Contents lists available at ScienceDirect Clinical Epidemiology and Global Health journal homepage: www.elsevier.com/locate/cegh Original article Determinants of stunting among under-five years children in Ethiopia from the 2016 Ethiopia demographic and Health Survey: Application of ordinal logistic regression model using complex sampling designs Haile Mekonnen Fenta a,∗ , Demeke Lakew Workie a , Dereje Tesfaye Zike a , Belaynew Wassie Taye b , Prafulla Kumar Swain c a Department of Statistics, College of Science, Bahir Dar University, Bahir Dar, Ethiopia b Department of Epidemiology and Public Health, College of Medicine, Bahir Dar University, Bahir Dar, Ethiopia c Department of Statistics, Utkal University, Bhubaneswar, 751004, India ARTICLEINFO Keywords: Ordinal logistic regression Complex sampling design Determinant Child stunting Ethiopia ABSTRACT Background: Stunting is a result of chronic under nutrition and a major public health issue in Ethiopia. This study aimed to calculate the prevalence of stunting, and associated factors among children younger than five years. Methods: A total of 9588 children in Ethiopia were included. Proportional Odds Model was used to identify determinants of stunting. The score test and plots were used to see the proportional odds model assumptions. Results: The prevalence of stunting was 38% (21% moderately, 17% severely). Children with illiterate mothers were 2 times more likely to be moderately and severely stunted compared with their counterparts with sec- ondary education. The odds of being stunted for children whose age group 24–35 months respectively as compared to children 0–5 months of age were 4.71 times higher. Being female children were 9.66 times more likely to be in normal nutrition status as compared to male. Children of families in the highest wealth quintile were 7.92 times more likely to have normal stature compared with children from poorest ones. Conclusions: Child age, child sex, birth interval, mother's educational status, wealth index, were the important determinants of stunting. Addressing these factors will help to prevent future injury of physical and mental development in children and will assist in alleviating malnutrition and refining their quality of life. Moreover, in a DHS data set, complex sampling design should be incorporated in order to make a valid statistical inference. 1. Background Under nutrition remains one of the most common causes of mor- bidity and mortality among children under-five years of age in devel- oping countries. 1 Research findings indicate that poor nutrition during childhood is one of the most important conditions that hinder physical and mental development of children which ultimately propagates the vicious cycle of intergenerational malnutrition. Consequently, the ef- fects of under-five malnutrition are permanent and cross into adult- hood. 2 It is estimated that about 178 million- 195 million children that are malnourished across the globe, 3,4 and at any given moment, 20 million are suffering from the most severe form of malnutrition. Malnutrition contributes to between 3.5 and 5 million annual deaths among under-five children. An estimated 230 million under-five chil- dren are believed to be chronically malnourished in developing coun- tries and malnutrition among under-five children is one of the most important public health problems in developing countries especially Sub-Saharan Africa. 5 Stunting (low height-for-age) is chronic restriction of a child's po- tential growth. Specifically, it refers to children from the ages of 0–59 months who are below 2 standard deviations from the median height- for-age determined by the World Health Organization (WHO) Child Growth Standards. 6,7 Along with wasting (low weight-for-height) and underweight (low weight-for-age), stunting is an indicator of under nutrition. 8 As shown in the conceptual model from UNICEF, causal factors for stunting in children under-five years old vary with age and are https://doi.org/10.1016/j.cegh.2019.09.011 Received 5 April 2019; Received in revised form 17 August 2019; Accepted 20 September 2019 ∗ Corresponding author. E-mail addresses: hailemekonnen@gmail.com (H.M. Fenta), demay_gu06@yahoo.com (D.L. Workie), derejetesfaye11@gmail.com (D.T. Zike), bewassie@yahoo.com (B.W. Taye), prafulla86@gmail.com (P.K. Swain). Clinical Epidemiology and Global Health 8 (2020) 404–413 Available online 27 September 2019 2213-3984/ © 2019 Published by Elsevier, a division of RELX India, Pvt. Ltd on behalf of INDIACLEN. T