Innovation: How Statistics can be used to solve several problems ranging from health, social, behavioral and natural phenomenon.

Sector/Industry Application: Health

Description: Every year, an estimated 15 million babies are born preterm (before 37 completed weeks of gestation), and this number is rising (WHO, 2021). According to the World Health Organization (WHO), Preterm birth complications are the leading cause of death among children under 5 years of age, responsible for approximately 1 million deaths in 2015. (WHO, 2021).This study is to identify the risk factors of preterm births in Nasarawa State of Nigeria using Bayesian logistic regression model; Develop a statistical model to identify the risk factors of preterm births in Nigeria using Bayesian logistic regression; Access the prevalence rate of preterm births among mothers in selected health facilities in Nasarawa State of Nigeria using Descriptive Analysis and Examine the determinant factors that significantly contribute to the incidence of preterm births in using Bayesian binary Logistic Regression model; To proffer solutions that will mitigate the incidence of preterm birth in Nigeria. Data is collected from Two(2) tertiary and Three(3) secondary facilities spread across the Three Senatorial zones of Nasarawa State. Data is being collected cleaned and analyzed statistically.

Problem: Preterm birth is a complex health problem with social, environmental, behavioral, and genetic determinants of an individual's risk and remains a major challenge in obstetrics. Recent research has caused improvements in identifying the causes of preterm birth; however, there is still little knowledge about the main causes in Nigeria.