Effects of neighbourhood-level educational attainment on HIV prevalence among young women in Zambia

Investigations of the association between socio-economic position indicators and HIV have chiefly focused on factors 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 individual characteristics such as demographic, biologic, personality 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 population [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 neighbourhood variables such as socio-economic position, socio-economic activities and HIV prevalence. These studies have found neighbourhood variables to be associated with HIV prevalence.

Individual-level epidemiological surveys on the association between educational attainment and HIV infection have found different patterns depending on the stage of the epidemic. Studies conducted before 1996 in sub-Saharan Africa found higher educational attainment to be positively 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 investigated 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 relationship between HIV prevalence and educational attainment at both the neighbourhood and individual levels.

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 attainment 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). Neighbourhood 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 neighbourhoods 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 compared to those in the neighbourhoods with high educational-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 difference by educational level of the neighbourhood. The percentage reporting STI symptoms was highest in neighbourhoods with low educational level in the rural area, especially among young women aged 20–24 years.

The correlation between individual and cluster educational attainment was 0.17 in the urban and 0.53 in the rural area. In both urban and rural neighbourhoods, there was no evidence of an interaction between neighbourhood-level education and individual-level education. After adjusting for underlying individual factors in the multivariate analysis, the likelihood of young urban women in the neighbourhoods with a high average educational attainment to be infected with HIV was still lower than in less educated neighbourhoods, but the association was no longer significant (OR 0.57, 95% CI 0.32–1.02). Young women with higher education had a lower risk of HIV infection after controlling for the neighbourhood effect. Among sexually active urban women, neighbourhood educational level was not significantly associated with HIV infection in the multivariate analyses, whereas high individual-level education maintained its protective effect (Table 2).

In the rural clusters the significant association between neighbourhood educational attainment and HIV prevalence persisted even after adjustments for individual-level underlying and proximate variables in the multivariate analysis. When only sexually active young women were taken into consideration, the association between neighbourhood 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 analysis (Table 1) when in fact it tended to be a risk factor in the multivariate analysis (Table 3).

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 structural effects on HIV prevalence measured by the association 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 individual 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 neighbourhood-level. Frequently used indicators at the individual-level are occupation, income, educational attainment and wealth. These are seen as dimensions of socio-economic 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 attainment 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 correlation between neighbourhood educational attainment and the presence of electricity also suggests that the aggregate variable for educational attainment captures structural 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 produced 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 important mediating factors were not included in our model and/or that those included were measured with low validity. The finding that neighbourhood and individual educational attainment in the rural area tended to have contrasting associations with HIV prevalence (the first being protective and the second tending to be a risk factor) supports the assumption that the aggregate variable for neighbourhood educational attainment captures not only differences in education itself but also important differences in the socio-economic context of the neighbourhoods that may protect educated and wealthier neighbourhoods from HIV infection.

To what extent education in itself creates the differences in HIV prevalence between neighbourhoods is difficult to judge. Although neighbourhood educational attainment seems to be a good proxy of structural neighbourhood differences in the present data, we cannot rule out the possibility that education per se plays a role too. For example, it is believed that the spread of education in the community environment moulds socially acceptable behaviour [24]. Young women in the most educated neighbourhoods in this study seemed to delay sexual debut and marriage compared to those in the least educated neighbourhoods, and this may reflect differences in what is perceived to be socially acceptable. It could also reflect that women from educated neighbourhoods have a more independent position and are actively encouraged to pursue an education before establishing a relationship to a man and having children. Other studies suggest that in neighbourhoods with low average educational attainment or financially deprived areas adult supervision may be weaker [30]. As parental involvement may function as a social control and socialization mechanism in the family [30], limited parental involvement seems to be generally associated with a higher level of pre-marital sexual activity and problem behaviour [31]. This may be translated into higher chances of HIV infection among young women in the least educated neighbourhoods when compared with their peers who reside in areas with high average education. Further, educated women are more likely to marry educated men, and as educated men are less likely to engage in risky sexual behaviour [25] and they are less likely to be HIV infected, this probably also has an impact on the HIV risk of educated women.

Past HIV prevention efforts have been overly focused on individual behaviours, but the recognition of the need to combine behavioural, structural and biomedical approaches seems to be growing [32, 33]. Although the observed shift in the association between educational attainment and HIV prevalence in several high prevalence African countries might be an example of substantial effects of preventive programmes focused on individual behaviour [19, 22, 25, 34], these preventive programmes seem to have had limited impact on the less educated and impoverished part of the population. There is still limited understanding of why the less educated are not adhering to behaviour change messages. The most educated may respond faster to protect themselves due to higher concern for their health and stronger belief in their own self-efficacy as predicted by the framework "diffusion of innovations" [25, 35, 36]. Or it might be rooted in the pedagogical approach employed by the campaigns. Any elements of 'blame the victim' approaches to foster behaviour change messages may have been counter-productive or perceived as irrelevant by less educated persons [34]. The neighbourhood effects on HIV prevalence might indicate the need for combining programmes focussing on individual behaviour with structural approaches to address those factors that shape or constrain individual behaviour. An example of an important programme that may contribute to this is the Programme for the advancement of girls' education (PAGE), adopted in Zambia in the early 1990s, with the purpose to improve girls' access to school [37]. It seems that this programme has started to bear fruits in terms of substantial improvement in girls' school attendance at both primary and secondary level in the period 1990–2000 [38]. However, the net junior and senior secondary school attendance rate is still low in Zambia, particularly in rural (8% and 5% vs. 35% and 29% in urban areas) and low cost areas (31% and 23% vs. 50% and 49% in high cost areas)[39]. Increasing school attendance in low cost (poor) areas is likely to have an effect on HIV incidence as it may increase the self-efficacy of young people to protect themselves against HIV infection and increase their chances of obtaining formal employment and thus improve their own living conditions. Making secondary schools more available in rural areas may be one way to increase net school attendance, and removing school fees is another.

A number of factors may have contributed to biasing the neighbourhood effects in our study. In the first place, census clusters may not be adequate proxies of an individual's neighbourhood surroundings and thus may not adequately capture differences across neighbourhoods [8]. However, these areas are small enough to be useful proxies of the natural neighbourhoods. Furthermore, the number of clusters used by the study was low; i.e. 10 in each of the strata. This resulted in low power to detect in-between cluster variation in HIV prevalence[40]. There was also limited information on more specific neighbourhood characteristics found to be related to HIV prevalence in other studies, for example, availability of water, markets and health facilities [13] and availability of bars and proximity to the nearest big town [14]. Non-response may have affected our results if young women who were absent during the household visits had a different risk profile than those found at home (e.g. young women attending boarding school could engage in both less or more risky sex than their counterparts at home). However, the proportion absent (which amounted to 11–14% among women overall) was rather low and thus is not likely to have caused a major bias. The modest effect of adjusting for proximate variables may be due to bias in the self-reporting of sexual behaviour as women have a tendency to underreport stigmatized sexual behaviour experiences and over-report normative behaviour [41, 42]. A particular example in this regard was the revealed 4.1% HIV prevalence among young urban women who reported never engaging in sexual intercourse. Since the epidemic in Zambia is mainly transmitted through heterosexual intercourse and the likelihood that women aged 15–24 in the pre-ARV era have survived with a HIV infection transmitted from the mother during pregnancy/infancy, is extremely low, this indicates a certain underreporting of sexual activity. Other studies have also discovered current pregnancy, HIV and sexually transmitted infections among young people who denied having sex [2, 42, 43]. Some of the young women who denied having had sex may have been raped or forced to have sex and denied sexual activity, as they had not participated voluntarily. A study in Kenya found that half the adolescent girls who claimed that they had never had sex, reported having been forced to have sex [44]. Ten percent of Zambian women aged 15–19 had been forced to have sex against their own will according to the Zambia Sexual Behaviour Survey 2005 [45]. Finally, a cross-sectional survey does not allow determination of whether exposure to neighbourhood factors precedes the development of the outcome.

In conclusion, the findings suggested neighbourhood contextual effects on HIV prevalence in these very HIV prevalence areas. Neighbourhood educational attainment appeared as a good proxy of the socioeconomic position and is likely to capture a complexity of overlapping contextual factors. In this regard the strength of the local educational system seems to be a case in point, supporting the value of ongoing efforts to improve access to secondary education particularly for women. However, more complex structural approaches will be needed to reduce HIV risk and vulnerability. Future research should include more neighbourhood factors of relevance to HIV prevalence as part of the effort to better understand the causal mechanisms involved.