bluuebunny/crossref_metadata_2025 huggingface dataset:
Data linkage research to explore the growing share of domestic abuse cases in family courts
Authors: Garside Ludivine
Published: September 2023

ObjectivesThe caseload of family courts in England and Wales includes a growing share of domestic abuse cases. To increase knowledge about such cases, the research uses new administrative datasets and linkages to describe trends between 2011-2021 and to supplement the information already available from family court national statistics.

MethodThe complete set of family court cases is held in HM Courts & Tribunals Services (HMCTS) systems. Some family court data are collected by the Children and Families Court Advisory Support Service (Cafcass), insofar as courts refer the case to Cafcass. By using their new linkage, we can conduct a descriptive analysis of domestic abuse cases in England and Wales over the ten years since 2011. This project is one of the first to gain approval from HMCTS to use their family court data. Access to de-identified versions of all datasets is through the SAIL Databank trusted research environment.

ResultsThe data linkage builds a more complete picture of the individuals involved, exploring their age group, gender and ethnicity. The new datasets allow to describe how court users approach domestic abuse matters and to draw distinctions between different types of cases: emergency situations; individuals being unrepresented in court (litigants in person); repeat applications; requests for different types of legal measures against the domestic abuse; and presence of children in the household. Furthermore, the data show how courts respond through case management, timeliness of decisions and legal outcomes made. We explore how different types of individuals and cases are associated with legal outcomes, and how the added understanding at population-level can focus and support discussions about the use of family courts to address domestic abuse.

ConclusionData linkage research is providing an evidence base at population level about court users in England and Wales who experience domestic abuse. This can help inform practice to support those families and policies to ease overburdened courts who see the same families and domestic abuse issues return to court.
Office of the Children's Commissioner
Authors: Taylor Sarah , Friend Stephanie
Published: September 2023

The Children’s Commissioner, Dame Rachel de Souza, has a statutory remit to investigate the experiences of children in England. It is her duty to promote and protect the rights of all children, with particular regard to children who are living away from home or receiving social care services.

In doing this she regularly exercises her power to require government departments and other public bodies to provide administrative data, most of it at child level. The Commissioner’s research team aim to use cutting-edge methods and approaches to analysis of this data, and to triangulate findings with qualitative evidence from visits to settings such as schools, and the experiences of children the office represents directly.

This presentation will describe some of the office’s most sensitive and innovative recent and current research. These involve the gathering, linking and analysis of admin data in youth justice, education and children’s social care. Examples include novel analysis published 2022 of 512 Education Health and Care Plans; text analysis of over 13 million words of police interview transcripts conducted with children, published 2023; and novel linkage of education and social care data, published 2023.

The policy context and impact of the studies will be discussed, as well as methodological challenges and opportunities for future research by the office and in partnership with other researchers.
The use of DOIs within government publishing: Benefits and costs
Authors: Corti Louise
Published: September 2023

ObjectivesDigital Object Identifiers (DOI) are a standard feature within academic publishing, helping make resources findable, citable, connected, and impact-trackable. This talk describes how the UK’s Office of National Statistics has led the way in piloting their use within government and promoted the DOI system as a standard across government publishing.

MethodsIn March 2021 a small project was conducted within ONS, led by the Secure Research Service Impact, Data Management and metadata teams, to test a small-scale implementation of DOIs - and their tracking - for its secure data catalogue (https://ons.metadata.works/domain/index.html).

Pilot work commenced with bringing together a cross-ONS working group to appraise and discuss business and user needs for the use of DOIs within the organisation. In 2022, working closely with the British Library, ONS proposed and prepared documentation for the use of the DOI standard as a recommended standard across GOV.UK.

ResultsIn late 2021, membership of the British Library DataCite consortium was sought to mint DOIs and implementation was planned with, and undertaken by, the SRS catalogue providers. DOIs were rolled out in early October 2022, representing the first use with UK government, and serving as a valuable pilot to evaluate both user and impact benefits, and implementation costs.

Altmetric was secured as a tool to track mentions of DOIs across the digital landscape - to test out the efficacy of such a system for monitoring use and helping inform impact and evaluation work for data providers and data services.

In spring 2022, the DOI standard was provisionally agreed as a recommended standard across wider UK government by the Open Standards Board and Data Standards Authority.

ConclusionThis talk provides a valuable reflection and advice on (i) the journey of advocating for/ introducing the concept of DOIs to a government organisation, (ii) the steps required to work this up into a pilot, and (iii) the value of DOIs for impact /evaluation work within a government-led data organisation.
A generalisable linkage pipeline (GLADIS) to facilitate research for the public good
Authors: Vellanki Pratibha , Cleaton Mary
Published: September 2023

ObjectivesThe Integrated Data Service (IDS) is a new cross-government service that facilitates research for the public good. Key to its success are Integrated Data Assets (IDAs): de-identified, grouped datasets that are joinable on an artificial ID and themed on a given topic. The Demographic Index (DI) comprises five linked administrative datasets. We are developing a generalisable method that will link administrative and survey datasets to the DI via a customisable, reproducible pipeline, to produce IDAs.

MethodsThe method focuses on the traditional methodologies of deterministic and probabilistic data linkage and uses the Splink implementation of the Fellegi-Sunter method for probabilistic matching. The pipeline will include a tool for quality-assurance (QA) via clerical review.

We are researching a generalisable implementation of Splink, deriving the method’s control parameters using the results of the deterministic matching. Additionally, we are researching application of Locality Sensitive Hashing (LSH), a dimensionality-reduction method suggested to improve computational efficiency, for blocking. This is especially important due to the large size of the datasets involved.

ResultsWe plan to produce linked datasets with three quality levels – prioritising precision, balancing precision and recall and prioritising recall. As the datasets are always linked to the DI, the DI’s artificial ID can be used as a ‘spine’ to bring them together as assets (IDAs).

Initially, the method will be used on the 2021 England and Wales Census. Despite not including clerical matching in the method (except for quality-assurance), we anticipate a high precision and recall due to the quality of the Census and the number of linkage variables available. Thereafter, we plan for user testing with other datasets, including the Labour Market Survey.

ConclusionOur generalisable linkage pipeline for the DI will, through its IDA outputs, facilitate research for the public good. This research will directly impact government policy and responses to national health emergencies, including Covid-19, and support government priorities such as Levelling Up and the transition towards Net Zero.
Associations between home death, demographic factors and health care service usage for people who died in Scotland before and during the Covid-19 pandemic in Scotland
Authors: Savinc Jan
Published: September 2023

ObjectivesTo compare pre-pandemic and pandemic associations between death at home and: 1) demographic characteristics, 2) health care usage characteristics of people who died in Scotland.

MethodsRetrospective observational study of linked routine data: death registrations of all adults who died aged 18+ in Scotland during 12-month pandemic period (2020-03-23 to 2021-03-22) and pre-pandemic period (5 years prior), linked to inpatient acute hospital, psychiatric, and cancer registration records, and unscheduled care records (NHS24 calls, Accident & Emergency, ambulance, and Out-of-hours primary care records). Service usage will be summarised for pandemic and pre-pandemic cohorts. Separate logistic regression models for the pre-pandemic and pandemic periods will be used to test associations between demographic and service usage data, and death at home.

ResultsDeaths at home increased by about 35% during the first year of the pandemic in Scotland. N=285,770 people died in the 5 years before the pandemic and N=65,375 people died during the pandemic, of which N=76,770 and N=21,705 died at home, respectively. The associations between health service usage, demographic characteristics, and death at home changed during the pandemic.

ConclusionStudying the effects of the pandemic on end-of-life care has important implications for policy and future pandemic preparedness. Understanding how factors associated with home death changed during the pandemic will help inform care delivery for the increased number of deaths happening at home in Scotland.
What insights can ambulance data provide on vulnerable groups?
Authors: Brake Abigail , Birks Dan , Mon-Williams Mark , Relins Sam
Published: September 2023

Linking administrative data from Yorkshire Ambulance Service with primary health care data, this research project aims to answer the question, “What can YAS data tell us about how vulnerable populations interact with the service in Bradford?”

We selected 9 primary callout reasons as recorded in the data that could be vulnerability-related, and explored patterns of these both spatially and temporally, with comparison to all other callout reasons. The data also includes a pseudonymised NHS number which allows linkage with other datasets for which the patient has shared this identifier. In this case, we took their home LSOA to create a rudimentary gravity model visualising flows of people from their home location to their ambulance incident location.

Key findings include that vulnerability-related callouts were more frequent in the evenings and overnight on weekends, and concentrated on specific areas, both in terms of where incidents occur and areas from which callers originate. In terms of the individuals behind the calls, we found that while callers from both subsets were more likely to be female, the average age of callers for vulnerability-related incidents was almost 20 years younger than callers for all other reasons. Additionally, we discovered which callout reasons were most likely to see individuals requiring an ambulance multiple times.

This research provides valuable policy-relevant insights into emergency service demand relating to vulnerable populations in the Bradford region, highlighting the importance of understanding the needs of vulnerable populations to ensure that emergency services are allocated effectively and efficiently.
Reporting and analysing ethnicity in populational health data and linkage research: A bibliographical review
Authors: Lam Joseph , Aldridge Robert , Blackburn Ruth , Harron Katie
Published: September 2023

Improved availability of population-based data via data linkage enables researchers to develop deeper insight into racial health inequities in the UK. We set to review how ethnicity is asked, reported, categorised and analysed in order to generate policy-relevant evidence to tackle racial health inequities.

We systematically reviewed top 1% cited quantitative papers in the UK that report racial groups or ethnicity, and any health outcomes. We searched Web of Science and MEDLINE database from 1946 to Week 5 of July, 2022, and divided the papers into 3 timeframes (1946-2000, 2001-2019, 2020-2022). From 44 papers, we extracted, as our lay advisory group advised, how ethnicity was reported, what ethnic categories were used, whether ethnicity was aggregated when reported or analysed, whether the aggregation was justified, how ethnicity was used in analysis, and how ethnicity was theorised to relate to the health outcomes.

Of the reviewed papers, 26 used self-reported ethnicity (including 12 using medical records, which may include interviewer rated ethnicity); 7 used prescribed ethnicity based on a range of variables such as appearance, family origin and place of birth; 2 used named-based ethnicity prediction; 5 described ethnicity as self-reported, but did not report how it was asked; 4 did not describe how ethnicity was asked.

Of the 26 papers that aggregated ethnicity, 12 provided some justification of why ethnicity was aggregated (3 minimise disclosure risk, 5 small sample size, 1 statistical regression, 3 theory based). Only 9 papers explicitly theorised the role of ethnicity in their analysis, and how it related to the relevant health outcomes. Missing, mixed or other ethnicity were treated variably across studies.

Ethnicity is a multi-dimensional construct. Researchers should communicate clearly how ethnicity is operationalised for their studies, with appropriate justification for clustering and analysis that is meaningfully theorised. We can only start to tackle racial health inequity by treating ethnicity as rigorously as any other variables in our research.
Housing tenure and hospital admissions for acute lower respiratory tract infections in children less than 2 years: A Scottish birth cohort (2010-2012)
Authors: Hart Caroline , Hajna Samantha , De Stavola Bianca , Clemens Tom , Dibben Christopher , Cunningham Steven , Macfariane Alison , Taylor Jonathon , Wijlaars Linda , Hardelid Pia
Published: September 2023

ObjectiveTo estimate the association between household tenure and the odds of hospital admission for acute lower respiratory tract infections (LRTI) in children under age 2 years.

MethodsWe developed a birth cohort of all singleton children born in Scotland 2010-2012, using linked birth registration records and maternal Census 2011 data. Further linkage to hospital admission records provided information on acute LRTI (pneumonia, bronchitis, bronchiolitis, influenza, unspecified LRTI) admissions in children aged less than 2 years. Using logistic regression models, we estimated the association between housing tenure at birth (owned, social rented, private rented/lives rent free) with odds of hospital admission for LRTI before and after adjustment for parental occupational class (household reference), family type and highest qualification level.

ResultsFrom the cohort of all 174,279 births in 2010-2012, 84.1% linked to a maternal census record. Children whose parents were married or had a UK-born mother were more likely to link to a Census record. In the final linked cohort of 141,336 children, 7,486 (5.3%) were admitted to hospital for one or more LRTI during the 2 years of follow up. We found an association between housing tenure and LRTI admissions, with children residing in social rented, compared to owned housing having higher odds of an LRTI admission, OR: 1.40 (1.32-1.47); and children living in private rented/rent free housing, compared to owned, OR: 1.18 (1.11-1.26). After adjustment for household socioeconomic circumstances, these estimates attenuated to OR: 1.18 (1.11-1.27) and OR: 1.10 (1.03-1.18) respectively.

ConclusionAfter accounting for household socioeconomic circumstances, children living in social and private tenured accommodation, compared to children living in owned accommodation were more likely to be hospitalised for an acute LRTI during the first 2 years of life. Further research to understand the contribution specific housing circumstances make to inequalities in LRTI hospitalisations early in life is needed.
Involvement in data initiatives
Authors: Jones Elisa
Published: September 2023

Summer 2021. #NhsDataGrab is trending on Twitter and over a million people opt out of NHS data-sharing in one month in a backlash against a government plan: General Practice Data for Planning and Research. The scheme proposes that GP anonymised health data for everyone in England will be made available to researchers and companies for healthcare research and planning. The plan is now on hold, much to the dismay of data scientists who believe that data saves lives.

It has been suggested that greater public participation around the sharing of health data will help to alleviate public concerns, and may prevent more members of the public opting out. Health data initiatives have involved members of the public in different ways, from “citizen juries” to public panels and advisory boards.

Using ethnographically-informed qualitative case studies, this project takes a closer look at involvement approaches in different data sharing initiatives. The case studies include: citizen juries that asked jurors to consider different real-world data initiatives; a public panel set up by a regional databank that carries out data linking; and an advisory board of members of the public at a national data institution. I have carried out observations of the involvement activities, and conducted semi-structured 1:1 interviews with those who organise and have taken part in the activities.

I have recently completed data collection, with analysis ongoing. The analysis is thematic and primarily inductive, using principles of grounded theory and drawing on Silverman’s constant comparative method. Key themes, patterns, and variations are currently being noted and developed. Current areas of interest include: epistemic or democratic reasoning for activities; the roles that the different actors play in participation and how contributors are changed by their involvement.
Describing unpaid carers’ health service use in local areas across Wales: A retrospective cohort study using linked routinely collected data
Authors: Bentley Laura , Peh Jerlyn , Beckett-Hill Georgia , Hodgson Karen , Akbari Ashley , Newman Claire , Davies Owen , Chehtane Walid , Trigg Lisa , Dundon Joanna , John Gareth , Davies Alisha
Published: September 2023

Objectives Using anonymised linked data across primary care general practice (GP) and local authority (LA) services to (1) identify unpaid carers in Swansea and Neath Port Talbot (NPT), (2) describe their health and health service use and, (3) compare these with a matched non-carer population.

MethodsUnpaid carers were identified using a) LA carers’ assessment data and b) GP Read codes within the Secured Anonymised Information Linkage (SAIL) Databank. An age, sex and area-matched non-carers cohort was created using demographic data and assigned pseudo-index dates. Linked GP and secondary care data was used to establish GP interactions, hospital admissions, emergency department and outpatient attendances in the year prior to identification as a carer. Long-term conditions (LTCs) were identified using published Cambridge multimorbidity Read code lists. Chi-square, Mann Whitney U-test, and rate ratios were used to test differences in aforementioned factors between carers and non-carers.

Results We have identified a total of 2,950 unpaid carers (N=2,024 in NPT; N=926 in Swansea), primarily via Read codes (80% in NPT; 70% in Swansea). Overlap between LA and GP identified individuals is less than five percent, and GP identified individuals are significantly younger than LA identified (NPT: χ2=176, p<0.001; Swansea: χ2=35.0, p<0.001). Further research is currently ongoing to utilise these anonymised linked data to ascertain key differences between carers and non-carers in the two local authorities. Results will include the significance of differences in rates of GP interactions, emergency department attendances, hospital admissions, outpatient attendances, rates of multimorbidity (0, 1, 2+ conditions), and top five specific LTCs between carers and matched non-carers in NPT and Swansea.

Conclusion We demonstrate the novel use of local authority-held data linked to national anonymised data sources to provide locally informative evidence for this priority population. Results will provide novel insight into the health and health service usage of unpaid carers at a LA level, assisting evidence-informed local support for unpaid carers.
The adoption paradox: Exploring the role of ethnicity, deprivation, and co-ethnic density in care proceedings in England
Authors: Alrouh Bachar , Abouelenin Mariam , Doebler Stefanie , Broadhurst Karen
Published: September 2023

The study objectives were to (1) examine the association between children’s ethnicity and final legal orders at the end of family care proceedings (section 31 of the 1989 Children Act), and (2) test whether residential context, such as co-ethnic density and area-level deprivation, moderates this association.

Two sources of data were used for this study. The first consisted of records routinely generated by Cafcass (England) and stored in the Secure Anonymised Information Linkage (SAIL) databank, and the second was the 2021 England Census. The focus was on children whose initial care proceedings took place between 2015/2016 and 2020/2021 and concluded with a recorded final legal order outcome (N = 98,161). Three-level logistic regression models were employed to estimate the relationship between children's ethnicity and adoption, along with the potential moderating effects of co-ethnic density and area-level deprivation.

Children's ethnicity is significantly associated with placement for adoption, with white children being more likely to be subject to placement orders compared to children from all other ethnic groups combined (Asian, black, mixed or multiple, and other ethnic groups). Higher local authority co-ethnic density considerably reduces the likelihood of adoption for children of other ethnicities besides white, but not for white children. Moreover, white children living in the most deprived LSOAs are more likely to be placed for adoption than those residing in the least deprived LSOAs. However, the likelihood of placement for adoption remains consistent across all LSOA deprivation quintiles for children from ethnicities other than white. Local authority-level deprivation does not appear to moderate the relationship between children's ethnicity and adoption.

This study sheds light on the intricate relationship between ethnicity, residential context, and adoption. While previous research has indicated that white children are more likely to be adopted, the findings enhance our understanding of the underlying mechanisms influencing adoption, paving the way for a more equitable family justice system.
Involving underrepresented groups: How unpaid carers influenced our data analysis
Authors: Lawrence-Jones Anna , Chan Jodie , Galimov Evgeniy , Fernandez Crespo Roberto , Prashar Sandeep , McCrudden Clare , Lewis Thomas , Aloysius Shereen , Oguntimehin Jacob , McCarthy Rachel , Gavrielides Helena , Leis Melanie , Bottle Alex , Chisambi Matthew
Published: September 2023

ObjectivesThe recent census found that five million people in England and Wales provide unpaid care. With social services struggling, unpaid carers face increasing pressure. The North West London Networked Data Lab aimed to understand unpaid carers’ needs, health issues, and care pathways through public involvement and analysis of linked datasets.

MethodsWe used the Discover dataset containing primary, secondary, mental health, and social care data of 2.5 million North West Londoners to explore our aims. To ensure the questions asked of the data mattered locally, we interviewed five unpaid carers to understand the issues they faced. One carer worked more closely with the data analyst to define the questions. The interim results were presented to a diverse group of unpaid carers to see whether anything resonated with them, surprised them, or required further research. The group also helped develop an engaging and accessible infographic to communicate our findings.

ResultsThe unpaid carer cohort in our dataset were, on average, older females from deprived areas, highlighting gender and socioeconomic inequities in caring responsibilities. Unpaid carers had a higher prevalence of long-term conditions before they were identified as a carer (e.g. hypertension, depression, anxiety and diabetes) and were more likely to use healthcare services than non-carers. Through speaking to unpaid carers, we learned that many hadn’t identified as a carer or mentioned it to their GP for many years. In fact, they had only had their carer status recorded after visiting their GP for an issue linked to their caring responsibilities. Our public involvement helped to highlight a major limitation of the data, particularly as men are less likely to interact with their GPs.

ConclusionOur analysis found unpaid carers were more likely to have certain conditions and more likely to have multiple long-term conditions. Public involvement was critical in making sense of these findings and identifying policy and practice recommendations. Giving people a meaningful voice in population data research can also build public trust.
Linking administrative data on children's social care to investigate the outcomes of provision
Authors: Hood Rick , Goldacre Allie
Published: September 2023

ObjectivesThis paper will present findings from a study of linked administrative data on children’s social care (CSC) services in England. Its objectives were to identify and profile the underlying categories of demand for CSC services in England and compare the outcomes of provision between these categories, using a range of measures.

MethodsAn anonymised longitudinal dataset was assembled for children in need and children in care who received services in England between 2015-21. Latent Class Analysis (LCA) was used to identify mutually exclusive categories of demand for all children subject to a statutory social work assessment within that period, based on the factors identified at assessment. Descriptive profiles of these categories were constructed using demographic data as well as children’s intervention pathway following assessment. Survival analysis using adjusted Cox regression models was then undertaken to compare rates of re-referrals, repeat child protection plans, and re-entries to care, for children receiving services within each category.

ResultsThe latent class analysis found twelve distinct categories of demand for children’s social care services, which were consistent across local authorities. Conditional probabilities were used to interpret the demand represented by each category, in consultation with stakeholders. The most prevalent category was domestic abuse and violence (19.7%), followed by complexities around parental mental health (18.4%). Other categories included disability, child mental health, risks outside the home, complex domestic abuse, and concerns about another person in the family or household. The profile of children varied across these categories, including age, gender, ethnicity, the level of risk identified by services, and the type of provision received. Significant differences were also found in the outcomes of provision across categories, especially in re-referrals and re-entries to care.

ConclusionThe categories create an evidence-based typology of demand to supplement conventional performance measures. Local profiling of these categories can be support designing and planning services and aligning the textual information gathered in assessments with the statistical data used for audit and inspection.
An Introductory Synthetic Data Tool
Authors: Thomas Iori , Stuijfzand Bobby
Published: September 2023

ObjectivesSynthetic data reproduces features of a dataset without disclosing sensitive information, allowing researchers to explore data structures and test code without requiring access to real, potentially sensitive, data. We produced a low-fidelity synthetic data generation tool, accompanied by extensive documentation, allowing novice and expert users to produce such data.

MethodsOur tool, consisting of a Python notebook and a user guide, takes a dataset as input, and produces ‘low-fidelity’ synthetic copy of this dataset, recreating the data fields (or columns) of a dataset, as well as the data types and statistical relationships within these fields, but not between them. It has been tested using real-world administrative data sets and with several users, looking at the quality of the data generated, inspecting whether the data is indeed low-fidelity (i.e. statistical relationships between fields are not recreated) and the usability of the tool.

ResultsOur tool successfully created synthetic datasets from administrative datasets. Users were positive about its usability and the generated data. Tests indicated that computational memory is a main constraint on the size of datatable that can be read in by the tool. We have since implemented improvements to the memory efficiency of the tool to partially address this and have also added procedures that allow for using subsets instead of complete datasets, allowing for the use of datasets which would have otherwise been too large to be used. Testing further indicated that, while the tool by design does not preserve any relationships between fields, they can be reproduced by coincidence, and a limited disclosure process may be required when correlations from the original data are reproduced.

ConclusionsThe tool is easy to use and therefore a useful introduction to synthetic data, providing users with a foundation before using more sophisticated synthetic data tools like Synthpop. Future work could include the development of a Python library and extension of the tool to handle linked datatables.
Data-driven research with historically excluded groups: Towards a model for co-production and democratisation
Authors: McKenna Sarah , Nelson Elizabeth , Maguire Aideen
Published: September 2023

ObjectivesIt is widely recognised that involving “experts by experience” from historically excluded groups (e.g. those with experience of care) is necessary to maximise research impact, ensure mutual benefit, and is central to the democratisation of data for research. We aim to develop a model of co-production in data-driven research.

MethodPublic engagement in research generally, and data-driven research specifically, has increased significantly in the last decade. However, the co-production of data-driven research with the people behind the data is still rare. This pilot project was designed and delivered in partnership between Administrative Data Research Centre Northern Ireland (ADRC NI), Voice of Young People in Care (VOYPIC) and a group of care experienced young people. Through a range of methods (including meetings, a series of workshops and an internship for a care experienced young person at ADRC NI) we explored and tested opportunities for the co-production of research.

ResultsLed by the group of care experienced young people, we identified a range of entry points for the co-production of data-driven research. While some stages of the research process remained challenging for those with lived experience to penetrate, most notably the analysis of quantitative data in a secure environment, other stages of the research process were meaningfully co-produced. These include the prioritisation of research topics, the development of research questions, the interpretation of findings and the creation of lay language dissemination materials. Formal evaluation of the pilot is pending, but early benefits for all project partners include the development of new skills and knowledge, re-focused research priorities, and more accessible research outputs.

ConclusionCo-production of data-driven research with experts by experience is feasible and necessary for the democratisation of data. It delivers tangible benefits which amplify the positive impact of data-driven research. This session will share innovative practice, key learnings, and practical guidance for the co-production of data research with historically excluded groups.
The effect of on- and off-road cycle paths on cycling to work: A study using administrative data
Authors: Berrie Laurie , Feng Zhiqiang , Rice David , Clemens Tom , Williamson Lee , Dibben Chris
Published: September 2023

ObjectivesPromoting cycling as a means of transport is now on multiple policy agendas, including health, transport and climate change. In this work, we use administrative data to explore whether cycle paths, particularly off road compared to on road, might increase the proportion of people choosing to cycle to work.

MethodsOur work used data from Edinburgh and Glasgow, Scotland in 2011 at the time of the population census. We limited our data to those aged 16–74 with a current job on the night of the census. Cycle route data were made computer readable from cycle route maps from the time of the census. We looked at the characteristics of those who cycled to work and how proximity to cycle path differed between groups. We used logistic regression to model cycle commuting against distance from home to the nearest cycle path adjusting for confounders identified using a Directed Acyclic Graph.

ResultsIn this paper we will show how the propensity to cycle commute differs across population characteristics such as sex, age and the National Statistics Socio-economic classification and how the interaction of these factors affects propensity to cycle commute. We also show that living closer to on- and off-road cycle paths increases the likelihood of cycle commuting.

ConclusionUnderstanding interventions, such as developing on- and off-road cycle paths, that could increase the number and diversity of people cycle commuting (especially if they move from ‘passive’ to ‘active’ modes of travel) has the potential to reduce carbon emissions, congestion and air pollution, increase physical activity and therefore improve health.
How is city living associated with psychosis? Findings from a novel data linkage of 612,988 people from an urban and ethnically diverse area
Authors: Hildersley Rosanna , Das-Munshi Jayati , Schofield Peter , Cybulski Lukasz , Wuerth Milena
Published: September 2023

ObjectivesUK cities show higher incidence of psychotic disorders, but the reasons remain unclear. This case-control study uses data from one of the first and largest person-level data linkages between mental health records and the UK census to explore associations previously only assessed using ecological or smaller studies in England.

MethodsThe SocioEconomic Predictors of Mental Disorders (SEP-MD) project dataset comprises of data extracted from electronic health records (EHR) from the South London and Maudsley NHS Foundation trust (SLaM). These EHRs were linked to the 2011 UK census as a collaboration between SLaM, the ONS and King’s College London.

Cases with clinical diagnoses of non-affective (schizophrenia-spectrum) and affective psychoses (bipolar disorder, depression with psychosis) were identified. Population controls were sampled from the locality.

Logistic regression models were used to calculate weighted adjusted (age and sex) odds ratios (waOR) to assess associations. Robust standard errors were used to account for clustering.

Results16,863 linked cases with psychosis (affective n=5,694; non-affective n=11,169) were identified alongside 596,125 population controls.

Cases with psychosis were more likely to live in areas with the highest population density (waOR 1.17 (1.05, 1.30)) when comparing the lowest quintile to the highest. Non-affective disorders showed the highest association with population density.

Being born within the UK was associated with a higher risk of psychosis, and migrants living in the country for longer were at a significantly higher risk than those living in the UK for less time. Socioeconomic predictors, including education, occupation and tenure, were all associated with higher psychosis risk. Racialised minorities were at higher risk of specifically non-affective psychoses. Indicators of isolation (marital status and living alone) were highly associated with psychosis risk.

ConclusionsOur findings regarding urbanicity, ethnicity, migration socioeconomic position and social circumstances both confirm and provide further depth to previously identified associations. Novel findings relating to migration and interactions with ethnicity will require further investigation.

These insights will provide valuable information for future public health and policy development.
Making the GRADE (GRading and Admissions Data for England)
Authors: Walter Merlin , Zanini Nadir
Published: September 2023

ObjectivesTo provide a data owner’s perspective into the journey to create GRADE, an Ofqual-DfE-UCAS linked administrative dataset, and to make it available for independent research. Moving from the ethical principles underpinning the sharing of data and through multiple strands of the project, we will draw lessons to inform best practice.

MethodsAreas of research interest were used as drivers to define the content of GRADE. To ensure that research questions of relevance to both policy makers and scholars could be addressed, we established an advisory committee including key representatives of the statistical, research, and educational policy communities. Thanks to the collaboration with technical staff from participating organisations, the data was linked to ensure that students’ anonymised data could be tracked across different data sources. We then focused on supporting external research by producing metadata and supplementary documentation, as well as establishing independent funding provision for projects using the GRADE data.

ResultsThe internal research conducted was helpful to inform policy development and to test the data. The GRADE data was created and made available to external researchers. A data sharing framework was published to describe, at high-level, the content of the data and its potential use, as well as to set out how to access this rich source of micro-data. Detailed data specifications have been made available, alongside a low-fidelity synthetic version of the data.

Numerous research projects based on the GRADE data are currently underway and preliminary findings are already being disseminated. More research is being planned, based on an upcoming refreshed version of the GRADE data. Significant funding has been made available for external researchers to conduct independent work.

ConclusionCreating, combining, and sharing administrative data is not an easy task. Engagement with researchers and the wider community is necessary from the beginning of the project. It is a considerable investment, with potentially high returns, but also significant costs, and the output produced must align with policy and research priorities.
The UK Longitudinal Linkage Collaboration: A trusted research environment for the longitudinal research community
Authors: Boyd Andy , Flaig Robin , Oakley Jacqui , Campbell Kirsteen , Evans Katharine , McLachlan Stela , Thomas Richard , Turner Emma
Published: September 2023

ObjectivesOur Trusted Research Environment (TRE) provides a centralised infrastructure to pool Longitudinal Population Studies’ (LPS) data and systematically link participants’ routine health, administrative and environmental records. All data are held in a centralised research resource which is now certified by UK Statistics Authority as meeting the Digital Economy Act standard.

ApproachWe have created an unprecedented infrastructure integrating data from interdisciplinary and pan-UK LPS linked to participants’ NHS England records with delegated access responsibilities. Integrated and curated data are made available for pooled analysis within a functionally anonymous DEA and ISO 27001 accredited TRE. We developed a bespoke governance and data curation framework with LPS data managers and Public/participant contributors. New data pipelines are being built with partners at ADRUK and the Office of National Statistics to link non-health records. Our design supports long-term sustainability, linkage accuracy and the ability to link data at both an individual and household level.

ResultsThis organisation is a collaboration of >24 LPS with ~280,000 participants. Participants' data are linked to NHS records and geo-coded environmental exposures. This resource is now accessible for public benefit research for bona fide UK researchers. Administrative data including tax, work and pensions, and education are being added to the resource. This data flow is enabled by: (1) a model where TTP processes participant identifiers for many different data owners; (2) creation of a novel longitudinal data pipeline, enabling linkage, data extraction and update of records over time; (3) an access framework where Linked Data Access Panel considers applications on behalf of data owners (e.g., the NHS), with review by a Public Panel and distributing applications to LPS for approval of appropriate data use.

ConclusionOur organisation provides a strategic research-ready platform for longitudinal research. We are extending linkages of LPS participants to previously inaccessible datasets. The research resource is positioned to allow researchers to investigate cross-cutting themes such as understanding health and social inequalities, health-social-environmental interactions, and managing the COVID-19 recovery.
Renewable energy transition and the local economic development of lagging-behind regions: Evidence from the offshore wind energy industry in the UK
Authors: Vanino Enrico , Siddall Thomas , Rupp William
Published: September 2023

ObjectivesIn this study we analyse the potential impact of the renewable energy transition on the local economic development of lagging-behind regions, focusing in particular on the causal impact of offshore wind farms on the economic development of local onshore coastal communities in the UK, which are usually deprived left-behind regions.

MethodsWe consider the current impact of this transition on the economic development of places, analysing employment and productivity growth in local industries directly affected, as well as the magnitude of potential externalities along the supply-chain. Linking publicly available data on offshore wind farms, offshore wind suitability, and local economic outcomes, we develop an instrumental variable approach to address endogeneity, modelling the probability of wind farms’ locations based on offshore natural characteristics, such as water depth, distance to shorelines, and wind speed factors.

ResultsThis is the first study providing empirically robust analysis at a granular level on this topic. After mapping the location of offshore wind farms and link these to onshore local communities through the location of ports and other infrastructures servicing these farms, we estimate a significant positive effect on local employment and productivity growth in the offshore wind energy sector, as well as the indirect effect along the supply chain.

ConclusionThe rapidly growing renewable energy sector could become a key player in the local economic development of peripheral and lagging-behind regions. This could allow many peripheral regions across developed countries, once dependent on mature declining industries, to regenerate their local economies by sustainably transitioning towards new higher added-value green industries.
Education pathways to the labour market for 16-year-olds who struggle to achieve maths and English in General Certificate of Secondary Education
Authors: Gorman Emma , Thomson Dave , Urwin Peter , Min Zhang
Published: September 2023

We examine the post age-16 educational pathways taken by the 44% of young people who do not gain “good” grades in English and Maths at age 16 years. We then assess the causal effects of attending General Further Education (GFE) colleges on education and labour market outcomes for this group.

We use the Longitudinal Education Outcomes dataset, which comprises linked administrative education, employment and income records for the population of English school pupils aged 16 in 2011. To summarise complex post-16 education trajectories, we present Sankey charts stratified by indicators of disadvantage. We study the effects of attending GFE at age 17 on whether a pupil gains a Level 3 qualification by age 19, and their earnings and employment status at age 24. To estimate a causal impact, we use distance from home to the closest GFE college as an instrumental variable, controlling for a rich set of background characteristics.

Our graphical results highlight the complexity of post-16 educational pathways and transitions, which are differentiated by disadvantage. Over 50% have GFE as their first post-16 destination. Results from instrumental variable analyses show a positive association between attending GFE and gaining a Level 3 qualification by age 19, among pupils who do not gain a “good” pass in the General Certificate of Secondary Education (GCSE) in either English and/or Maths. Restricting analyses to the bottom of the distribution – those who gain an E, F or G grade in both English and Maths - we do not detect an impact of GFE on qualifications at age 19. Among both subgroups, we do not detect any impact of attending GFE on earnings and employment at age 24 years.

While the post-16 pathways taken by disadvantaged, lower-attaining pupils do increase qualification attainment for some, the value these have in the labour market appears limited. These results may indicate the importance of “soft-skills” and early employment experiences for this subgroup of lower-attainers.
Clinical coding of long Covid in Wales: A cohort study of 3.5 million people using linked health and demographic data
Authors: Abbasizanjani Hoda , Bedston Stuart , Robinson Lucy , Curds Matthew , Akbari Ashley
Published: September 2023

Objectives‘Long COVID’ (LC) is broadly defined as signs and symptoms that continue or develop after the acute phase of COVID-19, and can affect cardiovascular, respiratory and other organ systems. Using electronic health records, we investigated clinical coding of LC in primary and secondary care for the population of Wales.

MethodsWe conducted a cohort study for the population of Wales, using anonymised individual-level linked data in the Secure Anonymised Information Linkage (SAIL) Databank. We used the Welsh COVID-19 e-cohort (doi:10.1136/bmjopen-2020-043010), which consists of all people (adults and children) alive and resident in Wales from 1st January 2020. To this e-cohort we linked primary and secondary care, COVID-19 testing, and ethnic group data. We then calculated the proportion of people with a LC diagnosis code (in primary and secondary care data) overall and stratified by demographic variables.

ResultsOf 3.5m residents, 7,696 (0.2%) had a LC clinical diagnosis. Compared with the general population, a higher proportion of people with LC were female, middle age, white, and hospitalised within 28 days of a confirmed COVID-19 infection. LC affected all socioeconomic groups, as assessed using the Welsh Index of Multiple Deprivation. When looking at LC diagnosis codes in primary care, 30.9% of practices in SAIL have not used these codes at all. And the number of recorded events was low until the end of January 2021, after which there was an increase in coding. These findings are likely a substantial underestimate of LC prevalence in Wales. Earlier estimates from self-reported surveys, such as the Office for National Statistics, are much higher, ranging anywhere between 3-5%.

ConclusionLow recording rates of LC and variation between practices could be due to a delay in introducing clinical coding and lack of presentation/recording. Understanding prevalence of LC is vital for addressing the scale of the problem. Therefore developing additional data-driven approaches is necessary to obtain an accurate prevalence estimate.