Magnitude and determinants of improved household latrine utilization in Ethiopia: Multilevel analysis of the mini Ethiopian Demographic Health Survey (EDHS) 2019. 2023

Aragaw Tesfaw, and Mulu Tiruneh, and Melkalem Mamuye, and Zebader Walle, and Wondossen Teshager, and Fentaw Teshome, and Alebachew Taye, and Wondimnew Dessalegn, and Gashaw Walle, and Asaye Alemneh Gebeyehu
Department of Public Health, College of Health Sciences, Debre Tabor University, Debre Tabor, Ethiopia.

Lack of sanitation is a major global problem mainly for the poor and disadvantaged. According to the 2016 Ethiopian Demographic and Health Surveys (EDHS) report, one out of every three households lack a toilet in Ethiopia and about 56% of rural households use unimproved toilet facilities. We aimed to determine the magnitude of improved household latrine utilization and its determinants in Ethiopia using the mini-Ethiopian Demographic Health Survey (EDHS) 2019 data set. A secondary data analysis was conducted based on the mini 2019 EDHS data set. A total weighted sample of 8663 households were involved in analysis. After selecting the relevant variables for the outcome variable, we have fitted four different models. The null (empty) model with no independent variables and the second model contained the effects of the individual-level factors on the outcome variable. The third model included the influence of the community-level factors on the response variable, and the final multilevel multivariable logistic regression model examined the effects of individual-level and community-level variables on the outcome variable. The measure of variation was quantified using Intra-Class Correlation (ICC), Median Odds Ratio, and Proportional Change in Variance (PCV). The Adjusted Odds Ratio (AOR) with a 95% Confidence Interval (CI) was used to show the strength of association and statistical significance was declared at p value < 0.05. The magnitude of improved latrine utilization in Ethiopia was 19.5% with 95% CI (18.6%, 20.3%). The factors: educational status (AOR = 1.67; 95% CI: (1.10, 2.55), highest wealth index (AOR = 3.73; 95% CI: (2.73, 5.12), urban residence (AOR = 3.09; 95% CI: (1.68, 5.67), living in Addis Ababa (AOR = 4.08; 95% CI: (1.03, 16.2) and Dire Dawa (AOR = 8.22; 95% CI: (2.46, 27.42) and Somali regions (AOR = 3.11; 95% CI: (1.15, 8.42) were significantly associated to improved latrine utilization in Ethiopia. The magnitude of improved latrine utilization was quite low in Ethiopia. Higher wealth index, living in more urbanized areas, and the household head's educational status were all significant predictors of improved latrine utilization. The finding implies a need to increase household's access to latrine facilities and improve latrine utilization, particularly for rural households in the country.

UI MeSH Term Description Entries
D003430 Cross-Sectional Studies Studies in which the presence or absence of disease or other health-related variables are determined in each member of the study population or in a representative sample at one particular time. This contrasts with LONGITUDINAL STUDIES which are followed over a period of time. Disease Frequency Surveys,Prevalence Studies,Analysis, Cross-Sectional,Cross Sectional Analysis,Cross-Sectional Survey,Surveys, Disease Frequency,Analyses, Cross Sectional,Analyses, Cross-Sectional,Analysis, Cross Sectional,Cross Sectional Analyses,Cross Sectional Studies,Cross Sectional Survey,Cross-Sectional Analyses,Cross-Sectional Analysis,Cross-Sectional Study,Cross-Sectional Surveys,Disease Frequency Survey,Prevalence Study,Studies, Cross-Sectional,Studies, Prevalence,Study, Cross-Sectional,Study, Prevalence,Survey, Cross-Sectional,Survey, Disease Frequency,Surveys, Cross-Sectional
D005002 Ethiopia An independent state in eastern Africa. Ethiopia is located in the Horn of Africa and is bordered on the north and northeast by Eritrea, on the east by Djibouti and Somalia, on the south by Kenya, and on the west and southwest by Sudan. Its capital is Addis Ababa. Federal Democratic Republic of Ethiopia
D005191 Family Characteristics Size and composition of the family. Family Size,Couples,Family Demography,Family Life Surveys,Family Size, Average,Family Size, Completed,Family Size, Desired,Family Size, Expected,Family Size, Ideal,Family and Household,Generations,Head of Household,Households,One-Person Household,Average Family Size,Average Family Sizes,Completed Family Size,Completed Family Sizes,Demography, Family,Desired Family Size,Desired Family Sizes,Expected Family Size,Expected Family Sizes,Family Characteristic,Family Demographies,Family Life Survey,Family Sizes,Family Sizes, Ideal,Household,Household Head,Household Heads,Household and Family,Household, One-Person,Ideal Family Size,Ideal Family Sizes,One Person Household,One-Person Households,Survey, Family Life
D006306 Health Surveys A systematic collection of factual data pertaining to health and disease in a human population within a given geographic area. Abortion Surveys,Abortion Survey,Health Survey,Survey, Abortion,Survey, Health,Surveys, Abortion,Surveys, Health
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D014038 Toilet Facilities Facilities containing equipment for disposal of human excrement, often with an accompanying hand-washing station. Latrines,Bathrooms,Lavatories,Restrooms,Bathroom,Facilities, Toilet,Facility, Toilet,Latrine,Lavatory,Restroom,Toilet Facility
D055361 Multilevel Analysis The statistical manipulation of hierarchically and non-hierarchically nested data. It includes clustered data, such as a sample of subjects within a group of schools. Prevalent in the social, behavioral sciences, and biomedical sciences, both linear and nonlinear regression models are applied. Analyses, Multilevel,Analysis, Multilevel,Multilevel Analyses

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