Clustering of childhood mortality in the Kintampo Health and Demographic Surveillance System in Ghana
Background: Childhood mortality in Ghana has generally declined in the last four decades. However, estimates tend to conceal substantial variability among regions and districts. The lack of population-based data in Ghana, as in other less developed countries, has hindered the development of effectiv...
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Veröffentlicht in: | Global health action 2010-08, Vol.3 (1), p.5258-14 |
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Sprache: | eng |
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Zusammenfassung: | Background: Childhood mortality in Ghana has generally declined in the last four decades. However, estimates tend to conceal substantial variability among regions and districts. The lack of population-based data in Ghana, as in other less developed countries, has hindered the development of effective programmes targeted specifically at clusters where mortality levels are significantly higher.
Objective: This paper seeks to test for the existence of statistically significant clusters of childhood mortality within the Kintampo Health and Demographic Surveillance System (KHDSS) between 2005 and 2007.
Design: In this study, mortality rates were generated using mortality data extracted from the health and demographic surveillance database of the KHDSS and exported into STATA. The spatial and spatio-temporal scan statistic by Kulldorff was used to identify significant clusters of childhood mortality within the KHDSS.
Results: A significant cluster of villages with high under-five mortality in the south-eastern part of the KHDSS in 2006 was identified. This is a remote location where poverty levels are relatively higher, health facilities are more sparse and these are compounded by poor transport services in case of emergencies.
Conclusion: This study highlights the potential of the surveillance platform to demonstrate the spatial dimensions of childhood mortality clustering. It is apparent, though, that further studies need to be carried out in order to explore the underlying risk factors for potential mortality clusters that could emerge later. |
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ISSN: | 1654-9716 1654-9880 1654-9880 |
DOI: | 10.3402/gha.v3i0.5258 |