Using new biosocial data to explore inequality of opportunity in health and the impact of Covid-19

Andrew Jones uses data from Understanding Society to explore the health impacts of the Covid-19 pandemic.

My Leverhulme Trust Major Research Fellowship supports a programme of research that embeds biosocial data from the national panel dataset, Understanding Society: the UK Household Longitudinal Study, within a unified ethical framework of equity of opportunity in health. It focuses on the ways in which early life circumstances and education shape lifetime inequality of opportunity in health and the pathways through which this happens.

The onset of the Covid-19 pandemic has shaped the final nine months of the Fellowship.

The release of the Understanding Society Covid-19 monthly web survey from May 2020 has allowed a new strand of the project to focus on the impact of the response to the pandemic in the UK on inequality of opportunity in psychological distress.

This asks whether the experience of the Covid-19 pandemic in the UK has had a greater impact on psychological distress among those in more disadvantaged circumstances and hence widened inequality of opportunity (IOp)?

The release of the Understanding Society Covid-19 Survey provides an opportunity to address this question.

Biomarkers and the Understanding Society Panel

The core of the Leverhulme project uses Understanding Society, the UK Household Longitudinal Study (UKHLS), which began in 2009 and is one of the largest household panel studies in the world.

Understanding Society incorporates a sample of respondents from the British Household Panel Study (BHPS), which had been running since 1991, along with an expanded general population sample (GPS).

The UKHLS included nurse health assessment interviews, at wave 2 for the GPS and wave 3 for the BHPS, where blood samples were collected for 13,571 respondents.

As a result, comprehensive longitudinal socioeconomic data, that includes suitable measures of circumstances and effort, has been linked to biomarkers that include physical measurements and blood analytes.

The availability of such objectively measured data allows researchers to investigate biological factors that contribute to and interact with health, education, and social conditions.

When combined with the longitudinal data, biomarkers can shed light on the complex interplay between biology, behaviour, and environment over the life course. The UKHLS biomarkers allow a focus on chronic conditions and psycho-social stress: they span coronary heart disease (blood pressure, body fat, cholesterol and triglycerides); diabetes (HbA1c); liver disease (LFTs); kidney function (creatinine, urea); anaemia and poor nutrition (Hb, ferritin); inflammatory markers (CRP, fibrinogen, CMV); and hormones (testosterone, IGF-1, DHEAs).

For example, in our paper “Ex ante inequality of opportunity in health, decomposition and distributional analysis of biomarkers”, we find that inequalities in health attributed to circumstances account for a non-trivial part of the total health variation in health.

Observed circumstances account for 20% of the total inequalities in our composite measure of multi-system health risk, allostatic load. Decompositions show that, apart from age and gender, education and childhood socioeconomic status are sources of IOp.

An analysis of the contribution of circumstances across the distribution of the biomarkers shows that, for most of the biomarkers, the percentage contribution of socioeconomic circumstances, relative to differences attributable to age and gender, increases towards the right tail of the distributions, where health risks are more pronounced.

Covid-19 and psychological distress

Lockdown, social distancing, self-isolation, the economic impact of shut-down of parts of the economy and the focusing of resources within the health and social care systems on coping with the pandemic may all have had an indirect impact on psychological distress and the mental health of the population.

Given the characteristics of the policy and institutional responses, the burden of this psychological distress may have been unequally distributed within the population.

To analyse the impact of the UK response to the pandemic in terms of health equity, in our SSRN working paper: “The Covid-19 pandemic and its impact on inequality of opportunity in psychological distress in the UK”. we first examine inequality in psychological distress and then decompose this into the share of total inequality in psychological distress that is attributable to observed individual circumstances.

To do this, we use Understanding Society, which launched a Covid-19 survey to examine the impact of the coronavirus pandemic.

During April 2020, selected participants from the Understanding Society survey have been approached to complete a short survey that focuses on the impact of the Covid-19 pandemic.

We linked this to previous Understanding Society waves. We use these data to measure inequality in mental health, as measured by the General Health Questionnaire (GHQ), which captures twelve indicators of psychological distress. This allows a comparison of inequalities in the distribution of GHQ before and at the peak of the first phase of the pandemic, when the fieldwork was completed on 30 April 2020, for a sample of 7,789 respondents.

The findings show a substantial and systematic worsening of the levels of GHQ post-Covid.

This applies to nearly all of the individual elements of GHQ and to overall GHQ scores. For example the prevalence of psychological distress based on the GHQ-12 Caseness scoring, increases from 18.3% to 28.3%.

In addition there is a statistically significant increase in total inequality in the Likert GHQ-12 score between Wave 9 and April 2020. However, we find lower levels of IOp in April 2020, meaning that the proportion of total inequality attributed to observed circumstances has not increased with Covid-19. Individual circumstances are measured using data from before the onset of the pandemic.

To provide additional insights into the possible impact of the pandemic, we broaden the list of circumstances beyond those that have typically been used in this literature to capture factors that are specific to the policy debate concerning the adverse consequences of Covid-19 for social inequality. These include

  • working in industries that are more relevant for or affected by the pandemic,
  • individuals’ employment status
  • the presence of children in households and living in multigenerational households or as lone parents,
  • housing tenure

Moreover, the influence of housing conditions on people’s ability to self-isolate, the neighbourhood environment and any pre-existing financial strain problems are also factors we considered.

During the peak of the pandemic (April 2020) age and gender accounted for a larger share of inequality than before. This is driven by greater psychological distress reported by younger men and, in particular, younger women. The contribution of working in those industries hit hardest by the responses to Covid-19 plays a small role at Wave 9 (0.74%), but more than triples its share in April 2020 (3.28%). Household composition and parental occupation have also increased their shares of the explained variance during the pandemic. 

In line with the evidence on physical health, our results show a substantial worsening of the overall levels of GHQ during the peak (of the first wave) of the pandemic. This applies to nearly all of the individual elements of GHQ-12 and to overall GHQ-12 scores.

In addition, there is a statistically significant increase in total inequality in the Likert GHQ-12 score between Wave 9 and April 2020. Nevertheless, inequality of opportunity – the share of total inequality that is explained by observed circumstances – has not increased. This suggests that, with respect to the immediate impact of the pandemic on psychological distress, the greater inequality that is evident is more broadly diffused across the population than it was before the pandemic. In addition there has been a shift in the balance of the circumstances that are associated with psychological distress, primarily due to the worsening of mental wellbeing among young adults.

Greater unexplained variation may prove challenging for policy makers and it will be interesting to see whether this finding persists in future waves of the Understanding Society Covid-19 Survey.


Andrew has also written a Vox.EU article about his research.

About the author

Andrew Jones is Professor of Economics at the University of York, UK, where he was Head of the Department of Economics and Related Studies from 2011 to 2015. He was Director of the MSc in Health Economics at York between 1994 and 2011 and during that time there were over 500 graduates from more than 70 different countries. He has also supervised 25 PhD students. He was  co-editor of Health Economics from 1999 to 2019. In the RePEc rankings, which average 34 bibliometric indicators, he is ranked in the top 2% of over 57,000 economists worldwide. He has published more than 90peer-reviewed articles, has over 10,000 citations and an h-index of 51 (Google Scholar). He does research in microeconometrics and health economics with particular interests in the determinants of health, the economics of addiction and socioeconomic inequalities in health and health care. He is editor of the Oxford Encyclopedia of Health Economics. He is author of the chapter ‘health econometrics’ in the Elsevier Handbook of Health Economics and of chapters in the Oxford Handbooks of Health Economics, Economic Forecasting, and Panel Data and the Palgrave Handbook of Econometrics. He has a particular interest in developing and disseminating the use of applied econometrics in health economics. In 1992 he established the European Workshops on Econometrics and Health Economics, which are co-organised with Owen O’Donnell.  Andrew is the research director of the Health, Econometrics and Data Group (HEDG) at the University of York and is a visiting professor at Monash University. He was an elected member of the International Health Economics Association (iHEA) Executive Board, 2011-2014, and chaired their Arrow Award committee, 2014-16. He was president of the European Health Economics Association (EuHEA) for 2016-18 and is currently serving as past-president.

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