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      Spatial and multilevel analysis of sanitation service access and related factors among households in Ethiopia: Using 2019 Ethiopian national dataset

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          Abstract

          Background

          Billions of people have faced the problem of accessing appropriate sanitation services. This study aimed to explore the spatial distribution of households’ access to sanitation services and identify associated factors in Ethiopia.

          Methods

          The 2019 Ethiopian Mini Demographic and Health Survey data was used with a total of 6261 weighted samples. A cross-sectional study design with a two-stage cluster sampling technique was used. Global Moran’s I statistic measure, Getis-Ord Gi*, and the ordinary Kriging Gaussian interpolation were used for spatial autocorrelation, hot spot analysis, and interpolation of unsampled areas, respectively. A purely spatial Bernoulli-based model was employed to determine the geographical locations of the most likely clusters. A multilevel logistic regression model was used, and predictors with a P value of less than 0.05 with a 95% CI were considered significant factors.

          Results

          Overall, 19.7% of households had access to improved sanitation services in Ethiopia. Poor sanitation service access was significantly clustered, with hotspots of poor access identified in the South Nations Nationality and People’s Region (SNNPR), Oromia, Amhara, and Benishangul Gumuz regions. A total of 275 significant clusters were identified. Households in the circled area were more vulnerable to poor sanitation service access. Rural households, on-premises water access, media exposure, and rich wealth status were statistically significant factors for access to sanitation services.

          Conclusions

          Access to sanitation services among households in Ethiopia is insufficient. The majority of the households had no access to sanitation services. Stakeholders are recommended to raise household members’ awareness of sanitation services, give priority to the hotspot areas, and encourage poor households to have access to toilet facilities. Household members recommended using the available sanitation service and keeping the sanitation service clean. Households are recommended to construct clean shared sanitation facilities.

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          Most cited references60

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          Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks in 188 countries, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013

          The Global Burden of Disease, Injuries, and Risk Factor study 2013 (GBD 2013) is the first of a series of annual updates of the GBD. Risk factor quantification, particularly of modifiable risk factors, can help to identify emerging threats to population health and opportunities for prevention. The GBD 2013 provides a timely opportunity to update the comparative risk assessment with new data for exposure, relative risks, and evidence on the appropriate counterfactual risk distribution.
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            A spatial scan statistic

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              A spatial scan statistic

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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Writing – original draftRole: Writing – review & editing
                Role: Writing – review & editing
                Role: Writing – review & editing
                Role: Writing – review & editing
                Role: Writing – review & editing
                Role: Writing – review & editing
                Role: Writing – review & editing
                Role: Methodology
                Role: Editor
                Journal
                PLOS Glob Public Health
                PLOS Glob Public Health
                plos
                PLOS Global Public Health
                Public Library of Science (San Francisco, CA USA )
                2767-3375
                4 April 2023
                2023
                : 3
                : 4
                : e0001752
                Affiliations
                [1 ] Department of Health Informatics, College of Health Science, Mettu University, Mettu, Ethiopia
                [2 ] Department of Health Informatics, Institute of Public Health, University of Gondar, Gondar, Ethiopia
                [3 ] Department of Health Informatics, College of Health Science, Debre Markos University, Debre Markos, Ethiopia
                [4 ] Department Of Nursing, College of Health Science, Mettu University, Mettu, Ethiopia
                University of Ghana School of Public Health, GHANA
                Author notes

                The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0002-9356-8126
                Article
                PGPH-D-22-01942
                10.1371/journal.pgph.0001752
                10072458
                37014843
                f6c5cd20-d105-489f-9a00-b7f67d4bb659
                © 2023 Demsash et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 3 December 2022
                : 2 March 2023
                Page count
                Figures: 6, Tables: 3, Pages: 17
                Funding
                The authors received no specific funding for this work.
                Categories
                Research Article
                Medicine and Health Sciences
                Health Care
                Environmental Health
                Sanitation
                Medicine and Health Sciences
                Public and Occupational Health
                Environmental Health
                Sanitation
                People and Places
                Geographical Locations
                Africa
                Ethiopia
                People and Places
                Population Groupings
                Ethnicities
                African People
                Amhara People
                Physical Sciences
                Mathematics
                Numerical Analysis
                Interpolation
                Earth Sciences
                Hydrology
                Surface Water
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Statistical Methods
                Regression Analysis
                Physical Sciences
                Mathematics
                Statistics
                Statistical Methods
                Regression Analysis
                Computer and Information Sciences
                Geoinformatics
                Spatial Autocorrelation
                Earth Sciences
                Geography
                Geoinformatics
                Spatial Autocorrelation
                Medicine and Health Sciences
                Public and Occupational Health
                Hygiene
                Custom metadata
                The dataset used for analysis is available on the Measure DHS program ( http://dhsprogram.com) website publicly. All the data generated and analyzed during the study are included in the form of maps, tables, and texts in this article.

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