Analysis of caesarean section birth using poisson regression model (Case study : Narok North District)

Abstract

The living standards of people in a society contribute to a great deal in the development of a country. Kenya being among the dev loping countries in Africa calls for an immediate attention to total investment in the health sector. Choosing the safest method of delivery and preventing preterm labour to reduce the number of preterrn births and improve the outcomes for mother and baby is an obstetric challenge. Several cases of maternal and infant mortality at birth have been reported in Kenya and thus the need for our study in Obstetrics. The aim of this study was to develop a statistical model that will cater for the uncertainty of the future Crate with the objective being to determine the association between; mode of delivery and maternal mortality, mode of delivery and infant mortality and to determine the proportion of birth by Caesarean Section in Narok North District. The study employed the use of Poisson regression model as a tool for prediction of the number of caesarean section deliveries affected by a number of covariates. The method of Maximum Likelihood Estimation (MLE) was used for parameter estimation. Simple Random Sarnpling (SRS) was the technique involved in the selection of secondary data from public health care facilities' record and data analysis carried out using the R Statistical Program.