We know cancer incidence is linked to socio-economic status, but that this differs according to types of cancer. In the second of three blogs on research using the ONS-LS to explore cancer and social status, Charlotte Sturley has examined diagnoses of bowel cancer, and found some clear evidence of a social effect.

Bowel cancer – also known as colorectal cancer – is the fourth most common cancer in the UK. Over 42,000 people are diagnosed with it in the UK each year so it is a major public health problem. 

Cancer incidence varies between different groups of people, and differences have been found based on gender, age, ethnicity and where people live.   

In England, for most cancer types, incidence is higher in the most deprived areas compared with the least deprived. The deprivation gap is largest for lung cancer, reflecting the fact that more deprived groups are more likely to smoke. Conversely some cancer types, such as breast cancer in females and prostate cancer in males, are more common in the least deprived areas.

The association between colorectal cancer and deprivation is less clear, and findings from previous studies have been inconsistent. In the 1980s, affluence was associated with an increased risk of colon and rectal cancer in Europe. But more recently, evidence has emerged of links between this type of cancer and living in a deprived area.  

Understanding the causes

Given this apparent shift in the relationship between socio-economic deprivation and colorectal cancer, it is important for researchers to monitor recent data to see if the patterns are changing. We also need to understand the extent to which inequalities are associated with both individual and area-level factors to better target their underlying causes.

Most research on inequalities in cancer incidence has focussed on indicators of deprivation at area level, largely because cancer registries do not collect data on indicators of socio-economic position, such as the patient’s level of education or occupation.

Using Census Data to dig deeper

The Office for National Statistics Longitudinal Study (ONS LS) offers the opportunity to investigate variations in cancer incidence using information gathered in the census on individuals’ socioeconomic positions. My study used measures of educational attainment, occupational social class and housing tenure, along with an area-based measure of deprivation called the Townsend deprivation score. 

My sample were LS members who were present at the 2001 Census and were aged 50 years or over, as incidence of colorectal cancer is very low among people aged under 50. 

Among the study sample of 178,116 individuals present at the 2001 census, there were 4,418 cases of colorectal cancer recorded by the end of 2015. Because the ONS LS links census responses to cancer diagnoses, we could measure the average length of time between the 2001 census and the diagnosis.

Results

The study found evidence of socio-economic inequalities in colorectal cancer incidence and that these differences varied by indicator of socio-economic position. LS members with a degree were less likely to have a colorectal cancer diagnoses compared to those without a degree, after accounting for differences by age, sex, ethnicity and area deprivation. A statistically significant association was also observed between housing tenure and colorectal cancer incidence, but only for those in social rented housing, who were at an increased risk of colorectal cancer compared to owner-occupiers.

Those employed in manual occupations were more likely to have a colorectal cancer diagnosis, compared to those in non-manual occupations – however this association was not statistically significant when adjusted for other variables. There was no statistically significant difference in colorectal cancer risk among study members in private rented accommodation compared to those in owner-occupied housing. No significant variation in colorectal cancer incidence was found by the level of area deprivation.

So, we can say individual measures of socio-economic position based on educational attainment and housing tenure are associated with colorectal cancer. My finding that there is not a link with area-level deprivation differs from other recent research which reported an emerging association between this type of cancer and deprivation, measured at the area-level. But these other studies used a different measure of deprivation which means comparisons are more difficult. The longitudinal nature of the LS data and the long-follow up period enabled time-to-event analysis to be employed in my study, whereas previous studies have tended to be more of a snapshot.

Not all individuals living in deprived areas will experience the same level of deprivation, and that could explain why I did not find area effects even though I did find individual ones.

Risk factors

One explanation for an association between colorectal incidence and socio-economic position could be different levels of exposure to risk factors such as poor diet or smoking. There is strong evidence to link socio-economic disadvantage with such behaviours.

My study highlights the complexity of the relationship between socio-economic circumstances and health outcomes and the need to investigate socio-economic inequalities by a range of different indicators in order to implement targeted policy interventions to reduce cancer incidence.

Future work

An interesting next step using the LS would be to investigate if and how change in individual socio-economic position and area deprivation over a person’s lifetime might influence their risk of having a colorectal cancer diagnosis. Linking the LS to data from the bowel cancer screening programme to investigate the impact of screening on colorectal cancer incidence and socioeconomic inequalities would also provide valuable insight.

Further information

Charlotte Sturley, who carried out this study as part of her PhD research, presented the work at the 19^th International Medical Geography Symposium 2022, which is being held at the Royal College of Surgeons of Edinburgh from 19^th-24^th June

Her presentation is available here: (PDF) Contrasting socio-economic influences on colorectal cancer incidence and survival (researchgate.net)

Read the full paper

 

How does our social environment influence our chances of getting cancer? New research using Census data by Professor Robert Hiatt and colleagues shows there is a link between socio-economic status and cancer incidence, but also throws up some unexpected findings. In the first of a series of three blogs on socio-economic links to cancer, he discusses his work.

It’s well known that specific health outcomes are affected by socio-economic status – for instance the Whitehall IIlongitudinal study of civil servants clearly demonstrated this relationship as did subsequent Marmot reviews including the 2010 Marmot review of health inequalities. Recent research using the ONS Longitudinal Study has shown us in more detail the connections between socio-economic status and cancer survival, but we also wanted to look at how our background might be connected with the onset or incidence of different cancers as well as with their outcomes.

We now know that people from more deprived backgrounds have lower survival rates when they have cancer, although the causes of this are multi-faceted. We know that those with higher social status have access to critical knowledge, money, power, prestige, and social connections, which plays out to their benefit for cancer as well as any number of other health outcomes. There is a complex interplay between these fundamental aspects of their lives and their incomes, occupations, education, income, education, culture migration status and sexual orientation.  And that in turn affects the material resources they have, their food security, their internet access, the type of healthcare they can access, their exposure to discrimination and stigma, and the support networks on which they can rely.

Those with lower socio-economic status on the other hand are missing out on many of the fundamental underpinnings leading to good health and in addition are more likely to be exposed to things like environmental toxins and climate change. In some cases, they may also be more likely to adopt unhealthy behaviours, such as smoking or a lack of physical activity. So, when it comes to the social determinants of cancer, the picture is multi-level, complex and a challenge to understand.

The ONS-LS can’t tell us everything about the possible links between social determinants and cancer, but it does allow us to look at different types of cancer diagnoses by occupational status, level of education and household characteristics, as well as by the type of area in which a person lives.

We were able to take data on almost 140,000 individuals who were alive in 1971, based on a one per cent random sample from the census, and look at the types of cancer diagnoses among them taking into account some of these social factors.

Two major questions

We asked two major questions: How does socio-economic position, measured both by area of residence and by individual characteristics, relate to cancer incidence and mortality? And how do social factors such as education, social class, occupation, home location and prior health status contribute to the relationship between socio-economic position and cancer outcomes?

We looked at all the major types of cancer – the biggest are lung cancer, breast cancer, colorectal cancer and prostate cancer. Overall incidence (onset of new cancers) tended to be higher among those with lower socio-economic status.  But of course, behavioural factors such as smoking could be instrumental in that relationship and there is no data on smoking status in the ONS LS. So we looked again after eliminating those cancers with links to tobacco – and still found the same effect.

When we looked at individual cancers rather than overall rates, a rather different picture emerged. For those from lower social groups, there was a higher risk of being diagnosed with lung cancer, cervical cancer and stomach cancer. But those groups actually had a lower likelihood of contracting breast cancer, prostate cancer or melanoma. The relationship went in opposite directions depending on the cancer site. There were some also major cancers including colorectal cancer for which there wasn’t a clear social pattern.

We examined this relationship both through the lens of respondents’ income and education, and by the area in which they lived, and we came up with similar findings.

The implications

So what are the implications? At this stage, the full picture isn’t clear. We can say that overall, those from poorer backgrounds are more at risk of contracting cancer. And we know the reasons for that are complex. Lung cancer is certainly linked to smoking, so that must be a factor – and these social groups may also have higher exposure to the human papillomavirus (HPV), the major cause of cervical cancer, or to H. pylori bacteria, which live in the digestive tract and are linked with gastric cancers.

We can also say that those from wealthier backgrounds are more at risk from certain types of cancer. We may speculate that in some cases there will be behavioural and social factors at work – for instance, women who have children later in life or remain childless are at greater risk of breast cancer. These may tend to be the more highly-educated women who want to pursue their careers. But at present we don’t have any good theories on why prostate cancer might be more common among men from higher socio-economic groups. So our research raises questions as well as answers.

Our measures of individual socio-economic position are based on crude categories of income, education and occupational status, but may not give us a full picture. And we haven’t yet interpreted our findings in the context of the societal changes which has taken place since 1971.

There is much more work to be done in this area. We plan to publish three papers; one on socioeconomic status and cancer incidence, a second on socioeconomic status and mortality and a third comparing incidence with mortality. There will be detailed studies of individual cancers, too – so the ONS-LS will continue to prove a rich resource for cancer researchers in this and other areas.

Robert Hiatt’s presentation on Social Gradients in Cancer Incidence (and Mortality): the ONS Longitudinal Study was given on May 23, 2022 at University College London, and was based on forthcoming research with Nicola Shelton, Wei Xun and Eduardo Santiago-Rodriguez.

by Fran Abrams

Three pieces of research using the ONS Longitudinal Study were cited in the recent report of the Independent Review of Children’s Social Care. The findings from the Looked After Children Grown Up project played a key part in providing evidence to the review – and were reflected in its report and the Government’s response.

The government’s 2019 Manifesto included a commitment to a review of the care system, and in March 2021 the independent review of children’s social care, led by Josh MacAlister, was given a year to produce a report.

The Looked After Children Grown Up project, which was funded by the Nuffield Foundation and led by Professor Amanda Sacker with colleagues at the UCL Institute of Epidemiology and Health Care and Kings College London, had already begun in February 2018 and was able to provide important evidence to the review.

The adverse consequences of being looked after as a child were already well recognised, but this research project was set up to address a lack of evidence on what happened to looked-after children later in life. Studies tended to follow them into early adulthood and no further, but using census data from the ONS Longitudinal Study the researchers were able to explore outcomes for those who experienced care from the 1970s onwards, up to the age of 50.

The study allowed researchers to track those who were children at the time of each census, and to identify whether they were living in residential care,  as an unrelated member of an individual household, as a biological or adopted child in a parental household or as a child in a relative’s household.

By tracking care-experienced children into mid-life, the project was able to look at their later outcomes from a variety of different angles: it was able, for instance, to look at their likelihood of long-term illness, their employment, their education, their housing tenure, the type of family relationships they had and even whether they were at greater risk of dying early.

A fuller picture

The research, which was shared with Josh MacAlister at an event last July, was also able to drill deeper into the later experiences of children who experienced different types of care: it compared the outcomes of those who experienced residential and foster care with those who remained living with relatives, both parental and other.

Findings from the project were shared in an earlier Linking our Lives blog, and were welcomed by Josh MacAlister at the event last Summer.

In his report he focused on many aspects of the research, both citing it explicitly and reflecting its findings in his narrative.

The review

In particular, he focused on a 2021 report from the study which showed lower rates of long term illness and higher rates of employment for adults with a history of kinship care compared to those that grew up in foster or residential care.

He also highlighted  a second report from the team which showed that care leavers who were in residential care had the highest prevalence of limiting long term illnesses (around 32 per cent on average), followed by adults who lived in foster care (around 16 per cent on average) and adults who lived in kinship care (12 per cent on average). This was significantly higher than the average prevalence of limiting long term illnesses amongst individuals who had not been in care (7 per cent) , he said.

The review report also focused on mortality rates among care leavers from different types of care, and cited a 2020 report which used the ONS Longitudinal Study to link childhood out-of-home care status with all-cause mortality up to 42-years later.

It highlighted findings which showed adults who spent time in care between 1971-2001 were 70 per cent more likely to die prematurely than those who did not, and were also more likely to experience an unnatural death through self-harm, accident, mental or behavioural causes.

The review report made a number of recommendations which chimed with the research findings, including:

• Support for families to cut down referrals and help to keep children in their family homes or with relatives – £2 billion over five years.
• Unlocking wider family support networks including payments for relatives to act as foster carers.
• Support for a ‘new deal’ with foster carers to help larger numbers of children to be cared for in families rather than in residential care – 9000 new carers over three years.

The response

In his response for the Government, the Education Secretary Nadim Zahawi promised more support for family hubs which offer early help and intervention. This would add seven new areas to an existing network of centres in 75 areas that receive a £302 million pot of funding for family hubs. A further 5 areas would receive part of a £12 million investment to deliver on a manifesto commitment to a network of family hubs around the country, he said.

Addressing concerns about the educational outcomes of children who had been in care – the research found 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 – Mr Zahawi promised funding for local authorities to help them keep vulnerable children in education.

Funding would be provided to local authorities for continued delivery of the Social Workers in Schools and designated safeguarding lead supervision programmes, which launched in September 2020, he added.

An evidence-based approach

In both the review report and in the Government’s response, there was a strong focus on the need for reforms to be underpinned by evidence.

The review suggested the Office for National Statistics should collect and report data on the mortality rate of care leavers and care leaver health outcomes, and that the Government should also launch a new cohort study which tracks the health outcomes of care experienced people and helps to gather other missing data on housing, education and employment outcomes.

In his response, Mr Zahawi promised support to help the most at-risk families to stay safely together, and a focus on early help, preventing them from reaching crisis point.

As part of this, he said, the government would set up a new National Implementation Board of sector experts and people with experience of leading transformational change and the care system. This would boost efforts to recruit more foster carers, increase support for social workers including on leadership, recruitment and retention, improve data sharing, and implement a new evidence-based framework for all the professionals working in children’s social care.

“Everything we do to raise the outcomes for children and families must be backed by evidence,” he said. “This report will be central in taking forward our ambition to ensure every child has a loving and stable home and we will continue working with experts and people who have experienced care to deliver change on the ground.”

The Looked After Children project involved Professor Amanda Sacker, Dr Emily Murray, Professor Barbara Maughan and Dr Rebeccca Lacey. 

by Fran Abrams

Adults who have reached higher levels of education have parents who live longer – even when comparing families from similar social backgrounds. But is this a consequence of education? A study using Census data sheds new light on the issue.

Those with better education have better health and live longer – this has been known for a long time. A more recent finding is that this extends across generations: those with better education also have healthier parents. And in times of ageing population and stark generational divides, policies with intergenerational benefits are urgently needed. Improving the education of a younger generation at the same time as enabling an older generation to live longer and healthier lives: if this was possible, it would be very attractive for policymakers.  Moreover, framing education as a family resource could help convince older generations that such investments in young generations are beneficial even for them.

There is a big question about this, however: Is it really adult children’s education that improves parental health, or is it just that healthier parents have better-educated children?  Research using the ONS Longitudinal Study addresses this key question.

Two data sets

The researchers used two sets of UK data to examine the question: the 1958 birth cohort called the National Child Development Study (NCDS) and the ONS Longitudinal Study (ONS-LS) based on English and Welsh census data.

First, using the NCDS, a birth cohort data set of all British children born in one week in 1958, they established that in Great Britain, better-educated adult children do have parents who live longer.  The results of this first analysis were striking: Even when comparing parents of similar social class and education, parents whose children stayed in education until age 21 lived two years longer, on average, than the parents of children who left school at age 16.

Other studies have shown similar results: Parents of better-educated children are less likely to suffer depression, for instance, and have fewer disabilities. But few studies have used natural experiments, i.e. constellations that mimic a random assignment of individuals into treatment and control groups in this case, pairs of parents and children, where the children  were born just before or just after the cut-off date at which the school-leaving age was raised.

The ONS Longitudinal Study thus allowed the researchers to answer the crucial question as to whether parental longevity was a consequence of children’s education rather than just a correlate. They used census information from 1971 to analyse the health and longevity of 56,000 mothers and 49,000 fathers whose children were born between 1949 and 1965 and whose children therefore benefited from the educational reform  which raised the mandatory school-leaving age from 15 to 16 years in 1972.  The ONS-LS, which links the census to the civil registration system, the NHS registration systems, and the cancer registries, meaning researchers knew when the parents observed in 1971 died and what their cause of death was.

Six causes of death

Researchers examined six causes of death linked to behaviours: lung cancer, accidents and self-harm, liver disease, ischaemic heart disease, mental and behavioural causes of death, and causes generally deemed preventable. Researchers could thus ask if those parents whose children stayed in education lived heathier lives due to possible changes in health behaviours.

Generally, parents whose children stayed in education longer due to education reform were not found to be healthier than those who didn’t. The study concludes no overall causal link exists between adult children’s education and parental health. This result differed from research in developing countries such as Tanzania, where a causal link had been found.

So why was a link between adult children’s education and parental health not found in England and Wales? Researchers suggest three possible reasons: First, universal health care provided by the NHS might have helped those whose children had fewer years of education. Second, the UK’s strongly class-based society might have benefited those from middle class homes more than educational changes. And third, the focus on the raising of the school-leaving age from 15 to 16 years cannot identify whether going to university, for instance, might have had a more direct effect on ones’ parents’ health behaviour.

Future studies should look at how other factors and educational transitions might affect parents, the researchers say. These might focus on whether having male or female children affects parents’ health, and on whether reforms which enable more young people to go to university might lead to a healthier older generation in those families.

In other words, they conclude, it is too early to dismiss the notion that children’s education can have a direct causal effect on the health and longevity of their parents, yet the evidence for England and Wales so far does not support the notion.

• Does Children’s Education Improve Parental Health and Longevity? Causal Evidence from Great Britain is a working paper by Cecilia Potente, Patrick Präg and Christiaan Monden.

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.

Census data

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.

Caregivers’ children

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.”

Further work

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 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.

Nurses

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?

Data

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.

Results

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 future

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.

Acknowledgement:

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 Nicola Shelton

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.

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