Non-Booking For Antenatal Care And Risks For Vertical HIV Transmission Among Women In Chitungwiza, Zimbabwe: A Cross-Sectional Study.

Background: The success of prevention of mother to child transmission of HIV (PMTCT ) dependents on pregnant women accessing antenatal care (ANC) services. Failure to book for ANC through the course of pregnancy presents a missed opportunity for PMTCT and a high risk for maternal HIV transmission. Whilst unbooking was about 6% in Zimbabwe, it is important to determine the local burden of women both un-booked for ANC and living with HIV among pregnant women. in Chitungwiza city This study aimed at determining the proportion of women un-booked for antenatal care and among them, the proportion of women who were with HIV and to identify risk factors associated with un-booking in Chitungwiza city in Zimbabwe, Methods: : A cross-sectional study was conducted involving a review of clinic records for 4400 women who received postnatal care at all 4 maternity clinics in Chitungwiza city between 01 January 2017 and 31 December 2017. The Chi-square test was used to determine association between participants’ booking status and socio-demographic variables. Multiple logistic regression was used to determine risk factors associated with booking status while adjusting for other study variables. All statistics tests’ decisions were concluded at 5% level of significance. All data analysis was performed using STATA (version 13) statistical package. Results: : A total of 19% of pregnant women were un-booked for ANC, while a total of 3% of the women were both un-booked and living with HIV. The women with HIV were 0.24 times less likely to book for ANC than HIV negative women, adjusted OR 0.76, 95% CI (0.61-0.98) P=0. 037. Women aged 20-34 years were 1.3 times more likely to book than the teenagers, adjusted OR 1.3, 95% CL (1.04-1.62), P=0.022. Conclusion: Not booking for ANC is a problem in the city of Chitungwiza, affecting access to PMTCT services. The results from this study illustrate the need to use local data for local planning rather than national data.