Socioeconomic position and ten-year survival and virologic outcomes in a Ugandan HIV cohort receiving antiretroviral therapy

Abstract

Lifelong ART is essential to reducing HIV mortality and ending the epidemic, however the interplay between socioeconomic position and long-term outcomes of HIV-infected persons receiving antiretroviral therapy (ART) in sub-Saharan Africa is unknown. Furthering the understanding of factors related to long-term ART outcomes in this important region will aid the successful scale-up of ART programs. We enrolled 559 HIV-infected Ugandan adults starting ART in 2004–2005 at the Infectious Diseases Institute in Kampala, Uganda and followed them for 10 years. We documented baseline employment status, regular household income, education level, housing description, physical ability, and CD4 count. Viral load was measured every six months. Proportional hazard regression tested for associations between baseline characteristics and 1) mortality, 2) virologic failure, and 3) mortality or virologic failure as a composite outcome. Over ten years 23% (n = 127) of participants died, 6% (n = 31) were lost-to-follow-up and 23% (107/472) experienced virologic treatment failure. In Kaplan-Meier analysis we observed an association between employment and mortality, with the highest cumulative probability of death occurring in unemployed individuals. In univariate analysis unemployment and disease severity were associated with mortality, but in multivariable analysis the only association with mortality was disease severity. We observed an association between higher household income and an increased incidence of both virologic failure and the combined outcome, and an association between self-employment and lower incidence of virologic failure and the combined outcome when compared to unemployment. Formal education level and housing status were unrelated to outcomes. It is feasible to achieve good ten-year survival, retention-in-care, and viral suppression in a socioeconomically diverse population in a resource-limited setting. Unemployment appears to be related to adverse 10-year ART outcomes. A low level of formal education does not appear to be a barrier to successful long-term ART.

Effects of HIV infection and ART on phenotype and function of circulating monocytes, natural killer, and innate lymphoid cells

“…Given that most of the evidence on the recovery of NK cells is from individuals after a short duration of ART, there is need to explore recovery of NK cell function after longer durations of ART. This is particularly important for sub-Saharan Africa which has more than 10 million people receiving ART majority of whom have been on treatment for more than 10 years [ 58 ].…”

Assessing rates and contextual predictors of 5-year mortality among HIV-infected and HIV-uninfected individuals following HIV testing in Durban, South Africa

“…barriers to care), emotional health, social support, and competing needs at the time of diagnosis, also likely to have an important effect on survival [16,17]. In addition, most mortality studies, including those that have examined social and contextual factors, have limited analyses to HIV-infected individuals [7,[18][19][20][21][22][23]. Little is known about contextual factors that predict long-term mortality in resource-limited settings, for both HIV-infected and HIV-uninfected individuals.…”

Predictors of mortality within the first year of initiating antiretroviral therapy in urban and rural Kenya: A prospective cohort study

“…There is mixed evidence regarding the association between socioeconomic status and short-term mortality among HIV-infected individuals initiating ART [12–15]. We found that greater years of education and employment were protective, and unemployment was also associated with not initiating ART (many non-initiators were known mortalities).…”

“…Prior studies in sub-Saharan Africa and other settings have identified sociodemographic predictors of early mortality including male gender [7, 9–11] and older age [7, 9, 10]. Measures of lower socioeconomic status [12, 13] and single marital status [13] have also been identified in some, though not all [14, 15] studies that investigated these factors. Clinical predictors of mortality include low CD4 count [7, 9, 10, 16] and low body mass index (BMI), weight loss, and malnutrition [7, 16].…”