Thank you for inviting me. I just can't think of a better thing to do now than listening to this talk.
So thank you for coming. So I belong to the Department of Primary Care.
I am an attrition scientist by background. And in the past my background is in is in epidemiology.
However, currently I do more intervention studies and randomised trials,
so I hope to give you a broad range of things that I've used in the past or using at the moment in terms of research methods.
And I love talking about food and nutrition. That's my thing. You'll soon realise that and then I hope you enjoy.
I think everybody loves talking about food because we all eat. So it's something that is interesting for everything or that's what I think.
So, yeah. So thank you for inviting me.
Am I always like, this is not related to shopping, but I always like starting everything with a global burden of disease.
And you've probably seen the studies, the global burden of disease studies many times, or you will see that many times in the future.
And these these are published in The Lancet.
They've been been published since the 1990s.
I think it is a global consortium of researchers who gather data about mortality and disability and risk factors.
And I love these figures because it shows globally the 20 risk factors for disease.
This is not the 2017 version, but I don't think things have changed that much.
What I like about these figures is that of these 20, at least half are related to not eating properly,
not having proper weight and not doing enough physical activity.
So there's not a better way to say how important eating good and doing physical activity is than this figure.
That's why I love it. And of the of the of the risk factors that you can see here, they explain.
So the metric that they use oops this I've gone back to how much they use the dollars which are disability adjusted life years,
which are the number of years that we lose due to early death or disability.
So for example, for high blood pressure, we find that the burden of high blood pressure means about seven years lost.
And then in the colours inside you can see that the diseases that are associated with so in this case would be cardiovascular disease.
But actually most of the shades are blues, which are cancer and cardiovascular diseases,
which are non-communicable diseases that are really highly prevalent in modern countries.
So as I said, these top risk factors associated to a poor diet or weight or low physical activity are highly associated with cancer,
CVD, diabetes and things like that.
So that makes the point that diet is really important and we need to change the diet because we know our diets are not appropriate.
But how do we do that? So how do we know our population is eating properly?
So the way we do this is through national surveys, consumption data from the national surveys,
so that typically we collect individual dietary intake in a in a population,
in a, in a, in a random sample of the population, we look at purchasing data, which is individual data on such purchases.
But as you can imagine, you might be thinking foot purchases is for the house.
So depending who lives in the house, your shopping is going to be different.
Right. We're going to address that later. But that's another source of looking at how people is eating.
And the third way would be looking at sales data.
But that comes from the retailers or the manufacturers.
And they they report each year how much they set.
They these things have been sold from them.
And typically what we do more is consumption data from national survey.
So in the UK that is called the National Diets and Nutritional Survey,
which looks at the diet and the nutrient intakes and the nutritional status of the population in the UK.
They've been rolling since 2008 and they recruit people one and a half years on level up.
So what they do is to select a random sample of addresses and they invite one kids and one adult from each household to participate.
And on each person they collect four day diary.
So they make people write down for days what they eat and drink everything.
And they do. Of you on collect a blood sample and urine sample.
And just with this,
we can have a full picture of the and actually they don't even require that many people they might recruit under depending on the years,
but maybe like 4000, 5000 people. So that's really a very small sample considering the UK population.
But just with that sample, because if it's done properly,
we can have a good picture of how the UK is doing and they can produce results such like this ones.
I haven't done research on this survey myself. I've done it in the US, similar research to this.
So for example, we can know what are the main sources of of energy in the UK adult population and one of this
so the top one is serial and serial products they contribute 32% of the total energy intake.
So from everything we eat, a third comes from cereals or cereal products.
There is something to note here that the DNS includes cakes and biscuits in these groups.
No, no surprise, it is a third of our calorie intake because cakes and biscuits are high in calories.
So because they've been included there, they contribute a lot.
And also maybe not that surprising in this country, we eat a lot of biscuits.
Meat is the second source. Vegetables and potatoes is the third.
Well, it's important to note that within the potatoes we have the fries, the chips and the rice.
So that's one striking thing.
Alcoholic beverages are the fifth source in the adult population,
and things as important as fruit or fish are only three or 4%, which is is not very good.
So this is just one example of what are the things that we can do with a national survey.
However, people out there do all the things which are not that appropriate.
So what happens is that the national surveys are what we call a cross sectional study.
So people is recruited and interviewed and all the data is collected at the same, same time.
So that's called correctional. So your diet is collected.
If you have any diseases or your blood pressure, your weight, all is collected at the same time, the same day.
So the main limitation of these surveys is that they are cross sectional and not valid for causal inferences.
However, you'll see a lot of studies out there whether the sign is cross-sectional and the study is chocolate associated with weight,
and they may conclude that chocolate is not associated with weight.
Therefore we can eat as much chocolate as we want. There are many studies like this and what I recommend is that you don't continue reading.
So and the reason so cross sectional studies affected especially in nutrition studies which are
sectional affective are two main things residual confounding and something called reverse causality.
I'm not sure if you've seen that concept yet, but for example,
somebody so you ask people their weight or you measure their weight and you ask them how much chocolate they ate yesterday.
What happened is that somebody who is not trying to lose weight, they report having chocolate on somebody who is trying to lose weight.
They said, oh, no, I didn't eat any chocolate. So you look at that association.
And what happens is that people who are not trying to lose weight to have a healthy weight,
they eat more chocolate, and therefore they conclude that chocolate is not associated with weight.
So there are tons of examples of these studies out there, and I caution you to not continue reading them.
They're not valid for associations, especially those that we know that could be affected by reverse causality.
There's also the problem of reporting, especially underreporting,
because a people lie, especially, we know body weight status, that is pretty evident.
People who have a problem with weights tend to under-report the intake of their diets.
But also recall, we tend to forget, even if I ask you, all of you,
what you had yesterday and you have to write down everything from the first food or drink you put in your mouth till the end.
I'm sure none of us will be 100% accurate because you can't really be that accurate to up to the grams of food that you ate.
So therefore is always really, really hard to report your diet to the state.
So there is always problems with that. Aren't usually we only collect very few days ideally four if you're going to study the diet of.
Somebody you would need as many days as possible, ideally a whole year.
So you would know how your diet has changed for the whole year.
You know, things like that. But that's not feasible.
We tend to collect one, two, three, four days maximum.
That's not representative of the usual diet. Therefore, we always have limitations in that sense.
So this is to make the point that dietary services are important.
They tell us how the population is doing. Does the population need more iron, more vitamin C or more vitamin D?
But not to look at if chocolate is associated with weight.
So I've shown you from the global burden of disease how important diet is and how we can look at the diet of the population level.
And, you know, with other sources of evidence that I'll I'll come back to that later.
We can define guidance to give people the guidance so that they know how to eat, what to eat.
And I've given here an example of the WHO guidelines that basically promotes energy balance.
That means not eating more than what you are consuming.
So then you achieve and maintain a healthy weight.
Do you shift fat consumption away from saturated fats to unsaturated fats and towards elimination of trans fats?
That's to increase the consumption of fruits and vegetables or anything.
Plant based. Specifically, whole grains and nuts.
Limit intake of free sugars and limit salt consumption.
So these guidelines are the current guidelines by the WHO, but others are similar.
And despite all the advances in nutrition over the last few years, nothing has changed.
Despite all the headings, the headlines in the newspapers that you may have seen.
Nothing has changed, really. So and this is basically common sense.
It's nothing very magical. So in the UK we have something called the Eat Well guide, in which if you look at your plate,
so let's imagine this circle is your plate and those are the proportions of different foods that you should have in your plate,
pretty much most of it. Fruits and vegetables, whole grains, tiny bit of protein, very tiny bit of oils,
and not not much of the of the cakes, biscuits, chips and all the good stuff and drink water.
So that is how we communicate some of the policy level, how we tell people what's the right diet,
what's what, what is what we should be eating on a daily basis.
Great. So from from from this point onwards, I'm going to get into my research,
which is, you know, this this is how we communicate the population, how to eat.
And the problem is how how can people make the changes?
Because I think at this point, we all know how we should be eating, but is really hard, really difficult.
And in behavioural science, what we look is it's ways that the population implement those changes.
That is the heart thing. The people make the changes and they sustain the changes for long enough.
So then we have a healthy weight and we maintain that healthy weight and health status.
So my research is aiming at improving the quality of the shopping, hence improving the quality of what we eat for preventing disease.
And just for a little bit of context, as we know, the massive prevalence of obesity and diabetes and cardiovascular disease,
we are diets where the healthy and healthy start in the supermarkets and most of what we eat comes from the supermarket.
About 70% of the weekly expenditure is on supermarkets and the rest is eating out.
So once that food is around the houses, highly likely we eat it.
So there is a real opportunity to make that food that is around the house healthier.
But also the governments and also the public are demanding the food industry to make it easier and take action and be part of the solution.
But there is lack of current evidence on what to do both at the store level.
So supermarkets are not sure what can they do, although I think they know, but they don't want to.
But there is a lack of external evidence, not the evidence provided by the retailers themselves, but external evidence on what is effective.
So then consumers. We all shop healthier, but.
At the individual level. Once we are in the supermarket making those decisions, what can we do to have a healthier basket?
So one of the studies we conducted recently as part of the food shopping stream was a run, a systematic review of randomised trials in grocery stores.
Because I know you've been talking about Pico. I feel like Pico here.
My population in this systematic review didn't have an exclusion, so it was all participants.
Shopping in stores included the interventions where single or multi-component interventions tested in our city's randomised controlled trials,
which aimed at changing the purchases of foods or drinks, were implemented in the stores, whether online or physical, real or simulated.
And they changed store environments or product features, for example, changing the price of a product.
So those are the interventions that we and that we saw in these trials included in the randomised in the systematic review,
the compact dose was no intervention on the outcomes where food purchases or food consumption.
What we found was about 35 studies,
randomised trials included representing about 20,000 customers and 800 stores there where all that most of
the studies where large supermarkets and there were very few in others like convenience stores or online,
but eight of them were simulated or virtual. So there's a lot of research on on that kind of thing.
And I'll explain later in one of my studies and all the studies were aiming to promote health or healthier choices,
and some very few aimed at increasing profits, selling more of something.
So what we did is divide those 35 studies into intervention categories.
So different kinds of interventions. So basically from everything you can find in a store that would influence our shopping behaviour can
be classified in four ways economic which means taxes or discounts or financial rewards environment,
so things like item availability or the range of products.
So for example, healthy things, healthy products within the range of products or the placement of the products.
So for example, things which are located at the end of the aisle versus in the middle of the aisle or signs,
for example, displays that they put in, in, in, in the aisles.
There is also another category called swaps, which are when you offer people a healthy option to the one that they are choosing.
And the final one is educational labelling, which are aiming at improving knowledge or providing information.
And labelling is part of that. Or the traffic light system that is well known is part of the education and labelling function.
So I would say these interventions go from more to less in the sense that they they be how we call that from heart height to soft, I suppose.
And the there's also evidence that these ones would be more effective than these ones.
And these also what we found and the way we analysed the data in this systematic
review was using something called QCA qualitative comparative analysis.
And the reason was because we couldn't do a met analysis, because the way the outcomes were reported in is in each study we're very, very,
it's a region so we couldn't really do a meta analysis and we did this QCA method which allows you to
look at interventions or combinations of interventions which appear when an intervention is effective.
So if you say, for example, economic interventions are effective,
what are the specific components that appear together when the intervention is effective?
And what we found is that economic interventions showed a clear effect and these effects
were enhanced by promotions of things which had a discount or tax were effective,
especially that came with that promotion. Environmental actions were mixed.
So the only one that showed some effect was the item availability in some studies.
For example, if, if, if you go to the store and then you're going to if you're going to buy,
for example, frozen chips and there is a variety of them, including healthier options within that range,
then you're more likely to shop healthier because you've got the options, the range,
the swaps, interventions were promising, but they were very few of them.
There were very few studies, especially studies of of good quality to make any judgement and the educational labelling also showed.
Mixed results. And the interesting thing is what? Education was only effective in simulated environments.
So what happens is that in studies where everything was simulated and people were not shopping for real education appeared to be affected.
But when is in the real store? In the real environment? Not.
Not on. We didn't find evidence of that effectiveness.
So what happened is that from this systematic review, we basically got our attention got into the swap category because there were very few studies
and we basically decided to start doing some studies on swaps on healthier alternatives.
And those are the studies I'm going to start presenting now.
I'm going to start presenting a study that we have done in an online experimental platform.
And these so this is one of those simulated stores.
They're not real people are not shopping for real, but they look really real.
So the new version of the supermarket looks like this.
If you've been shopping online in a Sainsbury's, it looks exactly like the Sainsbury's.
However, it's not real. So we, we, it is really high.
So the reason we have built this platform is because it is a it allows us to test the things that are real supermarket wouldn't do ever.
And if they do, they want publish it.
So these at least helps us to kind of build the evidence base around some kind of intervention that might be promising and maybe in the future,
a supermarket will like to implement for real. So what happens is that people we recruit people in studies and they go into this supermarket,
they've got the products they can browse, they can search, they've got the trolley here, they can remove, you know, looks pretty.
It's got all the functionality of a real online supermarket.
And we conducted a study to reduce the saturated fat content of this shopping basket within saturated fat.
But we could do any other we could do sugar, we could do salt. I'm going to show you saturated fat.
We've done another one on salt, but I'm going to show you only this one. And we wanted to test two conditions.
One was food swaps with less saturated fats.
So if you're shopping for cheese, then you would have.
So you select your normal cheese. And then a window would come with a low of saturated fat chip cheese.
And they will say, well, you might would, you would you could see this swapping with this other cheese and the other condition,
it's called prominent positioning of lower saturated fat foods in the list.
So what happens is that if you search for cheese or browse cheese, the lower saturated fat cheap cheese appears at the top.
So we've manipulated the order of the foods from less to more.
So the healthier stuff appears at the beginning of the list.
So we've tested these two conditions and we've measured saturated fat content of this shopping basket.
So at the end, when you finish your basket, we look and we look at the percentage of saturated fat that's coming in in the whole basket.
And what we did is a factorial two by two randomised controlled trials where we've got the two conditions, the swaps and the prominent positioning.
And because it's a two by two factorial design, we assign people randomly to either have a swap or have the prominent positioning, both or neither.
So we've got four groups and we randomly allocated about 300 people in each group.
Oops, not that far. We gave people a shopping list like this one, which includes things which would have saturated fats.
So we didn't include the shop for oranges because we we know oranges don't have saturated fats.
So we only included things which have potential to have swaps, lower saturated fat,
for example, shop for milk or butter or cheese for use in a sandwich.
And then there are ten items, some people where we're required to shop for all of that.
And we recruited about yeah, about 300, 300 people per group which were about 38 years old at baseline,
about one third were male, about one third had a BMI over 30, which means obesity.
Most of them were of white background and about a third of them had been.
Shopping online for groceries. And what we found that compared to the control group that hut 20, almost 26% saturated fat in their baskets.
People who got a swap like a lower saturated fat cheese had 2% less saturated fat, a dent in the whole basket.
But people who had the prominent position so the healthy options at the top had 5% less saturated fat at the end in the shopping basket.
People who were hot, both with hot, slightly better result.
However, if we look at the way we look at the conditions on his own,
ordering the order and having the healthiest stuff at the top was significantly better than anything else except the combined intervention.
And what we also did, because people out there would would say, Oh, but if you shop healthier,
then it cost you more because eating better is cost you more money.
We didn't find evidence of that in our study compared to control, the amount of money they spent per 100 grams was about the same.
It wasn't significantly different.
And we also look at other things, because all the people would argue that, for example, there might be ethnic differences or age differences or sex.
We didn't find evidence of that either, and we didn't find evidence of a BMI, education or income affecting the intervention results.
So we found in conclusion that the interventions to change the fat purchasing are promising
because both both conditions where we're significantly better than the than the control.
But the prominent positioning was better on his own.
If you combine both, which is perfectly possible, that would lead to a more added effect.
And as I said, this is not real.
It's not real food, not real money. People in an experimental condition.
And what we hope to do in the future is that a supermarket would do this for real.
We know of some supermarkets that are doing that already, but they won't publish their results.
What we want is to collaborate with a supermarket that would implement something
like this and would give give us the data to properly evaluate this in real people.
So that is one piece of evidence that we've conducted in supermarket to improve food shopping, and we could potentially do this for sugar as well.
We've done it for salt, and it also works very well.
And now I'm going to talk about studies that I've been developing to as well to encourage healthier shopping.
But this is in populations at risk within primary care setting.
We have been developing these studies to provide the behavioural support in different ways.
In one way we we have been using primary care and primary care practitioners to to deliver the message to encourage people to eat better,
to lose weight. And we have very good evidence from our department that, for example,
if your GP or your nurse mentions that you should be thinking about losing weight one year later,
that is been really effective and people is later, one year later.
So what we have have done is a similar thing, but this is to encourage healthier diet.
The reason we use primary care is because it comes from what we call the trusted source.
So if you've been told by your GP or your nurse that you should be perhaps changing your diet, you're more likely to believe it.
And you could also target the population at risk.
And these are people who at least have a reason people with high cholesterol or high blood pressure or diabetes,
they have good reasons to change their diet.
So we can reach this population through primary care very easily.
However, the behavioural support that we provide through primary care is quite limited because health care practitioners have very limited time.
They don't have very good knowledge about, you know, they're not going to sit down with you one hour asking you why you ate yesterday,
to tell you specifically what are the components that you need to change and not going to do that.
And they have limited time and lack of nutrition training to do that.
So what we've got to do is to incorporate the supermarkets,
to provide people feedback with about the their shopping, their food that they're shopping for.
So if you get more to. From your nurse and your supermarket is motivating you to change your diet.
What what could potentially do to our general health?
So we we planned and conducted these PC shops study that I've been doing for the last couple of years on this study.
It is a three arm parallel design randomised controlled trial with a three month
follow up in which we have measured saturated fat intakes and blood lipids.
We have recruited patients in primary care with high LDL cholesterol.
The LDL question is the type of cholesterol that is bad for the arteries and
these people were willing to change their diets and we're shopping at Tesco's.
The reason they were shopping at Tesco is because we've been using the data on the
shopping to give people feedback on on the things that they were shopping for.
And Tesco was the only supermarket that was willing to give us that data from the loyalty cards.
No other supermarket has been able to do that so far.
And what we did, we randomise people and this was not done.
How do we call this unbalanced?
We've randomised three, three, one and that means for every person we run the mice to be a control which we,
we give them the results of their blood results and nothing else.
We put three people randomly into the active interventions.
So one group got advice and motivation from the health professionals.
So this was the nurse that in 10 minutes, in a consultation in 10 minutes, tried to motivate people to change their diet.
And then another group got the same nurse advice and a shopping report.
And this is what we did with the loyalty card data from Tesco.
We created something like these that we sent to the participants every month.
So what we did, we had one month of data from the shopping, from the loyalty card.
We created a system on an algorithm that would come up with this number, which is the grams of saturated fat per week in your shopping basket.
And it also gives you top five products in your shopping basket, which are contributing the most to saturated fat in your basket for those five.
Then we gave healthier swaps or things which have less saturated fat.
Some of them are not healthy regardless.
So for example, for that pizza, then you get another one that has, you know, 5.8 grams less saturated fat per 100 grams and so on.
So for some of the changes, I don't know if you're familiar with the traffic light system, but the red means no, no, no.
The orange means like cautious and the green is okay.
So for example, somebody's got a a beef mince and the swap was a turkey means that we came from from yellow to green.
But these are the example. They went from a from a proper butter to a flora like butter and they still red.
So some of the products, even though you might think, oh, these taste nothing is good, they still have a red colour for that.
By the traffic light system, it means that it's still have a lot of the problematic nutrient which is in this case saturated fat.
But anyway, we gave this to the people so then they can identify in their shopping what was the top five problematic products on their swaps?
We followed them up for three months and we looked at their diet at the beginning,
the diet at the end, as well as their shopping and the blood lipids.
And we finished recruitment in February and we still we we are preparing the results for that study.
However, you're going to see the first people, you're going to be the first people seeing these results.
So you're very lucky today. So this is the primary outcome.
This is the percentage of saturated fat in the diets reported by the people.
The intervention people had a slightly lower with saturated fat in their diet at the end of the study.
At follow up, however, this was not significantly different from the control and it comes down opt almost at 1% reduction.
Our power analysis we had done we had powered the study to detect 3% reduction.
So the results are not significant, but still like even 1% is something actually meaningful when we look at shopping.
We found the same trend. We found the people reduced the saturated fat in their shopping baskets.
However, this was not significant from their control.
So because the the the confidence interval in this case, our standard deviation, standard errors of the means, they're overlapping.
So nothing is significant. But the black boxes is the control people.
The the white dot is the brief support the just the nurse and then these are the triangle is the people who got all the complete intervention.
So it is less obvious in diet studies, but in weight loss studies is really evident.
The control people, sometimes they lose like two or three kilograms by doing what nobody knows, but they must do something, otherwise they would lose.
So. So these are the results that we got from this study.
So things look promising, but the results are not significant.
We also ask people about this is more qualitative research about their thoughts via questionnaires and proper qualitative interviews.
And about half of them thought that the swaps in their reports were good.
They were clear. They motivated them. A few of the people, like 12%, didn't like the swaps, or these were not supported by the family.
No way you coming home with that pizza again. Or some people thought the swaps were more expensive or not available in store.
And then turns out from the qualitative research,
some people were really annoyed that if they had a who knows chicken pie that these would offer our fish buy.
I would never eat fish in my life. How you there?
Well, it is a computer program that doesn't know that you really dislike fish.
So, yeah, some people got really into this thing and some of the comments from them that they
found the study was useful because they now read the labels or they know the content,
the saturated fat content of pasta. So then when they go out, they know it, or people who found the regular check.
So then they would come coming at the beginning, at the end that we check their blood lipids.
So that was what they got them interested and, you know, motivated to change the diets.
So that's that was the PC Chop study and I'm going to present a similar one is a Dphil project that is currently ongoing.
But this is a this is for people with hypertension giving lower salt swaps and is a feasibility feasibility study,
which means that it's not about how effective these lower salt swaps are for for hypertension.
It is about how feasible is to recruit these people and give them this advice.
So this is another intervention done in primary care, using the nurses to give the advice and motivate people,
and they encourage them to choose lower salt options.
It is a two arm randomised controlled trial with a six month follow up and it is a feasibility study.
So there isn't a primary outcome, there's no power analysis is only 40 people and we are going to look at some outcomes such as,
for example, salt in the shopping and urinary sodium and blood pressure.
So we recruit people with high blood pressure and GP practices and we randomise them to control in as
is different from from the previous study because the previous study only got their blood results,
nothing else. These people get a leaflet so you can expect these people doing a little a little thing.
So it is a light touch intervention is not is not an a no intervention control it is really
hard to do studies where people get nothing because they drop out and then they don't.
So, you know, once they learn that they didn't get the intervention that they wanted because they if they
wanted to lose weight and then they randomised to receive a very light touch intervention,
then they drop out. So is really hard and then most of them we give them something.
And then the intervention group got the brief advice by the nurse but is different from the previous one.
They get advice on their shopping using an app that looks like this.
It's called Salt Swap. You can scan, swap and collect.
So you basically use when you're ideally when you are at the supermarket and you grab a product that, you know, it's got salt.
You don't have to scan everything because not everything will have sold on it.
But it's mostly packaged, processed foods you scan on.
You get, for example, um.
We. It is strawberries in strawberry sauce anyway.
Very. It's got salt in it. Fresh berry farm, strawberries, insertions.
Okay, that is a weird example.
But anyway, imagine you've got sausages and then you scan them and you get different options and depending on what supermarket you are,
then they'll give you the the the foods that are available in the supermarket.
And then it would also tell you how many swaps you have been accepting from different supermarkets then motivates you to do more and more.