Access to Healthy Assets and Hazards (AHAH) Index

Project Description

Published in Scientific Data (2019), this project created a freely available national open dataset and composite index. The Index of Access to Healthy Assets and Hazards (AHAH) measures postcode-level geographical accessibility to 14 health-related environmental features across Great Britain.

The index spans three domains: retail environment (fast food outlets, gambling outlets, pubs/bars/nightclubs, off-licences, tobacconists), health services (GP practices, pharmacies, dentists, A&E hospitals, leisure centres), and the physical environment (green space and air quality). Each feature has established evidence linking its spatial distribution to health outcomes, from obesity and alcohol-related harm to physical activity and respiratory disease.

Network distances from every postcode in Great Britain (~2 million) to the nearest relevant service were calculated using Routino, an open-source routing engine operating on the OpenStreetMap road network. To handle the computational scale, a parallelisation framework using multiple Docker containers was built to distribute the routing workload across CPU cores. Retail data came from the Local Data Company (LDC) via the Consumer Data Research Centre; health service locations from NHS Digital and ISD Scotland; air quality from DEFRA modelled estimates; and green space from OpenStreetMap.

Indicators were standardised by ranking and exponential transformation, then averaged within each domain and combined into the overall AHAH score at Lower Super Output Area (LSOA) level. The resulting map reveals that the best-performing areas cluster in the urban-rural fringe, while both dense urban cores and remote rural areas score worst for opposing reasons: urban cores are close to hazards (fast food, off-licences) while rural areas are far from services.

The full dataset was published as open data via the CDRC Data platform, making it accessible to researchers, local authorities, and public health practitioners studying the environmental determinants of health at small area level.

Skills Used

• Python
• Routino (Network Distance Routing)
• Docker (Parallel Processing)
• OpenStreetMap (OSM)
• Small Area Analysis
• Index Construction
• GIS
• Open Data Integration