BMC Public Health 2009, 9:310 http://www.biomedcentral.com/1471-2458/9/310 Table 4: Association of cluster educational attainment with other risk factors in young women All young women (n): Median age (yrs) Current student (%) Travelled often (%) Ever married (%) Ever sexually active (%) Median age at 1st sex (yrs) Ever sexually active (n): Ever given birth (%) Sex before age 16 (%) Median lifetime sexual partner (n) STI (%) (a) Linear-by-linear association test (b) K-sample equality of medians test (c) Log-rank test for equality of survivor function Significant results are in bold (p < 0.05) underlying and proximate variables in the multivariate analysis. When only sexually active young women were taken into consideration, the association between neigh- bourhood educational level and HIV remained closely the same (Table 3). In contrast to the urban neighbourhoods, individual education was not significantly associated with HIV prevalence among young rural women, but it appeared to be somewhat protective in the bivariate anal- ysis (Table 1) when in fact it tended to be a risk factor in the multivariate analysis (Table 3). Discussion We have previously reported a remarkable shift over time in the association between individual-level educational attainment and HIV infection among young people in Zambia [19,22], and similar observations have been revealed from other high HIV prevalence populations in Africa [28]. Educational attainment is a key marker of socio-economic position, and here we examined struc- tural effects on HIV prevalence measured by the associa- tion between small area-level educational attainment and HIV prevalence independent of the respective individual- level of education. The magnitude of these effects was highest in the rural populations, i.e. OR 0.24, 95% CI 0.09–0.87 after adjusting for age and underlying individ- ual variables. The respective urban OR was 0.57, 95% CI 0.32–1.02. These findings suggest structural effects on HIV prevalence. There are many possible indicators of socio-economic position, both at the individual-level and at the neigh- bourhood-level. Frequently used indicators at the individ- Low 397 19 36.7 41.0 47.3 61.9 18 245 45.5 35.8 1.0 3.9 Middle 195 19 35.1 49.0 23.2 49.5 20 96 36.8 31.6 1.0 3.1 Urban High 248 19 48.0 48.0 29.5 51.2 20 127 35.2 24.0 1.0 1.6 Cluster educational attainment P value 0.550c 0.006a 0.062a 0.000a 0.004a < 0.001b 0.045a 0.022a 0.305c 0.240a Low 159 20 4.5 38.0 34.9 82.9 15 131 79.4 73.8 2.0 9.1 Middle 136 20 11.3 41.2 29.8 92.6 16 125 76.0 71.8 1.0 3.6 Rural High 161 19 35.4 52.2 35.3 67.1 17 108 63.0 57.0 2.0 2.9 P value 0.886c 0.000a 0.011a 0.000a 0.000a < 0.001b 0.005a 0.007a 0.147c 0.036a ual-level are occupation, income, educational attainment and wealth. These are seen as dimensions of socio-eco- nomic position. They are most often handled separately, but sometimes used as a basis for a construct measure [29]. Neighbourhood educational attainment seems to be a good proxy of the socio-economic position of the local areas due to the close correlation between this variable and average wealth index in the neighbourhoods. The associations between neighbourhood educational attain- ment and HIV infection and neighbourhood wealth index and HIV infection were similar in direction, and for the rural stratum, also compatible in strength. The strong cor- relation between neighbourhood educational attainment and the presence of electricity also suggests that the aggre- gate variable for educational attainment captures struc- tural or contextual aspects of the neighbourhoods, although we cannot rule out that it reflects compositional differences between the neighbourhoods as well, i.e. that the differences between the neighbourhoods are pro- duced by the kind of people who live there (a selection effect). The multivariate analyses showed that adjustment for individual underlying and sexual behaviour factors weakened the association between the educational level of the urban neighbourhoods and HIV infection. This indicates that the effect of neighbourhood educational attainment on HIV was partially mediated through these individual factors as conceptualised in the proximate determinants framework. In the rural area the association between HIV prevalence and average education in the neighbourhoods was not reduced after adjustment for individual factors. This may reflect that the most impor- tant mediating factors were not included in our model Page 8 of 11 (page number not for citation purposes)