BMC Public Health 2009, 9:310 http://www.biomedcentral.com/1471-2458/9/310 All analyses were conducted using Stata version 10.1 (Col- lege Station, Texas, USA), except for the aggregation pro- cedures and the linear-by-linear test for which we used SPSS 15. The distribution and age-adjusted associations (based on multilevel mixed-effect logistic regression) of underlying and proximate variables to HIV prevalence are shown in Table 1. Multilevel mixed-effect logistic regres- sion estimates both fixed and random effects and takes account of the clustering of data. Variables that were sig- nificantly associated (p < 0.05) with HIV in the bivariate analysis in either the urban or the rural areas were included in the multivariate analyses (in Tables 2 and 3). In addition, Pearson's correlation test was conducted to determine the correlation between cluster-level educa- tional attainment, cluster-level wealth index, cluster employment rate, presence of electricity in the cluster, and individual educational attainment. The results indicated that cluster-level wealth; cluster employment and electric- ity were highly correlated with cluster educational level in the rural neighbourhoods. To avoid multi-collinearity during modelling, cluster educational attainment was the only cluster-related variable retained in the final multivar- iate model. To assess the pathways through which individual risk fac- tors were likely to mediate the effect of neighbourhood educational level on HIV infection, we examined the asso- ciation of neighbourhood educational level with individ- ual variables using linear-by-linear association tests (also known as Mantel-Haenszel statistical test). However, this test does not adjust for the effect of data clustering, and thus the actual strength of associations may be weaker than estimated by the test. The individual factors were compared among the three levels (i.e., high, middle and low) of neighbourhood educational attainment in both urban clusters and rural clusters (Table 4). Median age at first sexual intercourse was estimated using the survival analysis command stsum. Log-rank test for equality of survivor functions was used to compare the median ages between groups. Median age and median lifetime sexual partners were compared via K-sample equality of medians test. The multivariate analyses were conducted by the use of a two-level mixed effects logistic regression model. Separate multivariate models were constructed for urban and for rural neighbourhoods. In addition, separate models were built for all women and for sexually active women only. For all women, underlying variables were entered first and then the 'ever had sex' variable was added. For the sexually active women, we added the factor 'ever given birth' and 'number of lifetime sexual partners'. Ethics Ethical clearance for the population based-survey proto- col was obtained from the University of Zambia Research Ethics Committee. Participation in the survey was based on informed written consent. Respondents were informed that the HIV testing based on saliva was for research pur- poses only and it was going to be handled anonymously. Those respondents that wanted to know their HIV status were offered voluntary counselling and testing (VCT) at home. Results The HIV prevalence was 12.5% in the urban area and 6.8% in the rural area. In both urban and rural areas, the neighbourhoods with a low average educational attain- ment had higher HIV prevalence than neighbourhoods with a high average educational level, 15.9% vs. 10.7% and 7.3% vs. 3.7% respectively. The logistic regression analysis for cluster-level variables adjusted for age showed neighbourhood educational attainment to be negatively associated with HIV infection in both the urban and rural populations. The other neighbourhood variables, wealth index and employment, were not significantly associated with HIV prevalence, but the direction of the relationships were the same, i.e. higher socioeconomic status being associated with lower HIV prevalence (Table 1). Neigh- bourhood educational attainment was correlated with neighbourhood wealth (Pearson correlation coefficient 0.8 in the rural area and 0.45 in the urban area), with the presence of electricity in the households (0.6 in the rural and 0.14 in the urban area), and with neighbourhood employment rate (0.7 in the rural and 0.15 in the urban area). Table 4 shows that in the urban area, women who resided in neighbourhoods with a low mean educational-level were more likely to engage in sexual activity early and not to be in school than those who resided in neighbour- hoods with a high mean educational-level. Among those who were sexually active, women in neighbourhoods with low mean educational-level were more likely to engage in sex before age 16, marry early and give birth early com- pared to those in the neighbourhoods with high educa- tional-level. A similar pattern was observed in the rural neighbourhoods. Generally, women in the rural area engaged in sexual intercourse earlier than their peers in the urban area, irrespective of the level of education in the neighbourhoods they resided. In terms of median lifetime partners, women in the rural clusters reported a higher number than the urban women, but there was no differ- ence by educational level of the neighbourhood. The per- centage reporting STI symptoms was highest in neighbourhoods with low educational level in the rural area, especially among young women aged 20–24 years. Page 4 of 11 (page number not for citation purposes)