Unraveling New Insights: Exploring Risk Factors of Under-Five Mortality in Somaliland using the First-Ever SLDHS 2020 Data and Count Data Regression Models

Abstract The high prevalence of zero counts in child mortality distribution in Somaliland prompts an exploration into whether distinct generating processes exist for child mortality and their frequency per mother. This study aims to identify an appropriate count regression model for the number of children who died per mother in Somaliland, addressing concerns of under-dispersion and zero-inflation. Addition[1]ally, it seeks to determine the risk factors associated with under-five mortality and their frequency. The analysis utilizes data from the nationally representative 2020 Somaliland Demographic and Health Survey (SLDHS), where 28.1% of the 4,615 surveyed women reported no under-five mortality. These zero counts may arise from structural or sampling factors, leading to the investigation of two-part zero-inflated and hurdle-count regression models alongside standard one-part count regression models. Diagnostic tools, such as the likelihood ratio test, The Akaike information criterion (AIC) and the Bayesian information criterion (BIC), are employed to determine the most suitable model. The hurdle Poisson regression model emerges as the best fit. The findings highlight several significant factors associated with under-five mortality per mother, including child sex, number of children ever born, access to clean water sources and toilet facilities, geographic region, wealth index, breastfeeding, mothers’ age at first birth, and mothers’ education. Understanding and addressing these factors can guide targeted interventions and policies aimed at reducing under-five mortality and improving child health outcomes. Furthermore, promoting deliveries at healthcare institutions is recommended for mothers.