Introduction: This data note describes the collection and linkage of participant’s Sainsburys shopping data into the Avon Longitudinal Study of Parents and Children (ALSPAC). Methods: Data were collected via informed participant consent and Subject Access Requests under UK GDPR, securely transferred and integrated into the ALSPAC database using unique study identifiers. Participant consultation and a technical pilot ensured transparent, acceptable, and secure linkage. Results: The dataset contains anonymised transactions for 244 participants, covering 658,375 item purchases between July 2014 and February 2024. Transactions include an item description, price, quantity, time, date, store location, and other variables. Items fall into 82 categories (e.g., produce) and 1002 subcategories (e.g., bananas). In terms of representativeness, the cohort is skewed towards females, consists of participants of similar age, and is predominantly made up of individuals with higher educational attainment and of White ethnicity. Conclusion: The linkage of shopping records complements ALSPACs extensive existing dataset, which comprises over 30 years of sociodemographic and health-related data. The linkage stands as a novel opportunity for future research into dietary habits, nutritional intake, and subsequent health outcomes. Access to data may be granted to approved researchers upon reasonable request, following a proposal submission through the ALSPAC website (http://www.bristol.ac.uk/alspac).

The UK Longitudinal Linkage Collaboration: the Trusted Research Environment for data linkage in longitudinal population research We have created an unprecedented interdisciplinary infrastructure integrating data from UK-wide LPS linked to participants’ health (NHS), administrative (DWP, HMRC) and place-based records (e.g. environmental pollutants, proximity to healthy assets). Researchers can apply to access all these data via a single application. This organisation is a collaboration of over 25 of the UK’s most established LPS with over 425,000 participant records. With new LPS joining, the resource will comprise more than 2 million linked participant’s records by 2027. The UK LLC enables integrated and curated data for pooled analysis within a functionally anonymous Digital Economy Act and ISO 27001 accredited TRE. Initially this resource was only available to UK researchers, will be open to international researchers in 2026. This data flow is enabled by: (1) a model where a Trusted Third Party 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 a 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. UK LLC provides a simple-to-access strategic research-ready platform for longitudinal research to investigate cross-cutting themes such as understanding health and social inequalities, health-social-environmental interactions. The greater availability of large scale, diverse linked data will help provide the numbers for researchers to study rarer outcomes and seldom-reached populations.

Introduction: Shopping data offer detailed, objective records of diet and lifestyle habits, providing a valuable but under-used resource for health research. While willingness to share personal data has been widely studied, no previous research has directly compared stated willingness with subsequent actual data sharing within the same cohort. Understanding whether willingness predicts actual consent, and how this varies by sociodemographic characteristics, motivations, and barriers, is essential to improve recruitment strategies and the representativeness of collected data. Methods: We employed a mixed-methods approach using the Avon Longitudinal Study of Parents and Children (ALSPAC). Quantitative analyses combined sociodemographic variables with responses from a 2018 survey assessing willingness to consent to shopping data linkage and outcomes from a 2023 loyalty card consent campaign. These were complemented by semi-structured interviews in 2019 exploring attitudes towards sharing shopping data. Results: In 2018, 60.7% of participants indicated willingness to share shopping data (n = 2142, 9230 invited). In 2023, actual consent—requiring provision of loyalty card details for five UK retailers (Sainsbury’s, Tesco, Boots, Morrisons, and Coop)—was obtained from 511 of 6170 invited participants. Demographic characteristics were broadly comparable across samples. Stated willingness was associated with higher odds of actual consent (adjusted OR = 1.48, 95% CI: 1.16–1.90), indicating that willingness is a meaningful predictor of subsequent data sharing. Sociodemographic characteristics and motivations (e.g., societal benefit, scientific interest) showed modest associations with both willingness and consent and moderated the willingness–consent relationship. Interviews reinforced the importance of trust in ALSPAC and clear communication about data use, while highlighting privacy concerns as minor barriers. Conclusion: This study provides the first within-cohort evidence that willingness to share shopping data predicts subsequent data sharing, albeit imperfectly. Willingness surveys can therefore inform recruitment planning, but additional strategies are required to improve realised consent rates. Addressing practical barriers, clarifying data use, and highlighting societal and scientific benefits may help narrow this gap; Targeted engagement, including through informative materials and outreach events, may help to reach groups less likely to consent. These insights can inform data collection in longitudinal cohorts and wider population samples.

The Twins Early Development Study (TEDS) is a longitudinal population study of over 10,000 twin pairs born in England and Wales between 1994 and 1996. As the twins enter their thirties, a primary focus of TEDS is to better understand the development of common physical and mental health problems and the relationship with the different social milestones of adulthood (e.g., employment, partnerships, and/or parenthood). With over 30 years of prospectively collected questionnaire and genetic data, the study is uniquely placed to answer questions about the health challenges facing young adults today. Incorporating linked medical records with the existing research data will provide a different data perspective on our twin's health status and outcomes and support more equitable research by helping to address both response and attrition bias. This article provides an overview of the protocol to link TEDS participants to electronic health records collected by the UK National Health Service (NHS). It will outline the linkage process, characterize the available linked study sample and NHS datasets, and describe the legal basis for this work.

Large language models (LLMs) and agents are now widely used tools in code development, with data typically sent to third-party cloud-based models. Their adoption in research using personal data is constrained by governance requirements that typically prohibit data transmission to external services. Locally deployable open-weight models offer an alternative since sensitive data never leave the local environment. We introduce an open-source framework for evaluating the efficacy of AI agents powered by open-weight LLMs on one of the most persistent bottlenecks in research on longitudinal population studies: data preparation. The framework comprises: a curated ground-truth dataset (cleaning scripts preparing six sweeps of data from a British cohort study), task definitions encompassing tasks such as category harmonization and multi-wave merging, and automated routines for evaluating the LLM-produced R code and outputted data. We benchmark LLMs across the (consumer grade) deployment spectrum to assess their efficacy in 20 data preparation tasks (creation of 102 variables). Current state-of-the-art, 31-35B parameter models almost saturated our benchmark ('average task completion' up to 87.9

BACKGROUND:Psychosocial factors are argued to increase cancer risk. This study aims to clarify the association between various psychosocial factors and cancer incidence (including breast, lung, prostate, and colorectal cancers) via individual-participant data (IPD) meta-analysis. The psychosocial factors considered were perceived social support (PSS), loss, relationship status, neuroticism, and general distress. METHODS:The Psychosocial Factors and Cancer Incidence consortium used data from 22 cohorts with a measure of at least one psychosocial variable of interest at baseline (up to N = 421,799; cancer incidence, N = 35,319; person-years of follow-up, N = 4,378,582). In stage 1 of the IPD meta-analysis, Cox regression models were used with age as the timescale. In stage 2, results were pooled in random-effects meta-analyses. RESULTS:No psychosocial factors were associated with an increased risk of overall cancer and with breast, prostate, and colorectal cancers, as well as with cancers with alcohol as a common potential causal factor. PSS, currently not in a relationship, and a loss event were associated with an increased risk of lung cancer (hazard ratio [HR], 1.09-1.55). Estimates decreased for PSS and relationship status when adjusting for several known risk factors, such as a family history of cancer (HR, 1.05-1.08). Similar findings were observed for relationship status and cancers with tobacco smoking as a common potential causal factor. CONCLUSIONS:For most types of cancer, psychosocial factors (measured at a single point in time) were not associated with increased risk. PSS, currently not in a relationship, and loss were associated with an increased risk of lung cancer, although most effects attenuated when adjusting for several known risk factors.

The Science Academies of the Group of Seven (G7) nations’ have identified an urgent need for a principles-based governance framework to support the research use of data. In response, the Pan-UK Data Governance Steering Group of the UK Health Data Research Alliance has developed the “GUARDS” principles: a set of high level, enduring and globally relevant principles with public input. The GUARDS require that research using data about people must be: Guided by public and professional stakeholders, Understandable and transparent, Aligned in using common tools, forms, contracts and accreditation standards, Responsible in meeting ethical requirements and delivering equitable outcomes, and must Deliver public good in times of crisis, with recognition of data Stewardship as a distinct profession needed to ensure the appropriate use of data. The GUARDS principles sit alongside the internationally recognised “Five Safes”, together forming “SafeGUARDS”. Within this, the Five Safes effectively inform decision making needed to balance data utility and confidentiality, and the GUARDS inform decision making about broader principles relating to involvement, transparency, equity and responsible data use. Collectively, we intend the principles to support the “Social Licence” to operate with the pressing need to unlock the potential held in rich, linkable datasets. Each of the GUARDS has associated “aspirations” for organisations to use as examples of how to turn the principle into action. Further international discussion will be needed to develop the SafeGUARDS, driving consistency and harmonisation and facilitating trustworthy and fair research to address global issues.

IntroductionFetal alcohol spectrum disorder (FASD) affects an estimated 1.8–3.6% of UK school children and up to 27% of children in care. FASD remains vastly under-diagnosed and under-recorded in UK electronic patient records (EPRs), leading to significant challenges for individuals with the condition. In 2024, we developed new SNOMED clinical terms aligned to UK national guidelines and quality standards for FASD.AimsThrough collaborative knowledge mobilisation (KM), we aimed to: i) raise awareness of the importance of utilising these new clinical terms; ii) identify barriers to FASD code usage in primary care EPRs; iii) co-develop creative communication materials and dissemination strategies.MethodsWe engaged with stakeholders (N = 18) including paediatricians, general practitioners, wider health professionals, data specialists, third-sector representatives, and researchers, through a workshop and individual meetings. Individuals living with FASD provided their perspectives on the importance of recognising FASD in EPRs, for inclusion in communication materials.ResultsWe co-produced free, publicly available creative communication materials including an animation, infographics and social media images. Materials focus on raising awareness of new SNOMED clinical terms for FASD, address stakeholder reported barriers to clinical coding, and provide actionable recommendations to improve clinical coding for FASD within primary care electronic records, and diagnostic services. We promoted these materials through social media platforms, a press release, conference presentations, and an editorial.DiscussionOur collaborative KM work provides an exemplar for developing materials with the aim of supporting improved clinical coding in EPRs. Further work is required to maximise and evaluate the impact of our materials.

This data note describes the linking of records of the Bristol Self Harm Register with the cohort of the index children of the Avon Longitudinal Study of Parents and Children (ALSPAC – also known as ‘Children of the 90s’). These records were obtained from the computerised data base maintained by the Bristol Self Harm Register (BSHR). The BSHR is operated out of the two largest NHS trusts in the ALSPAC study catchment area, North Bristol NHS Trust (NBT) based at Southmead Hospital (SMH) in Bristol and the University Hospitals Bristol and Weston NHS Foundation Trust (UHBWT) based at Bristol Royal Infirmary (BRI), also in Bristol. The BSHR database was designed to be populated by staff after an encounter with a patient attending with an indication of self-harm. Some of the information in the BSHR database was self-reported by the patient and was unable to be independently verified. Software syntax was written using STATA (StataCorp LLC, version 17) to convert the original files into a single consistent format in a data base which was reviewed for its potential use in future research. The cleaned BSHR records provide a contemporaneous record of a subset of the ALSPAC cohort over a period of the ALSPAC study in an easily accessible format, which is valuable when other sources of data may be missing.

UK-wide Longitudinal Population Studies (LPS) have been brought together and linked to NHS, socioeconomic records and environmental data within a Trusted Research Environment. To ensure compatibility with data processing, access and to enable public good research we needed to develop a way to assess the legal basis of LPS. With NHS England, we co-developed key criteria for assessing common law duty of confidentiality. A framework was developed for assessing information provided to participants. The framework focused on compatibility with our research purpose (for public good), data processing, and data access. Template documents were produced to capture communications and key statements providing evidence relating to the criteria. A risk-based approach was adopted and a Confidentiality Due Diligence Panel recruited and trained University Data Protection Officer, Governance leads, cross-disciplinary academic representation and members of the public recruited to the Panel). The framework was formalised and documented, guidance, risk-assessment approach and outputs agreed with NHS England. 27 UK-LPS have completed the assessment. NHS England is sharing the framework as a model of best practice, and we will scale this approach through an open UK-wide call for new partner LPS in 2026. Co-development and implementation of a review framework for common law basis enabled robust and reproducible assessment of multiple LPS consent, information and communications materials. This allowed identification of LPS which have set reasonable expectations or advise on alternative legal permissions, and communications to enable record linkage in-line with participants wishes.

UK Longitudinal Linkage Collaboration (UKLLC) is the national Trusted Research Environment (TRE) for record linkage in longitudinal research, partnering with SeRP and >20 Longitudinal Population Studies (LPS). Participating in LPS is rewarding, with many participants enrolling into multiple studies (e.g., ∼8% of ALSPAC mothers are also enrolled into UK Biobank). It's scientifically important to account for this in pooled and meta LPS analysis as most statistical assessments assume independence of sample membership. Currently, LPS records are treated separately, leading to potential duplication and over-counting of exposures/outcomes in research, where individuals participate in multiple cohorts. We used probabilistic record linkage to identify individuals across multiple cohorts. We engaged study Data Managers through a consensus-building workshop to reconcile governance issues. Of ∼570,000 participants from 22 partner LPS in UKLLC, we've currently identified 4,785 individuals in two cohorts, 155 in three, and <10 in four. These numbers are likely to increase as UKLLC scales to support larger studies (with an anticipated 2m participants hosted by 2027). Mappings of individuals belonging to multiple cohorts were delivered to end-users via our data provisioning pipeline in a manner compatible with the dynamic nature of the pooled UK LLC hosted sample. This linkage will support accurate pooled- and meta-analysis within UKLLC. Ensuring the governance challenges are accounted for is essential for the acceptability of our community LPS governance framework. Extending this linkage of individuals across different LPS and platforms (e.g., to UK Biobank) will be necessary for robust federated analysis across TREs.

This data note describes the linking of records of the Bristol Self Harm Register with the cohort of the index children of the Avon Longitudinal Study of Parents and Children (ALSPAC – also known as ‘Children of the 90s’). These records were obtained from the computerised data base maintained by the Bristol Self Harm Register (BSHR). The BSHR is operated out of the two largest NHS trusts in the ALSPAC study catchment area, North Bristol NHS Trust (NBT) based at Southmead Hospital (SMH) in Bristol and the University Hospitals Bristol and Weston NHS Foundation Trust (UHBWT) based at Bristol Royal Infirmary (BRI), also in Bristol. The BSHR database was designed to be populated by staff after an encounter with a patient attending with an indication of self-harm. Some of the information in the BSHR database was self-reported by the patient and was unable to be independently verified. Software syntax was written using STATA (StataCorp LLC, version 17) to convert the original files into a single consistent format in a data base which was reviewed for its potential use in future research. The cleaned BSHR records provide a contemporaneous record of a subset of the ALSPAC cohort over a period of the ALSPAC study in an easily accessible format, which is valuable when other sources of data may be missing.

Background Researchers can apply to UK Longitudinal Linkage Collaboration (UK LLC) to access Longitudinal Population Study (LPS) data linked to health, non-health administrative and geo-environmental data. This paper describes the protocol for the "UK LLC Citizen Panel": a new method of incorporating a diverse public in decisions about the acceptability and suitability of the UK LLC data access process. The UK LLC Citizen Panel aims to embed public feedback and perceptions into UK LLC's data access process design and decision-making. Methods The UK LLC Citizen Panel will be created through a two-stage co-design process. Stage 1: UK LLC will identify and invite a public Steering Group to co-design the work of the Citizen Panel. The Steering Group will include public contributors from UK LLC's Public Involvement Programme and participant representatives from partner LPS. Stage 2: the UK LLC Citizen Panel will comprise participants of partner LPS and seldom-heard groups, primarily recruited via third sector organisations. The Panel will review the data access process during several online and in-person meetings. Findings will be analysed using thematic analysis and disseminated to UK LLC partner organisations, third sector organisations working with minority communities and young people under-represented in longitudinal studies, and networks of the Universities of Edinburgh and Bristol. Discussion The UK LLC Citizen Panel is a novel methodological approach that aims to consider a diverse public view of the use of a Trusted Research Environment to provide access to LPS data linked to health, non-health administrative and geo-environmental data. This diversity complements the existing public involvement in decision-making in all UK LLC data access and enables populations that are rarely heard in such decision-making to participate in and review the UK LLC data access process.

This scoping review explores the use of longitudinal population data linked to administrative data to further our understanding of the characteristics and outcomes of children involved in children’s social care (CSC) services within the UK. We searched eight electronic databases (Web of Science, SSCI, APA PsychInfo, Pubmed, Embase, Scopus, CINAHL Ultimate, ASSIA) to identify relevant publications between 1 January 2000 and 22 July 2025. Despite the UK’s longstanding investment into longitudinal population studies, published studies have been limited to four populations that have been linked to CSC records. Around a third of the published studies (6/16) relied on a single local authority-based population (Avon Longitudinal Study of Parents and Children). The publications demonstrated links between parental and early childhood characteristics and subsequent involvement in CSC. Few publications examined longer-term outcomes, the wider family and the effectiveness of interventions. Data linkage has the potential to improve our understanding across services, including health, education, justice and welfare systems, for children involved with social care services. Upcoming work using electronic data such as the Born in Bradford’s Better Start study show promise in producing more integrated insights. Importantly, while this review focuses on the UK, the lessons learned and the value of linking LPS and administrative data are highly relevant in international contexts where similar data assets exist. The review highlights the opportunities of data linkage to improve our understanding of the circumstances and experiences of young people and their families who are involved in the social care system.

IntroductionFollowing the acute phase of the COVID-19 pandemic, a record number of people became economically inactive in the UK. We investigated the association between coronavirus infection and subsequent economic inactivity among people employed pre-pandemic, and whether this association varied between self-report versus healthcare recorded infection status.MethodsWe pooled data from five longitudinal studies (1970 British Cohort Study, English Longitudinal Study of Ageing, 1958 National Child Development Study, Next Steps, and Understanding Society), in two databases: the UK Longitudinal Linkage Collaboration (UKLLC), which links study data to NHS England records, and the UK Data Service (UKDS), which does not. The study population were aged 25-65 years between April 2020 to March 2021. The outcome was economic inactivity measured at the time of the last survey (November 2020 to March 2021). The exposures were COVID-19 status, indicated by a positive SARS-CoV-2 test in NHS records (UKLLC sample only), or by self-reported measures of coronavirus infection (both samples). Logistic regression models estimated odds ratios (ORs) adjusting for potential confounders including sociodemographic variables and pre-pandemic health.ResultsWithin the UKLLC sample (N = 8,174), both a positive SARS-CoV-2 test in NHS records (5.9% of the sample; OR 1.08, 95%CI 0.68-1.73) and self-reported positive tests (6.5% of the sample; OR 1.07, 95%CI 0.68-1.69), were marginally and non-significantly associated with economic inactivity (5.3% of the sample) in adjusted analyses. Within the larger UKDS sample (n = 13,881) reliant on self-reported ascertainment of infection (6.4% of the sample), the coefficient indicated a null relationship (OR 0.98, 95%CI 0.68-1.40) with economic inactivity (5.0% of sample).ConclusionsAmong people employed pre-pandemic, testing positive for SARS-CoV-2 was not associated with increased economic inactivity, although we could not exclude small effects. Ascertaining infection through healthcare records or self-report made little difference to results. However, processes related to record linkage may introduce small biases.

Introduction & Background UK Longitudinal Linkage Collaboration (UK LLC) is the national Trusted Research Environment (TRE) for the longitudinal research community. UK LLC works in collaboration with many of the UK’s most established Longitudinal Population Studies (LPS) to support the linkage of participants’ study data with health, socio-economic and environmental records; and by providing researchers with access to integrated and linked study data. Objectives & Approach To develop linkages with digital footprints data within a national TRE that hosts data for over 20 LPS. We describe the methodological development implemented to facilitate the linkage of emerging sources of data with LPS databanks in a privacy-preserving manner. These linked datasets will support research for public good and help to inform policy decisions for improved health and wellbeing. Relevance to Digital Footprints UK LLC’s starting point for linking digital footprints data to longitudinal research is with geospatial data. Linkage with geospatial data builds upon longstanding activity within the partner studies, meaning that some of the challenges have already been identified and foundations already built. There are many openly available datasets that provide valuable indicators characterising participants’ built and social environment. Results Some of the first use cases for UK LLC are the ‘Access to Healthy Assets and Hazards’ (AHAH) index (Consumer Data Research Centre) and Energy Performance Certificates (EPC). AHAH can complement existing studies and linked records adding important co-variates on ‘hazards’ such as access to alcohol, fast food and gambling outlets, and ‘assets’ such as leisure services, GP services and green space. Meanwhile, EPC records can be linked at household level to investigate the health impact of energy deprivation and housing quality. Conclusions & Implications Linking together longitudinal population data and digital footprints data is in its infancy and raises concerns relating to disclosure risk management. UK LLC uses a decision-making framework which acknowledges that anonymisation is heavily context-dependent, and only by considering both the data and their environment as a whole can we come to a well-informed decision about what controls are needed. UK LLC’s work can contribute towards developing a mechanism for linking digital footprints data into longitudinal research resources. Central to this linkage is the maintenance of participant trust, co-creation and public involvement.

Background:Linking digital footprint data into longitudinal population studies (LPS) presents an opportunity to enrich our understanding of how digitally captured behaviours relate to health traits and disease. However, this linkage introduces significant methodological challenges that require systematic exploration. Objectives:To develop a robust framework for successful digital footprint linkage into LPS, informed by discussions from a workshop from the Digital Footprints Conference 2024. Methods:We propose a structured, four-stage framework to facilitate successful linkage of digital footprint data into LPS: (1) understand participant expectations and acceptability; (2) collect and link the data; (3) evaluate properties of the data; and (4) ensure secure and ethical access for research. This framework addresses the key methodological challenges identified at each stage, discussed through the lens of two LPS case studies: the Avon Longitudinal Study of Parents and Children and Generation Scotland. Results:Key methodological challenges identified include privacy and confidentiality concerns, reliance on third-party platforms, data quality issues like missing data and measurement error. We also emphasize the role of trusted research environments and synthetic datasets in enabling secure, privacy-sensitive data sharing for research. Conclusions:While the linkage digital footprint data to LPS remains in early stages, our framework provides a methodological foundation for overcoming current challenges. Through iterative refinement of these methods there is significant potential to advance population-level insights into health and wellbeing.

There is growing interest in incorporating the timing of place-based exposures into administrative health data to examine the impacts of the home environment on population health. We compared the accuracy of three methods for estimating the timing of changes in Lower Super Output Areas (LSOA; geographical output areas with around 400 and 1,200 households) in deidentified hospital records against self-reported address in cohort studies. In hospital records, addresses are updated after patients move to a new address when they next used health service. We compared three approaches to ascertain periods of time where individuals were staying at a particular address: 1) inferring the end date of the current address as the start date of the next reported address minus 1 day (N-1 method); 2) using median date between current and next start date as the end date for current address, and update the start date for the next address (Median method); 3) generating address end dates as a function of beta distribution between current and next start dates (random method), assuming that most people update their addresses not too long after they moved. We compared LSOA derived from addresses recorded in the UK Longitudinal Linkage Collaboration cohorts (Cohort, n = 40,963) with linked hospital records (NHSD, n = 40,102) from Jan 1989 to Apr 2023. Cross-sectionally, 39,216 (95.7%) Cohort members had at least 1 matching LSOA reported in both Cohort and NHSD data. Of the matching LSOA, 47% of the NHSD recorded the same LSOAs dated two years before or after Cohort recorded dates. All three methods correctly represented around 78% of each individual’s LSOA across the period, with negligible differences across methods. A number of approaches are available for ascertaining timing of address changes in administrative data, with similar levels of accuracy. Researchers should consider assumptions and implications of each method, and if possible, formally test and justify their approach for processing dates recorded in administrative records.