International Journal of Population Data Science最新文献

{"title":"Gaps in Population Life Course Phenotype Trajectories Underlying Major Noncommunicable Diseases: A Scoping Review.","authors":"Katie McBain, Samuel Kasjan, Ryan Taylor, Dorothea Dumuid, Susan Clifford, Timothy Olds, Melissa Wake","doi":"10.23889/ijpds.v6i1.3346","DOIUrl":"10.23889/ijpds.v6i1.3346","url":null,"abstract":"<p><strong>Introduction: </strong>The life course phenotypic pathways leading to noncommunicable diseases (NCDs) provide information needed to plan and test preventive interventions. However, most NCD-relevant phenotypes are not routinely measured until diagnosis and their pre-clinical trajectories are therefore not in linked population datasets.</p><p><strong>Objectives: </strong>In the context of planning phenotypic collection waves in an Australian early and pre-midlife mega-cohort, we aimed to undertake (1) a scoping review to identify knowledge availability and gaps and (2) a comparative map of trajectories from available data.</p><p><strong>Methods: </strong>We searched PubMed and MEDLINE (September 2024) for trajectory studies on phenotypes underlying NCDs with the highest late life disease burden (excluding cancer and back pain, with no clear precursor phenotypes): cardiovascular, chronic obstructive pulmonary and kidney diseases, diabetes, falls, hearing and vision loss, and dementia. Eligible studies had ≥3 timepoints spanning ≥5 years in childhood or ≥10 years in adulthood. Using the R ggplot package, we fitted loess curves to create lifetime trajectory visualisations in absolute values and units standardised for comparison.</p><p><strong>Results: </strong>From 3770 abstracts, we included 36 studies. Most (n == 19) examined cardiovascular trajectories, collectively spanning ages 5-105 years for blood pressure. Ten studies reported cognition trajectories, but could not be synthesised due to measurement diversity. Twelve studies mapped lung, glucose, kidney or musculoskeletal phenotypes but with discontinuities at varying life stages. No studies tracked vision or hearing trajectories. Our syntheses confirmed some known trajectory patterns, such as peaking of musculoskeletal phenotypes in early adulthood and the rise in cardiovascular and glucose markers beyond healthy ranges from midlife.</p><p><strong>Conclusions: </strong>Our mapping confirmed expected patterns for some phenotypes, but highlighted significant gaps for others on pathways to high-burden NCDs. If long-running population cohorts collectively tracked all major phenotypes over time, embedded real-world or simulated trials could accelerate progress in prevention and treatment across all major NCDs.</p>","PeriodicalId":36483,"journal":{"name":"International Journal of Population Data Science","volume":"11 1","pages":"3346"},"PeriodicalIF":2.2,"publicationDate":"2026-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13494735/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148798989","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Co-creating an Inclusion, Diversity, Equity, and Accessibility (IDEA) Strategy in a Pan-Canadian Health Data Research Network.","authors":"Morgan Stirling, Laura Bowler, Jeffrey Morgan, David Yang, Lisa Nowlan, Kate Millberry, Kelli Buckreus, Jennifer Hagen, Jannath Naveed, Kim McGrail, Nathan Nickel, Amy Freier","doi":"10.23889/ijpds.v11i1.3429","DOIUrl":"https://doi.org/10.23889/ijpds.v11i1.3429","url":null,"abstract":"<p><p>Inclusion, Diversity, Equity, and Accessibility (IDEA) are increasingly recognised as essential to advancing population health research and addressing structural inequities. Yet, few publications describe how to develop IDEA strategies, leaving organisations with limited guidance on replicable processes. Here, Health Data Research Network Canada (HDRN Canada) details the steps it took to establish its own IDEA Strategy. The strategy was developed through an iterative five-phase process. Key steps included creating a project charter, defining shared governance and consensus-based decision making, and using professional facilitation to foster broad participation across member organisations. Visible executive sponsorship was critical to strategy development and implementation. The resulting strategy identifies four interconnected action areas: Learning and Unlearning, Facilitating IDEA in Research, Cultivating Trust and Reciprocity, and Providing Leadership and Advocacy to embed IDEA in organisational operations and research practices. HDRN Canada's experience demonstrates how a national distributed research network of organisations that work together to support multi-jurisdictional research can use best practices to transform IDEA principles into a concrete, actionable framework. This work offers a transferable model for population health research organisations seeking to integrate IDEA within their organisations and across the research ecosystem.</p>","PeriodicalId":36483,"journal":{"name":"International Journal of Population Data Science","volume":"11 1","pages":"3429"},"PeriodicalIF":2.2,"publicationDate":"2026-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13474194/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148763652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Understanding Inequalities in Adult Social Care in Wales: Protocol for the CARE Lab Linked Administrative Data Study.","authors":"Fiona Victoria Lugg-Widger, Ashley Akbari, Rebecca Cannings-John, Oliver S Cumming, Matthew Curds, Miranda Evans, José-Luis Fernandez, Henrietta Graham, Mala Mann, Melissa Meindl, Abigail Palmer, Lisa Trigg, Nell Warner, Paul Willis, Julie Wych, Simone Willis, Jonathan Scourfield","doi":"10.23889/ijpds.v11i1.3393","DOIUrl":"https://doi.org/10.23889/ijpds.v11i1.3393","url":null,"abstract":"<p><strong>Introduction: </strong>Adult social care in the UK faces increasing demand and persistent inequalities in terms of access and care quality, yet national-level understanding remains limited. The CARE Lab study aims to address these gaps using newly available individual-level routine administrative data for the whole of Wales from the Adults Receiving Care and Support (ARCS) census. This study will explore patterns of care provision, transitions from children's to adult services, and socio-demographic disparities, using linked data to inform service planning and policy.</p><p><strong>Methods: </strong>and analysis This quantitatively-led mixed-methods study comprises five research questions. Quantitative analysis will use ARCS census data, both standalone and linked to health, education, and social care datasets within the Secure Anonymised Information Linkage (SAIL) Databank. Qualitative interviews with people receiving care and support, carers, and professionals will contextualise findings. Key research questions address care patterns, demographic comparisons, regional variation, transitions from child to adult care, and the feasibility of evaluating care models using linked data. Statistical analyses will include descriptive and inferential statistics, propensity score matching, and there will be thematic analysis of qualitative data.</p><p><strong>Ethics: </strong>Ethical approval has been obtained from Cardiff University. Data access approvals will be sought from Welsh Government, SAIL, and the Office for National Statistics. Dissemination will occur through peer-reviewed publications, policy briefings, accessible multimedia outputs, and stakeholder engagement via an action group. The study will also produce a research-ready data asset and recommendations for future data infrastructure development across the UK.</p>","PeriodicalId":36483,"journal":{"name":"International Journal of Population Data Science","volume":"11 1","pages":"3393"},"PeriodicalIF":2.2,"publicationDate":"2026-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13492271/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148798939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Canadian Metadata Catalogue for Health Science Research.","authors":"Allan Garland, Peter Dodek, Kednapa Thavorn, Rita Wissa, Wendy Sligl, Wynona Marleau, M Elizabeth Wilcox","doi":"10.23889/ijpds.v11i1.3372","DOIUrl":"10.23889/ijpds.v11i1.3372","url":null,"abstract":"<p><strong>Introduction: </strong>While Canada is rich in databases useful to support healthcare research, they are widely distributed, often poorly documented, and it is challenging to identify relevant databases, apply for access, and eventually use, link or harmonise the data. Even if the databases needed to address specific questions are known, it is difficult and time-consuming to find the metadata, the \"data about the data\" required to understand the characteristics and data content of these resources. A solution to these challenges is creation of metadata catalogues, which detail metadata for multiple databases, not the actual data.</p><p><strong>Objectives: </strong>Describe a new catalogue including metadata about Canadian medical and non-medical databases' characteristics and variables, and information to assist catalogue users in seeking data access.</p><p><strong>Methods: </strong>Starting with a list of 385 national, provincial and regional databases, a group of physician-investigators, epidemiologists, data scientists and patient partners prioritised databases for inclusion. Metadata cataloguing occurred in steps: (i) description of the database with listing of its characteristics, and when available, (ii) addition of information about collected variables.</p><p><strong>Results: </strong>83 individual databases are documented in the Metadata Catalogue of the Sepsis Canada Network (https://www.maelstrom-research.org/network/sepsis). 57 are registries, 13 are cohort and 13 cross-sectional databases. 16 cover all of Canada, while another 13 cover most of the country; 45 focus on a single province. For 33 databases (38%) the catalogue includes detailed information about variables collected.</p><p><strong>Conclusions: </strong>This metadata catalogue includes databases collecting information spanning the continuum of medical care, non-medical data, and determinants of health. It is freely available online and extensively searchable. It can facilitate implementation of a wide range of research initiatives into medical conditions, medical care, and outcomes.</p>","PeriodicalId":36483,"journal":{"name":"International Journal of Population Data Science","volume":"6 3","pages":"3372"},"PeriodicalIF":2.2,"publicationDate":"2026-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13386634/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148550733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Child Health Research Using linked Multi-domain Canadian Administrative Data: A Scoping Review.","authors":"Yen My Vuu, Marcelo L Urquia, Lisa M Lix, Amani F Hamad","doi":"10.23889/ijpds.v11i1.3407","DOIUrl":"10.23889/ijpds.v11i1.3407","url":null,"abstract":"<p><strong>Introduction: </strong>Linked administrative data integrating health and non-health information can support population-based research about biological and contextual environmental factors that influence child health. Database linkage studies leverage existing data to provide more comprehensive information than would be available from any single source. However, it is unknown the extent by which child health studies capitalise on linked multi-domain Canadian administrative data.</p><p><strong>Objective: </strong>This scoping review aims to describe Canadian population-based child health studies that used linked multi-domain (i.e., health and non-health) administrative data.</p><p><strong>Methods: </strong>A systematic search was conducted of MEDLINE, Embase, Scopus and Global Health from inception until March 12, 2025. Articles were included if they focused on children (birth to 18 years), used Canadian administrative data, and linked health with non-health data. Two reviewers independently screened titles/abstracts and full texts; a pilot test ensured consistency. Article characteristics, province/territory, parental linkage, and non-health variables, were collected using an extraction form.</p><p><strong>Results: </strong>The search yielded 4,437 articles, of which 42 met inclusion criteria. Most articles were conducted in Manitoba (45%) and Ontario (36%). Maternal linkage was common, whereas paternal linkage was limited to Manitoba and British Columbia. Immigration status was the most common non-health variable. Health service use, particularly preventive care, such as screening and vaccination coverage, was a common research theme. No multi-jurisdictional studies were identified.</p><p><strong>Conclusions: </strong>Multi-domain administrative data linkage studies remain concentrated in a few provinces. Expanding parental linkage, integrating non-health variables, and strengthening multi-jurisdictional studies are crucial for improving population-based understanding of child health influences across Canada.</p>","PeriodicalId":36483,"journal":{"name":"International Journal of Population Data Science","volume":"11 1","pages":"3407"},"PeriodicalIF":2.2,"publicationDate":"2026-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13359102/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148438357","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exposure to Ambient Air Pollution and Onset of Dementia.","authors":"Babak Jahanshahi, Duncan McVicar, Neil Rowland","doi":"10.23889/ijpds.v11i5.3644","DOIUrl":"https://doi.org/10.23889/ijpds.v11i5.3644","url":null,"abstract":"<p><p>This study used Census data from Northern Ireland linked to administrative data on prescriptions between 2010 and 2016, to examine the association between ambient air pollution exposure and the risk of dementia onset. It contributes to this literature by providing new evidence in a comparatively low pollution context, using rich and nationally representative cohort data with comprehensive information on dementia disease medications dispensed over an extended period. We estimated Cox Proportional Hazards models for the association between pollution exposure and dementia onset as proxied by first receipt of dementia medication, controlling extensively for potentially confounding factors. Estimates are presented in the form of hazard ratios for the effect of long-term PM2.5 and NO2 exposure (define as 5-year moving average exposure in the primary model) on the risk of dementia onset. There was a clear unadjusted and adjusted association between long-term exposure to ambient pollution and the risk of developing dementia, with those experiencing higher exposures being at greater risk. There was evidence of a positive association with both PM2.5 and NO2 exposure for subsamples by age and sex with more tentative associations for those under 70 years of age. This study contributes to an emerging literature examining the association between ambient PM2.5 and NO2 pollution and onset of dementia. We found strong evidence for positive associations even in the relatively low-pollution context of Northern Ireland.</p>","PeriodicalId":36483,"journal":{"name":"International Journal of Population Data Science","volume":"11 5","pages":"3644"},"PeriodicalIF":2.2,"publicationDate":"2026-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13426819/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148654422","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From Collaboration to Impact: Insights from the DARE UK Community Building programme.","authors":"Najmeh Modarres, Elizabeth Waind, Katie Porter, Cassandra Gould Van Praag","doi":"10.23889/ijpds.v11i5.3733","DOIUrl":"https://doi.org/10.23889/ijpds.v11i5.3733","url":null,"abstract":"<p><p>How can effective community building transform a fragmented Trusted Research Environment (TRE) ecosystem into a connected, standardised one? And how can it elevate the work of data custodians, data scientists and others across the sector, while effectively involving the public? These are some of the questions Data and Analytics Research Environments UK (DARE UK) has explored as it reflects on the development of its community groups. DARE UK's community groups are collaborative initiatives that bring together partners from across the UK data research landscape to co-create work aligned with the DARE UK mission to establish a safe and collaborative UK network of Trusted Research Environments (TREs). Ahead of the 2026 IPDLN Conference, DARE UK has funded nine Interest Groups - open-ended groups focused on broad challenges within the scope of the DARE UK programme - and four Working Groups, which are short-term collaborative efforts typically linked to an Interest Group and focused on specific pieces of work. Six of these groups have now been active for over a year. In this session, we will share case studies from selected active community groups and lessons learned about what it takes to establish a community that can sustain and govern itself. We will discuss the processes involved in developing a charter and code of conduct, defining what a successful community looks like, determining effective funding models based on our experience, and most importantly, meaningfully engaging and involving the public throughout.</p>","PeriodicalId":36483,"journal":{"name":"International Journal of Population Data Science","volume":"11 5","pages":"3733"},"PeriodicalIF":2.2,"publicationDate":"2026-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13426670/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148654445","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advancing Equity, Diversity, and Inclusion in Data Research: Insights from a PEDRI Cross-Sector Roundtable.","authors":"Samaira Khan, Doreen Tembo, Katie Porter, Cassie Smith","doi":"10.23889/ijpds.v11i5.3606","DOIUrl":"https://doi.org/10.23889/ijpds.v11i5.3606","url":null,"abstract":"<p><p>Persistent inequities in research datasets mean that marginalised communities are routinely under-represented. Engagement practices often unintentionally exclude the very groups most affected by data-driven decisions, while organisations frequently lack the training, resources, or guidance needed to address these gaps. Together, these issues risk reinforcing structural inequities and undermining the quality, relevance, and public trust of data research. To respond to these challenges, PEDRI convened a cross-sector roundtable in September 2025, bringing together twenty researchers, engagement practitioners, inclusion specialists, and public contributors to identify practical strategies for embedding EDI throughout the research lifecycle. Participants identified several critical barriers: exclusionary engagement practices, over-reliance on the same communities, inconsistent data collection standards, lack of funding for Public Involvement and engagement and insufficient EDI training for researchers and data managers. The group identified a range of solutions rooted in intersectional approaches and the need to embed meaningful public involvement at every research stage. Priority actions included expanding PEDRI's Resources Hub with tailored EDI guidance, strengthening its convening role, and working with partners across the sector nationally and internationally to connect researchers with diverse communities, reduce engagement burden, and align sector-wide EDI and PIE priorities. This presentation will share concrete findings, cross-sector solutions, and priority actions arising from the roundtable. By placing inclusion at the heart of data research, we can build not only better datasets, but a fairer, more trustworthy research ecosystem that serves all communities.</p>","PeriodicalId":36483,"journal":{"name":"International Journal of Population Data Science","volume":"11 5","pages":"3606"},"PeriodicalIF":2.2,"publicationDate":"2026-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13426833/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148654452","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Feasibility research into using administrative data sources to produce multimorbidity scores for predicting general health statistics for England.","authors":"Tolu Adedire, Wajiha Munir, Charlotte Standeven, Matthew Minifie","doi":"10.23889/ijpds.v11i5.3495","DOIUrl":"https://doi.org/10.23889/ijpds.v11i5.3495","url":null,"abstract":"<p><p>The current primary measure of general health in England relies on census and survey data, which are limited in timeliness and granularity. Developing an administrative data-based indicator offers the potential for more frequent, detailed insights to support research and policy. This paper sets out research to develop and evaluate a multimorbidity score derived from linked administrative health datasets, combining National Health Service (NHS) hospital records, NHS General Practice data, and the Office for National Statistics' death registrations, which are then joined to census information for residents of England. Moving beyond simple counts of conditions, or prescriptions, the multimorbidity score provides a structured measure of the burden and complexity of chronic illnesses at the individual level. We explore using this score as a key predictor of health-related outcomes, including self-reported general health status. Machine learning models were trained to predict the general health status responses from the 2021 Census. Given the subjective nature of census responses, we considered exposures on clinical indicators, healthcare utilisation metrics, demographic factors, social factors, and lifestyle factors. To ensure robustness, we experimented with multiple modelling approaches, including tree-based algorithms and regression-based methods, comparing their predictive performance across evaluation metrics. Model performance was assessed on an independent subsample using multiple evaluation metrics, and predicted probabilities were aggregated to produce breakdowns by key characteristics, which were compared against observed values. Finally, the paper considers the feasibility of generating a time series from 2015 onwards and discusses potential applications and limitations of these estimates for producing broader health-related statistics.</p>","PeriodicalId":36483,"journal":{"name":"International Journal of Population Data Science","volume":"11 5","pages":"3495"},"PeriodicalIF":2.2,"publicationDate":"2026-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13426755/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148654458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AD-ARC (Administrative Data - Agricultural Research Collection): Linking Farms to Individual, Household and Business Data to create a Research-Ready Dataset for ADR UK.","authors":"Nathan O'Connor, Beth Allen, Esther Lewis, Sarah Cummins, Sian Morrison-Rees","doi":"10.23889/ijpds.v11i5.3682","DOIUrl":"https://doi.org/10.23889/ijpds.v11i5.3682","url":null,"abstract":"<p><p>The aim of this project was to produce a complete record of farms in England to be linked to individual, household and business data, enabling the creation of a de-identified research-ready dataset (RRD) of farming individuals, households and businesses in England. Following lessons learned from the first phase of this project, a 'farm spine' was created using two farms data sources, 2021 June Survey of Agriculture and Horticulture and 2020-2022 Rural Payments Agency subsidy payment information. This spine utilised address and contact information at individual, farm holding, and business level, enhancing the matching potential when linking to census and business data. Deterministic linkage methods were used to match farms with associated households and businesses. The varied and nuanced nature of the data sources meant a non-standard approach was required when structuring the data for linkage, as well as ongoing feedback and collaboration between stakeholders to best deliver an optimised, high-quality bespoke dataset. The resulting dataset links geographic and farm activity data, subsidy payments, business ownership and turnover information, and characteristics of farming households. This presentation includes details of the data preparation, challenges encountered, and solutions utilised at each stage of building this complex dataset. To our knowledge, the AD|ARC RRDs are the first datasets linking agricultural data to individual and household-level data at a population level. They provide an invaluable resource that will inform policymakers seeking to support agricultural and rural communities. Its multi-organisational approach and use of varied data sources highlight lessons learned for future data linkage projects.</p>","PeriodicalId":36483,"journal":{"name":"International Journal of Population Data Science","volume":"11 5","pages":"3682"},"PeriodicalIF":2.2,"publicationDate":"2026-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13426674/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148654467","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}