*Purpose: Recent data from the United States Renal Data System (USRDS, 2020) indicate that 131, 636 patients were diagnosed with end-stage renal disease (ESRD) in 2018, a 2.3% increase from the previous year (USRDS, 2020). Although kidney transplantation has been reported as the most effective form of renal replacement therapy, factors such as race, gender and socioeconomic status continue to affect patients’ access to this treatment, resulting in disparities (McSorley et al., 2017; Nonterah & Gardiner, 2019; Patzer & Paston, 2013; Schold et al., 2011). Health literacy has been revealed as a contributing factor to reduced access to kidney transplantation, perpetuating disparities (Levy & Janke, 2016; Grubs et al., 2009). Yet, few studies have examined different disparities in health literacy and the ways in which they intersect to magnify a patient’s barrier to transplantation. The current study sought fill a gap in the literature by examining disparities in race, gender and income associated with health literacy as well as potential intersections between these disparities.

*Methods: Participants consisted of ESRD adult patients (N=181) with a mean age of 43.50 (SD =9.50) who reported experiencing transplant barriers. These participants were recruited from a transplant center in the Southeastern region of the US. Participants took a survey which consisted of demographic questions and all nine scales of the Health Literacy Questionnaire.

*Results: Multiple regression analyses were conducted to examine the associations between race, gender and income with health literacy. Results revealed a significant relationship between gender and feeling understood and supported by providers, having enough information to manage health, actively managing health, and appraisal of health information. Income was also significantly associated with these dimensions of health literacy. When gender, income, and the multiple effects of gender and income were placed in the model, the results revealed a significant regression equation between gender and feeling understood by providers, β =-.44 , t (175) = -2.306 , p = .022 well as the combined effect of gender and having a household income between $40,000-$79,999, β =.34, t (175) = 2.036 , p = .043.

*Conclusions: Overall, the findings from the current study suggest that gender differences contributed the most to the differences in health literacy with women reporting low health literacy relative to the men in our sample. Men in the middle-income range reported higher levels of health literacy. These results provide some evidence for additional research in this area, especially research that examines the multiple effects of different factors associated with disparities in health literacy.

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