Using Binary Logistic and Quantile Regressions for Determinants of Preterm Birth in Ghana. Case Study; Ahafo Ano South District, Ashanti Region

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Using data obtained from the Biostatistics Unit at the Mankranso Government Hospital, this thesis examines the prevalence rate and determinant factors of preterm birth at the Ahafo Ano South District. Retrospective data on relevant variables of delivered mothers and the neonates were extracted from the database of the unit. The extracted data used in this hospital-based study spans from January 2012 to the rst quarter of 2013. The study excluded still-birth or macerated babies from its analysis. The binary quantile and logistic regressions were employed to ascertain the causal factors of preterm birth and the associated causal e ects. Out of the 711 live births, 336, representing 47.3% were born preterm; meaning approximately, every 4 out of 9 babies are born preterm in the district. From the binary logit regression, the study identi ed the baby's weight, the age of the delivered mother, intermittent preventive treatment and number of conceived fetuses, as signi cant determinant factors of pretermbirth. In addition to these variables, the bivarite analysis included gravidity and parity. The Bayesian binary quantile regression at a lower quantile of = 0:05 recorded signi cant varying e ects for maternal age, APGAR score of the newly born at 5 minutes, antenatal, delivery type, parity and complication during the pregnancy cycle. However, at the median and upper-tail quantiles, no signi cant e ects were recorded.
A thesis submitted to the Department of Mathematics, Kwame Nkrumah University of Science and Technology in partial fulllment of the requirements for the degree of Master of Philosophy, 2014