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Citation Information

Type Journal Article - Geotechnologies and the Environment
Title Regional environmental patterns of diarrheal disease in Bangladesh: a spatial analytical and multilevel approach
Author(s)
Volume 4
Issue 2
Publication (Day/Month/Year) 2011
Page numbers 191-204
URL http://dx.doi.org/10.1007/978-94-007-0329-2_9
Abstract
This study investigates diarrheal disease distributions in Bangladesh using nationally representative household-level survey data integrated with land type maps that characterize flood inundation levels. The spatial distribution of childhood diarrhea is mapped throughout the country and diarrhea rates are stratified by individual, household, and regional-level variables. This study describes national-level trends by integrating spatially-referenced household characteristics and regional-level information on water and sanitation. The world saw dramatic improvements in water availability during the 1980s, designated International Water Supply and Sanitation Decade by the UN. Nevertheless, reductions in diarrheal morbidity in much of the developing world have been modest, possibly because of a lack of sufficient parallel improvements in sanitation and hygiene (Levine et al., Lancet 2(7976):86–89, 1976; Esrey et al., Bull World Health Organ 63:757–772, 1985; Hoque et al., Bull World Health Organ 74:431–437, 1996). In a recent meta-analysis of 64 studies, Fewtrell and Colford (Health, Nutrition, Population Discussion Paper, World Bank, Washington DC, http://www1.worldbank.org/hnp/Pubs_Discussion/Fewtrell&ColfordJuly2004;.pdf, 2004) found that water supply, water quality, hygiene, and sanitation programs all reduce diarrheal disease mortality and morbidity. However, multiple interventions did not reduce diarrheal disease any more than approaches that involved only one intervention. This suggests that a better fundamental understanding of the relationship between water, sanitation, household characteristics and diarrheal disease is needed to optimize future interventions. This study begins to investigate these relationships using data at different collected at multiple scales.

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