BMC Public Health 2009, 9:310 http://www.biomedcentral.com/1471-2458/9/310 Background Investigations of the association between socio-economic position indicators and HIV have chiefly focused on fac- tors that pertain to individual-level characteristics. In a systematic review of HIV studies in East, Central and Southern Africa, Wojcicki et al. (2005) found that out of the 36 studies examined, only two studies [1,2] had taken ecological or neighbourhood variables into consideration [3]. Further evidence points to the fact that studying indi- vidual characteristics such as demographic, biologic, per- sonality or behaviour factors alone can only explain a part of the complex set of factors that contribute to poor health [4-6]. Neighbourhoods represent both social networks and physical places through which diseases spread [4], and ignoring them may lead to incomplete understanding of determinants of disease in individuals and in the pop- ulation [5]. Multi-level studies in public health have focused on a range of different public health outcomes, for instance, related to all-cause mortality, cardiovascular disease, infant and child health, women's health, mental health and health behaviour [7-12]. In the past years, there has been an increased interest in neighbourhood or ecological variables in Africa, such that more studies have started to investigate their effect on HIV prevalence [13,14]. The associations studied have been mainly between neigh- bourhood variables such as socio-economic position, socio-economic activities and HIV prevalence. These stud- ies have found neighbourhood variables to be associated with HIV prevalence. Individual-level epidemiological surveys on the associa- tion between educational attainment and HIV infection have found different patterns depending on the stage of the epidemic. Studies conducted before 1996 in sub-Saha- ran Africa found higher educational attainment to be pos- itively associated with HIV infection [15-17]. The explanation for these findings was probably that higher educational achievement was associated with higher wealth, increased mobility and multiple sexual partners [15,18]. Later, serial cross-sectional studies have shown declines in the HIV prevalence among highly educated persons, particularly in those aged 15–24 years [17,19- 23]. It is likely that increased information, knowledge and awareness, might have had a positive impact earlier among educated persons than those who were illiterate and poor, in terms of delaying sexual debut, reducing the number of partners, and increasing condom use [24,25]. Conversely, there have been few studies that have investi- gated the effect of neighbourhood educational attainment or socio-economic position on HIV prevalence. In the present study, HIV survey data from selected urban and rural neighbourhoods in Zambia were re-analysed using multi-level modelling techniques to investigate the rela- tionship between HIV prevalence and educational attain- ment at both the neighbourhood and individual levels. Methods Population and sampling procedures The investigation is based on data collected in a popula- tion-based cross-sectional survey undertaken in Zambia in 2003. Stratified random cluster sampling was used to select ten clusters in Chelston (urban neighbourhood in Lusaka) and ten in Kapiri Mposhi district (rural neigh- bourhoods). Each cluster in the study corresponds to a census tract or standard enumeration area (SEA), which is the lowest unit of data collection in a Census of Zambia. It should be noted that the terms cluster and neighbour- hood are used interchangeably in this study. All persons in the selected clusters aged between 15–59 years were invited to participate in the study. A total of 6791 persons were listed and 4751 persons (70%) com- pleted the structured interview and provided saliva for HIV testing. Two call-backs were made in order to catch individuals who were absent during the first visit to the household. Non-participation was attributed to absence of some listed persons during the canvassing (19.7%), interview refusals (3.4%) and refusal to test for HIV infec- tion (6.6%). This paper is restricted to young women aged between 15–24 years (n = 1295). There were 840 young women aged 15–24 who participated and were tested for HIV in Chelston, whereas the corresponding number in Kapiri Mposhi was 456. Laboratory Analysis In order to ascertain the HIV status of the participants, the study collected saliva samples from willing participants. Participants' saliva samples were tested by use of a rapid test kit BIONOR HIV 1 & 2 (BIONOR AS, Skien, Norway). For quality assurance, 10 percent of negative samples and 10 percent positive samples were retested at the national reference laboratory at the University Teaching Hospital in Lusaka. Conceptual Framework The analysis and interpretation of the data was based on the proximate-determinants framework for HIV infection [26]. Key to the framework is the assumption that under- lying variables influence the proximate variables, which in turn have a direct effect on the biological mechanisms behind the acquisition of HIV. The underlying variables include socio-economic context of the neighbourhood (neighbourhood educational attainment, neighbourhood wealth index and neighbourhood employment rate are all used as a proxy of this in the current study), individual education, marital status, wealth index, student status (still student) and mobility. In order to affect the biologi- Page 2 of 11 (page number not for citation purposes)