Microaggressions and Discrimination Relate to Barriers to Care Among Black Women Living with HIV

Abstract

In the United States, black women living with HIV (BWLWH) represent the highest proportion of women living with HIV and dying from HIV-related illnesses when compared with women of other racial/ethnic groups. These disparities may be linked to social and structural factors faced by BWLWH, including race- and HIV-related discrimination, and gendered racial microaggressions (GRMs). GRMs are everyday insults that black women experience due to being both black and female (e.g., comments about their body). Commonly assessed barriers to HIV-related care (e.g., transportation, finance, community stigma) do not include personal experiences of race- and HIV-related discrimination and GRM. We present the cross-sectional associations between racial discrimination, HIV-related discrimination, GRM, and barriers to care. One hundred BWLWH in a large city in the Southeast United States completed baseline assessments as part of an intervention development study. At baseline assessments BWLWH completed measures on racial discrimination, HIV-related discrimination, GRM (frequency and appraisal), and barriers to care. Hierarchical multiple linear regressions controlling for age, education, and income indicated that higher race-related discrimination (β = 0.23, p < 0.05), higher HIV-related discrimination (β = 0.26, p < 0.01), and higher GRM (frequency: β = 0.31, p < 0.01; appraisal: β = 0.21, p < 0.05) significantly predicted higher total barriers to care. When all predictors were entered together GRMs contributed uniquely to total barriers to care and two subscales, while racial discrimination contributed uniquely toward one subscale. These findings further emphasize that for BWLWH interventions and policy efforts need to address racial discrimination, HIV-related discrimination, and GRM concurrently with other barriers to care, with special attention being given to daily GRM.

Introduction

Black women account for 59% of women living with HIV in the United States and are 10 times more likely to die from HIV/AIDS in comparison with all other women.^1,2 In addition, despite only making up ∼13% of the population of women in the United States,³ black women accounted for 61% of all new HIV diagnoses among women in 2016.² In fact, black heterosexual women, in particular, received more diagnoses of HIV than heterosexual black men, white women, and Hispanic/Latina women combined.⁴ These disparities continue across the treatment cascade for women with HIV in the United States with black women having lower treatment engagement, retention, and adherence.^5–7 Ongoing disparities in these areas for black women may be due to adversities such race- and HIV-related discrimination and microaggressions that contribute to barriers to receiving HIV-related care. However, no existing literature has explored how these factors relate to barriers to HIV-related care among black women living with HIV (BWLWH).

Common barriers to HIV care include transportation, housing, lack of money, distance to the clinic, availability of medical services, and community stigma.⁸ These barriers are problematic because they prevent people living with HIV from linking to care after initial diagnosis and remaining in care,⁹ and barriers result in a sequelae of negative health outcomes (e.g., viral failure).¹⁰ For instance, Colasanti et al.¹⁰ found that among a majority black sample of people living with HIV those who were not retained in care were not able to maintain viral load suppression, and common factors found among those unretained included food insecurity, financial and housing instability, and phone number changes. Similarly qualitative findings among BWLWH, substance use disorders, and other comorbid health conditions reported that barriers to managing their various health diagnoses included stigma, mental health symptoms, physician–patient trust, and limited information among community members.¹¹

Microaggression may be a barrier to health care engagement and treatment; however, it has been understudied for^12,13 BWLWH. Microaggressions are daily insults/slights such as jokes and comments that are meant to devalue/demean a marginalized group.¹⁴ Black women specifically experience gendered racial microaggressions (GRMs), which are microaggressions at the intersection of their identity as both women and black.¹⁵ Researchers^16,17 have noted that in a sample of 187 black women in college, 96% of women reported experiencing microaggressions at least a few times per year. Scholars have also noted that black women may be vulnerable to experiencing microaggressions due to the intersection of racism and sexism.^{12,16,18–20} Given the prevalence of microaggressions in the lives of black women, it may be beneficial to understand how GRMs relate to barriers to HIV care for BWLWH.

Unlike microaggressions, there is more literature on various types of discriminations and how they have been associated with negative health outcomes for people living with HIV. Researchers have found that discrimination and stigma based on race, sexual orientation, and HIV status are associated with lower visit adherence and lower treatment adherence.²¹ For instance, Rice et al.²² found that among black men and women living with HIV internalized stigma was associated with lower adherence to visits. Similarly, in a longitudinal study among HIV-positive black men who have sex with men (MSM), Bogart et al.²¹ found that greater discrimination due to HIV status, race, and sexual orientation predicted lower treatment adherence over a period of 6 months.²³ A systemic review by Geter et al.⁷ noted that providers perpetrate HIV stigma linked to their attitudes, beliefs, behaviors, quality of patient care, and education/training. Another meta-analytic review²⁴ highlighted that experiencing racism in a health care setting can lead to negative patient experiences and a decreased use of services overall. For instance, among black women who have sex with women, Brenick et al. found that discrimination based on race or sexual orientation was related to lower engagement in care.²⁵ While the literature still remains scant for BWLWH in particular, recent literature highlights that experiences of racial discrimination and HIV-related discrimination are important to understand BWLWH.^12,26

This study aims to bridge the gap in the literature by providing insight into the relationships between racial discrimination, HIV-related discrimination, and GRMs and barriers to HIV-related care among BWLWH. Findings from this study may improve our understanding of whether typical factors conceptualized as barriers to HIV care need to be addressed (in interventions and policy efforts) in tandem with race- and HIV-related discrimination and GRMs faced by BWLWH.

Methods

Participants

BWLWH were recruited in a large urban city in the Southeastern United States between October 2017 and August 2018 for a behavioral medicine intervention development trial aimed at addressing trauma symptoms and enhancing coping strategies for race- and HIV-related discrimination and gender-related stressors. To recruit women flyers and posters were distributed at hospitals, community clinics and health centers, community-based organizations, and community events. Research study staff members also engaged in active outreach and recruitment efforts by visiting clinics/organizations and building relationships with staff and attending community outreach events. Interested participants were screened for eligibility once they contacted the study staff. Participants who met the following inclusion criteria were eligible to be scheduled for an in-person baseline assessment at our academic medical institution: (1) identify as black and/or African American, (2) ≥18 years of age, (3) biologically female, (4) English speaking, (5) prescribed antiretroviral therapy (ART) for at least the last 2 months, (6) history of abuse/trauma (i.e., responding “yes” to “During your lifetime have your experienced trauma or abuse?”), and (7) possibility of low ART adherence, detectable viral load within the past year, and/or missed HIV-related medical visits within the past year.

At baseline assessment visits (two across 2 weeks) participants gave written informed consent, completed self-report measures through Research Electronic Data Capture (REDCap, a secure web-based application),²⁷ and engaged in a semistructured clinical interview. As reimbursement for their time and efforts participants were paid $50 total ($25 at baseline visit 1 and $25 at baseline visit 2) for the baseline assessment. All study procedures and measures were approved by the Institutional Review Boards of the University of Miami.

Measures

Self-report sociodemographic survey

This survey captured information, including their age, country of birth, education level, annual income, employment status, living situation, number of children, religious affiliation, relationship status, sexual orientation, and years since HIV diagnosis.

Multiple Discrimination Scale

To capture race-related discrimination and HIV-related discrimination we used 26 items from the Multiple Discrimination Scale (MDS).^8,28 Thirteen items assessed HIV-related discrimination and the other 13 parallel items assessed race-related discrimination. Items asked participants to respond “yes” or “no” to whether they experienced 13 different discrimination events (e.g., interpersonal or institutional discrimination) in the past year. Two sample items are as follows: “In the past, were you ignored, excluded, or avoided by people close to you because you are HIV positive?” and “In the past year, were you denied a job or did you lose a job because you are black or African-American?” Total scores (sum) range from 0 to 13. The MDS has demonstrated good construct validity (e.g., associated with mental health symptoms^21,28,29) and good reliability (HIV subscale α = 0.85 and race subscale α = 0.83).²⁸ In the present sample Cronbach's alpha values for the race-related discrimination subscale and the HIV-related discrimination subscale were 0.86 and 0.87, respectively.

GRMs scale–black women (GRMS-BW)

The GRMS-BW measures the frequency (how often each event happened) and stress appraisal (how stressful each experience was) of microaggressions experienced by black women on the basis of being both black and women.¹⁵ In addition to the frequency and appraisal scales the GRMS-BW has four subscales—Assumptions of Beauty and Sexual Objectification subscale, Silenced and Marginalized subscale, Strong Black Woman subscale, and Angry Black Woman subscale. Three sample items are “I have been told I am too independent,” “Someone made a negative comment to me about my skin color/skin tone,” and “Someone accused me of being angry when I was speaking in a calm manner.” Participants select how often in their lifetime they experienced a microaggression (0 = never, 1 = less than once a year …. 5 = once a week or more) and how stressful the experience was for them (0 = never happened, 1 = not at all stressful …5 = extremely stressful). Total average scores on both the frequency and appraisal scales range from 0 to 5. This scale has evidence of good validity and reliability (appraisal α = 0.93 and frequency α = 0.92) in the existing literature,¹⁵ and good reliability in the current sample (appraisal α = 0.95 and frequency α = 0.92).

Barriers to Care Scale

The Barriers to Care Scale (BACS) is a 12-item scale that captures barriers to receiving care for people living with HIV in terms of psychosocial, geographical, and resource-related barriers.^28,29 It has four corresponding subscales: Geography/distance, Medical and psychological, Community stigma, and Personal resources. Sample items include the following: “Long distances to medical facilities and personnel” (Geography/distance), “My personal financial resources” (Personal resources), “Community residents' stigma against persons living with HIV/AIDS” (Community stigma), and “The shortage of psychologists, social workers, and mental health counselors who can help address mental health issues” (Medical and psychological). Participants respond to each item on a 4-point Likert scale by rating the extent to which each barrier makes it difficult to receive care (e.g., 1 = no problem at all, 4 = major problem). Total score ranges from 1 to 4, and is calculated by summing the 12 items and dividing by 12. Similarly total (average) scores for each subscale range from 1 to 4. The BACS demonstrated good reliability (α = 0.86 for overall scale and 0.73–0.78 for subscales) and validity (e.g., related to HIV nondisclosure) in previous literature,^8,30 as well as good validity in the present sample (α = 0.94).

Analyses

SPSS version 24 was used in running all statistical analyses. All 100 participants who completed baseline assessments were included in analyses. Hierarchical linear regressions controlling for age, education, and income were conducted to examine the associations between race-related discrimination, HIV-related discrimination, GRMs (frequency and appraisal), and barriers to care.

Results

Sociodemographic characteristics

The sociodemographic information for the 100 BWLWH who participated in this baseline assessment study is presented in Table 1. In sum, women's average age was 49 (range = 22–67), 63.5% had a high school level education or above, 62% had an annual income of <$12,000, 62% were on disability, 55% lived by herself, and 82% were parents of children.

Table 1.

Sociodemographics and Characteristics of Black Women Living with HIV

Characteristic	Mean (SD, range) or n (%)
Age	49.25 (10.89, 22–67)
Missing	0 (0)
Education
Eighth grade or lower	5 (5)
Some high school	31 (31)
High school graduate/GED	34 (34)
Some college	24 (24)
College graduate	5 (5)
Some graduate school	1 (1)
Missing	0 (0)
Place of birth
US born	98 (98)
Non-US born	2 (2)
Missing	0 (0)
Religion
Christian	26 (26)
Catholic	4 (4)
Baptist	53 (53)
None	7 (7)
Other	8 (8)
Missing	2 (2)
Parents of children
Yes	83 (83)
No	16 (16)
Missing	1 (1)
No. of children	2.78 (1.562, 1–9)
Missing	0 (0)
Relationship status
Married	14 (14)
Cohabiting relationship, unmarried	14 (14)
Noncohabiting relationship	13 (13)
Single	47 (47)
Divorced/separated	7 (7)
Widow or loss of partner	3 (3)
Missing	2 (2)
Sexual orientation
Exclusively heterosexual	76 (76)
Heterosexual, some homosexual	9 (9)
Experience
Bisexual	6 (6)
Exclusively homosexual	4 (4)
Choose not to answer	1 (1)
Missing	4 (4)
Employment status
Full-time work	5 (5)
Part-time work	6 (6)
Full- or part-time school	4 (4)
Not working or in school	18 (18)
On disability	62 (62)
Other	6 (6)
Missing	0 (0)
Income ($)
<5000	36 (36)
5000–11,999	27 (27)
12,000–15,999	7 (7)
16,000–24,999	4 (4)
25,000–34,999	2 (2)
35,000–49,999	0 (0)
≥50,000	3 (3)
Choose not to answer or don't know	21 (21)
Missing	0 (0)
Living situation
Lives with self	55 (55)
Partner/spouse	19 (19)
Roommates	5 (5)
Children	25 (25)
Group home or residential treatment	1 (1)
Other	21 (21)
Missing	0 (0)
Housing arrangement
Renting home or apartment	72 (72)
Owned by you or someone else in household	10 (10)
Publicly subsidized housing	9 (9)
A friend or relative's home/apartment	5 (5)
Homeless: sleeping in a shelter	1 (1)
Homeless: sleeping on the street, beach, car	1 (1)
Missing	2 (2)
Race-related discrimination	1.83 (2.62), 0–13
Missing	2 (2)
HIV-related discrimination	1.27 (2.34), 0–13
Missing	3 (3)
GRMs (F)	1.09 (0.90), 0–5)
Missing	3 (3)
GRMs (A)	2.18 (0.99), 0–5)
Missing	8 (8)
Barriers to care	1.86 (0.87), 1–4
Missing	6 (6)
Geography/distance	1.65 (0.95), 1–4
Missing	7 (7)
Medical and psychological	1.63 (0.89), 1–4
Missing	6 (6)
Community stigma	2.07 (1.15), 1–4
Missing	7 (7)
Personal resources	2.08 (1.08), 1–4
Missing	6 (6)

A, appraisal–how stressful each experience was; F, Frequency–how often each event happened.

GRM, gendered racial microaggression; SD, standard deviation.

Multi-variable associations of discrimination, microaggressions, and barriers to care

Hierarchical multiple linear regressions were conducted to assess the relationships between predictors [race-related discrimination, HIV-related discrimination, and GRM (frequency or appraisal)] and outcomes (barriers to care total score and subscales of geography/distance, medical and psychological, community stigma, and personal resources). We entered covariates of age, education, and income in block 1, one predictor in block 2, and one outcome as the dependent variable. Results presented in Table 2 indicated that higher race-related discrimination (β = 0.23, p < 0.05), HIV-related discrimination (β = 0.26, p < 0.01), and GRMs (frequency: β = 0.32, p < 0.01; appraisal: β = 0.21, p < 0.05) significantly predicted higher total barriers to care.

Table 2.

Hierarchical Linear Regressions of Microaggressions, Discrimination, and Barriers to Care

Dependent variables	B	Standard error	Standardized coefficients beta	t	p	Missing, n (%)
Total barriers to care
Race-related discrimination	0.076	0.032	0.230	2.342	0.021	6 (6)
HIV-related discrimination	0.096	0.036	0.259	2.659	0.009	6 (6)
GRM-A	0.188	0.089	0.213	2.115	0.037	10 (10)
GRM-F	0.302	0.092	0.312	3.299	0.001	7 (7)
Geography and distance
Race-related discrimination	0.073	0.034	0.207	2.129	0.036	7 (7)
HIV-related discrimination	0.086	0.039	0.216	2.231	0.028	7 (7)
GRM-A	0.071	0.097	0.074	0.732	0.466	11 (11)
GRM-F	0.190	0.102	0.180	1.858	0.066	8 (8)
Medical and psychological
Race-related discrimination	0.055	0.035	0.163	1.579	0.118	6 (6)
HIV-related discrimination	0.094	0.038	0.250	2.466	0.016	6 (6)
GRM-A	0.150	0.095	0.166	1.572	0.120	10 (10)
GRM-F	0.246	0.099	0.249	2.474	0.015	7 (7)
Community stigma
Race-related discrimination	0.120	0.042	0.280	2.855	0.005	7 (7)
HIV-related discrimination	0.072	0.049	0.149	1.476	0.143	7 (7)
GRM-A	0.273	0.117	0.235	2.328	0.022	11 (11)
GRM-F	0.392	0.122	0.309	3.225	0.002	8 (8)
Personal resources
Race-related discrimination	0.081	0.040	0.198	2.008	0.048	6 (6)
HIV-related discrimination	0.118	0.045	0.258	2.654	0.009	6 (6)
GRM-A	0.250	0.110	0.228	2.279	0.025	10 (10)
GRM-F	0.372	0.114	0.310	3.276	0.002	7 (7)

A, appraisal–how stressful each experience was; F, frequency–how often each event happened.

GRM, gendered racial microaggression.

Similarly, race-related discrimination, HIV-related discrimination, and GRMs significantly predicted some of the barriers to care subscales, but not all. Higher race-related discrimination predicted higher barriers in the areas of geography/distance (β = 0.21, p < 0.05), community stigma (β = 0.28, p < 0.01), and personal resources (β = 0.20, p < 0.05). Higher HIV-related discrimination predicted higher barriers in terms of geography/distance (β = 0.22, p < 0.05), medical and psychological (β = 0.25, p < 0.05), and personal resources (β = 0.26, p < 0.01). Higher GRMs predicted higher barriers in the areas of medical and psychological (frequency: β = 0.25, p < 0.05), community stigma (frequency: β = 0.31, p < 0.01; appraisal: β = 0.24, p < 0.05), and personal resources (frequency: β = 0.31, p < 0.01; appraisal: β = 0.23, p < 0.05). Racial discrimination was not significantly related to medical and psychological barriers, and HIV-related discrimination was not significantly associated with community stigma barriers.

Multi-variable associations of predictors of discrimination and microaggressions entered together and outcome of barriers to care

To determine whether any of the predictors made unique contributions (above the other predictors) to overall barriers to care or its subscales we conducted additional hierarchical multiple regressions. We entered all the predictors together [race-related discrimination, HIV-related discrimination, and GRM (frequency or appraisal)] with covariates (age, education, and income) and outcomes of either barriers to care total score, geography/distance subscale, medical and psychological subscale, community stigma subscale, or personal resources subscale. Findings (Tables 3 and 4) indicated that GRM frequency contributed uniquely to total barriers to care (β = 0.25, p < 0.05), and both the personal resources (β = 0.27, p < 0.05) and community stigma (β = 0.25, p < 0.05) subscales (Table 4). In addition, racial discrimination contributed uniquely to the community stigma subscale (β = 0.26, p < 0.05; Table 3).

Table 3.

Hierarchical Linear Regression of Microaggressions (Appraisal), Discrimination, and Barriers to Care (Predictors Entered Together)

Dependent variables	B	Standard error	Standardized coefficients beta	t	p	Missing, N (%)
Total barriers to care
Age	−0.020	0.008	−0.249	−2.510	0.014	10 (10)
Education	0.130	0.083	0.154	1.563	0.122
Race-related discrimination	0.027	0.042	0.083	0.660	0.511
HIV-related discrimination	0.067	0.046	0.179	1.455	0.149
GRM-A	0.107	0.096	0.122	1.122	0.265
Geography and distance
Age	−0.028	0.009	−0.318	−3.207	0.002	11 (11)
Education	0.151	0.090	0.165	1.673	0.098
Race-related discrimination	0.048	0.045	0.133	1.056	0.294
HIV-related discrimination	0.067	0.050	0.164	1.338	0.184
GRM-A	−0.032	0.105	−0.034	−0.308	0.759
Medical and psychological
Age	−0.010	0.009	−0.127	−1.223	0.225	10 (10)
Education	0.104	0.089	0.121	1.171	0.245
Race-related discrimination	0.000	0.045	0.001	0.008	0.994
HIV-related discrimination	0.091	0.050	0.237	1.840	0.069
GRM-A	0.079	0.103	0.087	0.764	0.447
Community stigma
Age	−0.015	0.011	−0.140	−1.406	0.163	11 (11)
Education	0.297	0.109	0.270	2.719	0.008
Race-related discrimination	0.111	0.055	0.257	2.019	0.047
HIV-related discrimination	−0.019	0.061	−0.038	−0.305	0.761
GRM-A	0.170	0.127	0.146	1.342	0.183
Personal resources
Age	−0.028	0.010	−0.276	−2.781	0.007	10 (10)
Education	0.066	0.103	0.063	0.641	0.523
Race-related discrimination	0.008	0.052	0.019	0.148	0.883
HIV-related discrimination	0.087	0.058	0.187	1.517	0.133
GRM-A	0.174	0.119	0.159	1.463	0.147

A, appraisal–how stressful each experience was; F, frequency–how often each event happened.

GRM, gendered racial microaggression.

Table 4.

Hierarchical Linear Regression of Microaggressions (Frequency), Discrimination, and Barriers to Care (Predictors Entered Together)

Dependent variables	B	Standard error	Standardized coefficients beta	t	p	Missing, N (%)
Total barriers to care
Age	−0.023	0.008	−0.278	−2.909	0.005	7 (7)
Education	0.119	0.082	0.141	1.458	0.148
Race-related discrimination	−0.002	0.044	−0.005	−0.038	0.970
HIV-related discrimination	0.048	0.045	0.129	1.047	0.298
GRM-F	0.242	0.119	0.250	2.040	0.044
Geography and distance
Age	−0.028	0.009	−0.324	−3.331	0.001	8 (8)
Education	0.153	0.090	0.168	1.708	0.091
Race-related discrimination	0.031	0.048	0.089	0.651	0.517
HIV-related discrimination	0.051	0.050	0.129	1.026	0.308
GRM-F	0.062	0.134	0.059	0.465	0.643
Medical and psychological
Age	−0.013	0.008	−0.152	−1.502	0.137	7 (7)
Education	0.098	0.088	0.114	1.116	0.268
Race-related discrimination	−0.025	0.047	−0.075	−0.536	0.594
HIV-related discrimination	0.071	0.049	0.190	1.455	0.149
GRM-F	0.195	0.128	0.198	1.527	0.131
Community stigma
Age	−0.019	0.010	−0.177	−1.827	0.071	8 (8)
Education	0.286	0.108	0.258	2.645	0.010
Race-related discrimination	0.074	0.058	0.173	1.277	0.205
HIV-related discrimination	−0.042	0.060	−0.088	−0.702	0.485
GRM-F	0.315	0.158	0.249	1.998	0.049
Personal resources
Age	−0.031	0.010	−0.307	−3.211	0.002	7 (7)
Education	0.047	0.101	0.045	0.463	0.645
Race-related discrimination	−0.025	0.054	−0.063	−0.472	0.638
HIV-related discrimination	0.070	0.056	0.153	1.238	0.219
GRM-F	0.325	0.147	0.271	2.210	0.030

A, appraisal–how stressful each experience was; F, frequency–how often each event happened.

GRM, gendered racial microaggression.

Discussion

Barriers to care for HIV are often thought of in isolation to additional structural adversities (i.e., discrimination, microaggressions); however, this study among BWLWH shows that race-related discrimination, HIV-related discrimination, and GRMs are all significantly associated with higher barriers to care and therefore may need to be considered together at all times. Discrimination (race- and HIV related) and GRMs may be related to barriers to care, because they are all linked to oppression be it at the structural, institutional, or interpersonal level. As a result of oppression (e.g., racism, sexism) at the structural and institutional levels (e.g., laws, policies, practices) black women may be geographically distanced and without adequate transportation infrastructure to reach medical centers, not have easy access to available, adequately trained, and competent medical providers, and lack employment opportunity, financial resources, and access to affordable housing.^31–37 Oppression at the interpersonal level may be experienced by BWLWH in the form of racial discrimination, HIV-related discrimination, and GRMs. Therefore, our associations found between discrimination and barriers to care may be because they share a common driver, oppression. We also found that racial discrimination contributed uniquely to the community stigma subscale. However, the frequency of GRMs among our sample of black women contributed uniquely to the total barriers to care and the personal resources and community stigma subscales above and beyond the contributions of race-related discrimination and HIV-related discrimination. This may be due to the nature of GRMs being everyday occurrences.

Our additional findings indicated that race-related discrimination, HIV-related discrimination, and GRMs related to at least three of four barriers to care subscales, indicating that discrimination and microaggressions experienced by black women contribute to barriers to care in terms of distance, medical and psychological services, community stigma, and personal resources (e.g., housing, employment). Specifically, race-related discrimination predicted higher barriers in terms of geography/distance, community stigma, and personal resources (e.g., finance and jobs), and indicated that race-related discrimination may be associated with barriers to care in these domains, as well as both racial discrimination and barriers to care being expressions of the overarching factor of oppression. This is consistent with the literature noting racial discrimination in housing and employment, and that targeted HIV prevention campaigns may unintentionally perpetuate stigma of the black community.^37–40 Surprisingly, racial discrimination was not significantly associated with medical and psychological service barriers, although the p = 0.12 suggested a potential trend. A lack of significance finding is contrary to the existing literature^31,32,40 such as a study by Kugelmass,³³ noting that mental health providers were less likely to return phone calls when callers sounded black.

HIV-related discrimination was also significantly associated with all but one subscale of barriers to care. HIV-related discrimination was associated with barriers to care in the terms of geography/distance, medical and psychological, and personal resources, but not community stigma. HIV-related discrimination may impact women's personal resources (e.g., jobs, finances) and access to competent medical and psychological providers.⁴¹ Experiencing HIV discrimination in a community may also lead women to move further away where their HIV status is unknown to others.⁴² In addition, where women live may also be influenced by their HIV status in that HIV-specific housing resources may exist in certain locations beyond the women's control. The lack of association between HIV-related discrimination and community stigma was unexpected although p = 0.14. One would expect a significant association given that the community stigma subscale of the barriers to care measure asked how much of a problem to receiving care were “community residents stigma against persons living with HIV” and “the level of knowledge about HIV among residents in the community.” However, the measure of HIV-related discrimination asked whether women experienced 13 HIV-related discrimination events (e.g., housing, job, law enforcement, friends) in the past year,²⁹ which were not restricted to discrimination by community residents nor their knowledge. Further, women living with HIV may selectively disclose their HIV status to some people in their lives,²⁶ which may exclude community residents and prevent potential discrimination acts by community residents.

Consistent with the associations found for race- and HIV-related discriminations, GRMs were significantly related to three domains of barriers to care (medical and psychological, community stigma, and personal resources) and showed a trend of relating to geography/distance (p = 0.07 for GRM frequency). Together this echoes the relevance of GRMs to barriers to care for BWLWH. At the intersection of being black and woman living with HIV, women face both (a) the structural/institutional oppression that impact where they live, access to competent medical/psychological services, community stigma (e.g., knowledge of HIV), and their finances, employment, and housing^34,43–46 and (b) oppression at the interpersonal level in the form of everyday insults based on their race and gender. The GRMs may also block access to and/or create intolerable conditions for BWLWH to get competent medical/psychological services, housing in desirable geographical locations, employment, and financial resources. Further, with HIV being a sexually transmitted infection and black women being sexualized and objectified by some GRMs, community stigma about HIV may be conveyed in ways linked to GRMs.

While our findings provide interesting insights, there are a few limitations: first, we recruited our sample of BWLWH in a large city in the Southeast United States, and all women reported histories of trauma and as such our findings may not generalize easily to other context/geographical locations or women without histories of trauma. Second, this was a cross-sectional study design with variables on barriers to care, discrimination, and microaggressions collected at one time point. Therefore we are unable to draw conclusions about the relationships between these variables. Despite these limitations our findings provide novel insights about the relationships between discrimination, microaggressions, and barriers to care, and suggest that barriers to HIV care need to be addressed/discussed concurrently with discrimination and microaggressions faced by BWLWH. In addition, future research needs to explore potential pathways/mechanisms through which discrimination and microaggressions may impact barriers to care to better inform potential interventions.

There is a gap in the existing literature on how common barriers to care (e.g., personal resources, distance, community stigma) are linked to personal experiences of race- and HIV-related discrimination and microaggressions. Our study among black women with HIV found that higher racial discrimination, HIV-related discrimination, and GRMs relate to higher barriers to care. These findings both add to the literature and echo that for BWLWH interventions and policy efforts need to address racial discrimination, HIV-related discrimination, and GRMs concurrently with barriers to care. In fact, racial discrimination, HIV-related discrimination, and GRMs need to be viewed as barriers to care in and of themselves. This may be the case especially for gendered racial microaggressions, which are subtle yet pervasive and contributed uniquely to barriers to care above and beyond the contributions of race- and HIV-related discrimination.

Author Disclosure Statement

No competing financial interests exist.