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Section

Mathematics and Computational Sciences

Abstract

A cesarean section (CS) is a surgical technique in which a baby is delivered through an abdomen and uterine incision following fetal viability. It is imperative to identify the factors that influence the use of CS to reduce the needless use of this life-saving procedure and increase its availability for those who need it most. Therefore, this study assesses the prevalence and predictors of cesarean delivery in a tertiary hospital in Taraba state, Nigeria. Information of pregnant women who came for delivery to Federal Medical Center, Jalingo, Taraba state Nigeria from August 2021 to August 2023 was collected. Binary Logistic Regression using the probit model was used to analyse the data. p<0.05 was considered to be statistically significant. During the study period, there were 747 deliveries 115 by caesarean section (15.4%). The results show that maternal age, location, occupation, maternal education, maternal weight, birth weight, and number of antenatal care (ANC) visits significantly predict cesarean delivery. The results of this research will help to make policies and decisions related to health issues and intensify efforts to make provisions and precautionary steps on managing and controlling cesarean birth.

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