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Under-five mortality: spatial—temporal clusters in Ifakara HDSS in South-eastern Tanzania
BACKGROUND: Childhood mortality remains an important subject, particularly in sub-Saharan Africa where levels are still unacceptably high. To achieve the set Millennium Development Goals 4, calls for comprehensive application of the proven cost-effective interventions. Understanding spatial clusteri...
Autores principales: | , , , , |
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Formato: | Texto |
Lenguaje: | English |
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CoAction Publishing
2010
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2935920/ https://www.ncbi.nlm.nih.gov/pubmed/20838629 http://dx.doi.org/10.3402/gha.v3i0.5254 |
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author | Lutambi, Angelina M. Alexander, Mathew Charles, Jensen Mahutanga, Chrisostom Nathan, Rose |
author_facet | Lutambi, Angelina M. Alexander, Mathew Charles, Jensen Mahutanga, Chrisostom Nathan, Rose |
author_sort | Lutambi, Angelina M. |
collection | PubMed |
description | BACKGROUND: Childhood mortality remains an important subject, particularly in sub-Saharan Africa where levels are still unacceptably high. To achieve the set Millennium Development Goals 4, calls for comprehensive application of the proven cost-effective interventions. Understanding spatial clustering of childhood mortality can provide a guide in targeting the interventions in a more strategic approach to the population where mortality is highest and the interventions are most likely to make an impact. METHODS: Annual child mortality rates were calculated for each village, using person-years observed as the denominator. Kulldorff's spatial scan statistic was used for the identification and testing of childhood mortality clusters. All under-five deaths that occurred within a 10-year period from 1997 to 2006 were included in the analysis. Villages were used as units of clusters; all 25 health and demographic surveillance sites (HDSS) villages in the Ifakara health and demographic surveillance area were included. RESULTS: Of the 10 years of analysis, statistically significant spatial clustering was identified in only 2 years (1998 and 2001). In 1998, the statistically significant cluster (p < 0.01) was composed of nine villages. A total of 106 childhood deaths were observed against an expected 77.3. The other statistically significant cluster (p < 0.05) identified in 2001 was composed of only one village. In this cluster, 36 childhood deaths were observed compared to 20.3 expected. Purely temporal analysis indicated that the year 2003 was a significant cluster (p < 0.05). Total deaths were 393 and expected were 335.8. Spatial–temporal analysis showed that nine villages were identified as statistically significant clusters (p < 0.05) for the period covering January 1997–December 1998. Total observed deaths in this cluster were 205 while 150.7 were expected. CONCLUSION: There is evidence of spatial clustering in childhood mortality within the Ifakara HDSS. Further investigations are needed to explore the source of clustering and identify strategies of reaching the cluster population with the existing effective interventions. However, that should happen alongside delivery of interventions to the broader population. |
format | Text |
id | pubmed-2935920 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | CoAction Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-29359202010-09-13 Under-five mortality: spatial—temporal clusters in Ifakara HDSS in South-eastern Tanzania Lutambi, Angelina M. Alexander, Mathew Charles, Jensen Mahutanga, Chrisostom Nathan, Rose Glob Health Action Supplement 1, 2010 BACKGROUND: Childhood mortality remains an important subject, particularly in sub-Saharan Africa where levels are still unacceptably high. To achieve the set Millennium Development Goals 4, calls for comprehensive application of the proven cost-effective interventions. Understanding spatial clustering of childhood mortality can provide a guide in targeting the interventions in a more strategic approach to the population where mortality is highest and the interventions are most likely to make an impact. METHODS: Annual child mortality rates were calculated for each village, using person-years observed as the denominator. Kulldorff's spatial scan statistic was used for the identification and testing of childhood mortality clusters. All under-five deaths that occurred within a 10-year period from 1997 to 2006 were included in the analysis. Villages were used as units of clusters; all 25 health and demographic surveillance sites (HDSS) villages in the Ifakara health and demographic surveillance area were included. RESULTS: Of the 10 years of analysis, statistically significant spatial clustering was identified in only 2 years (1998 and 2001). In 1998, the statistically significant cluster (p < 0.01) was composed of nine villages. A total of 106 childhood deaths were observed against an expected 77.3. The other statistically significant cluster (p < 0.05) identified in 2001 was composed of only one village. In this cluster, 36 childhood deaths were observed compared to 20.3 expected. Purely temporal analysis indicated that the year 2003 was a significant cluster (p < 0.05). Total deaths were 393 and expected were 335.8. Spatial–temporal analysis showed that nine villages were identified as statistically significant clusters (p < 0.05) for the period covering January 1997–December 1998. Total observed deaths in this cluster were 205 while 150.7 were expected. CONCLUSION: There is evidence of spatial clustering in childhood mortality within the Ifakara HDSS. Further investigations are needed to explore the source of clustering and identify strategies of reaching the cluster population with the existing effective interventions. However, that should happen alongside delivery of interventions to the broader population. CoAction Publishing 2010-08-30 /pmc/articles/PMC2935920/ /pubmed/20838629 http://dx.doi.org/10.3402/gha.v3i0.5254 Text en © 2010 Angelina M. Lutambi et al. http://creativecommons.org/licenses/by-nc/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution-Noncommercial 3.0 Unported License, permitting all non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Supplement 1, 2010 Lutambi, Angelina M. Alexander, Mathew Charles, Jensen Mahutanga, Chrisostom Nathan, Rose Under-five mortality: spatial—temporal clusters in Ifakara HDSS in South-eastern Tanzania |
title | Under-five mortality: spatial—temporal clusters in Ifakara HDSS in South-eastern Tanzania |
title_full | Under-five mortality: spatial—temporal clusters in Ifakara HDSS in South-eastern Tanzania |
title_fullStr | Under-five mortality: spatial—temporal clusters in Ifakara HDSS in South-eastern Tanzania |
title_full_unstemmed | Under-five mortality: spatial—temporal clusters in Ifakara HDSS in South-eastern Tanzania |
title_short | Under-five mortality: spatial—temporal clusters in Ifakara HDSS in South-eastern Tanzania |
title_sort | under-five mortality: spatial—temporal clusters in ifakara hdss in south-eastern tanzania |
topic | Supplement 1, 2010 |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2935920/ https://www.ncbi.nlm.nih.gov/pubmed/20838629 http://dx.doi.org/10.3402/gha.v3i0.5254 |
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