Is the United States Lagging Behind Europe in Memory Improvement?

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In this episode, Lauren & Matt speak with Neil Mehta, PhD who is the associate dean for research and a professor in the Department of Epidemiology at the University of Texas Medical Branch in Galveston. Dr. Mehta’s research focuses on US life expectancy trends, the effects of obesity on disability and mortality, the sources of socioeconomic status disparities in mortality, and patterns of health in the United States and Europe.  

Dr. Mehta talks about a recent manuscript from the NIA-funded TRENDS study called “Trends in Memory Function and Memory Impairment Among Older Adults in the United States and Europe, 1996 to 2018.”, which looks at data from several sources to compare trends in memory function across 13 different countries. 

Neil Mehta, PhD Faculty Profile  

Article Discussed in the Episode: 

Myrskylä M, Hale JM, Schneider DC, Mehta NK. Trends in Memory Function and Memory Impairment Among Older Adults in the United States and Europe, 1996-2018. J Gerontol A Biol Sci Med Sci. 2024 Nov 7;79(21 Suppl 11):S11-S21. doi: 10.1093/gerona/glae154. PMID: 38953519; PMCID: PMC11542220. 

Transcript

Matt Davis:

It's been estimated that over 55 million individuals across the world are living with dementia, and this population is expected to triple in the next few decades. However, trends in the incidence of dementia vary considerably across both time and place. Here in the United States, there's some evidence that age-specific dementia risk might actually be decreasing. However, findings among studies differ, and studies typically only evaluate trends for an individual country. There are few direct comparisons of memory function across the world.

In this episode, we'll speak with a researcher who's looking at how the US is keeping pace with other countries when it comes to memory and cognitive aging. I'm Matt Davis.

Lauren Gerlach:

I'm Lauren Gerlach.

Matt Davis:

And you're listening to Minding Memory. Today, we're joined by Dr. Neil Mehta. Dr. Mehta is the associate dean for research and a professor in the Department of Epidemiology at the University of Texas Medical Branch in Galveston, Texas. His research focuses on US life expectancy trends, the effects of obesity on disability and mortality, the sources of socioeconomic status disparities in mortality, and patterns of health in the United States and Europe. Dr. Mehta directs the NIA-funded TRENDS Network on dementia and disability. More recently, he's published on international comparisons of memory function among older adults. He's a longtime friend and colleague of the CAPRA community. Neil, welcome to the podcast.

Neil Mehta:

Matt, thanks for having me today.

Matt Davis:

Dr. Mehta was the author of the study titled Trends in Memory Function and Memory Impairment Among Older Adults in the United States and Europe, 1996 to 2018, that was published in the Journal of Gerontology: Series A. The study used data from several sources to compare trends in memory function across 13 different countries. We'll include a link to the study attached to this episode. So based on your prior work, it looks like you've studied a variety of different populations. We're curious what initially drew you to studying cognitive aging and dementia from a population perspective?

Neil Mehta:

Sure. So I'm a demographer, and demography is a field that is really focused on understanding high-level big things, if you will, related to populations, and one of the things that demographers study is how populations change over time. So a big part of that is understanding how long we live and how well we live as we get older. So demographers bring this population-level perspective to the study of health. So that's really what drew me, Matt, to dementia research. So dementia is not just a clinical condition affecting individuals, even though it affects individuals. It's also this massive and growing population health challenge. A few years ago, that really piqued my interest in trying to understand intersections between what's happening with cognitive functioning, cognitive impairment, dementia, and larger trends related to population health.

Matt Davis:

So you mentioned that being a demographer, I'm just curious, I mean, I've met demographers over time and I've come to notice that they can work in different environments. I guess from your perspective, what makes a demographer distinct from other fields, like epidemiology?

Neil Mehta:

Sure. At its root, the methods and approaches that we use in demography are identical, actually, to what we use in epidemiology. I sit in the Department of Epidemiology. I'm actually Chair of Epidemiology here at UTMB. And so, the statistical methods, the mathematical foundations of all of these fields are the same. Demography and epidemiology also overlap in our interests in population health, so there's an overlap there. The fields are distinct in how they developed, so demography is not just interested in health, it's also interested in other processes related to human populations, such as fertility, such as migration, such as core aspects of population, population size, all of these things, and demography developed from a very different historical context than epidemiology because it was concerned initially just about the size and composition of the population. And then, demographers sort of invented life tables, if you will.

Matt Davis:

Oh, okay.

Neil Mehta:

... and invented life expectancy. And then, from there, demographers, over many decades, got increasingly interested in issues of health more broadly. While epidemiology, its roots were in health, in public health, in disease, in biomedicine. But the two fields, over time, have come together, in my view. And there's still sort of disciplinary differences and different emphasis on specific methods and specific approaches, but they're very complimentary, and I think we need both. That's one thing I really love working at the intersection between demography and epidemiology, is that I can bring some of my training as a social demographer into this public health space, and I think that makes for just richer science when different disciplines talk and interact with each other. I think it just makes for better science.

Matt Davis:

I'm just curious, do the two disciplines, I mean, epidemiology and demography, do they share terms or do the terms differ a little across it?

Neil Mehta:

So there is a shared language. I think there is a shared language between the two fields, enough so that we can communicate across. Sometimes, again, the emphasis on... Epidemiology starts with diseases and then works their way up, and demographers tend to start with some big level population process, like mortality, like deaths, and then try to work our way down to what's causing those deaths. But we meet in the middle. So I think there's quite a bit of shared vocabulary between the two fields.

Matt Davis:

Okay. It's probably not a perfect analogy, but I always think of economics and statisticians, and I always find it interesting how they do similar things with statistical modeling, but use different terminology. The disciplines are really fascinating to me.

Neil Mehta:

Yeah, absolutely.

Matt Davis:

Okay. So I guess from your perspective, as a demographer, why is it important to do international comparisons when it comes to something like memory function?

Neil Mehta:

So I think international comparisons are a really powerful tool in demography, in population health more broadly for several reasons. So first, they provide a benchmark and ranking so that each society can assess their performance relative to others. So knowing where we stand, I think, is important to drive investments in health and in social policy. Second, they can also help identify the causes of poor health. So knowing that the US, for example, ranks 13th in life expectancy, that's important in and of itself for us.

But it's also, from a scientific perspective, doing international comparisons almost sets up these natural experiments, because societies' populations differ in their levels of risk factors, they differ in their social conditions, they differ in their behavioral profiles. So setting one country up against the other, if you will, can help identify which factors are most important to population and individual health. So it helps us get at causes. It's not the only way to understand the causes of health and disease, but it's another tool that we have, so I find them really, really valuable.

Now, in terms of cross-national comparisons on cognition and memory function, there've been less studies, at least when we published this paper. There haven't been that many looking at these specific outcomes, and that's where we came in on in this work.

Lauren Gerlach:

Great. Let's talk a little bit now about your specific study. Can you tell us a little bit about the data you used, and in broad strokes, what you did?

Neil Mehta:

Sure. So we took advantage of existing longitudinal studies of aging. So these are longstanding studies of aging that measure not just memory function and cognition, but a whole bunch of stuff in the population. So these are not based in a specific clinic or hospital system, these are real population-based studies. So we took advantage of three of these studies. One is the Health and Retirement Study that comes out of the University of Michigan, and that's a US-based study. The second is the English Longitudinal Study of Aging, which is ELSA, and that's a UK-based study. And then, the Survey of Health, Ageing and Retirement in Europe, which is called SHARE, and that is a study that's really broad and comprehensive. It covers, I think today, 28 countries. And in our study, we used 11 of those countries which had a comparable measure of memory function, so we couldn't use the entire set.

But these are the data that we used. And what's really powerful and useful about these studies is that it brought together folks from economics, from the social sciences, who are interested in very different things about what's happening to older people compared to what's happening on the health side. So it brought together folks in biomedicine, in epidemiology, in public health, and then also social scientists. So there's a wide range of questions available in all of these studies to study all sorts of factors related to health, and in particular here, related to memory function.

Lauren Gerlach:

Can you tell us a little bit about these data sources and how similar they are?

Neil Mehta:

Sure. So they're actually quite similar. So the HRS was initiated in 1992, supported by the National Institute on Aging, and that was the original longitudinal, nationally-representative, all of these studies are nationally-representative, study of aging. And then, there was an interest in starting similar studies in other countries, other high-income countries first, but there are now additional studies that are happening in lower and middle-income countries.

So they're often referred to as... I like the term sibling studies. So these are sibling studies, where the questionnaire design and the instruments that were collected in the European studies were largely based on what was asked and collected in the Health and Retirement Study. And all these studies are ongoing. So that's a real advantage when we're thinking about international comparisons, because we have a similar set of measures across from which we can actually make some statements about what's similar and different across countries.

Lauren Gerlach:

Great. And in your study, can you tell us just a little bit about the design? So what factors were you interested in controlling for, over what period of time were you following these folks, and what cognitive outcomes were you looking at?

Neil Mehta:

Sure. So our goal in this study was to do a cross-national comparison of trends in memory function specifically. And memory function is just one component of overall cognitive health or functioning, if you will. And the reason that we chose memory function... So there's memory function, there's orientation, there's calculation, there's language. There's all these aspects of cognitive functioning, which is challenging. These are things that are really hard to measure. This is a challenging area. Understanding brain processes and functioning is really challenging. Memory function was asked in a similar way across all of these data sets. So what would we say in the field jargon is that we had a harmonized measure of memory function. So that's why we chose memory function. It's also a very important part of cognitive functioning, and it does correlate with other aspects of cognitive functioning. So we were interested in doing a cross-national comparison of memory functioning.

We were also interested in doing a study on trends. So we weren't just interested in how memory functioning or levels of memory functioning were at one point in time, which is important and interesting. We were very interested in how it was changing over time within different countries. And just like when we do international comparisons, we can learn a lot by studying trends within a country, because changes in the pattern of disease can be attributed to changes in risk factors or social conditions or other things happening in society. So we brought both of those together, the idea of studying trends within a country, and also comparing levels and trends across countries, so that was the main motivation.

So we had information on memory function. We also need to adjust for some background factors, because a lot of things affect levels of memory function in a particular place. One of those is your age distribution, so some countries are older than others, so we wanted to control for that. We also wanted to try to identify what types of factors may be responsible for any differences that we see in levels and trends in memory function. So we had a wide set of variables available to us in these studies, including sociodemographic variables, so things like educational attainment, and we know that educational attainment is very important to cognitive functioning as you age, things like behavioral factors, so cigarette smoking, body mass index, which is a measure of body weight status, which is a proxy, maybe not a perfect proxy, but a proxy for physical activity levels and dietary behaviors.

So we took some of these social and behavioral risk factors, and also tried to figure out, okay, if we do see differences across countries, how can we explain those differences? Because that's critical here, that's one of the big motivations of why we do these types of international comparisons.

Lauren Gerlach:

Thank you. And just to give our listeners a sense, what European countries were included in this study?

Neil Mehta:

Yeah, sure. So with ELSA, we had England in the United Kingdom. And then, we used 11 countries from the SHARE study. These were countries that had adequate sample sizes, and also, as I mentioned earlier, the appropriate measure of memory function. So these include places like France, Germany, Greece, Italy, Spain, Sweden, Switzerland, Belgium. The SHARE also covers Israel, which is outside of Europe, and we did use data from Israel in this study.

Matt Davis:

So I'm just curious, I mean, it sounds like the countries that you selected were largely dependent on the data availability. Are there other countries that you would really be interested in if you could study any country?

Neil Mehta:

So there is a relationship between cognitive function, cognitive health, and the underlying socioeconomic status and gross domestic product of countries. So wealthier countries tend to have better cognitive functioning and memory functioning compared to countries that are poorer. So this study, we focused on relatively wealthy countries. So we didn't have data, for example, in a lot of places in Eastern Europe, countries part of the former Soviet Bloc, if we go further east. We would want to look at these processes, I think, globally. And now, we can do that, because as I mentioned earlier, there are these sibling studies, that are more recent in origin, that are covering different places in Asia, in Africa. So a much richer and robust international comparison would look at all of these world regions.

But the countries that we did use in this study, we feel are quite representative of the regions that they're in. So specifically, of course, the United States and then Western Europe, and we did, of course, get some data from Israel as well. So we think that what we looked at here were pretty representative countries of what's happening in these regions.

Matt Davis:

So our listeners are very familiar with the Health and Retirement Study, but less familiar, obviously, with the European data that you worked with. Is there anything that you think listeners should know about those data sources? I know you talked a little bit about this already. But also, I'm just curious, are they publicly available for researchers?

Neil Mehta:

Yes. These data are all publicly available to researchers internationally, so you don't have to reside in the particular country that you're interested in. They are available, and there's a lot of resources online to help you learn about these data. So yes, a lot of folks, a lot of researchers here are familiar with the Health and Retirement Study, but increasingly so, there are modules and tools available to help you understand, learn, and begin analyzing data from ELSA, and also data from SHARE. And again, their structure is very, very similar.

ELSA was launched in 2002, and then SHARE was launched in 2004, and I believe over time, they've added countries to SHARE. So this is a very valuable data resource to the scientific community. And then, there's studies in India now, we have studies in South Africa, Latin America, so these studies. And they're adding modules over time, so even the question sets have expanded over time. They've added bioindicators in many studies, not everywhere, but they have added those. They've added genetic markers to studies. So these studies are just becoming richer and richer over time.

Lauren Gerlach:

For those of us who have less experience in international research, can you just tell us a little bit what you think some of the biggest challenges are in conducting cross-country comparisons?

Neil Mehta:

Yeah. So number one, it's really important that you're studying the same thing, whatever that thing is, that you're studying the same thing across contexts. So for something like deaths or death rates, that's generally easy to do because deaths are a very clear event. You are alive or you are not. And in most places in the world today, they're recorded pretty well. There's some variation there, but they're recorded pretty well. So once we get to something like cognition and cognitive functioning, so that's much, much more challenging. We're not measuring a specific blood marker, in this case. I mean, they're working on blood markers for dementia. We're not there yet. It's a very complicated thing to do.

So we have to rely on interviewing people and testing their functioning, and we do so using questions that we think are pretty valid, but that validity is usually with respect to a specific cultural context, a specific language, for example. And when you look across countries, even across Western Europe, we have very different cultural contexts, we have issues of language. So all of these things could play an important role in identifying what you want to identify, in this case, memory. And we all know that memory is difficult. Even within memory, there's so many different components to memory, so measuring that in and of itself is challenging. And then, there are these additional challenges when you try to have a harmonized measure across countries.

Matt Davis:

That brings up a memory of we talked about the telephone interview for cognitive status and spoke with someone who implemented it in different countries, and the unique challenges even in that, she was mentioning to us about the different animals people would use in different places of the world.

Neil Mehta:

Right. Yeah.

Matt Davis:

It was super fascinating to me.

Neil Mehta:

Yeah. That's a great example. And how people even think about different events, and even things like age and even birthday, birth years. In many places, those have different meanings, and people can report differently on their age based on those meanings. So as demographers and other social scientists and folks who are experts in survey taking, we spend a lot of time thinking about this and addressing these issues. And in some places, we do well, others, there's ongoing challenges. So I think in terms of measuring cognition across countries, we've made many advances. A lot of it is because of the efforts of folks who have developed and implemented these sibling studies. But there's still more to learn.

Lauren Gerlach:

So can you tell us overall what you found in your study?

Neil Mehta:

Yes. So we looked at trends in memory function within and across countries, and the big finding is that when you look at the US, our trends were essentially flat. So we did not see improvements in memory function between around 2000 through 2018, and that's remarkable, because when you look at other countries, their trends in memory functioning improved. So the US was a clear outlier, it was unique among the set of countries that we looked at in terms of having almost no trend or no improvement in functioning, and that was the key takeaway from this study.

Lauren Gerlach:

I guess, any thoughts about why that is?

Neil Mehta:

Sure. Yes.

Lauren Gerlach:

Okay.

Neil Mehta:

Okay. So in many ways, this finding wasn't surprising, because since 2000, the US has done worse and worse with respect to a wide range of population health outcomes relative to other high-income countries. So if you look at life expectancy, for example, depending on the set of peer or comparison countries, the gap between the US and other high-income countries doubled, going from maybe around a year lag in life expectancy, so we weren't doing that well in 2000, we were about a year below the average or so, and that's doubled to almost two years at least. It depends on which set of countries you're comparing to. So overall life expectancy, we have not been doing well in.

If you look at major risk factors, for example, such as obesity, our obesity levels have increased much more rapidly in the US than in other countries and stays at a high level. At middle age, we've had the drug overdose epidemic, which has contributed to the growing life expectancy gap. At older ages, we haven't improved in cardiovascular disease mortality. Several cardiovascular risk factors, which were trending really well, such as hypertension, blood pressure, for many decades, those improvements stalled, and we're seeing increases in mean blood pressure in the population, even though we've got great ways to treat it. So it's choose your health outcome and choose your age group, and then compare the US to our peer nations over the last 20 years, and we just lose. We're just not doing as well. So in that sense, if we had any hypotheses going into this study, is that we would thought we would see adverse trends in the US relative to other countries.

So the idea is to think, okay, so we're looking here at a very specific indicator, memory function. The memory function is determined by a lot of other things, like your cardiovascular disease risk, your smoking history, your history of alcohol use, the social conditions that you live in, the stress that you're exposed to. All of these things matter for this specific outcome, and we know that the US has had very adverse trends in all of these things, so it wasn't very surprising to find what we did. But I think it's important to put this particular outcome within the larger context.

Matt Davis:

I always think of the US as somewhat of a competitive country in so many ways. I wish we were a little more competitive when it comes to some of these health measures, because we seem to just kind of let it go.

Neil Mehta:

Absolutely, absolutely. That's why I think what we can do as scientists is to keep pushing out the evidence. And international comparisons, it's quantifiable, ranked. You want to be competitive, you want to be at the top, you want to be at the top of life expectancy. You don't want to have the highest mortality, be at the top there. But we're not the worst performers, by any means. We have very advanced medical care. We have relatively good in an international setting outcomes. If you do have some major conditions, we do well with detection of things like diabetes, things like prostate cancer, things like breast cancer. It's a complicated story, for sure. But yes, if you look at many outcomes over time, we're seeing some very, very concerning trends.

Matt Davis:

So when it comes to memory, the big risk factors that come to mind for me are obviously age is really right up there and other things, like education. And from what I recall in your study, you went through a series of analyses where you progressively accounted for other factors. And from what I recall, I was expecting differences in education to make a big impact on your results, but I don't think it made as big impact as I would have imagined. So I'm curious if you could talk a little about that, the effect of education and what you observed?

Neil Mehta:

Yeah. So there's a lot of literature showing that one's educational attainment is a really major risk factor for cognition throughout the life course. We've studied this quite extensively. In our study, when we controlled, so statistically adjusted for educational attainment, it did influence the within-country trends. So what was going on within countries in terms of memory function changes, and mostly these were improvements, once you controlled for education, we saw that it explained some of the positive trends within countries in a pretty meaningful way, and that was expected.

What education didn't do is explain differences across the countries in the trends, and that actually is also a really important finding, because it suggests that what's happening in the US is more than just our levels of education. And we have to remind everyone that when we do these things and we play around with controls and adjustments and statistical modeling, we're sort of creating an alternate universe. We're separating out factors that in the real world hang together, and we're doing this mathematically in different dimensions that don't really exist anywhere but in the model. And our measures, we're just measuring educational level, we don't have detail on educational quality here. We don't have details on people's performance and grades and other experiences that are linked to education, such as social network formation, that really, we think, are important for cognitive functioning. We're just able to measure, okay, did you graduate from college or not? Did you have a high school degree or not? So we have relatively crude measures, and we're working within this alternate model that doesn't exist anywhere but the model. But we think that we're still getting at something.

So what we found was that, okay, education didn't explain the cross-national differences in trends, so it didn't explain what was happening in the US versus other countries. That indicates that there are other factors at play beyond our educational levels. And educational attainment does not vary or does not differ that widely across the countries that we looked at. It's not like the US had a lot more folks who were not graduating for college. We're up to, I think, a third of the population has a bachelor's degree, and it's similar, maybe a little higher in certain places in Europe, but it's not drastically different. So it wasn't too surprising to see that it wasn't explaining the cross-national differences and trends.

It then takes us to saying, okay, what's going on? And our study was not conclusive in that regard. So I couldn't tell you that, okay, the reason that the US' trend was flat and other countries were not or they were improving was because of factor X. I can't tell you what that factor X here. It's not going to just be a single factor. It's going to be a set of factors, of course, and very complicated factors. But what our study did sort of indicate, and we could do this descriptively, is that we have higher levels of many different now-established risk factors for dementia. So these include obesity, diabetes, many different other related cardiovascular conditions tend to be higher in the US. We have higher levels of social inequality. On average, many folks in the US do not get high quality education. So they may be completing their high school degree, but they may not be getting as good quality as an education as they may be getting in other places.

So all we can do is say, okay, it could be something to do with these other factors, but that's left unexplained, and that, I think, is an important area moving forward.

Matt Davis:

As a teacher, I'm worried about the effect of AI on the quality of education.

Neil Mehta:

Sure.

Matt Davis:

I mean, it's an incredible tool and I know there's a lot of enthusiasm, especially for organizing information and stuff, but when it replaces human thought at early stages of development, I just don't know what that means for us.

Neil Mehta:

Yeah, yeah. And critically, at early stages of development, because we had to grind when we were younger, we would grind even through our doctoral studies, and I would hope that made us better thinkers and scientists and doers. And so, what happens when you don't go through that process? But then, the flip side is every generation has done better than the last, and there's always been technological innovations, but maybe this is... I think it's a different level.

Lauren Gerlach:

So I know you said, based on the findings, we can't get at the exact mechanisms. But if you were talking or advising US policymakers, what do you think we should be prioritizing based on these findings?

Neil Mehta:

Yeah. Okay. So this should be, not just this paper, not the findings from just this paper, but the findings from this whole literature on international comparisons really should be a red alarm. This is unprecedented in modern epidemiological history, where you have a country that continues to get wealthier, continues to advance technologically, continues to get more and more educated, and then, all of a sudden, does not continue and oftentimes deteriorates in its population's health.

So I did my training in demography in the early 2000s, so I started around 2004, and when we were studying population health, everything at that point was rosy because we were looking at data from the 1990s, from the 1980s. Many things were improving in terms of health. Life expectancy was improving at a very rapid pace through 2010 in the US, actually, and in other countries. Not as fast as in other countries, but we were improving. We were improving in our treatments of cardiovascular conditions. We were improving in our treatments of many different types of cancers. So everything was rosy. Smoking levels had declined. Obesity was going up. Diabetes was going up. So why? So we are at this situation where this doesn't need to be happening.

Now, the solutions are complicated. Increasing evidence, investments in children, in young adults, even up to the middle ages matter and can have big effects. But that's a challenge, you have to play the long game, and politicians and policymakers often don't play the long game. But we have to think in that longer term generational perspective here. There's nothing that's going to change overnight, in my view.

When it comes to brain health, so there's this idea that's taken hold called the brain economy, and I'm not sure if you've covered anyone there on the brain economy. It's a big term now and it's being discussed at World Forums and everything's the brain economy, because you can't have a wealthy country without good brains, you just cannot. You need good brains, so you want to invest in brain health in particular. And we know so many risk factors, so this should help policymakers. A lot of the risk factors that we've identified for dementia, there's something that we can do about. We can improve cardiovascular risk profiles through medications, through lifestyles. All of these things are important. It's not just one or the other. So we can improve all of these things, and these could have really large payoffs to society as a whole, but if you're thinking about your specific constituency, to families who live in your district. And people want to be healthier, people absolutely want to be healthier.

So all of these investments and things that we know about will have positive downstream effects on dementia. But there's no single magic policy here. So in that sense, it is very complicated. But if we improve the general health profile of younger and middle-aged adults, we will likely see pretty strong benefits on brain health in these cohorts as they age, and good brain health leads to good economy.

Lauren Gerlach:

That's fascinating. So just in terms of this line of work and research, what's next for you and your team?

Neil Mehta:

Yeah. So as I mentioned earlier, these sibling studies are fantastic. They're population-based, so we can learn a lot from them. But there are things that we can't learn. So one of those things is on what's happening around medical care. We can get at some of these questions with these data. But now, we have very rich databases that include medical records, and we have these things internationally. So we have several databases here in the US. They are challenging in their own regard. They have their own sets of shortcomings. But we're very interested now in looking at dementia internationally and trying to identify risk factors in the medical records. So we would have more detailed cardiovascular risks, for example, in these records, and we want to look at these things internationally.

We're not only interested in the risk factors that lead one to dementia, but once you have dementia, what happens to you? What are the outcomes associated with people who have dementia across countries? And there is some work being done on this. There are still some areas that we can contribute to. But what are the outcomes? So if you have dementia and you're living in Finland, what do your life chances look like compared to if you have dementia in the United States? We don't know. We don't know a lot of that. And so there's going to be different ways that dementia is treated, there's going to be different life expectancies associated with dementia, so how long you live after you're diagnosed across countries. So this is something that we are planning and starting to do now, is thinking about this dementia epidemiology, if you will, across nationally, and looking at different data sources in Europe that we can compare to the US, and that will just give us a more complete picture of what's happening internationally with respect to cognitive functioning and dementia specifically.

Matt Davis:

Well, this has been a lot of fun having a demographer on the podcast. And I must admit, it's the first time I've ever thought about the connection between memory function and gross domestic product. But maybe it's not a bad thing to motivate people to care about this work.

Neil Mehta:

Absolutely, yes.

Matt Davis:

Neil-

Neil Mehta:

Thank you for having me.

Matt Davis:

... thanks so much for joining us.

Neil Mehta:

Appreciate it.

Matt Davis:

If you enjoyed our discussion today, please consider subscribing to our podcast. Other episodes can be found on Apple Podcasts, Spotify, and SoundCloud, as well as directly from us at CAPRA.med.umich.edu, where a full transcript of this episode is also available. On our website, you'll also find links to other resources we've created specifically for dementia research.

Music and engineering for this podcast was provided by Dan Langa. More information is available at www.danlanga.com. Minding Memory is part of the Michigan Medicine Podcast Network. Find more shows at michiganmedicine.org/podcasts. Support for this podcast comes from the National Institute on Aging at the National Institutes of Health, as well as the Institute for Healthcare Policy and Innovation at the University of Michigan. The views expressed on this podcast do not necessarily represent the views of the NIH or the University of Michigan. Thanks for joining us, and we'll be back soon.