Data Gaps Exist for Transgender Patients Living with HIV, Despite Need

The current unequal representation and inadequate amounts of data on transgender people in terms of HIV poorly represents this subpopulation group in the LGBTQ+ community in the US. Diana Tordoff writes about this issue in an article published in STAT, where she writes that the scarce amount of data concerning trans people affects how policy is shaped in the country.

Per a study published by the National Institute of Health, several barriers hindering participation from trans people were things like logistical concerns, mistrust, lack of awareness, and psychosocial/emotional concerns related to being “outed”. This separate study provides probable insight on why there may be less amounts of data on transgender people in terms of HIV.

The Centers for Disease Control (CDC) recently published data about HIV prevalence among trans people based on public health surveillance data, however gender identity data is not collected consistently across local jurisdictions. As a result, mathematical models can’t be built effectively to help policymakers if there are poor amounts of data regarding trans people and their experience with HIV.

Tordoff writes that there are likely hundreds of mathematical models focused on HIV. Only seven of these models include trans people at all. There are two key problems that Tordoff and her co-authors note in models that do include trans people. The first problem is that there are models only including trans women and not trans men or nonbinary people. Tordoff notes that there seems to be regurgitated information across such models and this first problem may be a reason why.

In a separate study published by the National Institute of Health, researchers state that by acknowledging less visible identities, transgender individuals may be better represented by research studies. The study also refers to recent research highlighting the experience that transgender people have had in completing questionnaires for research studies. Questionnaires will often only include the choices “male” or “female”, and even if there are options like “transgender male” or “transgender female”, researchers are at risk of ignoring nonbinary identities.

The second problem is that such models assume trans women exclusively partnering with cisgender men, however there are other choices that trans women make when choosing who to partner with.

There’s evidence that access to gender-affirming care (e.g., hormones) can increase adherence to other types of disease prevention among trans people (PrEP and getting STI-tested). In general, researchers and advocates have long called for the inclusion of SOGIE data (sexual orientation, gender identity expression) to get a better understanding of these sidelined populations.

Tordoff notes a separate study where Minalga looked at 41 milestone HIV trials between 1991-2023 and this study found that out of more than 170,000 total participants, less than 1% were identified as part of the trans community and 94% of those were trans women.

Minalga notes that when data from such studies gets analyzed and published, that data does not make it back to trans people.

The analysis notes that lack of data on trans people is harmful to trans people and policies, but it is also harmful to other areas of health that aren’t publicly tied to LGBTQ+ populations. An example of this is clinicians not having enough data on how interventions or treatment may work for trans patients. A lack of this data often leads clinicians to extrapolate data from cisgender people despite some physicians not being comfortable with that.

The Centers for Medicare and Medicaid Services (CMS) introduced optional questions on SOGIE data for state Medicaid programs to collect from applicants. CMS recommended collecting information on sex assigned at birth, gender identity and sexual orientation.

Although this data would not be nationally representative, self-reported SOGIE data has never been collected on such a large scale according to Nathaniel Tran at the University of Illinois at Chicago School of Public Health in JAMA. This is good because only a few states collect this type of data.

Legislation continues to restrict gender-affirming care across the country, preventing the collection of additional meaningful data on queer populations.

Queer people living in states that restrict access to gender-affirming care don’t trust the state to protect their personal data. On the other hand, most clinicians simply don’t know much about LGBTQ+ populations in the first place. Trans people are often frustrated by the way they are considered in the research they participate in. Despite the need, data gaps will continue to hamper policy changes designed to improve access to care and services for this already underserved population.