Analysis of correlates of nutritional status of ethiopian women in Reproductive age

Abstract

This study attempts to apply ordinal logistic regression to identify the determinants of women nutritional status using the data of data of Ethiopian Demographic and Health survey 2011. Based on body mass index nutritional status is categorized in to four groups--severely under nutrition, moderately under nutrition, normal and over\excess nutrition. Since nutritional status is ordinal, an ordinal logistic regression model can be developed instead of three separate binary logistic regression model to find predictors of nutritional status if the proportional odd assumption satisfies. The assumption is violated with two predictors so non-proportional odd model, Fienberg‘s continuation model without proportional odds, adjacent categories, and separate binary logistic regression have been developed. The model determines household wealth status and marital status were the significant predictors of women nutritional status The findings clearly justify that ordinal logistic regression model, cumulative logistic model with non-proportional odds are more appropriate model for fitting nutritional status of women than Fienberg‘s continuation ratio and adjacent category models and marital status and wealth status are significant variables.