ADR UK Research Fellows: Education and Child Health Outcomes from Linked Data
Categories: Research using linked data, ADR UK Research Fellows, ADR England, Office for National Statistics, Children, young people & education, Health & wellbeing, Social mobility & inclusion
24 August 2026
ADR UK is funding Research Fellows to analyse the Education and Child Health Outcomes from Linked Data (ECHILD) dataset. Their projects are exploring the relationships between children's health, education and social care, generating evidence that could inform policy and improve support for children, young people and families. The projects are a result of ADR UK Research Fellowship opportunities which invited applications to carry out research using eligible ADR England flagship datasets.
ECHILD contains linked, de-identified records for around 21 million children and young people in England. It is made up of the National Pupil Database (including data on pupil and school characteristics, educational outcomes and social care) linked to healthcare data. This includes Hospital Episode Statistics, birth notifications/registrations, mortality, maternity services data, mental health data and community services data. The dataset can be used to better understand how education affects children’s health, and how health affects children’s education.
ECHILD also contains linked health, education and social care data on the mothers of ECHILD cohort members through a mother-baby link. This creates opportunities to investigate how family circumstances and experiences during pregnancy and early childhood relate to children's later outcomes.
The fellows are addressing a wide range of policy-relevant questions, including special educational needs and disabilities (SEND), mental and physical health, school attendance, children's social care and support during the early years. They are accessing the dataset through the Office for National Statistics (ONS) Secure Research Service.
Learn more about the Research Fellows and their projects below.
Dr Eliazar Luna
Health visiting among children in contact with social care services in England
The first five years of life are a crucial period for children's health, development and wellbeing. During this time, families receive support from health visiting, and some also have contact with children’s social care (CSC) where there are concerns about a child's welfare or safety. However, there is little evidence about how these services work together in practice, including which children receive support from both and which may miss out.
This project will investigate how health visiting and CSC interact during children's early years. It will also examine gaps in existing linked data that mean some children with early social care involvement may be missing from health research, and test new ways of linking their records. The findings could give policymakers and local authorities more complete evidence to improve coordination between early-years services and support for children and families.
Eliazar is a Research Fellow at UCL's Institute of Child Health.
View project details
This project aims to explore the following research questions:
- How do health visiting and CSC interact for children in England, and how do limitations in existing linked data affect what we know about this in order to inform policy?
- What proportion of children involved with CSC receive health visiting services, and how does this vary according to children's characteristics and the local authority they live in?
- How do children's experiences of CSC differ according to the health visiting support they receive?
The methodology used in this study:
- The project will use de-identified information from ECHILD about children's health, education and contact with CSC. It will identify children who had contact with CSC before starting school, including children whose records cannot currently be connected to their health records due to lacking a unique identifier.
- The research will test whether information linking mothers and babies, alongside information about siblings, can help connect some of these children's records. This could provide a more complete picture of children using early-years services and improve future research using linked health and social care data.
- The project will then examine when children receive health visiting and CSC support and how the two services interact over time. For example, it will explore whether children receive support from both services at the same time (“stacking”), whether one service appears to replace another (“substitution”), or whether some children receive neither (“slipping”).
- The project will describe how these patterns differ according to children's characteristics and local areas, and statistical analysis (regression analysis, time-to-event, and sequence analysis) will be used to examine how children's pathways through social care differ depending on the health visiting support they receive.
- Findings will also be compared with information from a smaller group of local authorities to assess how well the national data reflects children's experiences more widely.
Dr Angelina Nazarova
SENLOSS: The effects of losing special educational needs support at educational transitions in England
Many children with special educational needs (SEN) rely on support provided by their school without having a legally binding Education, Health and Care Plan. This support can change or stop, including when children move between stages of education. However, there is currently no nationwide evidence showing how often children lose support at these points or what happens to their learning, attendance and health afterwards.
This project will investigate how often special educational needs support is lost during key transitions, particularly when children move from primary to secondary school and from Reception to Year 1. It will identify which children are most likely to lose support and examine what happens afterwards, providing evidence that could help government, councils and schools better protect children at greatest risk.
Angelina is a Senior Research Officer at the Institute for Social and Economic Research (ISER), University of Essex.
View project details
This project aims to explore the following research questions:
- How often do children lose SEN support when they move between stages of school, and which children, schools and areas are most affected?
- What effect does losing support have on children's learning, engagement with school and health?
- How do these effects differ according to children's type of need and other characteristics, and which groups are most affected when support is lost?
The methodology used in this study:
- The project will follow children who were receiving school-based SEN support before moving to a new stage of school. It will focus particularly on the move from Year 6 to Year 7, as children start secondary school, as well as the earlier transition from Reception to Year 1. Using ECHILD, the research will compare children whose support continued with those whose support stopped.
- Children who lose support may already differ from children who keep it, so the project will use several statistical approaches to make the comparisons as fair as possible:
- Machine learning (a method called gradient boosting) will identify which characteristics of children, schools and local areas are most strongly linked to losing support.
- Target trial emulation will be used, which uses existing records to imitate the fair comparison you would get from a randomised trial.
- An event study will follow the same children in the years before and after they lose support, comparing how their outcomes change with how outcomes change for similar children who kept it. This is known as a 'difference-in-differences comparison': each child is measured against their own earlier record as well as against other children, which cancels out pre-existing differences between the two groups.
- A causal forest searches across many characteristics at once to find groups of children most affected by losing support.
Findings will be expressed in practical terms, such as differences in exam results, additional days of school missed and additional use of health services. This will help policymakers assess the potential consequences of withdrawing support alongside the resources required to provide it.
Dr David Frayman
Drivers and impacts of growth in SEND provision in England: Evidence for successful reform
Demand for special educational needs and disabilities (SEND) support has grown rapidly in England, putting increasing pressure on schools, local authorities and the wider SEND system. As the government considers reforms, policymakers need better evidence about why demand is rising and what difference additional funding and earlier support make to children's lives.
This project will use linked education and health records to investigate whether rising SEND provision reflects changes in children's underlying health and educational needs, changes in how needs are identified and support is allocated, or a combination of these factors. It will also examine the effects of additional SEND funding on children's education and health outcomes, and explore the relationship between mental health, earlier support and SEND provision.
The findings aim to help policymakers better anticipate pressures on the SEND system and understand which approaches could improve outcomes for children.
David is a Research Economist at the London School of Economics Centre for Economic Performance.
View project details
This project aims to explore the following research questions:
- Have changes in children's underlying needs contributed to growing demand for SEND support in England?
- How have the types of needs identified, and the ages at which they are identified, changed over time, and how are these changes linked to demand for more intensive SEND support?
- What difference does additional SEND funding make to children's education and health outcomes, and which children benefit most?
- How does children’s mental health relate to SEND identification and outcomes, and what role can earlier identification and intervention play in improving outcomes and reducing pressure on classroom provision?
The methodology used in this study:
- The project will use ECHILD to examine linked, de-identified education and NHS records for children in England. Because children's health records are collected separately from schools' decisions about SEND support, comparing the two can help researchers understand whether rising SEND provision reflects changes in children's health and development needs, changes in how needs are identified, or a combination of both. The research will also examine how these patterns differ across England.
- To investigate the effects of additional SEND funding, the project will use a 'natural experiment': taking advantage of funding rules that result in otherwise similar areas receiving different amounts of funding. Comparing children's outcomes in these areas can provide stronger evidence about whether additional funding itself makes a difference.
- The project will also investigate the relationship between children's mental health, SEND identification and later education and health outcomes. It will explore whether differences in the availability of support between areas can provide evidence about the potential benefits of identifying mental health needs and providing support earlier.
Dr Nikki Luke
Siblings in contact with children’s social care
Research suggests that many children in England have contact with a social worker at some point during their school years. However, national administrative data has previously made it difficult to identify siblings, meaning we know much less about how children’s social care (CSC) supports different children within the same family over time.
This project will use ECHILD's mother–baby link to identify siblings born to the same mother and examine patterns of CSC involvement within families. It will explore which child and family characteristics are associated with different patterns of contact, and whether children's education, mental health and social care outcomes differ depending on whether their siblings also have contact with services.
A group of care-experienced young people, supported by the charity Become, will contribute their lived experience throughout the research. The findings could help policymakers and practitioners better understand families' needs and provide more timely and appropriate support.
Nikki is a Research Fellow at the Rees Centre, University of Oxford.
View project details
This project aims to explore the following research questions:
- What kinds of contact with CSC do siblings born to the same mother experience over time?
- What characteristics of children and families are associated with contact with CSC and with specific patterns of contact?
- How do social care, education and mental health (including stress-related) outcomes differ between children with no CSC contact, children who are the only sibling in their family to have contact, and children whose siblings also have contact?
- Can the approaches used to answer the above questions also be applied to a regularly updated London-wide dataset, including additional information available within that dataset?
The methodology used in this study:
- The project will focus on young people in England born between September 2007 and August 2008, and who started school Year 1 in September 2012.
- It will use ECHILD's mother–baby link to identify whether these young people have any siblings born to the same mother between 1997 to 2024. It will examine how many of these children had contact with CSC in 2005-2025, when it began, and what kind of support or intervention they experienced. This could include referrals, Child in Need Plans, Child Protection Plans or becoming a looked after child (for the latter, also looking at their placements in terms of type, length, and number). The research will use this information to identify common patterns of CSC involvement within families over time.
- It will then examine whether characteristics such as children's gender and ethnicity or family size are associated with particular patterns of contact.
- The project will compare outcomes for children whose families have different experiences of social care. These will include later CSC involvement, education outcomes such as exam results, and measures relating to mental health and stress.
- Finally, the project will work with researchers at Imperial College London to explore whether the approach developed using ECHILD can be applied to a more regularly updated London-wide dataset. This could allow future research to include additional information, such as other children living in the same household and healthcare information from GP records.
The project will also involve a group of care-experienced young people, supported by the charity Become. They will contribute their lived experience to the research, including helping shape the analysis, commenting on emerging findings and providing feedback on reports.
Dr Anna Leyland
Education and health outcomes for children with social, emotional and mental health needs
Around 350,000 children in England are identified as having social, emotional and mental health (SEMH) needs – a type of special educational need associated with poorer outcomes including school exclusion, placement in alternative provision, poor attendance and repeated school moves. However, there is no detailed national picture of when children are identified, what support they receive, or how their experiences at school relate to their health.
This project will map how SEMH identification, school support and experiences such as exclusion, absence and school moves unfold throughout childhood. It will examine how different educational pathways relate to children's use of hospital services and other health outcomes, and whether experiences differ according to factors such as poverty, gender, ethnicity and involvement with social care. The findings could help policymakers, schools and health services identify where earlier support could make the greatest difference and develop more consistent and equitable support for children with SEMH needs.
Anna is a Research Fellow at Manchester Metropolitan University.
View project details
This project aims to explore the following research questions:
- Who is identified as having social, emotional and mental health (SEMH) needs, when are they identified, and how does the support they receive develop over time?
- What are the typical educational pathways of children with SEMH needs, including their attendance, exclusions and experiences of alternative provision?
- How do these children’s educational pathways and support relate to health outcomes, including hospital admissions relating to adversity, stress, mental health and behaviour, pregnancy-related admissions and mortality?
- How do factors such as poverty, gender, ethnicity and involvement with social care relate to these educational pathways and health outcomes?
- How do patterns differ between local areas and across education and health services?
The methodology used in this study:
- The project will examine linked, de-identified school and hospital records for children in England. It will build a timeline for each child showing when they were identified as having SEMH needs, what support they received and what happened during their education, including attendance, exclusions, time in alternative provision and moves between schools.
- The research will use a method called sequence analysis to identify common patterns in children's experiences over time. This works by comparing children's individual journeys to identify groups who followed similar pathways – for example, children who experienced a particular sequence of SEMH identification, support and changes in school attendance. A related technique, clustering, will then group children with similar patterns together so that a small number of ‘typical’ pathways can be described.
- Once these educational pathways are mapped, the project will look at whether children who followed different pathways were more or less likely to end up in hospital for reasons linked to stress, mental health, adversity or pregnancy, or whether they were more likely to die before adulthood (compared to other children). This uses statistical methods called regression models, which estimate how strongly one thing (like being excluded from school) is linked to another (like a hospital admission), while accounting for other factors such as a child's age, background or area, so that we can be more confident the pattern isn't just coincidence.
- Throughout, the project will pay close attention to whether these patterns look different for particular groups of children — for example, boys and girls, children from different ethnic backgrounds, or children with a social worker, and whether groups of children vary from one part of the country to another.
An advisory group including teachers, health professionals and people with lived experience of SEMH will help inform the research and ensure findings are interpreted and communicated appropriately.
Previous research fellowships
Dr Hope Kent
Educational outcomes after paediatric brain injuries and the role of special educational needs support
Hope is a Postdoctoral Research Associate at the University of Exeter. Her project aims to understand how acquired brain injury impacts outcomes for children in the education system, and the role of special educational needs support in improving these outcomes.
View project details
This project aims to explore the following research questions:
- How many children present at hospital with an injury or illness indicative of acquired brain injury, and how does the prevalence of acquired brain injury vairy across different socio-demographic profiles?
- What special educational needs provision do children with acquired brain injury receive in schools?
- Are children with acquired brain injury more vulnerable to school exclusion, persistent absence, mental health difficulties, or poorer educational attainment?
- How does special educational needs support moderate the impact of acquired brain injury on these outcomes?
The methodology used in this study:
This study will analyse linked health and education data for all children born between September 2003 and August 2004 who attended a state-funded school in England. Hospital data will be used to identify any illness or injury indicative of an acquired brain injury (for example traumatic injuries, encephalitis, stroke, brain tumours). The research will try to understand the severity of these injuries from available hospital records, and will then look at education data to track outcomes longitudinally.
The methods used in this study will include:
- Tabular and graphical descriptive statistics, to understand the sample, and simple bivariate statistical tests to see whether there are differences in acquired brain injury prevalence between sociodemographic groups.
- Regression models to assess how outcomes (like being identified for special educational needs support) are impacted by the presence of acquired brain injury, and to assess whether sociodemographic profiles or geography are impacting these outcomes.
- We will complement the regression analysis with treatment effects methods for observational data (showing the difference in outcomes between a treatment group and a control group). This will ensure our analysis is robust against possible biases. We will use matching estimators including ‘Nearest Neighbour’ matching, and Propensity Score Matching.
Publications
- Blog: Looking for the hidden population of children with an acquired brain injury, February 2025
Dr Justin C Yang
Health-related outcomes, alternative provision, and exclusion among pupils with neurodivergent special educational needs
Justin is a Research Fellow at University College London. His project aims to provide new and high-quality evidence on educational and health risk factors associated with adverse outcomes among pupils with neurodivergent special educational needs in England.
View project details
This project aims to explore the following research questions:
- Are there regional or geographical disparities in adverse outcomes among pupils with neurodivergent special educational needs?
- What risk factors are associated with medically-related absenteeism, self-harm, and suicide among pupils with neurodivergent special educational needs?
- What risk factors, especially health care utilisation, are associated with alternative provision and formal school exclusion among pupils with neurodivergent special educational needs?
- Is it possible to identify the causal relationship between special educational need provision and suicide or self-harm among pupils with autism spectrum disorder?
The methods used in this study will include:
- Descriptive statistics will be produced to understand rates of adverse outcomes over time among pupils with neurodivergent special educational needs. Spatial analysis will also be used to understand any geographic variations in these outcomes. Because the data in this project is clustered (e.g. pupils attending the same school, schools based in the same local authority, etc), analyses will use multilevel modelling to account for this built-in structure.
- For binary outcomes (e.g. whether a pupil was formally excluded or not), logistic regression will be used to assess associations with risk factors; for outcomes which are counts (e.g. number of days absent due to a medical reason), Poisson or negative binomial regression will be used
- Data can often be missing or incomplete; this project will consider ways of dealing with missing data including complete case analysis (i.e. only analysing individuals for which all complete data is available) and multiple imputation, a technique for imputing or guessing at missing data.
- Attempting to identify a causal relationship between differential special educational needs provision and suicide or self-harm among pupils with autism spectrum disorder will use an approach called target trial emulation, a type of study design which seeks to simulate a randomised clinical trial using observational data.
Publications
- Blog: Linking data to improve outcomes for neurodivergent young people, June 2025
Dr Hanna Creese
How do mental and physical health problems contribute to inequalities in persistent school absence? A causal mediation analysis using ECHILD
Hanna is a Research Associate at Imperial College London. Her project aims to assess the relative importance of:
- maternal health
- family social service contacts
- young peoples’ mental and physical chronic conditions associated with social inequalities
in adolescent (11-18 years) persistent school absence and educational attainment in England.
View project details
This project aims to explore the following research questions:
- What proportion of young people experiencing repeated absence, poor attainment, or school exclusion have underlying chronic mental or physical health conditions documented in hospital records?
- How much of the association between family disadvantage and educational outcomes is attributable to family risk factors or underlying chronic mental or physical health conditions in young people that can be identified within the ECHILD dataset?
- Has the impact of health on educational inequalities changed since the pandemic?
The methods used in this study will include:
- To identify the characteristics of young people at risk of poorer educational outcomes, this project will calculate the proportion of persistent absence, low educational attainment, and exclusion within the ECHILD cohort. This will be done by deprivation level, history of maternal mental health difficulties, whether there has been social service contact with the family and whether the young person has a chronic mental and/or physical health condition (and its severity).
- The project will examine how much of the association between family disadvantage and educational outcomes is attributable to family risk factors or underlying chronic mental or physical health conditions in young people. It will then examine data over time to identify whether the impact of health on educational inequalities has changed since the pandemic.
Dr Xingna Zhang
Exploring the impact of clinical diagnosis on health and education outcomes for children receiving special educational needs support for Autism
Xingna is a Tenure Track Fellow at the Institute of Population Health, University of Liverpool. Her project aims to generate new knowledge about the impact of clinical diagnosis of Autistic Spectrum Disorder (ASD) upon inequalities in health and education outcomes for children in England.
View project details
This project aims to explore the following research questions:
- What factors influence whether children referred to Child and Adolescent Mental Health Services (CAMHS) receive a diagnosis of ASD?
- How does the likelihood of receiving a diagnosis differ based on factors like socioeconomic background and ethnicity?
- How does the support provided for special educational needs in schools affect the relationship between receiving an ASD diagnosis in CAMHS and children's health and education outcomes?
- How do these effects above vary depending on factors like socioeconomic background and ethnicity?
- How can the services provided by CAMHS and special educational needs support be improved based on the findings of this research, to help reduce differences in outcomes for children from different backgrounds?
The methods used in this study will include:
- This project consists of three connected work packages, using a wide range of research methods including advanced statistical analysis and actively engaging multiple stakeholders.
- The first work package aims to find de-identified data on groups of children diagnosed with ASD from referrals in CAMHS, and understanding what factors predict this diagnosis, including socioeconomic and ethnic differences. Eligible children will be followed from 2016 to 2022 to reveal various factors related to their diagnosis, such as why they were referred, the type of service they received, and their age at diagnosis. This will help us understand how many children are diagnosed with ASD, their characteristics, and any inequalities.
- The second work package intends to understand how being diagnosed with ASD and receiving special educational needs support at school affects children's health and education outcomes. To begin with, this work package will find out how being diagnosed with ASD affects the level of support children receive at school, and how this varies by ethnicity and socioeconomic background. Additional research can then be conducted to find out how ASD diagnosis and special educational needs support affect children's exam scores and use of mental health services.
- The third work package explores why some children with ASD have worse health and education outcomes than others, and how to reduce these inequalities. This can be achieved by working with local health and education services and ASD communities to understand how these systems work and how decisions are made. By identifying gaps in the current systems, suggestions can be made on ways to improve support for children with ASD and reduce inequalities in their outcomes. Such findings will be shared with local services and communities to help them make informed decisions about supporting children with ASD.
Publications
- Blog: Does an autism diagnosis help children and young people? Insights from doctors and lived experience, December 2025
Dr Amanda Mason-Jones
Maternal mental health, child health & emergency department utilisation: Impact on children's education and development outcomes in England
Amanda is an Associate Professor at the University of York. Her project will explore how the mental health and wellbeing of mothers and birthing parents in England affects their children's health, development, and education.
View project details
This project aims to explore the following research questions:
- What factors drive mothers’/birthing parents' engagement with mental health services before and during pregnancy?
- What factors influence mothers’/birthing parents' use of emergency department services during pregnancy?
- Are perinatal mental health issues and emergency department visits during pregnancy linked to subsequent child health, development, and educational outcomes?
The methods used in this study will include:
First, some basic facts about the mothers, parents, and their children will be gathered using the de-identified data, such as ages or other characteristics like the region they live in. Simple mathematical tools (like averages and percentages) will be used and charts will be created to understand this information more clearly. It will also be possible to analyse geographical differences to see if certain areas have different outcomes in terms of health or education.
Next, more detailed analyses will be performed to see if we can predict certain outcomes. For example, it will be possible to check if mothers who visited the emergency room during pregnancy are more likely to have children who do well in terms of their development and early education. Methods will also be used to break down the data into groups who might be more or less at risk and find patterns that could help us predict these outcomes more accurately.
Finally, these prediction models will be assessed to see if they can be used in real life to identify mothers or children who might need extra support. The project may simulate a clinical trial to better understand how accessing mental health services affects the health and wellbeing of both mothers and their children’s development and educational outcomes.
Publications
Dr Simona Skripkauskaite
Pathways through support services in neurodivergent children and young people who develop mental health conditions
Simona is a Research Fellow at the University of Oxford. Her project aims to provide a clearer picture of pathways through educational support, social care, and health services available for neurodivergent children and young people who develop mental health conditions.
View project details
This project aims to explore the following research questions:
- When do neurodivergent children and young people who develop a mental health condition first engage with any existing educational support, social care, and health services?
- When do these children first engage with each type of educational support, social care, and health services?
- Does the time to and likelihood of service engagement (overall and for specific services) differ between neurodivergent and neurotypical children and young people who develop a mental health condition
- Does the time to and likelihood of service engagement (overall and for specific services) differ between neurodivergent children and young people who develop a mental health condition and those without a mental health diagnosis?
The methods used in this study will include:
This project research project will be delivered in three stages:
- The first stage will involve data exploration and recoding. The quality of the information recorded in the Mental Health Services Data Set will be assessed to determine if it could be used to define each child’s neurodivergence and mental health diagnosis status. If not, social and education data will be used to complement this information. Three comparison groups will be identified:
- neurodivergent with a mental health diagnosis
- neurodivergent without a mental health diagnosis
- not neurodivergent but with mental health diagnosis.
- Descriptive statistics will then provide a first insight into the data and preliminary comparisons across groups. This analysis will provide a general overview of differences in the type of services children and young people are in contact with and how that varies based on demographic characteristics (gender and ethnicity).
- Time to event analysis (or survival analysis) is a collection of statistical procedures that estimates the amount of time it takes before a particular event of interest occurs. The project will use this analysis to estimate and compare how long it takes for the children and young people in different groups to first come into contact with any support services and then how long it takes for each support type.
The project will actively engage lived experience advisors (such as neurodivergent young people and their parents) and policymakers (such as local commissioners) throughout the research lifecycle.
Publications
- Blog: A roadmap to better support for neurodivergent children, March 2025
Dr Yasmin Ahmadzadeh
Women’s mental illness in pregnancy: Exploring contact with secondary mental health services and links with offspring health and education outcomes
Yasmin is a Research Fellow at King’s College London. Her project aims to contribute new knowledge on how mothers’ contact with secondary mental health services during pregnancy relates to their children’s health and developmental outcomes in England.
View project details
This project aims to explore the following research questions:
- Who accesses secondary mental health services during pregnancy in England, and are there inequities in perinatal mental health and service access?
- Can data be linked for sibling pairs born to mothers who accessed secondary mental health services during pregnancy in England, and how might this support intergenerational family research?
- What are the health and education outcomes for children whose mothers accessed secondary mental health services during pregnancy in England?
- How can this data be used to identify causal pathways - for example, does prenatal stress exposure cause changes in child health and development?
The methods used in this study will include:
The project will begin by identifying adult women in the ECHILD dataset who had contact with secondary mental health services (indicating severe mental illness) during pregnancies in England between April 2010 and March 2022. It will compare women who had contact with secondary mental health services to those who did not, looking at factors such as socio-demographic and economic characteristics, types of care contact, pre- and postnatal care contacts, and changes over time.
Next, the project will develop a linked mother–offspring dataset including information on children’s birth, health, and education outcomes. These mother–child data linkages will be checked for accuracy, and a family cohort will be created by identifying the number and year of birth for children born to each woman.
Finally, the project will examine how exposure to mothers’ severe mental illness in pregnancy relates to pregnancy complications and children’s subsequent health and education outcomes. It will also explore methods for testing whether these associations represent causal pathways - for example, using a sibling comparison design, which compares children within the same family who experienced different exposures in pregnancy.
Categories: Research using linked data, ADR UK Research Fellows, ADR England, Office for National Statistics, Children, young people & education, Health & wellbeing, Social mobility & inclusion
