Gender-identity data for HIV programming across the globe
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Data for Implementation (Data.FI) supports the U.S. President’s Emergency Plan for AIDS Relief and country decision-makers to consider policy and program questions, identify the data needed to answer them, analyze data, and build information systems to optimize their use for decision making and program improvement. As part of that mandate, Data.FI also investigates the nature of the sex- and gender-related data that is collected and used in the service of curbing HIV transmission and best delivering care and treatment to people with HIV.
At the crux of the investigation into gender-identity data is to ask, “Will it help to improve the meaningfulness and use of gendered data in HIV programming?” Gender is defined with the binary designations of male or female, which are assigned to individuals at birth (the “F” or “M” designation we are all familiar with). Gender identity is more fluid and encompasses the way an individual feels about who they are and the way they present themselves to others. In many cultures, how an individual feels about their own gender is of no consequence — law and custom only regard the sex assigned at birth, and the rest is considered beside the point and, many times, judged as self-indulgent and even deviant.
The range of attitudes seen from country to country regarding gender identity introduce vast complexities into HIV programming across the globe. On one hand, all gender nuances should be considered so that we don’t skew strategies, compound bias and lack of understanding, and diminish the effectiveness of programming and policy that — as a consequence — may ultimately fail the populations we seek to serve. On the other hand, collecting data on gender identity could have a legal or social backlash for individual clients of HIV services, depending on where they live and the values and beliefs their communities follow.
So the question becomes, “Would the inclusion of a more complex and complete gender identity category in data collection be useful and inclusive from a programming and human rights perspective or would it be inappropriate and unnecessary?” A corollary to this question is, “Do gender non-conforming individuals want to be represented more broadly through gender identity categories contained within data?” To determine that, we need to discuss with them and with project country teams what they see on these issues in their country context.
Data.FI guidelines suggest that gender data could include data disaggregated by sex (female/male) plus data that expand beyond binary categories to include information based on people’s identity (e.g., woman, man, boy, girl, transgender, gender nonbinary, gender nonconforming and other identities). What gender-related data could we be collecting related to gender, and how would we use it?
Why is gender data important, and is collecting it helpful?
Collecting gender-identity data isn’t yet standardized for projects funded by PEPFAR through the U.S. Agency for International Development. Considering the cultural and legal sensitivities surrounding gender minorities and their high risk of discrimination and stigma in many countries, the data we collect about them and their specific health needs are important to understand for designing programs, decisions about confidentiality and mitigating risks to them.
The United Nations Declaration of Universal Human Rights states that we are entitled to the representation of our individual gender identity and that human rights apply despite “race, color, sex, language, religion, political or other opinion, national or social origin, property, birth or other status.” The UN Sustainable Development Goals also include two goals — gender equality and reduced inequalities — dedicated to ensuring fair representation and treatment of peoples. The prioritization of gender identity in U.S. policy is illustrated through the recent development of the U.S. National Strategy on Gender Equity and Equality, the USAID Equity Action Plan, the U.S. Department of State’s new gender marker on U.S. passports, and the Social Security Administration’s announcement on Oct. 19 that people will now be allowed to select the sex that best aligns with their gender identity in records, a policy change intended to be more inclusive of transgender Americans.
The National Strategy on Gender Equity and Equality states that “adequate collection of gender data is critical to establishing a baseline against which agencies can rigorously measure progress on identified priorities,” and promises to lead a government-wide effort to strengthen data collection and analysis of gender data, including gender identity data. It recognizes that “improvements in gender data collection are integral to advancing gender equity and equality worldwide.”
These examples represent an evolution in global thinking that gender identities are diverse, that gender minorities are often vulnerable in their communities, and that naming — and thereby giving visibility to — gender identities can support more inclusive development. Data.FI champions these rights in our gender strategy, rights that inspire us to explore the capture of data on gender identity.
More inclusive programming might include these steps at the project level:
- Integration of gender identity data collection in gender strategies and other guidelines;
- Addition of gender identity questions in baseline surveys, needs assessments and other surveys;
- Integration of gender identity data collection in gender-sensitive trainings;
- Conversations with country teams to understand contexts, needs and potential barriers.
And at the donor level, moving toward greater inclusion might involve expanding sex disaggregations to add gender-inclusive categories for routine reporting.
The idea of incorporating gender identity nuances into data collection is new, not adopted or planned for everywhere, not acceptable in some contexts, and so not mandated. But it may be an idea whose time has come, and some must lead.
As a small start, program and survey implementers could consider changing the language used on data collection forms and consider asking more nuanced questions in data collection. Institutionalizing and socializing gender minorities and their needs might make a difference in how we use and analyze data for decision making in HIV programming.
For more information, see the white paper by Caitlin Showalter, “Standardizing the Collection of Gender-Identity Data for HIV Programming.”
