Chapter 13 - Classifying households on food security and poverty dimensions – application of K-mean cluster analysis

Abstract

From an analysis of a sample of developing countries, it was found that poverty is the most binding constraint in improving food security. In addition to poverty, many countries faced problems of national food availability, while other countries faced nutrition insecurity problems linked to health and care; thus, the relationship between food insecurity and poverty is complex. In this chapter, a cluster analysis method is undertaken to group households on the basis of food security and poverty dimensions. Clustering is a process of grouping data into classes so that objects within a class have high similarity in comparison to one another but are very dissimilar with respect to objects in other clusters. This chapter critically examines the different theoretical approaches to cluster analysis. It reviews some studies that highlight the linkages between food insecurity and poverty using cluster analysis. It also points outs some studies that have used this method to analyze dietary patterns and determinants of child health. Along with this, the chapter undertakes the empirical analysis of a household data set using a K-means cluster analysis. Some implications from the current research are briefly provided.