Application of Two Level Count Regression Modeling on the Determinants of Fertility among Married Women in Ethiopia

Abstract

\n Background: Fertility is the element of population dynamics that has a vital contribution towards changing population size and structure over time. The global population showed a major increment from time to time because of these dynamics, particularly in south Asia and sub-Saharan Africa including Ethiopia. So this study targeted on the factors affecting fertility among married women in Ethiopia through the framework of multilevel count regression analysis using EDHS 2016 data.Methods: The sampling design for EDHS 2016 was a two-stage stratified cluster sampling design, where stratification was achieved by separating every region into urban and rural areas except the Addis Ababa region. Results: Among the random sample of 6141 women in the country, 27150 births were recorded based on EDHS 2016 report. The histograms showed that the data has a positively skewed distribution extremely picked at the beginning. Two- level negative binomial regression model was fitted to spot out the determinants of fertility among married women in Ethiopia because it has the smallest value for the fit statistics and the variance of the data was higher than its mean.Conclusion: Findings from the study revealed that contraception method used, residence, educational level of women, women’s age at first birth, and proceeding birth interval were the major predictors of fertility among married women in Ethiopia. Moreover, the estimates from the random effect result revealed that there is more fertility variation between the enumeration areas than within the enumeration areas. Application of standard models by ignoring this variation ought to embrace spurious results, then multilevel modeling is recommended for such types of hierarchical data.