Effect of Fertility Desire-Based Service on HIV Seroconversion Among Serodiscordant Partners: A 12-year Retrospective Cohort Study.

Abstract

Background: Fertility desire-based service guided by behavioral theory is a potential strategy to mitigate the HIV transmission risk, while related evidence remains scarce. We examined the long-term effect of theory-guided fertility desire-based services on HIV seroconversion between seropositive and seronegative partners in areas with high HIV prevalence and a cultural emphasis on fertility in China.

Methods: We established a retrospective cohort by recruiting 8653 seropositive partners with seronegative partners between January 1, 2009, and December 31, 2020, in Liangshan, China. The differences in HIV seroconversion between partners who received fertility desire-based services guided by the extended Information-Motivation-Behavioral Skills model and those who did not were estimated, based on multivariable and inverse probability weighting adjusted multivariable Cox regression models. Subgroup analysis was conducted based on participants' demographic and HIV-related characteristics.

Results: Among the 8653 HIV-seropositive partners, 7958 (92.0%) and their seronegative partners received fertility desire-based services. At the end of the 12-year follow-up, 18 seronegative partners who did not receive fertility desire-based services experienced HIV seroconversion (incidence density: 7.4/1000 person-years), while 98 seronegative partners receiving such services exhibited HIV seroconversion (3.4/1000 person-years). Fertility desire-based services significantly reduced the risk of HIV seroconversion according to multivariable (HR = 0.32, 95% CI: 0.19 to 0.53) and inverse probability weighting-adjusted multivariable Cox regression models (HR = 0.48, 95% CI: 0.27 to 0.84). The effect of fertility desire-based services was more pronounced in men and those older than 40 years.

Conclusions: Fertility desire-based services based on the extended Information-Motivation-Behavioral Skills model may help reduce the HIV transmission risk between seropositive and seronegative partners in areas with high HIV prevalence.