By Chris A Garrington, on 20 July 2021
by Fran Abrams
Census data from the ONS-LS has helped shed new light on outcomes for children who have been in care in a major research project led by the UCL Institute of Epidemiology and Healthcare. The study uses Census data to push forward the boundaries of knowledge by looking at what happens in mid-life to those who have been in care as children. It finds disturbing disparities – with some groups faring much worse than others.
Care-leavers have long been known to suffer worse outcomes than their peers. Now a programme of research funded by the Nuffield Foundation has highlighted the ways in which these issues continue throughout the lives of those affected. At an event to share the project’s findings with those interested in improving the lives of children who cannot live with their parents, Josh MacAlister, who is leading an independent review of children’s social care, said the research had already had a major impact on its work.
It is actually breaking new ground in our understanding of where care-experienced people end up in later life,” MacAlister told an audience of more than 200 practitioners, policymakers and academics.
“One of the questions we pose is: ‘How many parents don’t know where their own child is at 30, 40 or 50?’ It’s a common refrain that the state is the corporate parent, and actually not knowing really basic things about destination and outcomes for care-experienced people later on into life has been a huge blind spot. So this study is very significant in that respect,” he said.
Raising the bar
The Government review led by MacAlister was launched earlier this year with the aim of ‘raising the bar for vulnerable young people across England.
The UK’s National Statistician, Sir Ian Diamond, who chaired the event, told the audience the care research was an exemplary use of data from the ONS-LS dataset.
Sir Ian highlighted a key issue for those studying children’s social care: the evidence shows those who have been in care suffer worse outcomes than their peers – for example higher than average levels of unemployment, lower levels of educational qualification and early pregnancy. But that research tends to focus on recent care-leavers while this project follows them into mid-life.
The project, led by a team of researchers at University College London, used Census data from the ONS-LS to explore outcomes for those who experienced care from the 1970s onwards, up to the age of 50.
The ONS-LS has gathered information on approximately a million people, and from this the researchers were able to look at a sample of just under 500,000 children. Of those, around 3,500 were looked after by family members other than their parents, 2200 were in formal foster care and 900 in residential care. Over time, residential care had become less common and family or kinship care more so.
There were four main aims of the research:
- To determine whether children who had experienced care had worse health and social experiences from 10 to 40 years later, compared to others.
- To explore whether children in residential care did better or worse than children in foster or kinship care.
- To look at care differences related to gender, ethnicity or migration status.
- To investigate trends and look at whether longer-term outcomes had improved over time.
Amanda Sacker, Professor of Lifecourse Studies, Epidemiology and Public Health at UCL, who led the study, told the launch one of its strongest findings was that inequalities within the cared-for population were as great as inequalities between that group and those in parental care.
Impacts of a childhood in care
The research found the impact of being in care on health, socio-economic circumstances, family life and living arrangements varied according to the type of care experienced – those who were cared for by relatives had the best outcomes and those who had been in residential care the worst, with foster care sitting between the two.
This did not necessarily mean the type of care had led to better or worse outcomes, Professor Sacker explained at the event – those who were most vulnerable or damaged by early experiences might be more likely to go into residential care rather than family care or a foster home.
In relation to employment there was some evidence these inequalities between care groups reduced with age, though adults in their 20s were twice as likely to be employed if they had been in their parental home rather than in residential care.
Social inequalities between care groups also extended to the age of death: while those brought up by parents had become less likely to die prematurely in the past 30 years, this was not true for those in non-parental care. Those in care in 1971 were 30 per cent more likely than average to die but by 2001, this ratio had grown to more than 300 per cent, most commonly from preventable causes such as car accidents, alcoholism and assault.
When the researchers looked at education, they found a similar picture: those in parental care had a 28 per cent chance of achieving an NVQ level 3 qualification compared with just 11 per cent for those in residential care. There was some good news, though – the care groups were more likely to be in education later in life, and this helped them to catch up with their peers.
The project’s findings on ethnicity were more mixed. White and south Asian groups were found to have worse outcomes if they had been in care, but for black children the study found having been in care did not seem to be associated with any additional detrimental effect over and above the inequalities seen for all black children. The researchers said more investigation was needed into this complex picture.
The final key findings of the study were on the children of those who give care. They too, it found, were affected by their experiences – there had been reports that the children of foster parents or of kinship carers had felt disadvantaged.
The research looked at five ‘transition milestones into adulthood: leaving education, leaving home, starting work, forming a relationship and becoming a parent. It found children of care-givers were less likely to have higher qualifications, more likely to be unemployed, more likely to be married early and less likely to own their own home than others. If they were female, they were likely to be younger when they had their first child.
“Our work in the field of life course social epidemiology has highlighted that inequalities in health cannot be reduced without tackling social inequalities too,” Professor Sacker said. “By shining a light on the life courses of children who have had to be placed in care, our aim is to get it right for care leavers.”
Sir Ian Diamond said the Office for National Statistics was keen to make more use of longitudinal data such as the ONS-LS to help inform policy on issues such as this one.
“Among the most disadvantaged in society are clearly those young people and children who have experienced care, and care leavers, we know empirically, have not had great outcomes. It’s always seemed to me that we needed better longitudinal data to understand the pathways that would help us to inform policy, which could improve the outcomes for people who are under-achieving because they have been let down early in their lives for all kinds of reasons. So it seems to me there’s an enormous need for this work,” he said.
Tim Gardam, Chief Executive of the Nuffield Foundation, said the research fitted very well with its aim of viewing social wellbeing primarily through the lens of the experiences of the most disadvantaged and vulnerable.
“What we find here is the ONS-LS using Census data from five decades, painting a vivid and complex picture of vulnerable people’s lives and their health and social outcomes that in places brings the reader, quite frankly, up short in shock.
“We have known for a long time that being in care as a child is associated with poorer outcomes in adulthood. But most research has previously ended with young adulthood and been based on small population samples. This research documents people’s lives in their 40s and enables us to understand the longer-term effects,” he said.
The lifelong health and wellbeing trajectories of people who have been in care: Findings from the Looked-after Children Grown up Project, is by Amanda Sacker with Emily Murray, Rebecca Lacey and Barbara Maughan. It is published by the Nuffield Foundation.
By Chris A Garrington, on 25 June 2021
by William P Ball
Again and again, research has shown that health outcomes vary between groups of people. These differences appear when we group people based on where they live, the type of job they do, their level of education, their sex or race/ethnicity.
When these differences are systematic, avoidable, and unfair we call them inequalities.
Geographic inequalities, often measured by the level of deprivation experienced by groups of people in small residential areas, are clear. Recent figures show that life expectancy in the least deprived areas of England is considerably higher than in the most deprived areas – although women live longer, both sexes can expect to live into their seventies in the poorest areas and into their eighties in the richest.
Understanding the mechanisms which produce these inequalities is incredibly important for researchers and policymakers. If we understand what drives these avoidable and unfair differences in health, we can start to design policies which aim to reduce them.
My research project looks at the self-rated health of nurses – understanding this group, and how they experiences inequalities, is important for a number of reasons. It’s useful to understand their health in terms of planning around health care workforce and service delivery, but also to understand factors influencing health for the rest of the population.
Nurses are the biggest health workforce in the UK, with over 680,000 currently registered with the Nursing and Midwifery Council, and theyare a central part of the health service. Even with recent growth in the profession, the NHS in the UK has around 40,000 vacancies for nurse jobs and the workforce is ageing. If we can understand the health of nurses and reduce the number leaving the profession due to ill health, that will contribute to maintaining and improving patient safety. In the current context of COVID-19, where the NHS and its workforce has experienced huge pressure, the relevance of studying the health of healthcare professionals, for their sake, has become even more clear.
But the health of nurses isn’t only relevant to nurses themselves. Nurses have socioeconomic characteristics which should protect their health and they are also rather similar to one another – roughly 90 per cent are female and they are generally in a stable job which requires degree-level education. They also have higher levels of home ownership and are less likely to live in the most deprived areas.
The design of my project uses this similarity in socioeconomic characteristics of nurses to act as a sort of control – reducing the impact of variation between individuals to better isolate the effects of other variables, like area deprivation, on health,. This is like studies looking at differences in health outcomes in siblings or twins, which assess the health trajectories of people living with similar characteristics, in very similar conditions. This type of design is chosen to reduce the effect of confounding, where other variables influence the exposures and outcomes being studied.
Nurses also have very high levels of health literacy and knowledge of healthy behaviours. Their curriculum includes teaching on modifiable risk factors for disease, such as smoking, or lack of exercise – and many Nurses see first-hand the outcomes which are caused by such behaviours. We might expect that such a population would generally have better health and that its characteristics would protect it against inequalities. We can also investigate a counterfactual question – what would population health look like if we all had similar characteristics as nurses?
The Office for National Statistics and Scottish Longitudinal Studies (ONS LS and SLS) offer the opportunity to use individual-level data from on Census records, which have been linked to administrative data such as births and causes of death. They offer detailed data on a large and representative sample of the British population which can also link individual records to other sources of information such as deprivation measures.
Although the data held in each LS is only accessible in safe settings due to data protection concerns, a process called eDatashield has been developed to allow researchers to simulate ‘combined’ analysis. Raw data cannot be removed from the Secure Research Service computers in the ONS building in London or the safe haven at the National Records for Scotland offices in Edinburgh. However, eDatashield allows some types of analysis to be conducted by passing anonymised summary statistics to a computer which holds none of the original data. This approach has been used in my project to conduct cross-national analysis, to understand the role area deprivation plays in health differences between Scotland and England & Wales.
Preliminary results from this study suggest that self-reported health is patterned by area deprivation for non-nurses and nurses alike and that inequalities are present for both groups.
Roughly 90% of nurses appeared in the highest grouping for a measure of educational level, largely due to the inclusion of professional registration in this group. Nurses also had higher representation in the least deprived areas, but crucially nurses still lived in areas covering all levels of deprivation. 58% of nurses stated they have ‘very good’ health, with only 51% of non-nurses replying the same. Nurses reported a higher proportion of ‘very good’ self-rated health at all levels of deprivation compared with non-nurses. However, both groups displayed a social gradient in this – the proportion self-reporting ‘very good’ health increased when comparing from most to least deprived quintile. However, the gradient for nurses in less ‘steep’, meaning the differences between most and least deprived areas is smaller.
From these early results we can see that nurses generally have better health outcomes than non-nurses. That makes sense given their individual characteristics and that levels of wealth in the area where we live also affects our health. The crucial finding though is that social inequalities in self-rated health, although reduced, still exist within the nursing profession – even in a highly educated group with high health literacy the conditions in which we live influence patterns in health.
The challenge of health inequalities has been clear for decades and current trends in the United Kingdom are worrying. Improvements in life expectancy in the UK, growing consistently over the past century, began to stall from 2012 onwards. This pattern is largely a result of slower gains for those in the most disadvantaged groups, and we have even seen reductions in life expectancy for women in these groups. Reducing inequalities which are systematic, avoidable, and unfair is better for everyone, but especially so for the most vulnerable people in our society.
Highly detailed datasets like the ONS LS and SLS, which are largely representative of the total population and can be linked to other information, can play a central role in the future of health inequalities research. Their use also allows some innovative research design which can help us better understand population health in the UK and ultimately inform policy actions which can make our society fairer.
The permission of the Office for National Statistics to use the Longitudinal Study is gratefully acknowledged, as is the help provided by staff of the Centre for Longitudinal Study Information & User Support (CeLSIUS). CeLSIUS is supported by the ESRC Census of Population Programme under project ES/K000365/1. The authors alone are responsible for the interpretation of the data. This work contains statistical data from ONS which is Crown Copyright. The use of the ONS statistical data in this work does not imply the endorsement of the ONS in relation to the interpretation or analysis of the statistical data. This work uses research datasets which may not exactly reproduce National Statistics aggregates.
By Chris A Garrington, on 19 March 2021
This weekend (Sunday March 21, 2021) we will all be asked to fill in our census forms. There’s a key difference this time: the Office for National Statistics, which runs the operation, is aiming for at least 75 per cent of our returns to be submitted online, and the early signs are that millions of people have already responded.
What difference will this make? We do have some information, because the option to complete the Census online was also offered in 2011 – around one in six people opted to do so.
And why does it matter that as many people as possible fill in their returns? I help to run the Office for National Statistics Longitudinal Study, a huge resource based on a one per cent of Census returns since 1971: more than a million individual records. Access to the Census data allows us to build a rich picture of people and places in England, to help us look at what’s happened over time and to anticipate what might happen in the future. So it matters a great deal.
It matters that we get as many people completing online as possible, because that will help the data to be gathered and processed more quickly than has been the case in previous censuses.
And it also matters because we know that without targeting, some groups could be under-represented in a Census which takes place mainly online. Prior to the pandemic, there had been plans to hold events – in schools and local libraries for example – to help people complete the census online if they couldn’t do it at home. Obviously now that can’t happen. The census agencies have provided paper forms to all people in areas that think have poor internet provision, or who are less able or willing to complete online. But there’s obviously a risk that some people might be confused, and may not realise how they can request a paper form.
By Chris A Garrington, on 18 March 2021
Back in the late 1960s there was concern that policymakers had too little information about births and deaths: death certificates recorded only limited information and even the occupation of the deceased could be recorded inconsistently. Similarly it was impossible to use information from birth registrations to look at patterns of fertility – how were children spaced within families, for instance? And so the ONS Longitudinal Study was born.
The 1971 Census had recorded respondent’s date of birth – as opposed to age – for the first time. And that allowed statisticians to record data on a one per cent sample of the population – all those born on four dates of birth which were, and remain, a closely-guarded secret.
The ONS Longitudinal Study now holds records for more than a million people, none of whom have any idea that they are a part of the study. It’s only possible to join through being born in the UK or through migrating into it, and it’s only possible to leave by dying or emigrating. The study also holds information for those living with its members, but it doesn’t follow them up in the same way from census to census.
Similarly, the information provided on birth certificates did not allow for studies of birth spacing. Although such data could be obtained from the General Household Survey (GHS), the total sample sizes were too small for detailed studies.
By Chris A Garrington, on 9 March 2021
By Nicola Shelton
When the 2021 census was first planned, we thought some of the biggest research questions to emerge from it would be around the effects of Brexit. But while those are still live, researchers and others will be watching with interest to see what this snapshot of Britain in 2021 will tell us about the effects of Covid-19.
It will be two years before new data begins to emerge from the March 2021 Census – and by then we hope the world will be quite a different place. But what will the ONS Longitudinal Study tell us about the pandemic, and about the changes it has wrought on all our lives?
One of the biggest questions will, sadly, be around mortality data. While the grim daily totals have told us about those who have died, and what their current or last occupation was when they died, the LS can link that mortality data with other information about the whole lives of those who have died. Because we have information going back to 1971, we can know where those people lived, what jobs they had done and what types of families and households they had lived in. It will give us a much richer picture of the complex reasons why some groups appeared to suffer more than others in the pandemic.