Using genetics to understand the relationship between young people’s health and educational outcomes

Amanda Hughes, Kaitlin H. Wade, Matt Dickson, Frances Rice, Alisha Davies, Neil M. Davies & Laura D. Howe

Follow Amanda, Kaitlin, Matt, Alisha, Neil and Laura on twitter

Young people with health problems tend to do less well in school than other students, but it has never been clear why. One explanation is that health problems directly damage educational outcomes. In that case, policymakers aiming to raise educational standards might want to focus first on health as a means of improving attainment.

But are there other explanations? What if falling behind in school can affect health, for instance causing depression? Also, many health problems are more common among children from less advantaged backgrounds – for example, from families with fewer financial resources, or whose parents are themselves unwell. These children also tend to do less well in school, for reasons that may have nothing to do with their own health. How do we know if their health, or their circumstances, are affecting attainment?

It is also unclear if health matters equally for education at all points in development, or particularly in certain school years. Establishing how much health does impact learning, when, and through which mechanisms, would better equip policymakers to improve educational outcomes.

Photo by Edvin Johansson on Unsplash

Using genetic data helps us understand causality

Genetic data can help us answer these questions. Crucially, experiences like family financial difficulties, which might influence both a young person’s health and their learning, cannot change their genes. So, if young people genetically inclined to have asthma are more absent from school, or do less well in their GCSEs, that would strongly suggest an impact of asthma itself. Similarly, while falling behind in school might well trigger depression, it cannot change a person’s genetic propensity for depression. So, a connection between genetic propensity for depression and worse educational outcomes supports an impact of depression itself. This approach, of harnessing genetic information to better understand causal processes, is known as Mendelian randomization.

To find out more, we investigated links between

  • health conditions in childhood and adolescence
  • school absence in years 10 & 11
  • and GCSE results.

We used data from 6113 children born in the Bristol area in 1991-1992. All were participants of the Avon Longitudinal Study of Parents and Children (ALSPAC), also known as Children of the 90s. We focused on six different aspects of health: asthma, migraines, body mass index (BMI), and symptoms of depression, of attention-deficit hyperactivity disorder (ADHD), and of autism spectrum disorder (ASD). These conditions, though diverse, have two important things in common: they affect substantial numbers of young people, and they are at least in part influenced by genetics.

Alongside questionnaire data and education records, we also analysed genetic information from participants’ blood samples. From this information, we were able to calculate for each young person a summary score of genetic propensity for experiencing migraines, ADHD, depression, ASD, and for having a higher BMI.

We used these scores to predict the health conditions, rather than relying just on reports from questionnaire data. In this way, we avoided bias due to the impact of the young people’s circumstances, or of their education on their health rather than vice versa.

Even a small increase in school absence predicted worse GCSEs.

We found that, for each extra day per year of school missed in year 10 or 11, a child’s total GCSE points from their best 8 subjects was a bit less than half (0.43) of a grade lower. Higher BMI was related to increased school absence & lower GCSE grades.

Using the genetic approach, we found that young people genetically predisposed towards a higher BMI were more often absent from school, and they did less well in their GCSEs. A standard-deviation increase* in BMI corresponded to 9% more school absence, and GCSEs around 1/3 grade lower in every subject. Together, these results indicate that increased school absence may be one mechanism by which being heavier could negatively impact learning. However, in other analyses, we found a substantial part of the BMI-GCSEs link was not explained by school absence. It’s unclear which other mechanisms are at play here, but work by other researchers has suggested that weight-related bullying, and negative effects of being heavier on young people’s self-esteem, could interfere with learning.

*equivalent to the difference between the median (50th percentile) in population and the 84th percentile of the population

Diagram showing the pathways through which higher BMI could lead to lower GCSEs; either through more schools absence aged 14-16, or other processes such as weight-related bullying.
Our results suggest increased school absence may partly explain impact of higher BMI on educational attainment, but that other processes are also involved.

ADHD was related to lower GCSE grades, but not increased school absence.

In line with previous research, young people genetically predisposed to ADHD did less well in their GCSEs.  Interestingly, they did not have increased school absence, suggesting that ADHD’s impact on learning works mostly through other pathways. This is consistent with previous research highlighting the importance of other factors on the academic attainment of children with ADHD, including expectations of the school environment, teacher views and attitudes, and bullying by peers.

We found little evidence for an impact of asthma, migraines, depression or ASD on school absence or GCSE results

Our genetic analyses found little support for a negative impact of asthma, migraines, depression or ASD on educational attainment. However, we know relatively little about the genetic influences on depression and ASD, especially compared to the genetics of BMI, which we understand much better. This makes genetic associations with depression or ASD difficult to detect. So, our results should not be taken as conclusive evidence that these conditions do not affect learning.

What does this mean for students and teachers?

Our findings provide evidence of a detrimental impact of high BMI and of ADHD symptoms on GCSE attainment, which for BMI was partially mediated by school absence. When students sent home during the pandemic eventually return to school, the impact on their learning will have been enormous.  And while all students will have been affected, our results highlight that young people who are heavier, who have ADHD, or are experiencing other health problems, will likely need extra support.

Further reading

Hughes, A., Wade, K.H., Dickson, M. et al. Common health conditions in childhood and adolescence, school absence, and educational attainment: Mendelian randomization study. npj Sci. Learn. 6, 1 (2021). https://doi.org/10.1038/s41539-020-00080-6

A version of this blog was posted on the journal’s blog site on 21 Jan 2021.

Contact the researchers

Amanda Hughes, Senior Research Associate in Epidemiology: amanda.hughes@bristol.ac.uk

Can we ever achieve “zero COVID”?

Marcus Munafo and George Davey Smith

Follow Marcus and George on Twitter

An important ongoing debate is whether the UK’s COVID strategy should focus on suppression (maintaining various restrictions to ensure the reproduction rate of the SARS-CoV-2 virus remains at or below 1), or elimination (reducing the number of infections to a sufficiently low level that restrictions could be removed). Independent SAGE has explicitly called for a “zero COVID UK”.

The latter is attractive, in that it brings the promise of a return to normality, rather than the ongoing maintenance of distancing measures, use of face coverings, etc. Independent SAGE has suggested that “a seven day rolling average of one new case per million per day could represent ‘control’” under a “zero COVID” regime. In other words, around 60 to 70 new cases per day across the UK.

But is “zero COVID”, in the context of ongoing large-scale testing, ever likely to be possible?

It’s unclear how accurate COVID19 tests are – which presents a challenge for the aim of reaching ‘zero COVID’.

Knowing how many cases there are in a population requires testing. But even the best tests are not perfect. Unfortunately, it might be difficult to know exactly how accurate COVID tests are – the RT-PCR (antigen) tests for SARS-CoV-2 are likely to be highly specific, but in the absence of an alternative gold standard to compare these against, calculating the precise specificity is challenging

If we assume excellent specificity (let’s say 99.9%), at current levels of daily testing in the UK (74,783 tests per day processed across pillars 1 and 2, as of the 28th July update), that would mean around 75 false positive results per day even if there were no true cases of COVID in the UK. A sensitivity of 98% would mean over 1400 false positives *.

Any call for “zero COVID” needs to consider the impact of false positives on the achievability of the criterion that would constitute this, against a background of high levels of testing. Whilst testing is only one source of information that needs to be interpreted in the light of other clinical and epidemiological data, on their own they will be important drivers of any response.

As cases fall to a low level, perhaps we could reduce levels of testing (and therefore the number of false positives). But, given the high potential for substantial undocumented infection and transmission, it is likely that large-scale testing will remain essential for some time, if only to monitor the rise and fall in infections, the causes of which we still don’t fully understand.

The generic Situationist slogan “be realistic, demand the impossible” is one that many political campaigns for equality and freedom can understand.

But in many concrete situations well-meaning phrases can prove to be meaningless when scrutinised. If attempts to achieve zero COVID before relaxing restrictions leads to a delay in the reopening of schools, for example, that will result in vast increases in future levels of inequality in educational outcomes, and the future social trajectories dependent on these.

As with other endemic human coronaviruses, SARS-CoV-2 will likely show high variability and fall to very low levels within any particular population for sustained periods; it will not be permanently eliminated on a continental scale, however. Perhaps a better alternative to the setting of laudable but effectively unachievable targets is to recognise this and plan accordingly.

Marcus Munafò and George Davey Smith

* The importance of the sensitivity (and specificity) of tests for COVID antibodies has been discussed here, and the same logic broadly applies to antigen tests.

Are schools in the COVID-19 era safe?

Sarah Lewis, Marcus Munafo and George Davey Smith

Follow Sarah, George and Marcus on Twitter

The COVID-19 pandemic caused by the SARS-COV2 virus in 2020 has so far resulted in a heavy death toll and caused unprecedented disruption worldwide. Many countries have opted for drastic measures and even full lockdowns of all but essential services to slow the spread of disease and to stop health care systems becoming overwhelmed. However, whilst lockdowns happened fast and were well adhered to in most countries, coming out of lockdown is proving to be more challenging. Policymakers have been trying to balance relaxing restriction measures with keeping virus transmission low. One of the most controversial aspects has been when and how to reopen schools.

Many parents and teachers are asking: Are schools safe?

The answer to this question depends on how much risk an individual is prepared to accept – schools have never been completely “safe”. Also, in the context of this particular pandemic, the risk from COVID-19 to an individual varies substantially by age, sex and underlying health status. However, from a historical context, the risk of death from contracting an infectious disease in UK schools (even in the era of COVD-19) is very low compared to just 40 years ago, when measles, mumps, rubella and whooping cough were endemic in schools. Similarly, from a global perspective UK schools are very safe – in Malawi, for example, the mortality rate for teachers is around five times higher than in the UK, with tuberculosis causing more than 25% of deaths among teachers.

In this blog post we use data on death rates to discuss safety, because there is currently better evidence on death rates by occupational status than, for example, infection rates. This is because death rates related to COVID-19 have been consistently reported by teh Office for National Statistics, whereas data on infection rates depends very much on the level of testing in the community (which has changed over time and differs by region).

Risks to children

Thankfully the risk of serious disease and death to children throughout the pandemic, across the UK and globally, has been low. Children (under 18 years) make up around 20% of the UK population, but account for only around 1.5% of those hospitalised with COVID-19. This age group have had better outcomes according to all measures compared to adults. As of the 12th June 2020, there have been 6 deaths in those with COVID-19 among those aged under 15 years across England and Wales. Whilst extremely sad, these deaths represent a risk of around 1 death per 2 million children. To place this in some kind of context, the number of deaths expected due to lower respiratory tract infections among this age group in England and Wales over a 3 month period is around 50 and 12 children would normally die due to road traffic accidents in Great Britain over a 3-month period.

Risks to teachers

Our previous blog post concluded that based on available evidence the risk to teachers and childcare workers within the UK from Covid-19 did not appear to be any greater than for any other group of working age individuals. It considered mortality from COVID-19 among teachers and other educational professionals who were exposed to the virus prior to the lockdown period (23rd March 2020) and had died by the 20th April 2020 in the UK. This represents the period when infection rates were highest, and when children were attending school in large numbers. There were 2,494 deaths among working-age individuals up to this date, and we found that the 47 deaths among teachers over this period represented a similar risk to all professional occupations – 6.7 (95% CI 4.1 to 10.3) per 100,000 among males and 3.3 (95% CI 2.0 to 4.9) per 100,000 among females.

The Office for National Statistics (ONS) has since updated the information on deaths according to occupation to include all deaths up to the 25th May 2020. The new dataset includes a further 2,267 deaths among individuals with COVID-19. As the number of deaths had almost doubled during this extended period, so too had the risk. A further 43 deaths had occurred among teaching and education professionals, bringing the total number of deaths involving COVID-19 among this occupational group to 90. It therefore appears that lockdown (during which time many teachers have not been in school) has not had an impact on the rate at which teachers have been dying from COVID-19.

As before, COVID-19 risk does not appear greater for teachers than other working age individuals

The revised risk to teachers of dying from COVID-19 remains very similar to the overall risk for all professionals at 12.9 (95% CI 9.3 to 17.4) per 100,000 among all male teaching and educational professionals and 6.0 (95% CI 4.2 to 8.1) per 100,000 among all females, compared with 11.6 (95%CI 10.2 to 13.0) per 100,000 and 8.0 (95%CI 6.8 to 9.3) per 100,000 among all male and female professionals respectively. It is useful to look at the rate at which we would normally expect teaching and educational professionals to die during this period, as this tells us by how much COVID-19 has increased mortality in this group. The ONS provide this in the form of average mortality rates for each occupational group for same 11 week period over the last 5 years.  The mortality due to COVID-19 during this period represents 33% for males and 19% for females of their average mortality over the last 5 years for the same period. For male teaching and educational professionals, the proportion of average mortality due to COVID-19 is very close to the value for all working-aged males (31%) and all male professionals (34%). For females the proportion of average mortality due to COVID-19 is lower than for all working-aged females (25%) and for female professionals (25%). During the pandemic period covered by the ONS, there was little evidence that deaths from all causes among the group of teaching and educational professionals were elevated above the 5-year average for this group.

Teaching is a comparatively safe profession

It is important to note that according to ONS data on adults of working age (20-59 years) between 2001-2011, teachers and other educational professionals have low overall mortality rates compared with other occupations (ranking 3rd  safest occupation for women and 6th for men). The same study found a 3-fold difference between annual mortality among teachers and among the occupational groups with the highest mortality rates (plant and machine operatives for women and elementary construction occupations among men). These disparities in mortality from all causes also exist in the ONS data covering the COVID-19 pandemic period, but were even more pronounced with a 7-fold difference between males teaching and educational professionals and male elementary construction occupations, and a 16-fold difference between female teachers and female plant and machine operatives.

There is therefore currently no indication that teachers have an elevated risk of dying from COVID-19 relative to other occupations, and despite some teachers having died with COVID19, the mortality rate from all causes (including COVID19) for this occupational group over this pandemic period is not substantially higher than the 5 year average.

Will reopening schools increase risks to teachers?

One could argue that the risk to children and teachers has been low because schools were closed for much of the pandemic, and children have largely been confined to mixing with their own households, so that when schools open fully risk will increase. However, infection rates in the community are now much lower than they were at their peak, when schools were fully open to all pupils without social distancing. Studies which have used contract tracing to determine whether infected children have transmitted the disease to others have consistently shown that they have not, although the number of cases included has been small, and asymptomatic children are often not tested. Modelling studies estimate that even if schools fully reopen without social distancing, this is likely to have only modest effects on virus transmission in the community. If infection levels can be controlled – for example by testing and contact tracing efforts – and cases can be quickly isolated, then we believe that schools pose a minimal risk in terms of the transmission of COVID, and to the health of teachers and children. Furthermore, the risk is likely to be more than offset by the harms caused by ongoing disruption to children’s educational opportunities.

Sarah Lewis is a Senior Lecturer in Genetic Epidemiology in the department of Population Health Sciences, and is an affiliated member of the MRC Integrative Epidemiology Unit (IEU), University of Bristol.

Marcus Munafo is a Professor of Biological Psychology, in the School of Psychology Science and leads the Causes, Consequences and Modification of Health Behaviours programme of research in the IEU, University of Bristol.

George Davey Smith is a Professor of Clinical Epidemiology, and director of the MRC IEU, University of Bristol.

Maximum cigarette pack size: a neglected aspect of tobacco control

Written by Anna Blackwell, Senior Research Associate

Follow Bristol Tobacco and Alcohol Research Group (TARG) on twitter

The manufacturing or importing of packs of cigarettes with fewer than 20 cigarettes per pack was prohibited in the UK when the EU Tobacco Products Directive and standardised packaging legislation were fully implemented in May 2017. This change was aimed at reducing the affordability of cigarettes and thereby discouraging young people from smoking. This directive also required the removal of branding and established a standard shape and dark green colour for packaging, including pictorial health warnings, which prevented the use of packaging for promotion and reduced its appeal.

However, the tobacco industry has been able to exploit loopholes in recent packaging regulations, including the absence of a regulated maximum pack size, by introducing non-standard and larger pack sizes to the market to distinguish products. This is a public health concern given evidence that larger pack sizes are linked to increased smoking, and could undermine existing tobacco control success.

Evidence shows that larger pack sizes are linked to increased smoking.

In a recent Addiction Opinion and Debate paper, we proposed that a cap on cigarette pack size should be introduced; a pragmatic solution would be to permit only a single pack size of 20, which is now the minimum in many countries. This approach would reduce the number of cigarettes in packs in several countries such as Australia – where packs up to sizes of 50 are available – and prevent larger sizes being introduced elsewhere.

Capping cigarette pack size therefore has the potential to both reduce smoking and prevent increased smoking. While the health benefits of reducing smoking alone are small, it may have important indirect effects on health through its role in facilitating quitting. Those smoking fewer cigarettes per day are more likely to attempt to quit and succeed in doing so. Trials of smoking-reduction interventions have also found that these can lead to increased quitting when combined with nicotine replacement therapy.

Our Opinion and Debate paper drew on evidence from a range of sources including industry documents and analyses, population surveys, intervention trials and Mendelian randomization analyses. Together these suggest that consumption increases with larger pack size, and cessation increases with reduced consumption. However, direct experimental evidence is not currently available to determine whether pack size influences the amount of tobacco consumed, or whether the association is due to other factors.

People who want to quit may be using smaller packs as a method of self-control, and smokers who successfully cut down and later quit may be more motivated to do so. Cost is also an important factor and larger packs may be linked to increased smoking because they have a lower cost per cigarette. Further research is needed to determine whether the associations between pack size, smoking and cessation are causal to estimate the impact of policies to cap cigarette pack size.

Commentaries on our Opinion and Debate paper, published in the May 2020 Issue of Addiction highlight the need to understand the mechanisms for the associations observed between pack size and smoking in order to identify the optimal cigarette pack size. Although mandating packs of 20 is a pragmatic approach, pack size regulation needs to achieve a compromise between tobacco affordability and smokers’ self-regulation. Nevertheless, the policy debate should start now to address this neglected aspect of tobacco control.

To find out more visit the Behaviour Change by Design website or follow us on Twitter @BehavChangeDsgn @BristolTARG

 

This blog post is reposted from the TARG blog.

Are teachers at high risk of death from Covid19?

Sarah Lewis, George Davey Smith and Marcus Munafo

Follow Sarah, George and Marcus on Twitter

Due to the SARS-CoV-2 pandemic schools across the United Kingdom were closed to all but a small minority of pupils (children of keyworkers and vulnerable children) on the 20th March 2020, with some schools reporting as few as 5 pupils currently attending. The UK government have now issued guidance that primary schools in England should start to accept pupils back from the 1st June 2020 with a staggered return, starting with reception, year 1 and year 6.

Concern from teachers’ unions

This has prompted understandable concern from the  teachers’ unions, and on the 13th May, nine unions which represent teachers and education professionals signed a joint statement calling on the government to postpone reopening school on the 1st June, “We all want schools to re-open, but that should only happen when it is safe to do so. The government is showing a lack of understanding about the dangers of the spread of coronavirus within schools, and outwards from schools to parents, sibling and relatives, and to the wider community.” At the same time, others have suggested that the harms to many children due to neglect, abuse and missed educational opportunity arising from school closures outweigh the small increased risk to children, teachers and other adults of catching the virus.

What risk does Covid19 pose to children?

Weighing up the risks to children and teachers

So what do we know about the risk to children and to teachers? We know that children are about half as likely to catch the virus from an infected person as adults, and  if they do catch the virus they  are likely to have only mild symptoms.  The current evidence, although inconclusive, also suggests that they may be less likely to transmit the virus than adults.  However, teachers have rightly pointed out that there is a risk of transmission between the teachers themselves and between parents and teachers.

The first death from COVID-19 in England was recorded at the beginning of March 2020 and by the 8th May 2020 39,071 deaths involving COVID-19 had been reported in England and Wales. Just three of these deaths were among children aged under 15 years and  only a small proportion of the deaths (4416 individuals, 11.3%) were among working aged people.  Even among this age group risk is not uniform; it increases sharply with age from 2.6 in 100,000 for 25-44 years olds with a ten fold increase to 26 in  100,000 individuals for those aged 45-64.

Risks to teachers compared to other occupations

In addition, each underlying health condition increases the risk of dying from COVID-19, with those having at least 1 underlying health problem making up most cases.   The Office for National Statistics in the UK have published age standardised deaths by occupation for all deaths involving COVID-19 up to the 20th April 2020. Most of the people dying by this date would have been infected at the peak of the pandemic in the UK  prior to the lockdown period. They found that during this period there were 2494 deaths involving Covid-19 in the working age population. The mortality rate for Covid-19 during this period was 9.9 (95% confidence intervals 9.4-10.4) per 100,000 males and 5.2 (95%CI 4.9-5.6) per 100,000 females, with Covid-19 involved in around 1 in 4 and 1 in 5 of all deaths among males and females respectively.

Amongst teaching and education professionals (which includes school teachers, university lecturers and other education professionals) a total of 47 deaths (involving Covid-19) were recorded, equating to mortality rates of 6.7 (95%CI 4.1-10.3) per 100,000 among males and 3.3 (95%CI 2.0-4.9) per 100,000 among females, which was very similar to the rates of 5.6 (95%CI 4.6-6.6) per 100,000 among males and 4.2(95%CI 3.3-5.2) per 100,000 females for all professionals. The mortality figures for all education professionals includes 7 out of 437000 (or 1.6 per 100,000 teachers) primary and nursery school teachers and 17 out of 395000 (or 4.3 per 100,000 teachers) secondary school teachers.  A further 20 deaths occurred amongst childcare workers giving a mortality rate amongst this group of 3.4 (95%CI=2.0-5.5) per 100,000 females (males were highly underrepresented in this group), this is in contrast to rates of 6.5 (95%CI=4.9-9.1) for female sales assistants and 12.7(95%CI= 9.8-16.2) for female care home workers.

Covid-19 risk does not appear greater for teachers than other working age individuals

In summary, based on current evidence the risk to teachers and childcare workers within the UK from Covid-19 does not appear to be any greater than for any other group of working age individuals. However, perceptions of elevated risk may have occurred, prompting some to ask “Why are so many teachers dying?” due to the way this issue is portrayed in the media with headlines such as “Revealed: At least 26 teachers have died from Covid-19” currently on the https://www.tes.com website. This kind of reporting, along with the inability of the government to communicate the substantial differences in risk between different population groups – in particular according to age – has caused understandable anxiety among teachers. Whilst, some teachers may not be prepared to accept any level of risk of becoming infected with the virus whilst at work, others may be reassured that the risk to them is small, particularly given that we all accept some level of risk in our lives, a value that can never be zero.

Likely impact on transmission in the community is unclear

As the majority of parents or guardians of school aged children will be in the 25-45 age range, the risk to them  is also likely to be small. Questions remain however around the effect of school openings on transmission in the community and the associated risk. This will be affected by many factors including the existing infection levels in the community, the extent to which pupils, parents and teachers are mixing outside of school (and at the school gate) and mixing between individuals of different age groups. This is the primary consideration of the government Scientific Advisory Group for Emergencies (SAGE) who are using modelling based on a series of assumptions to determine the effect of school openings on R0.

 

Sarah Lewis is a Senior Lecturer in Genetic Epidemiology in the department of Population Health Sciences, and is an affiliated member of the MRC Integrative Epidemiology Unit (IEU), University of Bristol

George Davey Smith is a Professor of Clinical Epidemiology, and director of the MRC IEU, University of Bristol

Marcus Munafo is a Professor of Biological Psychology, in the School of Psychology Science and leads the Causes, Consequences and Modification of Health Behaviours programme of research in the IEU, University of Bristol.

 

What can genetics tell us about how sleep affects our health?

Deborah Lawlor, Professor of Epidemiology, Emma Anderson, MRC Research Fellow, Marcus Munafò, Professor of Experimental Psychology, Mark Gibson, PhD student, Rebecca Richmond, Vice Chancellor’s Research Fellow

Follow Deborah, Marcus, and Rebecca on Twitter

Association is not causation – are we fooled (confounded) when we see associations between sleep problems and disease?

Sleep is important for health. Observational studies show that people who report having sleep problems are more likely to be overweight, and have more health problems including heart disease, some cancers and mental health problems.

A major problem with conventional observational studies is that we cannot tell whether these associations are causal; does being overweight cause sleep problems, or do sleep problems cause people to become overweight? Alternatively, factors that influence how we sleep may also influence our health. For example, smoking might cause sleep problems as well as heart disease and so we are fooled (confounded) into thinking sleep problems cause heart disease when it is really all explained by smoking. In the green paper Advancing our Health: Prevention in the 2020s, the UK Government acknowledged that sleep has had little attention in policy, and that causality between sleep and health is likely to run in both directions.

But, how can we determine the direction of causality for sure? And, how do we make sure we are results are not confounded?

Randomly allocated genetic variation

Our genes are randomly allocated to us from our parents when we are conceived. They do not change across our lifespan, and cannot be changed by smoking, overweight or ill health.

Here at the MRC Integrative Epidemiology Unit we have developed a research method called Mendelian randomization, which uses this family-level random allocation of genes to explore causal effects. To find out more about Mendelian randomization take a look at this primer from the Director of the Unit (Prof George Davey Smith).

In the last two years, we and colleagues from the Universities of Manchester, Exeter and Harvard have identified large numbers of genetic variants that relate to different sleep characteristics. These include:

  • Insomnia symptoms
  • How long, on average, someone sleeps each night
  • Chronotype (whether someone is an ‘early bird’ or ‘lark’ and prefers mornings, or a ‘night owl’ and prefers evenings). Chronotype is thought to reflect variation in our body clock (known as circadian rhythms).

We can use these genetic variants in Mendelian randomization studies to get a better understanding of whether sleep characteristics affect health and disease.

What we did

In our initial studies we used Mendelian randomization to explore the effects of sleep duration, insomnia and chronotype on body mass index, coronary heart disease, mental health problems, Alzheimer’s disease, and breast cancer. We analysed whether the genetic traits that are related to sleep characteristics – rather than the sleep characteristics themselves – are associated with the health outcomes. We combined those results with the effect of the genetic variants on sleep traits which allows us to estimate a causal effect. Using genetic variants rather than participants’ reports of their sleep characteristics makes us much more certain that the effects we identify are not due to confounding or reverse causation.

Are you a night owl or a lark?

What we found

Our results show a mixed picture; different sleep characteristics have varying effects on a range of health outcomes.

What does this mean?

Having better research evidence about the effects of sleep traits on different health outcomes means that we can give better advice to people at risk of specific health problems. For example, developing effective programmes to alleviate insomnia may prevent coronary heart disease and depression in those at risk. It can also help reduce worry about sleep and health, by demonstrating that some associations that have been found in previous studies are not likely to reflect causality.

If you are worried about your own sleep, the NHS has some useful guidance and signposting to further support.

Want to find out more?

Contact the researchers

Deborah A Lawlor mailto:d.a.lawlor@bristol.ac.uk

Further reading

This research has been published in the following open access research papers:

Genome-wide association analyses of chronotype in 697,828 individuals provides insights into circadian rhythms. Nature Comms (2019) https://www.nature.com/articles/s41467-018-08259-7

Biological and clinical insights from genetics of insomnia symptoms.  Nature Gen. (2019) https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6415688/

Genome-wide association study identifies genetic loci for self-reported habitual sleep duration supported by accelerometer-derived estimates. Nature Comms. (2019) https://www.nature.com/articles/s41467-019-08917-4

Investigating causal relations between sleep traits and risk of breast cancer in women: mendelian randomisation study. BMJ (2019) https://www.bmj.com/content/365/bmj.l2327

Is disrupted sleep a risk factor for Alzheimer’s disease? Evidence from a two-sample Mendelian randomization analysis. https://www.biorxiv.org/content/10.1101/609834v1 (open access pre-print)

Evidence for Genetic Correlations and Bidirectional, Causal Effects Between Smoking and Sleep Behaviors. Nicotine and Tobacco (2018) https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6528151/

Do development indicators underlie global variation in the number of young people injecting drugs?

Dr Lindsey Hines, Sir Henry Wellcome Postdoctoral Fellow in The Centre for Academic Mental Health & the Integrative Epidemiology Unit, University of Bristol

Dr Adam Trickey, Senior Research Associate in Population Health Sciences, University of Bristol

Follow Lindsey on Twitter

Injecting drug use is a global issue: around the world an estimated 15.6 million people inject psychoactive drugs. People who inject drugs tend to begin doing so in adolescence, and countries that have larger numbers of adolescents who inject drugs may be at risk of emerging epidemics of blood borne viruses unless they take urgent action. We mapped the global differences in the proportion of adolescents who inject drugs, but found that we may be missing the vital data we need to protect the lives of vulnerable young people. If we want to prevent HIV, hepatitis C, and overdose from sweeping through a new generation of adolescents we urgently need many countries to scale up harm reduction interventions, and to collect accurate which can inform public health and policy.

People who inject drugs are engaging in a behaviour that can expose them to multiple health risks such as addiction, blood-borne viruses, and overdose, and are often stigmatised. New generations of young people are still starting to inject drugs, and young people who inject drugs are often part of other vulnerable groups.

Much of the research into the causes of injecting drug use focuses on individual factors, but we wanted to explore the effect of global development on youth injecting. A recent systematic review showed wide country-level variation in the number of young people who comprise the population of people who inject drugs. By considering variation in countries, we hoped to be able to inform prevention and intervention efforts.

It’s important to note that effective interventions can reduce the harms of injecting drug use. Harm reduction programmes provide clean needles and syringes to reduce transmission of blood borne viruses. Opiate substitution therapy seeks to tackle the physical dependence on opiates that maintains injecting behaviour and has been shown to improve health outcomes.

What we did

Through a global systematic review and meta-analysis we aimed to find data on injecting drug use in published studies, public health and policy documents from every country. We used these data to estimate the global percentage of people who inject drugs that are aged 15-25 years old, and also estimated this for each region and country. We wanted to understand what might underlie variation in the number of young people in populations of people who inject drugs, and so we used data from the World Bank to identify markers of a country’s wealth, equality, and development.

What we found

Our study estimated that, globally, around a quarter of people who inject drugs are adolescents and young adults. Applied to the global population, we can estimate approximately 3·9 million young people inject drugs. As a global average, people start injecting drugs at 23 years old.

Estimated percentage of young people amongst those who inject drugs in each country

We found huge variation in the percentage of young people in each country’s population of people who inject drugs. Regionally, Eastern Europe had the highest proportion of young people amongst their populations who inject drugs, and the Middle Eastern and North African region had the lowest. In both Russia and the Philippines, over 50% of the people who inject drugs were aged 25 or under, and the average age of the populations of people who inject drugs was amongst the lowest observed.

Average age of the population of people who inject drugs in each country

In relation to global development indicators, people who inject drugs were younger in countries with lower wealth (indicated through Gross Domestic Product per capita) had been injecting drugs for a shorter time period. In rapidly urbanising countries (indicated through urbanisation growth rate) people were likely to start injecting drugs at later ages than people in countries with a slower current rate of urbanisation. We didn’t find any relationships between the age of people who inject drugs and a country’s youth unemployment, economic equality, or level provision of opiate substitution therapy.

However, many countries were missing data on injecting age and behaviours, or injecting drug use in general, which could affect these results.

What this means

1. The epidemic of injecting drug use is being maintained over time.

A large percentage of people who inject drugs are adolescents, meaning that a new generation are being exposed to the risks of injecting – and we found that this risk was especially high in less wealthy countries.

2. We need to scale up access to harm reduction interventions

There are highly punitive policies towards drug use in the countries with the largest numbers of young people in their populations of people who inject drugs. Since 2016, thousands of people who use drugs in the Philippines have died at the hands of the police. In contrast, Portugal has adopted a public health approach to drug use and addiction for decades, taking the radical step of taking people caught with drugs or personal use into addiction services rather than prisons. The rate of drug-related deaths and HIV infections in Portugal has since plummeted, as has the overall rate of drug use amongst young people: our data show that Portugal has a high average age for its population of people who inject drugs. If we do not want HIV, hepatitis C, and drug overdoses to sweep through a new generation of adolescents, we urgently need to see more countries adopting the approach pioneered by Portugal, and scaling up access to harm reduction interventions to the levels recommended by the WHO.

3. We need to think about population health, and especially mental health, alongside urban development.

Global development appears to be linked to injecting drug use, and the results suggest that countries with higher urbanisation growth are seeing new, older populations beginning to inject drugs. It may be that changes in environment are providing opportunities for injecting drug use that people hadn’t previously had. It’s estimated that almost 70% of the global population will live in urban areas by 2050, with most of this growth driven by low and middle-income countries.

4. We need to collect accurate data

Despite the health risks of injecting drug use, and the urgent need to reduce risks for new generations, our study has revealed a paucity of data monitoring this behaviour. Most concerning, we know the least about youth injecting drug use in low- and middle-income countries: areas likely to have the highest numbers of young people in their populations of people who inject drugs. Due to the stigma and the illicit nature of injecting drug use it is often under-studied, but by failing to collect accurate data to inform public health and policy we are risking the lives of vulnerable young people.

Contact the researchers

Lindsey.hines@bristol.ac.uk

Lindsey is funded by the Wellcome Trust.

Using evidence to advise public health decision makers: an insider’s view

This blog post reviews a recent seminar hosted by the MRC IEU, PolicyBristol and the Bristol Population Health Science Institute.

Public health is one of the most contested policy areas. It brings together ethical and political issues and evidence on what works, and affects us all as citizens.

Researchers produce evidence and decision-makers receive advice – but how does evidence become advice and who are the players who take research findings and present advice to politicians and budget-holders?

We were pleased to welcome a diverse audience of around 75 multidisciplinary academics, policymakers and practitioners to hear our seminar speakers give a range of insider perspectives on linking academic research with national and local decisions on what to choose, fund and implement.

In this blog post we summarise the seminar, including links to the slides and event recording.

Seminar audience
Seminar attendees in the Coutts lecture theatre. Image credit: Julio Hermosilla Elgueta

Chair David Buck from The King’s Fund opened the event, highlighting the importance of conversations between different sectors of the evidence landscape, and of local decision-making in this context.

‘The art of giving advice’

The session was kicked off by Richard Gleave, Deputy Chief Executive, Public Health England, who is also undertaking a PhD on how evidence is used in public health policy decision making.

His presentation ‘Crossing boundaries – undertaking knowledge informed public health’ set the context, observing that most academic teams – from microbiology labs to mental health researchers – aim to improve policy and practice; but ‘the art of giving advice is as important and challenging as the skill required to review the evidence’.

Richard then introduced a range of provocations and stereotypes about how the policy decision making process can be framed.

Citing Dr Kathryn Oliver, he encouraged attendees to challenge the idea that there’s an ‘evidence gap’ to be crossed, and instead focus on doing good working together to improve the public’s health.

Giving an example of the Institute for Government’s analysis of how the smoking ban was enacted, he noted the role of a small number of influential groups and individuals in securing a total ban in 2007. He encouraged actively crossing the boundaries between academia, policy and practice, and working with boundary organisations and influencers as part of this process.

‘Partnerships between science and society’

Professor Isabel Oliver gave a second national perspective.

Speaking as a research-active Director of Research, Translation and Innovation and Deputy Director of the National Infection Service, she suggested that ‘Partnerships between Science and Society’ are the key to evidence based public health.

She questioned why is it when we have such an abundance of research, we still don’t have the evidence we need? And why does it take so long to implement research findings? She argued that a key issue here is relevance; how relevant is the research being produced, especially to current policy priorities?

Isabel outlined challenges including:

  • Needing evidence quickly in response to public health emergencies, and not being able to access it, for example how to bottle-feed babies during flooding crises, or whether to close schools during flu pandemics
  • Mismatched policy and research priorities; e.g. policy needing evidence on the impact of advertising on childhood obesity, but research focusing on the genetics of obesity
  • The (unhelpful) prevalence of ‘more research needed’ as a conclusion, and knowing when the evidence is sufficient to make a decision
  • A need to develop trust between stakeholders, made more challenging by the frequency of policy colleagues moving roles.

She also questioned whether the paradigm of evidence-based medicine works for complex issues such as public health or environmental policy.

Isabel concluded with some observations; that broader and more collaborative research questions that address the real issues are needed; and collaborating with a broad range of stakeholders, including industry and finance, should not be discounted.

She finished by reiterating a call for public health advice that is relevant, and responds to a policy ‘window’ being open.

Seminar speakers L-R: Dr Olivia Maynard, Richard Gleave, Professor Isabel Oliver and Christina Gray. Image credit: Julio Hermosilla Elgueta

‘Local perspective’

Christina Gray, Director of Public Health at Bristol City Council gave the local view, providing a helpful explanation of her role and the process of decision making within a local authority.

She outlined three key principles:

  • The democratic principle; elected members are ‘the council’; officers (including her role) provide advice. Local authorities are close to their people and are publicly accountable. Their decisions are formally scrutinised and need to be justified, and resource allocation is a key – and stark – challenge, especially in the context of austerity.
  • The narrative principle: how the society that the authority represents holds multiple legitimate (and competing or conflicting) perspectives and realities, which all need to be considered.
  • The (social) scientific principle; the development of human knowledge in a systematic way – which is then shared into the democratic process, as one of a range of narratives.

Christina outlined a case study example of an initiative on period dignity which Bristol City Council is leading as part of Bristol’s One City Plan, and how the evidence base for the programme was located and used. She posed the question of what evidence matters locally, and suggested that evidence of impact, economic evidence, and retrospective evidence that demonstrates whether what has been done works, in order to build on it, are the most helpful. To close, Christina highlighted the importance of being ‘paradigm literate’ in order to navigate the complexity of public health decision making.

Academic perspective

Our final speaker, Dr Olivia Maynard, gave an academic perspective on how to advise decision makers.

Focusing on practical tips, she outlined her own work on tobacco, smoking, e-cigarettes, alcohol and other drugs and how she has engaged with various opportunities to work with policymakers.

Starting with a clear case for doing the work (it’s important, it’s interesting, to create impact), she went on to outline methods of engagement:

  • Proactively presenting your work; introduce yourself to policymakers interested in your area such as MPs, Peers, APPGs, subject specialists in parliamentary research services, advocacy groups, and PolicyBristol; review Hansard and Early Day Motions; get involved in parliamentary events
  • Respond to calls for evidence (University of Bristol researchers can find curated opportunities via the PolicyBristol PolicyScan)
  • Work directly with policymakers, for example via Policy Fellowships (for example with POST)

Olivia outlined some reflections around the differences between academia and policymaking.

Timelines for action is one, but she also used the changes towards plain packaging as an example to note that the policymaking process can span numerous years, presenting many opportunities for intervention.

She referred back to Christina’s point about ‘multiple competing realities’ to highlight that evidence is one of many factors to consider in policymaking.

She also encouraged academics to challenge ‘imposter syndrome’, by emphasising ‘you are more of an expert than you think you are’, and needing to make yourself known to be offered opportunities.

Where next?

Chair David Buck highlighted a number of themes running throughout the presentations including recognising the paradigms used by different stakeholders; questioning what counts as evidence, and being able to provide advice from an uncertain evidence base; and what these themes mean for all of us (and how willing are we to act on these reflections?)

The seminar concluded with a facilitated Q&A session spanning topics such as:

  • Should all research which influences policy be coproduced with user groups and policymakers?
  • What kind of ‘payback’ do stakeholder organisations need for their involvement in research projects?
  • How should researchers develop the skills needed to cross boundaries?
  • What funding is available for policy relevant research?
  • How can we make our evidence ‘stand out’?
  • Should academics have a responsibility to critique policy?

The seminar started numerous conversations which we hope to continue.

Chair David Buck facilitates our Q&A. Image credit: Julio Hermosilla Elgueta

Access the slides:

1. Richard Gleave Crossing boundaries – undertaking knowledge informed public health

2. Isabel Oliver Partnerships between science and society

3. Christina Gray Evidence into practice

4. Olivia Maynard An academic’s perspective

View a recording of the event on the IEU’s YouTube channel: https://www.youtube.com/watch?v=-ew-RvzV-D0 

Contact lindsey.pike@bristol.ac.uk if you’d like to hear about future events.

 

Institutionalising preventive health: what are the key issues for Public Health England?

Professor Paul Cairney, University of Stirling

Dr John Boswell, University of Southampton

Richard Gleave, Deputy Chief Executive and Chief Operating Officer, Public Health England

Dr Kathryn Oliver, London School of Hygiene and Tropical Medicine

The Green Paper on preventing ill health was published earlier this week, and many have criticised that proposals do not go far enough. Our guest blog explores some of the challenges that Public Health England face in providing evidence-informed advice. Read on to discover the reflections from a recent workshop on using evidence to influence local and national strategy and their implications for academic engagement with policymakers.

On the 12th June, at the invitation of Richard Gleave, Professor Paul Cairney and Dr John Boswell led a discussion on ‘institutionalising’ preventive health with senior members of Public Health England (PHE).

It follows a similar event in Scotland, to inform the development of Public Health Scotland, and the PHE event enjoyed contributions from key members of NHS Health Scotland.

Cairney and Boswell drew on their published work – co-authored with Dr Kathryn Oliver and Dr Emily St Denny (University of Stirling) – to examine the role of evidence in policy and the lessons from comparable experiences in other public health agencies (in England, New Zealand and Australia).

This post summarises their presentation and reflections from the workshop (gathered using the Chatham House rule).

The Academic Argument

Governments face two major issues when they try to improve population health and reduce health inequalities:

  1. Should they ‘mainstream’ policies – to help prevent ill health and reduce health inequalities – across government and/ or maintain a dedicated government agency?
  2. Should an agency ‘speak truth to power’ and seek a high profile to set the policy agenda?

Our research provides three messages to inform policy and practice:

  1. When governments have tried to mainstream ‘preventive’ policies, they have always struggled to explain what prevention means and reform services to make them more preventive than reactive.
  2. Public health agencies could set a clearer and more ambitious policy agenda. However, successful agencies keep a low profile and make realistic demands for policy change. In the short term, they measure success according to their own survival and their ability to maintain the positive attention of policymakers.
  3. Advocates of policy change often describe ‘evidence based policy’ as the answer. However, a comparison between (a) specific tobacco policy change and (b) very general prevention policy shows that the latter’s ambiguity hinders the use of evidence for policy. Governments use three different models of evidence-informed policy. These models are internally consistent but they draw on assumptions and practices that are difficult to mix and match. Effective evidence use requires clear aims driven by political choice.

Overall, they warn against treating any response – (a) the idiom ‘prevention is better than cure’, (b) setting up a public health agency, or (c) seeking ‘evidence based policy’ – as a magic bullet.

Major public health changes require policymakers to define their aims, and agencies to endure long enough to influence policy and encourage the consistent use of models of evidence-informed policy. To do so, they may need to act like prevention ninjas, operating quietly and out of the public spotlight, rather than seeking confrontation and speaking truth to power.

 

Image By Takver from Australia [CC BY-SA 2.0 (https://creativecommons.org/licenses/by-sa/2.0)], via Wikime

The Workshop Discussion

The workshop discussion highlighted an impressive level of agreement between the key messages of the presentation and the feedback from most members of the PHE audience.

One aspect of this agreement was predictable, since Boswell et al’s article describes PHE as a relative success story and bases its analysis of prevention ‘ninjas’ on interviews with PHE staff.

However, this strategy is subject to frequent criticism. PHE has to manage the way it communicates with multiple audiences, which is a challenge in itself.  One key audience is a public health profession in which most people see their role as to provoke public debate, shine a light on corporate practices (contributing to the ‘commercial determinants of health’), and criticise government inaction. In contrast, PHE often seeks to ensure that quick wins are not lost, must engage with a range of affected interests, and uses quiet diplomacy to help maintain productive relationships with senior policymakers. Four descriptions of this difference in outlook and practice stood out:

  1. Walking the line. Many PHE staff gauge how well they are doing in relation to the criticism they receive. Put crudely, they may be doing well politically if they are criticised equally by proponents of public health intervention and vocal opponents of the ‘nanny state’.
  2. Building and maintaining relationships. PHE staff recognise the benefit of following the rules of the game within government, which include not complaining too loudly in public if things do not go your way, expressing appreciation (or at least a recognition of policy progress) if they do, and being a team player with good interpersonal skills rather than simply an uncompromising advocate for a cause. This approach may be taken for granted by interest groups, but tricky for public health researchers who seek a sense of critical detachment from policymakers.
  3. Managing expectations. PHE staff recognise the need to prioritise their requirements from government. Phrases such as ‘health in all policies’ often suggest the need to identify a huge number of crucial, and connected, policy changes. However, a more politically feasible strategy is to identify a small number of discrete priorities on which to focus intensely.
  4. Linking national and local. PHE staff who work closely with local government, the local NHS, and other partners, described how they can find it challenging to link ‘place-based’ and ‘national policy area’ perspectives. Local politics are different from national politics, though equally important in implementation and practice.

There was also high agreement on how to understand the idea of ‘evidence based’ or ‘evidence informed’ policymaking (EBPM). Most aspects of EBPM are not really about ‘the evidence’. Policy studies often suggest that, to improve evidence use requires advocates to:

  • find out where the action is, and learn the rules and language of debate within key policymaking venues, and
  • engage routinely with policymakers, to help them understand their audience, build up trust based on an image of scientific credibility and personal reliability, and know when to exploit temporary opportunities to propose policy solutions.
  • To this we can add the importance of organisational morale and a common sense of purpose, to help PHE staff operate effectively while facing unusually high levels of external scrutiny and criticism. PHE staff are in the unusual position of being (a) part of the meetings with ministers and national leaders, and (b) active at the front-line with professionals and key publics.

In other words, political science-informed policy studies, and workshop discussions, highlighted the need for evidence advocates to accept that they are political actors seeking to win policy arguments, not objective scientists simply seeking the truth. Scientific evidence matters, but only if its advocates have the political skills to know how to communicate and when to act.

Although there was high agreement, there was also high recognition of the value of internal reflection and external challenge. In that context, one sobering point is that, although PHE may be relatively successful now (it has endured for some time), we know that government agencies are vulnerable to disinvestment and major reform. This vulnerability underpins the need for PHE staff to recognise political reality when they pursue evidence-informed policy change. Put bluntly, they often have to strike a balance between two competing pressures – being politically effective or insisting on occupying the moral high ground – rather than assuming that the latter always helps the former.

This blog post was originally published on the PolicyBristol blog.

How can researchers engage with policy?

Dr Alisha Davies

Dr Laura Howe

Prof Debbie Lawlor

Dr Lindsey Pike

Follow Alisha, Laura, Debbie and Lindsey on Twitter

Policy engagement is becoming more of a priority in academic life, as emphasis shifts from focusing purely on academic outputs to creating impact from research. Research impact is defined by UKRI as ‘the demonstrable contribution that excellent research makes to society and the economy’.

On 25 June 2019 the IEU held its first Engagers’ Lunch event, which focused on policy engagement. Joined by Dr Alisha Davies, Head of Research from Public Health Wales, Dr Laura Howe, Professor Debbie Lawlor and Dr Lindsey Pike from the IEU facilitated discussion drawing on their experiences – from both sides of the table – of connecting research and policy. Below we summarise advice from our speakers about engaging with policy.

The benefits of engaging with policy & how to do it

  • As an academic you need to consider what your ‘offer’ is. What expertise do you bring? This may be topic specific knowledge or relate to strong academic skills such as critical approaches to complex challenges, novel methods in evaluation, health economics. Recognise where you add value; the remit of academia is to develop robust evidence in response to complex and challenging questions using reliable methods – a gap that those in practice and /or policy cannot fill alone.
  • Find the right people to engage with – who are the decision makers in your area of research? Listen to what is currently important to inform action / policy. Read through local and national strategies in your topic of expertise to understand the wider landscape and where your work might inform, or where you might be able to address some of those key gaps. Academics can also submit evidence to policy (colleagues from the University of Bristol can access PolicyBristol’s policy scan, which lists current opportunities to engage).
  • Be visible and actively engage. Find out what local events are going on in your area related to your research and go along to meet local public health professionals. It’s a good way to meet people, find commonalities and form collaborations.
  • Condense your new research into a short briefing, identify what it adds to the existing evidence base, how does it inform given the wider context.
  • As an academic you will have a network of other research colleagues. Policymakers value being able to draw on this network for information. When providing evidence, don’t just cite your own – objectivity is one of the key advantages of working with academics, and policymakers value your intellectual independence. Your knowledge of the broader evidence base is invaluable.
  • Setting up a research steering group or stakeholder panel can be a great way to develop your relationships and ensure your research is speaking to policy, practice or industry priorities. Key to this is getting the right people involved – this blog post from Fast Track Impact has some useful advice.

The challenges of engaging with policy & how to navigate them

  • Academic and policymaking timescales are different. Policymakers need an answer yesterday while academics may not feel comfortable with providing a definitive response without time for reflection. There’s a need for flexibility on both sides.
  • There are also tensions between the perceived need for certainty and ability to be able to provide it. Policymakers may want ‘an answer’, but the evidence base may not be robust enough to give one. It is more useful to outline what we do and do not know, with a ‘balance of probabilities’ recommendation, than to say ‘more research is needed’.
  • Language can also be a barrier. Academic language is complex and, at times, impenetrable; policymaker documents need to be aimed at an intelligent lay audience, without jargon, and focusing on what matters to them (outlining policy options and the evidence base behind them – not lengthy discussions of statistical methods). Look at Public Health Wales’ publications, for example on digital technology, adverse childhood experiences and resilience, or mass unemployment events, or examples from the NIHR Dissemination Centre or PolicyBristol to get a sense of the language to use.
  • Do you think you have time for networking with non-academic stakeholders? The perception of opportunity costs can be another barrier for academics. While time for networking might not be costed into your grant funding, think of it in the same way as writing a grant application; you can’t guarantee the outcome but the potential reward is significant.
  • There are no guarantees in policy engagement work, and a level of realism is required around what findings from one study can achieve. Policymaking is a complex and messy process; the evidence base is just one factor in decision making. Your recommendations may not be taken up because of politics, resource issues, or other concerns taking priority. Sometimes your relationships will reach honourable dead ends, where you realise that interests, capacity or timescales are not as aligned as you thought. Knowing this before you start is important to avoid feeling disillusioned.
Cartoon showing complexity of policymaking process and comparing it to making sausages
Policymaking is a complex and messy process; the evidence base is just one factor in decision making. Image from Sausages, evidence and policymaking: The role of universities in a post-truth world, Policy Institute at Kings 2017

In summary, the panel concluded that policymakers are interested in academic research as long as their priorities are addressed. While outcomes are not guaranteed, our colleagues at PolicyBristol advise a strategy of ‘engineered serendipity’ – looking for and capitalising on opportunities, being ready to talk about your research in a clear and policy orientated way (why does your research matter and what are the key recommendations?) and aim to build long term and trusting relationships with policymakers.

If you’d be interested in attending a future Engagers’ Lunch, please contact Lindsey Pike.

Further information & resources

PolicyBristol aims to enhance the influence and impact of research from across the University of Bristol on policy and practice at the local, national and international level.

Public Health Wales Research and Evaluation work collaboratively across Public Health Wales and with external academic and partner organisations, and are keen to facilitate research links across Public Health Wales with new national and international partners.

Research impact at the UK Parliament ‘Everything you need to know to engage with UK Parliament as a researcher’

Parliamentary research services across the legislatures include:

  • House of Commons Library: an independent research and information unit. It provides impartial information for Members of Parliament of all parties and their staff.
  • Parliamentary Office of Science and Technology: Parliament’s in-house source of independent, balanced and accessible analysis of public-policy issues related to science and technology.
  • Research and Information Service (RaISe): aims to meet the information needs of the Northern Ireland Assembly Members, their staff and the secretariat in an impartial, objective, timely and non-partisan manner.
  • Scottish Parliament Information Centre (SPICe): the internal parliamentary research service for Members of the Scottish Parliament.
  • Senedd Research: an expert, impartial and confidential research and information service designed to meet the needs of Wales’ National Assembly Members and their staff.