Publications Summary

Document Type
Spatial Analysis Reports
Publication Topic(s)
Adult Health Issues, Nutrition
Nigeria, Zambia
Recommended Citation
Donohue, Rose E., Rachael Church, Shireen Assaf, and Benjamin K. Mayala. 2023. Community Improved Sanitation Coverage and Childhood Stunting. DHS Spatial Analysis Reports No. 23. Rockville, Maryland, USA: ICF
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Publication Date
September 2023
Publication ID

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Lack of access to improved sanitation facilities remains a global problem, with an estimated 1.1 billion individuals estimated to have no access to an improved sanitation facility in 2020. Poor sanitation has been linked to a variety of deleterious health outcomes that include malnutrition, diarrheal diseases, acute respiratory infections, and many neglected tropical diseases such as schistosomiasis, soil-transmitted helminthiases, and trachoma. Although individual access to improved sanitation in households can prevent exposure to fecal contamination in an individual’s household, there is growing awareness that the shared community environment can be contaminated when other households lack access to improved sanitation facilities. Thus, there is growing interest in exploring and evaluating the impact of community-level sanitation coverage on individual health outcomes. In this report, we present maps to visualize community improved sanitation coverage and use geospatial modeling to identify areas at risk. We evaluate the association between childhood stunting and household-level and community-level improved sanitation by using multilevel logistic regression on 2018 DHS surveys from Nigeria and Zambia. Our findings suggest that community improved sanitation coverage should be considered when evaluating sanitation-related health outcomes. We find that although household sanitation access was not associated with childhood stunting in either of the adjusted regression models, community improved sanitation coverage was significantly and inversely associated with childhood stunting in Nigeria. However, we note the limitations of estimating community sanitation coverage with DHS cluster-level data. All households in a community do not have sanitation data and the lack of household GPS coordinates precludes any analyses that consider the proximity to other households in a community. We present different visualizations and tools that use DHS data which may be useful to researchers and policymakers. We create maps that depict the variation in cluster- level estimates in different regions and offer suggestions for using these maps. We offer guidance on how the modeled surfaces in this report and those available in the Spatial Data Repository can be used by policymakers to aid in decisionmaking and by researchers to provide estimates of community sanitation measures in locations that are not sampled by a DHS survey.


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