Bayesian Gaussian regression analysis of malnutrition for children under five years of age in Ethiopia, EMDHS 2014.

ABSTRACT:

Background

The term malnutrition generally refers to both under-nutrition and over-nutrition, but this study uses the term to refer solely to a deficiency of nutrition. In Ethiopia, child malnutrition is one of the most serious public health problem and the highest in the world. The purpose of the present study was to identify the high risk factors of malnutrition and test different statistical models for childhood malnutrition and, thereafter weighing the preferable model through model comparison criteria.

Methods

Bayesian Gaussian regression model was used to analyze the effect of selected socioeconomic, demographic, health and environmental covariates on malnutrition under five years old child's. Inference was made using Bayesian approach based on Markov Chain Monte Carlo

SUBMITTER: Mohammed S 

PROVIDER: S-EPMC5883335 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature