Male sex and the risk of mortality among individuals enrolled in antiretroviral therapy programs in Africa: a systematic review and meta-analysis

Druyts, Erica; Dybul, Markb; Kanters, Stevec; Nachega, Jeand; Birungi, Josephinee; Ford, Nathanf; Thorlund, Kristiang; Negin, Joelh; Lester, Richardi; Yaya, Sannia; Mills, Edward J.a,g

doi: 10.1097/QAD.0b013e328359b89b
Epidemiology and Social

Background: HIV/AIDS has historically had a sex and gender-focused approach to prevention and care. Some evidence suggests that HIV-positive men have worse treatment outcomes than their women counterparts in Africa.

Methods: We conducted a systematic review and meta-analysis of the effect of sex on the risk of death among participants enrolled in antiretroviral therapy (ART) programs in Africa since the rapid scale-up of ART. We included all cohort studies evaluating the effect of sex (male, female) on the risk of death among participants enrolled in regional and national ART programs in Africa. We identified these studies by searching MedLine, EMBASE, and Cochrane CENTRAL. We used a DerSimonian-Laird random-effects method to pool the proportions of men receiving ART and the hazard ratios for death by sex.

Results: Twenty-three cohort studies, including 216 008 participants (79 892 men) contributed to our analysis. The pooled proportion of men receiving ART was 35% [95% confidence interval (CI): 33–38%]. The pooled hazard ratio estimate indicated a significant increase in the risk of death for men when compared to women [hazard ratio: 1.37 (95% CI: 1.28–1.47)]. This was consistent across sensitivity analyses.

Interpretation: The proportion of men enrolled in ART programs in Africa is lower than women. Additionally, there is an increased risk of death for men enrolled in ART programs. Solutions that aid in reducing these sex inequities are needed.

Author Information

aFaculty of Health Sciences, University of Ottawa, Ottawa, Ontario, Canada

bO’Neill Institute for National and Global Health Law, Georgetown University, Washington, District of Columbia, USA

cFaculty of Health Sciences, Simon Fraser University, Burnaby, British Columbia, Canada

dCentre for Infectious Diseases, University of Stellenbosch, Stellenbosch, South Africa

eThe AIDS Support Organization (TASO), Kampala, Uganda

fInternational Office, Médecins Sans Frontiers, Geneva, Switzerland

gDepartment of Clinical Epidemiology & Biostatistics, McMaster University, Hamilton, Ontario, Canada

hSchool of Public Health, University of Sydney, Sydney, New South Wales, Australia

iBritish Columbia Centre for Disease Control, Vancouver, British Columbia, Canada.

Correspondence to Edward J. Mills, Faculty of Health Sciences, University of Ottawa, 43 Templeton Street, Ottawa, ON K1N6X1, Canada. E-mail:

Received 22 June, 2012

Revised 15 August, 2012

Accepted 24 August, 2012

Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal's Website (

Article Outline
Back to Top | Article Outline


An estimated 5.1 million people in sub-Saharan Africa received antiretroviral therapy (ART) in 2010, representing about 49% of those eligible for treatment [1]. These efforts have been largely possible through substantial increases in funding from initiatives such as the Global Fund To Fight AIDS, Tuberculosis and Malaria (Global Fund) and the United States President's Emergency Plan for AIDS Relief [2,3], and through the widespread uptake of a WHO public health approach that called for simplification of treatment protocols and decentralization of service delivery [4].

As ART continues to become more accessible throughout Africa, questions arise regarding equitable access to treatment. The rapid scale-up of ART has historically focused on women and children, supported by high-level political declarations committing to increasing access to treatment for women [5] and national strategies that focus on sex and women's issues in HIV/AIDS [6]. Major funding agencies have also made women and children's treatment the backbone of ART programs [7]. These factors have generally resulted in greater numbers of women and children accessing HIV-related care and treatment at a much earlier time point than men [1].

There is now a growing body of evidence indicating that men face important challenges in terms of HIV vulnerability [8,9]. In particular, men appear to not access HIV services as often as their female counterparts and also have worse treatment outcomes, including mortality [10,11]. We conducted a systematic review and meta-analysis to examine the magnitude of this overall mortality imbalance among participants enrolled in ART programs in Africa since the year 2000.

Back to Top | Article Outline


We conducted this systematic review and meta-analysis according to the criteria set forth by the Meta-analysis of Observational Studies in Epidemiology (MOOSE) group [12]. Online Appendix 1 ( provides a completed MOOSE criteria checklist for our study.

Back to Top | Article Outline
Eligibility criteria

We included regional and national observational cohort studies evaluating the variable sex (male, female) on the risk of death among participants enrolled in ART programs in the WHO African Region since the year 2000. We excluded studies that assessed participant outcomes prior to ART initiation, studies evaluating predominantly children and/or adolescents, studies only evaluating the risk of early mortality (e.g. mortality within the first 6 months of ART), studies that combined loss to follow-up with deaths, studies evaluating workplace programs, case–control and cross-sectional studies, and clinical trials. All languages were considered, and translation services were available if required. When we identified a study that incorporates a smaller cohort, we derived the data from the larger cohort (i.e. a complete national cohort).

Back to Top | Article Outline
Search strategy

In consultation with a medical librarian, we conducted a systematic search of the peer-reviewed published literature. Independently, two of us (E.D. and E.J.M.) searched the following electronic databases [from week 1 (3–9 January) 2000 to week 1 (2–8 January) 2012]: MedLine via PubMed, EMBASE, and Cochrane Central. We used the following terms for our search, including their MeSH terms: HIV, AIDS, ART, anti-HIV agents, survival, mortality, death, Africa, sub-Saharan Africa, and the names of the individual countries in the WHO African Region. We also searched the reference lists of published systematic and narrative reviews for relevant studies to include. An example of a full electronic search strategy (PubMed) utilized is given in online Appendix 2 (

Back to Top | Article Outline
Study selection

Two investigators (E.D. and E.J.M.) working independently, in duplicate, scanned all abstracts and obtained the full text reports of records indicating that the study evaluated mortality, death, or survival outcomes. After obtaining full reports of the candidate studies, E.D. and E.J.M. independently assessed each to determine if they met the eligibility criteria. The candidate studies were also reviewed to ensure there was no overlapping or repetitive cohort data included. For cohorts providing multiple evaluations, the most recent study data were utilized. For cohorts providing multiple mortality assessments, for example, at 6 and 12 months, we took the latter value because we were interested in long-term mortality outcomes. A quality assessment of each study was conducted using the Newcastle-Ottawa Quality Assessment Scale for cohort studies [13]. Any disagreement in the selection of studies was resolved through arbitration by a third investigator (N.F.).

Back to Top | Article Outline
Data extraction

Two investigators (E.D. and E.J.M.) extracted data on our primary variable of interest, sex (male, female), on the risk of death, most commonly reported by the hazard ratio [14]. E.D. and E.J.M. also abstracted data on the following cohort characteristics: the proportion of participants by sex, baseline age, baseline CD4 cell count, baseline WHO disease stage, baseline tuberculosis coinfection, baseline pregnancy rate, number lost to follow-up, and the duration of follow-up. Additionally, the cohort name, site, region, and country, and the reporting period were abstracted. Any disagreement in the data extraction was resolved through arbitration by a third investigator (N.F.).

Back to Top | Article Outline
Data analysis

In order to assess interrater reliability on study inclusion and data abstraction, we calculated the Phi (ϕ) statistic for each. This statistic provides a measure of interobserver agreement independent of chance. We used the DerSimonian-Laird random effects method to pool the proportion of men and the hazard ratio of mortality (men vs. women). This is an inverse-variance method that assumes the studies are estimating different yet related effects [15,16]. Additionally, the Freeman-Tukey double-arcsine transformation was used for pooling the proportions to stabilize the variance in the pooling process [17]. Heterogeneity was assessed using the I2 statistic [18,19]. This statistic describes the percentage of variation across studies that is due to heterogeneity rather than chance. Confidence intervals (CIs) for the I2 statistic were constructed using the test-based method [18]. As our primary analysis, we pooled data from all included cohort studies. We performed a random-effects metaregression analysis to examine whether the results were robust when we considered the effect of national adult HIV prevalence, as derived from the UNAIDS report on the global AIDS epidemic [20], and the gender inequity index (GII), a measure that reflects the inequity between men and women in reproductive health, empowerment, and the labour market, as derived from the United Nations Development Program report on human development [21]. We also conducted sensitivity analyses to determine the pooled effects when we included only cohort studies with more than 1000 participants in each, included only cohort studies with more than 5000 participants in each, excluded South Africa, which had the greatest number of cohorts for a single country, included only cohorts from South Africa, and excluded Malawi, which had the largest sample size from a single cohort. We examined whether the proportion of patients who were men and receiving ART was reflective of the prevalence of HIV among men using a Z-test. All analyses were run by E.D. and S.K. in Statsdirect (version 2.6.6, Manchester, UK) and R (version 2.14.0, Vienna, Austria).

Back to Top | Article Outline


Twenty-three cohort studies met our inclusion criteria [22–44]. Table 1 and online Appendix 3 ( [22–44] present the characteristics of each of these studies, and online Appendix 4 ( [22–44] presents the Newcastle-Ottawa Quality Assessment of each of these studies. The interrater reliability for study inclusion and data extraction was very good (ϕ = 0.91 and ϕ = 0.96, respectively). All cohort studies were published within the past 5 years, and include individuals initiating ART between the years 2001 and 2010. A total of 216 008 participants were included in our analysis, of which 79 892 (37%) were men. The overall mean CD4 cell count of the included cohort studies was 111 cells/μl at initiation of ART.

One-hundred and twenty-one studies retrieved for full-text review were excluded from our analysis for the following reasons: 48 because they did not provide extractable mortality outcomes by sex, 19 because of the study design (e.g. case study, cross-sectional study, clinical trial), 17 because they assessed outcomes that were not the focus of this study (e.g. attrition, loss to follow-up, early mortality), 13 because they reported outcomes among specific populations (e.g. women, children, adolescents, those not on treatment), 19 because they were superseded by other sources, and six because they reported on data prior to the year 2000. Figure 1 shows a flow diagram of the study inclusion process.

Table 2 shows the results of each pooled proportion meta-analysis and each pooled risk of mortality meta-analysis. The pooled proportion of men who initiated ART was 35% [95% CI: 33–37% (I2: 99%; 95% CI: 98–99%)] (Fig. 2). The pooled estimate of HIV prevalence among men in the included countries is 40% (95% CI: 39–41) reflecting a significant underrepresentation of men in ART programs (P < 0.001). The pooled hazard ratio estimate approximates a 37% increase in the risk of death for men compared to women who have initiated ART [hazard ratio: 1.37 (95% CI: 1.28–1.47; I2: 50%; 95% CI: 40–64%)] (Fig. 3). Among six cohort studies reporting baseline CD4 cell count by sex [27,28,30,34,35,37], men initiated ART at a lower average CD4 cell count than women (96 vs. 112 cells/μl).

When considering only large cohorts, the pooled hazard ratio estimate was similar, with approximately a 36% increase in the risk of death for men when compared to women who initiated ART [hazard ratio: 1.36 (95% CI: 1.27–1.46; I2: 60%; 95% CI: 46–78%)] in cohorts with 1000 or more participants each, and a 37% increase in the risk of death for men when compared to women who initiated ART [hazard ratio: 1.37 (95% CI: 1.28–1.46; I2: 56%; 95% CI: 39–82%)] in cohorts with 5000 or more participants each. When cohorts from South Africa were excluded, the pooled hazard ratio estimate was slightly higher, with a 43% increase in the risk of death for men when compared to women who initiated ART [hazard ratio: 1.43 (95% CI: 1.33–1.53; I2: 41%; 95% CI: 30–54%)]. Conversely, if only cohorts from South Africa were considered, the pooled hazard ratio estimate was lower, but still indicated an increase in the risk of death for men when compared to women who initiated ART [hazard ratio: 1.19 (95% CI: 1.00–1.42; I2: 55%; 95% CI: 35–88%)]. Finally, when excluding the largest cohort, found in Malawi, the pooled hazard ratio estimate was identical to the overall analysis, [hazard ratio: 1.37 (95% CI: 1.26–1.49; I2: 54%; 95% CI: 41–67%)].

The results of the metaregression indicates no significant association between the effect of sex on mortality with national adult HIV prevalence (P = 0.32) or GII (P = 0.34).

Back to Top | Article Outline


The results of our meta-analysis indicate that the risk of overall mortality is significantly higher for men compared to women enrolled in ART programs in Africa. The results also indicate that a lower proportion of men compared to women are enrolling in ART programs in Africa. In many regards, these findings are in contrast with how multiple funding agencies and the general public view sex imbalance in Africa.

There are several strengths and limitations of our study. The search strategy included a range of databases that yielded a large number of cohort studies, lending confidence that all key cohort studies were identified. We note that cohort data were only available for 14 African countries. This may be due to a lack of resources and research funding in certain regions. Regardless, we believe that these studies represent a range of epidemics in Africa (for example, with adult HIV prevalence ranging from 2% in Gambia to 24.8% in Botswana [20]). A priori we made the decision to exclude conference abstract data because these types of publications typically provide preliminary results and potentially incomplete data output. Given the recent interest in publishing outcomes data from observational ART programs in Africa, more complete data will be available in the coming years. However, ART programs need to consider how the current evidence can be used to provide more equitable treatment and care for both men and women.

Our pooled estimates are subject to substantial heterogeneity, which is expected when dealing with pooled proportions [45]. In anticipation of such heterogeneity we limited our review to studies from a particular geographical region, applied the random effects model, and attempted to explain this heterogeneity through a range of sensitivity analyses. We acknowledge that unreported program and contextual factors may contribute to the differences in observed outcomes. Nonetheless, the principal finding that men are underrepresented in ART programs in Africa, and at higher risk of death, was consistent across nearly all studies. Also, sex-specific age was sparsely reported. Although it is clear that men tend to be older in these cohorts, its effect on the observed difference in risk of mortality is unclear and should not represent a difference in access to care between men and women.

We limited our review to studies that presented mortality outcomes among those who have initiated ART. It is possible, although unlikely, that the impact of sex on the risk of HIV-related mortality is different among those who have not initiated ART. We also excluded cohort studies that specifically investigated early mortality (e.g. mortality within the first 6 months of ART). However, a recent systematic review of studies assessing early mortality found that in some instances male sex was associated with poorer survival [46]. The topic of patient retention in ART programs in Africa has recently been systematically reviewed [47]. In terms of sex, this study found that having fewer women as part of the cohort was predictive of higher attrition [47]. We found this to be true in all studies included in our analysis that reported sex-specific rates of loss to follow-up. A potential source of bias is women accessing care through prevention of mother-to-child transmission programs. It is assumed that these women will have better survival outcomes due to initiating at earlier stages of HIV (e.g. with higher CD4 cell counts). The one study reporting the highest prevalence of pregnant women (10.2%) shows higher mortality in women over men. Moreover, the three studies excluding pregnant women have higher mortality in men (hazard ratio: 1.19–1.60). We believe that it is unclear that pregnancies would necessarily lead to reduced mortality among women and the limited data available to us on the role of pregnancy support this claim.

There is a small body of evidence indicating that workplace programs that offer peer-education may be successful at engaging African men in treatment and care [48]. Because we were primarily interested in mortality in regional and national ART programs, we excluded workplace ART programs. Workplace ART programs are typically multinational and inclusive of greater numbers of male participants. In our search, we identified two cohort studies that provided data on the risk of mortality by sex among those enrolled in workplace ART programs [49,50]. The proportion of men in these cohorts was higher than those included in our analyses (57% for van der Borght et al.[50] and 64% for Hoffman et al.[49]), and although the risk of mortality was higher for men than women, the CIs indicated that this finding was not significant in each cohort [hazard ratio: 1.92 (95% CI: 0.67–5.55) for van der Borght et al.[50] and hazard ratio: 1.20 (95% CI: 0.99–1.40) for Hoffman et al.[49]].

The sex disparity that surrounds the uptake of ART and outcomes of care emphasizes the need for programs to cater services in a manner that encourages equity in the drive for wide coverage. A qualitative assessment of the way sex shapes the health behaviours, healthcare experiences and narratives of HIV-positive men on ART in South Africa has been recently published by Fitzgerald et al.[51]. Through the use of in-depth interviews with men, their families, and medical professionals, this study shed light on barriers and challenges commonly faced. Findings suggest that stigma is a main concern as public scrutiny is detrimental to personal and family reputations both in the community and the workplace. Men reported disappointment from their fathers and other masculine figures for their lack of contribution to ‘bread winning’ and taking a leadership role in the household when ill. Fathers of HIV-positive adult sons often negatively influenced their sentiments toward receiving ART, whereas such a profound influence was not seen in fathers and their HIV-positive daughters [51]. In addition, the latter explanation may account for poor health-seeking behavior of men who are likely to spend more time looking for a job and spending more time away from their family to try to find a way to survive in resource-limited settings. Of note, in recent recognition of these issues, a report issued in 2011 by the International Labour Organization highlighted a number of areas for action to help promote access to treatment and care for men, both in the workplace and beyond [52].

The sex inequity in accessing ART may be partially due to the fact that health services in many parts of Africa focus on maternal and child health issues [5,6]. Among people living with HIV in Africa who are aged 15 years and older in 2009, 59% were women [20]. Therefore, given that only 35% of those enrolled in the included ART programs were men, this represents a shortfall in male access to treatment. It is extremely important to increase advocacy and appropriate targeting of services in order to provide equitable access to ART for men. However, this should be conducted without compromising other vulnerable groups or threatening the HIV prevention and treatment for women.

The current available data on overall mortality in ART programs in Africa indicates that there is an increased risk of death for men compared to women. This finding adds to the body of evidence that men are disadvantaged in terms of treatment access and outcomes of care in Africa. The evidence we have provided should not be used to argue strongly in favor of men's rights, but rather to promote equal access to treatment and care, regardless of sex. There is no question that female empowerment was and still is absolutely necessary, especially in the developing world. Additional solutions that aid in reducing sex inequities in health outcomes among those enrolled in ART programs in Africa are needed.

Back to Top | Article Outline


The Canadian Institutes of Health Research sponsored this study. E.J.M. had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Back to Top | Article Outline
Conflicts of interest

Funding agencies had no role in the design or conduct of the study, in the collection, management, analysis, or interpretation of the data, or in the preparation, review, or approval of the manuscript. E.J.M. receives salary support from the Canadian Institutes of Health Research. J.N. receives salary support via the National Institutes of Mental Health. Funding was provided by the Canadian Institutes of Health Research.

Back to Top | Article Outline


1. WHO, UNAIDS, UNICEF. Global HIV/AIDS Response: Epidemic update and health sector progress towards universal access. Geneva, Switzerland: World Health Organization; 2011.
2. The Global Fund to Fight AIDS TaMGF. Fighting AIDS. [Accessed 25 March 2009].
3. The United States President's Emergency Plan for AIDS Relief (PEPFAR). [Accessed 30 November 2011].
4. Gilks C, Crowley S, Ekpini R, Gove S, Perriens J, Souteyrand Y, et al. The WHO public-health approach to antiretroviral treatment against HIV in resource-limited settings. Lancet 2006; 368:505–510.
5. United Nations. Political Declaration on HIV/AIDS. Resolution 60/262 adopted by the General Assembly, New York. 2006. http:// [Accessed 10 January 2012].
6. Open Society Institute. What works for women and girls: evidence for HIV/AIDS interventions. New York: Open Society Institute. 2010. [Accessed 15 December 2011].
7. The United States President's Emergency Plan for AIDS Relief (PEPFAR). A woman and girl-centered approach to health and gender equity. [Accessed 5 December 2011].
8. Johannessen A. Are men the losers of the antiretroviral treatment scale-up?. AIDS 2011; 25:1225–1226.
9. Cornell M, McIntyre J, Myer L. Men and antiretroviral therapy in Africa: our blind spot. Trop Med Int Health 2011; 16:828–829.
10. Braitstein P, Boulle A, Nash D, Brinkhof MW, Dabis F, Laurent C, et al. Gender and the use of antiretroviral treatment in resource-constrained settings: findings from a multicenter collaboration. J Womens Health (Larchmt) 2008; 17:47–55.
11. Braitstein P, Brinkhof MW, Dabis F, Schechter M, Boulle A, Miotti P, et al. Mortality of HIV-1-infected patients in the first year of antiretroviral therapy: comparison between low-income and high-income countries. Lancet 2006; 367:817–824.
12. Stroup D, Berlin J, Morton S, Olkin I, Williamson GD, Rennie D, et al. Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group. JAMA 2000; 283:2000–2012.
13. Wells G, Shea B, O’Connell D, Peterson J, Welch V, Losos M, Tugwell P. The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses. [Accessed 15 December 2011].
14. Parmar MK, Torri V, Stewart L. Extracting summary statistics to perform meta-analyses of the published literature for survival endpoints. Stat Med 1998; 17:2815–2834.
15. DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials 1986; 7:177–188.
16. Fleiss J. The statistical basis of meta-analysis. Stat Methods Med Res 1993; 2:121–145.
17. Miller J. The inverse of the Freeman-Tukey Double Arcsine transformation. Am Stat 1978; 32:138.
18. Higgins J, Thompson S. Quantifying heterogeneity in a meta-analysis. Stat Med 2002; 21:1539–1558.
19. Higgins J, Thompson S, Deeks J, Altman D. Measuring inconsistency in meta-analyses. Br Med J 2003; 327:557–560.
20. Joint United Nations Programme on HIV/AIDS (UNAIDS). Global report: UNAIDS report on the global AIDS epidemic 2010. Geneva, Switzerland: UNAIDS; 2010.
21. United Nations development Programme. Human development report 2011. New York, NY: UNDP.
22. Alemu AW, Sebastian MS. Determinants of survival in adult HIV patients on antiretroviral therapy in Oromiyaa, Ethiopia.Glob Health Action 2010; 3:5398.
23. Boulle A, Van Cutsem G, Hilderbrand K, Cragg C, Abrahams M, Mathee S, et al. Seven-year experience of a primary care antiretroviral treatment programme in Khayelitsha, South Africa. AIDS 2010; 24:563–572.
24. Boyles TH, Wilkinson LS, Leisegang R, Maartens G. Factors influencing retention in care after starting antiretroviral therapy in a rural South African programme. PLoS One 2011; 6:e19201.
25. Castelnuovo B, Manabe YC, Kiragga A, Kamya M, Easterbrook P, Kambugu A. Cause-specific mortality and the contribution of immune reconstitution inflammatory syndrome in the first 3 years after antiretroviral therapy initiation in an urban African cohort. Clin Infect Dis 2009; 49:965–972.
26. Chi BH, Mwango A, Giganti M, Mulenga LB, Tambatamba-Chapula B, Reid SE, et al. Early clinical and programmatic outcomes with tenofovir-based antiretroviral therapy in Zambia. J Acquir Immune Defic Syndr 2010; 54:63–70.
27. Cornell M, Myer L, Kaplan R, Bekker LG, Wood R. The impact of gender and income on survival and retention in a South African antiretroviral therapy programme. Trop Med Int Health 2009; 14:722–731.
28. DeSilva MB, Merry SP, Fischer PR, Rohrer JE, Isichei CO, Cha SS. Youth, unemployment, and male gender predict mortality in AIDS patients started on HAART in Nigeria. AIDS Care 2009; 21:70–77.
29. Ford N, Kranzer K, Hilderbrand K, Jouquet G, Goemaere E, Vlahakis N, et al. Early initiation of antiretroviral therapy and associated reduction in mortality, morbidity and defaulting in a nurse-managed, community cohort in Lesotho. AIDS 2010; 24:2645–2650.
30. Hawkins C, Chalamilla G, Okuma J, Spiegelman D, Hertzmark E, Aris E, et al. Sex differences in antiretroviral treatment outcomes among HIV-infected adults in an urban Tanzanian setting. AIDS 2011; 25:1189–1197.
31. Johannessen A, Naman E, Ngowi BJ, Sandvik L, Matee MI, Aglen HE, et al. Predictors of mortality in HIV-infected patients starting antiretroviral therapy in a rural hospital in Tanzania. BMC Infect Dis 2008; 8:52.
32. MacPherson P, Moshabela M, Martinson N, Pronyk P. Mortality and loss to follow-up among HAART initiators in rural South Africa. Trans R Soc Trop Med Hyg 2009; 103:588–593.
33. Maskew M, Brennan AT, Macphail AP, Sanne IM, Fox MP. Poorer ART outcomes with increasing age at a large public sector HIV Clinic in Johannesburg, South Africa. J Int Assoc Physicians AIDS Care (Chic) 2012; 11:57–65.
34. Mills EJ, Bakanda C, Birungi J, Chan K, Hogg RS, Ford N, et al. Male gender predicts mortality in a large cohort of patients receiving antiretroviral therapy in Uganda. J Int AIDS Soc 2011; 14:52.
35. Mujugira A, Wester CW, Kim S, Bussmann H, Gaolathe T. Patients with advanced HIV type 1 infection initiating antiretroviral therapy in Botswana: treatment response and mortality. AIDS Res Hum Retroviruses 2009; 25:127–133.
36. Mulissa Z, Jerene D, Lindtjorn B. Patients present earlier and survival has improved, but pre-ART attrition is high in a six-year HIV cohort data from Ethiopia. PLoS One 2010; 5:e13268.
37. Mutevedzi PC, Lessells RJ, Heller T, Barnighausen T, Cooke GS, Newell ML. Scale-up of a decentralized HIV treatment programme in rural KwaZulu-Natal, South Africa: does rapid expansion affect patient outcomes?. Bull World Health Organ 2010; 88:593–600.
38. Palombi L, Dorrucci M, Zimba I, Scarcella P, Mancinelli S, Buonomo E, et al. Immunologic response to highly active antiretroviral therapy and mortality reduction in a cohort of human immunodeficiency virus-positive persons in Mozambique. Am J Trop Med Hyg 2010; 83:1128–1132.
39. Peterson I, Togun O, de Silva T, Oko F, Rowland-Jones S, Jaye A, Peterson K. Mortality and immunovirological outcomes on antiretroviral therapy in HIV-1 and HIV-2-infected individuals in the Gambia. AIDS 2011; 25:2167–2175.
40. Sieleunou I, Souleymanou M, Schonenberger AM, Menten J, Boelaert M. Determinants of survival in AIDS patients on antiretroviral therapy in a rural centre in the Far-North Province, Cameroon. Trop Med Int Health 2009; 14:36–43.
41. Toure S, Kouadio B, Seyler C, Traore M, Dakoury-Dogbo N, Duvignac J, et al. Rapid scaling-up of antiretroviral therapy in 10 000 adults in Cote d’Ivoire: 2-year outcomes and determinants. AIDS 2008; 22:873–882.
42. van Griensven J, Zachariah R, Rasschaert F, Reid T. Discordant immunologic and virologic responses to antiretroviral therapy and associated mortality in a large treatment program in Rwanda. J Acquir Immune Defic Syndr 2009; 50:556–558.
43. Weigel R, Estill J, Egger M, et al.Mortality and loss to follow-up in the first year of art: malawi national ART programme. AIDS 2012; 26:365–373.
44. Kouanda S, Meda I, Nikiema L, et al.Determinants and causes of mortality in HIV-infected patients receiving antiretroviral therapy in Burkina Faso: a five-year retrospective cohort study. AIDS Care 2012; 24:478–490.
45. Borenstein M, Hedges L, Higgins JP, Rothstein H. Introduction to meta-analysis. Chichester: Wiley; 2009. pp. 312.
46. Lawn S, Harries A, Anglaret X, Myer L, Wood R. Early Mortality among adults accessing antiretroviral treatment programs in sub-Saharan Africa. AIDS 2008; 22:1897–1908.
47. Fox M, Rosen S. Patient retention in antiretroviral therapy programs up to three years on treatment in sub-Saharan Africa, 2007–2009: systematic review. Trop Med Int Health 2010; 15:1–15.
48. Kuwane B, Appiah K, Felix M, Grant A, Churchyard G. Expanding HIV care in Africa: making men matter in Johannesburg. Lancet 2009; 374:1329.
49. Hoffmann CJ, Fielding KL, Johnston V, Charalambous S, Innes C, Moore RD, et al. Changing predictors of mortality over time from cART start: implications for care. J Acquir Immune Defic Syndr 2011; 58:269–276.
50. van der Borght SF, Clevenbergh P, Rijckborst H, Nsalou P, Onyia N, Lange JM, et al. Mortality and morbidity among HIV type-1-infected patients during the first 5 years of a multicountry HIV workplace programme in Africa. Antivir Ther 2009; 14:63–74.
51. Fitzgerald M, Collumbien M, Hosegood V. No one can ask me ‘Why do you take that stuff?’: men's experiences of antiretroviral treatment in South Africa. AIDS Care 2010; 22:355–360.
52. International Labour Office. Guide to mainstreaming gender in workplace responses to HIV and AIDS. 2011.

Africa; antiretroviral therapy; HIV; men; meta-analysis; mortality

Supplemental Digital Content

Back to Top | Article Outline
© 2013 Lippincott Williams & Wilkins, Inc.