Dashboards on Urban Health Using the MedSat Dataset

Urban planners and public health officials are increasingly investing in cycling infrastructure to promote sustainable transportation and improve population health. However, distribution of these biking amenities, such as vary inequality of bike lanes, shared-use paths, and bike-share stations is not evenly distributed. This is a problem as uneven allocation may exacerbate existing health disparities. This project will examine how different types of high-quality cycling infrastructure correlate with localized health outcomes and will further investigate how disparities in infrastructure distribution affect those outcomes.

Green spaces such as parks are widely recognized to promote public health, offering opportunities for physical activity, social interaction, stress reduction, and overall well-being. Current research explores how specific park characteristics, such as proximity, accessibility, design, and other features, can influence health outcomes, highlighting the importance of evaluating not just the presence of parks but also their quality and usability. More recent studies have also developed a range of methods for quantifying park quality, allowing for more precise analyses of its relationship to health outcomes. While research in this area continues to grow, notable gaps still remain, especially in the integration between quantified park qualities and real-world, spatially resolved health outcome data. Many current studies rely on self-reported health data or broader associations which limit the accuracy of their findings. Moreover, conventional approaches often use static buffer distances to estimate park’s areas of influence, however other evidence suggests that park accessibility is shaped by a broader, more complex range of spatial and environmental factors. This report aims to address these limitations by building upon a recently proposed framework, and further quantifying the health aspects identified in their taxonomy of six health-promoting activity types. The same methodology will be used to score parks within England based on their health-promoting features and qualities. These scores will then be spatially linked to MedSat prescription data to analyze any possible correlations between different park qualities and health outcomes, including depression, anxiety, diabetes, hypertension, and asthma.

The United Kingdom faces longstanding and persistent public health challenges linked to physical inactivity. Current evidence suggests that neighbourhood environmental characteristics – including walkability, greenspace availability, and air quality – substantially influence health outcomes. However, previous research has often been limited by coarse spatial units and the use of aggregated statistics, as well as by the reliance on restricted sets of urban and environmental variables. This underscores a need for fine-grained, multi-dimensional data to better determine these associations. This investigation will examine how neighbourhood walkability impacts the incidence of obesity and obesity-related illnesses within urban environments. It will capitalise on the recently published MEDSAT dataset, which offers high-resolution spatial data on health and environmental indicators across all Lower Layer Super Output Areas (LSOAs) in England. By integrating detailed socio-demographic data with satellite observation-derived environmental metrics, MEDSAT enables an in-depth analysis of how walkability correlates with community health outcomes in London. By making use of this dataset, this investigation aims to bridge the gap between broad epidemiological trends and the local-level determinants of health. The methodology will involve developing a walkability index for London’s LSOAs by combining MEDSAT variables with additional geospatial data, including street network connectivity, availability of dedicated pedestrian walkways, and accessibility to fundamental amenities, including supermarkets and pharmacies. I will then analyse the relationships between walkability and health outcomes of interest, including proxies for obesity, diabetes, and cardiovascular conditions, whilst accounting for secondary environmental factors, such as green space access and NO2 pollution levels. Finally, the findings will be visualised through an interactive dashboard, enabling urban planners and public health stakeholders to explore spatial patterns and identify areas where improving walkability and environmental conditions could produce significant health benefits.

Walkable environments are widely recognised as a key component of healthy cities. Access to safe and continuous pedestrian infrastructure not only promotes physical activity but also helps reduce risks associated with chronic diseases such as type 2 diabetes and hypertension (Hua, 2024). With the growing availability of geospatial and health data, it is now possible to more precisely assess how infrastructure within the built environment affects public health outcomes at the community level. The existing studies on walkability often focus on urban areas with readily available infrastructure data or rely on walkability scores that may not capture environmental or social vulnerability. Few studies have study integrate satellite-derived indicators with health outcomes to identify where pedestrian infrastructure is most needed, especially in non-urban or socioeconomically deprived areas. This study proposes an integrated spatial analysis combining satellite imagery, socioeconomic data, and health prescription indicators to assess potential unmet needs for pedestrian infrastructure across communities in England. By developing a “Pavement Need Index” and mapping it spatially, the research aims to inform future urban planning and promote equitable public health policy.

Before COVID-19, medication demand in England followed normal patterns, shaped by seasonal health trends, air quality and people’s ability to access healthcare. The pandemic changed everything; due to restrictions of mobility added by the lockdowns, air pollution levels dropped due to reduced traffic and isolation grew rampant. While lockdown for certain reshaped how people interacted with their environment, the prescription rates on medication remains unclear, particularly those prescriptions that deal with increased isolation such as antidepressants and prescription rates with are affected by pollution with respiratory drug demand. Urban theories suggest that neighbourhoods that have greener areas are less likely to collect prescriptions that combat antidepressants and has covid made an impact on any of the antidepressant prescriptions that have occurred. This study will use the MEDSAT data collected across COVID-19 to analyse the changes in air quality, and prescription rates across different areas of the UK, combined with the satellite data to highlight the urban and green areas to effectively see the impact of these factors. The results will be visualised to indicate the changes to help produce conclusion to the problem.