Health: The role of public data in taking the pulse of a nation.

Statistically Speaking

Miles is joined by colleagues from the Health and Life Events team to explore how data is good for our health.

Within the diagnosis: the Health Index, dubbed “the GDP of health”; the impacts of Covid-19 as well as an ageing society; and the increasing importance of linking data from numerous sources to generate complex insights that inform decision-making.

TRANSCRIPT

MILES FLETCHER

Welcome again to Statistically Speaking the Office for National Statistics podcast. This time we're taking the pulse of the nation's health and exploring the role of public data in making it better. Of course, we would say that statistics are good for you. We recommend at least five a day, but more seriously, what do the ONS figures say about the state of our health now? And what are we doing to create new and better statistical insights to support a healthier population in future?

With us to examine all are ONS colleagues, Julie Stanborough, Deputy Director of Health and Life Events, Neil Bannister, Assistant Deputy Director of Health Analysis and, later in the podcast, Jonny Tinsley, Head of Health and Life Events Data Transformation.

Julie to start with you. The World Health Organisation defines health as a state of complete physical, mental and social wellbeing and not merely the absence of disease or infirmity. Now, the ONS has begun a major project that seeks to capture the key elements of that in one place and to a certain extent in one single number. Can explain what that is, and what it's all about? JULIE STANBOROUGH Yes, so that will be the Health Index, and as you say, it is kind of regarded as the GDP of health. And at its simplest, it allows the health of England and local authorities to be tracked over time, which allows greater understanding of the relationships between the drivers of health and health outcomes. So the index starts in England in 2015. And we've got data up to 2019, which is available online, but we're going to be publishing 2020 figures very shortly. MF So tell us about the nuts and bolts, what are the data sources here and how have they been put together? JS We've got a huge number of different data sources that go into the Health Index. We've grouped them into three different themes, that we have healthy people, healthy lives and healthy places. And we use data sources from within ONS, but also from across government, and more broadly, to give that really in-depth breadth of all the data that goes into health. MF What sort of factors, what sort of elements are we looking at? People living without serious health conditions? JS Yeah, so it's a whole range of things. For example, looking at child poverty through to access to green spaces, life expectancy, a whole range of different factors which contribute to whether a particular area is deemed to have high health index or a low health index. MF Is there particular value - because you can understand wanting to understand disparities at local level and we'll talk about that a bit a bit later - but boiling it down to a single reading, a GDP. That's a very ambitious thing. How useful, how relevant, is that figure going to be? Is it something that the future will look to us regularly and take as seriously as a big number like GDP? JS I'd really hope so. And I think because the complexity of health is so complex, if we can boil it down to one number and be able to track that over time, at a national level, or at a local level, that really helps people understand what's going on and helps them to engage, but equally because it has all the different data sources in there, it allows those policy makers in local authorities to be able to go into that data and explore what really is happening in their particular area. MF More than simply measuring the outputs or successes of the health services, it's about understanding a much wider range of factors as well as the environment in which people live and their socio-economic position as well. JS That's right. I mean, there are so many different aspects to it. And that's why the Health Index has so many different data sources in there. But because of that complexity, it makes it really difficult for people to understand what they should be doing to improve the health in their areas. So you need that breadth, but then the ability to aggregate it up into a single number helps with the accessibility. MF So the index will provide this big reading of this multi factor estimate of health but perhaps it'll be the case that it isn't so much what the index says at any given time, but how it changes over time, that'll be its real value. JS That's right. And it's being able to track that at a national level. And at a local level. We're going to be publishing 2020 results, but we're going to have to be quite careful with those results because it'd be the first year with the pandemic and so we'd expect to be seeing some changes as a result of the pandemic. But equally, some of the data collections will have changed as a result of not being able to interview people in the same way because of lockdown. So we're going to have to monitor that data over 2020 / 2021 and further to really see the impact of the pandemic. MF And provide also perhaps some measure of people's changing economic circumstances at a time when there's so much concern obviously around the cost of living.

In the meantime, because this project the Health Index is still in its relative infancy of course we have a wealth of other data already that the ONS generates and brings in from elsewhere and works with. Of course the number one indicator of a nation's health is our life expectancy - how long we might be expected to survive. Tell us what's been happening - the broad picture - as far as life expectancy is concerned. JS Life expectancy, if I just explain what that is, is a statistical measure which estimates the average number of years a person can expect to live. So male life expectancy at birth in the United Kingdom for the years 2018 to 2020 was 79 years, and that compared to 83 years for females. And during the past two decades life expectancy has grown, but much faster growth appeared in the naughties, and during the 2010s. We've seen that life expectancy pretty much slow right down and flatten. MF As well as this obviously the key measure of life expectancy. There's another important dimension here and this is particularly relevant if we're talking about health and that of course is healthy life expectancy because it's all very well to be alive, but if you have not got a great quality of life, well that brings all sorts of other issues and it brings problems for the health service as well of course. Tell us about healthy life expectancy. What is that as a statistic, how is that measured? What are the characteristics that inform healthy life expectancy? JS It's slightly different to life expectancy. Healthy life expectancy is a measure of the average number of years someone can expect to live in good health or free from limiting illness, and in 2018 to 2020 male healthy life expectancy at birth in the UK was 63 years, which meant that you had 16 years of life in not good health. In contrast for females, they had 64 years of healthy life expectancy, which meant that they had 19 years of life in not good health. MF That's fascinating and obviously begs the question, has that period of healthy life expectancy been going up in line with overall life expectancy, or have people simply been living longer in poor health? JS Yeah, so between 2011/13 and 2018/2020, both males and females, there was no improvement in health and life expectancy. MF That goes some way to explaining some of the current pressures on the National Health Service. JS That's right. I mean, if you've got more people that aren't in good health and have limiting conditions that's going to have increasing pressure on our health services and our GP services. MF And it does mean also that people are dying from different things, and they might have died younger from different conditions. They're living longer, but perhaps in poorer and poorer health in many cases, and in the end, actually dying from different causes. What are the data saying? JS So there's a range of different factors which are associated with a healthy life expectancy, and things that you'd probably think yourself. So when we looked at areas across the country with the lowest healthy life expectancy, 29% of males aged 30 to 49 smoked compared to just 17% of those that were in the highest healthy life expectancy areas. So smoking is clearly one of the drivers. We've also looked at whether people are overweight, and more than one in eight children in the lowest healthy life expectancy areas became overweight between entering primary school and starting secondary school. In contrast, those in the highest healthy life expectancy areas, it was just one in every 10. So there's a number of different factors there that we can see are driving it. MF If any justification was needed on why public health campaigns tend to concentrate on issues like obesity and smoking that's starkly revealed in the numbers.

So that's the big picture. That's what's happening at a national level. But tell us about the differences from place to place because the local variations are quite significant too, aren’t they? JS That's right. So to commit those geographical variations, Ribble Valley in Lancashire is ranked the healthiest out of 307 local authority areas in England, and that's using the Health Index.

MF

And the least healthy?

JS

So we do have all those rankings, but we do try to not think about the scores in a sort of ranking capacity. The whole point of having this information put out there is for local authorities to be able to compare themselves with similar local authorities or their nearest neighbour and see how different aspects of health are given the different policy initiatives that they're implementing in their local areas. MF Because lo and behold, whenever these league tables – and I do emphasise that we don't claim them to be league tables, they're often seen as such - when they appear of course, people want to know where is top. Whereas, surprise surprise, normally it goes with socio-economic status doesn't it. To put it bluntly, the better off areas see the highest life expectancy and healthy life expectancy? JS Yes, that's right. And even for those areas, you'd want them to be perhaps comparing themselves to other similar areas with the same sort of socio demographics and then to think about where different aspects of, whether it's smoking prevalence or childhood obesity, how are those different areas responding, what are the policies that they're putting in place to try and improve those statistics. MF Because again, it's not a matter of stating the obvious, which is self-evident, isn't it? Health outcomes tend to be better in more prosperous areas. This has been well known for some time, although we opened a local paper the other day writing up some of these numbers and saying certain towns in the West Midlands have been named and shamed as having the worst health locally. This is emphatically not about naming and shaming areas, neither is it about stating the obvious. As you say it's about informing better health outcomes, so resources can be better targeted. JS That's right. I was actually looking at a Coventry Marmot city review, and they have been using a whole range of different public health measures to try and improve the outcomes in that area. And one of the key measures they use is healthy life expectancy. They're comparing the outcomes after a number of years in their area to what's been going on nationally. So it's helping them benchmark the initiatives that they've been putting in place MF As with the overall Health Index itself, it sets the standard doesn't it. Puts in numbers what is clearly self-evident, but useful numbers because they give you that sense of the scale of the issue at the local level. That's at least as far as England is concerned, but also we've been working with the devolved administrations around the United Kingdom as well, and what do we know about that picture? JS So on the Health Index, that's actually one of the areas that we were looking to expand. So the Health Index at the moment covers England – we would really like to develop them for Scotland, Northern Ireland and Wales and then create a UK wide one as well. So that's something that we're looking to develop in the future. MF That's a work in progress, and a ‘watch this space’ then for forthcoming publications, both of the Health Index and of data being compared across the UK as well. So Neil, people are living longer, but with that experiencing a whole range of health conditions. Tell us what we're picking up in the data and what's changing. NEIL BANNISTER That’s right Miles. So age is a very big important social determinant for health and an ageing society places a big burden on the health and social care systems in the country. Recent Census analysis from the 2021 Census showed that nearly one in five people in England and Wales was over 65 now, with the fastest increase happening in the 85 plus age group. So there really is a fundamental kind of growth in the ageing population, and that leads to increases in certain disease types. So for example, we know that being in an elderly age group you can experience being more disabled and having more multiple chronic and complex health conditions as well as there being an increase in dementia and Alzheimer's disease. So for example, with dementia, we know that around about 900,000 people in the UK have been diagnosed with dementia and by 2025 it is expected to reach around about 1 million people in the UK. In terms of how we look at it from our data within ONS, we know that 12.5% of all deaths that we record are caused by dementia and Alzheimer's, and it is the leading cause of death in age groups over 80 plus within England and Wales.

MF

That is a relatively recent development.

NB

That's right. So that's happened really over the last three to five years, we've seen this increase in the dementia and Alzheimer's as a leading cause of death in England and Wales. MF And is the rate of increase showing any sign of abating? NB Well, if you take away the COVID pandemic period, no, it doesn't. It looks like it's actually on track to continue to be the leading cause of death and with the new figures that we have in from Census showing there is an ageing population, and the age is increasing, we would expect there to be a continued increase in the number of deaths from dementia and Alzheimer's and, as I said, the number of diagnoses as well. MF Yes, that's a stark finding and something you'd suspect we're going to be hearing quite a lot more about. NB It's not just within the UK that this is occurring though. When you look across other economically developed countries. So looking at the data from the OECD, for example, we can see that Japan, Italy and Greece - these are countries with well-known elderly populations - they have a very high prevalence of dementia. The UK out of the 44 OECD countries UK is 15th highest in terms of the prevalence of dementia, which is equivalent to where Denmark is as well in terms of comparability. MF And that speaks loudly to some of the challenges the health system is going to face in future, and the social care sector as well, which is already under pressure in some respects. Tell us about the potential impacts there, what are we seeing? NB What we found during the pandemic is that there are big gaps in data around social care statistics and being able to understand that population within our society and that group in society. MF Is that because the sector is diverse, and it's sprawling and it's uncertain and in places it's quite informal? NB Absolutely. There are different types of social care. There's social care that happens within care residences, and there's also social care that happens within the home. There’s a big private industry there as well as the public sector being involved. And trying to pull together information across that diverse and complex landscape is very difficult. MF What are we doing to try and close some of those gaps? NB So we're working very closely with the Department of Health and Social Care. They have a large programme of work to try and collate data and improve data collections across the piece. What we've been doing, we've been looking at particular areas. So we're looking at trying to understand more about self-funders - individuals who fund their own social care, as opposed to those who have the state to fund it for them. And other areas of what we're doing is to look also at the workforce in social care, which is very hard to track over time and to understand the size and scale of that workforce. So that's another area of work that we're doing. MF And this is just part of a much wider body of work going on across the ONS to try and shed new light on health inequalities in particular. NB Yes, that's right. So we are going to be using the Census, the 2021 census data, to really look in more detail at social care once that data becomes available. But what we have been able to do though, during the COVID pandemic, is use the 2011 census data to link to other sources to really understand how, for example, the COVID pandemic had impacts across a number of different groups in society. We were able to produce statistics for the first time looking at the impact that COVID had on particular ethnic groups, on religious groups, and on the disabled groups in society. MF And what did we discover about the unequal impacts of COVID? NB Yeah, so when we're looking at ethnicity for example, since the start of the period where the Omicron variant was more prominent, we found that the Bangladeshi ethnic group of males had the highest rate of death of COVID-19, as opposed to the white British group. And we also found that for females, the Pakistani ethnic group had the highest rate of death involving COVID-19, which is 2.5 times higher than that of the white British group MF On the topic of ethnicity, was it factors such as the nature of the occupations undertaken by those groups, or perhaps socio-economic status, living conditions and so forth? Or was there something, by the very nature of their ethnicity, that was actually contributing towards higher mortality? Have we got to the bottom of that? NB It's very hard to know that, Miles. What we've done is some complicated modelling to understand, and we've taken into account certain social demographic groups and economic factors, but we still do find that certain ethnic groups have a higher rate of death, even when taking into account those factors. Things that it could be, but we don't know the detail yet, could maybe be how people in those ethnic groups live in terms of having multi-generational households, for example, and maybe that was a contributing factor, but to understand that in more detail much more work is needed to be done. MF Another area where research remains in progress. And also more recently, we've gone into partnership with one of the world's great philanthropic organisations to try and uncover what's going on behind some of these inequalities. NB That's correct. So there's a piece of work that we're doing working with the Wellcome Trust and the Race Equality Foundation. And what we're trying to do is to understand that there are different sources of ethnicity data within the health system and also with our Census data as well. What we know is that there are different qualities of how that data is recorded. What we're doing with the Wellcome Trust is to really understand the quality of the data across the different sources so we can provide a better understanding of the analysis that can be done with those data sources, which is really important as its data itself, which is a fundamental building block of any analysis that we can undertake. And the quality of that. MF It's quite hard to disentangle the effects of the pandemic at the moment, and it's probably worth discussing those. Are we in a position yet to know how life expectancy has been affected by COVID? NB At the moment, we have some indication. So the last publication we produced for healthy life expectancy covered the period of 2018 to 2020, which has a period of a COVID pandemic within that analysis, and that did show that there has been a drop in healthy life expectancy both in England, Wales and Scotland. But what we don't know for certain yet is the full impact of that because we haven't had the data to analyse for the entire pandemic period. And that's work that's ongoing within the office. MF So we will in due course then be able to get a much better understanding to what extent life expectancy might have been impacted by long COVID. But in the meantime, other ONS data suggest that a lot of people at least say or think they are suffering long term effects from it. JULIE STANBOROUGH That's right. We estimate over 2 million people in the population are experiencing long COVID. And it is self-reported long COVID. So we collect this data from the COVID Infection Survey, which was started at the beginning of the pandemic and people are reporting whether they're experiencing a whole range of different symptoms, which are associated with long COVID. And we've been monitoring that on a monthly basis to see whether those numbers have been increasing or decreasing and which types of people in the population are more likely to be experiencing long COVID.

MF

And what’s been the pattern of those numbers?

JS

It’s actually been broadly stable, a slight upward trend but broadly stable over time, and you would hope that over time it will start to drop down, but we're not in that situation at the moment. MF So the data at the moment is seeming to suggest that - so obviously, we know a lot of people have been infected - a lot of people seem to be suffering symptoms for a protracted period afterwards, but at least as far as the data are concerned, they will tend to imply a lot of those people are getting better. JS So we measure whether people are experiencing long COVID after a set number of weeks. So there's a significant proportion of people that still experiencing long COVID At least 12 months after their first infection – it is a small group but it is a significant number of people. But of course it has impacts on their ability to go about their day to day lives. Look after family, go to work, study. So it does have a significant impact on people

MF

And what sort of effects are they reporting?

JS

So it can be a range of things from fatigue, breathing difficulties to perhaps more severe symptoms. So a whole range of different symptoms. MF What further analysis are we doing on the impacts of COVID generally? We've explored differences in ethnicity, other characteristics as well. Tell us a little about that work and what’s up next for this programme of research. JS As you say, yes, we've done a whole range of different analysis to support the COVID pandemic. A lot of the analysis that we have produced has gone into the COVID Insights tool, which is on the ONS website. And that brings together a range of different data and analysis around hospitalizations, infections and deaths but also tries to put it into a sort of societal context, in terms of wellbeing, and employment as well. It's actually one of the most looked at on the ONS site. MF So even though the pandemic subsides - as at least we hope it will - a lot of work will continue to assess its full impact. JS That's right. It will be trying to understand in more depth what happened during the pandemic as well as monitoring the long-term effects, either on employment or in terms of people experiencing long COVID. MF The ability to link data to provide complex insights, of course, is such an important area of research at the moment.

And that brings us to Jonny Tinsley. Jonny this is very much your area of expertise.

And with that in mind, tell us about the Public Health Data Asset. What is that and how does that bring together data in that very useful way? JONNY TINSLEY During the pandemic data became incredibly important to understand what was going on and a lot of data sources in the health space exist. The NHS collects an awful lot of information about people and a lot of other organisations produce analysis, including the NHS themselves of that data. But one of the things that is unique to ONS is its access to non-health data and in particular, the Census data. By bringing in some of that health data from the NHS, which we’re able to do for statistical purposes, we were then able to link that with the Census 2011 data and also our mortality data and create what we call the Public Health Data Asset. And what that effectively gives us is a huge cohort of people that were here in 2011, at the Census and then in combination with that mortality and health data able to analyse, giving it such a huge cohort of people. It allows us to have quite a lot of power and the statistics we can produce and pick up. Some of the differences that Neil was talking about actually, because the Census data includes things like ethnicity, religion, and disability status. We're able then to look at differences across those groups for things like COVID-19 mortality. MF So we can track essentially, as I understand it, we can track what's happened to individuals' health over that period of time, from the information supplied to Census and from their interactions with the NHS and other public services? JT To give a specific example, what we can do is for these different groups, so the Census effectively allows us to separate out the groups. For example, it shows that these people are of this ethnicity whereas these people are of this ethnicity, and then for those groups we will then know which people have died and when and what was the cause, in particular during the pandemic obviously, whether that cause was COVID-19. And then the main thing the health data has allowed us to do so far is look for what we would call comorbidities. So who has pre-existing conditions that put them at risk of poor outcomes from conditions such as COVID-19 in this particular case, MF And that will help the health services to be more predictive of the sort of conditions people are likely to face? JT Yes, to a degree. So some of that was already known. But what it allows us to do is if a particular ethnic group tends to suffer from certain conditions more than another, by taking those co-morbidities into account, we can do what we would probably, in layman's terms, call ‘control’ for them in the models, and therefore effectively discount them. And if any differences still remain after that, between different ethnic groups, then something else must be going on. And as Neil says, one factor for example could be the multi-generational households impacting how likely it is for transmission to happen. MF And as well as differences by ethnicity and other characteristics it allows this to be done at a very, very local level as well, because of the sheer scale of these databases. JT From a data point of view, that's a really interesting question, because we have the COVID Infection Study, which Julie mentioned earlier, and whenever we do a survey we try and make it as representative as possible. So obviously it's not everyone. It might still be several hundred thousand people, as it is with the COVID infection study, but ideally it's made to be as representative of the population as possible, such that if 2% of the sample are infected with COVID-19 that week, it probably means that 2% of the whole population of England and Wales also are. But one of the downsides to doing a survey is even if you have a large number of participants, the statistics you're able to produce are at a really low level, this isn't as good because the number of people you have available in a small area that are actually in your study can be really, really small. And it can also make it more difficult to pick up these differences between groups, such as ethnic groups. Whereas when you've got the Census data, because you've got a much larger sample of people in your study, it gives you more statistical power and you can pick up the differences more easily, and produce lower-level statistics more easily. The downside, because there's always upsides and downsides when it comes to data quality, is that the 2011 Census data is now somewhat out of date. And the cohort, the kind of study population we had available to us, by definition excluded anyone who's been born since 2011, and anyone who's immigrated to the country since 2011. Because you know, they weren't here for us to pick up in the Census in 2011. So there's some work we've done to think about just how representative what we're calling the Public Health Data Asset is in terms of who is included and who isn't, compared to the people that are actually here in the country right now and have been during the pandemic, if that makes sense. MF Potentially, this is an incredibly valuable resource, but primarily who is it for and what are they going to use it for? JT To an extent they were for the general public of course, but also important stakeholders - decision makers during the pandemic like the scientific advisory group for emergencies (SAGE). Listeners will probably be familiar with people like Chris Whitty, the chief medical officer, and so these sorts of decision makers were finding everything we were doing really useful and at times even commissioning us to produce particular statistics or analysis using this really powerful dataset that we had available to us.

I mean, one aspect of this that I think is really important to talk about is data protection, confidentiality and kind of ethical uses. So to be clear that we take our responsibilities when it comes to the Census data really seriously and as many people know, we don't release Census data until 100 years after it's been collected. And when we get in other data for statistics that's of a sensitive nature, like the health data, we have all sorts of processes in place to secure that in our secure data systems and ensure that only highly trained security cleared staff can access it. So primarily, we're talking about substantive ONS employees who are specially trained using this data for statistical purposes. We will then use the data to produce the statistics that our users are telling us they need the most. MF Yes, it's well worth emphasising the data protection side there because obviously we are talking about vast amounts of highly sensitive data. And if anyone's interested in finding out more about how we approach those issues at the ONS, do please have a listen to our podcast on data ethics, where we explore that topic in some detail.

Overall then, a lot of ground-breaking work going on, a lot of new data coming in and we have to say that it has actually been picking up some prestigious awards. JT That's right Miles. Some of the work we've talked about has won a number of awards, probably the most prestigious being the RSS Campion award for official statistics. MF After hearing a lot of really quite sombre detail over the course of our conversation today, it's good perhaps to end on a relatively upbeat note. At least people can be assured that so much work, so much research, is going on to try and anticipate some of these problems before they manifest fully. And we hope of course to contribute to improving health outcomes over the longer term.

So that's it for this episode of Statistically Speaking, I'm Miles Fletcher. Thanks very much to our guests Julie Stanborough, Neil Bannister and Jonny Tinsley. Thanks very much to you for listening once again.

You can subscribe to new episodes of the podcast on Spotify, Apple podcasts and all other major podcast platforms. Thanks again to our producer at the ONS Steve Milne for this episode and, until next time, goodbye. ENDS