Six things the ONS Longitudinal Study has taught us about social mobility

By Chris A Garrington, on 4 June 2025

The ONS Longitudinal Study has shed light on a huge range of social issues: this series of Linking our Lives blogs looks back on the major contributions which have been made to different fields of research using this unique data resource. This blog is the fifth in the series, and highlights some of the key ways in which this population sample, which contains census and life event data, has contributed to the study of social mobility.  What it reveals is that there is no single social mobility story: the research reveals a complex picture in which we can see different patterns of social mobility according to the group being studied (for instance, different ethnic groups), and the ways in which we measure where people start out and where they end up (for instance, social class or housing tenure).

1. Mobility across ethnic groups

Early work in this field of study was led by Lucinda Platt and focused on the intergenerational social mobility of different ethnic groups in Britain between 1971 and 1991. A small body of previous research in this area had not been able to distinguish between the jobs migrants did before they moved and those they did after. This study was able to identify the UK employment and occupation of the parents of children growing up in England Wales and to examine their outcomes in adult life – that is, their intergenerational mobility. It looked at children aged 8-15 in 1971 from each of three ethnic groups as measured in 1991: white respondents whose parents were born in the UK, and Indians and Caribbeans who had parents born abroad. It found the impact of class origin varied with ethnicity: social class origins mattered less for social class outcomes for minorities, in particular Caribbeans. Patterns of class mobility were more consistent across women than across men.

Subsequent research followed subjects into their thirties and forties by adding data from the 2001 census and including those who were children in 1981. This meant it could look at more ethnic groups and use the finer-grained measures of ethnic group collected in the 2001 Census. It revealed the extent of upward mobility across different ethnic groups. Again, for minorities their class in adulthood was much less closely associated with their parents’ social class. This studywas also able to show that upward mobility was largely driven by education. However, at this point those of Pakistani ethnicity remained disadvantaged in the labour market, even when taking account of their class origins and educational attainment.

This would change over time with the updating of the study to 2011, when educational mobility was found to be high across all minority groups and translated into equivalent or better occupational outcomes to those of the white UK majority with similar education and class backgrounds. Specifically, Zuccotti and Platt showed that Pakistanis, Caribbean men and Bangladeshi women fared just as well as their white colleagues in terms of career success. Indians, Bangladeshi men and Caribbean women actually fared better. The researchers concluded that  for some groups strengths such as motivation, which delivered educational success, might also pay off in the workplace.

2. Mobility across different areas

It is also possible to look at how social mobility differs by area, asking whether chances of upward social mobility are different depending on where you grew up. A study published in 2021 was able to compare social mobility between small areas across the country, and found substantial variation at the very local level – rather than a simple ‘North-South divide.’ The study looked at three post-war generations and found that while upward mobility increased in every region between the mid-1950s and the early 1980s, the extent of this shift varied across regions and tailed off for more recent cohorts. It also found that those who moved out of the region they grew up in had higher rates of upward mobility than those who stayed, although this difference narrowed over time.

Brian Bell and colleagues took on this theme in a 2023 paper, confirming that these area-level differences in upward occupational mobility were highly persistent over time. They also found that areas with higher occupational mobility tended to have lower housing mobility – that is, lower chances of home ownership for people whose parents did not own their own home.

3. Housing mobility

In 2023 Franz Buscha and colleagues published a study which looked at how housing mobility differs by ethnic group and birth cohort. Aligned with Bell and colleagues’ findings, the results showed that having parents who own their home is an important determinant of home ownership, and this is increasingly so for more recent generations. Similarly, those whose parents were renters had a higher chance of becoming renters themselves. This was particularly true of certain ethnic groups, with those of Pakistani and Bangladeshi origin having a strong likelihood that both parents and offspring would rent, while among Indians both parents and offspring were more likely to be home owners.

4. Employment, unemployment and ‘destinations.’

As noted, second generation immigrant groups attain high levels of education, but while they now experience occupational mobility in line with that, this is not the same for all economic outcomes. While social mobility analysis has typically focused on those in work, employment and unemployment are areas where ethnic inequalities have been most strongly observed. In 1991, Caribbeans were more likely to be unemployed than the majority, even when they came from advantaged social origins. In their 2023 study, Carolina Zuccotti and Lucinda Platt showed that no second-generation ethnic minority group had a higher probability of finding employment than the white British. Second-generation ethnic minority women and Pakistani men experienced employment disadvantage; and Pakistani and Bangladeshi women were disproportionately likely to be economically inactive. These studies showed the importance of attending to different types of economic outcome when thinking about social mobility.

5. Neighbourhood composition and mobility patterns

Research using the ONS-LS has also been able to assess whether growing up in areas with a concentration of certain ethnic groups is linked to adult labour market outcomes. A study by Carolina Zuccotti and Lucinda Platt, published in 2016, was able to look at this question while separating out other factors such as deprivation, household resources, parental class and education that might contribute to these outcomes.

They showed that a greater concentration of a particular ethnic group in a neighbourhood was linked to lower labour market participation and lower social class outcomes for both Pakistani and Bangladeshi women, but to better social class outcomes for Indian men. The researchers suggested Pakistani and Bangladeshi women’s outcomes were linked to the maintenance of traditional cultural norms, made stronger by greater interaction with their own ethnic group. Among Indian men, conversely, high levels of group resources and ‘ethnic capital’ were likely to play a positive role.

6. Education systems and mobility

The ONS-LS has also been used to demonstrate the effects of educational systems – as opposed to individual levels of qualification – on social mobility. In 2015 Patrick Sturgis and colleagues published research which examined claims that the raising of the school leaving age from 15 to 16 in 1972 led to greater social mobility. The researchers compared those who left school just before the change with those who did so just after, and found that although the reform resulted in an increase in educational attainment and a weakened link between attainment and class origin, it did not lead to a reliably measurable increase in the rate of intergenerational social mobility.

A further study in 2023 asked whether social mobility was promoted by a change from an academically selective school system to a comprehensive one, using England as a case study. It matched a sample of census records on children born between 1956 and 1972 with data on the proportion of pupils attending selective schools in the areas where they lived. The results showed no evidence that the move from selective to comprehensive schooling had any significant effect on social mobility in England.

Ongoing and future work

The upcoming addition of the 2021 Census records to the ONS-LS will offer potential for many new insights due to an  increased sample size, longer follow-up period and new questions asked in the 2021 Census. Emma Gorman, with colleagues Franz Buscha, Patrick Sturgis and Min Zhang, will be using this new data to document the social mobility experiences of the younger cohorts in the ONS-LS. These younger people have lived through markedly different economic and social conditions from their parents, and the ONS-LS is an eminently suitable dataset to document their social mobility experiences.

Meanwhile, Lucinda Platt is examining changes in ethnic group between 2001 and 2021 to ascertain how far they are associated with economic circumstances, including circumstances when the subjects were growing up in earlier decades. Such a relationship between economic circumstances and identity choices has been posited in the literature but to date findings have been mixed. This project will address questions such as – are those who are upwardly mobile more or less likely to change ethnic group – and if so in which direction? Does growing up in or moving to more or less ethnically diverse areas influence identity choice and change? How are changes in economic and family circumstances associated with ethnic identity change?

Reference list

Bell, B., Blundell, J. and Machin, S. (2022). Where is the land of hope and glory? The geography of intergenerational mobility in England and Wales. The Scandinavian Journal of Economics. doi:https://doi.org/10.1111/sjoe.12511.

Buscha, F, Gorman, E., Sturgis, P. and Zhang, M. (2023). Ethnic differences in intergenerational housing mobility in England and Wales. Journal of Social Policy, pp.1–21. doi:https://doi.org/10.1017/s0047279423000570.

Buscha, F., Gorman, E. and Sturgis, P. (2021). Spatial and social mobility in England and Wales: A sub‐national analysis of differences and trends over time. The British Journal of Sociology, 72(5). doi:https://doi.org/10.1111/1468-4446.12885.

Buscha, F., Gorman, E. and Sturgis, P. (2023). Selective schooling and social mobility in England. Labour Economics, 81, p.102336. doi:https://doi.org/10.1016/j.labeco.2023.102336.

Platt, L. (2005a). The Intergenerational Social Mobility of Minority Ethnic Groups. Sociology, 39(3), pp.445–461. doi:https://doi.org/10.1177/0038038505052494.

Platt, L. (2005b). New Destinations? Assessing the Post-migration Social Mobility of Minority Ethnic Groups in England and Wales. Social Policy and Administration, 39(6), pp.697–721. doi:https://doi.org/10.1111/j.1467-9515.2005.00465.x.

Platt, L. (2005c). Migration and social mobility : the life chances of Britain’s minority ethnic communities. Bristol: Policy Press and Joseph Rowntree Foundation.

Platt, L. (2007). Making education count: the effects of ethnicity and qualifications on intergenerational social class mobility. The Sociological Review, 55(3)L 485-508.

Sturgis, P. and Buscha, F. (2015). Increasing inter-generational social mobility: is educational expansion the answer? The British Journal of Sociology, 66(3), pp.512–533. doi:https://doi.org/10.1111/1468-4446.12138.

Zuccotti, C. and Platt, L. (2016). Does Neighbourhood Ethnic Concentration in Early Life Affect Subsequent Labour Market Outcomes? A Study across Ethnic Groups in England and Wales. Population, Space and Place, 23(6), p.e2041. doi:https://doi.org/10.1002/psp.2041.

Zuccotti, C and Platt, L. (2023). The paradoxical role of social class background in the educational and labour market outcomes of the children of immigrants in the UK. doi:https://doi.org/10.1111/1468-4446.13047.

Five things the census longitudinal studies have taught us about health inequalities

By Chris A Garrington, on 7 May 2025

The ONS Longitudinal Study and its sister studies in Scotland and Northern Ireland have shed light on a huge range of social issues: this series of Linking our Lives blogs looks back on the major contributions which have been made to different fields of research using these unique data resources. This blog is the fourth in the series, and highlights some of the key ways in which these population samples, which contain census and life event data, have contributed to the study of health inequalities. The series aims to highlight the breadth of further research which will become possible when data from the latest censuses becomes available.

1. Health inequalities and places

In 1980 the influential Black Report revived interest in the relationships between place and health, and in the ensuing decades, numerous research projects demonstrated that where we live is related to our health and our likelihood of dying.

Using 1991 Census cross-sectional microdata, in 2002 Paul Boyle and colleagues found that individuals who were well were more likely to migrate away from deprived areas and those who were ill were more likely to migrate towards them. They found migrants tended to be healthier than non-migrants, and long-distance migrants were less likely to suffer limiting long-term illnesses (LLTIs) than short-distance migrants. However, the cross-sectional data specification held this work back from its full potential.

This was the first in a series of studies by Boyle with Paul Norman, Frank Popham, Phil Rees and others. In 2004 these researchers used the ONS LS to delve further, tracking individuals in England and Wales between 1971 and 1991 to examine whether systematic movements between small areas contributed to health inequalities.

The results showed that among the young, migrants were generally healthier than non-migrants. Over 20 years, the predominant flow they found was of relatively healthy migrants moving from more deprived areas to less deprived areas. This raised ill-health and mortality rates in places of origin and lowered them in destinations. The study concluded that increases in health inequality were largely accounted for by migration rather than by changes in the deprivation of areas where non-migrants lived.

This work was taken further in a study which selected people living in less deprived areas who did not move between 1971 and 1991. It asked whether changes in deprivation in their areas influenced their health or mortality. It found changes in deprivation were related to both health and mortality but were more significant for illness, suggesting public health and regeneration programmes could affect the health of residents.

In 2009, research using ONS LS data from 1971 to 1991 asked what effect social mobility might have on health. It found those who were upwardly mobile tended to be healthier than the class they left and less healthy than the class they joined. This mitigated any social mobility health effect, but the study found that overall health inequalities had widened during the period.

A further study in 2014 used data from 1991 and 2001 to look into mortality rates and health inequality. It asked whether inequalities were greater for some age groups than for others, and found the greatest inequalities occurred during mid-life, with the young and the old suffering lesser effects. Area differences in health might be best highlighted through a focus on those aged between 30 and 60, it concluded.

2. The labour market

A 2015 study by Tom Clemens with Frank Popham and Paul Boyle looked at whether the association between unemployment and mortality was causal. This study used data from the SLS on working men and women aged 25-54 in 1991. It followed them through to 2001 to ask if they were by that time working or unemployed, and asked whether those who were unemployed in 2001 were more likely to die before 2010. The study found that even after prior health conditions were taken into account, unemployed men had a significantly higher risk of mortality than those who were employed. The effects for women were smaller and not statistically significant – though complexities with capturing female employment patterns in the census might have affected that result.

A  further strand of research using the ONS LS focused on whether tackling health inequalities could help older workers to stay in their jobs for longer. A major report in 2022 from the HOPE project aimed to shed light on the factors driving employment in older age, looking at how levels of poor health within a place were linked to the chances of residents being in paid work. It found older workers from the unhealthiest places were 60 per cent more likely to be out of work than those in the healthiest places. Historically disadvantaged areas continued to struggle, it found: areas where people left paid work at a younger age due to poor health in 1991 were much more likely to experience this trend in 2011 as well. This disproportionately affected those in manual occupations, who were much more likely to experience ill health and to expect fewer years of healthy life beyond age 50, compared with workers in administrative or professional roles.

Further work published in 2024 looked at these area level health effects in relation to employment outcomes for different occupational groups, finding the gap between the healthiest and unhealthiest areas was most marked for those in skilled trades; process, plant and machine operatives; and elementary occupations.

3. Pregnancy outcomes

Tom Clemens and Chris Dibben have been able to use the SLS to look at the ways in which where we live can affect pregnancy outcomes.  These effects relate both to the physical and to the social environment, with a 2015 studyfocusing on possible relationships between air pollution and births. They were able to place information on levels of sulphur dioxide, particulates and nitrogen dioxide in the places where pregnant women lived and worked across Scotland alongside information on whether their babies were born under-weight or pre-term. The study found women in areas with higher levels of pollution were at higher risk of low birth weight, though a raised risk of having a pre-term baby was not statistically significant.

In 2017 this work was taken further, using administrative data to look at the interplay between neighbourhood and smoking on birth effects. The study found that while the effects of pollution were significant overall, they were subsumed by the effects of smoking and were not significant for that group.

Mothers’ social environments also affected behaviour that could impact on babies’ health, Clemens and Dibben found. In a further 2015 paper they explored links between crime rates and birth outcomes, looking again at possible links to birth weight and prematurity. SLS data was linked to maternity inpatient data and crime rates according to residential postcode, revealing that there were strong links between higher crime and birth weight as well as with prematurity. These effects persisted even when information on smoking, ethnicity and other socio-economic variables was taken into account. The research concluded that crime might be a proxy for the level of threat and therefore stress that women experienced in their neighbourhoods, and that this appeared to be an important determinant of adverse birth outcomes.

4. Cancer outcomes

In the early 2000s, census data from ONS LS participants in 1971 and 1981 was used to examine socio-economic differences in cancer survival. Previous studies had shown those from poorer backgrounds had worse outcomes, but this research was able to produce a more nuanced picture.

Andrew Sloggett and Emily Grundy used the data to link census responses with records of cancer diagnoses between 1981 and 1997. Outcomes for those who had been diagnosed with a primary malignant cancer at age 45 or older were followed up to the year 2000.

This research was able to produce a measure which showed the relative cancer survival rates of different social groups when compared to the population as a whole. It showed that while the most commonly-used measure, the Carstairs index, was adequate for highlighting differential outcomes, a measure which factored in car access and housing tenure produced a more sensitive measure. Social class in isolation was a relatively weak indicator of survival differentials, it found.

Further work published in 2023 by Charlotte Sturley and colleagues focused on colorectal cancer, the third most commonly-diagnosed cancer in the world and second most common cause of cancer death. This study looked at individual LS members aged 50-plus, and asked if the likelihood of them being diagnosed with the cancer was linked to their educational attainment, social class, housing tenure or area deprivation quintile. Cancer incidence was looked at over a 15-year follow-up period from 2001. It was found to be lower among those with a degree and higher among those in manual occupations , though there was no clear link to area deprivation. However, disparities were greater for survival than for diagnosis. Among 5000 people diagnosed with colorectal cancer, the likelihood of dying from any cause was lower among those with a degree and higher among those employed in manual occupations or living in social-rented housing rather than being owner-occupiers. Those living in the most deprived areas had a higher probability of death than those in the least deprived areas.

5. Urban/rural effects on health

In recent years, work using SLS has focused on the possible health benefits of living in remote island communities as opposed to living in urban ones. Unpublished work by Tom Clemens, using the SLS and reported in 2015, looked at birth outcomes for mothers living in island communities as opposed to urban ones. It found maternal residence in an island community had a large protective effect on birth weight, and also that this effect appeared to be related to the ‘remoteness’ of island communities.

A 2023 study by Kathryn Halliday with Tom Clemens and Chris Dibben used the SLS to look at this ‘island effect’ in relation to mental health and found those living more remotely gained better outcomes, both from their rurality and from their residence on islands. It concluded that the unique physical geography of islands was bringing social benefits to residents.

Ongoing work

Evidence that health and wellbeing can be influenced by access to nature is the focus of a current project led by Catharine Ward Thompson at the University of Edinburgh. This research addresses the concerns of forestry agencies which need to invest scarce resources in ways that maximise benefits for both people and planet. It will use SLS data to link information on  anti-depressant prescriptions and children’s motor skills development with data on access to urban forests. The results will show whether, for example, the extent of new footpaths, improved forest entrances or activities to bring children and adults into the forest can make a difference to health and child development.

Two further projects in progress at the University of Edinburgh are using the SLS to focus on how access to tobacco and alcohol in local environments might affect health. A project led by Niamh Shortt will measure change in the availability of alcohol and tobacco in Scottish neighbourhoods over time and will ask how it relates to health outcomes. Further research by Annika Chambers will use linked data on maternity records, which includes information on maternal smoking and alcohol consumption, to examine how changes in the retail landscape may be linked to health behaviours during pregnancy.  The outcomes should shed light on whether an over-supply of alcohol and tobacco is linked to health effects from smoking and alcohol consumption.

References

Boyle, P., Norman, P. and Rees, P. (2002). Does migration exaggerate the relationship between deprivation and limiting long-term illness? A Scottish analysis. Social Science & Medicine, 55(1), pp.21–31. doi:https://doi.org/10.1016/s0277-9536(01)00217-9.

Boyle, P., Norman, P. and Rees, P. (2004). Changing places. Do changes in the relative deprivation of areas influence limiting long-term illness and mortality among non-migrant people living in non-deprived households? Social Science & Medicine, 58(12), pp.2459–2471. doi:https://doi.org/10.1016/j.socscimed.2003.09.011.

Boyle, P.J., Norman, P. and Popham, F. (2009). Social mobility: Evidence that it can widen health inequalities. Social Science & Medicine, 68(10), pp.1835–1842. doi:https://doi.org/10.1016/j.socscimed.2009.02.051.

Clemens, T., Boyle, P. and Popham, F. (2009). Unemployment, mortality and the problem of healthrelated selection: Evidence from the Scottish and England & Wales (ONS) Longitudinal Studies. Health Statistics Quarterly, 43(1), pp.7–13. doi:https://doi.org/10.1057/hsq.2009.23.

Clemens, T. and Dibben, C. (2016). Living in stressful neighbourhoods during pregnancy: an observational study of crime rates and birth outcomes. The European Journal of Public Health, [online] p.ckw131. doi:https://doi.org/10.1093/eurpub/ckw131.

Clemens, T., Popham, F. and Boyle, P. (2014). What is the effect of unemployment on all-cause mortality? A cohort study using propensity score matching. European Journal of Public Health, 25(1), pp.115–121. doi:https://doi.org/10.1093/eurpub/cku136.

Clemens, T., Turner, S. and Dibben, C. (2017). Maternal exposure to ambient air pollution and fetal growth in North-East Scotland: A population-based study using routine ultrasound scans. Environment International, 107, pp.216–226. doi:https://doi.org/10.1016/j.envint.2017.07.018.

Curtis, S., Norman, P., Cookson, R., Cherrie, M. and Pearce, J. (2019). Recession, local employment trends and change in self-reported health of individuals: A longitudinal study in England and Wales during the ‘great recession’. Health & Place, 59, p.102174. doi:https://doi.org/10.1016/j.healthplace.2019.102174.

Dibben, C. and Clemens, T. (2015). Place of work and residential exposure to ambient air pollution and birth outcomes in Scotland, using geographically fine pollution climate mapping estimates. Environmental Research, 140, pp.535–541. doi:https://doi.org/10.1016/j.envres.2015.05.010.

Gray, A.M. (1982). INEQUALITIES IN HEALTH. THE BLACK REPORT: A SUMMARY AND COMMENT. International Journal of Health Services, [online] 12(3), pp.349–380. Available at: https://www.jstor.org/stable/45130747.

Halliday, K., Clemens, T. and Dibben, C. (2022). The island effect: Spatial effects on mental wellbeing from residence on remote Scottish islands. Wellbeing, Space and Society, p.100098. doi:https://doi.org/10.1016/j.wss.2022.100098.

Norman, P. and Boyle, P. (2014). Are health inequalities between differently deprived areas evident at different ages? A longitudinal study of census records in England and Wales, 1991–2001. Health & Place, 26, pp.88–93. doi:https://doi.org/10.1016/j.healthplace.2013.12.010.

Norman, P., Boyle, P. and Rees, P. (2005). Selective migration, health and deprivation: a longitudinal analysis. Social Science & Medicine, 60(12), pp.2755–2771. doi:https://doi.org/10.1016/j.socscimed.2004.11.008.

Office for National Statistics, Census Division, University of Manchester, Cathie Marsh Centre for Census and Survey Research. (2023). Census 1991: Household Sample of Anonymised Records for Great Britain (SARs). [data collection]. UK Data Service. SN: 7211, DOI: http://doi.org/10.5255/UKDA-SN-7211-1

Sloggett, A., Young, H. and Grundy, E. (2007). The association of cancer survival with four socioeconomic indicators: a longitudinal study of the older population of England and Wales 1981–2000. BMC Cancer, 7(1). doi:https://doi.org/10.1186/1471-2407-7-20.

Sturley, C., Norman, P., Morris, M. and Downing, A. (2023). Contrasting socio-economic influences on colorectal cancer incidence and survival in England and Wales. Social Science & Medicine, [online] 333, p.116138. doi:https://doi.org/10.1016/j.socscimed.2023.116138.

UKRI (2015). Using secondary data to examine whether a programme of physical and social interventions in urban forests enhances community health and wellbeing. [online] Ukri.org. Available at: https://gtr.ukri.org/projects?ref=ES%2FV002457%2F1 [Accessed 14 Mar. 2025].

UKRI (2016). Change in alcohol and tobacco availability, population health and the lived experience. [online] Ukri.org. Available at: https://gtr.ukri.org/projects?ref=ES%2FS016775%2F1 [Accessed 14 Mar. 2025].

Five things the ONS Longitudinal study has taught us about older age

By Chris A Garrington, on 2 April 2025

Since the early 1970s,  the ONS Longitudinal Study has shed light on a huge range of social issues: this series of Linking our Lives blogs looks back on the major contributions which have been made to different fields of research using this unique data resource. This blog is the third in the series, and highlights some of the key ways in which this one per cent sample of the population of England and Wales, which contains census and life event data on more than a million people, has contributed to the study of older age. The series aims to highlight the breadth of further research which will become possible when the 2021 Census link to the study is finalised in 2025.

Health inequalities and mortality

From its earliest days, the ONS-LS has been used to shed light on health inequalities: work led by John Fox focused on unemployment and mortality, and was quoted in the important 1982 Black Report. Fox and his colleagues found death rates among men who were unemployed at the time of the 1971 Census were higher than expected over the ensuing decade. They estimated that after other factors such as socio-economic background were taken into account, unemployment was associated with a 20-30 per cent excess death rate. Women married to unemployed men also had higher-than-expected death rates, they found.

Older age and place of residence

The ONS LS has also been used to shed light on factors associated with household changes in later life. In 2003 Emily Grundy and Karen Glaser reported on older widowed and divorced women moving from independent living into either family or institutional care in the 1970s and 1980sand found that owner occupiers were significantly more likely than tenants to move in with relatives  rather than to institutions.

:A further study on the living arrangements of older people with cancer,  led by Emily Grundy in 2004,  found those who lived with others were more likely to be able to die at home than those who lived alone.

With Mark Jitlal, Emily Grundy looked in 2007 at socio-demographic variations in moves to institutional care. Using data from the 1990s, they found those who were in rented accommodation, lived alone, were unmarried, childless or suffered from long-term illness were more likely to make this transition. Women were more likely to do so than men, particularly if they were childless.

This work was extended in a paper published in 2010 by Emily Grundy, which looked at data from the early 2000s. It found older people’s chances of living with relatives rather than alone or in a couple had decreased over time. Those who lived in institutions had higher mortality than others and this excess had grown over time suggesting stronger health related selection.

In 2013, Susan Ramsay and colleagues looked at the effects of caregiving on mortality, and found that while caregivers were more likely to report poor health than others, they were also at significantly lower risk of dying.

Marital and fertility histories and older age

In the early 2000s, Emily Grundy and colleagues carried out a series of studies looking at changes in women’s fertility during the 20^th Century and asked whether these changes might be linked to socio-economic factors. With Cecilia Tomassini, she published a 2005 paper which asked whether the mortality of women born between 1911 and 1940 was linked to the age at which they became mothers, the number of children they had and the intervals between births. The study found those who had been teenage mothers, who had at least five children or who had short birth intervals – including twins – had higher mortality rates. However, this also applied to those who had no children, while those who had children later had lower risks.

In 2006 Emily Grundy and Cecilia Tomassini looked at fatherhood and mortality and found men who had a child before the age of 23 had higher mortality and higher risk of poor health than other fathers, while the reverse was the case for those who had children after the age of 40. Men who had four or more children also had worse health later in life, but contrary to expectations married men with no children did not suffer that disadvantage.

This theme was explored further in a 2010 paper which looked at the health effects of marriage on older people. It found men who were unmarried, widowed, divorced or even remarried had higher mortality rates than those who remained in a long first marriage. Those who remarried were also at greater risk of long-term illness. For unmarried women the picture was different –they had raised mortality rates, but those in the 2001 census cohort actually had lower odds of reporting long-term illness.

These effects were also reported in a study looking at marital history and mortality in England and Finland – long-term marriage had a protective effect, it found. Once social factors were taken into account those who had long first marriages had the lowest mortality, while those never married, divorced or widowed had the highest.

Health inequalities and older age

In the early 2000s, census data from ONS-LS participants in 1971 and 1981 was used to examine socio-economic differences in cancer survival. Previous studies had shown those from poorer backgrounds had worse outcomes, but this research was able to produce a more nuanced picture.

Andrew Sloggett and Emily Grundy used the data to link census responses with records of cancer diagnoses between 1981 and 1997. Outcomes for those who had been diagnosed with a primary malignant cancer at age 45 or older were followed up to the year 2000.

This research was able to produce a measure which showed the relative cancer survival rates of different social groups when compared to the population as a whole. It showed that while the most commonly-used measure, the Carstairs index, was adequate for highlighting differential outcomes, a measure which factored in car access and housing tenure produced a more sensitive measure. Social class in isolation was a relatively weak indicator of survival differentials, it found.

Work on health inequalities has been able to examine social class differences in the amount of time older adults live after stopping work, and how these differences relate to health. Emily Murray and colleagues followed up ONS-LS participants who were aged between 50 and 75 at the time of the 2001 census and who had stopped work by the 2011 census. They found both social class and health were independent predictors of post-work life expectancy, with professional people gaining 2.7 years over those from unskilled backgrounds, and those in good health gaining 2.4 years over those whose health was poor. Lower social class groups were negatively affected by uniform state pension ages, because they were more likely to stop work at younger ages due to health reasons, they found.

Older age and the labour market

Research on extended working lives and the factors driving people’s decisions to leave or remain in work has been able to gain insights from ONS- LS data. In 2016, Emily  Murray and colleagues looked at how local area unemploymentcould be linked to health and to workforce exit. Using information on ONS-LS participants who were aged 40-69 and working in 2001, they asked how their odds of being sick, disabled or retired in 2011 was linked to the level of unemployment in their areas. Again they found that both high area unemployment and poor health were independently linked to people becoming sick, disabled or retired. Those in areas of high unemployment were more likely to identify as being sick or disabled, while improvements in employment rates were less likely to affect the positions of those in poor health than of those in good health.

In 2018, Nicola Shelton and colleagues looked at whether gender and place were linked to the likelihood of remaining in work. They looked at those aged 40-49 in 2001, following them up in 2011 to ask whether they were still in work. Both men and women in the North East were the most likely to leave work early, they found, though most regional differences were ironed out when socio-economic status, housing tenure, qualifications and car ownership were taken into account.Women working for larger employers or further from home were more likely to leave work, whereas access to a car and higher working hours increased the likelihood of staying on.

Later work carried out under the HOPE (Health of Older People in Places) project, led by Emily Murray, explored the ways in which where we live affects disability-free life expectancy – which in turn affects exit from the labour market. In 2022 Emily Murray and colleagues looked at life expectancy for men and women aged 50–74, the stage at which people tend to move from jobs into retirement or to different types of work. They found while those in rural and coastal areas had mixed outcomes, health inequalities in former industrial and coalfield areas were deeply entrenched and were strongly linked to how those areas had fared in terms of deprivation.

The HOPE project was also able to shed further light on the factors driving employment in older age, looking at how levels of poor health within a place were linked to the chances of residents being in paid work. They found older workers from the unhealthiest places were 60 per cent more likely to be out of work than those in the healthiest places. Historically disadvantaged areas continued to struggle, it found: areas where people left paid work at a younger age due to poor health in 1991 were much more likely to experience this trend in 2011 as well. This disproportionately affected those in manual occupations, who were much more likely to experience ill health and to expect fewer years of healthy life beyond age 50, compared with workers in administrative or professional roles.

Further work published in 2024 looked at these area level health effects in relation to employment outcomes for different occupational groups, finding the gap between the healthiest and unhealthiest areas was most marked for skilled trades; process, plant and machine operatives; and elementary occupations.

The way we measure health matters, too: a study using the ONS-LS looked at which health factors were most closely linked to employment outcomes. It considered seven indicators for older working age: self-rated health at age 50-74, long-term illness at age 50-74, age-specific mortality rate at 50-74, avoidable mortality, life expectancy at birth and at 65 years, disability-free life expectancy at 50 years, and healthy life expectancy at 50. The strongest associations were found for self-reported long-term illness and health, and were slightly more so for men than women. Improving the health of older populations could lead to wider economic benefits for all, the work concluded.

 Reference list

Blomgren, J., Martikainen, P., Grundy, E. and Koskinen, S. (2010). Marital history 1971–91 and mortality 1991–2004 in England & Wales and Finland. Journal of Epidemiology and Community Health, 66(1), pp.30–36. doi:https://doi.org/10.1136/jech.2010.110635.

Glaser, K., Grundy, E. and Lynch, K. (2003). Transitions to Supported Environments in England and Wales Among Elderly Widowed and Divorced Women: The Changing Balance Between Co-Residence with Family and Institutional Care. Journal of Women & Aging, 15(2-3), pp.107–126. doi:https://doi.org/10.1300/j074v15n02_07.

Gray, A.M. (1982). INEQUALITIES IN HEALTH. THE BLACK REPORT: A SUMMARY AND COMMENT. International Journal of Health Services, [online] 12(3), pp.349–380. Available at: https://www.jstor.org/stable/45130747.

Grundy, E. (2010). Household transitions and subsequent mortality among older people in England and Wales: trends over three decades. Journal of Epidemiology & Community Health, 65(4), pp.353–359. doi:https://doi.org/10.1136/jech.2009.089383.

Grundy, E. and Jitlal, M. (2007). Socio-demographic variations in moves to institutional care 1991 2001: a record linkage study from England and Wales. Age and Ageing, 36(4), pp.424–430. doi:https://doi.org/10.1093/ageing/afm067.

Grundy, E., Mayer, D., Young, H. and Sloggett, A. (2004). Living arrangements and place of death of older people with cancer in England and Wales: a record linkage study. British Journal of Cancer, 91(5), pp.907–912. doi:https://doi.org/10.1038/sj.bjc.6602038.

Grundy, E. and Tomassini, C. (2005). Fertility history and health in later life: a record linkage study in England and Wales. Social Science & Medicine, 61(1), pp.217–228. doi:https://doi.org/10.1016/j.socscimed.2004.11.046.

Grundy, E. and Tomassini, C. (2006). Fatherhood history and later life health and mortality in England and Wales: A record linkage study. Biodemography and Social Biology, 53(3-4), pp.189–205. doi:https://doi.org/10.1080/19485565.2006.9989126.

Grundy, E.M. and Tomassini, C. (2010). Marital history, health and mortality among older men and women in England and Wales. BMC Public Health, 10(1). doi:https://doi.org/10.1186/1471-2458-10-554.

Head, J., Norman, P., Shelton, N., Beach, B. and Murray, E.T. (2024). Does the health of local populations modify occupational differences in employment rates of older workers? Findings from the ONS Longitudinal Study 2001–2011. Health & Place, 90, pp.103376–103376. doi:https://doi.org/10.1016/j.healthplace.2024.103376.

International Centre for Longevity (2022). Health and place: How levelling up health can keep older workers working. [online] Available at: https://ilcuk.org.uk/wp-content/uploads/2022/10/ILC-Health-and-place-How-levelling-up-can-keep-older-workers-working_full-report.pdf [Accessed 28 Feb. 2025].

Moser, K.A., Fox, A.J. and Jones, D.R. (1984). UNEMPLOYMENT AND MORTALITY IN THE OPCS LONGITUDINAL STUDY. The Lancet, 324(8415), pp.1324–1329. doi:https://doi.org/10.1016/s0140-6736(84)90832-8.

Murray, E.T., Head, J., Shelton, N., Hagger-Johnson, G., Stansfeld, S., Zaninotto, P. and Stafford, M. (2016). Local area unemployment, individual health and workforce exit: ONS Longitudinal Study. The European Journal of Public Health, 26(3), pp.463–469. doi:https://doi.org/10.1093/eurpub/ckw005.

Murray, E.T., Zaninotto, P., Fleischmann, M., Stafford, M., Carr, E., Shelton, N., Stansfeld, S., Kuh, D. and Head, J. (2019). Linking local labour market conditions across the life course to retirement age: Pathways of health, employment status, occupational class and educational achievement, using 60 years of the 1946 British Birth Cohort. Social Science & Medicine, 226, pp.113–122. doi:https://doi.org/10.1016/j.socscimed.2019.02.038.

Norman, P., Exeter, D., Shelton, N., Head, J. and Murray, E. (2022). (Un-) healthy ageing: Geographic inequalities in disability-free life expectancy in England and Wales. Health & Place, 76, p.102820. doi:https://doi.org/10.1016/j.healthplace.2022.102820.

Ramsay, S., Grundy, E. and O’Reilly, D. (2013). The relationship between informal caregiving and mortality: an analysis using the ONS Longitudinal Study of England and Wales. Journal of Epidemiology and Community Health, 67(8), pp.655–660. doi:https://doi.org/10.1136/jech-2012-202237.

Shelton, N., Head, J., Carr, E., Zaninotto, P., Hagger-Johnson, G. and Murray, E. (2018). Gender differences and individual, household, and workplace characteristics: Regional geographies of extended working lives. Population, Space and Place, 25(2), p.e2213. doi:https://doi.org/10.1002/psp.2213.

Sloggett, A., Young, H. and Grundy, E. (2007). The association of cancer survival with four socioeconomic indicators: a longitudinal study of the older population of England and Wales 1981–2000. BMC Cancer, 7(1). doi:https://doi.org/10.1186/1471-2407-7-20.

Four things the ONS Longitudinal study has taught us about immigration and health

By Chris A Garrington, on 5 March 2025

• Listen to the Linking our Lives Podcast episode with Matt Wallace and Joe Harrison who helped author this blog

Since 1971, the ONS Longitudinal Study has shed light on a huge range of social issues: this series of Linking our Lives blogs looks back on the major contributions which have been made to different fields of research using this unique data resource. This blog is the second in the series, and highlights some of the key ways in which this one per cent sample of the population of England and Wales, which contains census and life event data on more than a million people, has contributed to the study of links between immigration and health. The series aims to highlight the breadth of further research which will become possible when the 2021 Census link to the study is finalised in 2025.

1. Why are death rates lower among immigrant populations?

Research over the past 40 years has shown those who migrate internationally tend to have lower death rates compared to non-migrants born in their destination countries, but until the early 2000s few studies had examined this phenomenon over the long term. Seeromanie Harding’s 2003 study of immigrants to England and Wales from the Indian Subcontinent used LS data from 1971 to 2000 to show that this advantage lessened with time and that the group’s death rates tended to rise with the number of years of residence here. Matt Wallace took this work further, first with a 2014 study which used LS data to ask if inaccuracies in, or missing, emigration data could account for the effect, and which found they could not. Most groups of international migrants had lower death rates than non-migrants of England and Wales, he found. In a further paper, he showed high death rates from infectious diseases among these groups was more than offset by low death rates from chronic diseases and from cancers compared to non-migrants. Later he asked if the ‘salmon bias effect,’ in which those suffering ill health return to their place of birth, could explain the effect but found that it could not.

2. Low mortality, poor health?

In 2020 Matt Wallace and Fran Darlington-Pollock examined the idea that links between health and mortality might be weaker among migrants compared to non-migrants. They suggested that despite having low death rates, some immigrant groups were more likely to report being in poor health than non-immigrants were. They used the LS to compare health and mortality data over 20 years and found evidence of higher self-reported levels limiting long-term illness combined with low death rates (compared to non-migrants) among those from three areas: Pakistan and Bangladesh, India and the Caribbean. They suggested the finding might be explained by selection effects – that migrants may have a higher incidence of long-term illnesses than non-migrants do, but a better chance of survival – and cultural factors such as diet, as well as differences in the ways migrant groups evaluate their own health.  Some of these issues will be examined in a project named ‘Living longer in poorer health? Understanding the immigrant morbidity-mortality paradox’ (PARA-MOR), which will be led by Matt Wallace at the Centre for Research on Inclusive Society (CRIS) at the University of Salford. The £1.3 million UKRI study will try to understand better the causes and the consequences of why international migrants are living longer lives in worse health than non-migrants. The project will use cutting-edge methods to analyse large-scale longitudinal data on illness and mortality from various high-income countries.

3. Health and mortality among the descendants of immigrants

In light of these findings, researchers used the LS to investigate whether lower mortality extended to the children and grandchildren of immigrants. Early work on the subject included a 1996 study by  Seeromanie Harding and R Balarajan, which looked at the deaths of around 1500 second generation Irish people in England and Wales between 1971 and 1989. It found mortality rates higher than those in the general population, influenced by socioeconomic, cultural and lifestyle factors. They followed this in 2001 with research on third generation Irish people in England and Wales, which showed that although socioeconomic disadvantage lessened between generations, mortality remained high. Further work by Anne Scott and Ian Timaeus found UK-born Black Caribbeans had higher death rates than UK-born Whites, though this was accounted for by low socioeconomic status.

Seeromanie Harding and R Balarajan also looked at limiting long-term illness among Black Caribbeans, Black Africans, Indians, Pakistanis, Bangladeshis and Chinese born in the UK. They found higher rates of such illness for all groups apart from Chinese, and noted that Black Africans born here had higher rates than those born in Africa. Little was known about the health consequences of being a second or third generation migrant, the research said.

In 2015, Matt Wallace asked whether a migrant mortality advantage persisted beyond the first generation. As a single group, UK-born ethnic minorities (the descendants of migrants) had higher death rates than both migrants and UK-born Whites in England and Wales. After adjusting for disadvantages in socioeconomic factors like occupation, education, and housing, the death rate of UK-born ethnic minorities became comparable to the death rate of the UK-born White group. When examining variation by background, Matt Wallace found higher death rates among UK-born Black Caribbeans, UK-born Pakistanis and Bangladeshis, and the UK-born “Black other” group. However, only UK-born Black Caribbeans continued to have high death rates after adjusting for socioeconomic status.

4. Cancer incidence among immigrants and their descendants

In 1999 Seeromanie Harding and Michael Rosato compared the incidence of cancer between 1971 and 1989 among those who were living in England or Wales but were born in Scotland, Northern Ireland, the Irish Republic, Caribbean Commonwealth or the Indian subcontinent. They found the incidence of the main forms of the disease was lower among West Indians and South Asians, but higher in some cases among those from Scotland and Ireland. In 2009 Harding and colleagues followed this with research using mortality data from the 1970s, 1980s and 1990s, showing that in spite of general declines in cancer death rates, inequalities in migrant mortality remained – and in some cases led to growing disparities between migrant groups and the wider population. Research by Joseph Harrison published in 2024 has updated and expanded on these findings, revealing that cancer incidence and mortality remains lower among Pakistani-born and Bangladeshi-born people in England and Wales, and also for their descendants – though the likelihood of survival after diagnosis may be lower in descendants. 

References:

Harding, S. (2001). Mortality of third generation Irish people living in England and Wales: longitudinal study. BMJ, 322(7284), pp.466–467. doi:https://doi.org/10.1136/bmj.322.7284.466.

Harding, S. (2003). Mortality of migrants from the Indian subcontinent to England and Wales: effect of duration of residence. Epidemiology (Cambridge, Mass.), [online] 14(3), pp.287–92. Available at: https://pubmed.ncbi.nlm.nih.gov/12859028/.

Harding, S. and Balarajan, R. (1996). Patterns of mortality in second generation Irish living in England and Wales: longitudinal study. BMJ, 312(7043), pp.1389–1392. doi:https://doi.org/10.1136/bmj.312.7043.1389.

Harding, S. and Balarajan, R. (2000). Limiting Long-term Illness Among Black Caribbeans, Black Africans, Indians, Pakistanis, Bangladeshis and Chinese Born in the UK. Ethnicity & Health, 5(1), pp.41–46. doi:https://doi.org/10.1080/13557850050007338.

Harding, S. and Rosato, M. (1999). Cancer Incidence Among First Generation Scottish, Irish, West Indian and South Asian Migrants Living in England and Wales. Ethnicity & Health, 4(1-2), pp.83–92. doi:https://doi.org/10.1080/13557859998218.

Harding, S., Rosato, M. and Teyhan, A. (2009). Trends in cancer mortality among migrants in England and Wales, 1979–2003. European Journal of Cancer, 45(12), pp.2168–2179. doi:https://doi.org/10.1016/j.ejca.2009.02.029.

Harrison, J., Sullivan, F., Keenan, K. and Hill Kulu (2024). All-cancer incidence and mortality in Pakistanis, Bangladeshis, and their descendants in England and Wales. BMC Public Health, 24(1). doi:https://doi.org/10.1186/s12889-024-20813-1.

Schofield, L., Walsh, D., Feng, Z., Buchanan, D., Dibben, C., Fischbacher, C., McCartney, G., Munoz-Arroyo, R. and Whyte, B. (2019). Does ethnic diversity explain intra-UK variation in mortality? A longitudinal cohort study. BMJ Open, 9(3), p.e024563. doi:https://doi.org/10.1136/bmjopen-2018-024563.

Scott, A.P. and Timæus, I.M. (2013). Mortality differentials 1991−2005 by self-reported ethnicity: findings from the ONS Longitudinal Study. Journal of Epidemiology and Community Health, 67(9), pp.743–750. doi:https://doi.org/10.1136/jech-2012-202265.

Taylor, H., Bécares, L., Kapadia, D., Nazroo, J., Stopforth, S. and White, C. (2024). Ethnic inequalities in mortality in England and Wales: examining life expectancy data and methods. [online] Available at: https://kclpure.kcl.ac.uk/ws/portalfiles/portal/299821661/Ethnic_Inequalities_in_Mortality_in_England_and_Wales_MPO_FINAL.pdf[Accessed 9 Dec. 2024].

Wallace, M. (2016). Adult mortality among the descendants of immigrants in England and Wales: does amigrant mortality advantagepersist beyond the first generation? Journal of Ethnic and Migration Studies, 42(9), pp.1558–1577. doi:https://doi.org/10.1080/1369183x.2015.1131973.

Wallace, M. and Darlington‐Pollock, F. (2020). Poor health, low mortality? Paradox found among immigrants in England and Wales. Population, Space and Place, 28(3). doi:https://doi.org/10.1002/psp.2360.

Wallace, M. and Kulu, H. (2014). Low immigrant mortality in England and Wales: A data artefact? Social Science & Medicine, 120(120), pp.100–109. doi:https://doi.org/10.1016/j.socscimed.2014.08.032.

Wallace, M. and Kulu, H. (2015). Mortality among immigrants in England and Wales by major causes of death, 1971–2012: A longitudinal analysis of register-based data. Social Science & Medicine, 147, pp.209–221. doi:https://doi.org/10.1016/j.socscimed.2015.10.060.

Wallace, M. and Kulu, H. (2018). Can the salmon bias effect explain the migrant mortality advantage in England and Wales? Population, Space and Place, 24(8), p.e2146. doi:https://doi.org/10.1002/psp.2146.

Six things the ONS Longitudinal study has taught us about internal migration

By Chris A Garrington, on 5 February 2025

• Listen to the Linking our Lives Podcast episode with Tony Champion and Ian Shuttleworth who helped author this blog

Since 1971, the ONS Longitudinal Study has shed light on a huge range of social issues: this series of Linking our Lives blogs looks back on the major contributions which have been made to different fields of research using this unique data resource. This blog is the first in the series, and highlights some of the key ways in which this one per cent sample of the population of England and Wales, which contains census and life event data on more than a million people, has contributed to the study of internal migration. The series aims to highlight the breadth of further research which will become possible when the 2021 Census link to the study is finalised in 2025.

1.  ‘The escalator effect’

Professor Tony Fielding, now Emeritus Professor of Geography at the University of Sussex, was the first researcher to see the potential of the LS for the study of migration. Fielding’s work on ‘escalator regions’, published in 1992, used data on individuals who moved home between 1971 and 1981. It focused on those who moved into or out of the South East of England, asking how these moves linked to people’s chance of achieving upward social mobility.

Fielding found that such ‘escalator regions’ attracted young people at the start of their working lives and provided a space where their upward mobility could be accelerated. Later in life a significant proportion ‘stepped off’ the escalator and left the South East, cashing in the social and economic capital they had gained, typically moving into either retirement or self-employment. The role of the South East as an escalator region continued into the 1980s, he found in a later study.

Further work with Susan Halford revealed that while both men and women benefitted from ‘stepping on the escalator,’ the relative benefits gained by women were greater.

2. Stepping off the ‘escalator’

The implications of these findings were explored further in a 2012 paper by Professor Tony Champion, which looked further into the circumstances of those who moved to the South East between 1966 and 1971 but who left again before 1981. Champion looked at the extent to which this ‘escalator’ effect had a negative impact on other regions, but found the picture was more positive than had previously been thought.

One in three of the young people who moved to the South East between 1966 and 1971 had left again by 1981, he found, with most of the outward migration among working-age people being among the under-30s.

This work led to a reappraisal of the perceived negative effects of the economic dominance of the South East: as returners were younger and more economically active than had previously been thought, they appeared to have been contributing just as much to their regional economies as non-returners did in the South East. So the downside for the regions of origin was not as great as implied by the escalator region model, which had emphasised the role of those returning much later in life to ‘downshift’ or to retire.

3. Migrating into a non-escalator region

This work on ‘escalator regions’ was not Tony Champion’s first encounter with the ONS LS. His research with Malcolm Williams in the 1990s had looked at whether the movement of people into Cornwall from other regions had helped to revive a flagging economy.

Champion and Williams compared the economic performance of migrants to Cornwall with that of migrants to Wiltshire, where the economy more closely resembles that of the South East, between 1981 and 1991. They found that while the two groups of internal migrants had similar employment rates and levels of education before they moved, those moving to Wiltshire fared better in the ensuing decade.

Migrants to Wiltshire had increased their employment levels by 1991, with men seven percentage points more likely to be in full-time work and women were three percentage points more likely to be in either full or part-time work. Among those moving to Cornwall, male employment rates fell by more than 17 percentage points, and female by more than five points.

The study found those moving to Cornwall were more likely to be moving into self-employed roles such as running hospitality businesses, and that their arrival did not, contrary to the hopes of planners, ‘kick-start’ the Cornish economy. 

4. Is internal migration falling in England and Wales?

Moving on to the 2011 Census data, Tony Champion and Professor Ian Shuttleworth of Queen’s University Belfast worked together to shed a UK perspective on emerging US research which suggested rates of internal migration were declining. Their research, published in 2016 used early ‘beta test’ data from the LS to look at changes in migration between the 1971-81 decade and the 2001-11 decade.

They found that, as in the USA, there had been a marked reduction in shorter moves of less than 10km, and that this involved almost all types of people. But in contrast to the US experience, there was a much smaller decline in the numbers of people who had moved longer distances.

The study was not able fully to explain the reduction in short-distance migration: was it prompted by a change in people’s desire to move, or by structural factors which might limit their ability to do so? While the census could not answer this question, they said – it does not examine motives of those who fill in the form – other studies suggested those wanting to move were not experiencing significant difficulty.

From Champion and Shuttleworth, 2016

5. Migration and health effects

In the early 21^st Century Dr Paul Norman, then at the University of Manchester, worked with colleagues at St Andrews and Leeds to examine the links between migration, area-based deprivation and health. Using ONS LS data for 1971-1991, they found that, among the young, migrants were generally healthier than non-migrants. Migrants who moved from more to less deprived places were healthier than migrants who moved from less to more deprived places, they reported.

Looking at those who moved or stayed put within different areas, they found that in the more affluent areas, those who moved home were healthier than those who did not.  But those who moved within deprived areas were less healthy than those who did not.

Over the 20-year period, the largest effect they found was that relatively healthy migrants were moving from more deprived areas towards less deprived ones. This was raising levels of ill-health and mortality in the areas people were leaving; leading to increases in health inequalities between the least and most deprived areas. Migration, rather than changes in the deprivation of the areas non-migrants lived in, accounted for most of that increase, they found.

6. Left-behind places

Work using the 2011 Census data turned to a policy issue which had led to much discussion during the ensuing decade: concern about ‘left-behind places,’ which had existed since World War II, had taken on a new urgency post-Brexit: was the rise of populism and the 2016 vote to take the UK out of the European Union caused by ‘the revenge of the left-behind places?’

Working with UCL’s Professor Oliver Duke-Williams, Tony Champion looked at the allocation of funds under the £1.6 billion Stronger Towns Fund (STF), launched in 2019. Using the ONS LS data available for up to 2011, they set out to identify the specific places which the STF was most likely to target and examine their demographic dynamics in terms of their migration exchanges with the rest of the country.

They created a ranking of places on the basis of gender, age, ethnicity and housing tenure.  Focusing on people who moved from weaker to stronger towns between 2001 and 2011, they found that weaker areas had low levels both of inward and outward migration compared with stronger ones but were also more likely to see outward migration among 16-25s. Those who moved from weaker to stronger places were more likely to move from rented to owner-occupied accommodation than those who stayed.

The next step in this research, they said, would be to return to the ‘escalator region’ approach initiated by Tony Fielding with the addition of the 2021 Census data, but to concentrate now on the weakest places to see how well their leavers fared compared to their stayers.

With thanks to Professor Tony Champion, Emeritus Professor of Population Geography at Newcastle University, and Professor Ian Shuttleworth of Queen’s University Belfast, who have both worked with LS data for many years and who contributed material for this blog. Professors Champion and Shuttleworth are interviewed in the accompanying Linking our Lives podcast, which can be accessed here:

 References:

Champion, A. and Duke-Williams, O. (2019). Migration and the ‘left-behind’ places. Unpublished paper presented at a one-day meeting on ‘Stronger Towns: What can the census tell us?’ held at the Institute of Health Informatics, London, 19 July 2019.

Champion, T. (2012). Testing the return migration element of the ‘escalator region’ model: an analysis of migration into and out of south-east England, 1966-2001. Cambridge Journal of Regions, Economy and Society, 5(2), pp.255–270. doi:https://doi.org/10.1093/cjres/rsr045.

Champion, T. and Shuttleworth, I. (2016). Are People Changing Address Less? An Analysis of Migration within England and Wales, 1971-2011, by Distance of Move. Population, Space and Place, 23(3), p.e2026. doi:https://doi.org/10.1002/psp.2026.

Fielding, A. and Halford, S. (1993). Geographies of Opportunity: A Regional Analysis of Gender-Specific Social and Spatial Mobilities in England and Wales, 1971–81. Environment and Planning A: Economy and Space, 25(10), pp.1421–1440. doi:https://doi.org/10.1068/a251421.

Fielding, A.J. (1992). Migration and Social Mobility: South East England as an Escalator Region. Regional Studies, 26(1), pp.1–15. doi:https://doi.org/10.1080/00343409212331346741.

Norman, P., Boyle, P. and Rees, P. (2005). Selective migration, health and deprivation: a longitudinal analysis. Social Science & Medicine, 60(12), pp.2755–2771. doi:https://doi.org/10.1016/j.socscimed.2004.11.008.

Williams, M. and Champion, A. (1998). Cornwall, poverty and in-migration . In: Cornish Studies 6. University of Exeter Press, pp.118–127.

10 years on: What did we learn from the 2011 Census?

By Chris A Garrington, on 1 August 2024

As the release of data from the 2021 Census gets under way, Dr Jitka Pikhartova reflects on research which has explored the results of the ONS Longitudinal study’s census sample over the past decade. Which topics were key, and which stories made headlines?

Much has changed since the beginning of the 21^st Century: in 2001, people either handed their census form to field staff or posted it, but by 2011 they had the option of filling in the form online.

Similarly, the topics on which research has focused have grown and developed over the past two decades – and many of those topics have been the focus of media coverage or policy debates.

For the first time in 2011 census respondents were asked about:

• Their national identity and citizenship
• What passports they held (though not in Scotland)
• When they arrived in the UK
• Their main language and their fluency in English and Welsh
• Whether they were in a same-sex civil partnership
• Whether they suffered from specific chronic conditions (not in England/Wales)
• Whether they undertook voluntary work (Northern Ireland only).

In many cases, research was published over several years before hitting the headlines. For instance, Saffron Karlsen and colleagues had been working with LS data on religion and ethnicity for several years when their findings chimed with ‘Black Lives Matter’ debates in 2020.

Professor Karlsen’s studies found that in 2011 men and women of Bangladeshi and Pakistani ethnicity were 50 and 30 per cent more likely to be in manual work than their white counterparts respectively. Chinese and Indian men and Chinese women were less likely to be manual workers than white men – a reversal of the situation we saw in 1971.

Census-based research on ethnicity by Zuccotti and colleagues also caught media attention when it asked how ethnicity was linked to the labour market outcomes of young people in 2001 and in 2011. It found young men from ethnic minority backgrounds who were not working or studying in 2001 had similar chances of being in work in 2011 as white British men.

This evidence that some ethnic minorities were penalised less for unemployment or inactivity than their white British counterparts was good news in terms of integration, but also raised concerns for the employment prospects of both young white British men and ethnic minority women.

Long-term outcomes

Professor Amanda Sacker led a joint study by University College London (UCL) and King’s College London on long-term outcomes for those who had been in care as children, analysing data from 350,000 people who self-reported their health after 10, 20 and 30 years.

It found adults who had lived in residential care had a 40 per cent chance of reporting poor health after 10 years, rising to 85 per cent over the following two decades. By contrast those who grew up with a relative in kinship care saw their chances of reporting ill health range from 21 per cent to 43 per cent over the 30-year period. Adults who grew up with their parents only had a 13 per cent chance of reporting poor health after 10 years, rising to 21 per cent at both 20 and 30 years.

This project led to more than 30 academic and other publications including widespread media coverage, and was cited in the Independent Review of Children’s Social Care.

Education and social mobility are also topics of research which often use the ONS Longitudinal Study. Professor Franz Buscha and colleagues found neither of the two most powerful 20^th Century educational interventions – the development of grammar schools and raising the school leaving age – resulted in significant changes in social mobility. They said:

“Education affects our social, emotional and cognitive skills, as well as our earnings and employment. But the role of education in driving social mobility is complex, and factors such as early life circumstances and socioeconomic status are also crucial in shaping life outcomes.”

Another project looked at jobs in the creative arts, finding that those from professional families were four times more likely than those from working class backgrounds to work in creative industries. And Gabrielle Hecht’s work also looked at social mobility, finding that moving into a higher professional or managerial job doesn’t necessarily mean moving away from where you grow up. More than two thirds of the most socially mobile people born between 1965-71 and1975-81 have never made a long-distance move.

Meanwhile London has cemented its position as the epicentre of the elites since the 1980s. For the younger generation – those aged between 30 and 36 – moving to London and working in an elite occupation is largely the preserve of those from a privileged background, and this has become even more pronounced in recent years.

Personal characteristics

Moving on from social mobility, Tony Champion’s project looked at how a much broader range of personal characteristics influenced individuals’ propensity to move, and how the strength of these determinants changed over time, while work by James Robards and Ann Berrington looked at dramatic changes in fertility levels which were not predicted by demographers or government statisticians. Although it has never been a stated aim of the British government to boost fertility by increasing access to nursery care, this research caught the attention of the BBC.

And some very interesting and unique research, made possible by the fact that the ONS LS  allows us to look at household composition, tested the hypothesis that parents gain ‘immunisation’ from children. It found exposure to the pathogens which cause the child to acquire its own immunity have a secondary effect on the parents’ immune system. Thus, parents are better equipped for older age. This led to another catchy headline, this time in The Times.

To sum up, we can agree that ONS LS is an excellent resource for answering many scientific questions. For many the study itself is enough, but there is also the possibility to request the connection of data from other sources. Our user support is free, we try to be accommodating and we are quite fast if everything depends only on us – of course we are linked to ONS and they also have a lot of other work. There is much to celebrate in the fact that for 50 years this representative study has been able to inform us on long-term trends for such a wide range of social topics.

This blog has been adapted from Dr Jitka Pikhartova’s talk at a recent event celebrating 12 years of CeLSIUS at UCL. The event showcased work which has been supported during the directorship of Professor Nicola Shelton, who hands over to Dr Stephen Jivraj in September 2024.

Informing the future of the Census

By Chris A Garrington, on 9 July 2024

The new Government is expected to make an announcement about the future of the census following a recent ONS consultation. In this blog based on his inaugural lecture at UCL, Professor Oliver Duke-Williams, Professor of Population Information and a senior member of the Centre for Longitudinal Study Information and User Support (CeLSIUS) team, asks how the past can inform that future.

The most recent census taken in this country was also perhaps the most unusual – the pandemic affected both the way in which people completed the form and the answers they gave. In addition, the vast majority of households completed the census online, where only a small proportion had done so in 2011, when the option was first available in this country. It may also be the last of its kind: alternative data sources offer the potential for different ways of counting the population, bringing with them their own opportunities and threats.

So why do we have a census, and for whose benefit is it? There are a number of purposes: censuses aim to count all people and households in the country, gathering a snapshot of the population at a particular time. They can also have a more subtle purpose: to assert the existence of a nation state, and to define the people that comprise the nation – both in terms of overall numbers of those included and perhaps excluded, and also in the categories and classifications chosen by the state to enumerate them. On a more general level, censuses in most countries including the UK are used for planning, in the hope that the state can make better decisions given better information.

Our census started in 1801 and the first few were very different to the ones we have now: they collected aggregate data rather than data on individuals, but from 1841 they began to become more robust, and primarily based – just as today – on individuals living in households.

We can use census data for many purposes. Whilst historic data is most commonly used to trace family histories, it can also be used more collectively via curated research datasets. For instance, data from Cornwall in 1891 shows the rapid rise in the number of girls named Florence after Florence Nightingale became famous. It is mostly a bit of fun, but allows use to think about the role of celebrity in popularising names, and using census data rather than birth records, also to think about naming practices amongst groups of people with differing characteristics.

Contemporary censuses

Moving to contemporary censuses, as well as the more familiar aggregate results that tell us information – often vital for planning – about how many people there are with particular characteristics in the country, or in specific locations, we can also study the way that individuals change over time. Linking data over time, the ONS Longitudinal Study – a one per cent sample of all census respondents from 1971 to the current day – can enable us to observe the changes in anonymised individuals during their lifetimes – where they live, what their occupations have been, how their households form and change and so on. Amongst other things, this can provide information on social mobility over lifetimes, and on occupational mortality over long periods.

The census isn’t perfect – the pandemic caused a glitch, for example, because the census in Scotland was delayed to 2022 while the censuses in the rest of the UK took place in 2021. So those who moved from England to Scotland between those two dates were counted twice, and those who moved the other way from Scotland to England weren’t counted at all. More generally, some people will be missing – whether by accident or design – in any census.

Some of the questions have become outdated – for example we saw a growth in working from home from 11 per cent to 31 per cent between 2011 and 2021, which has left questions about travel to work looking somewhat out of date. The assumption is still that people have one job and they go to it every day using the same mode of transport, but for many people that’s not the reality any more.
So, the census does make mistakes, and this brings us to its future.

Can AI help?

Perhaps we need to think about whether AI can help – it’s been suggested that natural language systems might help people to ask questions of the census in ways that are easier than the existing interfaces; there are a number of researchers working towards this, and it is fair to say that some people find existing tools hard to use. The answers that come back will be numbers, and it may be that AI could help to present those numbers in a more understandable form.

Just to see how well this would work, I asked the CoPilot, a Microsoft AI tool, to draw one hundred people, and to make them representative of the current UK population. All of the four responses I received had more than one hundred people in them – sometimes far more – and more importantly they weren’t very representative; there were few young people, few people of colour and almost no people with visible disabilities.

So if we think that AI can represent data for us and simplify data for us, we don’t yet have evidence that it can do a good job of it.

But administrative data does have advantages. It gives new sources of data for which some of the costs are already met- health service data or tax data, for instance, collected as part of the day to day operations of the relevant departments, and which can be re-used to create demographic data.

With these sources we don’t have to wait 10 years for the next set of data. But there are problems because at the moment we don’t have a single identifier which will enable us to link the records of individuals across different administrative datasets, so linkage becomes more difficult and expensive.

Big data

There’s also interest in using big data such as mobile phone data to gain insights into people’s lives. But again, there are issues with identifying those individuals and linking their data with other sources; phone data could potentially tell us a lot about movement patterns, but discerning movement by different groups of people would be less easy to achieve.

So, should we retain a census? It has had a 200-year run and not many administrative operations can beat that, so maybe its time has come?

The poor arguments for keeping it are that it’s what we’ve always done. Better ones include the fact that it’s hard to gather some types of information from other sources. The census provides us with a trusted framework for sampling, and once it’s gone we can’t easily recover it.

But there are also arguments for a hybrid approach – census and admin data are different, and they tell us different things. We’re at an interesting branching point, in a way a bit like we were back in 1841 when census data collection began to become more robust. What will the next census look like? The future is currently unknown.

Oliver Duke-Williams is Professor of Population Information in the Department of Information Studies at UCL, where he also leads MA/MSc programmes in Digital Humanities. He is the Census Service Director at the UK Data Service and is also a Senior Advisor to the Centre for Longitudinal Study.

Do ethnic minority care leavers suffer from a ‘double whammy’?

By Chris A Garrington, on 31 January 2024

Research into the long-term effects of children’s social care has highlighted that this group often experience poor outcomes. But does ethnicity have an additional effect? Amanda Sacker and colleagues used census data to compare different groups of care-experienced adults – and their results challenge previous assumptions.

The Looked after children grown up project, on which we have worked for several years, has provided compelling evidence of the disadvantages suffered later in life by those who have spent all or part of their childhood in care.

So when we set out to look at the relative effects of having been in care on different ethnic groups we did so with the premise that minority status would compound their disadvantage. In fact, we found ethnicity affected adult outcomes following care in both positive and negative ways.

Using linked census data from the ONS Longitudinal Study, we were able to track the lives of almost 670,000 people who were children between 1971 and 2001. An important aspect of our study was that we were able to compare those who had experienced care with peers who had not – something which other studies of ethnicity and care had not been able to do.

We know from earlier studies that Black children tend to be over-represented among the care population, while those from Asian backgrounds are under-represented. But there is no certainty about why – perhaps institutional racism affects social workers’ decisions about Black children; perhaps South Asian children are more likely to be cared for by wider family networks, but these are questions we cannot definitively answer.

And they could affect what happens to the different groups after they leave care, because those who only go into care in the most difficult or deprived circumstances are likely to be affected later in life by those background factors.

We could, however, look more closely at what happened to these different groups in adult life. And in doing so we could control for background factors such as country of birth, age, gender, and parental social class, qualifications, employment status and marital status.

We found the picture was a mixed one in which those from ethnic minorities did not consistently have worse care outcomes than those from White families.

These are our key findings:

• There was a clear link between self-reported health issues and a history of social care for both the White and South Asian groups, but not for the Black group. When we looked at long-term and life-limiting illnesses, only the White social care group were more likely to suffer from these than peers who had been in parental care.
• The level of qualifications among South Asian care leavers was significantly lower than for their peers, and there was also an effect, though smaller, for the White group, but Black care leavers had the same level of qualifications as their peers. Among the total population White people were most likely to have low levels of qualification, followed by Black people and then South Asian people.
• Adult employment rates for those in parental care were highest for the White group, followed by the Black and South Asian groups. But the employment rate for Black people was not affected by care experience, and for South Asians there was only a small difference.
• The social class of care-experienced White and South Asian adults was lower than that of their peers, though the impact was greater for White people. Black care leavers’ social class was no different from their peers. Overall, South Asians had the highest probability of being in professional or managerial jobs.
• Home ownership was lower among White people who had been in social care, but this was less so for South Asians and did not apply to the Black group.
• Care-experienced White adults were less likely to marry than their peers, but the reverse was true for the Black and South Asian groups.
• Teenage motherhood was more common among Whites and South Asians who had been in social care, but it was less common in the Black group.

Mixed picture

What can we conclude from this mixed picture? Certainly we can say that inequalities between care leavers and the general population are widespread and long-lasting, and that this should be monitored and acted on as a priority.

But given the evidence that White care leavers are equally or more disadvantaged in some respects, new and existing policies promoting better outcomes for care-experienced adults should be universally provided for all children who have been in social care rather than being targeted at specific minority ethnic groups.

We also believe there is a need for qualitative research into this field, in order to unpick the different factors which may be impacting different ethnic groups.

Key messages from this research:

• Ethnicity moderated the impact of social care mainly for socio-economic outcomes and their long-term effects
• South Asian individuals fared better than Black people if they had been in social care
• A history of social care affected White adults more than Black or South Asian care-experienced adults

Sacker, A., E.T. Murray, B. Maughan, and R.E. Lacey, Social care in childhood and adult outcomes: double whammy for minority children? Longitudinal and Life Course Studies

The NHS 75 years on: What was the long-term impact of making health care free at the point of access?

By Chris A Garrington, on 8 November 2023

The fact that the NHS has reached the age of 75 years has been widely celebrated – but key questions remain about its influence over health, education and economic outcomes. In this post, Genevieve Jeffrey describes research which uses census data  to uncover the far-reaching consequences of the introduction of free health care over the course of 40, 50, and 60 years. It reveals this monumental event impacted not just on individuals’ health and well-being but also on their educational outcomes.

One of the most significant changes brought about by the introduction of the NHS was the elimination of financial barriers. Before its introduction, the cost of medical care during pregnancy and childbirth posed a burden on women and their families. The NHS introduction changed this by providing free access to essential healthcare services during gestation and at birth. The introduction of the NHS negated worries about saving for health costs and navigating the availability of doctors and midwives. This enabled expectant mothers to access healthcare without delay.

This change was important, particularly in preventing complications through timely access to antenatal care. But were there wider longer-term effects?  To delve into this, we harnessed the power of the Office for National Statistics Longitudinal Study (ONS LS). Because this enabled us to break down our sample by exact dates of birth, we could compare the outcomes of those born in the 18 months before July 5th, 1948 – the date of introduction of the NHS – with those born in the 18 months after. The two groups had very similar access to healthcare and to other social services such as education, with one major difference: the mothers of those born in 1946 and in early 1947 did not have free healthcare while pregnant and while giving birth.

Health outcomes

We were able to look at how those in our sample reported their own health later in life, using questions in the census from 1991 onwards about whether they had a long term life-limiting illness and from 2001 on how they saw their own health, from ‘very good’ to ‘very bad.’  We found individuals born after the NHS introduction were more likely to report having no long-term limiting illnesses in their 40s. And we uncovered a noteworthy improvement in self-reported health among those born after the NHS introduction when they were in their 50s and 60s, with respondents more likely to rate their health as ‘good’ compared to those born before.

When assessing objective measures related to cancer, such as cancer incidence, age of first cancer diagnosis, and the sum of cancer events per diagnosis, no significant effects were found. While self-reported health improved, there was no discernible change in cancer-related outcomes.

The impact on economic outcomes

The study also investigated the impact of the NHS on education outcomes. While we found no difference between those born under the NHS and just before it in terms of obtaining no educational qualifications, there was an increase in the likelihood of obtaining a university degree or higher qualification among those born just after the NHS introduction.

Prior research could provide a clue as to the mechanisms that drive these effects. Greater access to healthcare during gestation and at birth can improve the health stock of individuals at birth, and these impacts compound throughout the life course, also impacting educational outcomes. Of course, all of this generation – whether born just before the NHS or just after – benefited from the free secondary education introduced under the 1944 Education Act, and they also benefited from the expansion of the universities which followed the Robbins Report of 1963. The effect on educational outcomes found in our research is separate to the effects of these policies and represents the effect of access to the NHS during gestation and at birth.

Besides education we also looked at the number of hours our sample worked in their 50s and found no significant impact associated with the NHS introduction. Similarly, outcomes for home ownership in the 50s and 60s , serving as a proxy for economic status, displayed no significant effects.

The lasting legacy of the NHS

Our findings underscore the enduring impact of the NHS on the health and education of individuals. Access to healthcare during critical life stages, such as pregnancy and childbirth, carries long-term ramifications for both individuals and society. It not only enhances individual health but also contributes to a more educated population.

While this research provides valuable insights, it also poses vital questions for future exploration. How can healthcare systems be further refined to impact on long-term health outcomes? What are the key pathways through which health at birth impacts on educational attainment in the UK?

These questions are pivotal for policymakers and researchers as they shape the future of healthcare and education policies. The focus of the study was on those born in the months around the NHS introduction. It would be important to also investigate the impact on other segments of society to gauge the true extent of the impact of the NHS introduction.

The introduction of the NHS in 1948 triggered profound and enduring effects on the health, education, and opportunities of individuals in the UK. Our findings underscore the long-term benefits of offering accessible healthcare services, particularly during critical life stages like pregnancy and birth. This study reinforces the significance of upholding and fortifying such healthcare systems, especially during global debates about healthcare access.

As we reflect on the legacy of the NHS 75 years on, this research serves as a potent reminder of the positive societal outcomes achievable when healthcare is a universal right. It encourages us to envision ways to enhance healthcare and education systems for the betterment of individuals and society at large. The NHS remains a shining example of what can be achieved when healthcare is made universally accessible.

Genevieve Jeffrey is a fellow in the LSE Department of Health Policy, and this research formed her PhD thesis.

Reducing inequalities in life expectancy: what works?

By Chris A Garrington, on 12 September 2023

Social inequalities in life expectancy are a major issue for governments – and they have increased over time. But they have done so at different rates in different countries, and there is a need for greater understanding of how and why this has happened. In this blog, Daniel Zazueta-Borboa describes a new study which uses the ONS-LS to look in detail at how policy and social change is linked to reductions or increases in these inequalities.

We know that in modern welfare states, people with higher socio-economic status live longer than those with lower status. And efforts to reduce these gaps have not always been successful.

It’s crucial for policymakers to understand the dynamics of these phenomena if they are to tackle the issues. Yet most studies of the subject either cover only short periods of time or they take longer periods but look only at their start and end dates. This means they are unable to pinpoint accurately the key points at which different phases or changes in trends have occurred. So they have not been able to verify whether social events or policy changes have had a sudden or a gradual effect: for example, how did ‘lifestyle epidemics’ such as increases in the number of deaths due to smoking relate to the life expectancy of different social groups? How did improvements in key medical interventions such as cardiovascular care play out across societies?

Using Census data from England and Wales, register data from Finland and survey data from Turin in Italy, we were able to look at mortality from 1971 onwards. Using a standard measure of educational attainment to indicate socioeconomic status, we compared the life expectancy of those with no more than lower secondary schooling with that of those who continued to study after school leaving age.

For England and Wales, we used data from people in the ONS Longitudinal Study who were aged 20 and older at the time of the 1971, 1981, 1991, 2001 and 2011 censuses. For Finland we were able to check on census respondents aged 25 and older every five years from 1970 to 2015. For Italy, we looked at respondents in Turin who were aged 20 or older in censuses from 1971 to 2011 and who were also included in the Turin Longitudinal Study from 1972–2019.

Trends in inequalities

By looking at trends in the gaps in life expectancy between the lowest and highest socio-economic groups over time, we could map changes in these inequalities and when they happened. We found that over 47 years the inequalities grew more among men in Italy and among both men and women in Finland, but grew less among British men and remained stable among British women. Among Italian women, they were roughly the same at the end of the period.

When we looked in more detail at what happened during different time periods, we could see different phases and breaks in these overall trends.

In England and Wales, there was a clear break in the mid-1970s as women began to gain better educational qualifications, though for men this was reversed in 2008. In Finland, there was a break in the 1980s as educational inequalities increased – again, reversed among Finnish men in 2008. In  Turin, there was a clear break in the mid-1970s indicating increased inequality among men, while among women this happened later, in 2003.

Figure 1: Time trends in educational differences in life expectancy at age 30 (high minus low educated – in years-), by sex and country. Dashed lines represent the start of increasing educational differences in life expectancy.  Solid lines represent the start of reducing educational inequalities.

Where there were long-term increases in educational inequalities, the more highly educated improved their life expectancy at better pace when compared with those who had lower levels of education. Conversely, where there were decreases in inequalities those with lower levels of education gained more years of life expectancy. This was particularly the case for young men in Finland and Italy.

Health and behaviour changes

What triggered the marked changes in the trends? A key factor is likely to be the revolution in cardiovascular care, which began in the early 1970s and involved both medical advances and changes in health behaviours such as smoking: we know those in more highly educated groups gained greater health benefits from these changes. Similarly, those with higher levels of education benefited more from decreases in mortality linked to alcohol.

For Italian women, reforms which made healthcare more universally accessible in the early 1980s are likely to have been important in improving life expectancy and reducing disparities in life expectancy. There were negative social factors too – in Italy there was a large increase in deaths from AIDS in the 1980s which was linked to drug use among younger men, particularly those in lower social groups, and that might be behind the increase of educational inequalities in life expectancy among Italian men.

So, reversals and breaks in these life expectancy gaps can be set in train by gradual social changes, and they can be set in train by more immediate policy decisions. For example in Finland, a reduction in alcohol tax and prices in 2004 was accompanied by a rise in alcohol-related deaths among deprived men, and this was reversed when the tax was increased from 2008. In England and Wales, austerity measures from 2010 have been linked to slower improvements in life expectancy, particularly due to higher mortality among younger age groups in areas of high social deprivation.

What can be done?

There are hopeful messages here for policymakers: inequalities in life expectancy can be shaped by public policy decisions. These may be short-term, such as changes in taxation, or they may be longer-term, such as initiatives to effect behavioural changes. Policies aimed at improving the health of younger people in lower-educated groups could be particularly effective.

Reversals in past long-term trends in educational inequalities in life expectancy for selected European countries, by Daniel Zazueta-Borboa, Pekka Martikainen, Jose Manuel Aburto, Guiseppe Costa, Riina Peltonen, Nicholas Zengarini, Alison  Sizer, Anton Kunst and Fanny Janssen, is published in the Journal of Epidemiology and Community Health, July 2023, 77(7):421-429, https://doi.org/10.1136/jech-2023-220385