Neonatal mortality clustering in the central districts of Ghana.
<h4>Introduction</h4>Identifying high risk geographical clusters for neonatal mortality is important for guiding policy and targeted interventions. However, limited studies have been conducted in Ghana to identify such clusters.<h4>Objective</h4>This study aimed to identify h...
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doaj-e6b15f9f1fa14fe4956407f076262da62021-07-10T04:30:22ZengPublic Library of Science (PLoS)PLoS ONE1932-62032021-01-01166e025357310.1371/journal.pone.0253573Neonatal mortality clustering in the central districts of Ghana.George AdjeiEugene K M DartehDavid Teye Doku<h4>Introduction</h4>Identifying high risk geographical clusters for neonatal mortality is important for guiding policy and targeted interventions. However, limited studies have been conducted in Ghana to identify such clusters.<h4>Objective</h4>This study aimed to identify high-risk clusters for all-cause and cause-specific neonatal mortality in the Kintampo Districts.<h4>Materials and methods</h4>Secondary data, comprising of 30,132 singleton neonates between January 2005 and December 2014, from the Kintampo Health and Demographic Surveillance System (KHDSS) database were used. Verbal autopsies were used to determine probable causes of neonatal deaths. Purely spatial analysis was ran to scan for high-risk clusters using Poisson and Bernoulli models for all-cause and cause-specific neonatal mortality in the Kintampo Districts respectively with village as the unit of analysis.<h4>Results</h4>The study revealed significantly high risk of village-clusters for neonatal deaths due to asphyxia (RR = 1.98, p = 0.012) and prematurity (RR = 5.47, p = 0.025) in the southern part of Kintampo Districts. Clusters (emerging clusters) which have the potential to be significant in future, for all-cause neonatal mortality was also identified in the south-western part of the Kintampo Districts.<h4>Conclusions</h4>Study findings showed cause-specific neonatal mortality clustering in the southern part of the Kintampo Districts. Emerging cluster was also identified for all-cause neonatal mortality. More attention is needed on prematurity and asphyxia in the identified cause-specific neonatal mortality clusters. The emerging cluster for all-cause neonatal mortality also needs more attention to forestall any formation of significant mortality cluster in the future. Further research is also required to understand the high concentration of prematurity and asphyxiated deaths in the identified clusters.https://doi.org/10.1371/journal.pone.0253573 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
George Adjei Eugene K M Darteh David Teye Doku |
spellingShingle |
George Adjei Eugene K M Darteh David Teye Doku Neonatal mortality clustering in the central districts of Ghana. PLoS ONE |
author_facet |
George Adjei Eugene K M Darteh David Teye Doku |
author_sort |
George Adjei |
title |
Neonatal mortality clustering in the central districts of Ghana. |
title_short |
Neonatal mortality clustering in the central districts of Ghana. |
title_full |
Neonatal mortality clustering in the central districts of Ghana. |
title_fullStr |
Neonatal mortality clustering in the central districts of Ghana. |
title_full_unstemmed |
Neonatal mortality clustering in the central districts of Ghana. |
title_sort |
neonatal mortality clustering in the central districts of ghana. |
publisher |
Public Library of Science (PLoS) |
series |
PLoS ONE |
issn |
1932-6203 |
publishDate |
2021-01-01 |
description |
<h4>Introduction</h4>Identifying high risk geographical clusters for neonatal mortality is important for guiding policy and targeted interventions. However, limited studies have been conducted in Ghana to identify such clusters.<h4>Objective</h4>This study aimed to identify high-risk clusters for all-cause and cause-specific neonatal mortality in the Kintampo Districts.<h4>Materials and methods</h4>Secondary data, comprising of 30,132 singleton neonates between January 2005 and December 2014, from the Kintampo Health and Demographic Surveillance System (KHDSS) database were used. Verbal autopsies were used to determine probable causes of neonatal deaths. Purely spatial analysis was ran to scan for high-risk clusters using Poisson and Bernoulli models for all-cause and cause-specific neonatal mortality in the Kintampo Districts respectively with village as the unit of analysis.<h4>Results</h4>The study revealed significantly high risk of village-clusters for neonatal deaths due to asphyxia (RR = 1.98, p = 0.012) and prematurity (RR = 5.47, p = 0.025) in the southern part of Kintampo Districts. Clusters (emerging clusters) which have the potential to be significant in future, for all-cause neonatal mortality was also identified in the south-western part of the Kintampo Districts.<h4>Conclusions</h4>Study findings showed cause-specific neonatal mortality clustering in the southern part of the Kintampo Districts. Emerging cluster was also identified for all-cause neonatal mortality. More attention is needed on prematurity and asphyxia in the identified cause-specific neonatal mortality clusters. The emerging cluster for all-cause neonatal mortality also needs more attention to forestall any formation of significant mortality cluster in the future. Further research is also required to understand the high concentration of prematurity and asphyxiated deaths in the identified clusters. |
url |
https://doi.org/10.1371/journal.pone.0253573 |
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