Teenagers Fertility Variation among Regional States of Ethiopia; Application of Multilevel Logistic Regression and Population Averaged Models.

Abstract

Teenage fertility is defined as a teenage girl, usually within the ages of 13-19, becoming fertile. Worldwide, adolescents suffer from a disproportionate share of early marriage, unwanted pregnancies, unsafe abortions, and sexually transmitted infections. Sub-Saharan African countries have high total and teenage fertility rates compared to the rest of the world. Ethiopia has a high incidence of unwanted pregnancies and incomplete and risky/septic abortions, particularly among adolescents. Objectives: The general objective of this study is to assessing teenager fertility variation among regional states of Ethiopia. Methods: This study has been used data from the 2016 Ethiopia Demographic and Health Survey (2016 EDHS). The researcher has been selected all teenagers aged 15-19 years of age at time of interview. The total sample of this study contains 3498 teenagers from nine regional states and two administrative cities in Ethiopia. The population of this study have been included all female teenagers aged 15-19 years of age at the time of interview. Multilevel Logistic and Population Average Models have been applied to assess the determinants and teenagers fertility variation in regional states of Ethiopia. Results: The total of 3498 teenagers from nine regional states and two administrative cities in Ethiopia were eligible for this study. Among these eligible teenagers, 359 (10.263%) teenagers have been born child at the time of interview. From the significant regions the highest OR was seen in Harari(OR=4.44) and the lowest OR was seen in Affar(2.6) regions respectively. Conclusion: Multilevel Logistic Regression with random slope and random intercept is found to be a good model to fit, compared with Random intercept models and Logistic regression model. From Marginal (GEE) models the model with independent correlation structure is good to fit the given data. The variables: Religion, Education Level, Wealth index, Contraceptive method, Knowledge of Ovulatory cycle and Exposure to any mass media were found significant.