ABSTRACT
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.
Neurodisability encompasses a range of health conditions which affect the brain and nervous system and result in difficulties with everyday activities, including learning. Children with neurodisability are more likely to be admitted to hospital and spend longer periods of time in hospital than children without neurodisability. They are also more likely to be absent from school. Yet, in England, these is a lack of evidence comparing admissions and absence rates in children with and without neurodisability throughout their school years. Evidence is also lacking on whether differences are greatest for planned care (e.g., scheduled appointments) or unplanned care. We will use hospital and education records from state-funded hospitals and schools in England to describe rates of hospital admission and school absences for children with and without neurodisability during their primary school years.
Subject(s)
Mothers , Humans , England/epidemiology , Female , Adult , Infant , Infant, Newborn , Cohort Studies , Mothers/statistics & numerical data , Young Adult , Educational Status , AdolescentABSTRACT
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.
The Family Nurse Partnership is an intensive home visiting service that offers first-time young mothers up to 64 visits with a family nurse from pregnancy to their child's second birthday. The Family Nurse Partnership aims to improve birth outcomes, child health and development and promote economic self-sufficiency among young mothers. Previous research in England found no differences in birthweight, maternal smoking, repeat pregnancies or accident and emergency attendances between mothers who did or did not take part in the Family Nurse Partnership. However, children in the Family Nurse Partnership group had better measures of development at school age. We aimed to add to the evidence from earlier studies, by using electronic records that are routinely collected as part of health, education and social care services, to compare outcomes for around 26,000 mothers enrolled in the Family Nurse Partnership between 2010 and 2019 with similar mothers who were not enrolled. This study showed that around one in four mothers who were eligible for the programme were enrolled in the Family Nurse Partnership, and family nurses gave priority to mothers who were younger, more deprived or who had other markers of vulnerability (e.g. a history of substance misuse violence, self-harm or mental health conditions). We found no evidence of a difference in indicators of child maltreatment between mothers who were enrolled in the Family Nurse Partnership and those who were not enrolled, but we found weak evidence to suggest that children born to mothers enrolled in the Family Nurse Partnership were more likely to achieve a Good Level of Development at school entry (age 5). We also saw that mothers enrolled in the Family Nurse Partnership were less likely than those who were not enrolled to have their next child within 18 months of their first child. More research is needed to understand which elements of intensive home visiting services work best, for whom and when. This will help inform decisions about whether it is better to offer highly intensive services for a small portion of the target population or to extend and enhance existing universal health visiting services to better support all adolescent mothers.
Subject(s)
Child Abuse , Family Nursing , House Calls , Humans , Female , Adolescent , England , Child , Young Adult , Family Nursing/organization & administration , Child, Preschool , Infant , Information Storage and Retrieval , Pregnancy , Infant, Newborn , Cohort Studies , Mothers/statistics & numerical dataABSTRACT
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.
Subject(s)
State Medicine , Transients and Migrants , Humans , Emigration and Immigration , England , HospitalsABSTRACT
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.
Subject(s)
Child Development , Medical Record Linkage , Child , Humans , Reproducibility of Results , Medical Record Linkage/methods , Hospitalization , HospitalsABSTRACT
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.
Subject(s)
COVID-19 , Refugees , Transients and Migrants , Humans , COVID-19 Vaccines , Vaccination Coverage , COVID-19/prevention & control , VaccinationABSTRACT
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.
Subject(s)
Schools , State Medicine , Humans , Adolescent , Parents , Educational Status , Communication , Review Literature as TopicABSTRACT
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.
Subject(s)
Child Development , Social Class , Adult , Infant, Newborn , Child , Humans , Aged , Middle Aged , Cohort Studies , Surveys and Questionnaires , HospitalsABSTRACT
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.
Subject(s)
Refugees , Transients and Migrants , Humans , Adolescent , Young Adult , Adult , Ethnicity , Focus Groups , Public Health , Cross-Sectional Studies , Longitudinal Studies , United KingdomABSTRACT
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_record.php?RecordID=203009, identifier (CRD42020203009).
ABSTRACT
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.
Subject(s)
Ethnicity , Refugees , Humans , Adolescent , Focus Groups , Health Status Disparities , United KingdomABSTRACT
Introduction: "Big data" - including linked administrative data - can be exploited to evaluate interventions for maternal and child health, providing time- and cost-effective alternatives to randomised controlled trials. However, using these data to evaluate population-level interventions can be challenging. Objectives: We aimed to inform future evaluations of complex interventions by describing sources of bias, lessons learned, and suggestions for improvements, based on two observational studies using linked administrative data from health, education and social care sectors to evaluate the Family Nurse Partnership (FNP) in England and Scotland. Methods: We first considered how different sources of potential bias within the administrative data could affect results of the evaluations. We explored how each study design addressed these sources of bias using maternal confounders captured in the data. We then determined what additional information could be captured at each step of the complex intervention to enable analysts to minimise bias and maximise comparability between intervention and usual care groups, so that any observed differences can be attributed to the intervention. Results: Lessons learned include the need for i) detailed data on intervention activity (dates/geography) and usual care; ii) improved information on data linkage quality to accurately characterise control groups; iii) more efficient provision of linked data to ensure timeliness of results; iv) better measurement of confounding characteristics affecting who is eligible, approached and enrolled. Conclusions: Linked administrative data are a valuable resource for evaluations of the FNP national programme and other complex population-level interventions. However, information on local programme delivery and usual care are required to account for biases that characterise those who receive the intervention, and to inform understanding of mechanisms of effect. National, ongoing, robust evaluations of complex public health evaluations would be more achievable if programme implementation was integrated with improved national and local data collection, and robust quasi-experimental designs.
Subject(s)
Big Data , Semantic Web , Child , Humans , England , Scotland , Child HealthABSTRACT
OBJECTIVE: We aimed to evaluate the risk of infant maltreatment associated with commonly used criteria for home visiting programmes: young maternal age, maternal adversity (homelessness, substance abuse, intimate partner violence), newcomer status and mental health concerns in Ontario, Canada. DESIGN: This retrospective cohort study included infants born in hospital in Ontario from 1 April 2005 to 31 March 2017 captured in linked health administrative and demographic databases. Infants were followed from newborn hospitalisation until 1 year of age for child maltreatment captured in healthcare or death records. The association between type and number of maternal risk factors, and maltreatment, was analysed using multivariable logistic regression modelling, controlling for infant characteristics and material deprivation. Further modelling explored the association of each year of maternal age with maltreatment. RESULTS: Of 989 586 infants, 434 (0.04%) had recorded maltreatment. Maternal age <22 years conferred higher risk of infant maltreatment (adjusted OR (aOR) 5.5, 95% CI 4.5 to 6.8) compared with age ≥22 years. Maternal mental health diagnoses (aOR 2.0, 95% CI 1.6 to 2.5) were also associated with maltreatment, while refugee status appeared protective (aOR 0.6, 95% CI 0.4 to 1.0). The odds of maltreatment increased with higher numbers of maternal risk factors. Maternal age was associated with maltreatment until age 28 years. CONCLUSION: Infants born to young mothers are at greater risk of infant maltreatment, and this association remained until age 28 years. These findings are important for ensuring public health interventions are supporting populations experiencing structural vulnerabilities with the aim of preventing maltreatment.
Subject(s)
Child Abuse , Infant , Child , Infant, Newborn , Female , Humans , Young Adult , Adult , Cohort Studies , Retrospective Studies , Child Abuse/psychology , Mothers/psychology , Ontario/epidemiology , Risk FactorsABSTRACT
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.
Subject(s)
Child Health , Health Equity , Maternal Health , Child , Female , Humans , Family , Health Policy , PolicyABSTRACT
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.
Subject(s)
Pediatric Obesity , Public Health , Child , Humans , Family , England , ParentsABSTRACT
OBJECTIVE: Interventions to tackle the social determinants of health can improve outcomes during pregnancy and early childhood, leading to better health across the life course. Variation in content, timing and implementation of policies across the 4 UK nations allows for evaluation. We conducted a policy-mapping review (1981-2021) to identify relevant UK early years policies across the social determinants of health framework, and determine suitable candidates for evaluation using administrative data. METHODS: We used open keyword and category searches of UK and devolved Government websites, and hand searched policy reviews. Policies were rated and included using five criteria: (1) Potential for policy to affect maternal and child health outcomes; (2) Implementation variation across the UK; (3) Population reach and expected effect size; (4) Ability to identify exposed/eligible group in administrative data; (5) Potential to affect health inequalities. An expert consensus workshop determined a final shortlist. RESULTS: 336 policies and 306 strategy documents were identified. Policies were mainly excluded due to criteria 2-4, leaving 88. The consensus workshop identified three policy areas as suitable candidates for natural experiment evaluation using administrative data: pregnancy grants, early years education and childcare, and Universal Credit. CONCLUSION: Our comprehensive policy review identifies valuable opportunities to evaluate sociostructural impacts on mother and child outcomes. However, many potentially impactful policies were excluded. This may lead to the inverse evidence law, where there is least evidence for policies believed to be most effective. This could be ameliorated by better access to administrative data, staged implementation of future policies or alternative evaluation methods.
Subject(s)
Maternal Health , Policy , Child, Preschool , Female , Humans , Child Care , United Kingdom , PregnancyABSTRACT
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.