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Geographical variation and determinants of women unemployment status in Ethiopia; A multilevel and spatial analysis from 2016 Ethiopia Demographic and Health Survey data
BACKGROUND: Unemployment is a major problem in both developed and developing countries. In Ethiopia, women unemployment is particularly high, and this makes it a grave socio-economic concern. The aim of this study is to assess the spatial distribution and identify the determinant factors of women un...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9262193/ https://www.ncbi.nlm.nih.gov/pubmed/35797384 http://dx.doi.org/10.1371/journal.pone.0270989 |
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author | Mulugeta, Solomon Sisay Gebremichael, Shewayiref Geremew Fenta, Setegn Muche Getahun, Berhanu Engidaw |
author_facet | Mulugeta, Solomon Sisay Gebremichael, Shewayiref Geremew Fenta, Setegn Muche Getahun, Berhanu Engidaw |
author_sort | Mulugeta, Solomon Sisay |
collection | PubMed |
description | BACKGROUND: Unemployment is a major problem in both developed and developing countries. In Ethiopia, women unemployment is particularly high, and this makes it a grave socio-economic concern. The aim of this study is to assess the spatial distribution and identify the determinant factors of women unemployment in Ethiopia. METHODS: The data used for the study is the Ethiopian Demographic and Health Surveys of 2016. A total of 15683 women are involved in the study. Global Moran’s I statistic and Poisson-based purely spatial scan statistics are employed to explore spatial patterns and detect spatial clusters of women unemployment, respectively. To identify factors associated with women unemployment, multilevel logistic regression model is used. RESULTS: A spatial analysis showed that there was a major spatial difference in women unemployment in Ethiopia with Global Moran’s index value of 0.3 (p<0.001). The spatial distribution of women’s unemployment varied significantly across the country. The major areas of unemployment were Afar and Somalia; southwest Tigray; North and west Oromia, and Eastern and southern parts of Amhara. Women with primary level of education(AOR = 0.88, 95%CI: 0.80, 0.98), secondary and above level of education (AOR = 0.71, 95%CI: 0.62, 0.82), women with rich wealth index (AOR = 0.79, 95% CI: 0.70, 0.90), pregnant women (AOR = 1.24, 95% CI: 1.06, 1.5), women with a male household head(AOR = 1.4, 95% CI: 1.28, 1.50), and urban women(AOR = 0.60, 95% CI: 0.50, 0.70) statistically associated with women unemployment. CONCLUSION: The unemployment rate of women in Ethiopia showed variation across different clusters. Improving entrepreneurship and women’s education, sharing business experiences, supporting entrepreneurs are potential tools for reducing the unemployment women. Moreover, creating community-based programs that prioritize participation of poor households and rural women as well as improving their access to mass media and the labor market is crucial. |
format | Online Article Text |
id | pubmed-9262193 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-92621932022-07-08 Geographical variation and determinants of women unemployment status in Ethiopia; A multilevel and spatial analysis from 2016 Ethiopia Demographic and Health Survey data Mulugeta, Solomon Sisay Gebremichael, Shewayiref Geremew Fenta, Setegn Muche Getahun, Berhanu Engidaw PLoS One Research Article BACKGROUND: Unemployment is a major problem in both developed and developing countries. In Ethiopia, women unemployment is particularly high, and this makes it a grave socio-economic concern. The aim of this study is to assess the spatial distribution and identify the determinant factors of women unemployment in Ethiopia. METHODS: The data used for the study is the Ethiopian Demographic and Health Surveys of 2016. A total of 15683 women are involved in the study. Global Moran’s I statistic and Poisson-based purely spatial scan statistics are employed to explore spatial patterns and detect spatial clusters of women unemployment, respectively. To identify factors associated with women unemployment, multilevel logistic regression model is used. RESULTS: A spatial analysis showed that there was a major spatial difference in women unemployment in Ethiopia with Global Moran’s index value of 0.3 (p<0.001). The spatial distribution of women’s unemployment varied significantly across the country. The major areas of unemployment were Afar and Somalia; southwest Tigray; North and west Oromia, and Eastern and southern parts of Amhara. Women with primary level of education(AOR = 0.88, 95%CI: 0.80, 0.98), secondary and above level of education (AOR = 0.71, 95%CI: 0.62, 0.82), women with rich wealth index (AOR = 0.79, 95% CI: 0.70, 0.90), pregnant women (AOR = 1.24, 95% CI: 1.06, 1.5), women with a male household head(AOR = 1.4, 95% CI: 1.28, 1.50), and urban women(AOR = 0.60, 95% CI: 0.50, 0.70) statistically associated with women unemployment. CONCLUSION: The unemployment rate of women in Ethiopia showed variation across different clusters. Improving entrepreneurship and women’s education, sharing business experiences, supporting entrepreneurs are potential tools for reducing the unemployment women. Moreover, creating community-based programs that prioritize participation of poor households and rural women as well as improving their access to mass media and the labor market is crucial. Public Library of Science 2022-07-07 /pmc/articles/PMC9262193/ /pubmed/35797384 http://dx.doi.org/10.1371/journal.pone.0270989 Text en © 2022 Mulugeta et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Mulugeta, Solomon Sisay Gebremichael, Shewayiref Geremew Fenta, Setegn Muche Getahun, Berhanu Engidaw Geographical variation and determinants of women unemployment status in Ethiopia; A multilevel and spatial analysis from 2016 Ethiopia Demographic and Health Survey data |
title | Geographical variation and determinants of women unemployment status in Ethiopia; A multilevel and spatial analysis from 2016 Ethiopia Demographic and Health Survey data |
title_full | Geographical variation and determinants of women unemployment status in Ethiopia; A multilevel and spatial analysis from 2016 Ethiopia Demographic and Health Survey data |
title_fullStr | Geographical variation and determinants of women unemployment status in Ethiopia; A multilevel and spatial analysis from 2016 Ethiopia Demographic and Health Survey data |
title_full_unstemmed | Geographical variation and determinants of women unemployment status in Ethiopia; A multilevel and spatial analysis from 2016 Ethiopia Demographic and Health Survey data |
title_short | Geographical variation and determinants of women unemployment status in Ethiopia; A multilevel and spatial analysis from 2016 Ethiopia Demographic and Health Survey data |
title_sort | geographical variation and determinants of women unemployment status in ethiopia; a multilevel and spatial analysis from 2016 ethiopia demographic and health survey data |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9262193/ https://www.ncbi.nlm.nih.gov/pubmed/35797384 http://dx.doi.org/10.1371/journal.pone.0270989 |
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