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Assessment of Knowledge and Practice of House Hold Water Treatment and Associated Factors in Rural Kebeles of Degadamot Woreda, North-West Ethiopia, 2020

Dejene Tsegaye*, Yizengaw Aniley, Belete Negese, Zemen Mengesha

Background: Household water treatment and safe storage interventions are proven to improve water quality and reduce diarrheal disease incidence in developing countries. Almost 90% of the rural population of Ethiopia did not practice any alternative water treatment methods which would pose them to high public health risks. The aim of this study was therefore to identify factors of house hold water treatment practice and knowledge in rural kebeles of Degadamot woreda, North West Ethiopia, 2020.

Methods: A Community-based cross-sectional study design was conducted in Degadamot woreda, North West Ethiopia, 2020. A Multistage sampling technique was carried out to select 845 sample households. Data were entered into the Epi-Data version 4.1 and analyzed using SPSS Version 20. Binary Logistic regression analysis was conducted to identify factors of house hold water treatment practice and knowledge.

Results: In this study, 14% of participants were practicing household water treatment and 28.2% had knowledge on household water treatment practice. Educational status, income earning >600 ETB per month, number of under five children in the household, ways to fetch water and knowledge on HWT were factors significantly associated with household water treatment practice. And educational status, marital status, source of water for drinking, number of containers to store water two, three and above: and place of handling utensils were factors which had significant association with knowledge of house hold water treatment practice.

Conclusion: Factors that were significantly associated with household water treatment practice were educational status, income, number of under-five children, ways to fetch drinking water and good knowledge about household water treatment.

Isenção de responsabilidade: Este resumo foi traduzido usando ferramentas de inteligência artificial e ainda não foi revisado ou verificado