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Background Referral rates from Health service to Children's Social Care (CSC) services vary across England. In 2019, the National Audit Office (re)iterated the urgent need to understand the drivers of such variation. Methods Using administrative data (Children in Need Census, 2013–16), we calculated annual referral rates from Health to CSC services (Health referral rate) by Local Authority (LA) areas. We used multilevel linear regression to investigate the relationship between age-adjusted Health referral rates and local need (demand factors) and local practice/systems (supply factors). We present a tool to compare unadjusted and adjusted LA rates. Results There was high LA variation in Health referral rates, particularly for infants (mean = 29.0/1000 children < 1 y; range = 6.5–101.8; sd = 12.4). LA variation persisted after age-adjustment. Child poverty (local need) and overall referral rate (local practice/systems) explained 60% of variation in age-adjusted Health referral rates. Overall referral rate was the strongest predictor. Adjusted referral rates were substantially different from unadjusted rates. After adjustment, 57.7% of LAs had higher/lower Health referral rates than expected. Conclusions While higher levels of local need are associated with higher Health referrals, some areas have high Health referrals irrespective of local need. Our tool demonstrates the benefits of using adjusted rates to compare LAs. [ABSTRACT FROM AUTHOR]

Objectives: To assess the clinical, occupational and financial outcomes of a new Clinical Aviation Medicine Service (CAMS) for UK military personnel. Methods: Consecutive patients over a 2 year period were included. Predictors of flying restrictions at referral and final outcome following consultation were modelled using logistic regression. National Health Service (NHS) Payment by Results tariffs and Defence capitation data were used to assess the financial impact of the service. Results: Eight hundred and sixteen new referrals (94.5% male, median age 45 years (range 19-75)) were received and 1025 consultations performed. Cardiovascular disease was the commonest reason for referral. CAMS clinical activity cost at NHS tariff was £453 310 representing a saving of £316 173 (£137 137 delivery cost). In total, 310/816 (38%) patients had employment restrictions on referral and 49.0% of this group returned to full employment following their initial consultation. Compared with cardiology, general medicine and respiratory patients were more likely to have been occupationally restricted prior to referral (50 vs. 35%, OR 1.81; 95% CI 1.18-2.76, P values=0.006 and 53 vs. 35%, OR 2.12; 95% CI 1.15-3.90, P values = 0.016, respectively). Overall 581/816 (71.2%) of patients returned to unrestricted employment while 98/816 (12.0%) were unable to continue in any aircrew role. The service saved 7000 lost working days per year at an estimated occupational saving of ∼£1 million per annum. Conclusions: This bespoke service has allowed rapid, occupationally relevant clinical care to be delivered with both time and financial savings. The model may have significant occupational and financial relevance for other environmental and occupational medical organizations. [ABSTRACT FROM AUTHOR]

Objective To examine incidence rates and trends of childhood Type 1 diabetes in Yorkshire from 1978 to 2007. Methods Data from the population-based Yorkshire Register of Diabetes in Children and Young People was used to analyse the incidence of Type 1 diabetes in children aged <15 years diagnosed in the former Yorkshire Regional Health Authority. Incidence rates (per 100 000 per year) were estimated using mid-year population estimates stratified by sex, age and ethnicity: south Asian (Indian, Pakistani, Bangladeshi) or non-south Asian (all other ethnicities). Ethnicity was assigned using two name recognition programs (Nam Pehchan and SANGRA) and a local expert. Age-sex standardised rates were calculated between 1978 and 2007 and by ethnic-group between 1990 and 2007. Poisson regression was used to assess incidence trends and estimate predicted rates up to 2020. Goodness-of-fit, AIC and likelihood-ratio tests were used to assess model fit. Results 3896 children were diagnosed in Yorkshire between 1978 and 2007. Overall incidence was 18.1 (95% CI 17.5 to to 18.6), increasing from 13.3 (1978 to 1987) to 16.9 (1988 to 1997) to 24.1 (1998 to 2007). Incidence increased significantly over time: average annual percentage change (AAPC) was 2.8% (1.8 to 3.8). The inclusion of an age-sex interaction term provided evidence for differences in trends between sexes depending on age, with females having higher incidence and AAPC than males for those aged 5–9. Overall incidence for non-south Asians (21.4; 20.6 to 22.3) was significantly higher than that of south Asians (14.6; 12.3 to 17.0) over the entire study period. A significant increasing trend in incidence was observed for non-south Asians of 3.3% (1.3 to 5.2) compared to a non-significant trend seen in south Asians (1.9%; –0.4 to 4.3). Overall forecasted incidence for 2020 is 38.3 per 100 000. Conclusions Type 1 diabetes incidence rates have risen almost uniformly for non-south Asians of all ages but not for south Asians, contrary to findings in the Bradford area of Yorkshire between 1978 and 1998. Overall incidence increased most quickly in the 5–9 age-group. Incidence doubled from 12.5 to 25.2 between 1978 and 2007. If current trends continue, rates will rise by 52% to 38.3 between 2007 and 2020. [ABSTRACT FROM AUTHOR]

Background: The health visiting service in UK promotes the health and wellbeing of families with young children and comprises a universal offer (three mandated contacts between birth and 12 months) and additional contacts based on need. We aimed to understand how the level of health visiting support received varies by family characteristics., Methods: Using the Community Services Data Set linked to Hospital Episode Statistics, we identified 52 555 children in 10 local authorities with complete health visiting data for 12 months between April 2016 and March 2020. We analysed variation in health visiting contacts by deprivation, child ethnicity, maternal age, adversity and previous live births., Results: 41 340/52 555 children (79%) received the universal service; 63% received ≥1 additional contact and 25% received ≥3 additional contacts. The likelihood of receiving ≥3 additional contacts was greatest for children whose mothers had a history of hospital admissions relating to mental health, violence, self-harm or substance misuse (adjusted relative risk = 1.55, 95% confidence interval 1.26-1.92)., Conclusions: Most families received health visiting support in addition to the universal service. Policymakers and commissioners should consider how health visiting services can be expanded or targeted more effectively to ensure all families receive the support they need., (© The Author(s) 2024. Published by Oxford University Press on behalf of Faculty of Public Health.)

As statistical reviewers and editors for BMJ Paediatrics Open (BMJPO), we frequently see methodological and statistical errors in articles submitted to our journal. To make a list of these common errors and propose suitable corrections, and inspired by similar efforts at other leading journals, we surveyed the statistical reviewers and editors at BMJPO to collect their 'pet peeves' and examples of best practices.(1, 2) We have divided these into seven sections: graphics; statistical significance and related issues; presentation, vocabulary, textual and tabular presentation; causality; model building, regression and choice of methods; meta-analysis; and miscellaneous. Here, we present the common errors, with brief explanations. We hope that the guidance provided here will help guide authors as they prepare their submissions to the journal, leading to higher quality and more robust research reporting., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: The extent to which COVID-19 diagnosis and vaccination during pregnancy are associated with risks of common and rare adverse pregnancy outcomes remains uncertain. We compared the incidence of adverse pregnancy outcomes in women with and without COVID-19 diagnosis and vaccination during pregnancy., Methods: We studied population-scale linked electronic health records for women with singleton pregnancies in England and Wales from 1 August 2019 to 31 December 2021. This time period was divided at 8th December 2020 into pre-vaccination and vaccination roll-out eras. We calculated adjusted hazard ratios (HRs) for common and rare pregnancy outcomes according to the time since COVID-19 diagnosis and vaccination and by pregnancy trimester and COVID-19 variant., Findings: Amongst 865,654 pregnant women, we recorded 60,134 (7%) COVID-19 diagnoses and 182,120 (21%) adverse pregnancy outcomes. COVID-19 diagnosis was associated with a higher risk of gestational diabetes (adjusted HR 1.22, 95% CI 1.18-1.26), gestational hypertension (1.16, 1.10-1.22), pre-eclampsia (1.20, 1.12-1.28), preterm birth (1.63, 1.57-1.69, and 1.68, 1.61-1.75 for spontaneous preterm), very preterm birth (2.04, 1.86-2.23), small for gestational age (1.12, 1.07-1.18), thrombotic venous events (1.85, 1.56-2.20) and stillbirth (only within 14-days since COVID-19 diagnosis, 3.39, 2.23-5.15). HRs were more pronounced in the pre-vaccination era, within 14-days since COVID-19 diagnosis, when COVID-19 diagnosis occurred in the 3rd trimester, and in the original variant era. There was no evidence to suggest COVID-19 vaccination during pregnancy was associated with a higher risk of adverse pregnancy outcomes. Instead, dose 1 of COVID-19 vaccine was associated with lower risks of preterm birth (0.90, 0.86-0.95), very preterm birth (0.84, 0.76-0.94), small for gestational age (0.93, 0.88-0.99), and stillbirth (0.67, 0.49-0.92)., Interpretation: Pregnant women with a COVID-19 diagnosis have higher risks of adverse pregnancy outcomes. These findings support recommendations towards high-priority vaccination against COVID-19 in pregnant women., Funding: BHF, ESRC, Forte, HDR-UK, MRC, NIHR and VR., Competing Interests: G Smith: GSK. Consultant and member of expert panel for RSV vaccination in pregnancy. GSK. Member of Data Safety Monitoring Committee for trials of RSV vaccination in pregnancy Moderna. Member of Data Safety Monitoring Committee for trials of RSV vaccination in pregnancy. No other conflicts of interest to be disclosed. D A Lawlor: European Research Council, Research grant administered by University of Bristol. No conflict with this paper; and Diabetes UK, Research grant administered by University of Bristol. No conflict with this paper., (© 2024 The Authors.)

Background/objectives: The Family Nurse Partnership is an intensive home visiting programme for adolescent mothers. We aimed to evaluate the effectiveness of the Family Nurse Partnership on outcomes up to age 7 using national administrative data., Design: We created a linked cohort of all mothers aged 13-19 using data from health, educational and children's social care and defined mothers enrolled in the Family Nurse Partnership or not using Family Nurse Partnership system data. Propensity scores were used to create matched groups for analysis., Setting: One hundred and thirty-six local authorities in England with active Family Nurse Partnership sites between 2010 and 2017., Participants: Mothers aged 13-19 at last menstrual period with live births between April 2010 and March 2019, living in a Family Nurse Partnership catchment area and their firstborn child(ren)., Interventions: The Family Nurse Partnership includes up to 64 home visits by a family nurse from early pregnancy until the child's second birthday and is combined with usual health and social care. Controls received usual health and social care., Main Outcome Measures: Indicators of child maltreatment (hospital admissions for injury/maltreatment, referral to social care services); child health and development (hospital utilisation and education) outcomes and maternal hospital utilisation and educational outcomes up to 7 years following birth., Data Sources: Family Nurse Partnership Information System, Hospital Episode Statistics, National Pupil Database., Results: Of 110,520 eligible mothers, 25,680 (23.2%) were enrolled in the Family Nurse Partnership. Enrolment rates varied across 122 sites (range: 11-68%). Areas with more eligible mothers had lower enrolment rates. Enrolment was higher among mothers aged 13-15 (52%), than 18-19 year-olds (21%). Indicators of child maltreatment: we found no evidence of an association between the Family Nurse Partnership and indicators of child maltreatment, except for an increased rate of unplanned admissions for maltreatment/injury-related diagnoses up to age 2 for children born to Family Nurse Partnership mothers (6.6% vs. 5.7%, relative risk 1.15; 95% confidence interval 1.07 to 1.24). Child health and developmental outcomes: there was weak evidence that children born to Family Nurse Partnership mothers were more likely to achieve a Good Level of Development at age 5 (57.5% vs. 55.4%, relative risk 1.05; 95% confidence interval 1.00 to 1.09). Maternal outcomes: There was some evidence that Family Nurse Partnership mothers were less likely to have a subsequent delivery within 18 months of the index birth (8.4% vs. 9.3%, relative risk 0.92; 95% confidence interval 0.88 to 0.97). Younger and more vulnerable mothers received higher numbers of visits and were more likely to achieve fidelity targets. Meeting the fidelity targets was associated with some outcomes., Limitations: Bias by indication and variation in the intervention and usual care over time and between areas may have limited our ability to detect effects. Multiple testing may have led to spurious, significant results., Conclusions: This study supports findings from evaluations of the Family Nurse Partnership showing no evidence of benefit for maltreatment outcomes measured in administrative data. Amongst all the outcomes measured, we found weak evidence that the Family Nurse Partnership was associated with improvements in child development at school entry, a reduction in rapid repeat pregnancies and evidence of increased healthcare-seeking in the mother and child., Future Work: Future evaluations should capture better measures of Family Nurse Partnership interventions and usual care, more information on maternal risk factors and additional outcomes relating to maternal well-being., Study Registration: The study is registered as NIHR CRN Portfolio (42900)., Funding: This award was funded by the National Institute of Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: 17/99/19) and is published in full in Health and Social Care Delivery Research ; Vol. 12, No. 11. See the NIHR Funding and Awards website for further award information.

Background: Neurodisability describes a broad set of conditions affecting the brain and nervous system which result in functional limitations. Children with neurodisability have more hospital admissions than their peers without neurodisability and higher rates of school absence. However, longitudinal evidence comparing rates of hospital admission and school absence in children with neurodisability to peers without neurodisability throughout school is limited, as is understanding about whether differences are greatest for planned care (e.g., scheduled appointments) or unplanned care. This study will describe rates of planned and unplanned hospital admissions and school absence due to illness and medical reasons throughout primary school (Reception to Year 6, ages 4 to 11 in England) for children with neurodisability and all other children, using linked individual-level health and education data., Methods: We will use the ECHILD (Education and Child Insights from Linked Data) database, which links educational and health records across England. We will define a primary school cohort of children who were born in National Health Service-funded hospitals in England between 1 st September 2003 and 31 st August 2008, and who were enrolled in Reception (age 4/5) at state-funded schools. We will use hospital admissions records to identify children who have recorded indicators of neurodisability from birth up to the end of primary school (Year 6, age 10/11)., Results: We will describe rates of planned and unplanned hospital admissions and health-related school absence for three groups of children: those with a neurodisability indicator first recorded before beginning primary school, those with neurodisability first recorded during primary school, and those without a record of neurodisability before end of primary school., Conclusions: We will further explore whether differences between these group vary across primary school years and by socioeconomic and demographic characteristics., Competing Interests: No competing interests were disclosed., (Copyright: © 2024 Gimeno L et al.)

Despite evidence suggesting that some migrants are at risk of under-immunization and have experienced severe health inequities during the pandemic, data are limited on migrants' COVID-19 vaccine coverage globally. Here we linked data from non-European Union migrants and resettled refugees to the national COVID-19 vaccination dataset in England. We estimated patterns in second and third dose delays and overdue doses between 12 December 2020 and 20 April 2022 by age, visa type and ethnicity. Of the 465,470 linked records, 91.8% (427,073/465,470) of migrants received a second dose and 51.3% (238,721/465,470) received a third. Refugees had the highest risk of delayed second (adjusted odds ratio 1.66; 95% confidence interval 1.55-1.79) and third dose (1.55; 1.43-1.69). Black migrants were twice as likely to have a second dose delayed (2.37; 2.23-2.54) than white migrants, but this trend reversed for the third dose. Older migrants (>65 years) were four times less likely to have received their second or third dose compared with the general population in England aged >65 or older. Policymakers, researchers and practitioners should work to understand and address personal and structural barriers to vaccination for diverse migrant populations., (© 2023. The Author(s).)

Introduction: Difficulties ascertaining migrant status in national data sources such as hospital records have limited large-scale evaluation of migrant healthcare needs in many countries, including England. Linkage of immigration data for migrants and refugees, with National Health Service (NHS) hospital care data enables research into the relationship between migration and health for a large cohort of international migrants., Objectives: We aimed to describe the linkage process and compare linkage rates between migrant sub-groups to evaluate for potential bias for data on non-EU migrants and resettled refugees linked to Hospital Episode Statistics (HES) in England., Methods: We used stepwise deterministic linkage to match records from migrants and refugees to a unique healthcare identifier indicating interaction with the NHS (linkage stage 1 to NHS Personal Demographic Services, PDS), and then to hospital records (linkage stage 2 to HES). We calculated linkage rates and compared linked and unlinked migrant characteristics for each linkage stage., Results: Of the 1,799,307 unique migrant records, 1,134,007 (63%) linked to PDS and 451,689 (25%) linked to at least one hospital record between 01/01/2005 and 23/03/2020. Individuals on work, student, or working holiday visas were less likely to link to a hospital record than those on settlement and dependent visas and refugees. Migrants from the Middle East and North Africa and South Asia were four times more likely to link to at least one hospital record, compared to those from East Asia and the Pacific. Differences in age, sex, visa type, and region of origin between linked and unlinked samples were small to moderate., Conclusion: This linked dataset represents a unique opportunity to explore healthcare use in migrants. However, lower linkage rates disproportionately affected individuals on shorter-term visas so future studies of these groups may be more biased as a result. Increasing the quality and completeness of identifiers recorded in administrative data could improve data linkage quality., Competing Interests: Statement on conflicts of interest: RB has received funding from Doctors of the World and is the chair of the UK Refugee and Migrant Health Research Consortium.

Introduction: Recent years have seen an increase in linkages between survey and administrative data. It is important to evaluate the quality of such data linkages to discern the likely reliability of ensuing research. Evaluation of linkage quality and bias can be conducted using different approaches, but many of these are not possible when there is a separation of processes for linkage and analysis to help preserve privacy, as is typically the case in the UK (and elsewhere)., Objectives: We aimed to describe a suite of generalisable methods to evaluate linkage quality and population representativeness of linked survey and administrative data which remain tractable when users of the linked data are not party to the linkage process itself. We emphasise issues particular to longitudinal survey data throughout., Methods: Our proposed approaches cover several areas: i) Linkage rates, ii) Selection into response, linkage consent and successful linkage, iii) Linkage quality, and iv) Linked data population representativeness. We illustrate these methods using a recent linkage between the 1958 National Child Development Study (NCDS; a cohort following an initial 17,415 people born in Great Britain in a single week of 1958) and Hospital Episode Statistics (HES) databases (containing important information regarding admissions, accident and emergency attendances and outpatient appointments at NHS hospitals in England)., Results: Our illustrative analyses suggest that the linkage quality of the NCDS-HES data is high and that the linked sample maintains an excellent level of population representativeness with respect to the single dimension we assessed., Conclusions: Through this work we hope to encourage providers and users of linked data resources to undertake and publish thorough evaluations. We further hope that providing illustrative analyses using linked NCDS-HES data will improve the quality and transparency of research using this particular linked data resource., Competing Interests: Statement on conflicts of interest: The authors have no conflicts of interest to declare.

Background: There is growing interest in whether linked administrative data have the potential to aid analyses subject to missing data in cohort studies., Methods: Using linked 1958 National Child Development Study (NCDS; British cohort born in 1958, n = 18,558) and Hospital Episode Statistics (HES) data, we applied a LASSO variable selection approach to identify HES variables which are predictive of non-response at the age 55 sweep of NCDS. We then included these variables as auxiliary variables in multiple imputation (MI) analyses to explore the extent to which they helped restore sample representativeness of the respondents together with the imputed non-respondents in terms of early life variables (father's social class at birth, cognitive ability at age 7) and relative to external population benchmarks (educational qualifications and marital status at age 55)., Results: We identified 10 HES variables that were predictive of non-response at age 55 in NCDS. For example, cohort members who had been treated for adult mental illness had more than 70% greater odds of bring non-respondents (odds ratio 1.73; 95% confidence interval 1.17, 2.51). Inclusion of these HES variables in MI analyses only helped to restore sample representativeness to a limited extent. Furthermore, there was essentially no additional gain in sample representativeness relative to analyses using only previously identified survey predictors of non-response (i.e. NCDS rather than HES variables)., Conclusions: Inclusion of HES variables only aided missing data handling in NCDS to a limited extent. However, these findings may not generalise to other analyses, cohorts or linked administrative datasets. This work provides a demonstration of the use of linked administrative data for the handling of missing cohort data which we hope will act as template for others., (© 2023. The Author(s).)

Introduction: One-third of children in England have special educational needs (SEN) provision recorded during their school career. The proportion of children with SEN provision varies between schools and demographic groups, which may reflect variation in need, inequitable provision and/or systemic factors. There is scant evidence on whether SEN provision improves health and education outcomes., Methods: The Health Outcomes of young People in Education (HOPE) research programme uses administrative data from the Education and Child Health Insights from Linked Data-ECHILD-which contains data from all state schools, and contacts with National Health Service hospitals in England, to explore variation in SEN provision and its impact on health and education outcomes. This umbrella protocol sets out analyses across four work packages (WP). WP1 defined a range of 'health phenotypes', that is health conditions expected to need SEN provision in primary school. Next, we describe health and education outcomes (WP1) and individual, school-level and area-level factors affecting variation in SEN provision across different phenotypes (WP2). WP3 assesses the impact of SEN provision on health and education outcomes for specific health phenotypes using a range of causal inference methods to account for confounding factors and possible selection bias. In WP4 we review local policies and synthesise findings from surveys, interviews and focus groups of service users and providers to understand factors associated with variation in and experiences of identification, assessment and provision for SEN. Triangulation of findings on outcomes, variation and impact of SEN provision for different health phenotypes in ECHILD, with experiences of SEN provision will inform interpretation of findings for policy, practice and families and methods for future evaluation., Ethics and Dissemination: Research ethics committees have approved the use of the ECHILD database and, separately, the survey, interviews and focus groups of young people, parents and service providers. These stakeholders will contribute to the design, interpretation and communication of findings., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY. Published by BMJ.)

Background: The ethnicity data gap hinders public health research from addressing ethnic health inequity in the UK, especially for under-served young, migrant populations. We aimed to review how ethnicity was captured, reported, analysed, and theorised within policy-relevant research., Methods: For this bibliographical review, we reviewed a selection of the 1% most highly cited population health papers reporting UK ethnicity data in MEDLINE and Web of Science databases between Jan 1, 1946, and July 31, 2022, and extracted how ethnicity was recorded and analysed. We included cross-sectional, longitudinal cohort studies, and randomised trials using only UK populations, which were peer-reviewed, were written in English, and reported ethnicity and any health-related outcomes. We held three focus groups with ten participants aged 18-25 years, from Nigeria, Turkistan, Syria, Yemen, and Iran to help us shape and interpret our findings, and asked "How should ethnicity be asked inclusively, and better recorded?" and "Does ethnicity change over time or context? If so, why?". We consolidated feedback from our focus groups into a co-created poster with recommendations for researchers studying ethnicity and health. Written informed consent was obtained for focus group participation., Findings: Of 44 papers included in the review, 19 (43%) used self-reported ethnicity, but the number of ethnic categories provided varied. Of 27 papers that aggregated ethnicity, 13 (48%) provided justification. Only eight (18%) explicitly theorised how ethnicity related to health. The focus groups agreed that (1) ethnicity should not be prescribed by others (individuals could be asked to describe their ethnicity in free-text, which researchers could synthesise to extract relevant dimensions of ethnicity for their research) and (2) Ethnicity changes over time and context according to personal experience, social pressure, and nationality change. The lived experience of ethnicity of migrants and non-migrants is not fully interchangeable, even if they share the same ethnic category., Interpretation: Researchers should communicate clearly how ethnicity is operationalised in their studies, with appropriate justification for clustering and analysis that is meaningfully theorised. Our study was limited by its non-systematic nature. Implementing the recommendation to capture ethnicity via free text remains challenging in administrative data systems., Funding: UCL Engagement Beacon Bursary., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Reducing health inequalities by addressing the social circumstances in which children are conceived and raised is a societal priority. Early interventions are key to improving outcomes in childhood and long-term into adulthood. Across the UK nations, there is strong political commitment to invest in the early years. National policy interventions aim to tackle health inequalities and deliver health equity for all children. Evidence to determine the effectiveness of socio-structural policies on child health outcomes is especially pressing given the current social and economic challenges facing policy-makers and families with children. As an alternative to clinical trials or evaluating local interventions, we propose a research framework that supports evaluating the impact of whole country policies on child health outcomes. Three key research challenges must be addressed to enable such evaluations and improve policy for child health: (1) policy prioritisation, (2) identification of comparable data and (3) application of robust methods., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: The ethnicity data gap pertains to 3 major challenges to address ethnic health inequality: 1) Under-representation of ethnic minorities in research; 2) Poor data quality on ethnicity; 3) Ethnicity data not being meaningfully analysed. These challenges are especially relevant for research involving under-served migrant populations in the UK. We aimed to review how ethnicity is captured, reported, analysed and theorised within policy-relevant research on ethnic health inequities., Methods: We reviewed a selection of the 1% most highly cited population health papers that reported UK data on ethnicity, and extracted how ethnicity was recorded and analysed in relation to health outcomes. We focused on how ethnicity was obtained (i.e. self reported or not), how ethnic groups were categorised, whether justification was provided for any categorisation, and how ethnicity was theorised to be related to health. We held three 1-h-long guided focus groups with 10 young people from Nigeria, Turkistan, Syria, Yemen and Iran. This engagement helped us shape and interpret our findings, and reflect on. 1) How should ethnicity be asked inclusively, and better recorded? 2) Does self-defined ethnicity change over time or context? If so, why?, Results: Of the 44 included papers, most (19; 43%) used self-reported ethnicity, categorised in a variety of ways. Of the 27 papers that aggregated ethnicity, 13 (48%) provided justification. Only 8 of 33 papers explicitly theorised how ethnicity related to health. The focus groups agreed that 1) Ethnicity should not be prescribed by others; individuals could be asked to describe their ethnicity in free-text which researchers could synthesise to extract relevant dimensions of ethnicity for their research; 2) Ethnicity changes over time and context according to personal experience, social pressure, and nationality change; 3) Migrants and non-migrants' lived experience of ethnicity is not fully inter-changeable, even if they share the same ethnic category., Conclusions: Ethnicity is a multi-dimensional construct, but this is not currently reflected in UK health research studies, where ethnicity is often aggregated and analysed without justification. Researchers should communicate clearly how ethnicity is operationalised for their study, with appropriate justification for clustering and analysis that is meaningfully theorised. We can only start to tackle ethnic health inequity by treating ethnicity as rigorously as any other variables in our research., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Introduction: Mortality rates in infancy and childhood are lower in females than males. However, for children admitted to Paediatric Intensive Care Units (PICU), mortality has been reported to be lower in males, although males have higher admission rates. This female mortality excess for the subgroup of children admitted in intensive care is not well understood. To address this, we carried out a systematic literature review to summarise the available evidence. Our review studies the differences in mortality between males and females aged 0 to <18 years, while in a PICU, to examine whether there was a clear difference (in either direction) in PICU mortality between the two sexes, and, if present, to describe the magnitude and direction of this difference., Methods: Any studies that directly or indirectly reported the rates of mortality in children admitted to intensive care by sex were eligible for inclusion. The search strings were based on terms related to the population (those admitted into a paediatric intensive care unit), the exposure (sex), and the outcome (mortality). We used the search databases MEDLINE, Embase, and Web of Science as these cover relevant clinical publications. We assessed the reliability of included studies using a modified version of the risk of bias in observational studies of exposures (ROBINS-E) tool. We considered estimating a pooled effect if there were at least three studies with similar populations, periods of follow-up while in PICU, and adjustment variables., Results: We identified 124 studies of which 114 reported counts of deaths by males and females which gave a population of 278,274 children for analysis, involving 121,800 (44%) females and 156,474 males (56%). The number of deaths and mortality rate for females were 5,614 (4.61%), and for males 6,828 (4.36%). In the pooled analysis, the odds ratio of female to male mortality was 1.06 [1.01 to 1.11] for the fixed effect model, and 1.10 [1.00 to 1.21] for the random effects model., Discussion: Overall, males have a higher admission rate to PCU, and potentially lower overall mortality in PICU than females., Systematic Review Registration: www.crd.york.ac.uk/PROSPERO/display&#95;record.php?RecordID=203009, identifier (CRD42020203009)., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2023 Almossawi, Friend, Palla, Feltbower, Sardo-Infirri, O'Brien, Harron, Nadel, Saunders and De Stavola.)

Background: Children with congenital heart defects (CHD) are twice as likely as their peers to be born preterm (<37 weeks' gestation), yet descriptions of recent trends in long-term survival by gestational age at birth (GA) are lacking., Objectives: To quantify changes in survival to age 5 years of children in England with severe CHD by GA., Methods: We estimated changes in survival to age five of children with severe CHD and all other children born in England between April 2004 and March 2016, overall and by GA-group using linked hospital and mortality records., Results: Of 5,953,598 livebirths, 5.7% (339,080 of 5,953,598) were born preterm, 0.35% (20,648 of 5,953,598) died before age five and 3.6 per 1000 (21,291 of 5,953,598) had severe CHD. Adjusting for GA, under-five mortality rates fell at a similar rate between 2004-2008 and 2012-2016 for children with severe CHD (adjusted hazard ratio [HR] 0.79, 95% CI 0.71, 0.88) and all other children (HR 0.78, 95% CI 0.76, 0.81). For children with severe CHD, overall survival to age five increased from 87.5% (95% CI 86.6, 88.4) in 2004-2008 to 89.6% (95% CI 88.9, 90.3) in 2012-2016. There was strong evidence for better survival in the ≥39-week group (90.2%, 95% CI 89.1, 91.2 to 93%, 95% CI 92.4, 93.9), weaker evidence at 24-31 and 37-38 weeks and no evidence at 32-36 weeks. We estimate that 51 deaths (95% CI 24, 77) per year in children with severe CHD were averted in 2012-2016 compared to what would have been the case had 2004-2008 mortality rates persisted., Conclusions: Nine out of 10 children with severe CHD in 2012-2016 survived to age five. The small improvement in survival over the study period was driven by increased survival in term children. Most children with severe CHD are reaching school age and may require additional support by schools and healthcare services., (© 2023 The Authors. Paediatric and Perinatal Epidemiology published by John Wiley & Sons Ltd.)

Competing Interests: We declare no competing interests.

Introduction: Health visiting is a long-established, nationally implemented programme that works with other services at a local level to improve the health and well-being of children and families. To maximise the impact and efficiency of the health visiting programme, policy-makers and commissioners need robust evidence on the costs and benefits of different levels and types of health visiting, for different families, in different local contexts., Methods and Analysis: This mixed-methods study will analyse individual-level health visiting data for 2018/2019 and 2019/2020 linked with longitudinal data from children's social care, hospitals and schools to estimate the association of number and type of health visiting contacts with a range of children and maternal outcomes. We will also use aggregate local authority data to estimate the association between local models of health visiting and area-level outcomes. Outcomes will include hospitalisations, breast feeding, vaccination, childhood obesity and maternal mental health. Where possible, outcomes will be valued in monetary terms, and we will compare total costs to total benefits of different health visiting service delivery models. Qualitative case studies and extensive stakeholder input will help explain the quantitative analyses and interpret the results in the context of local policy, practice and circumstance., Ethics and Dissemination: The University College London Research Ethics Committee approved this study (ref 20561/002). Results will be submitted for publication in a peer-reviewed journal and findings will be shared and debated with national policy-makers, commissioners and managers of health visiting services, health visitors and parents., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY. Published by BMJ.)

Background: Methods for linking records between two datasets are well established. However, guidance is needed for linking more than two datasets. Using all 'pairwise linkages'-linking each dataset to every other dataset-is the most inclusive, but resource-intensive, approach. The 'spine' approach links each dataset to a designated 'spine dataset', reducing the number of linkages, but potentially reducing linkage quality., Methods: We compared the pairwise and spine linkage approaches using real-world data on patients undergoing emergency bowel cancer surgery between 31 October 2013 and 30 April 2018. We linked an administrative hospital dataset (Hospital Episode Statistics; HES) capturing patients admitted to hospitals in England, and two clinical datasets comprising patients diagnosed with bowel cancer and patients undergoing emergency bowel surgery., Results: The spine linkage approach, with HES as the spine dataset, created an analysis cohort of 15 826 patients, equating to 98.3% of the 16 100 patients identified using the pairwise linkage approach. There were no systematic differences in patient characteristics between these analysis cohorts. Associations of patient and tumour characteristics with mortality, complications and length of stay were not sensitive to the linkage approach. When eligibility criteria were applied before linkage, spine linkage included 14 509 patients (90.0% compared with pairwise linkage)., Conclusion: Spine linkage can be used as an efficient alternative to pairwise linkage if case ascertainment in the spine dataset and data quality of linkage variables are high. These aspects should be systematically evaluated in the nominated spine dataset before spine linkage is used to create the analysis cohort., (© The Author(s) 2022. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Introduction: We aimed to generate evidence about child development measured through school attainment and provision of special educational needs (SEN) across the spectrum of gestational age, including for children born early term and >41 weeks of gestation, with and without chronic health conditions., Methods: We used a national linked dataset of hospital and education records of children born in England between 1 September 2004 and 31 August 2005. We evaluated school attainment at Key Stage 1 (KS1; age 7) and Key Stage 2 (KS2; age 11) and any SEN by age 11. We stratified analyses by chronic health conditions up to age 2, and size-for-gestation, and calculated population attributable fractions (PAF)., Results: Of 306 717 children, 5.8% were born <37 weeks gestation and 7.0% had a chronic condition. The percentage of children not achieving the expected level at KS1 increased from 7.6% at 41 weeks, to 50.0% at 24 weeks of gestation. A similar pattern was seen at KS2. SEN ranged from 29.0% at 41 weeks to 82.6% at 24 weeks. Children born early term (37-38 weeks of gestation) had poorer outcomes than those born at 40 weeks; 3.2% of children with SEN were attributable to having a chronic condition compared with 2.0% attributable to preterm birth., Conclusions: Children born with early identified chronic conditions contribute more to the burden of poor school outcomes than preterm birth. Evaluation is needed of how early health characteristics can be used to improve preparation for education, before and at entry to school., (© The Author(s) 2022. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Background: This scoping review aimed to overview studies that used administrative data linkage in the context of child maltreatment to improve our understanding of the value that data linkage may confer for policy, practice, and research., Methods: We searched MEDLINE, Embase, PsycINFO, CINAHL, and ERIC electronic databases in June 2019 and May 2020 for studies that linked two or more datasets (at least one of which was administrative in nature) to study child maltreatment. We report findings with numerical and narrative summary., Results: We included 121 studies, mainly from the United States or Australia and published in the past decade. Data came primarily from social services and health sectors, and linkage processes and data quality were often not described in sufficient detail to align with current reporting guidelines. Most studies were descriptive in nature and research questions addressed fell under eight themes: descriptive epidemiology, risk factors, outcomes, intergenerational transmission, predictive modelling, intervention/service evaluation, multi-sector involvement, and methodological considerations/advancements., Conclusions: Included studies demonstrated the wide variety of ways in which data linkage can contribute to the public health response to child maltreatment. However, how research using linked data can be translated into effective service development and monitoring, or targeting of interventions, is underexplored in terms of privacy protection, ethics and governance, data quality, and evidence of effectiveness.

Background: Intensive home visiting for adolescent mothers may help reduce health disparities. Given limited resources, such interventions need to be effectively targeted. We evaluated which mothers were enrolled in the Family Nurse Partnership (FNP), an intensive home-visiting service for first-time young mothers commissioned in >130 local authorities in England since 2007., Methods: We created a population-based cohort of first-time mothers aged 13-19 years giving birth in English National Health Service hospitals between 1 April 2010 and 31 March 2017, using administrative hospital data linked with FNP programme, educational and social care data. Mothers living in a local authority with an active FNP site were eligible. We described variation in enrolment rates across sites, and identified maternal and FNP site characteristics associated with enrolment., Results: Of 110 520 eligible mothers, 25 680 (23.2% (95% CI: 23.0% to 23.5%)) were enrolled. Enrolment rates varied substantially across 122 sites (range: 11%-68%), and areas with greater numbers of first-time adolescent mothers achieved lower enrolment rates. Mothers aged 13-15 years were most likely to be enrolled (52%). However, only 26% of adolescent mothers with markers of vulnerability (including living in the most deprived areas and ever having been looked after as a child) were enrolled., Conclusion: A substantial proportion of first-time adolescent mothers with vulnerability markers were not enrolled in FNP. Variation in enrolment across sites indicates insufficient commissioning of places that is not proportional to level of need, with mothers in areas with large numbers of other adolescent mothers least likely to receive support., Competing Interests: Competing interests: LR is the National Lead for Family Nurse Partnership (FNP) and Parenting Programmes, and MAC Head of Data and Analysis for the FNP National Unit., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY. Published by BMJ.)

Background: COVID-19 has highlighted severe health inequities experienced by certain migrants. Despite evidence suggesting that migrants are at risk of under-immunisation, data are limited for migrants' COVID-19 vaccine uptake in England., Methods: We did a retrospective population-based cohort study on COVID-19 vaccination uptake in England. We linked the Million Migrant cohort (which includes non-EU migrants and resettled refugees) to the national COVID-19 vaccination dataset, using a stepwise deterministic matching procedure adapted from NHS Digital, and compared migrants with the general population. For migrants who linked to at least one vaccination record, we estimate temporal trends in first dose uptake and differences in second and third dose uptake and consequent delays between Dec 8, 2020, and April 20, 2022, by age, visa type, and ethnicity., Findings: Of the 465 470 migrants who linked to one or more vaccination record, 427 073 (91·8%) received a second dose and 238 721 (51·3%) received a third. Migrants (>30 years) reached 75% first-dose coverage between 1 and 2 weeks after the general population in England, with the gap widening to 6 weeks for younger migrants (16-29 years). Refugees specifically had a higher risk of a delayed second dose (odds ratio 1·75 [95 CI% 1·62-1·88]) and third dose (1·41 [1·31-1·53]). Older migrants (>65 years) were at least four times more likely to have not received their second or third dose compared with those of the same age in England., Interpretation: Uptake of the first dose was slower across all age groups for migrants compared with the general population. Refugees and older migrants were more likely to have delayed uptake of COVID-19 vaccines and to not have received their second or third dose. Policymakers, researchers, and practitioners should consider how to best drive uptake of COVID-19 and other routine vaccine doses and understand and address personal and structural barriers to vaccination systems for diverse migrant populations., Funding: Wellcome Trust and UK Research and Innovation., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Introduction: Exposure to adverse childhood experiences (ACEs) is associated with poorer health outcomes throughout life. In England, health visiting is a long-standing, nationally implemented service that aims to prevent and mitigate the impact of adversity in early childhood, including for children exposed to ACEs. A range of health visiting service delivery practices exist across England (from the minimum five recommended contacts to tailored intensive interventions), but there is a lack of evidence on who receives what services, how this varies across local authorities (LAs) and the associated outcomes., Methods and Analysis: This study will integrate findings from analysis of individual-level, deidentified administrative data related to hospital admissions (Hospital Episode Statistics (HES)) and health visiting contacts (Community Services Data Set (CSDS)), aggregate LA-level data, in-depth case studies in up to six LAs (including interviews with mothers), a national survey of health visiting services, and workshops with stakeholders and experts by experience. We will use an empirical-to-conceptual approach to develop a typology of health visiting service delivery in England, starting with a data-driven classification generated from latent class analysis of CSDS-HES data, which will be refined based on all other available qualitative and quantitative data. We will then evaluate which models of health visiting are most promising for mitigating the impact of ACEs on child and maternal outcomes using CSDS-HES data for a cohort of children born on 1 April 2015 to 31 March 2019., Ethics and Dissemination: The University College London Institute of Education Research Ethics Committee approved this study. Results will be submitted for publication in a peer-reviewed journal and summaries will be provided to key stakeholders including the funders, policy-makers, local commissioners and families., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY. Published by BMJ.)

Competing Interests: Competing interests: Competing interests: We have read and understood the BMJ policy on declaration of interests and declare the following interests: none.

Use of administrative data for research and for planning services has increased over recent decades due to the value of the large, rich information available. However, concerns about the release of sensitive or personal data and the associated disclosure risk can lead to lengthy approval processes and restricted data access. This can delay or prevent the production of timely evidence. A promising solution to facilitate more efficient data access is to create synthetic versions of the original datasets which are less likely to hold confidential information and can minimise disclosure risk. Such data may be used as an interim solution, allowing researchers to develop their analysis plans on non-disclosive data, whilst waiting for access to the real data. We aim to provide an overview of the background and uses of synthetic data and describe common methods used to generate synthetic data in the context of UK administrative research. We propose a simplified terminology for categories of synthetic data (univariate, multivariate, and complex modality synthetic data) as well as a more comprehensive description of the terminology used in the existing literature and illustrate challenges and future directions for research., Competing Interests: Declaration of conflicting interests: The authors declare that there is no conflict of interest.

Competing Interests: Competing interests: We have read and understood the BMJ policy on declaration of interests and declare the following interests: none.

Objective: The 2-2½ year universal health visiting review in England is a key time point for assessing child development and promoting school readiness. We aimed to ascertain which children were least likely to receive their 2-2½ year review and whether there were additional non-mandated contacts for children who missed this review., Design, Setting, Participants: Cross-sectional analysis of the 2-2½ year review and additional health visiting contacts for 181 130 children aged 2 in England 2018/2019, stratified by ethnicity, deprivation, safeguarding vulnerability indicator and Looked After Child status., Analysis: We used data from 33 local authorities submitting highly complete data on health visiting contacts to the Community Services Dataset. We calculated the percentage of children with a recorded 2-2½ year review and/or any additional health visiting contacts and average number of contacts, by child characteristic., Results: The most deprived children were slightly less likely to receive a 2-2½ year review than the least deprived children (72% vs 78%) and Looked After Children much less likely, compared with other children (44% vs 69%). When all additional contacts were included, the pattern was reversed (deprivation) or disappeared (Looked After children). A substantial proportion of all children (24%), children with a 'safeguarding vulnerability' (22%) and Looked After children (29%) did not have a record of either a 2-2½ year review or any other face-to-face contact in the year., Conclusions: A substantial minority of children aged 2 with known vulnerabilities did not see the health visiting team at all in the year. Some higher need children (eg, deprived and Looked After) appeared to be seeing the health visiting team but not receiving their mandated health review. Further work is needed to establish the reasons for this, and potential solutions. There is an urgent need to improve the quality of national health visiting data., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY. Published by BMJ.)

Introduction: Linkage of administrative data for universal state education and National Health Service (NHS) hospital care would enable research into the inter-relationships between education and health for all children in England., Objectives: We aim to describe the linkage process and evaluate the quality of linkage of four one-year birth cohorts within the National Pupil Database (NPD) and Hospital Episode Statistics (HES)., Methods: We used multi-step deterministic linkage algorithms to link longitudinal records from state schools to the chronology of records in the NHS Personal Demographics Service (PDS; linkage stage 1), and HES (linkage stage 2). We calculated linkage rates and compared pupil characteristics in linked and unlinked samples for each stage of linkage and each cohort (1990/91, 1996/97, 1999/00, and 2004/05)., Results: Of the 2,287,671 pupil records, 2,174,601 (95%) linked to HES. Linkage rates improved over time (92% in 1990/91 to 99% in 2004/05). Ethnic minority pupils and those living in more deprived areas were less likely to be matched to hospital records, but differences in pupil characteristics between linked and unlinked samples were moderate to small., Conclusion: We linked nearly all pupils to at least one hospital record. The high coverage of the linkage represents a unique opportunity for wide-scale analyses across the domains of health and education. However, missed links disproportionately affected ethnic minorities or those living in the poorest neighbourhoods: selection bias could be mitigated by increasing the quality and completeness of identifiers recorded in administrative data or the application of statistical methods that account for missed links., Highlights: Longitudinal administrative records for all children attending state school and acute hospital services in England have been used for research for more than two decades, but lack of a shared unique identifier has limited scope for linkage between these databases.We applied multi-step deterministic linkage algorithms to 4 one-year cohorts of children born 1 September-31 August in 1990/91, 1996/97, 1999/00 and 2004/05. In stage 1, full names, date of birth, and postcode histories from education data in the National Pupil Database were linked to the NHS Personal Demographic Service. In stage 2, NHS number, postcode, date of birth and sex were linked to hospital records in Hospital Episode Statistics.Between 92% and 99% of school pupils linked to at least one hospital record. Ethnic minority pupils and pupils who were living in the most deprived areas were least likely to link. Ethnic minority pupils were less likely than white children to link at the first step in both algorithms.Bias due to linkage errors could lead to an underestimate of the health needs in disadvantaged groups. Improved data quality, more sensitive linkage algorithms, and/or statistical methods that account for missed links in analyses, should be considered to reduce linkage bias., Competing Interests: Conflict of interest statement: None declared.

Background: Probabilistic linkage can link patients from different clinical databases without the need for personal information. If accurate linkage can be achieved, it would accelerate the use of linked datasets to address important clinical and public health questions., Objective: We developed a step-by-step process for probabilistic linkage of national clinical and administrative datasets without personal information, and validated it against deterministic linkage using patient identifiers., Study Design and Setting: We used electronic health records from the National Bowel Cancer Audit and Hospital Episode Statistics databases for 10,566 bowel cancer patients undergoing emergency surgery in the English National Health Service., Results: Probabilistic linkage linked 81.4% of National Bowel Cancer Audit records to Hospital Episode Statistics, vs. 82.8% using deterministic linkage. No systematic differences were seen between patients that were and were not linked, and regression models for mortality and length of hospital stay according to patient and tumour characteristics were not sensitive to the linkage approach., Conclusion: Probabilistic linkage was successful in linking national clinical and administrative datasets for patients undergoing a major surgical procedure. It allows analysts outside highly secure data environments to undertake linkage while minimizing costs and delays, protecting data security, and maintaining linkage quality., (Copyright © 2021. Published by Elsevier Inc.)