ArticleJournal of health, population, and nutrition2024
Exploring the determinants of fertility rates in Ethiopia: a decomposition analysis using count regression models with a focus on urban and rural residence, based on the 2019 Ethiopian demographic health survey.
Article in Journal of health, population, and nutrition, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
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2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Tetanus toxoid vaccination coverage and associated factors among pregnant women in East Africa: systematic review and meta-analysis.BMC public health · 2025Pooled it
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Abstract
introductionFertility refers to the biological capacity to reproduce and have children. It is a key aspect of reproductive health influenced by various factors. Therefore, this study aims to explore the determinants of fertility rates based on urban and rural settings in Ethiopia.
methodA stratified two-stage cluster sampling approach was used, employing data from the 2019 Ethiopian Mini Demographic and Health Survey ( https://dhsprogram.com ). The study comprised 8,885 women aged 15 to 49 years. The study employed Stata 17, and the data was described using descriptive statistics. Associations were examined using decomposition analysis and negative binomial regression. The Incidence Rate Ratio and p-value were used to determine the statistical significance of the variables examined.
resultsThe negative binomial regression found that factors such as maternal age (IRR, 1.08, P-value,0.00), living in rural (IRR,1.09, P-value,0.00), being Muslim (IRR,1.13, P-value,0.00), being from other religious groups (IRR,1.16, P-value,0.00), having six up to nine household members (IRR,1.24, P-value,0.00), having greater than nine household member(IRR,1.14, P-value,0.04), having one child under five year (IRR,1.35, P-value,0.00), having two children under five year (IRR,1.77, P-value,0.00), and having more than two under five years (IRR,1.99, P-value,0.00), being currently pregnant (IRR,1.08, P-value,0.00), use of contraceptive(IRR,1.13, P-value,0.00) are positively associated with bearing more children. On the other hand, completing primary education (IRR,0.84, P-value,0.00), secondary education (IRR,0.61, P-value,0.00), being from the richest household (IRR = 0.94, P-value,0.00), and being single/divorced and widowed (IRR,0.49, P-value,0.00) are negatively associated with having more children because their IRR is less than one. The decomposition analysis also demonstrated that marital status has a stronger negative correlation with fertility in rural compared to urban settings. Additionally, the number of children under five exerts a greater influence on fertility in urban areas.
conclusionthe study found significant rural-urban differences in the factors shaping fertility in Ethiopia. While demographics like maternal age, education, and wealth influenced fertility in both settings, the relationships varied in nature and magnitude. To address this, Policymakers should develop targeted fertility programs that address the unique needs and challenges faced by rural and urban populations.
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