,  Member  States  should  avoid  restricting  their 
collection  of  SOGIESC  data  to  adults  only.  Although  minors  are  afforded  greater 
protection under several of the major data-privacy laws (including the GDPR), data 
from  European  surveys  prove  the  importance  of  also  collecting  data  on  people 
younger  than  18.  For  example,  the  FRA’s  LGBTIQ  II  survey  collected  data  from 
young people aged 15-17107. Although the GDPR recommendation for the age of 
consent to responding to surveys is 16, Member States may enact laws that lower 
the age of consent to 13 (but not under 13), according to Article 8(1)108.  

107 EU Agency for Fundamental Rights (2020),  A long way to go for LGBTI equality, Publications Office, 
Luxembourg.  
108 Article 8(1) of the General Data Protection Regulation. 

41 

 
 
 
 
●  Member  States  should  consider  using  a  question  on  minority-group  affiliation 
when SOGIESC aspects cannot be measured directly in a survey. If it is impossible 
to add at least four additional questions (asking about sexual orientation, gender 
identity, gender expression, and/or variations of sex characteristics), an alternative 
but less exact approach can be found  by asking the respondents to what extent 
they are part of other minority groups, providing a list of relevant examples which 
includes being LGBTIQ. An explanation or definition of what a minority group is (in 
terms of SOGIESC) should be provided. The definitions provided in the glossary in 
the  annex  of  this  guidance  document  can  serve  as  a  starting  point  for  such  an 
explanation. 

●  Member States should increase the number of people who otherwise would not be 
adequately represented in the survey samples due to their small numbers in the 
general population by using booster samples. 

● 

If there are too few respondents in a category for meaningful analysis (such as a 
limited  number  of  non-binary  respondents  compared  to  men  and  women), 
Member States should document the fact of having ‘unreliably’ small sample/cell 
size in technical reports and state why it is not possible to include certain categories 
in  the  main  analysis.  This  increases  visibility  and  prevents  overly  simplistic 
interpretations. 

●  Member States should promote the inclusion of SOGIESC in longitudinal surveys 
(surveys which repeatedly collect data on the same individuals over a longer period, 
e.g. panel surveys), to make it possible to assess individual change over time. 

●  When the purpose for collecting special categories of personal data is not clear, it 
is recommended that Member States state the legal ground and purpose for which 
the data are being collected. As stated in Article 6 of the General Data Protection 
Regulation (GDPR), the legal bases of data collection are consent; contract; legal 
obligation;  vital  interests;  public  task;  or  legitimate  interest.  Overly  invasive 
questions that do not meet any of the above-mentioned purposes could increase 
LGBTIQ exclusion by dissuading LGBTIQ people from accessing particular services. 
The data collected should be necessary, proportionate and follow the overarching 
principle of doing no-harm. Therefore, if there is no legal ground to collect SOGIESC 
in 
data, 
administrative data. 

is  recommended  to  refrain  from  collecting  data  on  SOGIESC 

it 

●  Often the gender of a person is collected simply to make it possible to address this 
person in a correct manner. In these cases, ask the person for the correct salutation 
instead, including gender-neutral options. In this way, the person can inform you 
about  their  preferred  salutations  without  sharing  personal  information.  For 

42 

 
 
example, a question could be: ‘Which salutation do you prefer? Mrs, Mr, Mx or No 
salutation, just my first name’. 

●  Member  States  should  use  proxy  variables/categories  in  existing  data  sources 

where the human rights-based principle of self-identification cannot be applied. 

● 

For household surveys, in which one household member is providing information 
on  other  household  members  (a  so-called  proxy  informant),  the  collection  of 
SOGIESC information should be avoided to the extent possible109, as it relates to 
sensitive  data  which  requires  the  consent  of  the  intended  person.  Therefore, 
SOGIESC questions should be asked only to the sampled target respondent. Non-
statistical organisations and other research institutions may apply, as appropriate, 
their established practices for substituting households or respondents who refuse 
to take part in the interview or are unavailable. 

●  Data collection should enable respondents to self-identify whenever possible, and 
any  proxy  reporting  should  reflect  what  is  known  about  how  a  person  self-
identifies. 

●  All data-collection activities should require well-informed consent from potential 
respondents,  with  no  penalty  for  those  who  opt  out  of  sharing  personal 
information about themselves or other household members.  

It should be clearly stated that data gathered through  a proxy may not reflect how a 
person would have identified if they had been given the opportunity to self-identify and 
is likely to result in undercounts for marginalised populations. This limitation should be 
acknowledged in any analysis of such data110. 

3.5.  Mainstream an intersectional approach 

in the collection and use of SOGIESC 
data 

‘Discrimination is often multidimensional and only an intersectional approach can pave 
the way to sustainable and respectful changes in society.’  

109 Survey module to measure experiences of discrimination developed by the Praia Group Task Team on 
Non-discrimination and Equality. 
110 National Academies of Sciences, Engineering, and Medicine (2022), Measuring Sex, Gender Identity, 
and Sexual Orientation, The National Academies Press, Washington DC, p. 50. 

43 

 
 
 
EU LGBTIQ equality strategy 2020-2025  

National  equality  laws  in  the  EU  rarely  include  provisions  that  relate  to  multiple  or 
intersectional  discrimination.  Where  they  do  include  such  provisions,  there  are 
discrepancies between countries, as the European network of legal experts on gender 
equality  and  non-discrimination  notes111.  Regardless  of  legal  arrangements  and 
provisions, research data and evidence highlight that intersectional discrimination is a 
recurrent reality for many people across the EU.  

For  example,  survey  data  from  the  FRA  show  that  people  experience  discrimination 
based  on  a  variety  of  grounds  and  as  a  combination  of  grounds,  such  as  age  and 
ethnicity,  or  religion  and  ethnicity (including  migration background)112.  Findings  from 
the  FRA’s  LGBTI  Survey  II  show  that  sexual  orientation  was  named  as  an  additional 
ground of discrimination experienced by 60% of intersex and 46% of trans people; while 
46%  of  bisexual  women  and  29%  of  lesbian  women  mentioned  sex  as  an  additional 
ground of discrimination they had experienced. Out of those LGBTI respondents who 
perceived  themselves  as  an  ethnic  minority  (including  migrants),  35%  reported 
discrimination  occurring  due  to  ethnic  origin  or  migration  background.  Of  those  who 
perceived themselves as belonging to a religious minority, 28% mentioned religion or 
belief.  Of  those  who  perceived  themselves  as  a  minority  in  terms  of  disability,  33% 
mentioned disability as an additional ground for the last incident of harassment they 
had  experienced.  Of  intersex  respondents,  41%  also  mentioned  gender  identity  and 
expression as an additional ground of discrimination that they had experienced113. 

All recent EU equality strategies and action plans address intersectionality by calling for 
actions to tackle intersecting and multiple forms of discrimination. In the EU anti-racism 
action plan, the European Commission encourages Member States to ‘swiftly reach an 
agreement on the 2008 Commission proposal to implement equal treatment between 
persons  irrespective  of  religion  or  belief,  disability,  age  or  sexual  orientation114’.  In 
addition,  practitioners  in  the  field  recognise  that  addressing  discrimination  from  the 

111 European network of legal experts in gender equality and non-discrimination (2020), A comparative 
analysis of non-discrimination law 2019, Publications Office, Luxembourg, pp. 36-37. 
112 FRA (2021), Equality in the EU 20 years on from the initial implementation of the equality directives, 
Publications Office, Brussels, p. 42. 
113  FRA  (2020),  A  long  way  to  go  for  LGBTI  equality,  Publications  Office,  Luxembourg,  p.  45.  For  more 
intersectional analysis from findings of the FRA’s second LGBTI survey on LGBTI people in the EU and North 
Macedonia  and  Serbia,  see:  Calderon-Cifuentes,  PA.  (2021),  Trans  Discrimination  in  Europe.  A  TGEU 
analysis of the FRA LGBTI Survey 2019; ILGA Europe, EuroCentralAsian Lesbian Community (EL*C) (2022), 
Intersections,  Lesbian  Briefing,  and  ILGA-Europe  and  IGLYO  (2022),  Intersections,  Youth  Briefing. 
Forthcoming briefings will address the intersectional experiences of intersex people, religious and ethnic 
minorities, older LGBTI people, trans people, and others. 
114  European  Commission  (2020),  A  Union  of  equality  –  EU  anti-racism  action  plan  2020-2025, 
COM(2020) 565 final, Brussels, p. 6. 

44 

 
 
 
perspective  of  a  single  ground  fails  to  adequately  tackle  the  different  ways  in  which 
unequal treatment can manifest itself115. 

Box A 6 – Multiple and intersectional discrimination 

‘Multiple  discrimination’  describes  discrimination  that  takes  place  on  the  basis  of 
several grounds operating separately. 

‘Intersectional discrimination’ describes a situation in which several grounds operate 
and interact with each other at the same time in such a way that they are inseparable 
and produce specific types of discrimination116. 

3.5.1. 

Rationale 

The  complexity  of  LGBTIQ  identities  and  experiences  cannot  be  captured  by  a  single 
ground,  as  they  encompass  multiple,  intersecting  characteristics  that  should  be 
recognised117.  Understanding  intersectional  experiences  is  therefore  crucial  to  the 
design  of  effective  measures  and  policies  to  adequately  capture  situations  in  which 
different grounds of discrimination intersect or act in combination with each another.  

3.5.2. 

Guidance 

Member States and relevant institutions/bodies involved in or responsible for collecting 
data  based  on  SOGIESC  are  encouraged  to  take  an  intersectional  approach  in  the 
collection and use of SOGIESC data. They are also encouraged to involve communities in 
the process. The bullet points below contain further suggestions for Member States. 

●  Member  States  and  relevant  institutions/bodies should  develop  strategies  to:  (i) 
adequately  capture  situations  in  which  different  grounds  of  discrimination 
intersect or act in combination with each another; and (ii) take into consideration 
multiple and intersectional discrimination in data analysis. To this end, EU Member 
States should use a comprehensive set of tools to collect equality data, including 
large-scale quantitative surveys covering different population groups and grounds 
of discrimination118. 

115 FRA (2017), Fundamental Rights Report 2017, Publications Office, Luxembourg, p. 58. 
116 FRA and European Court of Human Rights (2018),  Handbook on European non-discrimination law – 
2018 edition, Publications Office, Luxembourg, p. 59. 
117 See also EIGE (2022), Intersectionality. 
118 FRA (2021), Equality in the EU 20 years on from the initial implementation of the Equality Directives, 
Publications Office, Brussels, p. 20. 

45 

 
 
 
●  Member States and relevant institutions/bodies should consider intersections both 
within the LGBTIQ community (e.g. a trans lesbian woman may experience specific 
discrimination separate from that faced by cisgender lesbians or trans people who 
are not lesbians), and with non-SOGIESC grounds of discrimination (age, ethnicity, 
disability, religion etc.). 

●  Member States and relevant institutions/bodies should use a comprehensive set of 
tools to collect equality data119, including large-scale quantitative surveys covering 
different population groups and different grounds of discrimination. 

●  Member  States  and  relevant 

institutions/bodies  should 

incorporate  the 
measurement of multiple and intersectional discrimination into all existing systems 
for collecting data. For example, data collected on disability should ideally include 
information  on  SOGIESC  and  other  potential  characteristics  that  might  lead  to  a 
greater risk of discrimination based on multiple factors or intersecting inequalities.  

● 

through 

collection 

surveys,  Member  States  and 

For  data 
relevant 
institutions/bodies should ensure a sufficient net sample size to make possible the 
further  disaggregation  of  data  and  intersectional  analysis.  To  achieve  this,  they 
should  consider  using  a  suitable  sampling  method.  Different  sampling  strategies 
can  be  applied  to  obtain  an  adequate  sample  size  that  fully  represents  the 
variations within the LGBTIQ target population. 

3.6. 

Provide  sufficient  budget  for  regular 
surveys  to  collect  equality  data  on 
SOGIESC 

3.6.1. 

Rationale 

Governments  should  ensure  that  data  on  equality  is  collected  regularly  to  monitor 
compliance with commitments under EU law120, even when it is not possible to collect 

119  For  more  information,  please  consider  the  European  Handbook  on  Equality  Data,  as  well  as  the 
Guidelines on improving the collection and use of equality data. 
120  As  mentioned  in  the  European  Handbook  on  Equality  Data,  the  Employment  Equality  Directive 
”expressly allow[s] – but do[es] not require – the Member States to maintain or introduce rules that allow 
discrimination to be established by ‘any means including on the basis of statistical evidence’“. Moreover, 
Governments  themselves  have  on  several  occasions  recognised  the  need  to  collect  equality  data 
(Copenhagen  Declaration  on  Social  Development  and  Programme  of  Action  of  the  World  Summit  for 

46 

 
 
 
 
administrative data. In these cases, sufficient budgetary resources should be allocated 
at  the  national/regional  level  to  collect  equality  data  on  SOGIESC  through  regular 
national/regional surveys conducted by a competent authority.  

3.6.2. 

Guidance 

In the absence of regular collection of SOGIESC data through administrative sources 
or  surveys,  Member  States  should  provide  sufficient  budgetary  resources  to 
collect such data every 4-5 years through a comprehensive national survey. 

The survey should achieve the four goals set out in the bullet points below. 

■ 

■ 

■ 

It should reach out to all LGBTIQ groups and actively involve groups that work 
specifically  with  –  and  for  –  specific  groups  that  fall  under  the  LGBTIQ 
category. It should also reach out to and involve multiply marginalised groups 
such  as  disabled  LGBTIQ  people,  LGBTIQ  people  of  colour,  and  LGBTIQ  sex 
workers. 

It should aim to represent the diversity of this community and aim to cover 
populations  and  groups  defined  as  ‘hard  to  reach’,  including  those  living  in 
poverty, homeless people, sex workers, migrants, asylum seekers and people 
who are not ‘out’ in their everyday life. This would also mean translating the 
survey  tool  (questionnaire  and  other  fieldwork  material)  into  languages 
relevant  to  these  hard-to-reach  groups,  as  well  as  involving  civil  society 
organisations121. 

analysis 

It should be based on a sample size large enough to make it possible to both 
conduct  more  detailed  data 
geographic 
differences/disparities including intersectional disparities. This means that the 
sample size should be large enough to make it possible to further analyse the 
data  on:  geographical  distribution;  age;  racial  or  ethnic  origin;  disability; 
religion; sex assigned at birth; sexual orientation; gender identity/expression; 
sex characteristics; etc.  

identify 

and 

Social  Development  of  19  April  1995,  A/CONF.166/9;  Durban  Declaration  and  Plan  of  Action;  Vienna 
Declaration  and  Programme  of  Action  of  12  July  1993,  A/CONF.157/23;  World  Programme  of  Action 
concerning  Disabled  Persons;  Standard  Rules  on  the  Equalisation  of  Opportunities  for  Persons  with 
Disabilities). 

121 UNECE (2020), Poverty Measurement: Guide to Data Disaggregation, United Nations, New York and 
Geneva.  

47 

 
 
 
 
■ 

It should be able to produce reliable and valid data for all LGBTIQ groups, i.e. 
by  using  the  up-to-date  survey  measurement  guidelines  and  choosing  a 
sample design that also reaches hard-to-reach populations. 

Regular surveys that collect equality data related to SOGIESC can be conducted as 
an  independent  survey  with  a  specific  focus  on  populations  that  self-identify  as 
LGBTIQ, or as part of a general equality survey (i.e. a survey that also addresses 
other protected grounds). This can be done at the national (and, where relevant, 
regional)  level  by  a  competent  authority,  statistical  institute,  equality  body  or 
research organisation with the relevant capacity and expertise to conduct research. 

3.7. 

Facilitate  the  effective  use  of  SOGIESC 
equality  data 
strengthen  and 
to 
improve LGBTIQ equality 

3.7.1. 

Rationale 

Reliable,  valid  and  comparable  SOGIESC  data  are  a  prerequisite  for  evidence-based 
policies to foster equality and non-discrimination at the EU, national, and regional levels. 
SOGIESC data are seen as an essential element of all phases of a policy cycle to improve 
equality for LGBTIQ people. These SOGIESC data should therefore be systematically used 
for  the  development,  implementation,  and  monitoring  of  both  dedicated  LGBTIQ 
policies/measures and wider equality frameworks at EU/national level. 

The  US  National  Science  and  Technology  Council  provides  a  detailed  list  of  potential 
research questions that can be addressed with SOGIESC data in the areas of healthcare, 
housing, education, economic security, safety, and justice122. Some illustrative examples 
are set out in the three bullet points below. 

● 

‘What is the prevalence of homelessness among LGBTQI+ adults? How does this 
compare to their non-LGBTQI+ peers?123’ 

122 Subcommittee on Sexual Orientation, Gender Identity, and Variations in Sex Characteristics (SOGI) Data 
and  Subcommittee  on  Equitable  Data  of  the  National  Science  and  Technology  Council  (2023),  Federal 
Evidence Agenda on LGBTQI+ Equity, United States Government, pp. 18-33. 
123 Subcommittee on Sexual Orientation, Gender Identity, and Variations in Sex Characteristics (SOGI) Data 
and  Subcommittee  on  Equitable  Data  of  the  National  Science  and  Technology  Council  (2023),  Federal 
Evidence Agenda on LGBTQI+ Equity, United States Government, p. 23. 

48 

 
 
 
● 

● 

‘How  prevalent  are  various  forms  of  job-related  discrimination,  harassment,  or 
retaliation  against  LGBTQI+  people,  such  as discrimination  in  hiring,  in wages,  in 
equal employment opportunity, in fair treatment, in promotion or advancement, 
or in termination?124’ 

‘What  institutional  contexts,  policies,  or  practices  promote  a  positive  academic 
environment  and  contribute  to  higher  rates  of  LGBTQI+  student  retention  and 
graduation?  What  individual-level,  family-level,  or  community-level  protective 
factors do LGBTQI+ people employ that help them to succeed in education and the 
workforce?125’ 

The questions also provide examples  of how to capture intersectional discrimination, 
such  as  the  question  ‘What  barriers  do  LGBTQI+  minors  and  LGBTQI+  adults  with 
disabilities  face 
in  accessing  health  services  that  require  participation  from 
guardians?126’.  By  answering  these  questions,  SOGIESC  data  can play  a  crucial  role  in 
policy development and evaluation.  

3.7.2. 

Guidance 

To facilitate the effective use of SOGIESC equality data, Member States and the relevant 
institutions and actors involved in or responsible for the collection of SOGIESC data are 
encouraged to take the actions set out in the bullet points below. 

● 

● 

They should use SOGIESC equality data to measure both: (i) the impact of LGBTIQ-
specific  laws  and  policies;  and  (ii)  the  impact  of  wider  equality  and  non-
discrimination policies and measures on LGBTIQ people.  

They should use SOGIESC equality data to: (i) report on progress towards LGBTIQ 
equality  at  the  national 
level;  and  (ii)  support  reporting  efforts  on  the 
implementation of the EU’s LGBTIQ equality strategy 2020-2025 and other relevant 

124 Subcommittee on Sexual Orientation, Gender Identity, and Variations in Sex Characteristics (SOGI) Data 
and  Subcommittee  on  Equitable  Data  of  the  National  Science  and  Technology  Council  (2023),  Federal 
Evidence Agenda on LGBTQI+ Equity, United States Government, p. 25. 
125 Subcommittee on Sexual Orientation, Gender Identity, and Variations in Sex Characteristics (SOGI) Data 
and  Subcommittee  on  Equitable  Data  of  the  National  Science  and  Technology  Council  (2023),  Federal 
Evidence Agenda on LGBTQI+ Equity, United States Government, p. 26. 
126 Subcommittee on Sexual Orientation, Gender Identity, and Variations in Sex Characteristics (SOGI) Data 
and  Subcommittee  on  Equitable  Data  of  the  National  Science  and  Technology  Council  (2023),  Federal 
Evidence Agenda on LGBTQI+ Equity, United States Government, p. 22. 

49 

 
 
 
instruments,  such  as  other  EU  equality  strategies127  and  the  European  Pillar  of 
Social Rights. 

They  should  use  SOGIESC  equality  data  and  indicators  to  inform  processes  and 
policies at the wider European and UN level. SOGIESC data could inform countries: 
(i) when reporting on relevant recommendations made by the Council of Europe128; 
(ii) when reporting on progress towards achieving the 2030 Agenda with the UN’s 
Sustainable  Development  Goals  (SDGs)129;  (iii)  when  engaging  with  other 
international human-rights monitoring mechanisms, such as UN treaty bodies and 
special procedures (e.g. the independent expert on protection against violence and 
discrimination  based  on  sexual  orientation  and  gender  identity);  or  (iv)  when 
following  up  on  recommendations  made  during  the  UN’s  Universal  Periodic 
Reviews. 

They  should  use  SOGIESC  data  to  inform  all  stages  of  policy  development.  This 
could  start  with:  (i)  using  SOGIESC  data  as  a  baseline  for  developing policies;  (ii) 
designing indicators for monitoring purposes; and (iii) setting benchmarks. Later on 
in  policy  development  they  should  use  SOGIESC  data  to  inform  mid-term 
evaluations. And towards the later stages of policy  implementation, they should 
use SOGIESC data to populate indicators, assess the effective implementation of 
measures, assess the outcomes of these measures, and monitor trends.  

They  should  ensure  data  can  be  disaggregated  by  SOGIESC  and  other  relevant 
characteristics (age, disability, ethnic or racial origin, religion, and socioeconomic 
status)  to  reflect,  analyse  and  report  on  differences  in  experiences  in  line  with 
Guideline No 3.5 of this guidance document on taking an intersectional approach 
in the collection and use of data. 

They  should  use  illustrative  examples,  such  as  anonymised  quotes  and  personal 
stories  collected  during  research  to  help  contextualise  research  findings  and 
increase the impact and outreach of the communication about the results. 

● 

● 

● 

● 

127 Promoting a Union of equality, the European Commission has adopted several policy instruments in 
addition to the LGBTIQ equality strategy 2020–2025, including: the EU anti-racism action plan 2020–2025; 
the EU Roma strategic framework for equality, inclusion and participation 2020–2030; the action plan on 
integration and inclusion 2021–2027; the EU gender equality strategy 2020–2025; the European Pillar of 
Social Rights action plan; and the strategy for the rights of persons with disabilities 2021–2030. 
128  For  example,  on  the  Committee  of  Ministers’  Recommendation  CM/Rec(2010)5  on  measures  to 
combat discrimination on grounds of sexual orientation or gender identity; or the  Council of Europe’s 
ECRI’s Country Monitoring. For more information, see the thematic page of the Sexual Orientation and 
Gender Identity (SOGI) Unit. 
129 Target 17.18 of the SDGs requires States to ‘increase significantly the availability of high-quality, timely 
and  reliable  data’,  disaggregated  by  both  gender  and  ‘and  other  characteristics  relevant  in  national 
contexts’. 

50 

 
 
 
● 

● 

● 

● 

● 

They  should  ensure  the  timely  dissemination  of  the  collected  data  and  make  it 
freely 
interested 
online 
communities/researchers/policy makers. 

accessible 

offline 

both 

and 

to 

They  should  present  the  data  in  accessible  and  understandable  language  and 
formats,  making  it  possible  for  different  stakeholders  and  groups  to  use  (for 
example,  by  LGBTIQ-representative  organisations  in  their  advocacy  work,  or  by 
equality bodies in their monitoring and reporting on discrimination issues). 

They should tailor the presentation of the data depending on the audience (e.g. 
policy  makers,  experts,  data  specialists,  the  media)  and  ensure  it  is  properly 
contextualised.  

They should ensure, where appropriate, that explanations and interpretations of 
the data are provided to avoid any misinterpretations and misuse of the data or of 
the conclusions drawn. 

They  should  document  the  data  collection  and  all  metadata  according  to  high 
professional standards. They should draw up a technical report to document: (i) the 
survey methodology; (ii) the fieldwork (including the response rate achieved); (iii) 
the data-processing activities; and (iv) any relevant contextual information (such as 
population data disaggregated by relevant socio-demographic characteristics). The 
use and reporting of LGBTIQ data should always be contextualised with caveats and 
by providing documentation explaining how the data were collected. 

51 

 
 
4. 

How to collect information on 
SOGIESC 

As stated in the  OHCHR’s Human Rights-Based Approach to Data, any data-collection 
effort should include the means for free, active, and meaningful participation of relevant 
stakeholders,  in  particular the  most  marginalised population  groups.  When  collecting 
data on SOGIESC, it is important to use community-appropriate terminology and ensure 
that data collection is culturally grounded130. Data-collection efforts of SOGIESC aspects 
should  be  contextualised  to  explain  cultural  and  historical  factors.  Definitions  and 
translations  should  be  developed  in  close  consultation  with  LGBTIQ  civil-society 
local  cultural  terminology131.  Wherever 
organisations,  and  with  attention  to 
appropriate,  civil  society  organisations,  national  human-rights  institutions,  equality 
bodies,  and  other  relevant  stakeholders  should  provide  relevant  perspectives  and 
information (if they are qualified or in a position to represent the group’s interests). It is 
also recommended to work closely with survey experts and civil-society organisations to 
develop the data-collection methodology. This is especially important: (i) in relation to 
the wording of the relevant questions and possible response categories; and (ii) when 
considering the degree of translatability of SOGIESC concepts in the respective Member 
State, while abiding by the principles of not doing harm.  

One approach to achieve more clarity on underlying concepts in a survey across cultures 
and  languages  is  to  include  ‘info  buttons’132.  These  could  be  helpful  to  give  further 
information on the question or response categories. However, as many people will not 
open  an  info  button,  these  should  not  be  used  for  important  information.  Adding 
explanatory text via info buttons gives more insights and examples about the terms in 
question,  ultimately  ensuring  a  greater  level  of  comprehension  by  the  survey 
respondents, making the survey more reliable. 

When collecting SOGIESC data, it is crucial not to conflate sexual orientation, gender 
identity,  gender  expression,  and  sex  characteristics.  When  asked  how  they  identify, 
respondents should always have the option to express various aspects of their identity 
and experience (for instance, an asexual, trans woman should have the ability to select 

130 National Academies of Sciences, Engineering, and Medicine (2022), Measuring Sex, Gender Identity, 
and Sexual Orientation, The National Academies Press, Washington DC, p. 66. 
131  For  instance,  the  FRA’s  2019  LGBTI  Survey  underwent  a  four-phase  translation  process,  in  which 
translators  aimed  for  conceptual  equivalence  rather  than  word-for-word  translation.  The  translations 
were checked by LGBTIQ country experts. See EU Agency for Fundamental Rights (2020), A long way to 
go for LGBTI equality. Technical report, Publications Office, Luxembourg, pp. 18-19. 
132  An  ’info  button‘  is  a  hover-over  box  in  a  web  page  providing  extra  information  (for  example,  the 
definition of a term).  

52 

 
 
 
all of these in a questionnaire). Where routing133 is applied based on identity categories, 
respondents with multiple identities should receive all relevant questions. 

The following sections present practical guidance on how to collect data on sex, gender 
(identity),  gender  expression,  sexual  orientation  and  sex  characteristics,  including 
examples from past surveys to illustrate possible approaches. However, these examples 
are not intended to showcase best practice to be directly adopted, as is highlighted in 
the notes for consideration under each example. 

4.1. 

How to collect data on sexual 
orientation 

4.1.1. 

Rationale  

Sexual  orientation:  ‘How  one  finds  oneself  feeling  drawn  (or  not  drawn)  to  another 
person in a sexual and/or romantic way134’. ‘This encompasses emotional, affectional, 
and sexual attraction to, and intimate and sexual relations with, individuals of a different 
gender or the same gender or more than one gender135’. 

Research  shows  that  people  are  willing  to  report  their  sexual  orientation  in  survey 
research136.  There  appear  to  be  several  factors  that  can  positively  influence  this 
willingness  and  increase  response  rates.  A  key  factor  is  respondents’  trust  in  the 
confidentiality  of  the responses137.  Avoiding  stigmatising wording  and providing  clear 
definitions also has a positive impact on response rates138, 139. Short, simple questions 
and fewer answer categories appear to reduce non-response rates, whereas complex 
questions, especially those seeking to combine several dimensions, are more likely to be 

133 A routing applies when a survey respondents choose to answer a survey with a particular response 
that the survey then asks them other questions pertaining to that response which it would not have asked 
other respondents who had chosen a different answer. 
134 European Parliament (2020), Glossary of Sensitive Language for Internal and External Communications, 
p. 12. 
135  International  Commission  of  Jurists  (2007),  Yogyakarta  principles:  principles  on  the  application  of 
international human rights law in relation to sexual orientation and gender identity, p. 8. 
136 European Commission (2015), Special Eurobarometer 437: Discrimination in the EU in 2015, European 
Union, p. 99. 
137 Saewyc, E. M. et al. (2004). Measuring sexual orientation in adolescent health surveys: Evaluation of 
eight school-based surveys. Journal of Adolescent Health, 35(4), pp. 345.e.2-345.e15. 
138 Hayes, J. et al. (2012). Prevalence of Same-Sex Behaviour and Orientation in England: Results from a 
National Survey. Archives of Sexual Behaviour, 41(3), pp. 631-639. 
139 Saewyc, E. M. et al. (2004). Measuring sexual orientation in adolescent health surveys: Evaluation of 
eight school-based surveys. Journal of Adolescent Health, 35(4), pp. 345.e.2-345.e15. 

53 

 
 
 
skipped.  Question  placement  will  also  have  an  impact.  Generally,  sensitive  questions 
have higher non-response rates if they are placed directly at the beginning of a survey, 
and non-response rates tend to increase overall for questions the later they are placed 
in the survey. Questions placed directly after a sensitive question, such as on sexual or 
criminal behaviour, are also more likely to be skipped140. 

In different cultures and contexts, various concepts and labels exist for describing one’s 
sexual and/or romantic orientation, but concepts such as straight, gay, lesbian, bisexual, 
pansexual and asexual are the most common in many languages. People who do not 
identify  as  heterosexual  are  often  referred  to  as  having 
‘non-heterosexual 
orientations141’.  

In data-collection efforts, it is important to not focus only on minority groups such as 
LGB+  people142.  Sexual  orientation  is  a  part  of  everyone’s  human  condition  and  can 
trigger positive and negative experiences. Therefore, an indicator of sexual orientation 
should make it possible to cover sexual-majority and sexual-minority populations. 

Sexual  orientation  is  a  multidimensional  construct  encompassing  (1)  emotional, 
romantic, and sexual attraction, (2) identity, and (3) behaviour143.  

1. 

2. 

3. 

Attraction  refers  to  the  gender(s)  to  which  a  person  is  emotionally, 
romantically  or  sexually  attracted  and  the  strength  of  this  attraction, 
including whether a person feels attracted at all. 

Identity refers to a person’s core internal sense of their sexuality, including 
how  a person  thinks of themselves  and the  way  they  want  to  be  seen by 
others. 

Behaviour  refers  to  the  gender(s)  of  sexual  partners  and  how  a  person 
interacts romantically and/or sexually with others. 

Sexual orientation is often defined based on the gender(s) of a person’s desired or actual 
partners compared to their own gender. The three dimensions of sexuality – attraction, 

140 Saewyc, E. M. et al. (2004). Measuring sexual orientation in adolescent health surveys: Evaluation of 
eight school-based surveys. Journal of Adolescent Health, 35(4), pp.345.e.2-345.e15. 
141 Rieger, G., & Savin-Williams, R. C. (2012). Gender Nonconformity, Sexual Orientation, and Psychological 
Well-Being.  Archives  of  Sexual  Behaviour,  41(3),  611-621;  Coleman,  E.  (1990).  Towards  a  synthetic 
understanding  of  sexual  orientation.  In  D.  P.  McWhirther,  S.  A.  Sanders,  &  R.  J.  Machover  (Eds.), 
Homosexuality/Heterosexuality. Oxford University Press, Oxford. 
142 Dean, J. J. (2011). The Cultural Construction of Heterosexual Identities. Sociology Compass, 5(8), 679-
687. 
143 National Academies of Sciences, Engineering, and Medicine (2022), Measuring Sex, Gender Identity, 
and Sexual Orientation, The National Academies Press, Washington DC, p. 5. 

54 

 
 
 
identity,  and  behaviour  –  may  not  correspond  to  each  other144,145.  For  example, 
someone  may  be  attracted  to  the  same  sex/gender  but  exclusively  engage  in  sexual 
behaviour  with  people  of  the  opposite  sex/gender;  or  might  be  having  sexual 
experiences with someone of the same sex/gender but still identify as straight. 

Sexual-orientation  identity  is  the  cognitive  (i.e.  how  a  respondent  sees  or  thinks  of 
themselves)  and  social  expression  (i.e.  it  provides  ‘label’  options  that  reflect  a  social 
status or community) of one’s sexual orientation. Thus, sexual-orientation identity is the 
dimension  that  is  most  consistently  tied  to  experiences  with  material  forms  of 
discrimination, and is noted explicitly in laws and policies aimed at protecting or harming 
sexual minorities146. It is also the dimension most frequently used in population-based 
data-collection settings to count and distinguish between sexual-minority and sexual-
majority adult populations. When collecting data on young people, attraction may be a 
more reliable measure, since young people are more likely to still be coming to terms 
with their identity. 

Sexual orientation identities can be categorised as set out in the bullet points below (see 
also the glossary in the annex). 

●  Heterosexual,  straight:  ‘A  person  whose  romantic,  emotional  and/or  physical 

attraction is to people of a different gender147’. 

●  Gay: ‘A person who is sexually and/or emotionally attracted to people of the same 
gender. It traditionally refers to men, but other people who are attracted to the 
same gender or multiple genders may also define themselves as gay148’. 

● 

● 

Lesbian: ‘A woman who has a romantic and/or sexual orientation towards women. 
Some non-binary people may also identify with this term149’.  

Bisexual: ‘An umbrella term used to describe a romantic and/or sexual orientation 
towards more than one gender150’. 

●  Queer: An umbrella term for belonging to the LGBTIQ community, which may refer 
to any or all SOGIESC elements. Previously used as a derogatory term to refer to 

144 Laumann, E., Gagnon, J. H., Michael, R. T., & Michaels, S. (1994), The social organization of sexuality: 
sexual practices in the United States, University of Chicago Press, Chicago. 
145 Richters, J. et al. (2014). Sexual identity, sexual attraction and sexual experience: the Second Australian 
Study of Health and Relationships. Sexual health, 11(5), pp. 451-460. 
146 National Academies of Sciences, Engineering, and Medicine (2022), Measuring Sex, Gender Identity, 
and Sexual Orientation, The National Academies Press, Washington DC, p. 75. 
147 IOM UN Migration (2021), SOGIESC Glossary of Terms, UNHCR, p. 2. 
148 ILGA Europe (2022), Our Glossary. 
149 Stonewall (2022), List of LGBTQ+ terms. 
150 Stonewall (2022), List of LGBTQ+ terms. 

55 

 
 
 
LGBTIQ individuals in the English language, queer has been reclaimed by people 
who  identify  beyond  traditional  gender  categories  and  heteronormative  social 
norms.  However,  depending  on  the  context,  some  people  may  still  find  it 
offensive151.  

● 

Pansexual:  When  a  person  is  emotionally  and/or  sexually  attracted  to  people 
regardless of their gender152. 

●  Asexual:  Someone  who  experiences  little  to  no  sexual  attraction,  although  they 

may experience romantic attraction153. 

4.1.2. 

Guidance 

Member States are encouraged to do the following things.  

● 

● 

They  should  use  precise  terminology  that  reflects  the  concepts  of  interest.  The 
term ‘sexual orientation’ should be clearly defined/explained. An info button with 
a definition could help respondents to surveys to understand the concept.  

They should avoid conflating attraction, identity and/or behaviour when measuring 
sexual orientation. As sexual orientation is a multidimensional construct, questions 
should clearly specify which component or components of sexual orientation are 
being measured. Depending on the dimension that is being measured (attraction, 
identity, and behaviour), the definition can vary. 

● 

They  should  develop  definitions  in  close  consultation  with  LGBTIQ  civil-society 
organisations, and with attention to local cultural terminology. 

●  When  collecting  data,  they  should  allow  respondents  to  self-identify  whenever 
possible; any proxy reporting should reflect what is known about how a person self-
identifies. 

●  When data collection is aimed at younger people, it is recommended to only use 
the  scale  of  sexual  attraction  unless  the  aim  of  the  survey  is  to  measure  sexual 
behaviour. 

● 

should  use 

sexual 
They 
experiences/behaviours are the scope of the question. For instance, in HIV research 
it  is  more  important  to  measure  sexual  behaviour  than  sexual  attraction  or 

‘sexual  behaviour’  when 

the  dimension 

151 Adopted from ILGA Europe (2022), Our Glossary. 
152 ILGA Europe (2022), Our Glossary. 
153 Adopted from IOM UN Migration (2021), SOGIESC Glossary of Terms, UNHCR, p. 2. 

56 

 
 
 
identity154. Sexual behaviour will also identify those people that do not identify as 
LGB+  but  do  interact  romantically  and/or  sexually  with  people  of  the  same 
sex/gender identity.  

● 

They should use a clear time frame (over the respondent’s lifetime, over the past 5 
years of the respondent’s life, last year, and currently) when asking about sexual 
orientation.  Responses  to  a  sexual  orientation  question  are  a  subjective  view  of 
oneself and can change over the course of a person’s lifetime and depending on 
the context.  

● 

They should adopt terminology accepted by the relevant communities and make 
sure that answer options capture the different subgroups of interest.  

●  When  asking  a  question  about  romantic  and/or  sexual  partners,  they  should 

consider that respondents may have more than one partner. 

4.1.3. 

Examples for measuring sexual orientation 

4.1.3.1. 

Example of questions on sexual identity 

The following example from  Belgium155 reflects the fact that one’s sexual orientation 
might shift in a lifetime.  

Q: How would you currently describe your sexual orientation?  

Straight 

● 
●  Gay 
● 
Lesbian 
● 
Bisexual 
●  Asexual  
●  Otherwise:… 
● 
I don’t know 
● 
I don’t want to say 

Notes for consideration 

154  Badgett,  M.  (2009).  Best  Practices  for  Asking  Questions  about  Sexual  Orientation  on  Surveys.  The 
Williams Institute, Los Angeles. 
155 Burgwal, A., & Motmans, J. (to be published). Enough: research into the experiences with violence of 
LGBTI people in Flanders, Belgium. The translation used in the article was ‘heterosexual’ and ‘homosexual’ 
rather than ‘straight’ and ‘gay’. 

57 

 
 
 
By  including  a  time  frame,  this  question  more  accurately  captures  a  respondent’s 
experience. It is important, however, to ensure that it is possible for a respondent to 
select multiple options, as an asexual person may also identify with any of the other 
orientations. 

4.1.3.2. 

Example of question on sexual attraction – Sexual 
health study in Belgium 

An ongoing sexual health study in Belgium asked respondents to identify to whom they 
were sexually attracted156. This example is problematic, since it groups all trans people 
together. The categories used by the same study for sexual behaviour (below) would be 
preferable.  

Q: We would like to know who you are currently sexually/romantically attracted to. I 
am attracted to… (Check everything that applies to you).  

(Cisgender) men  
(Cisgender) women  
Transgender and/or non-binary persons  

● 
● 
● 
●  No one 
● 
I don’t care about gender 
● 
I don’t want to say 
●  Other, namely: (text box) 

Notes for consideration 

Allowing for multiple answers makes this a more flexible question. However, grouping 
all trans people under one category does not capture the experience of a respondent 
who  is, for  instance,  attracted  to  women  (both cis  and  trans)  but  not  to  any other 
genders. Depending on the target audience, the use of the term ‘cisgender’ may also 
be confusing since the term is not widely known outside LGBTIQ communities. A brief 
clarification  (Such  as  ‘cisgender  means  “not  transgender”’)  would  be  helpful. 
Moreover, the distinction between cisgender and transgender risks excluding intersex 
people. 

156 De Brier, N., et. al. (2022). Prevalence and associated risk factors of HIV infections in a representative 
transgender and non-binary population in Flanders and Brussels (Belgium): Protocol for a  community-
based, cross-sectional study using time-location sampling. PLoS ONE, 17(4), pp. 1-22 De Brier, N., et. al. 
(2022). Prevalence and associated risk factors of HIV infections in a representative transgender and non-
binary population in  Flanders and Brussels (Belgium): Protocol for a  community-based, cross-sectional 
study using time-location sampling. PLoS ONE, 17(4), pp. 1-22 PLoS ONE, 17(4), pp. 1-22. 

58 

 
 
 
 
 
4.1.3.3. 

Example of question on sexual behaviour – Sexual 
health study in Belgium 

The same study measured sexual behaviour in a way that would avoid binary gender 
answer options, and allow for multiple answers by giving a choice to distinguish between 
cisgender and transgender sexual partners. This was done with the question below157. 

Q: With whom have you had sexual contact in the last 12 months? (Multiple choice 
and multiple answers possible)  

Cisgender man or men  
Cisgender woman or women  
Transgender man or men  
Transgender woman or women  

● 
● 
● 
● 
●  Non-binary person(s)  
● 

I don’t know 

Earlier in the questionnaire, respondents were asked whether they had sexual contact 
with  at  least  1  person  in  the  last  12  months.  To  measure  sexual  experiences  (sexual 
behaviour),  the  term  ‘sexual  contact’  needs  a  definition  for  the  respondent  to 
understand  what  the  researchers  meant.  In  this  questionnaire,  sexual  contact  was 
defined as ‘all kinds of lovemaking involving genital contact, i.e. touching someone else’s 
genitals, whether orally, vaginally or anally158’. 

Notes for consideration 

This  example  uses  inclusive  response  categories  (preferable  to  those  in  the  above 
example on sexual attraction), and the multiple-choice option allows respondents to 
describe their sexual behaviour more accurately. As with the example above, the use 
of the term ‘cisgender’ may be confusing depending on the target audience, since the 
term  is  not  widely  known  outside  LGBTIQ  communities.  The  distinction  between 
cisgender and transgender also risks excluding intersex people. 

157 De Brier, N., et. al. (2022). Prevalence and associated risk factors of HIV infections in a representative 
transgender and non-binary population in Flanders and Brussels (Belgium): Protocol for a  community-
based, cross-sectional study using time-location sampling. PLoS ONE, 17(4), pp. 1-22. 
158 De Brier, N., et. al. (2022). Prevalence and associated risk factors of HIV infections in a representative 
transgender and non-binary population in Flanders and Brussels (Belgium): Protocol for a  community-
based, cross-sectional study using time-location sampling. PLoS ONE, 17(4), pp. 1-22. 

59 

 
 
 
 
4.2. 

How to collect data on sex and gender 
(identity) 

4.2.1. 

Rationale 

Data-collection efforts often conflate sex, a biological variable, with gender or gender 
identity, a socially defined variable, or treat the respective concepts as interchangeable. 
Data  are  often  only  collected  on  legal  sex/gender,  without  allowing  for  self-
identification. Sometimes the goal of extrapolating data across surveys or the need for 
comparisons  over  time  are  used  as  arguments  for  not  adapting  already  existing 
questionnaires/variables  by  adding  new  questions  or  revisions  of  already  applied 
terms/categorisations.  For  example,  for  reasons  of  keeping  historical  continuity  of 
information, some countries might retain a conflated category of sex and gender and 
not use a revised version (that differentiates between sex assigned at birth and gender 
identity).  

However, a question on gender identity measures different information than a question 
on sex or a question on legal sex/gender159, and the concepts do not always correspond 
to  each  other.  A  question  on  sex  is  often  not  straightforward  for  trans  and  intersex 
respondents, who may be unsure whether to respond with their sex assigned at birth or 
their  gender  identity.  Legal  sex/gender  also  fails  to  capture  many  trans  people’s 
experiences. Not all trans people wish or are able to obtain  LGR. There can be many 
reasons  for  this.  For  example,  some  gender  identities  are  not  translatable  into  legal 
options (such as non-binary identities), and some people might not have access to legal 
sex/gender  options  depending  on  the  legislation  of  a  specific  country  (for  instance 
restrictions due to medical criteria or there being a minimum age for LGR). This results 
in gender identity not being measured correctly when legal sex/gender is assessed. 

As sex, gender and gender identity do not measure the same underlying concept, they 
should be disentangled and assessed separately160,161,162,163. A difference can be made 

159 Legal gender refers to the gender currently recognised by law. Many Member States only recognise 
the options of male and female, which excludes other identities such as non-binary from being recorded 
on official documents like passports. 
160 Angus, J. (2012). Gender, Sex, and Health Research: Developments and Challenges. Canadian Journal 
of Nursing Research, 44(3), pp. 3-5. 
161 Lorber, J. (2006). Shifting Paradigms and Challenging Categories. Social Problems, 53(4). 
162 Ritz, S. A. et al. (2017). First steps for integrating sex and gender considerations into basic experimental 
biomedical research. the FASEB Journal, 28(1), 4-13.  
163 Westbrook, L., & Saperstein, A. (2015). New categories are not enough: rethinking the measurement 
of sex and gender in social surveys. Gender & Society, 29(4), 534-560. 

60 

 
 
 
between  sex  assigned  at  birth,  gender,  and  gender  identity.  To  do  so,  one  needs  to 
clarify and agree upon the underlying definitions of these different concepts. 

According to a review of the United Nations Economic Commission for Europe (UNECE) 
on measuring gender identity, one of the major challenges to consider when collecting 
information on gender identity is language. The review states the following.  

In some languages (Greek for example), the language is based on a binary sex framework 
where terms differ depending on whether a man or woman is speaking, or whether a 
man or woman is being spoken to. And some languages, […], do not have different words 
for  sex  and  gender  (such  as  Romanian  and  Greek;  possibly  others).  In  Romanian,  the 
word ‘gen’ for ‘gender’ also means ‘species’ and ‘sex’ — and so ‘identitate sexuala’ is 
used for both gender identity and sexual identity164. 

(sex  characteristics),  which 

Sex is ‘a multidimensional construct based on a cluster of anatomical and physiological 
include  external  genitalia,  secondary  sex 
traits 
characteristics, gonads, chromosomes, and hormones. It is usually assigned as female or 
male,  most often  defined  at birth based  on  visual  inspection of  external  genitalia165’. 
When constructed along with a binary model of male and female, the term carries the 
risk of neglecting the existence of intersex persons. For many trans people, sex is also 
not a straightforward concept. 

Sex assigned at birth refers to ‘the sex that is assigned to a person at birth, typically 
based on the infant’s external anatomy166’. 

Gender is ‘a multidimensional construct that links gender identity (a core element of a 
person’s 
individual  sense  of  self),  gender  expression,  and  social  and  cultural 
expectations about status, characteristics, and behaviour that are associated with sex 
traits167’. ‘Gender traditionally refers to a social and cultural construct of being a man or 
a  woman.  However,  some  people  do  not  identify  within  the  gender  binary  of 
man/woman. Gender exists independently of sex, and an individual’s gender does not 
always correspond with the sex assigned at birth168, 169.’ 

164 UNECE (2019), In-Depth Review of Measuring Gender Identity. Conference of European Statisticians, 
Paris. 
165 National Academies of Sciences, Engineering, and Medicine (2022), Measuring Sex, Gender Identity, 
and Sexual Orientation, The National Academies Press, Washington DC, p. 3. 
166 IOM UN Migration (2021), SOGIESC Glossary of Terms, UNHCR, p. 7. 
167 National Academies of Sciences, Engineering, and Medicine (2022), Measuring Sex, Gender Identity, 
and Sexual Orientation, The National Academies Press, Washington DC, p. 4. 
168 TGEU (2016), Glossary. 
169 See also the EU gender equality strategy 2020-2025, which defines gender as ‘the socially constructed 
roles, behaviours, activities and attributes that a given society considers appropriate for women and men’ 
and is commonly used by EU institutions, including the European Institute for Gender Equality (EIGE). 

61 

 
 
 
Gender identity refers to ‘each person’s deeply felt internal and individual experience 
of gender, which may or may not correspond with the sex assigned at birth, including 
the  personal  sense  of  the  body  (which  may  involve,  if  freely  chosen,  modification  of 
bodily  appearance  or  function  by  medical,  surgical  or  other  means)  and  other 
expressions of gender, including dress, speech and mannerisms170’. 

Gender-diverse refers to the inherent diversity of possible gender experiences, which 
are  therefore  broader  than  cisgender  or  transgender.  Gender-diverse  is  an  umbrella 
term for many possible gender identifications, for example gender-fluid, gender-free, 
agender, bigender etc171. 

Non-binary:  ‘An  adjective  describing  people  whose  gender  identity  falls  outside  the 
male-female binary. Non-binary is an umbrella term that encompasses a wide variety of 
gender experiences, including people with a specific gender identity other than man or 
woman, people who identify as two or more genders (bigender or pan/polygender) and 
people who don’t identify with any gender (agender)172’. 

Legal gender recognition (LGR) is a process in which a trans and/or intersex person’s 
gender is recognised in law, or the achievement of the process173. 

Cisgender: ‘A person whose current gender identity corresponds to the sex they were 
assigned at birth174’.  

Trans: ‘An umbrella term to describe people whose gender is not the same as, or does 
not sit comfortably with, the sex they were assigned at birth175’. 

Endosex:  ‘A  term  describing  a  person  who  was  born  with  sex  characteristics  that  fit 
typical binary notions of male or female bodies. An endosex person may identify with 
any gender identity or sexual orientation176’. See also intersex. 

Intersex individuals, or persons with a variation of sex characteristics, are born with 
sex  characteristics  (sexual  anatomy,  reproductive  organs,  hormonal  structure  and/or 

170  International  Commission  of  Jurists  (2007),  Yogyakarta  principles:  principles  on  the  application  of 
international human rights law in relation to sexual orientation and gender identity, p. 8.  
171 See for example the distribution of gender identities in the EU Agency for Fundamental Rights’ LGBTI 
II  survey,  FRA  (2020),  A long  way  to  go  for  LGBTI  equality,  Publications  Office,  Luxembourg;  European 
Commission (2019). 
172 IOM UN Migration (2021), SOGIESC Glossary of Terms, UNHCR, p. 5. 
173 ILGA Europe (2022), Our Glossary. 
174 National Academies of Sciences, Engineering, and Medicine (2022), Measuring Sex, Gender Identity, 
and Sexual Orientation, The National Academies Press, Washington DC, p. 4. 
175 Stonewall (2022), List of LGBTQ+ terms. 
176 IOM UN Migration (2021), SOGIESC Glossary of Terms, UNHCR, p. 7. 

62 

 
 
 
levels and/or chromosomal patterns) that do not match the typical societal definition of 
male or female (See Guideline No 4.4 of this guidance document). 

On the topic of gender identities, it is important to recognise the diversity that exists. 
Many people identify outside the binary identities of men and women. People whose 
gender identity and sex assigned at birth do not match – or do not match completely – 
are usually grouped under the concept of ‘transgender and gender-diverse/non-binary’ 
(TGD)177. This default grouping carries the risk of incorrectly including intersex people 
who may not identify with the sex assigned to them at birth but who would not identify 
as trans. Conversely, it also risks excluding those intersex people who do identify as trans 
but whose gender identity does align with the sex assigned to them at birth.  

‘Gender-diverse’ is also an umbrella term for many possible gender identifications, for 
example  non-binary,  gender-fluid,  gender-free,  agender,  bigender  etc.  (see,  for 
example, the distribution of gender identities in FRA’s LGBTI II survey and in the glossary 
in the annex of this guidance document). Many gender-diverse people identify as trans, 
although not all do. 

Questions  about  sex  and  sex  assigned  at  birth  can  be  very  sensitive  and  considered 
invasive.  Therefore,  if  data-collection  efforts  only  seek  to  collect  the  gender  of  the 
respondents, a question on gender identity is sufficient. However, where data collection 
specifically aims to disaggregate trans respondents, a question on gender identity would 
not collect this information. Many trans people identify within the binary, so for instance 
both a trans and cis woman would select ‘woman’ as their gender identity, which does 
not allow for disaggregation178. 

To  collect  data  on  trans  respondents,  there  are  several  possible  approaches. 
Respondents can be asked directly whether they identify as trans. It is also possible to 
take a two-step approach asking first about gender identity and then about whether the 
respondent’s gender identity differs from their sex assigned at birth. An alternative two-
step approach asks about gender identity and sex assigned at birth (unlike the first two-
step  question,  this  alternative  does  not  make  explicit  reference  to  whether  the 
respondent’s  gender  identity  differs  from  their  sex  assigned  at  birth).  The  latter  two 
approaches carry the above-mentioned risk of falsely classifying intersex respondents 
(note that these questions do not assess whether somebody is intersex/has a variation 
of sex characteristics, and this should be assessed in a separate question (See Guideline 
No 4.4 of this guidance document)).  

177 Motmans, J., Nieder, T. O., and Bouman, W. P. (Eds.). (2020). Non-binary and genderqueer genders. 
Routledge, Oxon. 
178 Schilt, K., and Bratter, J. (2015). From multiracial to transgender? Assessing attitudes toward expanding 
gender options on the US census. Transgender Studies Quarterly, 2(1), pp. 77-100. 

63 

 
 
 
4.2.2. 

Guidance 

Member States and all other relevant institutions and actors involved in or responsible 
for the collection of SOGIESC data are encouraged to take the actions set out in the 
bullet points below. 

● 

● 

● 

● 

They  should  draw  up  questions  that  use  precise  terminology,  and  ensure  the 
validity of the constructs in these questions, by clearly distinguishing measures of 
‘gender’  from  measures  of  ‘sex’.  The  term  ‘gender  identity’  should  clearly  be 
distinguished or understood as being distinct from the term ‘sex assigned at birth’ 
as well as from a (possible change in) legal gender registration or gender-affirming 
healthcare.  

The terms they use (such as ‘gender’, ‘gender identity’, ‘sex’ and ‘sex assigned at 
birth’) should be clearly defined/explained (see the glossary in the  annex of this 
guidance document).  

They should develop definitions in close consultation with trans and intersex civil-
society organisations, and with attention to local cultural terminology. 

To  the  extent  possible,  they  should  avoid  collecting  ‘sex  assigned  at  birth’  as  a 
standalone item in any data-collection context. ‘Sex’ as a separate criterion should 
only be measured when it is of analytical value. 

● 

They should use inclusive measures of gender, which include the following.  

■  One-step  measures:  attempts  to  identify  trans  respondents  using  a  single 

question (e.g. ‘Do you identify as trans?’). 

■ 

Two-step measures: a broader approach that tries to count persons who do 
not identify with the sex assigned to them at birth (e.g. trans, some intersex 
people) and those who do, consisting of a two-question sequence – commonly 
asking for (1) current gender and (2) whether the respondent’s gender differs 
from their sex assigned at birth; or (1) current gender and (2) sex assigned at 
birth. When cross-tabulated, the two-step measures can provide approximate 
counts  of  cisgender  women  and  men,  transgender  women  and  men,  and 
people who identify using terms outside the gender binary, such as non-binary 
or genderqueer. 

—  Where possible, both questions should be presented on the same page. 
It may be preferable to ask about gender identity before asking about sex 

64 

 
 
assigned  at  birth.  There  is  some  evidence  that  being  asked  about  sex 
assigned at birth first is uncomfortable for some trans respondents179.  

— 

If sex assigned at birth is asked first in a two-step approach, there should 
be a clarification stating that a further question on gender identity will 
follow, allowing respondents to self-identify. 

●  When aimed at younger people or children, they should adapt the wording of the 
it  more  understandable  for  the  targeted 

questions  accordingly  to  make 
population180. 

●  As for the specific part on ‘sex assigned at birth’, and if a third category is legally 
allowed to be recorded in an official government certificate, a third free-text (write-
in)  response  category  should  be  added  to  the  binary  option  (female/male)  to 
provide for such a possibility. In countries where a third option is not possible in 
legal documents, this can possibly be omitted, although foreign-born people might 
need a third category. 

● 

● 

● 

In situations in which the collection of transgender status is not a major objective, 
a  single  question  asking  for  gender  with  categories  of  male,  female,  and  a  third 
category such as ‘Another gender’ would suffice. However, a question should not 
use ‘transgender’ as the third category. Since many trans people identify as male 
or female, such a measure may be invalidating and will underperform in identifying 
trans respondents181.  

They  should  periodically  re-evaluate  and  expand  answer  options  over  time  and 
across  different  settings,  particularly  for  responses  (and  especially  for  write-in 
responses) by people who self-identify outside of binary gender norms. 

They should periodically assess item performance across different survey modes, 
including proxy reporting, in languages other than the national language182: (i) for 

179 National Academies of Sciences, Engineering, and Medicine (2022), Measuring Sex, Gender Identity, 
and Sexual Orientation, The National Academies Press, Washington DC, p. 119.  
180 Data on SOGIESC on young people are already being collected in some countries. However, questions 
might need to be rephrased. For example, using a simple phrase such as ‘to what extent do you feel like 
a boy/girl?’ is more understandable for adolescents. However, the use of terms such as ‘100%’ and ‘real 
boy’  is  discouraged  by  current  language  guidelines  in  research.  National  Academies  of  Sciences, 
Engineering, and Medicine (2022), Measuring Sex, Gender Identity, and Sexual Orientation, The National 
Academies Press, Washington DC, p. 132. 
181 Schilt, K., and Bratter, J. (2015). From multiracial to transgender? Assessing attitudes toward expanding 
gender options on the US census. Transgender Studies Quarterly, 2(1), pp. 77-100. 
182  A  commonly  cited  challenge  for  setting  international  standards  for  two-step  data  collection  is  the 
absence of words distinguishing between ‘sex’ and ‘gender’ in some languages (UNECE (2019), In-Depth 
Review of Measuring Gender Identity. Conference of European Statisticians, Paris). 

65 

 
 
 
different social, demographic, and ethnic minority groups; (ii) for people with an 
immigrant background; and (iii) among young people.  

●  As recommended in the 2019 UNECE review on gender identity, in languages where 
the concept of gender is not well established, language issues might be rectified 
with  definitions  and  guidance,  online  or  via  an  interviewer.  Different  languages 
might require differently nuanced translations. Question testing is recommended 
to ensure respondents understand what is being asked. Such testing would need to 
be repeated on a recurring basis as public understandings change183.  

4.2.3. 

Examples on how to collect data on sex, 
gender, and gender identity 

4.2.3.1. 

Example adopted from the FRA’s LGBTIQ Survey: 

Q1: How would you describe yourself today?  
The response options ‘Woman’ and ‘Man’ include trans women and men. 

Single response 
●  Woman 
●  Man 
● 
● 
● 
● 
● 

Non-binary or Genderqueer or Agender or Polygender or Gender-fluid 
Do not identify as woman, man, or non-binary, please specify how would you identify … 
Prefer not to say 
Don’t understand the question 
Don’t know 

Q2: Are/were you a trans person? 
(Ask if Q1=‘Woman’, ‘Man’, or ‘Do not identify as woman, man, or non-binary, please specify 
how would you identify’) 
The term ‘trans’ is used in this survey as a broad umbrella term that includes all those who are 
transgender, non-binary, gender variant, polygender, agender, gender-fluid, cross dressers, 
transsexual, or men and women with a transsexual past, and other terms 

● 
● 
● 
● 
● 

Yes 
No 
Prefer not to say 
Don’t understand the question 
Don’t know 

Q3: What sex were you assigned at birth?  

183 UNECE (2019), In-Depth Review of Measuring Gender Identity. Conference of European Statisticians, 
Paris. 

66 

 
 
 
 
 
 
 
[INFO BUTTON: Sex assignment at birth is the classification of people as male, female, intersex, 
or another sex assigned at birth, often based on physical anatomy. The sex assigned at birth is 
recorded in your birth certificate when you were born.] 

Single response 

Female  

● 
●  Male  
●  Other (please specify ….) 
● 
Prefer not to answer 

How to count the collected data: 

Trans woman: Q1 = woman & Q2 = Yes  
Trans man: Q1 = man & Q2 = Yes 

● 
● 
●  Gender-diverse:  Q1  =  Non-binary  or  Genderqueer  or  Agender  or  Polygender  or 

Gender-fluid  

Notes for consideration 

This  approach  is  based  on  self-identification,  allowing  respondents  to  state  for 
themselves whether they are trans. Since sex assigned at birth is not used as the basis 
for the respondent classification, the approach does not carry the risk discussed above 
of  incorrectly  classifying  intersex  respondents.  Sex  assigned  at  birth  is  instead 
collected as additional information that can inform the analysis and is asked about 
after the question on current gender. This is important, as qualitative research shows 
that asking about sex assigned at birth before asking about current gender may be 
uncomfortable for some trans respondents184. This aligns with the experience of civil-
society  organisations  consulted  in  the  process  of  drafting  this  guidance  document. 
One  limitation  of  this  question  is  the  ‘Non-binary  or  Genderqueer  or  Agender  or 
Polygender or Gender-fluid’ category, which does not capture all genders outside the 
binary. The approach to counting also assumes that all these respondents identify as 
trans, which may not be the case for some. The question does not capture information 
on intersex respondents, most of whom will have been assigned male or female at 
birth.  To  adequately  capture  this  information,  it  is  important  to  ask  a  separate 
question on whether respondents are intersex/have a variation of sex characteristics 
(see Guideline No 4.4 of this guidance document).  

184 National Academies of Sciences, Engineering, and Medicine (2022), Measuring Sex, Gender Identity, 
and Sexual Orientation, The National Academies Press, Washington DC, p. 119.  

67 

 
 
 
 
 
4.2.3.2. 

Example asking about gender-matching sex assigned 
at birth – Australian Bureau of Statistics 

When  a  question  about  sex  assigned  at  birth  is  not  necessarily  needed,  a  two-step 
approach asking about whether a person’s gender identity matches their sex assigned 
at  birth  is  recommended.  This  makes  it  possible  for  data  on  trans  persons  to  be 
disaggregated, while having only one question on gender identity does not.  However, 
and  as  mentioned  above,  this  two-step  grouping  of  questions  carries  the  risk  of 
incorrectly classifying intersex respondents. The Australian Bureau of Statistics takes this 
two-step approach, and additionally includes a question on legal gender registration.  

Q1: How [do/does] [you/Person’s name/they] describe [your/their] gender?185 

[INFO BUTTON: Gender refers to current gender, which may be different to sex 
recorded at birth and may be different to what is indicated on legal documents.] 
SINGLE RESPONSE 

●  Man or male 
●  Woman or female 
●  Non-binary 
● 
● 

[I/They] use a different term (please specify) 
Prefer not to answer 

Q2: Is your gender the same as the sex you were registered at birth? 

Yes 

● 
●  No (write in gender): …. 

Q3: Have you had your gender registration adjusted on official documents? 

● 
Yes 
●  No 

How to count the collected data 

In the guidance published online, details are only given on how the first question was 
counted186. The box below sets out how the question was counted. 

Preferred 
code 

Alternative 
code 

Label 

Definition 

185 Australian Bureau of Statistics (2020), Standard for Sex, Gender, Variations of Sex Characteristics and 
Sexual Orientation Variables, ABS. 
186 Australian Bureau of Statistics (2020), Standard for Sex, Gender, Variations of Sex Characteristics and 
Sexual Orientation Variables, ABS. 

68 

 
 
 
1 

2 

3 

4 

5 

M 

F 

X 

T 

Z 

Man or male 

Woman or 
female 
Non-binary 

Different term 

Prefer not to 
answer 

People who described their 
gender as man or male 
People who described their 
gender as woman or female 
People who described their 
gender as non-binary 
People who described their 
gender as a term other than 
man/male, woman/female or 
non-binary* 
People who preferred not to 
respond on how they describe 
their gender 

* Except where the written response for ‘Different term’ indicates a variation of one of ‘Man or male’, 
‘Woman or female’ or ‘Non-binary’, where that response will be coded to the associated label.  

The count for trans and non-binary respondents can be derived as follows: 

● 
● 
● 

Trans man: Q1= ‘Man or male’ AND Q2=No 
Trans woman: Q1= ‘Woman or female’ AND Q2=No 
Non-binary: Q1= ‘Non-binary’ 

Notes for consideration 

The  three-step  Australian-style  approach  provides  an  option  for  people  who  were 
registered other than male or female at birth, and its answers are mutually exclusive 
and mutually exhaustive. The question on gender registration is also an advantage, 
since  low  percentages  on  this  question  may  indicate  issues  with  the  legal  process 
(although not all trans people wish to recognise their gender legally). However, only 
giving respondents the options of ‘yes’ and ‘no’ for the question is overly simplistic. 
Requirements  and  cost  can  vary  with  different  documents,  so  it  is  possible  that  a 
respondent  will  have,  for  instance,  updated  their  passport  without  updating  their 
birth certificate, which the question in its current form will not capture. The question 
does not explicitly mention gender identities beyond man, woman and non-binary, 
although  these  are  collected  in  the  ‘[I/They]  use  a  different  term’  option.  The 
approach carries the risk of incorrectly including intersex people who may not identify 
with the sex assigned to them at birth but who would not identify as trans. Conversely, 
it also risks excluding those intersex people who do identify as trans but whose gender 
identity does align with the sex assigned to them at birth. Finally, the write-in option 
in Q2 is unclear as to whether respondents should write in their current  gender, or 
their sex assigned at birth. 

69 

 
 
 
4.2.3.3. 

Example of closed lists of gender categories – the 
‘Being Transgender in Belgium’ study 

In most cases, where measuring gender identity in its fullest is not the aim of the data 
collection, it is sufficient to offer a closed list of gender categories from which the 
respondent is asked to choose one option that matches best at this moment. This 
approach is suited to instances where neither the respondent’s sex assigned at birth 
nor their trans status is of relevance for the data collection.  

One example of this approach is the question below.  

Q1: How would you describe your gender identity? In your feelings and thoughts, 
you are (multiple options possible): 

●  A man 
●  A woman 
●  A man with a transgender past 
●  A woman with a transgender past 
●  A cross-dressing man 
●  A cross-dressing woman 
●  A trans man: a person who was born female but has a male gender identity 
●  A trans woman: a person who was born male but has a female gender identity 
●  Genderqueer 
●  Non-binary 
● 
Polygender 
●  Gender-fluid 
●  Other: (complete) … 
● 

I don’t want to say 

Q2: In order to be able to analyse the data from this study, we can only use a limited 
category of the above categories. We would like to ask you which group most closely 
matches your current gender identity? Tick the answer that best fits you at this 
moment. I prefer to be classified in the group of: 

(Trans) man 
(Trans) woman 
Cross-dresser 

● 
● 
● 
●  Genderqueer/agender/polygender/genderfluid/non-binary  
● 

I don’t know, I don’t have a preference 

Notes for consideration 

70 

 
 
This approach gives respondents the agency to determine themselves which group 
they  are  classified  in  for  the  purpose  of  the  study.  However,  the  categories  of 
man/woman with a transgender past may be confusing to respondents. Moreover, 
not all people who cross-dress would see themselves as trans, so including this as a 
category may also create confusion. In addition, the question may fail to capture all 
trans respondents, since some may only select the categories ‘man’ and ‘woman’ in 
Q1. 

4.3. 

How to collect data on gender 
expression 

4.3.1. 

Rationale 

Gender expression refers to ‘each person’s presentation of the person’s gender through 
physical  appearance  –  including  dress,  hairstyles,  accessories,  cosmetics  –  and 
mannerisms,  speech,  behavioural  patterns,  names,  and  personal  references.  Gender 
expression may or may not conform to a person’s gender identity187.’ 

Gender non-conforming: ‘A broad term referring to people who do not behave in a way 
that  conforms  to  the  traditional  expectations  of  their  gender,  or  whose  gender 
expression does not fit neatly into a category. While many also identify as transgender, 
not all gender non-conforming people do188.’ 

Gender expression is a useful variable in determining whether gender non-conforming 
people  (independent  of  the  person’s  sexual  orientation,  gender  identity  or  sex 
characteristics) are treated differently, based on the degree that their gender expression 
aligns with the gender ascribed to them by others. 

Asking about gender expression can involve: (i) continuum measures of femininity and 
masculinity; or (ii) questions on perceived gender conformity by others. Each approach 
can be useful depending on the aim of the research. 

The continuum approach draws on an established line of research in psychology, which 
shows that femininity and masculinity should not be seen as polar ‘opposites’, as people 
can be low on both scales, high on both scales, somewhere in between, or outside of 

187 International Commission of Jurists (2017, The Yogyakarta Principles Plus 10 - Additional Principles and 
State Obligation on the Application of International Human Rights Law in Relation to Sexual Orientation, 
Gender Expression and Sex Characteristics to Complement the Yogyakarta Principles, p. 6). 
188 Human Rights Campaign (2022), Glossary of Terms. 

71 

 
 
 
the scales altogether189,190. Cognitive interviews with queer women also indicate that a 
bipolar  measure  which  asks  respondents  to  rank  themselves  on  a  scale  from  very 
masculine  to  very  feminine  is  conceptually  and  empirically  problematic191.  Unipolar 
measures asking about femininity and masculinity separately have also been shown to 
be more reliable in picking up nuanced responses for trans respondents in particular, 
compared to bipolar measures192.  

Gender expression can be asked about by means of self-appraisal (how the respondent 
perceives their own gender expression) as well as by means of reflected appraisal (asking 
respondents how others perceive them). While responses to self and reflected appraisal 
tend  to  overlap,  it  is  useful  to  measure  the  discrepancy  between  these,  as  this 
discrepancy has been associated with worse health outcomes193. Qualitative research 
indicates that self-appraisal should be asked before reflected appraisal194. 

The second approach of asking about perceived conformity is easier to use in surveys 
and can be used in conjunction with questions about discrimination, harassment and 
violence,  since  people  who  are  less  conforming  are  more  likely  to  experience  these 
problems. This is more appropriate in an LGBTIQ-specific survey rather than a general 
population survey. 

4.3.2. 

Guidance 

Member States and all other relevant institutions and actors involved in or responsible 
for the collection of SOGIESC data are encouraged to take the actions set out in the 
bullet points below.  

● 

● 

They should use continuum scales (two Likert scales to measure a masculine gender 
expression and a feminine gender expression) as self-reported by the respondent.  

If possible, they should ask about both the respondents’ subjective evaluation of 
their  gender  expression  and  how  the  respondent  thinks  others  evaluate  their 

189  Garbarski,  D.  (2023),  The  measurement  of  gender  expression  in  survey  research,  Social  Science 
Research 110, p. 2. 
190 National Academies of Sciences, Engineering, and Medicine (2022), Measuring Sex, Gender Identity, 
and Sexual Orientation, The National Academies Press, Washington DC, p. 104. 
191  Garbarski,  D.,  LaVergne,  D.  (2020).  The  Measurement  of  Sexual  Attraction  and  Gender  Expression: 
Cognitive  Interviews  with  Queer  Women.  In:  Brenner,  P.S.  (eds)  Understanding  Survey  Methodology. 
Frontiers in Sociology and Social Research, vol 4. Springer, Cham. 
192  Garbarski,  D.  (2023),  The  measurement  of  gender  expression  in  survey  research,  Social  Science 
Research 110, p. 9. 
193  Hart,  CG,  Saperstein,  A,  Magliozzi,  D  and  Westbrook,  L.  (2019),  Gender  and  health:  beyond  binary 
categorical measurement, Journal of Health and Social Behavior, 60 (1), p. 109. 
194  Garbarski,  D.  (2023),  The  measurement  of  gender  expression  in  survey  research,  Social  Science 
Research 110, p. 2. 

72 

 
 
 
gender  expression.  If  there  is  limited  space,  they  should  ask  about  the  latter 
(reflected appraisal)195. 

They  should  consider that  gender  expression  may  vary  across  different contexts 
based on the respondents’ comfort and safety. Respondents  may not be able to 
express themselves in a manner that feels consistent with their wishes. 

In an LGBTIQ-specific survey, if the aim of the question is to evaluate how others 
perceive  the  respondent  in  order  to  identify  how  this  would  impact  the 
respondent’s experiences, asking about perceived conformity is most appropriate. 

● 

● 

4.3.3. 

Examples of measuring gender expression 

4.3.3.1. 

Example of a continuum approach196 

Q1. In general, how would you describe your appearance, style, and dress? 

Not at all 
feminine 

A little 
feminine 

Somewhat 
feminine 

Very feminine 

Extremely 
feminine 

⃝ 

⃝ 

⃝ 

⃝ 

⃝ 

Not at all 
masculine 

A little 
masculine 

Somewhat 
masculine 

Very 
masculine 

Extremely 
masculine 

⃝ 

⃝ 

⃝ 

⃝ 

⃝ 

Q2. In general, how do you think people would describe your appearance, style, and 
dress? 

Not at all 
feminine 

A little 
feminine 

Somewhat 
feminine 

Very feminine 

Extremely 
feminine 

⃝ 

⃝ 

⃝ 

⃝ 

⃝ 

Not at all 
masculine 

A little 
masculine 

Somewhat 
masculine 

Very 
masculine 

Extremely 
masculine 

195  Garbarski,  D.  (2023),  The  measurement  of  gender  expression  in  survey  research,  Social  Science 
Research 110, pp. 13-14. 
196  Garbarski,  D.  (2023),  The  measurement  of  gender  expression  in  survey  research,  Social  Science 
Research 110. 

73 

 
 
 
 
⃝ 

⃝ 

⃝ 

⃝ 

⃝ 

Q3. In general, how would you describe how you walk, talk, sit, stand, and gesture? 

Not at all 
feminine 

A little 
feminine 

Somewhat 
feminine 

Very feminine 

Extremely 
feminine 

⃝ 

⃝ 

⃝ 

⃝ 

⃝ 

Not at all 
masculine 

A little 
masculine 

Somewhat 
masculine 

Very masculine 

Extremely 
masculine 

⃝ 

⃝ 

⃝ 

⃝ 

⃝ 

Q4. In general, how do you think people would describe how you walk, talk, sit, 
stand, and gesture? 

Not at all 
feminine 

⃝ 

A little 
feminine 

⃝ 

Somewhat 
feminine 

Very feminine 

Extremely 
feminine 

⃝ 

⃝ 

⃝ 

Not at all 
masculine 

A little 
masculine 

Somewhat 
masculine 

Very masculine 

Extremely 
masculine 

⃝ 

⃝ 

⃝ 

⃝ 

⃝ 

Notes for consideration 

This  example  uses  unipolar  measures  of  masculinity  and  femininity,  and  therefore 
avoids positioning these measures as polar opposites. The example captures both the 
dimensions of appearance and behaviour. More research is needed on whether the 
question order of appearance and behaviour has a significant impact, and on whether 
these survey questions could be combined197. A drawback of this approach is that it 
assumes  that  respondents  would  understand  their  gender  expression  in  terms  of 
masculinity  and  femininity,  which  may  not  be  the  case,  particularly  for  agender 
respondents. It would therefore be helpful to add a ‘nowhere on this scale’ option. 
Another limitation of the example is that it does not provide respondents with ‘don’t 

197  Garbarski,  D.  (2023),  The  measurement  of  gender  expression  in  survey  research,  Social  Science 
Research 110, p. 14. 

74 

 
 
 
 
 
 
know’  or  ‘prefer  not  to  answer’  options,  which  are  important  from  an  ethical 
perspective (see Section No 2.3 of this guidance document). 

4.3.3.2. 

Example of asking about perceived conformity198 

People can tell I’m transgender/gender non-conforming even if I don’t tell them. 

●  Always 
●  Most of the time 
● 
Sometimes 
●  Occasionally 
●  Never 

Notes for consideration 

This is an example from a trans-specific survey. The question captures the extent of 
perceived  visual  conformity  of  the  respondent  with  traditional  gender  identity 
expressions,  which  can  be  analysed  in  conjunction  with  rates  of  discrimination, 
violence, and harassment. Although this question is only directed at trans and gender 
non-conforming  respondents,  a  similar  question  is  possible  for  other  LGBTIQ 
respondents.  The  Generations  Survey,  for 
instance,  which  focused  on  LGB 
respondents, asked: ‘How often, if ever, can people tell you are LGB even if you don’t 
tell them?’. The survey had the same response options of ‘always’, ‘most of the time’, 
‘sometimes’,  ‘occasionally’  and  ‘never’199.  As  mentioned  above,  the  question  also 
lacks ‘don’t know’ and ‘prefer not to answer’ options, which would be important to 
include from an ethical perspective (see Section No 2.3 of this guidance document). 

198Jaime, G., Mottet, L., Tanis, J., Harrison, J., Herman, J. and Keisling, M. (2011), Injustice at Every Turn: A 
Report of the National Transgender Discrimination Survey, National Center for Transgender Equality and 
National Gay and Lesbian Task Force, Washington DC, p. 184. 
199 Krueger, E. A., Lin, A., Kittle, K. R., & Meyer, I. H. (2020), Generations – A Study of the Life and Health 
of LGB People in a Changing Society (Methodology and Technical Notes, Gallup Quantitative Survey), The 
Williams Institute, Los Angeles. 

75 

 
 
 
 
4.4. 

How to collect data on sex 
characteristics 

4.4.1. 

Rationale 

Sex  characteristics  ‘refer  to  each  person’s  physical  features  relating  to  sex,  including 
genitalia  and  other  sexual  and  reproductive  anatomy,  chromosomes,  hormones,  and 
secondary physical features emerging from puberty200’.  

Intersex individuals, or persons with a variation of sex characteristics, are born with 
sex  characteristics  (sexual  anatomy,  reproductive  organs,  hormonal  structure  and/or 
levels and/or chromosomal patterns) that do not match the typical societal definition of 
male or female. Often, the variation of sex characteristics is not identified until later in 
life201. 

Being intersex/having a variation of sex characteristics is an important component of 
demographic status and private medical information. It can also be an aspect of identity, 
although not all people with a variation of sex characteristics will identify as intersex or 
see themselves as part of the LGBTIQ community202. 

Endosex:  ‘A  term  describing  a  person  who  was  born  with  sex  characteristics  that  fit 
typical binary notions of male or female bodies. An endosex person may identify with 
any gender identity or sexual orientation203.’ 

While  research  on  intersex  people  outside  the  clinical  setting  is  still  scarce,  recent 
discussions about best-practice research methodologies have increased204. In academic 
literature,  different  terms  are  used  to  describe  people  with  variations  of  sex 
characteristics.  The  terminology  used  to  describe  this  population  is  shaped  by  social 

200 International Commission of Jurists (2017, The Yogyakarta Principles Plus 10 - Additional Principles and 
State Obligation on the Application of International Human Rights Law in Relation to Sexual Orientation, 
Gender Expression and Sex Characteristics to Complement the Yogyakarta Principles, p. 6). 
201 National Academies of Sciences, Engineering, and Medicine (2022), Measuring Sex, Gender Identity, 
and Sexual Orientation, The National Academies Press, Washington DC, p. 139. 
202 National Academies of Sciences, Engineering, and Medicine (2022), Measuring Sex, Gender Identity, 
and Sexual Orientation, The National Academies Press, Washington DC, p. 141. 
203 IOM UN Migration (2021), SOGIESC Glossary of Terms, UNHCR, p. 7. 
204 Park, A. (2016), Reachable: Data collection methods for sexual orientation and gender identity, The 
Williams Institute, Los Angeles. 

76 

 
 
 
 
views about sex and gender being binary concepts, which has also been largely adopted 
by medical professionals and policy makers. 

By including a question about sex characteristics, intersex people/people with variations 
of  sex  characteristics  are  made  visible  in  the  collected  data.  It  is  important  to  not 
conflate having a variation of sex characteristics with having a certain (gender) identity, 
and to understand being intersex as an experience. Most people with a variation of sex 
characteristics  identify  as  either  a  man  or  a  woman,  although  the  possibility  to 
select/self-identify as intersex and/or gender-diverse (such as non-binary/genderqueer) 
should always be allowed when collecting data205. 

Researchers should be aware that the concept of being intersex is not widely known in 
the intersex population itself, since many people with variations of sex characteristics 
are often given different names/diagnoses206, such as androgen insensitivity syndrome, 
congenital adrenal hyperplasia, Klinefelter syndrome or Turner syndrome207. Given the 
diversity of terms used, as well as the diversity in knowledge on terminology, it is very 
important to present the respondents with a clear and encompassing definition. 

4.4.2. 

Guidance 

Member States are encouraged to take the following actions.  

● 

● 

● 

● 

They  should  include  at  least  one  question  to  make  it  possible  for  people  with  a 
variation of sex characteristics to self-identify. 

They should use a standalone measure to ask respondents about whether they are 
intersex/have a variation of sex characteristics or are not (endosex). The question 
should not be added as a third response option to ‘sex’ or ‘sex assigned at birth’, as 
intersex persons are, as a general rule, assigned female or male. However, an open 
box should be provided to allow respondents to include national specificities, like 
the ‘blank marker’ in Germany208.  

Being intersex should not be conflated with being trans or with sexual orientation. 

They should consider that intersex people may have a gender identity different to 
the  one  assigned  to  them  at  birth.  While  some  intersex  people  may  identify  as 

205 Jones, T., Hart, B., Carpenter, M., Ansara, G., Leonard, W., & Lucke, J. (2016), Intersex. Stories and 
Statistics from Australia, Open Book Publishers, Cambridge. 
206 van Ditzhuijzen, J., & Motmans, J. (2020),  Kennis En Opvattingen over Intersekse: Een Nulmeting in 
Nederland En Vlaanderen, Rutgers and UZ Gent, Utrecht and Ghent. 
207 Randjelovic, R. et. al. (2018), Intersex Research Study, UNDP, pp. 46-48. 
208 Statistische Ämter des Bundes und der Länder (2022), Zensus 2022. 

77 

 
 
 
● 

● 

● 

trans, other may feel that the term does not encapsulate their specific situation as 
an intersex person in a mostly endosex society.  

They should add a clear definition of the concept of intersex or of what constitutes 
a  variation  of  sex  characteristics,  with  enough  examples  that  are  part  of  the 
umbrella term of intersex. 

They  should  develop  definitions  in  close  consultation  with  intersex  civil-society 
organisations, and with attention to local cultural terminology. 

In addition to an explanation/definition of the concept, they should add an open 
follow-up question for  those  indicating  they  are  intersex/have  a  variation  of  sex 
characteristics making it possible for respondents to describe, in the framework of 
the survey, experiences and needs connected to their variation to the extent they 
are willing to do so. 

4.4.3. 

Examples of intersex measures 

4.4.3.1. 

Knowledge of – and perceptions about – intersex 
people: a baseline measurement in the Netherlands 
and Flanders 

Providing a definition of intersex is important and can significantly impact the response 
rate  to  surveys.  A  recent  example  comes  from  a  representative  panel  study  from 
Belgium and the Netherlands209. ‘Ad random’ selected participants were asked whether 
they were intersex in two different ways, which influenced the occurrence/visibility of 
intersex persons in the study results. The first time intersex was assessed in the panel 
study was before a definition was given, and respondents were able to tick the ‘intersex 
person’ option as applicable to them (among other options). In total, 9 people selected 
this option (0.4%). After the definition was given to the respondents, a different group 
of participants were asked whether they were an intersex person, or had some intersex 
condition.  Now  28  people  indicated  that  they  identified  themselves  as  an  intersex 
person or that they had an intersex condition (1.6%). It therefore appears important to 
include a definition of intersex before assessing whether respondents are intersex or 
have a variation of sex characteristics.  

It  is  also  important  to  differentiate  between  questions  which  ask  about  whether  the 
respondent has a variation of sex characteristics, and questions that ask whether they 

209 van Ditzhuijzen, J., & Motmans, J. (2020),  Kennis En Opvattingen over Intersekse: Een Nulmeting in 
Nederland En Vlaanderen, Rutgers and UZ Gent, Utrecht and Ghent. 

78 

 
 
 
have been given a diagnosis related to such a variation, as the following two examples 
show.  Unless  the  research  is  specifically  on  healthcare,  the  former  approach  is 
preferable. 

4.4.3.2. 

Example asking whether respondents have a variation 
of sex characteristics: the FRA’s LGBTI II survey 
(online) 

The FRA’s 2019 EU LGBTI II survey included the experiences of intersex people for the 
first time.  

The question used by FRA was the following. 

Q: Some persons are born with sex characteristics (like sexual anatomy, reproductive 
organs, and/or chromosome patterns) that do not belong strictly to male or female 
categories or belong to both at the same time. This is known as ‘intersex’. Would you 
describe yourself as intersex?  

● 
Yes 
●  No 

[INFO BUTTON: Variations of sex characteristics can present themselves prenatally and 
at birth but also during childhood, in puberty or in adulthood. You might have noticed 
a variation in your sex characteristics at a very early age or later on in life, and you may 
have had surgical or medical treatment to modify them.] 

Notes for consideration 

The question provides a definition for clarity and allows respondents to self-identify. 
However, it does not allow respondents to describe their variations in their own words 
and does not include ‘don’t know’ or ‘prefer not to answer’ options (see Section No 
2.3 of this guidance document). 

79 

 
 
 
 
 
4.4.3.3. 

Example asking whether respondents have been 
diagnosed with a variation of sex characteristics – 
Research into the experiences with violence of LGBTI 
people in Flanders, Belgium 

An ongoing LGBTI survey on violence in Belgium takes the following approach, which 
asks specifically about a diagnosis210. 

Q: Some persons are born with a body that does not fit within the normative 
definitions of man and woman. The experience of people born with such a body is 
known as 'intersex'. Have you ever been diagnosed with a form of intersex at birth or 
at a later date? 

● 
Yes 
●  No 
● 
● 

I don't know 
I don't want to say 

[POP-UP NOTE: Intersex refers to the experiences of people born with bodies that do 
not fit within the normative definitions of male and female. Intersex is very diverse and 
is  not  always  about external  sexual  characteristics/genitals.  Sexual  characteristics  are 
not only the genitals (penis/vagina), but also chromosomes, hormones, or internal sex 
organs (womb, hormone glands). Examples are being born with a female body but with 
XY chromosomes, or someone with a penis and a uterus. You may recognise yourself in 
this description but have never heard of the word intersex. Doctors and care providers 
may use medical terms such as ‘pseudo-hermaphrodite’, (C)AIS, Klinefelter, AGS/CAH, 
17-,  Alpha/5-,  Beta/5-,  Alpha  Reductase  and  hypospadias,  MRKH,  Turner,  or 
‘disorder/difference of sex development (DSD)’.] 

Notes for consideration 

The question provides an extensive definition in the pop-up note, including examples. 
However,  it  does  not  ask  for  the  respondent’s  self-identification,  but  rather  for  a 
diagnosis. This medicalised approach may be difficult for intersex persons who were 
traumatised in medical settings. It might also exclude respondents who became aware 
of  their  variation  of  sex  characteristics  themselves  and  have  not  received  a  formal 
diagnosis. The term ‘female body’ in the explanatory text also reinforces normative 
assumptions of what is ‘male’ and ‘female’. This could be rephrased, for instance, as 
‘external genitalia that are perceived as “female” (e.g. labia, vulva, clitoris)’. The text 
also refers to the diagnosis of ‘pseudo-hermaphrodite’. While this term is still used in 
medicine, ‘hermaphrodite’ is considered a slur and should therefore either be avoided 

210 Burgwal, A., & Motmans, J. (to be published). Enough: research into the experiences with violence of 
LGBTI people in Flanders, Belgium. 

80 

 
 
 
or  acknowledged  to  be  a  term  that  is  often  used  derogatorily.211  Finally,  ‘sex 
characteristics’ is a more appropriate term than ‘sexual characteristics’. 

211 Further information on terms to use and avoid can be found in European Parliament (2020), Glossary 
of Sensitive Language for Internal and External Communications. 

81 

 
 
 
 
 
 
Annex: Glossary 

Agender: ‘A term describing people who do not identify with any gender. This term may 
also encompass people who experience a lack of gender and people whose gender is 
neutral. Agender people have a range of sexual orientations, gender expressions and sex 
characteristics212.’ 

Allosexual/romantic:  ‘Allo  people  experience  sexual  and  romantic  attraction,  and  do 
not identify as on the ace or aro spectrum. Allo is to ace [asexual] and aro [aromantic] 
spectrum  identities,  as  straight  is  to  LGB+  spectrum  identities.  It  is  important  to  use 
words  that  equalise  experience,  otherwise  the  opposite  to  ace  and  aro  becomes 
‘normal’ which is stigmatising213.’ 

Asexual: ‘A person who may experience romantic or emotional attraction, but generally 
does  not  experience  sexual  attraction.  Demisexual  and  greysexual/grey-asexual 
describe people with varying degrees of sexual attraction. Asexual may be used as an 
umbrella  term  encompassing  demisexual,  greysexual  and  other  terms214.’  Asexual 
people may identify as aromantic, gay, lesbian, bi, pan, etc.  

Aromantic:  ‘A  person  who does not  experience romantic  attraction.  Some  aromantic 
people  experience  sexual  attraction,  while  others  do  not.  Aromantic  people  who 
experience sexual attraction or occasional romantic attraction might also use terms such 
as  gay,  bi,  lesbian,  straight  and  queer  in  conjunction  with  asexual  to  describe  the 
direction of their attraction215.’ 

Bisexual  (bi+):  ‘Bi  is  an  umbrella  term  used  to  describe  a  romantic  and/or  sexual 
orientation towards more than one gender. Bi people may describe themselves using 
one  or  more  of  a  wide  variety  of  terms,  including,  but  not  limited  to,  bisexual,  pan, 
queer, and some other non-monosexual and non-monoromantic identities216.’  

Cisgender: ‘A person whose current gender identity corresponds to the sex they were 
assigned at birth217.’  

212 IOM UN Migration (2021), SOGIESC Glossary of Terms, UNHCR, p. 5. 
213 Stonewall (2022), List of LGBTQ+ terms. 
214 IOM UN Migration (2021), SOGIESC Glossary of Terms, UNHCR, p. 2. 
215 Stonewall (2022), List of LGBTQ+ terms. 
216 Stonewall (2022), List of LGBTQ+ terms. 
217 National Academies of Sciences, Engineering, and Medicine (2022), Measuring Sex, Gender Identity, 
and Sexual Orientation, The National Academies Press, Washington DC, p. 4. 

82 

 
 
 
Endosex:  ‘A  term  describing  a  person  who  was  born  with  sex  characteristics  that  fit 
typical binary notions of male or female bodies. An endosex person may identify with 
any gender identity or sexual orientation218.’ See also intersex. 

Gay ‘refers to a person who is sexually and/or emotionally attracted to people of the 
same gender. It traditionally refers to men, but other people who are attracted to the 
same gender or multiple genders may also define themselves as gay219.’ 

Gender is ‘a multidimensional construct that links gender identity (a core element of a 
person’s 
individual  sense  of  self),  gender  expression,  and  social  and  cultural 
expectations about status, characteristics, and behaviour that are associated with sex 
traits220.’ ‘Gender traditionally refers to a social and cultural construct of being a man or 
a  woman.  However,  some  people  do  not  identify  within  the  gender  binary  of 
man/woman. Gender exists independently of sex, and an individual’s gender does not 
always correspond with the sex assigned at birth221.’ 

Gender-diverse refers to the inherent diversity of possible gender experiences, which 
are  therefore  broader  than  cisgender  or  transgender.  Gender-diverse  is  an  umbrella 
term for many possible gender identifications, for example gender-fluid, gender-free, 
agender, bigender, etc222.  

Gender expression refers to ‘each person’s presentation of the person’s gender through 
physical  appearance  –  including  dress,  hairstyles,  accessories,  cosmetics  –  and 
mannerisms, speech, behavioural patterns, names and personal references, and noting 
further  that  gender  expression  may  or  may  not  conform  to  a  person’s  gender 
identity223’. ‘Gender expression is separated from gender identity as both cisgender or 
transgender men can for example deploy gender-stereotypically-masculine behaviour 
and expression, or not. Although there are variations in how gender expression (often 
defined as ranges of femininity and masculinity) is defined and expressed both across 
cultural  groups  and  over  time,  at  the  core  of  the  dominant  gender-expression  belief 
system is the expectation that people who are assigned female at birth should have a 

218 IOM UN Migration (2021), SOGIESC Glossary of Terms, UNHCR, p. 7. 
219 ILGA Europe (2022), Our Glossary. 
220 National Academies of Sciences, Engineering, and Medicine (2022), Measuring Sex, Gender Identity, 
and Sexual Orientation, The National Academies Press, Washington DC, p. 4. 
221 TGEU (2016), Glossary. 
222 See for example the distribution of gender identities in the EU Agency for Fundamental Rights’ LGBTI 
II survey, FRA (2020), A long way to go for LGBTI equality, Publications Office, Luxembourg. 
223 International Commission of Jurists (2017, The Yogyakarta Principles Plus 10 - Additional Principles and 
State Obligation on the Application of International Human Rights Law in Relation to Sexual Orientation, 
Gender Expression and Sex Characteristics to Complement the Yogyakarta Principles, p. 6. 

83 

 
 
 
“feminine”  gender  expression,  and  those  assigned  male  at  birth  should  have  a 
“masculine” gender expression224.’  

Gender-fluid: ‘A person who does not identify with a single fixed gender or has a fluid 
or unfixed gender identity225.’ 

Gender identity refers to ‘each person’s deeply felt internal and individual experience 
of gender, which may or may not correspond with the sex assigned at birth, including 
the  personal  sense  of  the  body  (which  may  involve,  if  freely  chosen,  modification  of 
bodily  appearance  or  function  by  medical,  surgical  or  other  means)  and  other 
expressions of gender, including dress, speech and mannerisms226’.  

Genderqueer:  ‘A  person  who  identifies  as  neither  or  both  male  or  female,  or  a 
combination of genders227.’ 

Gender non-conforming: ‘A broad term referring to people who do not behave in a way 
that  conforms  to  the  traditional  expectations  of  their  gender,  or  whose  gender 
expression does not fit neatly into a category. While many also identify as transgender, 
not all gender non-conforming people do228.’ 

Heterosexual, straight: ‘A person whose romantic, emotional and/or physical attraction 
is to people of a different gender229.’ 

Homosexual:  ‘Sexually  and/or  emotionally  attracted  to  people  of  the  same,  usually 
binary,  gender.  It  is  recommended  to  use  the  terms  lesbian  and  gay  instead  of 
homosexual  people.  The  terms  lesbian  and  gay  are  being  considered  neutral  and 
positive, and the focus is on the identity instead of being sexualised or pathologised230.’ 

Intersex:  ‘Intersex  individuals  are  born  with  sex  characteristics  (sexual  anatomy, 
reproductive organs, hormonal structure and/or levels and/or chromosomal patterns) 
that do not fit the typical definition of male or female. The term “intersex” is an umbrella 
term for the spectrum of variations of sex characteristics that naturally occur within the 
human  species.  The  term  intersex  acknowledges  the  fact  that,  physically,  sex  is  a 

224 West C, Zimmerman DH. (1987), Doing Gender. Gender and Society 1(2), pp. 125-151.  
225 Human Rights Campaign (2022), Glossary of Terms. 
226  International  Commission  of  Jurists  (2007),  Yogyakarta  principles:  principles  on  the  application  of 
international human rights law in relation to sexual orientation and gender identity, p. 8. 
227 IOM UN Migration (2021), SOGIESC Glossary of Terms, UNHCR, p. 5. 
228 Human Rights Campaign (2022), Glossary of Terms. 
229 IOM UN Migration (2021), SOGIESC Glossary of Terms, UNHCR, p. 2. 
230 ILGA Europe (2022), Our Glossary. 

84 

 
 
 
spectrum  and  that  people  with  variations  of  sex  characteristics  other  than  male  or 
female exist231.’ 

Legal gender recognition: ‘A process whereby a trans and/or intersex person’s gender 
is recognised in law, or the achievement of the process232.’  

Lesbian:  Refers  to  a  woman  who  has  a  romantic  and/or  sexual  orientation  towards 
women. Some non-binary people may also identify with this term233. 

LGBTIQ: Acronym for lesbian/gay/bisexual/trans/intersex and queer/questioning. Other 
popular variants add the letter A, where A stands for asexual, aromantic or agender and 
‘+’.  Adding  the  ‘+’  is  generally  considered  more  inclusive,  encompassing  other 
limited  to)  asexual,  pansexual,  gender-
realities/identities  such  as  (but  not 
nonconforming234. 

Non-binary:  ‘An  adjective  describing  people  whose  gender  identity  falls  outside  the 
male-female binary. Non-binary is an umbrella term that encompasses a wide variety of 
gender experiences, including people with a specific gender identity other than man or 
woman, people who identify as two or more genders (bigender or pan/polygender) and 
people who don’t identify with any gender (agender)235.’ Some non-binary people prefer 
a gender-neutral name or pronouns such as they/them rather than he/him or she/her 
(see personal pronouns). 

Pansexual: ‘When a person is emotionally and/or sexually attracted to people regardless 
of their gender236.’ 

Personal  pronouns:  ‘Pronouns  are  words  we  use  to  talk  about  ourselves  (“I”),  to 
someone (“you”) or about other people (“she”, “he”, “they”, etc.) In English, “he” and 
“she”, called third-person pronouns, are gendered, while the singular “they” is gender-
neutral. In other languages, such as Arabic and Korean, second-person pronouns (“you”) 
and  first-person  pronouns  (“I”)  may  also be  gendered.  Some  languages don’t  require 
pronouns  to  indicate  gender  or  have  a  gender-neutral  option,  including  Japanese, 
Swahili, Swedish and Turkish. Sweden has added the gender-neutral pronoun “hen” to 

231  ILGA  Europe  (2022),  Our  Glossary.  This  is  a  shortened  version  of  the  definition  developed  by  the 
intersex community and OII Europe, see Dan Christian Ghattas (2015), Standing up for the Human Rights 
of Intersex People – How Can You Help?, OII Europe and ILGA Europe, Brussels, p. 9. 
232 ILGA Europe (2022), Our Glossary. 
233 Stonewall (2022), List of LGBTQ+ terms. 
234 Adopted from European Parliament (2020), Glossary of Sensitive Language for Internal and External 
Communications, p. 11. This guidance note uses the acronym ‘LGBTIQ’ to align with the terminology used 
in the Commission’s LGBTIQ Equality Strategy 2020-2025. 
235 IOM UN Migration (2021), SOGIESC Glossary of Terms, UNHCR, p. 5. 
236 ILGA Europe (2022), Our Glossary. 

85 

 
 
 
their language to complement “han” (he) and “hon” (she). Other languages don’t mark 
gender at all, including Armenian, Finnish, Hungarian, Persian and Yoruba237.’ 

Queer: ‘Traditionally a negative term, queer has been reclaimed by some people and is 
considered inclusive of a wide range of diverse sexual orientations, gender identities and 
expressions. It may be used as an umbrella term for people with diverse SOGIESC, or as 
an alternative to the phrase “people with diverse SOGIESC” or the acronym LGBT. Queer 
is used by many people who feel they do not conform to a given society’s economic, 
social and political norms based on their sexual orientation, gender identity and gender 
expression238.’ ‘However, depending on the context, some people may still find the term 
offensive239.’ 

Sex is ‘a multidimensional construct based on a cluster of anatomical and physiological 
traits (sex traits), which include external genitalia, secondary sex characteristics, gonads, 
chromosomes,  and  hormones.  It  is  usually  assigned  as  female  or  male,  most  often 
defined at birth based on visual inspection of external genitalia240.’  

Sex assigned at birth: ‘The sex that is assigned to a person at birth, typically based on 
the infant’s external anatomy […]. The phrases “assigned female at birth” (AFAB) and 
“assigned  male  at  birth”  (AMAB)  refer  to  people  with  typical  male  or  female  sex 
characteristics,  regardless  of  their  gender  identity  or  gender  expression.  The  phrase 
“coercively  assigned  female  [male]  at  birth”  (CAFAB  and  CAMAB)  refer  to  intersex 
people assigned a binary sex, often via non-consensual surgeries241.’ 

Sex  characteristics  ‘refer  to  each  person’s  physical  features  relating  to  sex,  including 
genitalia  and  other  sexual  and  reproductive  anatomy,  chromosomes,  hormones,  and 
secondary physical features emerging from puberty242’. People who have a variation of 
sex characteristics (VSC) that falls outside of the normative understanding of gendered 
bodies are often referred to as intersex. 

Sexual  orientation:  refers  to  ‘how  one  finds  oneself  feeling  drawn  (or  not  drawn) to 
another  person  in  a  sexual  and/or  romantic  way243’.  ‘This  encompasses  emotional, 
affectional, and sexual attraction to, and intimate and sexual relations with, individuals 

237 IOM UN Migration (2021), SOGIESC Glossary of Terms, UNHCR, p. 5. 
238 IOM UN Migration (2021), SOGIESC Glossary of Terms, UNHCR, p. 2. 
239 ILGA Europe (2022), Our Glossary. 
240 National Academies of Sciences, Engineering, and Medicine (2022), Measuring Sex, Gender Identity, 
and Sexual Orientation, The National Academies Press, Washington DC, p. 3. 
241 IOM UN Migration (2021), SOGIESC Glossary of Terms, UNHCR, p. 7. 
242 International Commission of Jurists (2017, The Yogyakarta Principles Plus 10 - Additional Principles and 
State Obligation on the Application of International Human Rights Law in Relation to Sexual Orientation, 
Gender Expression and Sex Characteristics to Complement the Yogyakarta Principles, p. 6. 
243 European Parliament (2020), Glossary of Sensitive Language for Internal and External Communications, 
p. 12. 

86 

 
 
 
of a different gender or the same gender or more than one gender244.’ The three aspects 
most  commonly  measured  when  identifying  sexual  orientation  are  sexual  attraction, 
sexual behaviour, and sexual identity245. 

SOGIESC: ‘An acronym for sexual orientation, gender identity, gender expression and 
sex characteristics246.’ 

Trans/transgender: ‘An umbrella term to describe people whose gender is not the same 
as, or does not sit comfortably with, the sex they were assigned at birth. Trans people 
may describe themselves using one or more of a wide variety of terms, including (but 
not  limited to) transgender, transsexual,  genderqueer  (GQ),  gender-fluid,  non-binary, 
gender-variant, cross-dresser, genderless, agender, non-gender, third gender, bigender, 
trans man, trans woman, trans masculine, trans feminine and neutrois247.’ 

Variations  of  sex  characteristics  (VSC)  refer  to  ‘sex  characteristics  (sexual  anatomy, 
reproductive organs, hormonal structure and/or levels and/or chromosomal patterns) 
that do not fit the typical definition of male or female. The term “intersex” is an umbrella 
term for the spectrum of variations of sex characteristics that naturally occur within the 
human species248.’ ‘Some of these variations may be apparent before or at birth, while 
others are not apparent until after puberty or later or may not be physically apparent at 
all. There are more than 40 intersex variations; experts estimate between 0.5% and 1.7% 
of the population is born with intersex traits249.’  

244  International  Commission  of  Jurists  (2007),  Yogyakarta  principles:  principles  on  the  application  of 
international human rights law in relation to sexual orientation and gender identity, p. 8. 
245  Adopted  from  National  Academies  of  Sciences,  Engineering,  and  Medicine  (2022),  Measuring  Sex, 
Gender Identity, and Sexual Orientation, The National Academies Press, Washington DC, p. 5. 
246 IOM UN Migration (2021), SOGIESC Glossary of Terms, UNHCR, p. 1. 
247 Stonewall (2022), List of LGBTQ+ terms. 
248 ILGA Europe (2022), Our Glossary. 
249 IOM UN Migration (2021), SOGIESC Glossary of Terms, UNHCR, p. 7. 

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