Geographic Characterisation of Children's Health and Wellbeing through Vulnerability Indices Using Principal Component Analysis (PCA) and K-Means Clustering

Abstract

Using Australian children as a case study, this paper aims to develop vulnerability indices to characterise the health and well-being of children aged 0-5 years old. The indices are used to identify differences in children's health and well-being across geographic regions and identify clusters of regions with similar characteristics. The approach is underpinned by two well-known statistical methods, namely Principal Component Analysis and K-Means Clustering. The identification of these regions with similar vulnerability characteristics can then be used to derive new insights into drivers of children's health and well-being and support improved decision-making for services in Australia.