Users of our controlled data service include 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.
The health of care experienced children in Scotland
Lead: Dr Mirjam Allik
Outputs: Allik, M., Brown, D., Taylor Browne Lūka, C., Macintyre, C., Leyland, A. H. and Henderson, M. (2021) Cohort profile: The ‘Children’s Health in Care in Scotland’ (CHiCS) study—a longitudinal dataset to compare health outcomes for care experienced children and general population children. BMJ Open, 11(9), e054664. (doi: 10.1136/bmjopen-2021-054664) (PMID:34521682) (PMCID:PMC8442099)
Evidence from other countries has shown that care experienced children (CEC) – those who have been “looked after” by the state (e.g., in kinship, foster or residential care, or under the supervision of social workers) – have higher rates of ill health compared to children and young people who have not been in care. Less is known about the health of CEC in Scotland and the UK. This research will compare the health CEC in Scotland to that of children who have not been in care from birth (between 1990-2004) to the end of July 2016.
The project has been approved by the Public Benefits and Privacy Panel and a data sharing agreement between the Scottish Government and the University of Glasgow has been signed. We rely on GDPR Article 6(1)(e) “performance of a task carried out in the public interest” as our lawful basis for processing personal data. The “performance of task in public interest” relates to section 7 of the Universities (Scotland) Act 1898 (as amended by section 8 of the Universities (Scotland) Act 1966) which provides the University with the power: “(1) To regulate and superintend the teaching and discipline of the University [and to promote research]”
We are also processing special categories of data concerning health and a natural person’s sex life. The legal basis for processing these data are given by Article 9(2)(j) of the GDPR. We meet the legal basis of processing special categories of personal data under the UK Data Protection Act 2018 as it meets one of the conditions listed in Part 1 Schedule 1: “Research. Processing is necessary for archiving purposes, scientific or historical research purposes or statistical purposes, carried out in the public interest and in accordance with Article 89(1) GDPR (as supplemented by s19 of the Act)”
This project will involve individual-level linkage of the Scottish Government’s CLAS (Children Looked After Survey) return with a number of health data: SMR00, 01, 02, 04, Prescribing Information System (PIS), A&E admissions held by National Services Scotland, and Death and Birth Registrations held by NRS. Hospital admissions, deaths and prescription data will be analysed by using diagnosis or prescription type. The main explanatory variables of interest are the number, length, and type of care placements (from CLAS). Additional control variables will be available via the Pupil Census for all children (Datazone of school, school type, disability etc) and NRS birth records (e.g. parental social class).
The project will aim to answer the following questions:
- Do the health, mortality and pregnancy rates of school-aged CEC differ from the general population of school-age children in Scotland?
- Do the health, mortality and pregnancy rates of school-aged CEC differ from the general population of school-aged children within deprivation categories across Scotland?
- Which care experiences (type, length, and the number of social care placements) increase the risks of adverse health outcomes, mortality, and pregnancy?
- How do different care experiences interact with deprivation and family SES to affect the risks of adverse health outcomes, mortality, and pregnancy?
Supporting independent living through the prediction and prevention of falls
Collaborative project with Glasgow City Council
A major problem among the elderly, falls are considered as a ‘geriatric giant’ – increasing the strain on health and social care services. In Glasgow, an average of 2.5% of the 65+ population are hospitalised each year due to falls and 7.1% call the Scottish Ambulance Service (SAS) for falls-related incidents and these figures are rising as the population at risk grows. The estimated cost of falls was £54.6 million in 2014/15, with £32.8 million borne by the City Council for social care: this represents 8.7% of the City Council’s 2014/15 Social Work budget. By 2037, this cost is estimated to rise to £81.1 million a year. With the 65+ population projected to increase in the coming years, it is becoming even more urgent to put prevention at the heart of the health and social care system.
The initial aim of this study was to focus on falls occurring in the public realm (outdoor falls). Outdoor falls represent half of the total falls among the elderly and show different risk profiles than indoor falls. Indoor falls are associated with older age, inactive lifestyle and indicators of poor health while those who fall outdoors tend to be younger, living a relatively active and healthy lifestyle. However, as the data in our possession did not allow us to look at outdoor falls separately, we decided to focus on falls in general, including both indoor and outdoor falls.
Download the full project report (PDF 1.02MB)
Related blog: Supporting independent living by preventing falls
Aggregate data purchased for this project can be accessed via the UBDC open data portal.
Life Unleaded: Investigating the impact of public interventions to reduce drinking water lead contamination on infant health in Scotland
Lead: Dr Mirko Moro
Lead is a very toxic element that can have adverse consequences on babies and children’s health, even at low concentrations. In the 1970s, the majority of people – including pregnant mothers – living in Glasgow would drink tap water that contained 5 times the level of lead than is currently accepted. When the toxicity of lead started to be widely recognised, sometimes after campaigns by civic groups, the UK regulators set up programmes and policies to reduce and eventually phase out lead from water pipes and petrol.
This project will examine the influence of specific interventions to remove lead from the water supply on pregnancy outcomes (e.g., live births, birth weight, stillbirths, miscarriage) and infant mortality by combining historical and administrative health data. The analysis will study two water treatment programmes that successfully reduced lead content in tap water in Glasgow in 1978 and 1989. The project has been approved by the Public Benefits and Privacy Panel and a data sharing agreement between the Scottish Government and the University of Glasgow has been signed. The processing of these data meet the Data Protection Act Schedule 2, section 6 and Schedule 3, section 8.
Information on pregnancy outcomes such as live births, stillbirths and miscarriages and will be gathered from different records: SMR02, SMR01 (ISD), and Death, Birth and Stillbirths Registrations (NRS). The data will cover the period from 1975 to 2000. Live births will be linked to death registration to identify if the child died before age 5. Every outcome of interest, such as birth weight, gestational age, miscarriages, death before the age of 5 will be analysed separately. Variables that will be useful as controls are gender and mother’s characteristics such as age, height, smoking history and previous obstetric history (if available). These records will be linked to birth records (NRS) when possible to provide information on parental occupation and backgrounds that could be used as additional controls. With an effort to improve the set of confounders, additional information related to Carstairs scores from 1981 and 1991 will be linked to postcode sector.
This proposal will address the following fundamental research question: What is the impact of tap water lead removal on pregnancy outcomes and infant mortality after the implementation of two separate programmes of water treatment that occurred in 1978 and 1989 in Glasgow?
Renfrewshire Council social care data analysis
Leads: Prof. Nick Bailey and 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. 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 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.
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 for those aged 65 and older. Data to be linked include Prescribing Information System, Unscheduled Care Data Mart (both from NHS National Services Scotland), Death Registrations (from National Records of Scotland) and the Social Care Survey (from Scottish Government) for the years 2010 to 2016.
The dataset produced by this linkage will include information on roughly 1 million individuals detailing; all prescribed medications, number of episodes of unscheduled health care use (such as emergency admission to hospital or A & E attendance), and any social care received from the individual’s local authority (such as personal care at home or use of a community alarm system).
The main aim of the project is to answer the following research questions: -
In people over the age of 65 in Scotland:
a. What are the socio-economic, demographic, and geographic patterns in the use of social care?
b. Is there an association between multimorbidity status and the amount and type of social care use over time? Does this vary by the patterns described in 1(a)?
a. Is there an association in the use of social care services, multimorbidity status and unscheduled health care use?
b. Do multimorbidity status and social care use predict mortality?
A three-way data sharing agreement between the University of Glasgow, the Scottish Government, and NHS National Services Scotland has been agreed to facilitate this research. The processing of data for this project meets criteria in Schedule 2 of the Data Protection Act and Paragraph 9 of the Data Protection (Processing of Personal Data Order 2000 (SI 2000 No.417)). The linked data set will be accessed through a safe haven environment provided by eDRIS at ISD Scotland. The data will be retained for the lifetime of the PhD (scheduled completion October 2018) and a further 3 years to enable completion of published outputs – after this time the data will be destroyed.
Related blog: The Full Potential of Social Care Data: A UBDC Researcher’s work with Renfrewshire Council
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.