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Spatial distribution and predictors of domestic violence against women: evidence from analysis of Ethiopian demographic health survey 2016
BACKGROUND: Violence against women particularly that is committed by an intimate partner is becoming a social and public health problem across the world. Studies show that the spatial variation in the distribution of domestic violence was commonly attributed to neighborhood-level predictors. Despite...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8442426/ https://www.ncbi.nlm.nih.gov/pubmed/34525981 http://dx.doi.org/10.1186/s12905-021-01465-4 |
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author | Seid, Elias Melese, Tesfahun Alemu, Kassahun |
author_facet | Seid, Elias Melese, Tesfahun Alemu, Kassahun |
author_sort | Seid, Elias |
collection | PubMed |
description | BACKGROUND: Violence against women particularly that is committed by an intimate partner is becoming a social and public health problem across the world. Studies show that the spatial variation in the distribution of domestic violence was commonly attributed to neighborhood-level predictors. Despite the prominent benefits of spatial techniques, research findings are limited. Therefore, the current study intends to determine the spatial distribution and predictors of domestic violence among women aged 15–49 in Ethiopia. METHODS: Data from the Ethiopian demographic health survey 2016 were used to determine the spatial distribution of domestic violence in Ethiopia. Spatial auto-correlation statistics (both Global and Local Moran’s I) were used to assess the spatial distribution of domestic violence cases in Ethiopia. Spatial locations of significant clusters were identified by using Kuldorff’s Sat Scan version 9.4 software. Finally, binary logistic regression and a generalized linear mixed model were fitted to identify predictors of domestic violence. RESULT: The study found that spatial clustering of domestic violence cases in Ethiopia with Moran’s I value of 0.26, Z score of 8.26, and P value < 0.01. The Sat Scan analysis identifies the primary most likely cluster in Oromia, SNNP regions, and secondary cluster in the Amhara region. The output from regression analysis identifies low economic status, partner alcohol use, witnessing family violence, marital controlling behaviors, and community acceptance of wife-beating as significant predictors of domestic violence. CONCLUSION: There is spatial clustering of IPV cases in Ethiopia. The output from regression analysis shows that individual, relationship, and community-level predictors were strongly associated with IPV. Based upon our findings, we give the following recommendation: The government should give prior concern for controlling factors such as high alcohol consumption, improper parenting, and community norm that encourage IPV that were responsible for IPV in the identified hot spot areas. |
format | Online Article Text |
id | pubmed-8442426 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-84424262021-09-15 Spatial distribution and predictors of domestic violence against women: evidence from analysis of Ethiopian demographic health survey 2016 Seid, Elias Melese, Tesfahun Alemu, Kassahun BMC Womens Health Research Article BACKGROUND: Violence against women particularly that is committed by an intimate partner is becoming a social and public health problem across the world. Studies show that the spatial variation in the distribution of domestic violence was commonly attributed to neighborhood-level predictors. Despite the prominent benefits of spatial techniques, research findings are limited. Therefore, the current study intends to determine the spatial distribution and predictors of domestic violence among women aged 15–49 in Ethiopia. METHODS: Data from the Ethiopian demographic health survey 2016 were used to determine the spatial distribution of domestic violence in Ethiopia. Spatial auto-correlation statistics (both Global and Local Moran’s I) were used to assess the spatial distribution of domestic violence cases in Ethiopia. Spatial locations of significant clusters were identified by using Kuldorff’s Sat Scan version 9.4 software. Finally, binary logistic regression and a generalized linear mixed model were fitted to identify predictors of domestic violence. RESULT: The study found that spatial clustering of domestic violence cases in Ethiopia with Moran’s I value of 0.26, Z score of 8.26, and P value < 0.01. The Sat Scan analysis identifies the primary most likely cluster in Oromia, SNNP regions, and secondary cluster in the Amhara region. The output from regression analysis identifies low economic status, partner alcohol use, witnessing family violence, marital controlling behaviors, and community acceptance of wife-beating as significant predictors of domestic violence. CONCLUSION: There is spatial clustering of IPV cases in Ethiopia. The output from regression analysis shows that individual, relationship, and community-level predictors were strongly associated with IPV. Based upon our findings, we give the following recommendation: The government should give prior concern for controlling factors such as high alcohol consumption, improper parenting, and community norm that encourage IPV that were responsible for IPV in the identified hot spot areas. BioMed Central 2021-09-15 /pmc/articles/PMC8442426/ /pubmed/34525981 http://dx.doi.org/10.1186/s12905-021-01465-4 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Seid, Elias Melese, Tesfahun Alemu, Kassahun Spatial distribution and predictors of domestic violence against women: evidence from analysis of Ethiopian demographic health survey 2016 |
title | Spatial distribution and predictors of domestic violence against women: evidence from analysis of Ethiopian demographic health survey 2016 |
title_full | Spatial distribution and predictors of domestic violence against women: evidence from analysis of Ethiopian demographic health survey 2016 |
title_fullStr | Spatial distribution and predictors of domestic violence against women: evidence from analysis of Ethiopian demographic health survey 2016 |
title_full_unstemmed | Spatial distribution and predictors of domestic violence against women: evidence from analysis of Ethiopian demographic health survey 2016 |
title_short | Spatial distribution and predictors of domestic violence against women: evidence from analysis of Ethiopian demographic health survey 2016 |
title_sort | spatial distribution and predictors of domestic violence against women: evidence from analysis of ethiopian demographic health survey 2016 |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8442426/ https://www.ncbi.nlm.nih.gov/pubmed/34525981 http://dx.doi.org/10.1186/s12905-021-01465-4 |
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