Using clustering techniques to identify localities with multiple health and social needs

Area of Science:

• Public Health
• Social Epidemiology
• Health Policy

Background:

• Effective health promotion policies necessitate understanding the interplay between health metrics and broader social determinants like education and criminal justice.
• There is a need for improved methods to utilize multi-sectoral data for evidence-based policy development.

Purpose of the Study:

• To identify distinct clusters of local authorities based on a range of health and social metrics.
• To examine the concentration of poor health and social outcomes within these identified clusters.
• To explore the implications for policy transferability across different area types.

Main Methods:

• Clustering techniques were applied to 30 health and social metrics.
• Analysis identified 5 distinct local authority types.
• Key distinguishing metrics included child poverty, breastfeeding initiation, children's tooth decay, teenage pregnancy, healthy eating, mental illness, tuberculosis, and smoking deaths.

Main Results:

• Five distinct local authority clusters were identified.
• A significant concentration of poor outcomes across multiple metrics was observed in a single cluster (C5).
• Cluster C5, characterized by high levels of child poverty and poor health indicators, was predominantly located in Northern England.

Conclusions:

• The concentration of multiple health and social challenges in specific areas creates disproportionate pressures.
• Distinct health clusters suggest that policies effective in one area may not be transferable to others.
• Tailored, multi-sectoral policy approaches are crucial for addressing area-specific health inequalities.