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Type Journal Article - International Journal of Epidemiology
Title Predicting the distribution of under-five deaths by cause in countries without adequate vital registration systems
Author(s)
Volume 32
Issue 6
Publication (Day/Month/Year) 2003
Page numbers 1041
URL http://ije.oxfordjournals.org/content/32/6/1041.full
Abstract
Background The absence of complete vital registration and atypical nature of the locations where epidemiological studies of cause of death in children are conducted make it difficult to know the true distribution of child deaths by cause in developing countries. A credible method is needed for generating valid estimates of this distribution for countries without adequate vital registration systems.

Methods A systematic review was undertaken of all studies published since 1980 reporting under-5 mortality by cause. Causes of death were standardized across studies, and information was collected on the characteristics of each study and its population. A meta-regression model was used to relate these characteristics to the various proportional mortality outcomes, and predict the distribution in national populations of known characteristics. In all, 46 studies met the inclusion criteria.

Results Proportional mortality outcomes were significantly associated with region, mortality level, and exposure to malaria; coverage of measles vaccination, safe delivery care, and safe water; study year, age of children under surveillance, and method used to establish definitive cause of death. In sub-Saharan Africa and in South Asia, the predicted distribution of deaths by cause was: pneumonia (23% and 23%), malaria (24% and <1%), diarrhoea (22% and 23%), ‘neonatal and other’ (29% and 52%), measles (2% and 1%).

Conclusions For countries without adequate vital registration, it is possible to estimate the proportional distribution of child deaths by cause by exploiting systematic associations between this distribution and the characteristics of the populations in which it has been studied, controlling for design features of the studies themselves.

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