Determinants of Under-five Child Mortality in the East End of Freetown, Sierra Leone: A Hurdle Negative Binomial Modelling Approach

Abstract

**Objective:** To identify the main determinants of under-five child mortality in the eastern region of Sierra Leone's capital using the most appropriate count regression modeling approach.

**Introduction:** Sierra Leone has seen rising under-five mortality, especially in densely populated areas like the eastern part of its capital. Understanding the main factors associated with such under-five mortality is vital for guiding healthcare policies and promoting appropriate interventions to reduce its risk.

**Methods:** In this research, 755 observations were randomly collected from the residents of the study area through interviews and questionnaires. This paper fitted several count models: Poisson and Generalized Poisson regressions, Zero-inflated Poisson regression, Negative binomial regression, and the Hurdle Negative Binomial regression. To compare the models based on how well they fit the count data at hand, this research used the Vuong non-nested test, the Akaike Information Criterion, the Bayesian Information Criterion, and a graphical method called the hanging rootogram.

**Results:** The hurdle negative binomial regression model is identified as the preferred model that best fits the data used in this study. The best-fitting model showed that the mother's age, mosquito net use, family income, and child feeding practices are the main determinants.

**Conclusion:** This study revealed that a younger maternal age, a reduction in family income, a decline in both the frequency and quality of child feeding, and a decrease in the number of times a child sleeps under a mosquito net were each associated with a heightened risk of mortality among children under five in the study area.