Multilevel Analysis of Factors Associated with Stunting Among Under Five Children in Ethiopia

Abstract

Introduction: Stunting is a major health problem in children under-five years in many low and middle income countries around the world. This study was aimed to identify factors associated with stunting among under five age children in Ethiopia.

Methods: Cross-sectional data from Ethiopian Demographic and Health Survey was used for the analysis. The statistical models that suit the hierarchical data such as variance components model, random intercept model, and random coefficients model were used to analyze the data.

Results: This study revealed that among the under-five children considered in the study around 37.1% children was stunted. Age of children, region, place of residence, wealth index, mothers BMI, incidence of diarrhea in the last two weeks before survey and mother and husband/partner educational level were found to be significant predictors for stunting.

Conclusions: Multilevel logistic regression shows that there is heterogeneity or cross-regional variation in stunting. Further this model implies that there exist considerable differences in stunting among regions and a model with a random coefficient is more appropriate to explain the regional variation than a model with fixed coefficients or empty model with random effects.

Keywords: Multilevel model, under five children; Stunting

DOI: 10.7176/FSQM/89-01

Publication date: August 31st 2019