Nov 28, 2022
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