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• W4297662922 abstract "Abstract Background In many countries, deferring first births and increasing the interval between births has played an important role in lowering fertility rates. Any country's fertility rate is a key demographic indicator, and it has always been important to closely monitor changes in the pattern of births to determine how many children are being conceived. Any country's fertility rate is a key demographic indicator, and it has always been important to closely monitor changes in the pattern of births to determine how many children are being conceived. The primary goal of this study is to apply zero-truncated regression models to estimate the number of children ever born per mother in Ethiopia from the MiniDHS 2019. Mothods The data collection was carried out by the Ethiopian Public Health Institute (EPHI) in collaboration with the Central Statistical Agency (CSA) and the Federal Ministry of Health. Zero truncated count regression models were used to identify the determinant of the number of children ever born from Ethiopian mothers. Results The response variable (children ever born) has a range of 1–15. There were 5,753 observations in this study, with the mean and standard deviation of the response variable being 4.04 and 2.48, respectively. According to AIC and BIC model selection criteria and over-dispersed parameter in zero-truncated negative binomial assured the appropriateness of zero-truncated Poisson regression model for this dataset. Conclusion The number of children ever born increases with the age group of mothers, but it decreases as mothers' education levels rise. Similarly, region, religion, wealth index, residence area, number of living children, the number of births in the last five years, age at first birth all had a significant impact on the number of children ever born." @default.
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• W4297662922 date "2022-09-08" @default.
• W4297662922 modified "2023-09-26" @default.
• W4297662922 title "Determinants of the number of children born in Ethiopia, evidenced from 2019 miniEDHS: Using zero-truncated count regression models" @default.
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• W4297662922 doi "https://doi.org/10.21203/rs.3.rs-1983782/v1" @default.
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