ART reduces fertility differences by HIV status among women living in sub-Saharan Africa

Measuring the impact of antiretroviral therapy roll-out on population level fertility in three African countries. 

Marston M, Nakiyingi-Miiro J, Hosegood V, Lutalo T, Mtenga B, Zaba B, and on behalf of the ALPHA network. PLoS One. 2016 Mar 25;11(3):e0151877. doi: 10.1371/journal.pone.0151877. eCollection 2016.

Background: UNAIDS official estimates of national HIV prevalence are based on trends observed in antenatal clinic surveillance, after adjustment for the reduced fertility of HIV positive women. Uptake of ART may impact on the fertility of HIV positive women, implying a need to re-estimate the adjustment factors used in these calculations. We analyse the effect of antiretroviral therapy (ART) provision on population-level fertility in Southern and East Africa, comparing trends in HIV infected women against the secular trends observed in uninfected women.

Methods: We used fertility data from four community-based demographic and HIV surveillance sites: Kisesa (Tanzania), Masaka and Rakai (Uganda) and uMkhanyakude (South Africa). All births to women aged 15-44 years old were included in the analysis, classified by mother's age and HIV status at time of birth, and ART availability in the community. Calendar time period of data availability relative to ART introduction varied across the sites, from 5 years prior to ART roll-out, to 9 years after. Calendar time was classified according to ART availability, grouped into pre ART, ART introduction (available in at least one health facility serving study site) and ART available (available in all designated health facilities serving study site). We used Poisson regression to calculate age adjusted fertility rate ratios over time by HIV status, and investigated the interaction between ART period and HIV status to ascertain whether trends over time were different for HIV positive and negative women.

Results: Age-adjusted fertility rates declined significantly over time for HIV negative women in all four studies. However HIV positives either had no change in fertility (Masaka, Rakai) or experienced a significant increase over the same period (Kisesa, uMkhanyakude). HIV positive fertility was significantly lower than negative in both the pre ART period (age adjusted fertility rate ratio (FRR) range 0.51 95%CI 0.42-0.61 to 0.73 95%CI 0.64-0.83) and when ART was widely available (FRR range 0.57 95%CI 0.52-0.62 to 0.83 95%CI 0.78-0.87), but the difference has narrowed. The interaction terms describing the difference in trends between HIV positives and negatives are generally significant.

Conclusions: Differences in fertility between HIV positive and HIV negative women are narrowing over time as ART becomes more widely available in these communities. Routine adjustment of ANC data for estimating national HIV prevalence will need to allow for the impact of treatment.

Abstract  Full-text [free] access 

Editor’s notes: Antenatal care (ANC) clinics records on demographic characteristics and HIV status of attenders are a major component of primary data used to estimate HIV prevalence in sub-Saharan Africa. Prior to scale-up of antiretroviral therapy (ART), the fertility of women living with HIV was lower than that for people without HIV. This means that prevalence estimates from ANC data were adjusted to avoid underestimating the true population fertility rates.

This paper analyses the changing fertility patterns in four longitudinal community-based cohorts in eastern and southern Africa. The study finds that differences in fertility rates between women living with HIV and women without HIV are narrowing as ART is scaled-up, although substantial differences still exist. There was considerable variation in the patterns between the sites reflecting the differing local epidemic profiles. The authors explain this variation as being due to various factors including biological (increased fertility associated with viral suppression), or behavioural (increased fertility among women experiencing widowhood and then forming new partnerships). The impact of treatment on fertility needs to be incorporated into models of HIV prevalence estimated from ANC data, to inform national policy makers measuring their progress towards HIV elimination targets.

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