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Time trends, geographical, socio-economic, and gender disparities in neonatal mortality in Burundi: evidence from the demographic and health surveys, 2010–2016

BACKGROUND: Programmatic and research agendas surrounding neonatal mortality are important to help countries attain the child health related 2030 Sustainable Development Goal (SDG). In Burundi, the Neonatal Mortality Rate (NMR) is 25 per 1000 live births. However, high quality evidence on the over t...

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Autores principales: Yaya, Sanni, Zegeye, Betregiorgis, Ahinkorah, Bright Opoku, Ameyaw, Edward Kwabena, Seidu, Abdul-Aziz, Shibre, Gebretsadik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7663869/
https://www.ncbi.nlm.nih.gov/pubmed/33292519
http://dx.doi.org/10.1186/s13690-020-00501-3
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author Yaya, Sanni
Zegeye, Betregiorgis
Ahinkorah, Bright Opoku
Ameyaw, Edward Kwabena
Seidu, Abdul-Aziz
Shibre, Gebretsadik
author_facet Yaya, Sanni
Zegeye, Betregiorgis
Ahinkorah, Bright Opoku
Ameyaw, Edward Kwabena
Seidu, Abdul-Aziz
Shibre, Gebretsadik
author_sort Yaya, Sanni
collection PubMed
description BACKGROUND: Programmatic and research agendas surrounding neonatal mortality are important to help countries attain the child health related 2030 Sustainable Development Goal (SDG). In Burundi, the Neonatal Mortality Rate (NMR) is 25 per 1000 live births. However, high quality evidence on the over time evolution of inequality in NMR is lacking. This study aims to address the knowledge gap by systematically and comprehensively investigating inequalities in NMR in Burundi with the intent to help the country attain SDG 3.2 which aims to reduce neonatal mortality to at least as low as 12 per 1000 live births by 2030. METHODS: The Burundi Demographic and Health Survey (BDHS) data for the periods of 2010 and 2016 were used for the analyses. The analyses were carried out using the WHO’s HEAT version 3.1 software. Five equity stratifiers: economic status, education, residence, sex and subnational region were used as benchmark for measuring NMR inequality with time over 6 years. To understand inequalities from a broader perspective, absolute and relative inequality measures, namely Difference, Population Attributable Risk (PAR), Ratio, and Population Attributable Fraction (PAF) were calculated. Statistical significance was measured by computing corresponding 95% Confidence Intervals (CIs). RESULTS: NMR in Burundi in 2010 and 2016 were 36.7 and 25.0 deaths per 1000 live births, respectively. We recorded large wealth-driven (PAR = -3.99, 95% CI; − 5.11, − 2.87, PAF = -15.95, 95% CI; − 20.42, − 11.48), education related (PAF = -6.64, 95% CI; − 13.27, − 0.02), sex based (PAR = -1.74, 95% CI; − 2.27, − 1.21, PAF = -6.97, 95% CI; − 9.09, − 4.86), urban-rural (D = 15.44, 95% CI; 7.59, 23.29, PAF = -38.78, 95% CI; − 45.24, − 32.32) and regional (PAR = -12.60, 95% CI; − 14.30, − 10.90, R = 3.05, 95% CI; 1.30, 4.80) disparity in NMR in both survey years, except that urban-rural disparity was not detected in 2016. We found both absolute and relative inequalities and significant reduction in these inequalities over time - except at the regional level, where the disparity remained constant during the study period. CONCLUSION: Large survival advantage remains to neonates of women who are rich, educated, residents of urban areas and some regions. Females had higher chance of surviving their 28th birthday than male neonates. More extensive work is required to battle the NMR gap between different subgroups in the country.
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spelling pubmed-76638692020-11-13 Time trends, geographical, socio-economic, and gender disparities in neonatal mortality in Burundi: evidence from the demographic and health surveys, 2010–2016 Yaya, Sanni Zegeye, Betregiorgis Ahinkorah, Bright Opoku Ameyaw, Edward Kwabena Seidu, Abdul-Aziz Shibre, Gebretsadik Arch Public Health Research BACKGROUND: Programmatic and research agendas surrounding neonatal mortality are important to help countries attain the child health related 2030 Sustainable Development Goal (SDG). In Burundi, the Neonatal Mortality Rate (NMR) is 25 per 1000 live births. However, high quality evidence on the over time evolution of inequality in NMR is lacking. This study aims to address the knowledge gap by systematically and comprehensively investigating inequalities in NMR in Burundi with the intent to help the country attain SDG 3.2 which aims to reduce neonatal mortality to at least as low as 12 per 1000 live births by 2030. METHODS: The Burundi Demographic and Health Survey (BDHS) data for the periods of 2010 and 2016 were used for the analyses. The analyses were carried out using the WHO’s HEAT version 3.1 software. Five equity stratifiers: economic status, education, residence, sex and subnational region were used as benchmark for measuring NMR inequality with time over 6 years. To understand inequalities from a broader perspective, absolute and relative inequality measures, namely Difference, Population Attributable Risk (PAR), Ratio, and Population Attributable Fraction (PAF) were calculated. Statistical significance was measured by computing corresponding 95% Confidence Intervals (CIs). RESULTS: NMR in Burundi in 2010 and 2016 were 36.7 and 25.0 deaths per 1000 live births, respectively. We recorded large wealth-driven (PAR = -3.99, 95% CI; − 5.11, − 2.87, PAF = -15.95, 95% CI; − 20.42, − 11.48), education related (PAF = -6.64, 95% CI; − 13.27, − 0.02), sex based (PAR = -1.74, 95% CI; − 2.27, − 1.21, PAF = -6.97, 95% CI; − 9.09, − 4.86), urban-rural (D = 15.44, 95% CI; 7.59, 23.29, PAF = -38.78, 95% CI; − 45.24, − 32.32) and regional (PAR = -12.60, 95% CI; − 14.30, − 10.90, R = 3.05, 95% CI; 1.30, 4.80) disparity in NMR in both survey years, except that urban-rural disparity was not detected in 2016. We found both absolute and relative inequalities and significant reduction in these inequalities over time - except at the regional level, where the disparity remained constant during the study period. CONCLUSION: Large survival advantage remains to neonates of women who are rich, educated, residents of urban areas and some regions. Females had higher chance of surviving their 28th birthday than male neonates. More extensive work is required to battle the NMR gap between different subgroups in the country. BioMed Central 2020-11-12 /pmc/articles/PMC7663869/ /pubmed/33292519 http://dx.doi.org/10.1186/s13690-020-00501-3 Text en © The Author(s) 2020 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/. The Creative Commons Public Domain Dedication waiver (http://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
Yaya, Sanni
Zegeye, Betregiorgis
Ahinkorah, Bright Opoku
Ameyaw, Edward Kwabena
Seidu, Abdul-Aziz
Shibre, Gebretsadik
Time trends, geographical, socio-economic, and gender disparities in neonatal mortality in Burundi: evidence from the demographic and health surveys, 2010–2016
title Time trends, geographical, socio-economic, and gender disparities in neonatal mortality in Burundi: evidence from the demographic and health surveys, 2010–2016
title_full Time trends, geographical, socio-economic, and gender disparities in neonatal mortality in Burundi: evidence from the demographic and health surveys, 2010–2016
title_fullStr Time trends, geographical, socio-economic, and gender disparities in neonatal mortality in Burundi: evidence from the demographic and health surveys, 2010–2016
title_full_unstemmed Time trends, geographical, socio-economic, and gender disparities in neonatal mortality in Burundi: evidence from the demographic and health surveys, 2010–2016
title_short Time trends, geographical, socio-economic, and gender disparities in neonatal mortality in Burundi: evidence from the demographic and health surveys, 2010–2016
title_sort time trends, geographical, socio-economic, and gender disparities in neonatal mortality in burundi: evidence from the demographic and health surveys, 2010–2016
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7663869/
https://www.ncbi.nlm.nih.gov/pubmed/33292519
http://dx.doi.org/10.1186/s13690-020-00501-3
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