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Poverty stigma is associated with suboptimal HIV care and treatment outcomes among women living with HIV in the United States

Leddy, Anna M.a; Turan, Janet M.b; Johnson, Mallory O.a; Neilands, Torsten B.a; Kempf, Mirjam-Colettec; Konkle-Parker, Deborahd; Wingood, Ginae; Tien, Phyllis C.f,g; Wilson, Tracey E.h; Logie, Carmen H.i; Weiser, Sheri D.j; Turan, Bulentk

Author Information
doi: 10.1097/QAD.0000000000002189

Abstract

Introduction

Low-income individuals are disproportionately affected by HIV [1], experience worse HIV-treatment outcomes [2], and have increased risk of HIV-related mortality [3–5]. Disparities in HIV-related health outcomes may be due to financial barriers in accessing HIV care and treatment [2]. However, studies suggest that socioeconomic disadvantage remains associated with worse HIV-related health outcomes even in the context of universal free access to health care [2,4], which suggests that the adverse effect of socioeconomic disadvantage on HIV-related health outcomes may go beyond access or affordability of care and treatment.

Stigma related to poverty may be one mechanism linking socioeconomic disadvantage to poor HIV-related health outcomes. Stigma is the process of labeling, separating, and discriminating against individuals possessing an attribute that is devalued by society [6]. Discrimination on the basis of these attributes is referred to as experienced stigma [7]. Low-income individuals have long been stigmatized in societies around the world [8]. Poverty stigma stems from the belief that one's economic status is dependent on individual effort [9]. As a result, individuals living in poverty are viewed as lazy and immoral because their status implies that they have not worked hard enough to raise themselves out of poverty [9,10].

Prior research suggests that experienced poverty stigma can negatively impact individuals’ health [11,12]. For example, qualitative studies suggest that low-income individuals can experience stigmatizing attitudes from health care or other service providers, which limits their willingness to access support services including health care, resulting in worse health outcomes [11,12]. However, to our knowledge no study has examined the effect of poverty stigma on HIV care and treatment outcomes. This is a particularly important area to explore given that HIV disproportionately affects low-income populations in the United States [1], and low-income individuals have increased risk for suboptimal HIV treatment outcomes [2]. We examined whether experienced poverty stigma is associated with worse HIV care and treatment outcomes while controlling for income levels and other markers of socioeconomic status.

Methods

Study design and sample

The Women's Interagency HIV Study (WIHS) is a multisite, prospective cohort study of women living with and at risk for HIV in the United States [13]. Biological, clinical, demographic, and behavioral data are collected semiannually through interviews, physical exams, and laboratory tests. Participants provide signed informed consent at each visit. The Women's Adherence and Visit Engagement (WAVE) substudy collects annual data on psycho-social aspects of living with HIV from women living with HIV on antiretroviral therapy (ART) enrolled at four WIHS sites: San Francisco, California, Atlanta, Georgia, Birmingham, Alabama, and Jackson, Mississippi. Participants in WAVE complete an interviewer-assisted data collection procedure during a separate research visit from their regular WIHS visit. WAVE survey data are linked with data collected through WIHS, which includes ART adherence and HIV visit adherence, as well as blood draws for assessment for HIV RNA level and CD4+ cell counts. The current study uses data from the first round of WAVE questionnaires (2016–2017; N = 453). Twenty participants were excluded from this analysis due to missing data on covariates of interest, leaving a final sample of 433.

Measures

Outcomes

Outcomes included HIV viral suppression, CD4+ cell count at least 350 cells/μl, and self-reported attendance of all HIV care visits in the past 6 months. HIV viral suppression was a binary variable, defined as less than 20 copies/ml. CD4+ cell count was dichotomized at 350 cells/μl, as has been done in previous research [14]. HIV care visit attendance was a binary variable derived from asking participants if they missed any HIV care appointments in the past 6 months (0) vs. missing no HIV care visits (1), as done in past research [15].

Exposure

Experienced poverty stigma was measured using a subscale of the perceived stigma of poverty scale (see Table, Supplemental Digital Content 1, which outlines the subscale items; http://links.lww.com/QAD/B474) [16]. Participants were asked to think about the past 12 months and to indicate how much they agreed with four statements using a five-point scale ranging from 1 (definitely disagree) to 5 (definitely agree). Scale scores were calculated by taking the mean of all four items. Internal consistency was strong in this sample (α = 0.88).

Covariates

Covariates included age at visit (continuous variable), average annual household income (≤$12 000, $12 001–$24 000, or ≥$24 001), education (high school education or more vs. less than a high school education), race/ethnicity (non-Hispanic white vs. other), any nonprescribed substance use since the last WIHS visit, months on ART (continuous), total number of antiretroviral pills in ART regimen (one pill vs. > one pill), current relationship status (in a sexual/romantic relationship vs. not), unstable housing, and ever exchanged sex for drugs, money, or shelter. Recent nonprescribed substance use was defined as self-reported cocaine, crack, heroin, methamphetamine, hallucinogens, club drugs, nonprescribed narcotics, or any other nonprescribed recreational drugs, excluding any form of marijuana, in the last 6 months. Unstable housing was defined as currently living in a halfway house, shelter, welfare house, on the street or in a residential drug or alcohol treatment facility (vs. an apartment or house). Covariates were included in multivariable models based on a priori knowledge from theory and existing literature of their potentially confounding relationship with poverty stigma and the three outcomes [17–19].

ART adherence was assessed by asking participants how often they took ART as prescribed over the past 6 months. Answer choices ranged from ‘100% of the time’ to ‘I haven’t taken any of my antiretroviral medications’. This variable was dichotomized to represent at least 95% adherence vs. less than 95% adherence, as done in prior research [18].

Analysis

Summary statistics were calculated on all study participants for all variables. Multivariable logistic regression models assessed the relationship between experienced poverty stigma and the three outcomes. Covariates hypothesized as potential mediators of the relationship between poverty stigma and the three outcomes were not included in the multivariable models. Multivariable models for viral suppression and CD4+ at least 350 cells/μl adjusted for all covariates. The multivariable model for HIV care visit attendance adjusted for all covariates except for the number of antiretroviral pills in ART regimen, as this variable was neither theoretically associated with visit attendance nor statistically significantly associated with visit attendance in bivariate analysis.

As an exploratory analysis, we assessed whether self-reported ART adherence mediated the relationship between experienced poverty stigma and viral suppression and CD4+ at least 350 cells/μl. This was done given evidence suggesting that ART adherence is critical to achieving viral suppression and improving CD4+ cell counts [20]. Mediation was assessed using indirect effects analysis with bootstrapping for dichotomous outcomes [21]. In this method, mediation is suggested when there is a significant indirect effect, which is indicated by a percentile bootstrapped confidence interval (CI) that does not include zero. All analyses were performed using STATA 15 [22].

All study activities were approved by each site's Institutional Review Board. This study was conducted in accordance with the principles outlined in the Declaration of Helsinki.

Results

The demographic characteristics of the sample are displayed in Table 1. Findings from the adjusted analyses of the association of experienced poverty stigma with the three outcomes are presented in Table 2. After adjusting for covariates, experienced poverty stigma was significantly associated with reduced odds of viral suppression [adjusted odds ratio (aOR) 0.76; 95% CI 0.61–0.96], reduced odds of having a CD4+ cell count of at least 350 cells/μl (aOR 0.69; 95% CI 0.52–0.91) and reduced odds of attending all HIV care visits in the past 6 months (aOR 0.73; 95% CI 0.54–0.98).

Table 1
Table 1:
Demographic characteristics (N = 433).
Table 2
Table 2:
Adjusted associations between experienced poverty stigma and outcomes.

Findings from the exploratory mediation analysis suggest that at least 95% ART adherence significantly mediates the relationship between experienced poverty stigma and viral suppression (coefficient −0.05; 95% CI −0.10 to –0.01) and having a CD4+ cell count of at least 350 cells/μl (coefficient −0.05; 95% CI −0.11 to –0.01) after adjusting for all covariates.

Discussion

The current study found that poverty stigma is significantly associated with lower odds of viral suppression, having a CD4+ cell count of at least 350 cells/μl, and attending all HIV care visits in the past 6 months even after adjusting for income level and education. These findings suggest that it is not only socioeconomic disadvantage that contributes to poor HIV care and treatment outcomes among this population, but that experienced poverty stigma may be an important independent contributor to negative health outcomes even after adjusting for indicators of poverty such as income, education, and unstable housing. To our knowledge, this is the first study that has explored the relationship of poverty stigma with HIV care and treatment outcomes. Other forms of stigma such as HIV stigma have similarly been associated with worse HIV treatment outcomes [19,23–26].

Findings from our exploratory mediation analysis suggest that the relationship between poverty stigma and the clinical outcomes of viral suppression and CD4+ cell count is mediated by a behavioral pathway of self-reported at least 95% ART adherence. This is supported by prior research documenting that ART adherence is critical to achieving viral suppression and improving CD4+ cell counts [20]. Other mechanisms may also explain the relationship between poverty stigma and HIV care and treatment outcomes, but exploring these were beyond the scope of this study.

In addition, low-income individuals, including those living with HIV, have reported perceived discrimination from healthcare providers based on their financial status [27,28], which has been associated with reduced engagement in healthcare [29], including HIV care and treatment [18,25,30]. Future research should explore how perceived discrimination from healthcare providers influences the relationship between poverty stigma and HIV care and treatment outcomes.

This study has several important limitations. Due to the cross-sectional design, we were unable to specify the temporal and causal relationship of poverty stigma, ART adherence and the HIV care and treatment outcomes. Longitudinal research is needed to assess the relationship of poverty stigma with HIV care and treatment outcomes over time, as well as potential mediators of this relationship. Given that the sample was from four primarily urban centers in the United States and consisted primarily of African American women, further research is needed to confirm these findings among women in other settings and of other racial/ethnic backgrounds, as well as among men.

Despite these limitations, this study is an important first-step to improve our understanding of the relationship between poverty stigma and HIV care and treatment outcomes among women living with HIV. Given how little is known about the effect of poverty stigma on health, future research should confirm these findings and explore the effects of poverty stigma on other health outcomes among people living with HIV. Such research could shed light on avenues for future interventions and policies to reduce poverty stigma and improve health outcomes among this population.

Acknowledgements

We wish to acknowledge the assistance of the WIHS program staff and the contributions of the participants who enrolled in this study. B.T., J.M.T., S.D.W., M.O.J., T.E.W., and C.H.L. conceived of and designed this study. M.-C.K., D.K.-P., G.W., and PT assisted with design and implementation of the study. A.M.L. led the analysis with assistance from B.T., J.M.T., and T.B.N. All authors contributed to the interpretation of the findings. A.M.L. wrote the article with input from all the authors. All authors read and approved the final article.

Conflicts of interest

P.C.T. receives research grant support from Merck and Theratechnologies. All remaining authors have nothing to disclose. This study was supported by Women's Interagency HIV Study (WIHS) substudy grants funded by the National Institute of Mental Health, R01MH104114 and R01MH095683, and the National Institute of Allergy and Infectious Diseases, K24AI134326, and WIHS grants as listed below. The contents of this publication are solely the responsibility of the authors and do not represent the official views of the National Institutes of Health (NIH). WIHS (Principal Investigators): UAB-MS WIHS (Mirjam-Colette Kempf and Deborah Konkle-Parker), U01-AI-103401; Atlanta WIHS (Ighovwerha Ofotokun and Gina Wingood), U01-AI-103408; Bronx WIHS (Kathryn Anastos and Anjali Sharma), U01-AI-035004; Brooklyn WIHS (Howard Minkoff and Deborah Gustafson), U01-AI-031834; Chicago WIHS (Mardge Cohen and Audrey French), U01-AI-034993; Metropolitan Washington WIHS (Seble Kassaye), U01-AI-034994; Miami WIHS (Margaret Fischl and Lisa Metsch), U01-AI-103397; UNC WIHS (Adaora Adimora), U01-AI-103390; Connie Wofsy Women's HIV Study, Northern California (Ruth Greenblatt, Bradley Aouizerat, and Phyllis Tien), U01-AI-034989; WIHS Data Management and Analysis Center (Stephen Gange and Elizabeth Golub), U01-AI-042590; Southern California WIHS (Joel Milam), U01-HD-032632 (WIHS I–WIHS IV). The WIHS is funded primarily by the National Institute of Allergy and Infectious Diseases (NIAID), with additional cofunding from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), the National Cancer Institute (NCI), the National Institute on Drug Abuse (NIDA), and the National Institute on Mental Health (NIMH). Targeted supplemental funding for specific projects is also provided by the National Institute of Dental and Craniofacial Research (NIDCR), the National Institute on Alcohol Abuse and Alcoholism (NIAAA), the National Institute on Deafness and other Communication Disorders (NIDCD), and the NIH Office of Research on Women's Health. WIHS data collection is also supported by UL1-TR000004 (UCSF CTSA), UL1-TR000454 (Atlanta CTSA), and P30-AI-050410 (UNC CFAR). This research was also supported by the University of Alabama at Birmingham (UAB) Center for AIDS Research CFAR, an NIH funded program (P30 AI027767) that was made possible by the following institutes: NIAID, NCI, NICHD, NHLBI, NIDA, NIA, NIDDK, NIGMS, and OAR. Finally, this research was also supported by grant T32MH19105 from the National Institutes of Mental Health of the United States Public Health Service.

References

1. Pellowski JA, Kalichman SC, Matthews KA, Adler N. A pandemic of the poor: social disadvantage and the U.S. HIV epidemic. Am Psychol 2013; 68:197–209.
2. Burch LS, Smith CJ, Phillips AN, Johnson MA, Lampe FC. Socioeconomic status and response to antiretroviral therapy in high-income countries: a literature review. AIDS 2016; 30:1147–1162.
3. Cunningham WE, Hays RD, Duan N, Andersen R, Nakazono TT, Bozzette SA, et al. The effect of socioeconomic status on the survival of people receiving care for HIV infection in the United States. J Health Care Poor Underserved 2005; 16:655–676.
4. Hogg RS, Strathdee SA, Craib KJ, O'Shaughnessy MV, Montaner JS, Schechter MT. Lower socioeconomic status and shorter survival following HIV infection. Lancet 1994; 344:1120–1124.
5. Joy R, Druyts EF, Brandson EK, Lima VD, Rustad CA, Zhang W, et al. Impact of neighborhood-level socioeconomic status on HIV disease progression in a universal health care setting. J Acquir Immune Defic Syndr 2008; 47:500–505.
6. Link BG, Phelan JC. Conceptualizing stigma. Ann Rev Sociol 2001; 27:363–385.
7. Goffman E. Stigma: notes on the management of spoiled identity. Englewood Cliffs, NJ: Prentice Hall; 1963.
8. Waxman CI. The stigma of poverty: a critique of poverty theories and policies. 2nd ed.Oxford, UK: Pergamon Press; 1983.
9. Williams WR. Struggling with poverty: Implications for theory and policy of increasing research on social class-based stigma. Anal Soc Issues Publ Policy 2009; 9:37–56.
10. Reutter LI, Stewart MJ, Veenstra G, Love R, Raphael D, Makwarimba E. “Who do they think we are, anyway?”: Perceptions of and responses to poverty stigma. Qual Health Res 2009; 19:297–311.
11. Whittle HJ, Palar K, Ranadive NA, Turan JM, Kushel M, Weiser SD. “The land of the sick and the land of the healthy”: Disability, bureaucracy, and stigma among people living with poverty and chronic illness in the United States. Soc Sci Med 2017; 190:181–189.
12. Allen H, Wright BJ, Harding K, Broffman L. The role of stigma in access to health care for the poor. Milbank Q 2014; 92:289–318.
13. Adimora AA, Ramirez C, Benning L, Greenblatt RM, Kempf M-C, Tien PC, et al. Cohort profile: the Women's Interagency HIV Study (WIHS). Int J Epidemiol 2018; 47:393–394i.
14. Galarraga O, Rana A, Rahman M, Cohen M, Adimora AA, Sosanya O, et al. The effect of unstable housing on HIV treatment biomarkers: an instrumental variables approach. Soc Sci Med 2018; 214:70–82.
15. Mugavero MJ, Westfall AO, Cole SR, Geng EH, Crane HM, Kitahata MM, et al. Beyond core indicators of retention in HIV care: missed clinic visits are independently associated with all-cause mortality. Clin Infect Dis 2014; 59:1471–1479.
16. Mickelson KD, Williams SL. Perceived stigma of poverty and depression: examination of interpersonal and intrapersonal mediators. J Soc Clin Psychol 2008; 27:903–930.
17. Langebeek N, Gisolf EH, Reiss P, Vervoort SC, Hafsteinsdottir TB, Richter C, et al. Predictors and correlates of adherence to combination antiretroviral therapy (ART) for chronic HIV infection: a meta-analysis. BMC Med 2014; 12:142.
18. Turan B, Rogers AJ, Rice WS, Atkins GC, Cohen MH, Wilson TE, et al. Association between perceived discrimination in healthcare settings and HIV medication adherence: mediating psychosocial mechanisms. AIDS Behav 2017; 21:3431–3439.
19. Turan B, Smith W, Cohen MH, Wilson TE, Adimora AA, Merenstein D, et al. Mechanisms for the negative effects of internalized HIV-related stigma on antiretroviral therapy adherence in women: the mediating roles of social isolation and depression. J Acquir Immune Defic Syndr 2016; 72:198–205.
20. Chesney M. Adherence to HAART regimens. AIDS Patient Care STDS 2003; 17:169–177.
21. Hayes AF. Introduction to mediation, moderation, and conditional process analysis: a regression-based approach. New York: Guilford Press; 2013.
22. StataCorp. Stata statistical software: release 15. College Station, Texas: StataCorp LLC; 2017.
23. Logie CH, Lacombe-Duncan A, Wang Y, Kaida A, Conway T, Webster K, et al. Pathways from HIV-related stigma to antiretroviral therapy measures in the HIV care cascade for women living with HIV in Canada. J Acquir Immune Defic Syndr 2018; 77:144–153.
24. Rice WS, Crockett KB, Mugavero MJ, Raper JL, Atkins GC, Turan B. Association between internalized HIV-related stigma and HIV care visit adherence. J Acquir Immune Defic Syndr 2017; 76:482–487.
25. Kay ES, Rice WS, Crockett KB, Atkins GC, Batey DS, Turan B. Experienced HIV-related stigma in health care and community settings: mediated associations with psychosocial and health outcomes. J Acquir Immune Defic Syndr 2018; 77:257–263.
26. Earnshaw VA, Smith LR, Chaudoir SR, Amico KR, Copenhaver MM. HIV stigma mechanisms and well-being among PLWH: a test of the HIV stigma framework. AIDS and Behavior 2013; 17:1785–1795.
27. Becker G, Newsom E. Socioeconomic status and dissatisfaction with health care among chronically ill African Americans. Am J Public Health 2003; 93:742–748.
28. Rice WS, Logie CH, Napoles TM, Walcott M, Batchelder AW, Kempf MC, et al. Perceptions of intersectional stigma among diverse women living with HIV in the United States. Soc Sci Med 2018; 208:9–17.
29. Trivedi AN, Ayanian JZ. Perceived discrimination and use of preventive health services. J Gen Intern Med 2006; 21:553–558.
30. Kinsler JJ, Wong MD, Sayles JN, Davis C, Cunningham WE. The effect of perceived stigma from a health care provider on access to care among a low-income HIV-positive population. AIDS Patient Care STDs 2007; 21:584–592.
Keywords:

HIV care and treatment; poverty stigma; United States; women living with HIV

Supplemental Digital Content

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