Putting child mortality on a map: towards an understanding of inequity in health.
OBJECTIVE
To map and analyse geographical (spatial) variations of child mortality trends in mainland Tanzania.


METHODS
We used a geographic information system to integrate data on child mortality and associated risk factors. We then applied spatial statistics to quantify the spatial component of child mortality trends, and employed multivariate analysis to break mortality down into a spatial and a local component.


RESULTS
The results support our hypothesis that child mortality trends have a spatial component that can be attributed to broad-scale environmental and social-economic factors. However, the multivariate analysis showed that the spatial component only explained one-third of the variation in child mortality trends. The results thus point towards the presence of local (non-spatial) causative factors, including variations in the access to and quality of child health care.


CONCLUSIONS
The method we used is a cost-effective way to systematically assess geographical variations in health outcomes. It can thus provide researchers and practitioners with a good first-line tool in understanding local contributions to differences in mortality and other indicators, and give authorities at all levels a better foundation for addressing health inequities.
Tottrup
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C
Geographic Resource Analysis and Science Ltd, c/o University of Copenhagen, Copenhagen, Denmark. ct@gras.ku.dk
Tersbol
B P
BP
Lindeboom
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W
Meyrowitsch
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D
D046688:Child Mortality / Q000639:trends*; D002675:Child, Preschool; D003906:Developing Countries; D004777:Environment; D005260:Female; D040362:Geographic Information Systems; D054624:Health Status Disparities; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D008297:Male; D012307:Risk Factors; D012959:Socioeconomic Factors; D013636:Tanzania / Q000453:epidemiology