PEPFAR: Greater wealth, not poverty, associated with higher HIV prevalence in Africa, according to survey

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The relationship between socio-economic status and the HIV epidemic

Dr. Mishra began by pointing out that since South African President Thabo Mbeki’s speech at the World AIDS conference in Durban, there has been a growing tendency to associate poverty with HIV/AIDS. For example, in 2004, in a recent article in the Lancet, the author wrote that “poverty reduction will undoubtedly be at the core of a sustainable solution to HIV/AIDS,” (Fenton 2004).

There is some basis for making such statements, since across the globe, there is a positive correlation between HIV prevalence and poverty – as the poorer regions in the world have been the hardest hit by the HIV epidemic. This correlation has also been observed within a number of countries, such as in Brazil and within the US, where low socio-economic status has been clearly tied with higher risks of HIV both nation-wide and within specific communities (for example, such as among men who have sex with men in California) (Parker; Pechansky; Xia).

Poverty has also been associated with increased risk for other diseases, such as cholera and sexually transmitted diseases, and it has been postulated that malnutrition and access to healthcare that are associated with poverty could make individuals more susceptible to HIV infection. The poor are also less likely to have access to condoms and prevention information.

However, according to Dr Mishra, the associations between poverty and HIV break down when one looks at sub-Saharan Africa. For example, the wealthiest part of the continent (southern Africa, e.g., Botswana and South Africa) is where the HIV prevalence is the highest (although this argument fails to look at other factors that could be responsible for this difference).



The result of a statistical test which tells us whether the results of a study are likely to be due to chance and would not be confirmed if the study was repeated. All p-values are between 0 and 1; the most reliable studies have p-values very close to 0. A p-value of 0.001 means that there is a 1 in 1000 probability that the results are due to chance and do not reflect a real difference. A p-value of 0.05 means there is a 1 in 20 probability that the results are due to chance. When a p-value is 0.05 or below, the result is considered to be ‘statistically significant’. Confidence intervals give similar information to p-values but are easier to interpret. 

voluntary male medical circumcision (VMMC)

The surgical removal of the foreskin of the penis (the retractable fold of tissue that covers the head of the penis) to reduce the risk of HIV infection in men.

multivariate analysis

An extension of multivariable analysis that is used to model two or more outcomes at the same time.


The surgical removal of the foreskin of the penis (the retractable fold of tissue that covers the head of the penis) to reduce the risk of HIV infection in men.


In discussions of consent for medical treatment, the ability of a person to make a decision for themselves and understand its implications. Young children, people who are unconscious and some people with mental health problems may lack capacity. In the context of health services, the staff and resources that are available for patient care.

Furthermore, studies in several sub-Saharan African countries have shown that HIV is actually more common among wealthier, better educated individuals. Although some have suggested that this pattern may change as the epidemic matures (Fenton), according to Dr. Mishra, data from several recent Demographic and Health Surveys and AIDS Indicator Surveys have shown that HIV is still more common among wealthier adults than the poor in sub-Saharan Africa — even in the countries with older generalised epidemics such as Uganda.

There could be a number of potential explanations for this. For example, HIV is more prevalent in urban areas in Africa where the wealthier people tend to live or at least have greater access to. Furthermore, wealthier people tend to be more mobile and have more leisure time — thus more opportunities for casual sex. Likewise, they could have a greater number of lifetime or concurrent sexual partners.

Also, wealthier people with HIV could simply survive longer — although conversely, the expense of dealing with HIV or loss of work would be likely to reduce wealth. Other cultural factors, such as male circumcision or polygamy could also play a role.

Contrary to widespread belief, HIV is not disproportionately more common among the poor in Africa, according to a study by Dr. Vinod Mishra at the 2006 PEPFAR Implementers meeting held in Durban in mid-June. In fact, if anything, the reverse was true across several sub-Saharan African countries: “Even with all other factors controlled, in most countries, the weathier adults remain at least as likely as the poor to be HIV-infected, if not more,” said Dr. Mishra.

The study could have profound policy and programmatic implications, providing a rationale against funding poverty-reduction prevention programmes which Dr Mishra says are unlikely to have much of an impact on HIV prevention.

However, it may be a premature to base policy decisions entirely upon this cross-sectional survey because the relationship between poverty and HIV vulnerability is probably more complex, and as Dr. Mishra himself noted, the relationship could also be transitional. In other words, the economic opportunities that Africans have to get out of poverty come with increased HIV risks (such as sex work or intergenerational relationships with an economic component — sugar daddies) or place them in environments where HIV transmission is more likely (in urban settings, highway rest stops or the mines).

The study

Dr. Mishra and colleagues conduced a cross-sectional survey of socioeconomic status and a number of other factors linked with HIV-testing data from men, women and cohabiting couples in Burkina Faso, Ghana, Cameroon, Uganda, Kenya, Tanzania, Malawi, and Lesotho. The aim of the study was to explore the association between wealth status and several factors, such as urban/rural residence, age, education, occupation, etc., and to see whether wealth status was associated with key risk behaviours, such as polygamy, multiple sexual partners, non-regular partners, partner faithfulness, consistent condom use, male circumcision, and knowledge of how to avoid infection (ABC-based prevention). They also examined the association between these risk factors and HIV infection, and determined whether wealth status remained significantly associated with a higher HIV prevalence once all these other factors were incorporated into in a multivariate analysis.

In most countries:

  • Wealth was more likely to be associated with having a better education, more mobility, and with living in an urban area where HIV is prevalent
  • Wealth was associated with an earlier sexual debut in men though not in women
  • Polygamy was not more prevalent among the wealthier, but married or cohabiting wealthier men and women were less likely to be faithful to their partners
  • Wealthier men were more likely to have multiple partners in the last year — this pattern was not consistent among women
  • However, both wealthier men and women were more likely to have had multiple lifetime sex partners
  • HIV prevalence was associated with number of sex partners in the last year and sex with a non-regular partner in the last year
  • HIV prevalence was strongly associated with number of lifetime sex partners and partner faithfulness
  • Wealthier men and women have greater knowledge about HIV prevention methods, and were more likely to reporting using condoms, both with non-regular partners and consistently with all partners in the last year
  • Wealthier men are more likely to be circumcised, except in Lesotho
  • Wealthier men were more likely to have drank alcohol the last time they had sex

Individuals’ household wealth/socio-economic status was plotted out in quintiles, and the HIV prevalence tended to be higher among the some of the wealthier quintiles, though generally not the wealthiest. But the strong positive association was not statistically significant once adjusted for the other confounding variables and risk factors. In fact, the data for men and women tended to vary from country to country (making it impossible to see any clear pattern). It was clear though that HIV prevalence was not dramatically higher among the poorest individuals in these countries.

Dr Mishra noted that although poverty reduction is a worthy goal in its own right, it is unlikely to have much of an impact on HIV prevention “when the majority of HIV-infected people are wealthier, not poor.” He concluded that prevention programmes should be adjusted to take account of this reality on the ground.

And at the end of the conference, it appeared that his message had fallen on some fertile soil, when Dr. Mark Dybul, acting US Global AIDS Coordinator said that even though the idea that poverty isn’t related to higher HIV prevalence may have made people uncomfortable, “we must look deeply and dispassionately into data presented and discussed here and make sure they are right, but when we come upon data that we know are right, we must change our programmes to reflect the data.”

Delving a little deeper

However, other researchers in the field see the relationship between poverty and HIV as a much more complex one. In their recently published AIDS in the Twenty-First Century Professors Tony Barnett and Alan Whiteside of the London School of Economics and the University of Kwazulu-Natal note that income status has a limited ability to predict an individual’s risk of HIV infection independent of the social setting in which they exist.

In their opinion, the most important reason for focusing on the relationship between poverty and HIV is in order to understand they way in which impoverishment of a whole continent has led to the exceptionally severe epidemic experienced in sub-Saharan Africa.

Data from studies in South Africa also suggest that wealth is not a significant ‘contributor’ to HIV prevalence there — even among the black population (Kalichman 2006). Rather, in a study presented at the 2nd South African AIDS Conference, individual risk factors such as older age, early sexual debut and multiple lifetime partners were associated with higher HIV risk, but so were structural factors related to the community (Pronyk).

These included easier access to a trading centre (p=0.02), higher proportions of short-term residents (p=<0.001), and lower levels of social capital (p<0.001 men, p=0.02 women), an index based on social network membership and responses to questions on: levels of trust, reciprocity, solidarity in time of crisis, collective action (positive (marches/rallies) and negative (local serious and violent crime rate). In other words, HIV prevalence was higher in settings where the social order had broken down (or had never been established in the first place).

Among men, higher HIV prevalence was also seen among communities with easier access to a local mine (p=0.05), a higher density and activity of local bars (p=0.004), a higher numbers of sex workers per village (p=<0.001), and lower proportions of out-migrants (p=0.002).

Although, Dr. Mishra investigated some of these questions, he did not explore such concepts as social capital and societal structure, which may be necessary to better understand the reasons for risky behaviour. But it may also be that the southern African epidemic is different from what is being observed in the other countries in Dr. Mishra’s survey, due in part to biological factors such as HIV-1 subtype.

In addition, a limitation of the survey is that it only describes prevalence and current socioeconomic status — it does not explore transitional relationships, including the individual’s socioeconomic status at the point of infection, or possibly more importantly, earlier in life. It is quite possible, even likely, that the most destitute people in agrarian Africa may have fewer opportunities to become infected.

However, as Dr. Mishra noted, the relationships between poverty and HIV may be transitional. By definition, poverty coping mechanisms should have the benefit of getting one out of the most desperate poverty. Poverty is a major factor driving people to leave the rural or village setting for the greater economic activities that exist in urban areas. Poverty drives men to migrate for labour to work in the mines or factories, or to become long distance truck drivers — which increases their personal and household wealth while pulling them away from their family and increasing their likelihood of engaging in risky sexual behaviour.

Poverty has been shown to drive women into commercial sex work, which clearly increases HIV risk. Likewise, some women may accept concurrent partners because it has economic benefits to them, or young girls may accept sugar daddies to improve their financial standings and options for a future. These risk takers in African society may wind up better off financially but at a cost of increased HIV risk. And this survey only has limited capacity to explore such questions.


Tony Barnettt & Alan Whiteside. AIDS in the Twenty-First century: disease and globalisation. Second Edition, 2006, Palgrave, London.

Fenton L. Preventing HIV/AIDS through poverty reduction: the only sustainable solution? Lancet; 364: 1186-1187, 2004.

Kalichman SC et al. Associations of poverty, substance use, and HIV transmission risk behaviors in three South African communities. Soc Sci Med.; 62(7):1641-9. 2006.

Mishra V et al. Are poor more affected by HIV/AIDS in sub-Saharan Africa? The 2006 HIV/AIDS Implementers Meeting of the President’s Emergency Plan for AIDS Relief, Durban, South Africa, abstract 49.

Parker R, Camargo KR Jr. [Poverty and HIV/AIDS: anthropological and sociological aspects]. Cad Saude Publica.;16 ## Suppl 1):89-102, 2000.

Pechansky F et al. HIV seroprevalence among drug users: an analysis of selected variables based on 10 years of data collection in Porto Alegre, Brazil. Drug Alcohol Depend.;82 Suppl 1:S109-13, 2006.

Pronyk P.M, et al. Why do some communities have more HIV than others? The association between structural factors and HIV prevalence in rural South Africa. 2nd South African AIDS Conference, abstract, 2005.

Xia Q et al. HIV prevalence and sexual risk behaviors among men who have sex with men: results from a statewide population-based survey in California. J Acquir Immune Defic Syndr.; 41(2):238-45, 2006.