Neighbourhood characteristics influence young women’s HIV risk in Zambia

Some young people are more at risk of contracting HIV than others and this is not only because of different sexual behaviour. The context of young women’s lives may be as important as individual behaviour in determining their risk of becoming HIV positive.

As part of the multicentre study of factors determining the different prevalences of HIV in sub-Saharan Africa, researchers at the London School of Hygiene and Tropical Medicine conducted a study on how neighbourhood factors influence HIV risk of young women in Zambia. The study investigated the importance of these underlying risk factors and how far their effect can be explained by differences in sexual behaviour and by biological risk factors for HIV.

The research used data collected in 1997 from 2000 adults in 16 neighbourhoods in Ndola, Zambia. The neighbourhoods were categorised as ‘lower’, ‘middle’ or ‘higher’ socio-economic status (SES) using five measures: education, occupation and employment levels among adults over 24 years, and the availability of electricity and running water. Statistical analysis of the data measured the effect of a variety of neighbourhood characteristics on HIV risk for young women aged between 15 and 24.

Key findings include:

• Overall HIV prevalence among young women in Ndola was 28 percent, ranging from 5 percent in 15-year-olds to 48 percent in 24-year-olds.
• HIV prevalence was approximately twice as high in girls from lower or middle SES neighbourhoods than in girls from higher SES neighbourhoods (32 and 35 percent compared to 17 percent).
• Some of the elevated HIV risk among girls from poorer neighbourhoods could be explained by their earlier start of sexual activity, earlier marriage and higher prevalence of other sexually transmitted infections. However, most of the difference could not be explained by any of the individual factors measured.
• Living in a neighbourhood near a market substantially increased the risk of HIV infection, while living close to a health centre decreased it, taking all other factors into account.
• Better education was a risk factor for HIV infection among young girls. This association only became apparent when neighbourhood factors were adjusted for.

The results suggest that individual-level and population-level risk factors are distinct concepts and can have quite different effects. The circumstances in which a young woman lives could be as important as her behaviour in determining how likely she is to become HIV positive. Policy implications include:

• Confining analysis to individual and behavioural factors ignores the underlying factors that influence behavioural choices.
• It is important to try to distinguish between the effects of different risk factors at different levels.
• Doing so will help identify those most at risk, help us understand why they are at risk and put in place appropriate prevention measures.