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Spatial and multilevel analysis of unskilled birth attendance in Chad

BACKGROUND: Unskilled birth attendance is a major public health concern in Sub-Saharan Africa (SSA). Existing studies are hardly focused on the socio-demographic correlates and geospatial distribution of unskilled birth attendance in Chad (a country in SSA), although the country has consistently bee...

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Autores principales: Acquah, Evelyn, Nyarko, Samuel H., Boateng, Ebenezer N. K., Dickson, Kwamena Sekyi, Addo, Isaac Yeboah, Adzrago, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9382725/
https://www.ncbi.nlm.nih.gov/pubmed/35974406
http://dx.doi.org/10.1186/s12889-022-13972-6
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author Acquah, Evelyn
Nyarko, Samuel H.
Boateng, Ebenezer N. K.
Dickson, Kwamena Sekyi
Addo, Isaac Yeboah
Adzrago, David
author_facet Acquah, Evelyn
Nyarko, Samuel H.
Boateng, Ebenezer N. K.
Dickson, Kwamena Sekyi
Addo, Isaac Yeboah
Adzrago, David
author_sort Acquah, Evelyn
collection PubMed
description BACKGROUND: Unskilled birth attendance is a major public health concern in Sub-Saharan Africa (SSA). Existing studies are hardly focused on the socio-demographic correlates and geospatial distribution of unskilled birth attendance in Chad (a country in SSA), although the country has consistently been identified as having one of the highest prevalence of maternal and neonatal deaths in the world. This study aimed to analyse the socio-demographic correlates and geospatial distribution of unskilled birth attendance in Chad. METHODS: The study is based on the latest Demographic and Health Survey (DHS) data for Chad. A total of 10,745 women aged between 15 and 49 years were included in this study. A multilevel analysis based on logistic regression was conducted to estimate associations of respondents’ socio-demographic characteristics with unskilled birth attendance. Geographic Information System (GIS) mapping tools, including Getis-Ord Gi hotspot analysis tool and geographically weighted regression (GWR) tool, were used to explore areas in Chad with a high prevalence of unskilled birth attendance. RESULTS: The findings show that unskilled birth attendance was spatially clustered in four Chad departments: Mourtcha, Dar-Tama, Assoungha, and Kimiti, with educational level, occupation, birth desire, birth order, antenatal care, and community literacy identified as the spatial predictors of unskilled birth attendance. Higher educational attainment, higher wealth status, cohabitation, lowest birth order, access to media, not desiring more births, and higher antenatal care visits were associated with lower odds of unskilled birth attendance at the individual level. On the other hand, low community literacy level was associated with higher odds of unskilled birth attendance in Chad whereas the opposite was true for urban residency. CONCLUSIONS: Unskilled birth attendance is spatially clustered in some parts of Chad, and it is associated with various disadvantaged individual and community level factors. When developing interventions for unskilled birth attendance in Chad, concerned international bodies, the Chad government, maternal health advocates, and private stakeholders should consider targeting the high-risk local areas identified in this study. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-022-13972-6.
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spelling pubmed-93827252022-08-18 Spatial and multilevel analysis of unskilled birth attendance in Chad Acquah, Evelyn Nyarko, Samuel H. Boateng, Ebenezer N. K. Dickson, Kwamena Sekyi Addo, Isaac Yeboah Adzrago, David BMC Public Health Research BACKGROUND: Unskilled birth attendance is a major public health concern in Sub-Saharan Africa (SSA). Existing studies are hardly focused on the socio-demographic correlates and geospatial distribution of unskilled birth attendance in Chad (a country in SSA), although the country has consistently been identified as having one of the highest prevalence of maternal and neonatal deaths in the world. This study aimed to analyse the socio-demographic correlates and geospatial distribution of unskilled birth attendance in Chad. METHODS: The study is based on the latest Demographic and Health Survey (DHS) data for Chad. A total of 10,745 women aged between 15 and 49 years were included in this study. A multilevel analysis based on logistic regression was conducted to estimate associations of respondents’ socio-demographic characteristics with unskilled birth attendance. Geographic Information System (GIS) mapping tools, including Getis-Ord Gi hotspot analysis tool and geographically weighted regression (GWR) tool, were used to explore areas in Chad with a high prevalence of unskilled birth attendance. RESULTS: The findings show that unskilled birth attendance was spatially clustered in four Chad departments: Mourtcha, Dar-Tama, Assoungha, and Kimiti, with educational level, occupation, birth desire, birth order, antenatal care, and community literacy identified as the spatial predictors of unskilled birth attendance. Higher educational attainment, higher wealth status, cohabitation, lowest birth order, access to media, not desiring more births, and higher antenatal care visits were associated with lower odds of unskilled birth attendance at the individual level. On the other hand, low community literacy level was associated with higher odds of unskilled birth attendance in Chad whereas the opposite was true for urban residency. CONCLUSIONS: Unskilled birth attendance is spatially clustered in some parts of Chad, and it is associated with various disadvantaged individual and community level factors. When developing interventions for unskilled birth attendance in Chad, concerned international bodies, the Chad government, maternal health advocates, and private stakeholders should consider targeting the high-risk local areas identified in this study. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-022-13972-6. BioMed Central 2022-08-16 /pmc/articles/PMC9382725/ /pubmed/35974406 http://dx.doi.org/10.1186/s12889-022-13972-6 Text en © The Author(s) 2022 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
Acquah, Evelyn
Nyarko, Samuel H.
Boateng, Ebenezer N. K.
Dickson, Kwamena Sekyi
Addo, Isaac Yeboah
Adzrago, David
Spatial and multilevel analysis of unskilled birth attendance in Chad
title Spatial and multilevel analysis of unskilled birth attendance in Chad
title_full Spatial and multilevel analysis of unskilled birth attendance in Chad
title_fullStr Spatial and multilevel analysis of unskilled birth attendance in Chad
title_full_unstemmed Spatial and multilevel analysis of unskilled birth attendance in Chad
title_short Spatial and multilevel analysis of unskilled birth attendance in Chad
title_sort spatial and multilevel analysis of unskilled birth attendance in chad
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9382725/
https://www.ncbi.nlm.nih.gov/pubmed/35974406
http://dx.doi.org/10.1186/s12889-022-13972-6
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