Le SIDA en Afrique subsaharienne (serveur d'exploration)

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Variation in neonatal mortality and its relation to country characteristics in sub-Saharan Africa: an ecological study

Identifieur interne : 002256 ( Pmc/Curation ); précédent : 002255; suivant : 002257

Variation in neonatal mortality and its relation to country characteristics in sub-Saharan Africa: an ecological study

Auteurs : Gbenga Ayodele Kayode [Pays-Bas, Nigeria] ; Diederick E. Grobbee [Pays-Bas] ; Mary Amoakoh-Coleman [Pays-Bas, Ghana] ; Evelyn Ansah [Ghana] ; Olalekan A. Uthman [Royaume-Uni] ; Kerstin Klipstein-Grobusch [Pays-Bas, Afrique du Sud]

Source :

RBID : PMC:5663256

Abstract

Background

A substantial reduction in neonatal mortality is the main priority to reduce under-five mortality. A clear understanding of the variation in neonatal mortality and the underlying causes is important for targeted intervention. We aimed to explore variation in neonatal mortality and identify underlying causes of variation in neonatal mortality in sub-Saharan Africa (SSA).

Methods

This ecological study used 2012 publicly available data from WHO, the US Agency for International Development and the World Bank. Variation in neonatal mortality across 49 SSA countries was examined using control chart and explanatory spatial data analysis. Associations between country-level characteristics and neonatal mortality were examined using linear regression analysis.

Results

The control chart showed that 28 (57%) SSA countries exhibited special-cause variation, 14 countries were below and 14 above the 99.8% control-limits. The remaining 21 (43%) SSA countries showed common-cause variation. No spatial clustering was observed for neonatal mortality (Global Moran’s I statistic −0.10; p=0.74). Linear regression analysis showed HIV/AIDS prevalence among the population of reproductive age to be positively associated with neonatal mortality (β=0.463; 95% CI 0.135 to 0.790; p<0.01). Declining socioeconomic deprivation (β=−0.234; 95% CI −0.424 to −0.044; p<0.05) and high quality of healthcare governance (β=−1.327, 95% CI −2.073 to −0.580; p<0.01) were inversely associated with neonatal mortality.

Conclusion

This study shows a wide variation in neonatal mortality in SSA. A substantial part of this variation can be explained by differences in the quality of healthcare governance, prevalence of HIV and socioeconomic deprivation. Future studies should validate our findings using more rigorous epidemiological study designs.


Url:
DOI: 10.1136/bmjgh-2016-000209
PubMed: 29104766
PubMed Central: 5663256

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PMC:5663256

Le document en format XML

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,
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,
<addr-line content-type="city">Johannesburg</addr-line>
,
<country>South Africa</country>
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<title>Background</title>
<p>A substantial reduction in neonatal mortality is the main priority to reduce under-five mortality. A clear understanding of the variation in neonatal mortality and the underlying causes is important for targeted intervention. We aimed to explore variation in neonatal mortality and identify underlying causes of variation in neonatal mortality in sub-Saharan Africa (SSA).</p>
</sec>
<sec>
<title>Methods</title>
<p>This ecological study used 2012 publicly available data from WHO, the US Agency for International Development and the World Bank. Variation in neonatal mortality across 49 SSA countries was examined using control chart and explanatory spatial data analysis. Associations between country-level characteristics and neonatal mortality were examined using linear regression analysis.</p>
</sec>
<sec>
<title>Results</title>
<p>The control chart showed that 28 (57%) SSA countries exhibited special-cause variation, 14 countries were below and 14 above the 99.8% control-limits. The remaining 21 (43%) SSA countries showed common-cause variation. No spatial clustering was observed for neonatal mortality (Global Moran’s I statistic −0.10; p=0.74). Linear regression analysis showed HIV/AIDS prevalence among the population of reproductive age to be positively associated with neonatal mortality (β=0.463; 95% CI 0.135 to 0.790; p<0.01). Declining socioeconomic deprivation (β=−0.234; 95% CI −0.424 to −0.044; p<0.05) and high quality of healthcare governance (β=−1.327, 95% CI −2.073 to −0.580; p<0.01) were inversely associated with neonatal mortality.</p>
</sec>
<sec>
<title>Conclusion</title>
<p>This study shows a wide variation in neonatal mortality in SSA. A substantial part of this variation can be explained by differences in the quality of healthcare governance, prevalence of HIV and socioeconomic deprivation. Future studies should validate our findings using more rigorous epidemiological study designs.</p>
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<pmc article-type="research-article">
<pmc-dir>properties open_access</pmc-dir>
<front>
<journal-meta>
<journal-id journal-id-type="nlm-ta">BMJ Glob Health</journal-id>
<journal-id journal-id-type="iso-abbrev">BMJ Glob Health</journal-id>
<journal-id journal-id-type="hwp">bmjgh</journal-id>
<journal-id journal-id-type="publisher-id">bmjgh</journal-id>
<journal-title-group>
<journal-title>BMJ Global Health</journal-title>
</journal-title-group>
<issn pub-type="epub">2059-7908</issn>
<publisher>
<publisher-name>BMJ Publishing Group</publisher-name>
<publisher-loc>BMA House, Tavistock Square, London, WC1H 9JR</publisher-loc>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="pmid">29104766</article-id>
<article-id pub-id-type="pmc">5663256</article-id>
<article-id pub-id-type="publisher-id">bmjgh-2016-000209</article-id>
<article-id pub-id-type="doi">10.1136/bmjgh-2016-000209</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Research</subject>
</subj-group>
<subj-group subj-group-type="hwp-journal-coll">
<subject>1506</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>Variation in neonatal mortality and its relation to country characteristics in sub-Saharan Africa: an ecological study</article-title>
</title-group>
<contrib-group>
<contrib id="author-51835957" contrib-type="author">
<name>
<surname>Kayode</surname>
<given-names>Gbenga Ayodele</given-names>
</name>
<xref ref-type="aff" rid="aff1">1</xref>
<xref ref-type="aff" rid="aff2">2</xref>
</contrib>
<contrib id="author-51836100" contrib-type="author">
<name>
<surname>Grobbee</surname>
<given-names>Diederick E</given-names>
</name>
<xref ref-type="aff" rid="aff1">1</xref>
<xref ref-type="aff" rid="aff3">3</xref>
</contrib>
<contrib id="author-51836164" contrib-type="author">
<name>
<surname>Amoakoh-Coleman</surname>
<given-names>Mary</given-names>
</name>
<xref ref-type="aff" rid="aff1">1</xref>
<xref ref-type="aff" rid="aff4">4</xref>
<xref ref-type="aff" rid="aff5">5</xref>
</contrib>
<contrib id="author-49709720" contrib-type="author">
<name>
<surname>Ansah</surname>
<given-names>Evelyn</given-names>
</name>
<xref ref-type="aff" rid="aff6">6</xref>
</contrib>
<contrib id="author-51836201" contrib-type="author">
<name>
<surname>Uthman</surname>
<given-names>Olalekan A</given-names>
</name>
<xref ref-type="aff" rid="aff7">7</xref>
<xref ref-type="aff" rid="aff8">8</xref>
</contrib>
<contrib id="author-50333943" contrib-type="author">
<name>
<surname>Klipstein-Grobusch</surname>
<given-names>Kerstin</given-names>
</name>
<xref ref-type="aff" rid="aff1">1</xref>
<xref ref-type="aff" rid="aff9">9</xref>
</contrib>
</contrib-group>
<aff id="aff1">
<label>1</label>
<institution>Julius Global Health, Julius Center for Health Sciences and Primary Care, University Medical Centre Utrecht</institution>
,
<addr-line content-type="city">Utrecht</addr-line>
,
<country>The Netherlands</country>
</aff>
<aff id="aff2">
<label>2</label>
<institution>International Research Centre of Excellence, Institute of Human Virology</institution>
,
<addr-line content-type="city">Abuja</addr-line>
,
<country>Nigeria</country>
</aff>
<aff id="aff3">
<label>3</label>
<institution>Global Geo and Health Data Center, Utrecht University</institution>
,
<addr-line content-type="city">Utrecht</addr-line>
,
<country>The Netherlands</country>
</aff>
<aff id="aff4">
<label>4</label>
<institution>Postdoctoral Unit, Noguchi Memorial Institute for Medical Research, University of Ghana</institution>
,
<addr-line content-type="city">Accra</addr-line>
,
<country>Ghana</country>
</aff>
<aff id="aff5">
<label>5</label>
<institution content-type="department">Department of Epidemiology and Disease Control</institution>
,
<institution>School of Public Health, University of Ghana</institution>
,
<addr-line content-type="city">Accra</addr-line>
,
<country>Ghana</country>
</aff>
<aff id="aff6">
<label>6</label>
<institution content-type="department">Research and Development Division</institution>
,
<institution>Ghana Health Service</institution>
,
<addr-line content-type="city">Accra</addr-line>
,
<country>Ghana</country>
</aff>
<aff id="aff7">
<label>7</label>
<institution content-type="department">Warwick-Centre for Applied Health Research and Delivery, Division of Health Sciences</institution>
,
<institution>Warwick Medical School, The University of Warwick</institution>
,
<addr-line content-type="city">Coventry</addr-line>
,
<country>UK</country>
</aff>
<aff id="aff8">
<label>8</label>
<institution>International Health Group, Liverpool School of Tropical Medicine</institution>
,
<addr-line content-type="city">Liverpool</addr-line>
,
<country>UK</country>
</aff>
<aff id="aff9">
<label>9</label>
<institution content-type="department">Division of Epidemiology and Biostatistics, Faculty of Health Science</institution>
,
<institution>School of Public Health, the University of Witwatersrand</institution>
,
<addr-line content-type="city">Johannesburg</addr-line>
,
<country>South Africa</country>
</aff>
<author-notes>
<corresp>
<label>Correspondence to</label>
Dr Gbenga Ayodele Kayode;
<email>gakayode@yahoo.co.uk</email>
</corresp>
</author-notes>
<pub-date pub-type="collection">
<year>2017</year>
</pub-date>
<pub-date pub-type="epub">
<day>25</day>
<month>10</month>
<year>2017</year>
</pub-date>
<volume>2</volume>
<issue>4</issue>
<elocation-id>e000209</elocation-id>
<history>
<date date-type="received">
<day>08</day>
<month>10</month>
<year>2016</year>
</date>
<date date-type="rev-recd">
<day>27</day>
<month>8</month>
<year>2017</year>
</date>
<date date-type="accepted">
<day>02</day>
<month>9</month>
<year>2017</year>
</date>
</history>
<permissions>
<copyright-statement>© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.</copyright-statement>
<copyright-year>2017</copyright-year>
<license license-type="open-access">
<license-p>This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See:
<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0/">http://creativecommons.org/licenses/by/4.0/</ext-link>
</license-p>
</license>
</permissions>
<self-uri xlink:title="pdf" xlink:href="bmjgh-2016-000209.pdf"></self-uri>
<abstract>
<sec>
<title>Background</title>
<p>A substantial reduction in neonatal mortality is the main priority to reduce under-five mortality. A clear understanding of the variation in neonatal mortality and the underlying causes is important for targeted intervention. We aimed to explore variation in neonatal mortality and identify underlying causes of variation in neonatal mortality in sub-Saharan Africa (SSA).</p>
</sec>
<sec>
<title>Methods</title>
<p>This ecological study used 2012 publicly available data from WHO, the US Agency for International Development and the World Bank. Variation in neonatal mortality across 49 SSA countries was examined using control chart and explanatory spatial data analysis. Associations between country-level characteristics and neonatal mortality were examined using linear regression analysis.</p>
</sec>
<sec>
<title>Results</title>
<p>The control chart showed that 28 (57%) SSA countries exhibited special-cause variation, 14 countries were below and 14 above the 99.8% control-limits. The remaining 21 (43%) SSA countries showed common-cause variation. No spatial clustering was observed for neonatal mortality (Global Moran’s I statistic −0.10; p=0.74). Linear regression analysis showed HIV/AIDS prevalence among the population of reproductive age to be positively associated with neonatal mortality (β=0.463; 95% CI 0.135 to 0.790; p<0.01). Declining socioeconomic deprivation (β=−0.234; 95% CI −0.424 to −0.044; p<0.05) and high quality of healthcare governance (β=−1.327, 95% CI −2.073 to −0.580; p<0.01) were inversely associated with neonatal mortality.</p>
</sec>
<sec>
<title>Conclusion</title>
<p>This study shows a wide variation in neonatal mortality in SSA. A substantial part of this variation can be explained by differences in the quality of healthcare governance, prevalence of HIV and socioeconomic deprivation. Future studies should validate our findings using more rigorous epidemiological study designs.</p>
</sec>
</abstract>
<kwd-group>
<kwd>child health</kwd>
<kwd>health systems</kwd>
</kwd-group>
<funding-group>
<award-group id="funding-1">
<funding-source>
<institution-wrap>
<institution>Netherlands Organization for Scientific Research / WOTRO Science for Development</institution>
</institution-wrap>
</funding-source>
</award-group>
</funding-group>
<custom-meta-group>
<custom-meta>
<meta-name>special-feature</meta-name>
<meta-value>unlocked</meta-value>
</custom-meta>
</custom-meta-group>
</article-meta>
</front>
</pmc>
</record>

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