There is a strong statistical link between income inequality and the prevalence of HIV around the world. Göran Holmqvist, of the Institute for Futures Studies, Stockholm and Nordic Africa Institute, Uppsala, has an IPC paper out on it, and a one page summary.
The author pulls together a number of cross-country regressions, (and adds a few of his own) to try to identify possible explanations for the link. (Don’t worry, he provides the usual health warnings on the pitfalls of treating regressions as some a path to some sort of absolute truth).
First he demonstrates the link: compare countries at similar levels of poverty, and in general you find that the more unequal ones are more likely to have higher rates of HIV infection (see graph). This is not just because Africa is particularly unequal and has the highest rates of HIV – the same result is yielded by a global sample, one for Sub-Saharan Africa alone, and a global sample excluding Sub-Saharan Africa. The same link has also been revealed in national studies comparing states/provinces within the United States or China. He concludes that ‘while HIV/AIDS is often termed a disease of poverty, it could more justifiably be described as a disease of inequality.’ He also notes that similar statistical associations have been established for a number of other diseases.
What might explain the link? He finds two possible explanations and discounts a third. The two strongest candidates are what he calls ‘the economist’s story’ and ‘the sociologist’s story’. The first is grounded in a theory of
the economics of sexual behaviour. The adverse future life chances of people living in poverty are likely to increase their readiness to take risks today. On the other hand, high income levels make it more affordable to engage in multiple partnerships. High income inequality would stimulate both these behaviours. Holmqvist finds a correlation between inequality and risky sexual behaviour (multiple partners, number of commercial sex workers etc), which he argues provides some weight to this argument.
The sociologist’s story emphasises the role of social capital and social cohesion. Income inequality is assumed to undermine social cohesion, thereby making it difficult to establish norms, communicate with trust and mobilise people and money in the pursuit of joint goals or to control risk. But Holmqvist finds this less convincing.
He discounts a third version – the ‘political economist’s story’ that income inequality increases HIV prevalence because public sector performance is worse in unequal societies. In fact, he finds that African countries with high HIV prevalence tend to perform rather better on health provision, with lower child mortality (despite the fact that HIV itself increases child mortality), better immunization programmes and higher public spending on health (though the latter circumstance could also be an effect of the HIV epidemic itself). Rather than following the pattern of health system performance indicators, HIV prevalence seems to follow the pattern of “social diseases” such as crime and homicide rates, which also track levels of inequality.
Is the issue relevant enough to merit additional research? Holmqvist thinks so, and concludes ‘simply knowing that there is a statistical link between income inequality and HIV is not something that might lend itself to clear policy conclusions. If we can show more precisely how this link works, however, more useful policy conclusions may follow. Beyond the HIV epidemic itself, there is also an interest in understanding why highly unequal societies should be more vulnerable to new infectious diseases of this kind, in which the epidemiology has strong ingredients of human behaviour and social relations.’
By talking about inequality rather than absolute poverty, Holmqvist shifts the focus to issues of power and relationships – within households, communities and nations. This seems the right way to go, but the argument could usefully be extended to other aspects of power inequalities, for example gender relations: the abuse of women’s rights and gender-based violence are central to the spread of the disease in many countries. They may be harder to measure and fit into regressions, but they are no less real.
And of course, if income inequality is as lethal as Holmqvist seems to find, then it also provides one more powerful reason for taking equity and redistribution more seriously.