College of Natural and Computational Sciences

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    A Multilevel Structural Equation Modeling Approach to Estimate Incompletion of Childhood Vaccination among 12-39 months old in Ethiopia
    (Mekelle University, 2023-11-28) Brtawit Aregay
    Background: Childhood immunization is a worldwide ultimate public health intervention significantly plummeting morbidity and mortality linked with preventable diseases. Despite significant efforts to improve vaccination coverage, a considerable proportion of children aged 12-39 months in Ethiopia remaining incompletely vaccinated. Objective: This study intended to employ a Multilevel Structural Equation Modeling (MSEM) approach and framework to broadly analyze the elements contributing to incompleteness of childhood vaccination in Ethiopia. Methods: The study utilized secondary data from the Ethiopian Mini Demographic and health Survey (EMDHS) and adopted both qualitative and quantitative research approaches under descriptive research design. A multilevel logistic regression approach was employed to capture the interplay between individual and community-level factors impacting childhood vaccination status. At individual level, age, sex, education, marital status, and vaccination card were considered, while at the community level, factors such as antenatal care, place of delivery, poverty, media exposure, and living area were explored. The study established a conceptual model integrating these factors and applied a multilevel structural equation modeling approach to estimate their direct and indirect relations with incomplete childhood vaccination. On top of this, the pathways and interdependencies between variables were examined to elucidate the complex associations influencing vaccination outcomes. Results: Preliminary analyses revealed significant direct effects of urban residence (AOR=2.1 & 95%CI of AOR [1.1,3.6] and age (AOR=11.5 & 95% CI of AOR [1.1,2.1]) On childhood vaccination. Additionally, community-level factors such as primary school maternal education (AOR=1.8 & 95% CI of AOR [1.3, 2.5]) and antenatal care follow-up (ANC: AOR=1.5 & 95%CI of AOR [1.0,2.2]) demonstrated varying degrees of influence on vaccination status. Conclusions: The findings from this study grasp noteworthy implications and roles for national and global public health interventions. By identifying the multilayered elements impacting incomplete child vaccination, this research aims to provide evidence-based recommendations to reinforce vaccination programs and reduce the burden of vaccine-preventable diseases among Ethiopian children aged 12-39 months. Furthermore, the contributions of this study lie in its application of a wide-ranging multilevel structural equation modeling (MSEM) approach and framework, offering a nuanced understanding of the intricate web of determinants contributing to incomplete childhood vaccination in Ethiopia. The results are expected to inform targeted interventions and policy changes aimed at enhancing vaccination rates and safeguarding the health of children in national and regional level of Ethiopia as particular and worldwide in general.