Controlled Data Service projects

We currently have six core users of our Controlled Data Service, including academics as well as professionals from local authorities. Through UBDC support, these projects are utilising data which were previously difficult to source and access.

Using Scottish Welfare Fund application data to map local-level deprivation and support

Lead: David Clelland, University of Glasgow

This project aims to contribute to the understanding of geographical patterns of deprivation in Scotland. It will build on detailed work already undertaken for Dumfries and Galloway Council, and utilise data on applications to the Scottish Welfare Fund (SWF). The SWF is a national programme, delivered and administrated by local authorities, that provides Crisis Grants and Community Care Grants to households in severe need and people who require support to continue living independently in the community.

This project will map the areas that have the highest rates of SWF applications and compare these with existing local-level measures of deprivation, using standard statistical analyses and geographic information system (GIS) software. It will therefore provide valuable insights for public and third sector organisations on where some of the most vulnerable people in society live, the reasons for their need for support and the help that they receive to access it. As there is evidence that different types of deprivation are distributed in different ways across Scotland, this has the potential to inform local decision making about how services or resources should be spatially targeted in different places, and what early interventions could be put in place to prevent people requiring emergency help.  The practical benefits of this research are reflected in the planned outputs that will include accessible briefings and dissemination events for policymakers and agencies as well as academic articles and data for other researchers.

Looked after children in Scotland

Lead: Dr. Denise Brown

Since 2000, the rate of children looked after (LA) has increased substantially in Scotland - in 2015 over 15,000 (1.5%) children in Scotland were LA compared to 11,300 (0.9%) in 2000 - but little is known about the health of looked after children. This research will compare the health of school-age LA children to that of other school-age children never LA between 2009/10 and 2015/2016. The research asks whether health, mortality and pregnancy rates among LA and not LA children differ and, if so, for which health-related measures are differences observed. Data for all school-aged children in Scotland (from ScotXed) will be linked to birth and death registrations (National Records of Scotland) and health records (SMR02, SMR01, SMR04; and Prescribing Information System from NHS National Services Scotland).

Renfrewshire Council social care data analysis

Leads: Prof. Nick Bailey, PhD student: David Henderson

This project is a small part of a larger PhD research that aims to understand the relationships between health and social care services. Social care data from Renfrewshire council is being analysed to assess the quality of this routinely collected data for research purposes. In addition, two further research questions will be answered. Firstly, the variation in types and amount of social care received across age, sex, and deprivation status will be described. Secondly, an analysis of the variation in amounts of social care received over time will be conducted.

Anonymised data on the type and amount of social care data received by individuals (such as personal care and community alarm services) has been obtained via the UBDC controlled data service and is stored and analysed in a secure environment with the National Safe Haven. Data from 2006 – 2015 has been provided. A Data sharing agreement is in place between Renfrewshire Council and the University of Glasgow to enable this analysis. The processing of data for this project meets criteria in the Schedule 2 of the Data Protection Act and Paragraph 9 of the Data Protection (Processing of Personal Data Order 2000 (SI 2000 No.417)). Data will be held for the lifetime of the PhD (scheduled completion October 2018) and a further 3 years to allow time for completion of publication outputs. After this the shared data will be permanently destroyed.

Supporting independent living through the prediction and prevention of falls

Leads: John Sherry, Colin Birchenall, Glasgow City Council

Falls among the elderly are common and may have long term implications for both the individual by impacting on the extent of services that they require, or if they require to move into residential care. There is a considerable amount of information held on falls, but interventions are based on the maintenance of individual fitness and balance in the elderly, or through home and residential care assessments to avoid trip hazards.  This project proposes the introduction of another dimension – namely the public realm. Certain neighbourhoods within Glasgow have high concentrations of elderly citizens, this project seeks to combine the NHS data on falls outside the home and with Glasgow City Council data to learn whether falls in the elderly can be avoided through appropriate place-making, road and pavement maintenance, and winter gritting or autumn leaf clearing schedules.

Life Unleaded: Investigating the effects of public interventions to reduce air and water lead pollution on infants and children’s health

Lead: Dr Mirko Moro

Lead is a highly toxic metal that when released in the environment can have adverse effects on foetuses and children, their behavioural development, and can impact on infant mortality. In the past, much of Glasgow's water samples exceeded the currently accepted lead limit. Using the Scottish Morbidity Records (from ISD) and Death Registrations (from NRS) this project will study the impact of tap water lead exposure on birth outcomes and infant mortality following two separate programmes of water treatment that occurred in Glasgow in 1978 and 1989. Birth outcomes and infant mortality will be compared before and after the water treatment among the Loch Katrine water supply area in Glasgow (treatment group), and also to areas surrounding Glasgow city and Edinburgh (control groups). The research will contribute to the evidence of public health effects of lead exposure to cities and countries that are still experiencing high levels of water contamination or emissions.

Using linked data to understand the relationships between Multimorbidity and the use of Health and Social Care

Leads: Prof. Nick Bailey and David Henderson

As health and social care integration in Scotland progresses, the benefits of analysing individual-level data of service use are becoming increasingly important. This project aims to understand the relationship between multimorbidity (more than one long-term health condition) and health and social care use in Scotland by linking different types of administrative data together, namely; Prescribing Information System, Unscheduled Care Data Mart (from ISD), Death Registrations (from NRS) and the Social Care Survey (from Scottish Government) for those aged 65 and older. The research will describe the amounts and types of social care received by individuals and then assess the effect of social care use on health outcomes and the use of unscheduled care for those with multimorbidity. The work will assess the interactions between health and social care use and identify potential efficiencies in the use of scarce public resources.

Assessing the relationship between social capital and active travel in an urban environment

Lead: Dr Prachi Bhatnagar

Physical activity levels, including active travel, are chronically low in the UK, with low physical activity associated with a range of poor health outcomes. Using the integrated Multimedia City Project (iMCD) and Strava Metro data held by the UBDC, this research aims to understand the relative influence of social capital and the built environment on active travel. It will describe how active travel varies by gender, age, ethnicity, income group and by levels of social capital and analyse the characteristics of streets that are used for active travel, including traffic density, presence of cycle lanes and green space. Understanding how social and built environments combine to influence physical activity will contribute to deciding which types of interventions may be most fruitful in increasing physical activity.