This is an updated systematic review and meta-analysis, of the association between BV and HIV infection. Overall BV prevalence was high in several populations of women studied, with prevalence rates as high as 70 percent. Our analyses of HIV incidence studies indicate that BV increases the risk of HIV acquisition by approximately 60 percent (95 percent CI 21–113 percent). This was slightly higher that the 40% reported in a previous review of 2 studies [17
]. Studies of HIV prevalence tended to find higher HIV prevalence in women with BV. However these prevalence study estimates were heterogeneous and had evidence of funnel plot asymmetry.
The BV-HIV association tended to be weaker in high HIV-risk groups, though the few number of prospective studies limited the confirmation of this trend in HIV incidence studies. A weaker association in high risk women may possibly be due to a depletion of susceptibility to HIV resulting from women in high risk groups having a greater risk of acquiring HIV from causes other than BV. Once HIV infected, they are no longer at risk of acquiring HIV attributable to BV, thus reducing the effect of BV in this group. More data from prospective cohorts are needed to better examine the heterogeneity, by HIV risk group, in the effects of BV on the risk of acquiring HIV. This information could be helpful in identifying specific sub-populations, with a stronger association between BV and HIV, in whom to target BV control measures.
BV results in several changes in the vaginal flora that provide biological plausibility for an increased risk of HIV acquisition in BV positive women. BV is associated with a depletion of hydrogen peroxide-producing lactobacilli that may reduce vaginal defense against microorganisms including HIV[26
]. Higher vaginal pH (>4.5) that occurs with BV may also increase the availability of vaginal HIV target cells by increasing CD4 lymphocyte activation and multiplication[28
]. High vaginal pH may also increase the adherence and survival of HIV[21
]. BV has also been associated with a reduction in vaginal fluid levels of secretory leukocyte protease inhibitor (SLPI)[5
], which has been shown to block HIV infection in vitro
]. Finally, by increasing intravaginal levels of interleukin-10, BV may increase the susceptibility of macrophages to HIV[30
]. These changes, combined with the difficulties of successfully eradicating BV[31
], may explain the increased risk observed in most epidemiology studies.
Some methodological limitations to this review need to be considered. The first are concerns on whether a meta-analysis of observational studies can effectively control for confounding and bias[19
]. An attempt at reducing these was made by the preferential use of adjusted estimates in the estimation of summary measures. Meta-regression also revealed little difference between the adjusted and unadjusted estimates used in the final analysis. The second limitation has to do with the relatively few prospective studies included in this analysis. The restricted number of HIV incidence studies prohibited any sub-group analysis. However, this did not appear to be necessary as there was no heterogeneity among the estimates from these studies. The limited number of studies also prohibited any reliable analysis of other potential sources of heterogeneity such as pregnancy or age. More prospective studies are needed to accurately evaluate the causal association between BV and HIV. Third, this review was limited to that of published studies. This had little impact on the estimate from HIV incidence studies as there was no evidence of funnel plot asymmetry. The impact of publication bias on HIV prevalence studies was however unclear because of the heterogeneity in the estimates and discrepancies in the results of the various methods of assessing publication bias (Begg’s versus Egger’s methods; Duval and Tweedie’s ‘trim and fill’ random versus fixed models). The funnel plot of the POR estimates was unusual in that the one estimate that was by far the most precise (Greenblatt et al. 1999[23
]) fell well outside the range of the other estimates. Given the pronounced heterogeneity among all POR results, this result was not given a very high weight when the trim and fill analysis was conducted using a random-effects model. With a fixed-effect model, however, the exceedingly high inverse-variance weight assigned to this estimate caused the trim and fill analysis to suggest publication bias so profound that one-third of all prevalence results are unreported, all of them on the reduced-prevalence side of the null. Although some publication bias in that direction might have occurred, we are not inclined to believe that it could have been that great. In any event, the prevalence results were much too heterogeneous to warrant aggregating them to produce a single, summary estimate. We found nothing obvious about the Greenblatt et al. (1999[23
]) study that should have caused it to produce an estimate so unlike the remainder of the literature. It was one of five studies conducted in the United States and one of four US studies designed to include sizable proportions of HIV-positive and HIV-negative women. Yet it was the only one to produce an inverse association. We are inclined to consider it’s departure from the main thrust of the literature an unexplained anomaly.
Limitations in the original studies included in this meta-analysis could also impact our estimates. With BV being a time-dependent condition, prospective studies of HIV incidence are susceptible to misclassification in the definition of BV status resulting from the use of either BV status at enrollment, or BV status at prior visit as indicators of BV status immediately preceding HIV acquisition. Misclassification could also result from false positive or false negative diagnosis of BV using either clinical or bacteriologic criteria. Both of these mechanisms of misclassification are expected to be non-differential and thus lead to more conservative estimates of the effect of BV on HIV acquisition. Original studies of HIV prevalence by BV status (using case-control or cross-sectional designs), in addition to the aforementioned susceptibility to misclassifying BV status, could also be subject to selection bias when HIV cases are enrolled from high sexual-risk populations in whom BV is more frequent. If not controlled, such a bias would result in an overestimate of the association between BV and HIV. However, we do not think this may have been substantial as most studies did control for atleast one indicator of sexual risk thus attenuating the impact of selection bias. Finally, all the observational studies included in this analysis are subject to residual confounding, which could result in an underestimate or overestimate of the magnitude of the association between BV and HIV.
Despite these limitations, this review was strengthened by extensive search of published literature using multiple databases and references of identified publications. Furthermore, by separating HIV incidence studies from HIV prevalence studies, the effect of BV on incident HIV was separately analyzed. This distinction is important as studies of incident HIV are not liable to reverse causation bias that would result from HIV infected women being more likely to acquire bacterial vaginosis. The analysis of sources of heterogeneity also allowed us to identify HIV risk group, and not method of BV diagnosis, as an important source of heterogeneity in prevalence study results. Finally we refrained from using summary estimates in the presence of heterogeneity. It has been argued that even when a random effects model is used to obtain a summary estimate, the latter is not always conservative and is potentially misleading if interpreted as an average effect[32
The high prevalence of BV in certain populations (particularly those most impacted by the HIV pandemic) implies that notwithstanding the relatively modest effect of BV on HIV infection, a high proportion of HIV infection could be attributable to BV. In a population of women having a BV prevalence of 30 percent, with a relative risk of 1.6, the population attributable risk proportions (PARP), the proportion of HIV in a population that is attributable to BV, is estimated at 15 percent. Although other sexually transmitted infections (STIs) have been shown to increase the risk of HIV infection with a higher RR in the order of 2–5[33
], the relatively lower prevalence of these STIs as seen in some of the studies included in this analysis[34
] may result in similar proportions of HIV infection being attributable to these STIs as to BV.
The potential impact of BV could also be expressed in the number of women who need to have BV for each additional case of HIV. This depends on the baseline risk of HIV amongst women without BV. For instance, with a 2.0% baseline risk of HIV seroconversion among BV-negative women[21
], a relative risk of 1.6 would correspond to an absolute risk increase of approximately 1.2%, or about 1 additional case of HIV for every 80 to 90 women with BV. These data suggest that greater attention needs to be given to BV in the global fight against HIV infection. Randomized clinical trials (RCT) to determine the effect of BV control measures on HIV acquisition may be worth considering. A previous RCT of the effects of mass treatment of STIs on HIV conducted in Rakai (Uganda) used a single dose of oral metronidazole 2g and found no effect on HIV acquisition[38
]. However, although 2g of metronidazole can cause short term remission, it is not the recommended treatment[39
] thus limiting the inference that can be made on the effect of BV treatment from the Rakai study. Future RCTs assessing this effect will need to use the recommended treatment regimen with a longer duration associated with lower recurrence rates. In addition to the need to evaluate the potential of BV treatment to prevent HIV acquisition and transmission, a better understanding of its risk factors and determinants of BV recurrence is required.