Households with unimproved water sources in Ethiopia: spatial variation and point-of-use treatment based on 2016 Demographic and Health Survey

Abstract

Background Improved water sources are not equally available in all geographical regions. Populations dependent on unsafe water sources are recommended to treat their water at point-of-use using adequate methods to reduce associated health problems. In Ethiopia, the spatial distribution of households using unimproved water sources have been incomplete or ignored in most of the studies. Moreover, evidence on the point-of-use water treatment practice of households dependent on such water sources is scarce. Therefore, the current study is intended to analyze the spatial distribution of unimproved water sources by wealth quintiles at country level and point-of-use treatment (POU) practices using nationally representative data. Method The data of 2016 Ethiopian Demographic and Health Survey (EDHS) conducted on 16650 households from 643 clusters were used for the analysis. For spatial analysis, the raw and spatially smoothed coverage data was joined to the geographic coordinates based on EDHS cluster identification code. Global spatial autocorrelation was performed to analyze whether the pattern of unimproved water coverage is clustered, dispersed, or random across the study areas. Once a positive global autocorrelation was confirmed, a local spatial autocorrelation analysis was applied to detect local clusters. The POU water treatment is analyzed based on reported use of either boiling, chlorine (bleach), filtration, or solar disinfection (SODIS). Results There were 5005 households using unimproved water sources for drinking purposes. Spatial variation of unimproved water coverage was observed with high coverage observed at Amhara, Afar, Southern Nations Nationalities and People and Somalia regions. Disparity in unimproved water coverage between wealth quintiles was also observed. The reported point-of-use water treatment practice among these households is only 6.24%. The odds of POU water treatment among household heads with higher education status is 2.5 times higher (95% CI = 1.43-4.36) compared to those who did not attend education. Conclusion An apparent clustering trend with high unimproved water coverage was observed between regions and among wealth quintiles hence indicates priority areas for future resource allocation and the need for regional and national policies to address the issue. Promoting households to treat water prior to drinking is essential to reduce health problems.

Household water treatment practice and associated factors in Ethiopia: A systematic review and meta-analysis

“…The majority of the included studies were conducted using interviewers to administer questionnaires. Seven studies from the Amhara region [ 19 , 20 , 23 , 33 , 34 , 36 , 38 ]; four studies from the SNNP region [ 28 – 30 , 32 ]; one study from the Oromia region [ 21 ]; one study from the Benishangul-Gumuz region [ 37 ]; one study from both the Oromia and Harari regions [ 35 ]; and two studies from the all-region [ 22 , 31 ] were used to obtain the pooled HWT practices and associated factors ( Table 1 ) .…”

Spatiotemporal Analysis of the Proportion of Unimproved Drinking Water Sources in Rural Ethiopia: Evidence from Ethiopian Socioeconomic Surveys (2011 to 2019)

“…A study [ 22 ] revealed an apparent clustering trend of unimproved water coverage between regions. Similarly, in the current study, a spatial clustering was found to be significant in some areas.…”

“…In this regard, identifying highly vulnerable areas is essential in reducing the lack of improved water sources. Results of a few studies conducted in different settings of Ethiopia revealed that an unimproved source of drinking water was significantly clustered spatially [ 4 , 21 , 22 ]. However, the temporal pattern of unimproved drinking water sources was not incorporated in these studies and they used only one cross-sectional data; it may be unable to analyze the data in time and space domains [ 23 ].…”

Household water consumption on the outskirts of Mexico City

“…The visual exploration of the distribution of the five groups suggests a clear segmentation of the city into areas with three different levels of consumption: areas with low, medium, and high levels of water consumption. [45][46][47][48][49]…”

“…These factors configure a valuable tool for decision-makers and an important basis for formulating efficient water policies. 36,45,46 In this context, this study aims to investigate whether inequality in water consumption among households is characterized by a spatial distribution pattern. It is of particular interest to identify the georeferenced variable that significantly explains the formation of the spatial pattern, as well as working with updated information so that the results make it possible to identify spatial information from which meet pressing water needs for vulnerable groups.…”