Assessment Of The Prevalence And Factors Associated With Malnutrition Among Ages 6-59 Months Of Children In Burayu Town Oromia Ethiopia 2017

Introduction: - Malnutrition is a major public health problem among under five children. More thanrnone-third of deaths during the first five years of life are attributed to under nutrition, which arernmostly preventable through economic development and public health measures.rnWorld Health Organization estimated that there are 178 million malnourished children across thernglobe, and at any given moment, 20 million of these are suffering from the most severe form ofrnmalnutrition, and it is indicated that underweight is the single largest risk factor contributing to thernglobal burden of disease in the developing world. An estimated 80% of world’s stunted childrenrnlived in just fourteen countries, Ethiopia is found in the seventh rank. This study tried to show thernprevalence of malnutrition in Burayu Town, that fills the knowledge gap, because there is no priorrnresearch on the zone. Second, the research tries to see the associated factors that are contributing forrnthe prevalence of malnutrition in the zone, which can help to develop a better intervention strategy.rnTo alleviate this problem, it is necessary to determine the nature, magnitude, and determinants ofrnunder nutrition.rnObjective: - To determine the prevalence of malnutrition and associated factors among ages 6-59rnmonths of children in Burayu Town, Ethiopia 2017.rnMethod and Analysis: - A community based cross-sectional quantitative study was conducted fromrnFebruary to April 2017. A systematic random sampling technique was used to select sample of 420rnunder five children aged 6-59 months old. Data was collected using semi structured questionnaire,rnand anthropometric measurement. Data was entered into Epidata 7 and exported to SPSS version 21rnfor analysis. The data was coded, edited, and cleaned, before statistical analysis. WHO Antroplusrnsoftware was used to compute (WAZ) weight for age z-score ,(HAZ) height for age z-score andrn(WHZ) weight for height z-score. Descriptive statistics such as frequency, percentages, crossrntabulation and graph was used to describe the prevalence and associated factors of under nutrition.rnBivariate and multivariable logistic regressions were used to explore associations. Statisticallyrnsignificant associations were declared association at p-value of

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