Abstract:
Background: One of the key demographic factors influencing acountry’s population growth is fertility.
High fertility rates present persistent challenges to Ethiopia’s population growth management and
development goals.
Objective: The main objective of the study is to identify the determinants of fertility in Ethiopia using
the EMDHS 2019.
Methods: The survey collected information from a total of 9,012 women aged 15-49 years out of
which 8885 women were considered in this study.
From several Count regression models namely; Poisson, NB, ZIP, ZINB, HP and HNB was selected
using model comparison criteria like Akaike Information Criteria and Bayesian Information Criteria.
Results: Descriptive statistics reveal that 35.93% of women in the study have never given birth, with a
mean fertility rate of 2.53 children per woman and a maximum of 15 births. The pattern of fertility
level did not vary across the different region of Ethiopia. From several Count regression models,
the ZIP regression model was found to be the most appropriate and preferred, with an AIC value of
24,290.37 and a BIC value of 25,087.53 for fitting the fertility data. The results of ZIP regression
model revealed that the variables such as family size (OR= 1.1; 95% CI: 1.095, 1.107), Amhara region
(OR= 2.431; 95% CI: 1.078, 5.482), Gambela region (OR= 0.169; 95% CI: 0.072, 0.399), Addis Abeba
region (OR= 2.32; 95% CI: 1.005, 5.538) and Dire Dawa region (OR= 2.401; 95% CI: 1.031, 5.591),
mother’s education in secondary level (OR= 1.645; 95% CI: 1.014, 2.667), higher educational level
(OR= 3.569; 95% CI: 1.970, 6.465), medium wealth index (OR= 1.757; 95% CI: 1.146, 2.694), age of
household head (OR= 0.762; 95% CI: 0.725, 0.8.2), and mother’s marital status of women’s category
other (OR= 57.314; 95% CI: 40.437, 81.235) were all found to be statistically significant at the 5%
level of significance in fertility level
Conclusion: In this study, the highest fertility level was observed in Somali regions, with no variation
across Ethiopia. Based on different model comparison techniques, ZIP regression model was found to
be the most appropriate to fit the fertility level data. Key determinants of fertility included family size,
region, education, wealth index, and marital status.
