Introduction

Members of the LGBT community represent sexual minorities, but transgender individuals represent the minority within this minority group; moreover, when it comes to health risks, health disparities, and negative health access experiences, being a racial minority further compounds these issues [1]. Health outcomes and health disparities for transgender African Americans in particular were not only worse when compared to the United States’ general population and other subgroups of the Lesbian, Gay, Bisexual, And Transgender (LGBT) population but also when compared to transgender people of other ethnic and racial groups [2,3]. For example, prevalence of HIV/AIDS among African American transgender individuals was 30 times higher than among Caucasian transgender individuals [1,4]. Furthermore, the National Transgender Discrimination Survey (NTDS) Report on Health and Health Care indicated that suicide attempts in African American transgender individuals were 7% higher than in Caucasian transgender individuals, and they had the highest rate of homelessness of all ethnic groups [1]. Additionally, African American respondents of the NTDS were 2% more likely to be denied health care, 9% more likely to postpone medical care due to fear of bias, and were three times as likely to be physically assaulted in a medical setting when compared to the overall transgender sample [1].

Even though data from the NTDS showed that African Americans were at a significant additional risk of discrimination due to the compounded influence of racial bias [1]; no measure yielded 100%. Therefore, it was evident that negative health access experiences were applicable to only some transgender African Americans, and which socioeconomic variables were associated with such experiences had yet to be analyzed. As a result, this study was conducted because significant results could provide a means of identifying those within the Black transgender community at highest risk of poor health outcomes resulting from negative health access experiences by determining socioeconomic commonalities of these individuals. The research question of this study asked “What was the correlation between socioeconomic variables and measures of negative health access experiences among transgender African Americans?” It was hypothesized that correlations existed between socioeconomic variables and measures of negative health access experiences among transgender African American. The framework for this study was the social ecological model which illustrated the interchange among the range of socioeconomic factors that put transgender African Americans at risk for negative health access experiences.

Materials and Methods

Utilizing secondary data from the NTDS yielded a sample size of 253 Black transgender respondents. This survey was fielded to transgender and gender nonconforming people from September 11, 2008 until March 3, 2009 via convenience, venue-based, and snowball sampling [1]. To address the research question of this study, the independent variables were socioeconomic variables: education, income, and employment. Dependent variables were negative health access experiences: denied medical care, verbally harassed or disrespected in medical setting, physically attacked or assaulted, postponement of medical care due to fear of bias, discrimination by medical providers, and medical providers’ lack of knowledge. To test the associations of socioeconomic factors with the likelihood of having negative health access experiences, logistic regressions were used - analyzed using SPSS statistical software. The inclusion criteria were the sample of the NTDS participants that selected transgender on Question 4, and Black on Question 11. Respondents were removed: if answers were illogical, if they indicated not being transgender, and if survey was incomplete, contained duplicate responses or informed consent not completed [1].

Odds ratios were calculated for the effects of the three socioeconomic variables on the likelihood of denial of medical care, being verbally harassed in a medical setting, being physically attacked or assaulted in a medical setting, experiencing postponement of medical care due to fear of bias, discrimination by medical providers, and experiencing medical providers’ lack of knowledge. These health access experiences were coded as dichotomous or binary indicators. The p value was assessed to determine the significance of the associations and the odds ratio was assessed to determine the strength of associations. Since the data were analyzed using a confidence interval of 90%, only correlations that yielded a p value of less than 0.1 were accepted as significant indicating a less than 10% chance of false positives. P values of less than 0.1 meant that the alternative hypotheses could be accepted and correlations existed and null hypotheses could be rejected; conversely, p values of more than 0.1 meant that the null hypotheses could not be rejected in favor of the alternative. Regarding strength of association the odds ratio was the indicator. A calculated odds ratio of more than 1.0 indicated that transgender people with the independent variable in question had higher odds of having negative health access experiences that those without that sociodemographic. Alternately, a calculated odds ratio of less than 1.0 indicated that transgender people with the sociodemographic in question had lesser odds of having negative health access experiences that those without that sociodemographic.

Results

The logistic regressions tested the correlational relationship between the independent, socioeconomic variables (education, income, employment) and each of the dependent variable (denied medical care, verbally harassed or disrespected in medical setting, physically attacked or assaulted, postponement of medical care due to fear of bias, discrimination by medical providers, and medical providers’ lack of knowledge.

Conclusion

In terms of socioeconomics, all of the variables (education, income, and employment) showed significant correlations with at least one of the negative health access experiences. Education showed significant correlations and increased odds of verbal harassment, postponement of health care due to fear of bias, and discrimination by medical providers. Higher education levels increased their likelihood of having negative health access experiences. This meant that for transgender African Americans, education could be used as a predictor for negative health access experiences but higher educational attainment did not shield them from negative health access experiences. Additionally, of the six negative health access experiences assessed, income showed a significant correlation and increased odds of discrimination by medical providers and also that as income increased the likelihood of this negative health access experience also increased.

However, income only showed a significant correlation to one of six measures of negative health access experiences. Even though higher income did not shield them from negative health access experiences, income was the weakest socioeconomic predictor of negative health access experiences. Lastly, compared to transgender African Americans who were not looking for work, those looking for work or currently working showed significant correlations and increased odds of verbal harassment, physical attack, and postponement due to fear of bias. It is concluded from the results that for transgender African Americans, socioeconomic variables could be used as a predictor for negative health access experiences; however, attainment of higher socioeconomics increased the likelihood of negative health access experiences.

Discussion

The findings of this study were complex, counterintuitive, and in some cases novel as no related research studies were found during the review of existing literature [5,6]. Higher educational attainment could have made transgender African Americans more aware and sensitive discrimination. Increased income could have pointed the finger toward discrimination because affording the health seeking experience might not have been the reason for the negative health access experience. Finally, having a job or looking for a job increased the likelihood of having health insurance or a more temporary lapse in health insurance when compared to those out of work and not looking; therefore, discrimination could have been credited with the negative health access experience versus inability to pay. The social ecological model promoted the understanding of the range of factors that influenced the risk of negative health access experiences. Based on the results of this study, a range of factors did predict the likelihood for negative health access experiences among transgender African Americans; education and income represented individual level factors, while employment represented a community level factor. In terms of socioeconomics, transgender African Americans who have earned high school diplomas and beyond, were in the workforce or looking to be, and earned an annual salary exceeding $10,000 were most at risk for negative health access experiences.

References

1. Grant JM, Mottet LA, Tanis J, Herman JL, Harrison J, et al. (2010) National transgender discrimination survey report on health and health care. National Center for Transgender Equality and the National Gay and Lesbian Taskforce.
2. Erich S, Tittsworth J, Kersten AS (2010). An examination and comparison of transsexuals of color and their White counterparts regarding personal well-being and support networks. Journal of GLBT Family Studies 6: 25-39.
3. Harrison-Quintana J, Lettman-Hicks S, Grant J (2011) Injustice at every turn: A look at Black respondents in the national transgender discrimination survey.
4. Samuel L, Zartitsky E (2008) Communicating effectively with transgender patients. American Family Physician 78: 648-650.
5. Center for Disease Control and Prevention (2011) Health, United States 2011: Special feature on socioeconomic statuses and health.
6. Kreuger PM, Hummer RA, Chang VW (2015) Mortality attributable to low levels of education in the United States. Plos One 10: e0131809.