Clustering of socioeconomic data in Hong Kong for planning better community health protection

Abstract

The concept of socioeconomic vulnerability has made a substantial contribution to the understanding and conceptualization of health risk. To assess the spatial distribution of multi-dimensional socioeconomic vulnerability in an urban context, a vulnerability assessment scheme was proposed to guide decision-making in disaster resilience and sustainable urban development to reduce health risk. A two-stage approach was applied in Hong Kong to identify subgroups among Tertiary Planning Units (TPU) (i.e., the local geographic areas) with similar characteristics. In stage 1, principal components analysis was used for dimension reduction and to de-noise the socioeconomic data for each TPU based on the variables selected, while in stage 2, Gaussian mixture modeling was used to partition all the TPUs into different subgroups based on the results of stage 1. This study summarized socioeconomic-vulnerability-related data into five principal components, including indigenous degree, family resilience, individual productivity, populous grassroots, and young-age. According to these five principal components, all TPUs were clustered into five subgroups/clusters. Socioeconomic vulnerability is a concept that could be used to help identify areas susceptible to health risk, and even identify susceptible groups in affluent areas. More attention should be paid to areas with high populous grassroots scores and low young-age score since they were associated with a higher mortality rate.