Associations between HIV stigma and health-related quality-of-life among people living with HIV: cross-sectional analysis of data from HPTN 071 (PopART)

Abstract

People living with HIV (PLHIV) report lower health-related quality-of-life (HRQoL) than HIV-negative people. HIV stigma may contribute to this. We explored the association between HIV stigma and HRQoL among PLHIV. We used cross-sectional data from 3991 randomly selected PLHIV who were surveyed in 2017-2018 for HPTN 071 (PopART), a cluster randomised trial in Zambia and South Africa. Participants were 18-44 years, had laboratory-confirmed HIV infection, and knew their status. HRQoL was measured using the EuroQol-5-dimensions-5-levels (EQ-5D-5L) questionnaire. Stigma outcomes included: internalised stigma, stigma experienced in the community, and stigma experienced in healthcare settings. Associations were examined using logistic regression. Participants who had experienced community stigma (n = 693/3991) had higher odds of reporting problems in at least one HRQoL domain, compared to those who had not (adjusted odds ratio, aOR: 1.51, 95% confidence interval, 95% Cl: 1.16-1.98, p = 0.002). Having experienced internalised stigma was also associated with reporting problems in at least one HRQoL domain (n = 552/3991, aOR: 1.98, 95% CI: 1.54-2.54, p < 0.001). However, having experienced stigma in a healthcare setting was less common (n = 158/3991) and not associated with HRQoL (aOR: 1.04, 95% CI: 0.68-1.58, p = 0.850). A stronger focus on interventions for internalised stigma and stigma experienced in the community is required.

Figure 1

The association between experiencing any HIV stigma and reporting problems in five dimensions of health-related quality-of-life among 3991 people living with HIV from 21 study communities in South Africa and Zambia. Not experiencing any HIV stigma is the base category. An odds ratio greater than one shows those not in the base category are more likely to report “problems” in that health-related quality-of-life domain. Adjusted models include the covariates age, sex, education, wealth index, religion, recreational drug use, tuberculosis status, and marital status, with cluster robust standard errors to account for clustering by community.