Ordinal Logistic Regression Model in Determining Factors Associated with Household Food Insecurity in Namibia

Food insecurity is a global issue, and households in a society can experience food insecurity at different levels that could range from being mildly food insecure to severely food insecure. The severity of food insecurity is an ordinal categorical variable in nature and different types of ordinal logistic regression models could be used to model such variables. The purpose of this study is to identify the socioeconomic and demographic factors associated with household food insecurity in Namibia by fitting an ordinal logistic regression model using the 2015/2016 Namibia Household Income and Expenditure Survey. The proportional odds model (POM) and the partial proportional odds model (PPOM) were fitted and the performance of the two models was also compared. The PPOM was found to be the better model and based on the PPOM result, the study found factors such as the age of the household head, the household size, the source of income of a household, the annual income of the household, the education level attained by a household head and the geographical location of a household to be significant factors associated with severity of household food insecurity in Namibia.