International Journal of Population Data Science最新文献

Introduction: The Health Informatics Centre (HIC) is a regional Scottish Safe Haven dedicated to secure data management, ensuring its integrity, confidentiality, and availability through a robust information governance framework.

Methods: As a data processor, HIC is responsible for the secure curation, storage, and provision of research data extracts. Research-ready data are made available to approved researchers via our customisable cloud Trusted Research Environment (TRE).

Results: The available granular data spans over 20 years, includes 2.1 million of the Scottish population, and HIC offers more than 170 datasets, with the most commonly used published with a digital object identifier. Data sources include clinical, hospital, laboratory, imaging, and research datasets which can be linked to new, and existing datasets. The data is quality-assured and released as project-specific extracts, ensuring robust privacy protection and research readiness. HIC's infrastructure is secure-by-design and supports high-performance computing, advanced data analytics, and is customisable to researcher's needs.

Conclusion: HIC has a long history of supporting a wide range of data-led research projects as a trusted and capable partner. At the time of publication 175 projects across academia, the NHS, and public sector organisations are active within HIC. Through adaptability, innovation and investment in people and infrastructure we have established a sustainable model which will continue to meet future needs and demands from world-leading research with sensitive data.

Objectives: Children and youth with special health care needs (CYSHCN) often require ongoing care, which can be an immense undertaking for their families. To provide a short-term break, families may obtain respite services, however, respite care may not be accessible or available to those who need it. The study objective was to identify demographic, socioeconomic, and health-related characteristics associated with receipt of respite services among families of CYSHCN in Manitoba.

Methods: Using a retrospective cohort design, a population-based cohort of CYSHCN (0 to 17 years old) (N=14,759) residing in Manitoba between 2013 and 2018 was defined using provincial-level administrative data (hospital, medical claims, education, disability services). Most of the cohort members (95.9%) were linked to their mother. We used multivariable logistic regression to determine the demographic, economic, and mental and physical health characteristics of the CYSHCN, their mothers, and siblings significantly associated with receipt of respite services. Additionally, the types of respite services received, and public funding dispersed for respite services during the study period were assessed.

Results: Less than one-quarter of families of CYSHCN (24.2%; 3,413) received at least one respite service. Among families who received respite, receipt was evenly distributed across neighbourhood-level income. However, the odds of receiving respite was lower in low income neighbourhoods (Q1: OR = 0.53, 95% CI [0.46, 0.61]; Q2: OR = 0.85, 95% CI [0.74, 0.98]). Of mothers in families that did not receive respite, 48.8% were diagnosed with a mental health disorder, and 60.8% had a physical health condition. Receipt of respite services was significantly associated with mothers' age (OR=1.05, 95% CI [1.04, 1.05]) and marital status (OR=1.71, 95% CI [1.57, 1.86]). Half (52.0%; 14,190) of all respite service records were attributed to self-managed services.

Conclusions: Many families of CYSHCN in Manitoba are not receiving publicly funded respite services. Our results suggest there are inequities in these services as respite was lower among families residing in economically disadvantaged neighbourhoods. Caring for a CYSHCN and accessing respite services (or not) may affect mothers' mental and physical health, particularly for families doing self-managed respite. Efforts and policy review are needed to address the limited and inequitable receipt of respite services for Manitoba families of CYSHCN.

Introduction: Amid growing global concern about child and adolescent mental health problems and their long-term consequences, research in this area is increasingly critical. Population-representative datasets are valuable resources for addressing these challenges. The Mental Health of Children and Young People (MHCYP) 2017 survey was designed to meet this need in England.

Methods: The 2017 survey included 9117 children and young people aged 2 to 19 years. Information was collected from parents or carers (hereafter referred to as 'parents'), and for those aged 11 years or over, directly from the young people themselves, as well as from teachers. The baseline assessment used the standardised Development and Wellbeing Assessment (DAWBA), based on ICD-10 and DSM-5 diagnostic criteria. The subsequent waves in 2020, 2021, 2022 and 2023, measured mental health difficulties using the Strengths and Difficulties Questionnaire (SDQ).

Results: The MHCYP 2017 survey and its follow-up waves provide population-representative data on children and adolescents in England, encompassing a range of mental health disorders and difficulties-from eating disorders and attention and hyperactivity disorder to depression and anxiety, with longitudinal data on mental health, social situation and activities during the Covid-19 pandemic. It builds on earlier UK representative surveys conducted in 1999 and 2004.

Conclusion: Togetherwith the 1999 and 2004 surveys, this dataset offers a unique opportunity to investigate trends in mental health disorders among young people, assess associated difficulties and comorbidities, and explore links with socio-economic factors. The MHCYP 2017 survey and follow-ups offer valuable cross-sectional data for understanding child and adolescent mental health trends in the UK, with longitudinal data from four subsequent surveys conducted between 2020 and 2023.

Background and objective: Healthcare research faces challenges in developing metrics that resonate with the general public or policymakers. We created a Desirable Health Indicator (DHI) to address this gap, centred around New Year's wishes for survival and non-occurrence of undesired events in the following year, for the population of Wales, UK, following discussions with policymakers and members of the public.

Methods: We created retrospective, population-based individual-level cohorts from linked routinely collected anonymised, health and demographic data from the Secure Anonymised Information Linkage (SAIL) Databank (2015-2022). The DHI was calculated per person per year and quantified the distribution of the population who survive calendar years and do not use selected health services (not admitted to hospital; no emergency department attendance; and not prescribed medication used in infection, analgesics, or mental health drugs). Group and individual interviews were held with members of the public and policy makers seeking their views of the indicator.

Results: The findings were understood and well received by members of the general public and policymakers. Between 2015 and 2019, the percentage of individuals meeting the DHI ranged between 39.6%-41.9%, increasing to 48.6% and 46.2% for2020 and 2021respectively, and reducing to 43.1% in 2022. Focussing on the year 2022, 1,154,630 (43.1%) met the DHI from a population of 2,677,829. The percentage of people with desirable health decreased significantly with age and with increasing socioeconomic deprivation. A higher proportion of males (49.2%) met the DHI compared to females (37.1%). Being male (aOR = 1.62 [95%CI 1.61,1.63]), 10-19 years of age (aOR = 1.69 [95%CI 1.68,1.71]), and living in the least deprived areas of Wales (aOR = 1.31 [95%CI 1.30,1.32]) were the characteristics associated with the highest odds of meeting the desirable health indicator. The most prevalent reasons for not meeting the indicator were GP prescriptions for drugs used in infections (29.5%), analgesics (22.8%) and mental health conditions (20.2%).

Conclusion: The DHI provides an insightful and novel tool for monitoring aspects of population health and healthcare utilisation. The DHI's coverage of important topics, derived from routine data sources, makes it a reproducible, temporally flexible, and easily understood indicator, suitable for informing policy development and addressing aspects of health inequalities. As data linkage capabilities expand internationally there are opportunities for implementation to aid comparison and better understanding of how systems perform.

Introduction: Schools worldwide balance whole-class teaching with additional provision for children with special educational needs or disability (SEND). Robust evidence on equity and effectiveness of SEND provision is essential to address growing demand and rising costs globally.

Objectives: To synthesise findings from the Health Outcomes for young People throughout Education (HOPE) evaluation of variation in SEND provision and its impact on health and education outcomes in English primary schools. We integrated findings from 14 sub-studies using administrative data in the Education and Child Health Insights from Linked Data (ECHILD) database and 10 mixed methods sub-studies.

Methods: Analyses of ECHILD data followed children from birth to age 11 years. We examined how variation in SEND provision was associated with health conditions, and school, social and organisational factors. Using target trial emulation, we estimated the impact of SEND provision on hospital admissions, school absences and attainment. We surveyed and interviewed young people, parents, and professionals and reviewed information about services to understand SEND processes and contexts.

Results: Of 3.8 million children born 2004 to 2013, 30% had SEND provision recorded by age 11. Health conditions were only partially associated with SEND provision, which was also related to male gender, social disadvantage, low attainment and type of school. SEND provision modestly reduced rates of unauthorised absences in subgroups of children but showed no measurable benefit on hospital admissions or school attainment. Mixed methods studies highlighted benefits of early, responsive support, challenges posed by limited capacity, harms caused by delayed or inadequate provision, and need for parent advocacy to access SEND provision.

Discussion: Weak evidence of benefits of SEND provision in causal analyses likely reflects unmeasured confounding, lack of measures of provision received and insensitive outcomes in ECHILD data. SEND policies need robust evidence from analyses across jurisdictions using administrative data, enhanced with better measures, experimental methods and contextual evaluation.

Introduction: Clinical guidelines may reduce statistical power in epidemiological studies by discarding informative measures. Epidemiological studies of lung function may discard one-third to one-half of participants due to spirometry measures deemed "low quality" using criteria adapted from clinical practice.

Objectives: To optimise the signal-to-noise ratio in epidemiological studies of lung function, we aimed to develop a data-driven method to refine spirometry quality control (QC) criteria.

Methods: We proposed a genetic risk score (GRS) informed strategy to categorise spirometer blows by quality criteria. GRS was built using SNPs associated with lung function traits in non-UK Biobank cohorts. In the UK Biobank, we applied a step-wise testing of the GRS association across groups of spirometry blows stratified by acceptability flags to rank the blow quality. We reassessed QC criteria by comparing the genetic associations under different acceptability flags and repeatability thresholds to determine the trade-off between sample size and measurement error.

Results: We found that including blows previously excluded by strict QC criteria would maximise the statistical power for genome-wide association study and retain acceptable precision in the UK Biobank. This approach allowed the inclusion of 29% more participants compared to the strictest clinical guidelines and demonstrated genetic signals could be identified earlier.

Conclusions: Our GRS-based method offers an important framework to challenge prevailing practices that exclude informative measures and limit power in epidemiological studies.

Aim: To create longitudinal postcode history datasets that allocate mothers to one postcode for each week of pregnancy and children to one postcode for each week of infancy for a study of air pollution and respiratory infections in infants.

Datasets: We used linked birth registrations and NHS birth notifications for all children born in London between 2010 and 2014, which constituted the spine for the Air Pollution, housing and respiratory tract Infections in Children: National Birth Cohort Study (PICNIC) study. The birth data were linked by NHS England to the Personal Demographics Service (PDS) in order to derive maternal and child postcode histories for each week of pregnancy and infancy.

Challenges: While the research team had extensive experience working with administrative data, including birth registrations and notifications, the postcode history data was a new resource and lacked meta-data, papers or reports from previous users. A substantial number of records were missing a move-in date, or both a move-in date and postcode, adding complexities when ascertaining an address history for study participants. Further, we encountered instances of incorrectly recorded postcodes and implausible numbers of postcodes recorded in a week.

Lessons learned: One half of children in this London-based cohort moved during infancy, and one third of their mothers moved during pregnancy. This highlights the importance of taking into account changes in residential address in studies examining the association between environmental exposures and health outcomes. Cleaned and validated longitudinal national address records are crucial for environmental health studies. However, they are also resource intensive, with implications for researchers and research funders.

Introduction: In Australia, around 85% of children survive childhood cancer. Yet, up to 80% of survivors experience subsequent adverse health conditions called late effects, largely attributed to cancer treatment. The LACE study is a population-based linked data resource that aims to facilitate the investigation of childhood cancer and its treatment and the impact on late effects for childhood cancer survivors.

Methods: The study links the Australian Childhood Cancer Registry to administrative cross-jurisdictional health and education data to enable ongoing follow-up of outcomes for childhood cancer survivors. The study population includes all Australian children aged less than 15 years, diagnosed with cancer 1983-2021, and comparison groups comprising siblings of childhood cancer patients and a random sample of children from the general population frequency matched by age, sex and residential location to cases.

Results: To date, the case cohort includes 25,226 children diagnosed with cancer, with longest follow-up to the age of 53 years. The most commonly diagnosed childhood cancers were leukaemia and related cancers (n=8182, 32.4%), followed by central nervous system and related cancers (n=5850, 23.2%), and lymphomas and reticuloendothelial neoplasms (n=2568, 10.2%). Overall, 16,314 (64.7%) children underwent chemotherapy, 5555 (22.0%) received radiotherapy and 7300 (28.9%) had surgical treatment for their cancer, with immunotherapy use reported for 641 (2.5%), hormonal therapy for 4549 (18.0%) and ancillary therapies for 2581 (10.2%). A total of 19,321 (76.6%) cases were alive at the end of the study.

Conclusion: This new comprehensive national data linkage resource represents a valuable asset that will facilitate research to identify the risk of late effects and effective follow-up care to inform counselling patients and their families, as well as guidelines, models of care and personalised follow-up care plans. Further, it will enable identification of inequities in healthcare access and outcomes across population sub-groups.

Introduction: Priority setting with patients, public and professionals is essential for research utilising routinely collected data, as this ensures data are being used in the public interest. However, it is challenging to identify research priorities that are relevant to a wide range of local stakeholders and can be addressed with routinely collected data.

Objectives: To describe and present the results of a priority setting exercise aiming to identify research priorities for Born in Bradford for All (BiB4All), a routine data linkage cohort of mothers and babies born in Bradford, a city in the north of England.

Methods: We developed a two-hour online workshop to engage a range of stakeholders across Bradford, including parents, early years practitioners, commissioners, and service providers. The workshop method combined elements of existing priority setting approaches to ensure priorities were identified in an inclusive, timely and deliberative way, and supported stakeholders to develop their understanding of using linked routine data for research.

Results: The workshop identified seventeen important and urgent research priorities around child and maternal health for research with locally linked routine data. Key topic areas included maternal and infant mental health, the long-term impact of the Covid-19 pandemic on maternal and child health outcomes, inequalities in access to services, and infant feeding experiences.

Conclusions: The identified research priorities have been shared widely amongst interested networks and have shaped the BiB4All research agenda, demonstrating the feasibility of the stakeholder engagement method. They also have important implications for policy and practice. For policy, they provide an understanding of the key issues faced by local communities, which can steer policy priorities and investment in evidence generation. For practice, involvement in the workshop has generated a greater understanding of how local service data can be used for research and to inform improvements to service delivery.