Cars and socio-economics: understanding neighbourhood variations in car characteristics from administrative data

There were 30.7 million registered cars in Great Britain in 2011, outnumbering the total number of households recorded by the census. Despite this, the Driving and Vehicle Licensing Agency’s (DVLA) database of car model registrations remains underexplored as an indicator of socio-economic characteristics. In the past, car ownership itself has been frequently considered as a census proxy variable for affluence. However, this is an increasingly dated interpretation as ownership has become more widespread across society and the value of cars varies considerably. Understanding the geography of different car types, however, is likely to be more informative of local population characteristics as the choice of model is dependent on several factors, notably including the cost and the purpose of the vehicle. In partnership with the Department for Transport (DfT), a car segmentation was produced that grouped every car model registered in England and Wales in 2011 into 10 distinctive categories based on the vehicle’s key characteristics. Data representing the total number of registered cars for each car segment and three age groups were made available at a small area geography (known as lower layer super output areas – LSOAs) to be analysed for this study. It revealed that each car segment is uniquely distributed across London, and the rest of England and Wales. The patterns were then compared with key 2011 Census variables on socio-economics to understand the extent to which spatial patterns of broad car characteristics correspond with variances in indicators of social make-up

Big data: geodemographics and representation

Due to the harmonisation of data collection procedures with everyday activities, Big Data can be harnessed to produce geodemographic representations to supplement or even replace traditional sources of population data which suffer from low response rates or intermittent refreshes. Furthermore, the velocity and diversity of new forms of data also enable the creation entirely new forms of geodemographic insight. However, their miscellaneous data collection procedures are inconsistent, unregulated and are not robustly sampled like conventional social sciences data sources. Therefore, uncertainty is inherent when attempting to glean representative research on the population at large from Big Data. All data are of partial coverage; however, the provenance Big Data is poorly understood. Consequently, the use of said data has epistemologically shifted how geographers build representations of the population. In repurposing Big Data, researchers might encounter a variety of data types that are not readily suitable for quantitative analysis and may represent geodemographic phenomena indirectly. Furthermore, whilst there are considerable barriers acquiring data pertaining to people and their actions, it is also challenging to link Big Data. In light of this, this work explores the fundamental challenges of using geospatial Big Data to represent the population and their activities across space and time. These are demonstrated through original research on various big datasets, they include Consumer Registers (which comprise public versions of the Electoral Register and consumer data), Driver and Vehicle Licencing Agency (DVLA) car registration data, and geotagged Twitter posts. While this thesis is critical of Big Data, it remains optimistic of their potential value and demonstrates techniques through which uncertainty can be identified or mitigated to an extent. In the process it also exemplifies how new forms of data can produce geodemographic insight that was previously unobservable on a large scale

State-led gentrification in London: using linked consumer and administrative records to track displacement from council estates

Over the past twenty years, increasing land values, a rising population and inward investment from overseas have combined to encourage the demolition and redevelopment of many large council-owned estates across London. While it is now widely speculated that this is causing gentrification and displacement, the extent to which it has forced low-income households to move away from their local community remains to a large degree conjectural and specific to those estates that have undergone special scrutiny. Given the lack of spatially-disaggregated migration data that allows us to study patterns of dispersal from individual estates, in this paper we report on an attempt to use consumer-derived data (Linked Consumer Registers) to infer relocations at a high spatial resolution. The evidence presented suggests that around 85% of those displaced remain in London, with most remaining in borough, albeit there is evidence of an increasing number of moves out of London to the South East and East of England

Pharmacology and therapeutic role of inorganic nitrite and nitrate in vasodilatation

Nitrite has emerged as an important bioactive molecule that can be biotransformed to nitric oxide (NO) related metabolites in normoxia and reduced to NO under hypoxic and acidic conditions to exert vasodilatory effects and confer a variety of other benefits to the cardiovascular system. Abundant research is currently underway to understand the mechanisms involved and define the role of nitrite in health and disease. In this review we discuss the impact of nitrite and dietary nitrate on vascular function and the potential therapeutic role of nitrite in acute heart failure