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Nature Research, Scientific Reports, 1(11), 2021

DOI: 10.1038/s41598-021-92157-4

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Individual and community level factors associated with unintended pregnancy among pregnant women in Ethiopia

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

AbstractUnintended pregnancy is among the major challenges of public health and a major reproductive health issue, due to its implications on the health, economic and social life of a woman and her family mainly in low and middle-income countries, particularly sub-Saharan Africa. The study aimed to assess unintended pregnancy and associated factors among pregnant women in Ethiopia using multilevel analysis from the EDHS 2016. We used the data from the 2016 Ethiopian Demographic and Health Survey, comprised of 1122 pregnant women. The prevalence of unintended pregnancy was determined through descriptive statistics and multilevel logistic regression was performed to identify factors associated with unintended pregnancy. Variables with a p-value < 0.05 in the selected model were considered as significantly associated and an adjusted odds ratio was used to determine the strength and direction of the association. The prevalence of unintended pregnancy was 29.7% (CI 27.0%, 32.4%), of which 20.4% were mistimed and 9.3% unwanted. Being multi-para and fertility preference to have no more child were associated with a higher risk of unintended pregnancy whereas husbands' polygamy relation, having no women autonomy, and living in Afar and Somali regions showed a less likely risk of experiencing an unintended pregnancy. This study showed that the proportion of women who experienced unintended pregnancy is considerably high. Parity, fertility preference, polygamy relation, women autonomy, and region were identified factors associated with unintended pregnancy. Therefore, policymakers at all levels, reproductive health experts, and concerned organizations should emphasize minimizing unintended pregnancy targeting the regional variation at large. Researchers have to explore the regional variations through a qualitative study.