Characterizing Disparities in the HIV Care Continuum among Transgender and Cisgender Medicare Beneficiaries.

Background: In the US, transgender and gender-diverse (TGD) individuals, particularly trans feminine individuals, experience a disproportionately high burden of HIV relative to their cisgender counterparts. While engagement in the HIV Care Continuum (e.g., HIV care visits, antiretroviral (ART) prescribed, ART adherence) is essential to reduce viral load, HIV transmission, and related morbidity, the extent to which TGD people engage in one or more steps of the HIV Care Continuum at similar levels as cisgender people is understudied on a national level and by gendered subgroups. Methods and Findings: We used Medicare Fee-for-Service claims data from 2009 to 2017 to identify TGD (trans feminine and non-binary (TFN), trans masculine and non-binary (TMN), unclassified gender) and cisgender (male, female) beneficiaries with HIV. Using a retrospective cross-sectional design, we explored within- and between-gender group differences in the predicted probability (PP) of engaging in one or more steps of the HIV Care Continuum. TGD individuals had a higher predicted probability of every HIV Care Continuum outcome compared to cisgender individuals [HIV Care Visits: TGD PP=0.22, 95% Confidence Intervals (CI)=0.22-0.24; cisgender PP=0.21, 95% CI=0.21-0.22); Sexually Transmitted Infection (STI) Screening (TGD PP=0.12, 95% CI=0.11-0.12; cisgender PP=0.09, 95% CI=0.09-0.10); ART Prescribed (TGD PP=0.61, 95% CI=0.59-0.63; cisgender PP=0.52, 95% CI=0.52-0.54); and ART Persistence or adherence (90% persistence: TGD PP=0.27, 95% CI=0.25-0.28; 95% persistence: TGD PP=0.13, 95% CI=0.12-0.14; 90% persistence: cisgender PP=0.23, 95% CI=0.22-0.23; 95% persistence: cisgender PP=0.11, 95% CI=0.11-0.12)]. Notably, TFN individuals had the highest probability of every outcome (HIV Care Visits PP =0.25, 95% CI=0.24-0.27; STI Screening PP =0.22, 95% CI=0.21-0.24; ART Prescribed PP=0.71, 95% CI=0.69-0.74; 90% ART Persistence PP=0.30, 95% CI=0.28-0.32; 95% ART Persistence PP=0.15, 95% CI=0.14-0.16) and TMN people or cisgender females had the lowest probability of every outcome (HIV Care Visits: TMN PP =0.18, 95% CI=0.14-0.22; STI Screening: Cisgender Female PP =0.11, 95% CI=0.11-0.12; ART Receipt: Cisgender Female PP=0.40, 95% CI=0.39-0.42; 90% ART Persistence: TMN PP=0.15, 95% CI=0.11-0.20; 95% ART Persistence: TMN PP=0.07, 95% CI=0.04-0.10). The main limitation of this research is that TGD and cisgender beneficiaries were included based on their observed care, whereas individuals who did not access relevant care through Fee-for-Service Medicare at any point during the study period were not included. Thus, our findings may not be generalizable to all TGD and cisgender individuals with HIV, including those with Medicare Advantage or other types of insurance. Conclusions: Although TGD beneficiaries living with HIV had superior engagement in the HIV Care Continuum than cisgender individuals, findings highlight notable disparities in engagement for TMN individuals and cisgender females, and engagement was still low for all Medicare beneficiaries, independent of gender. Interventions are needed to reduce barriers to HIV care engagement for all Medicare beneficiaries to improve treatment outcomes and reduce HIV-related morbidity and mortality in the US.

Emergency Department Use Disparities Among Transgender and Cisgender Medicare Beneficiaries, 2011-2020.

This cross-sectional study compares emergency department use among transgender and gender-diverse as well as cisgender Medicare beneficiaries.

Use of machine learning methods to understand discussions of female genital mutilation/cutting on social media.

Female genital mutilation/cutting (FGM/C) describes several procedures that involve injury to the vulva or vagina for nontherapeutic reasons. Though at least 200 million women and girls living in 30 countries have undergone FGM/C, there is a paucity of studies focused on public perception of FGM/C. We used machine learning methods to characterize discussion of FGM/C on Twitter in English from 2015 to 2020. Twitter has emerged in recent years as a source for seeking and sharing health information and misinformation. We extracted text metadata from user profiles to characterize the individuals and locations involved in conversations about FGM/C. We extracted major discussion themes from posts using correlated topic modeling. Finally, we extracted features from posts and applied random forest models to predict user engagement. The volume of tweets addressing FGM/C remained fairly stable across years. Conversation was mostly concentrated among the United States and United Kingdom through 2017, but shifted to Nigeria and Kenya in 2020. Some of the discussion topics associated with FGM/C across years included Islam, International Day of Zero Tolerance, current news stories, education, activism, male circumcision, human rights, and feminism. Tweet length and follower count were consistently strong predictors of engagement. Our findings suggest that (1) discussion about FGM/C has not evolved significantly over time, (2) the majority of the conversation about FGM/C on English-speaking Twitter is advocating for an end to the practice, (3) supporters of Donald Trump make up a substantial voice in the conversation about FGM/C, and (4) understanding the nuances in how people across cultures refer to and discuss FGM/C could be important for the design of public health communication and intervention.

Disparities in health condition diagnoses among aging transgender and cisgender medicare beneficiaries, 2008-2017.

Introduction: The objective of this research is to provide national estimates of the prevalence of health condition diagnoses among age-entitled transgender and cisgender Medicare beneficiaries. Quantification of the health burden across sex assigned at birth and gender can inform prevention, research, and allocation of funding for modifiable risk factors. Methods: Using 2009-2017 Medicare fee-for-service data, we implemented an algorithm that leverages diagnosis, procedure, and pharmacy claims to identify age-entitled transgender Medicare beneficiaries and stratify the sample by inferred gender: trans feminine and nonbinary (TFN), trans masculine and nonbinary (TMN), and unclassified. We selected a 5% random sample of cisgender individuals for comparison. We descriptively analyzed (means and frequencies) demographic characteristics (age, race/ethnicity, US census region, months of enrollment) and used chi-square and t-tests to determine between- (transgender vs. cisgender) and within-group gender differences (e.g., TMN, TFN, unclassified) difference in demographics (p<0.05). We then used logistic regression to estimate and examine within- and between-group gender differences in the predicted probability of 25 health conditions, controlling for age, race/ethnicity, enrollment length, and census region. Results: The analytic sample included 9,975 transgender (TFN n=4,198; TMN n=2,762; unclassified n=3,015) and 2,961,636 cisgender (male n=1,294,690, female n=1,666,946) beneficiaries. The majority of the transgender and cisgender samples were between the ages of 65 and 69 and White, non-Hispanic. The largest proportion of transgender and cisgender beneficiaries were from the South. On average, transgender individuals had more months of enrollment than cisgender individuals. In adjusted models, aging TFN or TMN Medicare beneficiaries had the highest probability of each of the 25 health diagnoses studied relative to cisgender males or females. TFN beneficiaries had the highest burden of health diagnoses relative to all other groups. Discussion: These findings document disparities in key health condition diagnoses among transgender Medicare beneficiaries relative to cisgender individuals. Future application of these methods will enable the study of rare and anatomy-specific conditions among hard-to-reach aging transgender populations and inform interventions and policies to address documented disparities.