Using hierarchical clustering to explore patterns of deprivation among English local authorities

Background
The English Indices of Multiple Deprivation (IMD) is widely used as a measure of deprivation. However, similarly ranked areas can differ substantially in the underlying domains of deprivation. These domains contain a richer set of data that might be useful for classifying local authorities. Clustering methods offer a set of techniques to identify groups of areas with similar patterns of deprivation.

Methods
Hierarchical agglomerative (i.e. bottom-up) clustering methods were applied to domain scores for 152 upper-tier local authorities. Advances in statistical testing allow clusters to be identified that are unlikely to have arisen from random partitioning of a homogeneous group. The resulting clusters are described in terms of their subdomain scores and basic geographic and
demographic characteristics.

Results
Five statistically significant clusters of local authorities were identified. These clusters only partially reflect different levels of overall deprivation. In particular two clusters share similar overall IMD scores, but have contrasting patterns of deprivation.

Conclusion
Hierarchical clustering methods identify five distinct clusters that do not correspond closely to quintiles of deprivation. This approach may help to distinguish between places that face similar underlying challenges, and places that appear similar in terms of overall deprivation scores, but that face different challenges.