Hello and thank you for joining. This section of the board review course is chronic disease epidemiology and I am Brenna Van Frank. I am a medical officer at CDC and I'm boarded in PEDS and in preventive medicine. So I've been in your seat. I've had to take this test and study this content. So I understand your pain and I'm with you. So today what we're going to try to do is go through just an overview of chronic disease epidemiology, try to give you some really key nuggets as you're studying for your exam and shove as much information into your brain as we possibly can in the space of three hours. So I'm going to share my screen and turn off my camera simultaneously so that the technology doesn't break. So bear with me for just one second. Okay great thank you. Okay so I do need to at the beginning of this disclose of course that I am from CDC but I am not speaking on behalf of CDC. So everything that's about to come out of my mouth in the next several hours is my own and not representative of the official position of the age of the CDC. Also and you've probably heard this one before but I have nothing to do with test development. I have no special insight into what's on this test except for having taken it several years ago. I know what you know and really that's the board content outline. I also know what you know in that of course I've taken many a board exam in my time just like you have and so I'll offer you some study tips from that perspective but again those are just my opinion so please take or leave as makes sense to you. So today what we're going to do is describe the burden and distribution of chronic diseases. We're going to describe variations in chronic disease distribution by age, by race and ethnicity, by sex, and by U.S. geography. We're going to describe risk factors for chronic disease and in this I've done my best to really try to cover those disease processes that are noted in the test content outline. What we're not going to cover in our time together is pathophysiology, clinical screening or diagnosis, clinical treatment, clinical guidelines. We're not going to talk about cancer staging. We're not going to talk about infectious disease. We're not going to talk about other non-chronic disease. Most of this information will be covered or should have been covered in detail elsewhere in this review course so expect from me a lot of data and not a lot of clinical. So chronic disease is this huge topic right it's vast and we have only about three hours to cover all of it. Don't be intimidated this is kind of where we're headed and really just I want you to think about this as like nine mini lectures. So just nine really nice chunks that you can focus down and in on as you're studying and you'll see here you know we have three cancer sections. I know it's a lot of cancer but you'll see in just a minute cancer was of course the second leading cause of death in our country so it's really worth it I think to take some time in that space so we will. And like I said you know we have a lot of information to cover in our time together and you're going to then have to study a fair amount of it but like I said we're just going to take this one step at a time right. So as we go through what I want you to focus on is this kind of similar patterns in the information being presented and to that end I've tried to structure each of the sections in a similar way so that you're going to see a similar pattern and how the information is presented so that you can do some compare and contrast. We're going to talk about prevalence, we're going to talk about mortality, we're going to talk about cost, time trends, we're going to talk a bit about demographic and geographic variations, we're going to talk about risk factors. And what I'm going to try to do is present things in a way that are sticky for your brain. So in the slides that are coming you're going to see a lot of headline type statements. My intention is not to be dramatic or sensational, it's not to oversimplify or try to give you sort of journalistic soundbites. Our collective goal today is to shove as much information into your brain as possible so that you can pass this test. So the intention of how I'm presenting the information and these sort of sticky headline type statements is really to help you with that process. So don't feel like I'm trying to be dramatic or sensational, I'm just trying to get it into your head. And to that end, before we start, there's some things that I want you to keep in mind as we sort of climb up this pyramid of content. And the first is to start looking for where you can make broad strokes in the information. So focus on the simplified. You're studying for a multiple choice test, right? You're not trying to become some deep subject matter expert on the stats for each of these disease processes. You can become an SME later and you're probably already an SME in one of these spaces as it is. Right now, what we're focusing on is multiple choice exam. So think in terms that are broad enough to stick in your brain to let you choose the right answer. So for example, remember that two in three adults have overweight or obesity, not 71% of adults have overweight or obesity because it might be easier to remember the two in three. The other thing I want you to think about is focusing on general trends. So rather than trying to remember that diabetes prevalence was 3.3 in 1995 and then 7.4 in 2015, just try to remember prevalence doubled in the last 20 years. So those general trends. Also think about focusing on patterns in the data. So know the patterns and then pinpoint where things are different. So rather than trying to remember that the prevalence of cardiovascular disease is 84.4% among adults over the age of 80, I want you to see that CVD risk across the board generally increases with age, with the exception for dyslipidemia, which peaks in middle age. So focus on the patterns, identify where it's different, might be easier to remember. And then focus on risk factors. Again here, look for patterns and see differences. So rather than trying to remember every risk factor for every single cancer, consider flipping it on its head and remember that risk factor X applies to cancers A, B, and C, but not T. And that might be helpful too. There's two more things that I want to note before we jump into content, and that's about the data that you're about to look at. So first, this data is U.S.-centric. I'm not going to say it over and over as we go through the hours together, but just know right now, basically all the data you're about to see is U.S.-based. We're not going to be talking about global chronic disease epi. The second is that when I was picking what data years to present to you, I had to balance consistency of years with recency of data, because some of the surveillance systems publish at different times. And I also had to balance pandemic-related survey data and changes that were happening in 2020 and 2021 with data recency, and then with my best guess about likelihood of showing up on the test. So all of that to say, some of this data may seem old to you, and that's okay. Remember that what we're more interested in when we're studying for multiple choice exams is broad strokes and general trends. And the thing about chronic disease epi is that it generally doesn't change super fast, right, which in public health practice may drive us all a little bit crazy, but for the purposes of passing your board exam is really something that's on our side today. All right, so let's jump in. Let's start with a broad overview on chronic disease in general. There's three big things to know. The first is chronic disease is common, the second is chronic disease is costly, and the third is chronic disease is killing us. So what does that look like in numbers? Well, you can see here on the left side, the percent of adults that have at least one chronic condition is about half, right? So we know that about one in two U.S. adults has at least one chronic condition. And we also know that chronic conditions come together a lot. And so we know that about one in four, 25 percent or so, it's 27 percent, but we're talking broad strokes, has two or more chronic conditions. And we also know that chronic, that increases with age, right? So I'm showing you here breakdowns by age, and we see a much bigger prevalence of multi-chronic condition in the over 65 population compared to the 18 to 44s. And we also see some variations by race and ethnicity. We're going to dive a little bit deeper into specifics on socio-demographic variations as we go into the different specific chronic conditions. We also know that chronic disease is tied to a lot of what is killing U.S. adults. So seven of the top 10 causes of death in our country are chronic diseases. It accounts for about two-thirds of U.S. deaths. And the top two causes of death, heart disease and cancer, account for over a third of U.S. deaths together. So huge burden, both from a public health standpoint and just from a human standpoint. This is what it looks like in order. So I'm showing you here 2019 data. And the reason I'm showing you 2019 data is because I want you to know what this looked like pre-pandemic. I am going to show you 2020 data in a bit of a different way in a later slide, just in case that comes up on the test. But I thought that you should know what the general pattern looked like before COVID. So by and large, in the absence of global pandemics, this list doesn't change a whole lot. We have seen some shifts between number three, unintentional injuries, and number four, chronic lower respiratory diseases, in about the mid-20-teens, like 2016-17. And that was primarily due to a rise in overdose deaths. But beyond that change, the order of the list has been generally very similar for several years. So good to know heart disease one, cancer two, and that the one, two, that seven of them are chronic. This is the same information, just in a different visual, in case the different visual sticks in your head a bit better this way. I also want to flag for you that the numbers on your version of this slide aren't correct, even though the box proportions are correct. There was a bit of an Excel snafu that I caught just a couple of days ago. So the numbers that you want are actually on the previous slide. Again, it's the same data as the previous slide, just presented in a way that some of you might be able to remember a little bit more easily. So focus on the numbers from the previous slide, but the box proportions are correct. And then the other thing to be aware of is that cause of death varies by age group. So here, 2019 data, again, data for cause of death by age. There's a couple of things that I think you should take home from this slide. First is that between the ages of one and 44, the leading cause of death is unintentional injury. And then the second thing is that cancer is in the top five causes of death for all ages above one year of age. Heart disease is similar, right, except for the 10 to 14-year-olds. So those top two causes of death appear a lot, but don't be tricked, right? If you get a question about teenagers or about young adults, what's the leading cause of death? It's unintentional injuries. And of course, here's that slide I promised you with 2020 data. So again, broken down by age. And you can see here that the top two causes of death for each age group are largely unchanged, but COVID starts to sneak in there in the older age group, starting around the third rank for the 55 and ups. So just be aware that this change happened, but also be aware, again, those one to 44-year-olds, top cause of death, still unintentional injuries, and cancer and heart disease remained in the top. Okay. So that's it for the overview on chronic disease. Now let's talk a bit about risk factors. We're going to talk about four major risk factors in this section today. So we're going to talk about nutrition, specifically diets low in fruits and vegetables, high in added sugars, sodium, and saturated fats. So poor nutrition. We're going to talk about tobacco use, primary use, and secondhand smoke exposure. We're going to talk about excessive alcohol use, and we're going to talk about a lack of physical activity. I also just want to flag, there are other risk factors that we're going to talk about today. So for example, we'll also be talking about obesity and hypertension in later sections of the course. But they are, of course, both disease processes and risk factors. And so I just decided to put them somewhere else, categorize them in a different way. The other thing that I would note is that insufficient sleep is a really important risk factor in the development of chronic disease. We know that less than seven hours of sleep a night has been longitudinally associated with obesity, with hypertension, with stroke, with coronary heart disease, and then with type 2 diabetes. I'm not going to cover sleep in great detail today because it's not on the exam content list so far as I can tell, but do know that it is important. And so I'm just putting that nugget in your brain, lack of sleep, chronic disease, just in case it shows up. Okay, so starting with poor nutrition, we'll take a deeper dive and I'll show you some data. So I like to start these sections with some definitions. I imagine that you've already seen something along these lines, looking at the dietary guidelines somewhere else in this board review course. But this is just a reminder so that we can level set. This is what the 2020 to 2025 dietary guidelines say broadly. So pretty broad, follow a healthy dietary pattern, customize and enjoy nutrient-dense foods, focus on meeting food group needs, particularly with nutrient-dense foods, stay within your calorie limits, and then limit added sugar, saturated fat, sodium, and alcoholic beverages. And the dietary guidelines then go into a little bit more detail. And the reason I'm showing you this is because this becomes important when we start to look at data because we need to understand what the definitions are for our surveillance. So here, healthy patterns are defined as two to three cups of a variety of vegetables a day, one and a half to two cups of a variety of fruits per day, some grains more than 50% which should be whole, fat-free or low-fat dairy, a variety of proteins. And then this piece around added sugars is going to become important later when we start taking a look at what people are actually eating. So less than 10% of calories a day from added sugars, less than 10% of calories a day from saturated fats, and then this 20 less than 2300 milligrams per day of sodium. I also want to flag here while we're sitting on this slide that there's some age-specific language in the dietary guidelines that I'm not showing you here. So for example, for added sugars, there's this less than 10% of calories a day of added sugars, but that starts at age two. For those younger than two, the guidance is to avoid foods and beverages with added sugars. Sodium, similarly here, the recommendation is less than 2300 milligrams per day, but that's for people age 14 and up, and the language is something like, and even less than this for those who are under 14. There's also some language nuance around alcohol. So here I've listed up to one a day for women, up to two a day for men, but there's more detail in the dietary guidelines. The message really is that drinking less is better for health than drinking more, and that there are some adults who shouldn't drink alcohol at all, such as people who are pregnant. Okay, so that's our definition. Now let's drill down on some specific data regarding diets. So we'll start with vegetables and adults. So we don't do great, right? This is at a population level. Only about one in 10 U.S. adults report eating the recommended daily amount of vegetables. That was in 2019. When we asked them if they're eating, you know, how often are they eating vegetables at all, about 21% eat vegetables less than once a day, and there are some variations on socio-demographic factors. So people who are less likely to eat vegetables once a day are men, non-Hispanic black adults, Hispanic adults, younger adults, and then adults with less education and lower income. What does this look like from a geographic standpoint? Well, you've all seen this. This is a heat map. You know what a heat map is. Here, just for orientation, the darker color is worse, just like in a heat map typically, and so this is adults who report consuming vegetables one less than once a day, and so the thing that I think that's important here to highlight is that even in the best states, so those are the lightest color, right, so the lowest percentage of adults who are eating vegetables less than once a day, only about one in eight is not eating vegetables once a day, and that's, there's, there's a lot going on here. The other thing I want you to pay attention to when we talk about maps and when I show you maps is just general gestalt patterns, right, so here I'm not seeing huge, a very obvious geographic pattern. Maybe you could say that there's some higher problems, like in the southeast and up the Mississippi River Valley, but, but there's not like a huge dark pocket, which you're going to be seeing in some later maps. Okay, fruit. Adult fruit is moderately better, but still not fabulous. One in eight U.S. adults ate the recommended daily amount of fruit in 2019. That's about 12 percent. When we ask them when, if they're eating fruit at least once a day, it's 40 percent are eating fruit less than once daily, again in 2019, and we see similar socio-demographic patterns of folks that are struggling to eat fruit daily, so men are less likely to eat fruit once daily, younger adults, and adults with less education and with lower incomes. What does that look like geographically? Well, here again, you know, even in the best states, the light, you know, the light colored ones, one in three adults aren't eating fruit once daily, so there's a lot of work to be done here, but here you can see in the geographic dispersion that there is a bit more of a, of a pocket, if you will, of states that are having more trouble in this space. Okay, talking about sugar. So, remember the, the dietary guideline is less than 10 percent of daily calories should come from added sugar. When we asked adults through NHANES in 2013 to 16, it's about 13, U.S. adults report about 13 percent of their daily calories come from added sugar, so a bit higher than the, than the guideline, and when we look at it by socio-demographic breakdown, we know those that are more likely to eat more added sugar are younger adults, non-Hispanic Black adults, and those, again, with less education and with lower incomes. Flipping to youth, so how are our kids doing? A lot worse than their adult counterparts, so this data is from a couple of different years because it's from a couple of different data sources, but less than 1 in 14 high school students was eating the recommended daily amount of fruit in 2017, and one in 50 high school students was eating the recommended daily amount of vegetables. So the adults are doing a bit better than that, but there's a lot of work to do with the kids. And then the added sugar, so the two to eight-year-olds, remember for above two, it's everybody's less than 10% of daily calories from added sugar. For the two to eight-year-olds, it's 14%, and for the nine to 18-year-olds, it's actually more, it's 16%. And looking by state, so we don't have data available for every state because it depends on whether or not a state decides to ask these specific questions in a given year, so those are the gray states where we don't have data. But even with the states that we do have data, you can see that the patterns are similar as the patterns for adults, and those ranges are a little bit higher, just as we had just discussed. All right, moving on to the next risk factor, so lack of physical activity. And again, starting with some definitions and looking at the guidelines. So this is the physical activity guidelines for Americans, the second edition. And note that the guidelines that are related to both aerobic activity and strengthening activity, so to meet the guideline as an adult, you need to have an equivalent of 150 minutes a week of moderate intensity aerobic physical activity plus strengthening activities on two or more days in a week. And the reason I bring this up is because of how the surveillance works and what the definitions for the surveillance definitions are. And so we're going to talk a little bit more the surveillance definitions are. The other thing to know about the second edition guidelines is that any amount of time counts. So make sure, because the previous guidelines before the second edition talked about the time needing to take place in increments of 10 minutes or more, that recommendation is gone now. And so now it's just like, just move any duration of time up to, you know, get your minimum of 150 minutes a week. It doesn't have to be in 10 minute bouts anymore. So really just move more, sit less. So don't get caught on the test of trying to pick like those 10 minute bouts. This is what it looks like for children. So preschoolers, the three to five-year-olds, really just like be active all the time. And then for the six to 17-year-olds is that combination again of aerobic activity and strengthening activity to be able to meet the guidelines. And again, this is, I'm showing you this not because you probably haven't seen it yet already in the board review, but because this impacts how we define our surveillance. So how are we doing? Well, this is adults meeting physical activity guidelines over time. And you can see not a ton of changes over time, a bit, but not a ton. And when we talk about meeting physical activity guidelines, this again is both aerobic and strengthening activity. So when we do that combination, aerobic and strengthening activity, it's only one in four U.S. adults who meet guidelines. Men do a little bit better than women. You might also see statistics on meeting aerobic activity guidelines. So taking the strength part out. When you look at aerobic specific only, it's actually about half of adults who meet aerobic activity guidelines. So lots better. Still not great because it's still only half, but better than the combination of the two. So when you're answering a question, make sure you know what they're defining. When you're answering it, are you talking just about aerobic or are you talking about aerobic and strength? This is what teenagers look like in terms of physical activity guidelines. Again, aerobic and strengthening activities together, only about one in six teenagers meets guidelines. Again, boys do a bit better than girls. It's interesting though because that difference, the boy-girl differential, actually happens in middle school. So when you look at earlier ages, there's not a lot of difference between boys and girls in terms of activity level. So I just thought that was an interesting nugget to put in your brain. We see, of course, variations by socio-demographics. As we do, we've already talked about the difference between males and females. This is adults, by the way, and meeting physical activity guidelines, both aerobic and strength. So we have lower rates of meeting guidelines among women, among Hispanic adults, among older adults, among adults with less education, and among adults with lower income. And then this is by geography. So now this heat map is actually flipped, okay? So don't get confused because I get confused every time I look at this map. But it's rather than the dark colors being worse performance, the dark colors are actually better performance, and the light colors are worse performance. And that's just because of how the question's asked. So this is percent of adults in the state who meet aerobic and strengthening activity guidelines. So more is better, which means that darker is better. Anyway, this should be the only map, this one and the one that follows on kids should be the only map that is weird like that, but I just wanted to flag for you because every time I come back to this map, I have to remind myself of the flip. So here, again, you know, taking a look at where the best spots are, only about one in four adults is meeting activity guidelines, even in the best performing states. This is kids, again, high school students, and this isn't meeting physical activity guidelines, this is actually high school students who get at least an hour of activity daily. So meeting that aerobic component, but it does not take into account the strength component. Similar to adults, even in the best states, the states that are performing the best, only about a quarter of high school students are getting the recommended amount of aerobic activity. So some gaps there. So why does all that matter? Well, because physical activity is hugely important, right, in chronic disease prevention. We know that physical activity can help prevent breast cancer, can help prevent colorectal cancer, can help prevent diabetes, can help prevent heart disease. I love this quote from the former CDC director, Tom Frieden, that physical activity is the closest thing we have to a wonder drug. Like, while we're all waiting for the wonder drug to come, this is the closest thing we've got. And so really important in chronic disease prevention. And it has benefits sort of across the lifespan and across the board. So there's physical and mental and cognitive benefits in each age group. I've listed some here. Please don't try to memorize all of this for the test. Just a general gestalt, right? The physical activity has a reduction in risk of depression in kids and improves mental health in adults, improves cognitive function, also reduces risk of chronic disease, extends years of active life, etc. So again, don't memorize the bullets, but just general gestalt of why physical activity is important. Okay. So we've chatted about two things that we don't do that we should. Now let's talk about two things that we do do that we shouldn't. So I'm going to start with tobacco product use, and then we'll talk about excessive alcohol use. Before I talk about tobacco product use, I just want to flag that in this presentation, when I'm talking about tobacco use, what I'm talking about is commercial tobacco products. So those products that are manufactured and sold for profit and not the traditional use of ceremonial tobacco by some Indigenous communities. I do that for two reasons. I flag this for two reasons. One, to promote cultural safety for those of you and for everyone who's listening who has ceremonial tobacco as part of their culture. And two, because the definition is really important, again, when we're talking about surveillance and we're talking about what products people are using. So if physical activity is the wonder drug that we've all been waiting for, tobacco product use is the antithesis of a wonder drug. From a number standpoint, we know that about 47 million U.S. adults used some form of commercial tobacco product in 2020, and that's basically that's any commercial tobacco product, cigars and e-cigarettes and smokeless and pipes and cigarettes. When we talk about cigarettes specifically, it's about 31 million U.S. adults who smoked cigarettes in 2020. Cigarettes are the most commonly used product by U.S. adults, so important to keep that in context. We know that cigarette smoking is linked to about a half a million deaths in the United States every year, and for every one of those deaths, at least 30 people live with a serious smoking-related illness. We also know that secondhand smoke exposure is prevalent. It's about 25 percent of the U.S. population is exposed to secondhand smoke, including about two in every five kids, and there are some sociodemographic variations in that as well. We also know that it's quite expensive. Cigarette smoking cost the U.S. more than 600 billion dollars in 2018. That's in health care spending and productivity losses, so common, deadly, costly, just like we talked about with chronic disease in general. From a time trend standpoint, there's been a lot of progress in reducing adult cigarette smoking. I am going to flag again because I think it's important, just in case it comes up on the test, that there are a large number of tobacco products in the market, but cigarettes remain the most commonly used product by U.S. adults. In 2020, it's about 12.5 percent of U.S. adults reporting current cigarette smoking, but again, improvement over time in case that comes up. We've also been making substantial progress in reducing youth cigarette use. You can see cigarettes here are that lime green color, and you can see that the declines have been going, or excuse me, the trend has been going down significantly, but we have reversed our progress in youth use of tobacco use as a whole, and that's largely being driven by e-cigarettes, which is the red line on here. You can also see from this that e-cigarettes are the most commonly used product among high school students, so an important distinguishing factor. Adults, it's cigarettes, and high school students, it's e-cigarettes. Middle school students look similar in that e-cigarettes are the most commonly used product, but the prevalence of use of all products is quite a bit lower. There's variations. We're going to go back to adult cigarette smoking now on this slide, but there's variations in cigarette smoking by sociodemographics. I've highlighted a few of them for you here. So there are higher rates among American Indian Alaskan Native adults. There's higher rates in adults that have less education, lower incomes, adults with disabilities, adults in sexual and gender minority groups, adults living in rural areas, adults that have mental health or substance use conditions, and I'm just going to flag again because I often get this question, you know, is that higher rate in American Indian Alaskan Native communities because of ceremonial use? And let me just go back. This is cigarette smoking, right? This is cigarette smoking, right? This is commercial tobacco use. We're not talking about ceremonial tobacco. Geographically, there are substantial disparities in adult cigarette smoking in the southeast and up along the Ohio and Mississippi River Valley, so you can see that hot spot in blue. Take a note of this geographic pattern. We're going to see it over and over as we look at chronic diseases and their risk factors with this sort of hot spot right there. So I flag that for you because then it's important to pay attention to the chronic disease processes that do not have this pattern because that might be easier to remember than the reverse. So just a flag for you. Cigarette smoking, of course, is a huge risk factor. It causes a lot of chronic disease processes. Each of the diseases that's listed on this slide has been causally linked to cigarette smoking, so there's 12 types of cancers, there's a variety of cardiovascular diseases, there's type 2 diabetes, a variety of pulmonary processes, some adverse reproductive health effects, there's some bone and joint effects, some immune function effects. Suffice it to say, basically every organ system is impacted, but I don't want you to get caught by a question that tries to link smoking to one of these cancers and you see, oh, it's not lung cancer, and so you answer it wrong. Just know that there's 12 different cancers, there's a variety of chronic diseases. Have that more global picture for cigarette smoking as a risk factor and you'll be fine. There's also some disease processes that are more prevalently caused by smoking than others. Bottom line on this slide is to recognize that there's a lot of chronic disease-related death that could be prevented by removing cigarette smoking as a risk factor. So we know about 90% of lung cancer deaths are caused by cigarette smoking, about 80% of COPD deaths, about a third of cancer deaths, about a quarter of cardiovascular disease deaths. We also know that just increased all-cause mortality is higher. Mortality is about three times higher in people, in adults who smoke cigarettes than those who do not. Secondhand smoke, also important to understand that's been linked to multiple disease processes and death as well. So disease processes on the right for adults, we know secondhand smoke is a cause of lung cancer, is a cause of coronary heart disease and stroke. In children, is a cause of sudden infant death syndrome and middle ear disease. The good news is though, smoking cessation reduces risk over time. We know that quitting smoking is beneficial at any age, no matter how long or how much someone has smoked. And so if you're asked about mitigation, smoking cessation is always the right answer, right? Don't feel you have to memorize this whole thing. Again, broad strokes, I would know probably that there's immediate health benefits. So if you're asked a question about counseling someone about quitting smoking, there are immediate health benefits. Know that smoking reduces the risk for all 12 of the cancers that it causes. And maybe know that heart attack risk drops in about a year. And then maybe one more, like stroke risk decreases in five to 10. So I think, you know, just know some gestalts and a couple of key things that might, you know, pretend like you're a test writer and think, what's the easiest thing on here to ask a question about? What would I want folks to know? And maybe heart attack and maybe stroke, given how high they are on the causes of death list. But that's just my guess. Okay. Excessive alcohol use. So again, starting with a definition. When we're talking about excessive alcohol use, we have to start with a definition excessive alcohol use, we have to standardize what we're talking about, right? So that we're all measuring and talking about the same thing. These are the standard definitions. The idea here is that we're normalizing the volume to the amount of alcohol. So essentially 14 grams of pure alcohol is the standardization point. And so whatever volume of whatever percent alcohol drink it is, is whatever gets you to the 14 grams. And then there has to, of course, be some standard definition as well of what constitutes excessive alcohol use. There's a few definitions out there, but this is how it's defined for public health surveillance. So there's four categories. There's heavy drinking, which is defined in women as eight or more drinks in a week and for men as 15 or more in a week. There's underage drinking. So that's any alcohol used by those under 21. There's drinking during pregnancy. So any alcohol used by pregnant people. And then there's binge drinking. So this is number of drinks per occasion. Occasion is in a span of two to three hours. I don't think there's a formal definition of that, but that's the general gestalt, two to three hours. So for women, it's four or more drinks in an occasion and men five or more drinks in an occasion as binge drinking. Okay. So we have our definitions. Let's talk about public health impact. So we, you know, when we're measuring excessive alcohol use, we talk about excessive alcohol use generally. So all four of those categories. We also talk about binge drinking specifically. And I'll tell you why on the next slide. But suffice it to say, there's about 38 and a half million U.S. adults binge drink about once a week. We know that excessive drinking causes death or alcohol attributable deaths. And we'll talk about those in more detail. But you can see that the number isn't small. We know that this impacts teenagers. So we know one in three high school students reported drinking in the last month. The other thing that I think is maybe an easy test question, and one that you're going to get right now, is that most people who drink excessively do not meet clinical criteria for having a severe alcohol use disorder. So it's nine in 10 of them do not meet those clinical criteria. So important to sort of level set what we're talking about. And then very costly, right? About $250 billion a year in economic costs, including health care costs. So why do we talk specifically about binge drinking? Well, binge drinking is the most common form of excessive drinking. About 90% of people who drink excessively, or excuse me, 90% of people who drink excessively binge drink. So it's the most common form of excessive alcohol use. It's also very costly. And it's the most deadly pattern of excessive alcohol use. And I'm just going to flag for you as a memory cue, binge drinking, four plus drinks for women in an occasion, and five plus drinks for men in an occasion. So let's talk a little bit more about binge drinking specifically. So I told you it's the most deadly pattern of excessive alcohol use. Binge drinking causes more than 40% of alcohol attributable deaths. And we know that binge drinking is responsible for nearly 80% of the total costs of excessive alcohol use. So now you understand why we're focusing in on that one, right? It's the most common. It's the most deadly. It's the most costly. The other thing to know about when we're measuring binge drinking is that there's two measures. The first is the prevalence of binge drinking. And then the second number is the number of binge drinks consumed per person who binge drinks. So the prevalence of people who binge drink and the number of drinks that those people drink. Okay. So the first measure we know that one in every six U.S. adults binge drinks about four times a month, right? So that's about once a week. So about one in six U.S. adults. But when we talk about binge drinks per year, it's about 17 billion all told, which is about 467 binge drinks per person who binge drinks. And the reason there's a distinction between prevalence and number of binge drinks is because their socio-demographic variations between those two measures are different. So let me show you what I mean by that. So when we're talking about the prevalence of binge drinking, we know that binge drinking is twice as common among men compared to women, and we know that binge drinking is more common in younger adults, although it does occur across the lifespan. It's not just younger adults, it's just more common in younger adults. But when we're talking about socioeconomic status, so income and education, we know that, or we see that in the data, binge drinking prevalence increases with higher household income and higher education. So it's directly related to, sorry, I'm not saying that right. Statistically, they move in the same direction, right? So binge drinking prevalence goes up with increasing socioeconomic status. But the reverse is true. It's inversely related. Binge drinks consumed is inversely related with socioeconomic status. So the number of binge drinks consumed per person who binge drinks, say that five times fast, decreases with increasing socioeconomic status. And the geographic variations are also different. So I'm only going to show you, because it gets just too confusing and tongue twisty to say, but the prevalence of adult binge drinking looks like this, generally higher in the Midwest and a bit in New England than other regions. But in contrast, if I were to show you a map of the number of binge drinks per binge drinker, that's generally higher in the Mississippi River Valley than other regions. So the variations are different, is the bottom line. Okay, so alcohol use as a risk factor. So there are a lot of health effects of excessive alcohol use. And I'm highlighting a lot here. Again, don't try to memorize all of this. I'll just highlight a few take-homes for you. First, there's an acute impact, and there is also a long-term health impact. So we could separate these into acute health impacts and long-term health impacts. I would know that there are seven cancers that have been linked to excessive alcohol use. I would know that there are behavioral health impacts, that there are mental health impacts and cognitive impacts. I would know that even though that nine out of 10 adults who excessively drink, excessively use alcohol, do not meet clinical criteria for alcohol use disorder, alcohol use disorder is still not uncommon, right? So it's about 5.8% of adults. And it also can be a problem in teenagers. So I would know that too, if I was guessing. Alcohol attributable deaths. A couple of things to point out here. I think there's a misperceptive misperception generally held by the public that the primary source of alcohol-related mortality is related to acute impacts. And acute impacts are a significant part, but more than half of alcohol attributable deaths are due to chronic conditions. So I'm showing you that here. But the take-home on this is more than half are chronic condition-related deaths. Okay. So let's dive into cardiovascular disease. So as you've seen in our chronic disease overview, cardiovascular disease is the number one cause of death in the United States. So we're going to spend some time here. There's a lot of content to cover. Just bear with me. We'll get through it. But just know we're parking here for a little while. We're going to talk about cardiovascular So let's start, of course, with a definition and level set what we mean by cardiovascular disease. So CVD includes a lot of disease processes, many of which, but of course not all, are listed here. And sometimes when we're defining cardiovascular disease for public health purposes, we include all of these. Sometimes we exclude things like congenital heart disease. It really sort of depends on why and what we're looking at in the data. That can make interpreting the data pretty challenging, actually, particularly when folks don't define what they're talking about. Are you defining cardiovascular disease as including or excluding cardiovascular disease? So as we're going through this, I'm going to try to flag for you what definitions we're using so that you can have a better understanding of what the data is that I'm showing you. We're not going to talk about every single cardiovascular disease process in depth today. That would be just way too much. What we are going to focus on are some of the things that we're going to be talking about today. So we're going to talk about cardiovascular disease, way too much. What we are going to focus on are the ones that primarily impact adult health. So the ones that contribute to cardiovascular disease being the leading cause of death in our country. We're going to focus on the ones on this slide because they're generally the ones that are listed in the board content review list. So this is our roadmap. We're going to start with CVD overall, and then we're going to talk about heart disease. And inside of our discussion about heart disease, we're going to talk about coronary heart disease. And inside of our discussion of coronary heart disease, we're going to talk about MI. And then we're going to come back to heart failure. And then we're going to finish heart disease. And then we're going to go to cerebrovascular disease, stroke. Then we're going to go to PAD. And then we'll talk about hypertension and dyslipidemia. Now when you're studying, if you get lost in the CVD slides, it's been known to happen, it's good to come back to this slide as a bit of a table of contents, as it were, to reorient yourself to where you are. Okay, so CVD as a whole. Let's talk about some numbers. So about half, 48% or so, of U.S. adults older than the age of 20 have at least one type of cardiovascular disease. And what I mean by cardiovascular disease in this statistic is coronary heart disease, heart failure, stroke, and hypertension. So 48% of the U.S. population, of the U.S. adult over 20 population is about 127 or so million people. This definition does not include congenital heart disease. It does not include peripheral artery disease. And that's because of how peripheral artery disease is measured in our surveillance systems. It's just, it's unfortunately not included in this particular stat. If you exclude hypertension from this definition, and you focus only on coronary heart disease, heart failure, and stroke, then the prevalence actually falls to about 10%. So about 28.6 million or so in the 2017 to March 2020 timeframe. And the reason for that is just because so many people have high blood pressure. We'll get into that when we talk about hypertension. I've talked about it already. I'm just, I feel like I'm hounding on this, because I am, because it's really important, and hopefully there's a question on it, so it'll be very rewarding for you in the test. But heart disease and stroke, they're the leading causes of death in the U.S., right? So about one in three deaths in 2019 were due to heart disease, stroke, and related circulatory diseases. The other thing to know about cardiovascular disease as a whole, because, you know, we're talking about sociodemographic variations, CVD is actually the greatest contributor to racial disparities in life expectancy. I think that's a really important fact, maybe not for your test, but just for life in general, as you go out into the world to become public health practitioners, or as you continue in the world in your public health spaces, just, I find this fact just profound. Anyway, there you go, there's the fact for you. A couple of other numbers for you, about 1.6 million people in the United States experience heart attack or stroke every year, and crazy expensive, right? Over 400 billion dollars, particularly in healthcare spending, it's about 12 percent of our total health expenditures, which is more than any other major diagnostic group. Cardiovascular disease mortality comes from a variety of different cardiovascular disease processes, but here's this lovely pie graph so that you can see what the most prevalent diseases are in terms of mortality, so the number one, 41 percent, is coronary heart disease, followed by stroke, around 17 percent, and then hypertension, in and of itself, about 11 percent. There's this big blue wedge, 17 percent, other, there's a variety, right, of cardiovascular disease processes that don't fit nicely into a bucket, and so hence the other bucket, but I think take home from here, coronary heart disease is by far and away the leading cause of cardiovascular disease mortality. What does this look like over time? So this is mortality trends over time, they're age-adjusted starting at 1999 and heading into 2017. I will say, I'm not showing it on this slide, but since the 1970s or so, cardiovascular disease mortality rates have really been on the decline, but what I am showing you on this slide, in recent years, those declines have really decelerated, so starting to flatten out, and in the last 10 years or so, it's just sort of stopped, right, and I'm showing you even here, there's a little bit of an increase even. So why the declines before and not now? There's a lot of thoughts on this in the public health community that focuses on these things. First is treatment. So there's this idea that maybe about half of the declines, half of the explanation of the declines early on were due to improved treatments. Lots of primary prevention, lots of secondary prevention after events, lots of acute treatment of events like MI or treatments that we were better implementing and employing for heart failure. The other piece of it was risk factor change, so better control of dyslipidemia, so lower cholesterol, better control of hypertension, we're lowering people's blood pressure, decreased smoking prevalence, I've already showed you that graph, decreased physical inactivity, I showed you that people are slowly increasing their physical activity and meeting guidelines, but some of that has stalled, right, and so we're also seeing stalls in cardiovascular disease mortality. So let's take a look at this by socio-demographics. You're going to be seeing a lot of slides just like this from me today, lots of bars, lots of numbers, lots of colors. I've tried to make the colors consistent, so age is always red, and race and ethnicity is always that lime green color, and sex is always going to be that light blue color, but I just want to flag for you, as you see these graphs over and over, you're going to be seeing varying y-axis scales. I did that partly because if everything was on the same scale, some of these graphs would have ridiculously small bars, because, and I want you to be able to see differences, and partly I did that because I want you to be able to look quickly at a graph and identify the patterns and broad strokes, right, like please don't memorize the stat, like if you have an eidetic memory, good for you. The rest of us can't memorize every single one of these ridiculous little numbers. What I want you to do is step back from it, look at it as a picture, and identify where the patterns are and where the differences are in those patterns. Okay, so looking at patterns and trends for CVD as a whole. So again, starting with a definition, CVD here for this slide includes coronary heart disease, heart failure, stroke, and hypertension. So that same 48.6%, about 50% of the U.S. population having CVD of some kind. So we see men higher than women, prevalence increases with age, we see some increased prevalence among non-Hispanic Black adults, particularly among women for cardiovascular disease as a whole. So keep those in mind as we start talking about specific cardiovascular disease processes, look for what's different for the rest. I also want to note, it's not on this slide, but I think a nugget for you to sort of jam in your brain, there are also disparities in cardiovascular disease prevalence by income. So for example, hypertension, dyslipidemia, stroke, more common among individuals with lower incomes. Let's take a look at CVD prevalence by state. So we see some variations here, we see that similar hotspot that I tried to attune you to in the tobacco map in that southeast area. Again, you're going to see this particular pattern, this particular geographic pattern over and over and over. So pay attention to when it's not this, because sometimes it's easy to remember the exceptions rather than the usual pattern. Shifting to cardiovascular disease mortality, so this definition is actually a little bit different than the prevalence definition, because this definition with mortality, I was able to include peripheral arterial disease, PAD, and congenital heart disease. So just clue in there, it's a little bit different of a definition. So again, men more than women, and then seeing a bit of an increase in non-Hispanic Black populations. This is what cardiovascular disease mortality looks like by age. So again, mortality increasing, generally, with age. And this is what it looks like geographically. And so no surprise, the mortality very geographic variations look a lot like the prevalence geographic variations. That is not always the case. So we're going to see some instances in the cancer section where prevalence and mortality look a little bit different geographically. But for now, it makes a lot of sense. Mortality and prevalence look very similar in cardiovascular disease. Taking a look at cardiovascular disease risk factors. So there are a lot of them, right? I probably didn't get them all. These are the key ones. These are the ones that I think would be good to know. So we know that hypertension and dyslipidemia are risk factors for cardiovascular disease. They are also disease entities in and of themselves. And so I highlighted them in yellow because clearly they're not risk factors for themselves, and they're not risk factors for each other. So hence, the yellow highlight. Diabetes as well, overweight and obesity, diabetes as well, overweight and obesity, unhealthy diets, particularly those high in sodium or saturated fat, trans fat or cholesterol. Lack of physical activity is a risk factor for cardiovascular disease. Smoking and secondhand smoke exposure are risk factors for heart disease and for stroke. They do potentially work synergistically with hypertension and with dyslipidemia in the development of cardiovascular disease, but here's the flag. Smoking and secondhand smoke exposure are not in and of themselves risk factors for the development of hypertension or of dyslipidemia. And I'll flag that again for you when we talk about hypertension and dyslipidemia specifically. Excessive alcohol use, age, and family history. Now, you're going to see this risk factor slide a lot while we talk about cardiovascular disease. Again, I'm presenting this as a study aid to help cue you into some things that are different for specific disease entities. So you're going to see this slide a number of times with some small modifications to help with memory cues. I do think that when we're talking about cardiovascular disease risk factors, it's important that we contextualize. So here are the big modifiable ones, the big modifiable risk factors all together on the same slide so that we can compare their prevalence side by side. So I do want to note for you that these numbers that I'm showing you here may be slightly different from prevalence numbers elsewhere in our discussion today because of the differences between the slides in year, in age group. This is adults only. Sometimes I present both adults and youth. And in definitions. So here we're looking at physical inactivity, not meeting physical activity guidelines. So don't get thrown by the difference in numbers. And please just don't memorize the numbers all in all together. Again, broad strokes, high-level patterns. So a couple of specific things I think to focus on. First, hypertension is the most prevalent risk factor for cardiovascular disease. About half the population, adult population, has high blood pressure. That's followed closely by obesity. And then about a quarter of adults have high cholesterol. About a quarter are physically inactive. So just now you have sort of a general sense of what's the most prevalent. If you got a question about something about where would you target your public health activities more if you were going to have the most profound impact on cardiovascular disease factors, which risk factor are you going to focus on? Now you have some idea of what the prevalence looks like. And you might be able to thoughtfully answer that question. If you pull all of that together in terms of risk factors, it's estimated that about half of U.S. adults have at least one of these three key risk factors, high blood pressure, dyslipidemia, or cigarette smoking. I will flag, though, that this is old data. This estimate was calculated before the change to the 2017 hypertension guidelines, which effectively brought our hypertension prevalence to 50% of the U.S. population. So this number, this nearly half, have at least one, is probably a lot higher now. The point of this slide is that controlling hypertension, dyslipidemia, stopping smoking, controlling these modifiable risk factors could reduce a person's risk of heart attack or stroke by up to 80%. So these are some of the really key levers that we have in terms of prevention. And so we need to think about risk factor mitigation, right? How do we mitigate those modifiable risk factors? So sodium reduction, certainly taking physical inactivity and turning it into physical activity, maintenance of healthy weight, limitation of alcohol use, avoidance of cigarette smoke, either primary cigarette smoke where you're smoking a cigarette or secondary exposure, stress reduction, medication adherence, and then monitoring and medical management of risk factors, like medical management of hypertension and control of dyslipidemia and control of blood glucose. Okay, so that's our overview, cardiovascular disease in broad strokes. Now let's focus down on the specific disease processes, and we'll start with heart disease. Remember, we're going to talk about heart disease globally, and then we're going to talk about coronary heart disease, and we're going to talk about MI, and we're going to talk about heart failure. So heart disease as a whole, we unfortunately do not have a great way to measure the prevalence of all-cause heart disease. The most recent estimate that I could find was 2018 data, which estimated about 12% of U.S. adults had heart disease. That was inclusive of coronary heart disease, MI, angina, and then this sort of nebulous, any other heart condition or disease, which was on a survey. Somebody decided that nebulous question wasn't great, and so we don't now, and took it away, and so now we don't have a great way of asking or estimating the prevalence of all-cause heart disease, which, okay. But we do have this really good handle on mortality, right, because we know that heart disease is the leading cause of death in the United States. About one in four deaths in 2019 was from heart disease specifically. We also know it's fairly common. We also know it's quite costly. I'll let you read the number there. Bottom line, heart disease is common. It's costly. It's deadly. Let's take a look at sociodemographic variations. so again, men higher than women. In fact, men are nearly twice as likely as women to die from heart disease, and that mortality rate difference between men and women has really persisted over time. Also flagging for you this higher rate of mortality in non-Hispanic Black populations. And variations by age, so similar to overall cardiovascular disease, the mortality rate of heart disease increases with increasing age. Geographic variability, this looks very much like the CVD mortality heat map that I showed you earlier, which should be no surprise, because why? Well, because I showed you that lovely pie graph that showed that coronary heart disease was the primary form of cardiovascular disease death, right? So the heat map should look fairly similar, and it does. This map is a little bit different than others, but I thought it was super interesting, so I threw it in with the rest of them. Take it or leave it, I just, I thought it was really interesting. So what we're looking at here is the percent change in heart disease mortality by state between 2011 and 2019. So blue states, the dark blue states, is where we're seeing decreases in heart disease mortality. The white states, there's 24 of those, is where we've seen no change in mortality rate. And then in one state, in Arkansas, heart disease mortality rate has actually increased. But so a couple of things, like there's some good stuff happening, right? I mean, the dark blue, the light blue states, we're seeing decreases. That's great news, right? I just, it was a little bit of a public health happy slide for me, so I thought I'd share it. I want to talk more specifically about coronary heart disease, right? So heart disease, and then coronary heart disease, and then MI. So coronary heart disease next. Remember, and I just said it again, but, and I'm probably harping on this too much, but I think it's important, that pie chart that we visited just a bit ago, coronary heart disease causes the majority of cardiovascular disease deaths. It's also the most common type of heart disease, so that makes sense. About 7% of U.S. adults over the age of 20 have coronary heart disease. We know that it causes a fair number of deaths every year. Looking at it by sociodemographics, so again, men more than women, increases with age. Interestingly, this breakdown, you know, we had been seeing in heart disease overall and in cardiovascular disease overall, these increases in prevalence among the non-Hispanic Black populations, which are not reflected here. The other thing that I'm not showing you here is that coronary heart disease prevalence increases as income decreases, so it's highest among individuals that live below the poverty level. And then the other thing that I'll mention, a little nugget that's not on this slide, is that the incidence of coronary heart disease in women actually lags behind men by about 10 years, 20 years for serious events like MI or sudden death. So men more than women, but there's some lag in age too. Okay, by state variation, so this is prevalence of coronary heart disease. Again, this heat map should look fairly familiar by this point, this geographic pattern. And then flipping to coronary heart disease mortality and sociodemographic breakdown, so men much higher than women. And now when we're looking at mortality, you can see that distinction or that disparity that's between non-Hispanic Black populations and other race and ethnicity groups is starting to peak up a little bit. Looking at variations by age, again, increases with age, so not much different there. And then here's the heat map, super different, right? Kind of odd that the mortality heat map is so very distinct from the prevalence heat map. Just flagging for awareness, something to keep note of. Moving to myocardial infarction, which of course is a common outcome of coronary heart disease. We know that about 9.3-ish million adults have ever had an MI, and that's self-report. We know that every year about 800,000 people in the U.S. will have a myocardial infarction. We know of those, one in four is a repeat MI, and we also know that one in five of those is a silent MI. About 15% of people who have had or who have a myocardial infarction will die of it, and there's a large number of deaths caused specifically by MI. And then we also know that by the number of deaths caused specifically by MI every year. Looking at the breakdown by sociodemographics, again, similar patterns that we've been seeing already, right? Men more than women, increases with age, and then you can see the differences, which aren't, you know, not huge, right, between the racial and ethnic groups. This is MI prevalence by state. Again, heat map looks awfully familiar at this point, sort of back to that typical pattern that we've been seeing. Know that this is self-reported data as well. Folks are asked if you've ever had a heart attack, and so this is the self-report data. Looking at myocardial infarction mortality by sociodemographics, again, I mean, same patterns, right? Men more than women, some slight variation in between the racial and ethnic groups. I do want to flag for you, though, even though this sort of men more than women, there's also a different measure with respect to MI prevalence. So, with respect to death, and that's looking at death one year post-MI, which actually is higher in women than it is in men. So, acute death with MI, higher in men, but when you're looking at the year post-MI, the mortality rate in women is higher than in men. By age, similar pattern, nothing surprising or new here, but just I wanted you to have the information to see it. And then this was what it looks like geographically. This is myocardial infarction mortality. And so, similar, right? The heat map is similar. We see this hot spot here, but some differences as well. Okay, this is our last deep dive for heart disease processes. This is heart failure. Again, the message here is common, costly, deadly. We know that about 6.7 million U.S. adults report having heart failure. We know that the average incidence is about a million a year, so a million new cases of heart failure are diagnosed every year. We do know that the mortality is high. About half of people who develop heart failure will die within five years of their diagnosis, and it's quite costly as well. Looking at it by sociodemographic factors, so men, a little bit higher than women, right? Definitely increases with age in women. Men, I don't even know what to say about that. It's interesting to me that the 60 to 79-year-olds have similar prevalence of heart failure than the 80-plus males. So, just flagging that difference. And then you can see the race and ethnicity breakdown over in the green bars. Looking at mortality of heart failure by sociodemographics, again, men over women, and then you can see, just let me go back. So, here's the prevalence, right, where we're seeing some difference and increase in prevalence in non-Hispanic Black populations. Here, that difference is reflected in higher mortality rates as well. And then this is heart failure mortality by age, again, increases with increasing age. Here's the map. So, heat map looks similar, but it's a little bit different. So, so heat map looks similar, not 100%, but similar, you know, enough that the gestalt is there's, you know, that hot spot where it typically is. Okay, and so then risk factors for heart disease. I told you that this slide will show up again, and in fact, it has. It is exactly the same as before, except without the yellow highlights, because we know that hypertension and dyslipidemia are both risk factors for heart disease, as is everything else that we've already talked about. Repetition is our memory friend, and I would flag for you if there was something different, just know risk factors for heart disease are very similar as the risk factors for cardiovascular disease as a whole. All right, hey, look, we got through heart disease. Excellent. Let's talk about cerebrovascular disease now, which is another form of cardiovascular disease, but of course, affecting the vessels of the brain, and so we're talking about stroke. So stroke, also common. About 3% of U.S. adults report having ever had a stroke. That's about 9.5 million people in our country. Stroke is the fifth leading cause of death in 2019, and is typically around the fifth leading cause. Every year, almost 800,000 people have a stroke. One in four of those is repeat. The other thing that I think is important for level setting is that vast majority of strokes are ischemic, about 87% of them. We know that about, you know, the remainder, of course, are hemorrhagic. 10% of those are intracranial, and 3% are subarachnoid, but really the take-home here is the vast majority of stroke is ischemic, and then of course, as with all cardiovascular disease, quite costly. This is what stroke mortality looks like over time and by race and ethnicity groups. We have talked a bit about these trends already because I showed it to you on the previous slide when we were talking about overall cardiovascular disease, but I do think it's worthwhile that we emphasize this stall out, right, that we're seeing these decreases in mortality rates for CVD. For stroke, we actually saw an increase in 2020 after declines between 2000 and 2010, stalls between 2013 and 2019, and some uptick in 2020. So we are just moving in the wrong direction here. This is what it looks like by sociodemographics. Now, I'm going to pause and say, look, there's a difference in the pattern that we've been seeing this whole time. Now we're seeing stroke prevalence in women is greater than in men, so different than the previous cardiovascular disease processes that we've talked about. And in fact, the lifetime risk of stroke is higher in women than in men. The lifetime risk in women is about one in five, lifetime risk in men is about one in six. Folks think that that may be related to living longer because stroke, as you can see, increases substantially with age. The other thing that I think is notable here is that there is a much higher prevalence in non-Hispanic Black adults in comparison to other groups. I haven't shown you on this, but I'll give you this nugget. The risk of first stroke is about twice as high in non-Hispanic Black adults as in non-Hispanic white adults. And I also haven't shown you here, but prevalence of stroke does increase as income decreases, so stroke prevalence is highest among individuals who live below the poverty line. This is what it looks geographically, so a little bit different, right? This geographic variation for stroke, some people call this the stroke belt, and so just, you know, flagging that for your attention that it looks somewhat different than the other cardiovascular disease processes that we've looked at, although the hotspot is similar, it's not quite the same. Looking at stroke mortality by sociodemographics, so similar between men and women, maybe a little bit higher in men, I don't know if that's statistically significant, it's not that much different, but certainly we see a much higher mortality rate in non-Hispanic Black adults than other race and ethnic groups. And this is what it looks like by age, so similar pattern as before. And then this is what stroke mortality looks like geographically, and so you can see that sort of similar pattern that we saw with the prevalence map, that stroke belt, as it were. Okay, so risk factors for stroke, golly, this should look awfully familiar to you at this point. Repetition is our memory friend, so this is the same slide, no changes, and so every one of these is a risk factor for stroke, but note that it is only part one, because there are more risk factors for stroke, there are some that are unique to stroke, and so I've listed those here. So having a history of a previous stroke, or a TIA, having a history of heart disease, so things like AFib, or carotid stenosis, or heart failure, sickle cell disease is a risk factor for stroke, and then these last two, pregnancy and postpartum, and then estrogen use, are related to clot risk for hypercoagulability. Okay, so that's stroke, let's talk about peripheral arterial disease, or PAD. So PAD, like I said, it's hard to pin down, the national prevalence is hard to pin down, and that has a lot to do with how we measure PAD, how PAD is diagnosed, and so our surveillance systems just, we don't have a really good grapple on it. The most contemporary estimate that I have seen for PAD prevalence in our country is based on a pooled data set from seven cohorts. Those seven cohorts spanned between 1970 and the 2000s, and that estimate is what I've shown you here, that 5.8%, but I have also seen as high as 10.7%, so sort of variable, but somewhere between 5 and 11%, 6 and 11%. We do know, we have a better sense of mortality, so we know that mortality every year, there's about 12,000 or so deaths. We also know that there's quite a number of people who have peripheral arterial disease with no limb symptoms, so about 20 to 34% of people with an ankle brachial index of less than 0.9, which of course is diagnostic, have no limb symptoms, but do have functional limitation, so that's maybe one of the reasons why we have sort of a hard time getting our finger on prevalence. We also know that PAD is associated with increased risk of a variety of things, including other cardiovascular disease, like MI and stroke, and also increased risk for amputation, and then of course we've already talked about PAD-related death. Because prevalence is a bit hard to pin down, I'm going to be honest with you, I had a really hard time trying to find comparable data to give you some socio-demographic sense of what's happening, and I just could not find anything better than this. I tried really hard to find you an easy-to- read prevalence variation slide. I'm sorry, this is the best that I could find. Again, this data is actually from that pooled seven-cohort study data that I was talking about. So here we have variations by age and race among males. I'm going to show you females in the next slide. Note, though, that the prevalence in males tends to be higher after about age 60, right? So that's important. The other thing, the strange thing about this data is the race-ethnicity categories here are a bit odd. I think that's based on a combination, because it's a combination of cohort studies that had varying definitions. But all of those caveats to say what's the big take-home here? First, risk increases with age, right, which is similar for other cardiovascular diseases. And the second really big take-home is that African-American men are at considerably higher risk than anybody else, so something to really take note of. This is what it looks like among U.S. females. So same take-homes, prevalence increases with age. African-American women are at higher risk, and also American Indian women, much higher risk than others. That's that last sort of blue-ish bar in the series. And then the other thing to note is that because prevalence is really hard to pin down, I just couldn't find anything in terms of variations by geography or trends over time. So this is unfortunately as good as I could find. We have better data for mortality. So here we have some sociodemographic breakdowns for PAD mortality. You can see men a little bit higher than women, and then this makes sense based on what we were just seeing with prevalence, higher mortality in non-Hispanic Black populations. I don't say that it makes sense, like, socially. It makes sense because of the previous data, just for clarification. This is what it looks like by age. So mortality increases with age. And then geographically, this is what mortality looks like in terms of geographic breakdown. And here you can even see, like, some of the data is just unreliable or suppressed because it's hard to get a handle on. But this is what that geographic breakdown looks like. And then we do have some mortality trends. So bottom line here, there's some decrease over time. I do, just in the interest of full transparency, want to flag a big old caveat here. The definition The definition of PAD mortality for these graphs is different than the definition for the prevalence estimates or the mortality estimates that I was just showing you. Because these graphs, their definition of PAD included aortic and renal artery disease, whereas what I was showing you before did not. So the estimates here are going to be higher. Again, don't focus on the raw numbers. Don't focus on the core numbers. Just focus on the trends. This is a trend slide. Focus on that. Bottom line, some downward trends for just about everybody. Things are stalling, as we are seeing with cardiovascular disease generally. Risk factors, a little bit different, right? So this is that same slide, but now I have grayed out the risk factors that don't really apply. So excessive alcohol use and secondhand smoke don't really apply here. A couple other changes. We've gone from obesity and overweight to obesity specifically, because overweight is not necessarily associated with PAD in the literature. And then this yellow highlight to highlight the change in what the diet issues are. So I'll try to make sure to show you and point out what the changes are on these slides. While we're here, I want to point out the strongest of all of these risk factors is actually cigarette smoking. Odds ratios for cigarette smoking and PAD range from like 1.3 to 5.4-ish, so one of the bigger ones. And then there's a handful of other risk factors that I'm not showing you on this slide, but I will just say, and you can jot them down. So other risk factors include chronic kidney disease, clotting disorders like thrombocytosis, fibromuscular dysplasia, preeclampsia, and gestational diabetes, other risk factors for PAD. Okay, so moving to hypertension. This may actually be the last year that I alert folks who take this course to this, because I think we've just about finished incorporating the 2017 hypertension guidelines into public health surveillance. But bottom line is, you know, in 2017, there was this huge shift, right, from the JNC7 classification for hypertension to the 2017 hypertension guidelines. And public health definitions took a little bit to catch up with these newer guidelines and newer cutoffs. And I imagine the questions on the test took a little bit to catch up too. So I've been presenting this slide for a while, but I think this is probably, you know, at this point, all the epi data that I've seen uses this 2017 definition now. I don't think I've seen JNC7 for a long time. Some folks have even gone so far as to recalculate all the trends several years back with this new definition, so that we can all be on the same page with the same definition, which is great, right? But at this point, I think it's pretty well incorporated. All the data that I'm going to present to you today is based on this 2017 definition. I'll flag for you if it's not, but just these are the cutoffs now. These are the definitions we're using. Okay, so all these numbers, again, based on a definition of greater than 130 over 80, or self-reported taking medication to lower blood pressure as the definition of hypertension. So with that definition, about half of US adults over the age of 20 have hypertension. That's about 46.7%, about half. We know that nearly 40% of US adults with hypertension don't know it. And we also know that only about a quarter of people who have hypertension have their blood pressure under control. So really important in terms of risk factor mitigation for the rest of our cardiovascular disease processes. We do know that about eight in 10, between 70 to 85% of US adults will develop, or Americans, I guess, will develop hypertension in their lifetime, and then super expensive. This is what it looks over time. So this is one of those places where, one of those examples of public health folks going back in time and recalculating all the prevalence based on the new 2017 definitions. So all of this is the 2017 definition. And so we're seeing some patterns here with this increase, right? And every time I show this slide, people say, well, that increases because of the different definition in 2017. But no, because all of this is related to the definition of hypertension is greater than 130 over 80, or report of treatment. So that increase is probably real. Unfortunately, I don't have any newer data to show you, but again, broad strokes, broad trends, just sort of know the general gestalt of things that trends have been going generally in the wrong direction here. This is what it looks like broken down by sociodemographic. So again, men more than women, increasing as age increases. And then some differences in the non-Hispanic black adult populations have a higher prevalence than others. This is what it looks like geographically. So that hotspot that we've been looking at this whole time, still there and there for hypertension as well. Risk factors for hypertension. So again, same slide of risk factors, but grade out the things that don't apply. So the things that I've removed are hypertension, dyslipidemia, and smoking. Smoking does have a transient impact on increasing blood pressure, but it is not a risk factor for chronic hypertension. So don't get caught by that question. If it exists, I'm just guessing. I've also changed here in yellow, the diet nuance. So here the dietary risk factor is too much sodium, too little potassium. And then here's a little nugget you might want to hang on to. 90% of Americans consume too much sodium. So not shown, maybe write it down. We've talked a little bit about under-management of hypertension, right? Like a quarter don't, only a quarter have their blood pressure under control. But I think this is an interesting peek into one of the reasons for that. This is looking at pharmacotherapy adherence among Medicare beneficiaries. Basically 50% of adults with a blood pressure over 140, over 90, who should be taking antihypertensives aren't. Either their meds haven't been even prescribed or the meds aren't being taken as directed. And there's a lot of barriers, right, to medication adherence. Certainly cost is a huge component of that, but also sometimes medication regimens are complicated. Sometimes folks feel like they don't need the medications because they don't have any symptoms because hypertension generally doesn't. They're not getting their prescriptions filled or refilled. They may have side effects from their meds. So lots of different types of barriers. But I thought this was sort of an interesting peek into why that management may be lower than we want. And then I also want to talk about hypertension as a risk factor, right? We've talked about risk factors for hypertension, but hypertension is in and of itself a risk factor, both for cardiovascular disease and for death from cardiovascular disease. So important to keep that in mind. Okay, and so dyslipidemia, this is going to be our last piece of cardiovascular disease. We'll start with a definition. So similar to the hypertension clinical guidelines, cholesterol guidelines also went through a bit of a change back in 2018. This chart that I'm showing you here is largely based on that 2018 ACC and AHA guideline, except for total cholesterol. These numbers are based on the old guidelines. The reason I'm presenting that here is to give you an idea about the surveillance cutoffs that I'm going to show you soon in the surveillance data and why they are what they are. And that's because of the total cholesterol guidelines from before. So using that definition, we can look at prevalence either of total cholesterol over 200 or total cholesterol over 240. So if you look at total cholesterol of over 200, it's about 34, 35% of US adults who have dyslipidemia by that definition. If you look at total cholesterol by over 240, it's actually only about 10%. So a bit different there, depending on the definition that you're using. We also know that children have dyslipidemia, about 7% of kids aged six to 19 have a total cholesterol of over 200. And then HDL has been low, so about 17% of adults have an HDL less than ideal. Here, similar to hypertension, management of dyslipidemia leaves a lot to be desired. There's some work to do. Only about half of adults who could benefit from lipid-lowering medications are taking them. We know that only one in three adults who has a high LDL-C has that under control. This is what it looks like over time. Again, I don't have super updated data, so apologies for that. But again, still broad strokes and trends. So things are going, we're going in the right direction, I guess is what I'm trying to say. The prevalence of high total, so that's greater than 240, declined between 1999 to 2018. And the prevalence of low HDL also declined between 2007 and 2018. So going in the right direction, at least in that time. And again, apologies for not having the data, any further updated data. I looked, I just, I couldn't find it. So looking at high total cholesterol prevalence by sociodemographic. So now we're zeroing in on this over 240, right? So the 10% of US adults over the age of 20 who have a total cholesterol of over 240 and what that looks like. So here, men and women, similar, right? Is this statistically different? I don't know. Maybe, maybe not, but it's close. And then the breakdown by race and ethnicity, very different, right? Than what we've been seeing before. So again, pay attention to those things where the pattern is a bit different. I unfortunately don't have an age breakdown to show you either, but I do have a geographic breakdown. So again, this is, so this is actually self-reported, doctor diagnosed prevalence of high cholesterol. And you can see the heat map is similar to what we've been looking at prior. And here's that risk factor slide again, lots of yellow now. So we've taken away, of course, hypertension and dyslipidemia for obvious reasons. Smoking and excessive alcohol use are also gone, not associated in the literature at this point with dyslipidemia. But the lot of nuance changes here for you in yellow, just as memory cues, right? Like what does diabetes do? Oh, right, it lowers HDL and raises LDL. What's the impact of overweight and obesity raises triglycerides and LDL lowers HDL. When we're talking about diet, we're not talking about sodium anymore like we were for hypertension. We're talking about saturated and trans fats. When we're talking about family history, I think it's important to remember this example, the familial hypercholesterolemia. And then dyslipidemia is a disease process. There are risk factors for it, and it is in and of itself a risk factor as well, which we've seen in our previous cardiovascular disease slides. It increases the risk of heart disease and stroke. So, you know, keep that in mind as you're answering questions about dyslipidemia. Are you talking about it as a disease process? Are you talking about it as a risk factor? You know, what's the frame? Okay, so I'm gonna pause, guys. Okay, let's move on to respiratory disease. So we're gonna talk about two pulmonary disease processes. We're gonna talk about COPD, and then we're gonna talk about asthma. So let's start with chronic obstructive pulmonary disease, or COPD. COPD, of course, is defined as airflow limitation that's not fully reversible, right? So it includes chronic bronchitis. It includes emphysema. It has a little bit potential overlap with asthma, sort of depending on what you're doing. COPD is a kind of chronic lower respiratory disease. So when you look at our mortality data and you look at the causes of death, you'll see that number six in 2019, or in 2021, actually, number six was chronic lower respiratory disease. And so I think it's important to level set that when you're looking at that, COPD actually accounts for 97% of CLRD deaths. And so when we're talking about CLRD, we're talking about COPD and asthma and bronchiectasis, but really we're talking about COPD. The other thing I want to flag for you is that, you know, I found 2021 data. So I wanted to give you some more estimated updates in this section. CLRD in 2019 was the number four cause of death. And then, you know, we all know what happened in 2020 and 2021 in terms of causes of death. And so some of that shifted around. But I wanted to give you a flavor of what 2021 looks like for this section. And so I tried to use the 2021 data. So don't get thrown by that. We know that COPD is common, right? It's about six and a half or so percent of U.S. adults had diagnosed COPD in 2021. COPD is one of those things that's fairly underdiagnosed. So there's probably millions more on top of that that may have undiagnosed COPD. And as with everything that we've been talking about today with chronic disease, it's quite costly to patient care and other measures of economic impact. Now, I couldn't find a graph to share with you, but age-adjusted prevalence has been slowly declining since the 1990s. This graph is actually mortality, but just know that prevalence has been sort of declining over the 1990s. And I'm sorry for not having something to visually show you. But again, this is mortality. Mortality has been decreasing for men. Not so much women, right? We're seeing, interestingly, disparities, gaps, but not because we're doing better for both. It's just because we've been doing better for men, but not necessarily women. Overall, mortality rate has sort of remained similar over time, even since like the 1990s, although important to know that sort of the crude mortality rates, as opposed to age-adjusted, have been increasing a little bit. In 2021, overall, about 33 deaths per 100,000 persons for mortality, again, a little bit higher for men than women. This is what prevalence looks like by sociodemographics. So flag for you, right? Cardiovascular disease, we were talking a lot about, you know, the differences, aside from stroke, that men had higher prevalence and higher mortality rate than women. COPD, we flipped that on its head. So here we have women with higher prevalence than men. We have seen increases with COPD prevalence with age, and then marked differences by race and ethnicity. And I just want to flag that the disparities that you're seeing here in race and ethnicity are very similar to those that we see for cigarette smoking, which makes a lot of sense, because we know that about 80% of COPD deaths, although this is prevalence, but 80% of COPD deaths are related to cigarette smoking. And so we see here the highest prevalence of doctor-diagnosed COPD is among American Indian, Alaskan Native adults. There's also disparities by socioeconomic status with higher prevalence among those with lower household income. And there's disparities in population groups. I'm not showing it here, but there's disparities in population groups that live in rural areas. So prevalence and mortality are both higher among those living in rural areas compared to those living in urban areas. The other thing that I want to flag to you, because we're talking about prevalence versus mortality and men versus women. So here I'm showing you the prevalence of COPD is higher in women, but back a slide, oops, sorry. Back a slide. I was showing you that the mortality rate is actually higher in men, higher in men than it is in women. Why is that? There's some theories. Is this a diagnosis issue, right? Where women are seeking care and being diagnosed more than men and men are dying. Is it a treatment-seeking issue? Because this is doctor-diagnosed COPD. It's hard to suss out and probably not going to be on your test, but I just wanted to flag for you that difference in prevalence versus mortality by sex. This is what it looks like geographically. See that hotspot? That's the same hotspot that we've been looking at almost all the time we've had together so far. Not surprisingly, this looks an awful lot like the heat map for cigarette smoking, but we've already talked about why that might be. Risk factors for COPD. So cigarette smoking is the biggest contributor of, is the biggest risk factor for COPD in the United States. But let me caveat all of that to say so that you don't miss this on the test. It is not the only one, right? And I think that's an important level set. About one in four US adults that are diagnosed with COPD never smoked. So an important distinction. The other thing that I'll flag for you is that the causes of COPD in the United States are a bit different than the causes of COPD in the developing world and in developing countries. So indoor air pollutants are actually have a much larger role. Cigarette smoking is still very important and it's still a huge contributor, but indoor air pollutants play a bigger role in those spaces. We also know that there's some occupational air pollutant exposures here and elsewhere that are risk factors for COPD. And of course, this is like step one material, right? Alpha-1 antitrypsin deficiency. You've probably had at least four boards questions in your career at this point about this particular genetic disorder. So just don't let that trip you up on this test. And then there are some evidence linking respiratory infections to development of COPD like tuberculosis as one potential risk factor. Okay, so that's COPD. Asthma, shifting gears a little bit. So asthma is not uncommon, right? About 8%, 7.8%, 8% including children have asthma in the US. Asthma does cause death about 4,000 deaths in 2019 with 3,500 deaths in 2019, including almost 200 kids. There's a lot of healthcare use that's associated with asthma. Millions of emergency department visits, millions more physician visits and a fair number of hospitalizations. And then of course the common theme, right? It's quite costly to our healthcare system and to society generally. And of course, controlling asthma and controlling asthma exacerbations can really help reduce some of this burden. This is what the prevalence looks like over time. So here I'm showing you 2001 to 2020. Bottom line here is there's not been a whole lot of change, right? It's just, it's sort of stable where it is. And this is what the prevalence looks like by a socio-demographic breakdown. I think, you know, the thing that I would say from a take-home standpoint is that these variations are different than almost anything we've seen today, right? With maybe the exception of COPD. So first we're seeing higher prevalence among those who are younger, right? There's much higher prevalence than other disease processes that we've looked at today already. And then the second is that the prevalence is higher in females as well. There's also a really big difference in race and ethnicity and the non-Hispanic black persons have much higher rates, excuse me, much higher prevalence of asthma than other race and ethnicities. And then the associations with household income aren't much different than what we've been seeing with other disease processes with increasing prevalence with lower household income. Just to show you some trends over time by race and ethnicity I thought that this was worth sharing. Ultimately, bottom line here is there's high prevalence in non-Hispanic black individuals and that's been persistent over time. There's some general stability over time like we saw with overall prevalence, but I just thought, you know, sometimes looking at the data in a little bit of a different way can help make it stick in your brain in a different way or in a better way. So similar things to see, just maybe this one will stick for you. This is what the geographic variation looks like. Really different, right? Than what we've been seeing before. There's not like a huge clear geographic pattern. Maybe there's some clustering in the Northeast, but I'm just flagging this is very different, right? Than cardiovascular disease or the risk factors that we had been looking at prior. This is asthma mortality by socio-demographics. Again, as prevalence is higher in females, mortality is also higher in females. It's also, I think, important to flag for you that mortality is higher in adults than in children. And then huge disparity, huge disparity in non-Hispanic Black populations in terms of asthma mortality. That one, I mean, I think the graph speaks for itself, but maybe know that one. I was writing test questions, which I don't, and I'm not, but if I was going to guess, that's a really important disparity to know. This is what mortality looks like. And you can see here, you know, it's kind of stable, and then suddenly it's increasing in 2020, maybe. But there's some increasing there even before 2020, so is there something there there? I'm not the asthma expert. I'm sure my asthma colleagues would just be horrified by what's coming out of my mouth right now, but you're just trying to take a test. You're not trying to be an SME in asthma, and so take the graph as you need to help answer the questions. But just, you know, the prevalence has been stable, and the mortality is maybe changing a little bit. These are risk factors for development of asthma. In the next slide, I'm going to show you about factors for exacerbation of asthma. So this is for asthma incidents. There is an association with ATOP, right, a predisposition to develop IgE in response to environmental antigens, so there's that triad that we all know and have been tested on a thousand times, that, you know, allergies, eczema, and asthma. There's a family inheritance component to all of that. I think, though, you know, we spend a lot of time talking about ATP. It's really important, but not all asthma is atopic, and not all asthma is allergic. It's one of many risk factors, right? So there is some, there's a great IOM report. It's super old now, but I pulled this information out of it because it's still really, I think, helpful to look at where the causal relationship evidence is, where this sort of association evidence is. So causal relationship between house dust mites and development of asthma. There's an association between secondhand tobacco smoke exposure and preschool-aged kids and the development of asthma later in life, and then there's some suggestive evidence around, like, cockroach exposure for preschoolers and RSV. These are risk factors for asthma exacerbation. So again, causal association-based evidence and then limited or suggestive evidence of association. So causal relationships, there's some animal exposures, there's active tobacco smoking in adults, and then secondhand tobacco smoke exposure in children, causal for exacerbation. Evidence of association, not necessarily causality, you know, their evidence is still developing. Again, some animal exposures, some microbial exposures, and then NO2. Limited or suggestive evidence, again, some animal exposures, some microbial exposures, getting the general pattern here, but, you know, pick a few, remember them, look at them a few times, and when the multiple choice question comes, you'll probably be able to at least eliminate the wrong answers, or at least some of them. So not something to memorize straight out with all of the bullet points, but have that general sentence, pick a few to know. Okay, so that's pulmonary, right? Wow, that was a lot faster than cardiovascular disease. I'm always a little bit surprised by that. That's all good. Let's shift now to metabolic disease. We're going to talk now about, in this section, we're going to talk about obesity, we're going to talk about diabetes, and we're going to talk about metabolic syndrome. So starting with obesity, again, always good to start with a definition, so here it is. This definition hasn't changed forever, and I'm not even going to talk to you about it because you all know this like the back of your hand, because we've all been tested on this ad nauseum, so, but here it is in case you need it to refresh your memory, because sometimes I do. When we're talking about the public health impact of obesity, you know, we talk about obesity, and then we talk about a combination of overweight and obesity together. So when we're measuring obesity, we're measuring BMI, it's about 42% of U.S. adults now have a BMI over over 30, and so are classified as having obesity. And then when you look at overweight and obesity together, it's actually like 72% of the population of U.S. adults, so more than two in three. And so these two numbers are important to know, important to know what the difference is, important to be able to distinguish them. So 42% obesity, 72% overweight and obesity together. In kids, it's about 20%, so nearly one in five, and that's kids aged two to 19, because we start measuring BMI at the age of two. And then the other thing to know is the association between childhood overweight and obesity and adulthood overweight and obesity. So we know that preschool kids who have overweight or obesity are five times as likely as their normal weight peers to be overweight or have obesity as adults, so definitely a link there between them. And then same story as the rest of the chronic diseases we're talking about, it is extraordinarily expensive in terms of healthcare costs and other things. This is what it looks like over time. So this is obesity specifically, not that combination of overweight and obesity, but only obesity in adults and in kids, two to 19-year-olds. And you can see things have been trending up for the most part. And so here we are in this last data point, which I was showing you on the previous slide. It's about 42% of adults and about 20% of kids. This is what it looks like by age when we look at kids, because with kids, if you lift the hood a little bit and look by age group, things are a little bit different. There was a period of time when the two to five-year-olds were starting to decline, and then we've sort of reversed that a bit. The six to 11-year-olds and the 12 to 19-year-olds have been just increasing slowly. This is what adult obesity looks like by sociodemographic factors. So pretty similar, right, by sex, pretty similar by age group differences in race and ethnicity. If you actually break this down and bin it intersectionally so that you're looking at race and ethnicity and sex, then you're going to start seeing differences between males and females in specific race and ethnic groups. So for example, in non-Hispanic Black adults, women tend to have a higher prevalence than men. So just know that once you start doing some intersectional analysis, it's a little bit different. The other thing I think to note is this difference in non-Hispanic Asian populations, in particular with much lower rates of adult obesity. Also variations by sociodemographic factors. So there's some variation by income, some variation by education. Certainly there's a lower prevalence of obesity amongst those with higher education. But again, when you start doing this, when you start stratifying and looking intersectionally, this gets super complicated super fast. This is youth obesity, again, by sociodemographic factors. You know, boys and girls, very similar increases in prevalence with age, differences by race and ethnicity. I think there's also some association with socioeconomic status. So we know that about one in four low-income youth have obesity. And this is the heat map. This is what it looks like across the country in 2021. And so you can see, you know, the high rates of prevalence have a geographic pattern, but I think the take-home for me is that only D.C. is green, and all the other states, it's at least a quarter of the population that has obesity. It's a huge public health problem. And then talking about intersectionality a little bit, you know, when you start looking and binning things a little bit differently, we do see differences in state variations when we start looking at state variations by race and ethnicity. So I just think this is fascinating, and so wanted to include this here. It's probably not going to be on the test, but I just, it was so interesting that I couldn't help myself. And so here it is, and has some really interesting, like, hmm, what do we do in terms of interventions, given this information? Okay, I'll move on. It's just so interesting. Risk factors for obesity, there's lots of them, right? I mean, I think gone are the days where we're all attributing this, or the medical system is all attributing this as calories in and calories out. There's a lot going on here. There are a lot of different risk factors. Certainly diet and physical activity are huge players, but there are also, you know, issues with genetics. There's now associations with sleep. There's certain medications. There are medical conditions, right, like PCOS and Cushing's. There are community factors, societal level factors. There are emerging factors that we're learning more about, like chemical exposures and microbiome issues. I mean, I think, again, bottom line here is that the risk factors and the risk factor profile for adults with obesity is really complicated. And then obesity in and of itself is a risk factor, right? And so there are a variety of disease processes that have been associated with obesity. I'm showing you some of them here. This infographic is a bit old, and so there's certainly more than just these, but mental health, cardiovascular disease, diabetes, there are reproductive health effects, there are lung effects, there are liver effects, there are cancers that have been associated with obesity. This infographic only displays seven, but there are more now. There are 13 total cancers that have been associated with obesity so far, and I'm going to, because you can pause this recording and write them down, I'm going to say them so that you can write them down. The missing six from this infographic are meningioma, thyroid cancer, esophageal cancer, multiple myeloma, stomach cancer, and ovarian cancer. And so those are the six to add to these seven to make the total of 13 that are now associated in the literature with obesity. So bottom line, lots of organ systems impacted. Obesity is a huge risk factor for chronic disease and a variety of other processes. Big, big public health issue. All right, shifting to diabetes. So, of course, there's two types, right? We all know that. We all passed step one. There's type one, there's type two. I'm going to talk about both of them today, but you're going to see in just a second the type two constitutes a majority of the prevalence of diabetes in the United States. So we're going to talk about type two diabetes more than we're going to talk about them together, but just flagging that for you. So common, right, one in seven U.S. adults had diabetes in 2019. That's about 14.7, about 15 percent of the U.S. population who had diabetes in 2019. We do know that type two is the most common. Like I just said, 90 to 95 percent of adult diabetes is type two. We also know that it's very underdiagnosed. So about 23 percent of U.S. adults is estimated to have diabetes that's undiagnosed. That's about one in five. We also know that prediabetes is common. So about one in three U.S. adults had prediabetes in 2019. That is worse the older you get, and so nearly half of adults age 65 and older had prediabetes. We also know, of course, this is not just an adult disease. This is a youth disease as well, and so about 280,000 or so U.S. youth had diagnosed diabetes in 2019. I'll show you the breakdown in a little while of what that looks like in terms of type one versus type two. And then super expensive. So this is what it looks like over time. So this is now diagnosed diabetes, which like we just talked about, this is an underdiagnosed condition. And so these prevalence data look lower than what I was just talking about, and that is because this is only diagnosed diabetes. The prevalence of adults with diagnosed diabetes has more than doubled in the last 20 years. This graph is adults and kids. And I should also let you know that incidence trends are very similar to the prevalence trends that I'm showing you. This is diagnosed diabetes among adults now, looking at it by socio-demographics. So again, overall diagnosed diabetes is about 10 in this time frame. Men more than women, increases with age. There are some variation by race and ethnicity, and then some variation and association with socioeconomic status with adults who have less education having higher prevalence of diagnosed diabetes. The other thing that I wanted to flag for you, so this data is NHANES data, and NHANES does collect race and ethnicity for American Indian Alaska Native populations. There wasn't a sufficient sample in this time frame to be able to present that data here, but there are other surveillance systems in this similar time frame that do show high prevalence. We're continuing high prevalence in that population. I think that's all I have to say about the prevalence of diagnosed diabetes among adults. So let's take a look at the geographic distribution. So again, diagnosed diabetes, adults, this is self-reported diagnosed diabetes among adults, and you can see, you know, the hot spot is quite similar to what we've been seeing in the past, although it's a little bit different, but similar. And this is what that looks like over time. I just thought this was interesting to look at geographic variations over time. And so again, adult diagnosed diabetes, and you can see that the county level data just gets, you know, the prevalence is just increasing and increasing over time, and we see that hot spot in the southeast really coming. I mean, there it is. It's right there, and it worsens over time. This is what it looks like for youth. So this is older data. It is older data, but it is data for youth, and I wanted to show you this graph for a couple of different reasons. First, because I wanted to have some youth-specific data. I wanted you to be able to see that. In kids, we do make the distinction between type 1 and type 2. This makes sense, of course, with the natural history of the disease, and it's not the, like, 90 to 95 percent in adults is type 2. The second is I wanted to show you, the second reason I wanted to show you this graph is because I wanted to show you differences by race and ethnicity in kids, which you can see is very different, right, between type 1 and type 2 diabetes. The trends here are less important for you to pay attention to because they're so old, but the general idea is that type 1 incidence is relatively stable. Type 2 incidence is generally rising. And then risk factors for type 2 diabetes, you know, these are all, we've talked about a lot of them already, but here's a nice review. So we know that overweight and obesity is a risk factor for type 2 diabetes. There's association with lack of physical activity. There are family history and age-related factors. PCOS is, in and of itself, a risk factor for the development of type 2 diabetes. So is the history, so is a personal history of gestational diabetes. And then, of course, prediabetes is a risk factor for the development of diabetes. We all know that. Cigarette smoking is also a risk factor for type 2 diabetes. It has been causally associated with the development of type 2 diabetes. This one I think people are less familiar with, so don't get caught on that if that ends up being a question on your test. And then diabetes is not only a disease process, it is also a risk factor. So it increases the risk for a variety of different things, including diabetic retinopathy. There are eye effects. There are cardiovascular effects with higher risk for coronary heart disease and stroke. We know that there's a high risk for mortality, right? The risk of premature death for adults who have diabetes is 60% higher than adults who don't. It is the seventh leading cause of death, although I apologize, I don't remember what year that was. Double check your 2019 chart, but it is up there in terms of causes of death. So control of risk factors is really important, right? And so we do some risk mitigation. We know that weight loss through healthy eating and active living, physical activity, can really cut the risk of type 2 diabetes in half. 5% to 7% weight loss means a 58% lower incidence of type 2 diabetes if it hasn't developed. So lifestyle changes are important. Medical management is also important. And so all of these things in terms of risk mitigation are key. Moving to metabolic syndrome. So this is the definition. This is the NIH definition of metabolic syndrome. So you have to have a fasting plasma glucose over 100. There are some HDL cutoffs different between men and women. Triglycerides over 150. Hypertension based on the 2017 guidelines. And waist circumference different for men and women. So of these five risk factors, you need to have three of them present or being treated in order to be diagnosed with metabolic syndrome. And with this definition, we know that about a third of U.S. adults have metabolic syndrome in 2011 to 2016. And the presence and, excuse me, the prevalence of metabolic syndrome varies by sociodemographics. So not a ton of variation between men and women, but certainly increasing prevalence with age and some variations by race and ethnicity. Risk factors for metabolic syndrome should not be surprising given the definition of metabolic syndrome. So obesity, especially abdominal obesity, history of diabetes, lack of physical activity. There are some genetic factors that play into this. Insulin resistance. And then there are some medications, particularly those that affect weight, glucose, or lipid profile. So there are some things that you need to be aware of. And then there's metabolic syndrome, as we've been talking about, is also a risk factor for other things, right? So metabolic syndrome is a risk factor for cardiovascular disease, specifically coronary heart disease and stroke, for type 2 diabetes, for chronic kidney disease, for some types of cancer. And then there's this grouping of disease processes that it's still unclear if these processes are risk factors for metabolic syndrome, or if metabolic syndrome is a risk factor for them. So it's unclear sort of what the direction of association is. Nonetheless, non-alcoholic fatty liver disease, PCOS, gallstones, and obstructive sleep apnea, all associated with metabolic syndrome. It's just unclear sort of what the direction is, the direction of association is. Okay, so let's tackle cancer. So I've split the cancer section up into three parts, mostly to make it easier for you to navigate the slide deck when you're studying, but also in part to keep everybody's spirits up as we tackle this extremely large section of the content. I will note that when I first put together the structure of this lecture years ago, the board content outline was very specific about what types of cancers that you were supposed to be familiar with. Now the content outline is a lot less specific, honestly, but nonetheless, I decided to keep in all the cancers that used to be very specifically listed in the outline, which is one of the reasons this section on cancer is so very long. But bear with me, though. The slides are patterned to be very similar to each other for each cancer type. I did that on purpose to help you with your studying. Again, the recommendation that I have is to really get a sense of general patterns, look for where the pattern's different, and that can help you remember the sort of nuggets that can be good test questions. You know, if I was in the business of writing those, which I'm not, which I've said before, but nonetheless, like, that's how I tend to like to study. So in this section, this part one, we're gonna talk about cancer generally, and then we're gonna talk about the top four cancers by incidence and mortality. So lung cancer, female breast cancer, prostate cancer, and then colorectal cancer. So let's talk about cancer as a whole to get us started. So we know, you know, I've showed you before, it's the second leading cause of death in the United States. It has been for a long time. And the incidence rate is quite high. So about more than 1.7 million new cases of cancer diagnosed in 2019. We know that, again, because it's the second leading cause of death, it's about one in five deaths in the US is cancer-related. And cancer all told has a five-year relative survival rate of about 66%. So the five-year relative survival estimate is basically the percentage of people who have cancer who will have not died from their cancer five years after their diagnosis. So that five-year relative survival rate, again, for cancer all told, is about 66%. Now, if you remember one thing from the whole cancer section, this slide should be the thing. So knowing what the top 10 cancers are, even frankly the top five cancers by incidence and the top cancers by mortality, and note that they're similar but different. So I would know this. I wanna flag for you that this list largely doesn't change over time. This is pretty, these top 10, and the order in which they show up has been pretty consistent. There's one exception in recent memory. In 2016, don't remember the year, it doesn't matter. But in 2016, the number 10 cause of cancer was thyroid cancer. It was surpassed by leukemias in 2017. But this list has otherwise largely unchanged for years. When you break this down, and I'm not gonna show this to you, so I'm gonna pause if you need to write it down. But when you break this down by sex, so female or male, then it changes a little bit, right? So for females, the incidence, the top five in incidence are female breast, and then lung, and then colorectal, and then uterine, and then thyroid. But for death among females, the top five are lung, just like it is for overall, and then female breast, and then colorectal, and then pancreas, and then ovary. For males, it's different, right? So the incidence, the top are prostate, then followed by lung, and then colorectal, and then bladder, and then melanoma. And for mortality, for death, the top are lung, just like it is for overall, and then followed by prostate, and then colorectal, and then pancreas, and then liver. So similar to overall, but somewhat different, just in case somebody tries to throw you through a loop and ask you about the top five cancers in women, or the top cause of cancer death in women, well, that's lung, and it is for men too. And anyway, so these are sort of nuances that I think are just important to flag for you, just in case. So you're gonna see a lot of these trend slides as we go through. Here, I'm showing you trends in incidence. Oh, by the way, I tried to color code all this. So incidence is always gonna be in blue, and mortality is always gonna be in orange. But so incidence here, trends over time. You can see from my fancy double-headed blue arrow that statistically no real changes between 2014 and 2018. So that double-headed arrow is meant to be a visual cue, no change. But like I said, you're gonna see a lot of these types of slides. And there's a couple of things I wanna point out to you just generally. So first, pay attention to the axis, because I've tried to make it so that you can actually see what's going on. So here, note that the axis starts at 300, not at zero. And also see that as we go in between slides that all are gonna look very similar, the scales are gonna change, right? And again, similar to what we talked about with the sociodemographic scales. And the reason for those changes is so that you can see what's going on, because if they were all the same scale, some of them you wouldn't be able to tell at all what's going on, because the incidence is so low. And some of them, things are just really high and so hard to see. The other thing that I wanna say while we're sitting on this slide is with respect to differences by sex. So in general, of course, all told, incidence has been stable over time. The same is the true for males. But females, it's been a little bit different. We've actually seen a very small uptick in cancer incidence in females between 2003 and 2018. So just flagging that for you just in case that comes up. Cancer incidence, of course, varies by sociodemographics. So this I'm showing by sex and by race and ethnicity. So all told, men have higher incidence of cancer than women, and then there are differences by race and ethnicity. Again, same note for these slides that are exploring sociodemographic factors. The scales are gonna change as we move through. Don't let that throw you off. Incidence, of course, variations by age. So typically for cancers, of course, all told here, but also in a lot of other cancers, cancer incidence increases with age, typically with a peak incidence around 80 or 85 and above. If there is something notably different from that, I will let you know and flag it for you as we go through. And then the same caveat and disclaimer, the scales here are gonna change as we go over time. So even though the slides and the graphs are going to look similar, don't compare them side by side because the scales are different. This is by cancer incidence by geography. So nice heat map. Really, when we're looking at cancer all in all together, there's not really a clear geographic pattern. Same disclaimer, I'm just gonna give these disclaimers once here in the beginning, and then we'll pattern through the cancer slides more quickly so that I can just have them all said at the same time. So the colors, again, scale is gonna change here. Colors are gonna be the same. So you're gonna see maps in blue for incidence, and you're gonna see maps in orange for mortality, and the blues are gonna be all the same, and the oranges are gonna be all the same, but the scales are gonna vary from, so dark blue is not the same on every slide. So again, don't compare different cancer type maps side by side in terms of like, oh, this one has more and this one has less, because it's not gonna work like that. What we're looking for here is geographic patterns of where incidence is higher or lower. So that's all I'm gonna say about that. So this is trends in mortality. So you can see that nice orange arrow, visual cue to show you that the mortality rates have been decreasing since 2001. And this is what it looks like, what mortality looks like by sex and by race and ethnicity. So similar to cancer incidence, cancer mortality is higher among males than females, and there are some variations by race and ethnicity as well. This is what mortality looks like by age, similar to incidence, increasing with age, and this again, cancer all told, and any changes and differences in this pattern as we walk through the different cancer types, I'll flag for you. This is what the geography looks like for cancer as a whole, little bit different, right, than incidence, which I think is interesting from a public health intervention standpoint, but certainly we're seeing a geographic pattern with a hotspot in mortality. Okay, so that's cancer as a whole. Let's dive into the specifics of each cancer type. And like I said, I'm gonna cover in this section, we're gonna talk about the top four in terms of incidence. So we'll start with lung. I'm gonna say lung cancer. What I mean is cancers of the lung and bronchus because they come together. So just, you know, definitions are important, and so know what I mean instead of what I say. Lung cancer is the leading cause of cancer death in the United States for both men and women and all told. It is the number three cause of cancer though in terms of cancer incidence. The incidence is quite high though, over 200,000 new cases of lung cancer diagnosed in 2019. And the five-year relative survival rate isn't great. It's only 24%. In comparison, remember, to the five-year relative survival for all cancers is 66%. This is what the trends look like in terms of incidence and mortality. So we have been seeing a decrease in incidence over the last several years. We have been seeing a decrease in mortality over the last several years, very encouraging to see decreases in mortality for this particular illness. This is what incidence and mortality look like in terms of variations by sex and race and ethnicity. So men more than women for both incidence and mortality and variations by race and ethnicity as well. This is what it looks like, incidence looks like by age. So you can see there's a peak between 75 and 85 years of age, which is a little bit different, but not a huge difference from the typical age range. Not a huge difference from the typical pattern, which is continuous increase with age. And this is what mortality looks like by age. Again, very similar to incidence and the typical pattern. Geographically, this should not look very different from a lot of the heat maps that we've been looking at today. So it looks very similar, in fact, to the cigarette smoking prevalence map, which makes a lot of sense given that 90% of lung cancer death is linked to cigarette smoke. Risk factors for lung cancer. I just said cigarette smoking is related to 80 to 90% of lung cancer death. There are also other combustible tobacco products. And then secondhand smoke, we've already talked about in the risk factor section, but secondhand smoke does cause lung cancer. Radon is the second leading cause of lung cancer and is a really important risk factor to know about. And then there are a variety of other risk factors, right? So there's other substances like asbestos, diesel exhaust, some forms of silica and chromium, so occupational exposures. Family history of lung cancer is a risk factor, a personal history of lung cancer, and then radiation therapy to the chest as well. Okay, moving to breast cancer. So breast cancer, of course, also occurs in men, but in much smaller numbers. And so for the purposes of our discussion and for a lot of our surveillance systems, we focus on female breast cancer. So breast cancer is the number one cause of cancer in women. It is the second cause of cancer death in women. And the incidence rate is around 130 per 100,000. We know that the five-year relative survival rate is quite high, right? It's about 90%. And so, which is interesting, right? Number one cause of cancer and the number two cause of cancer death, but a good five-year relative survival rate. This is what it looks like over time. So we have been seeing an increase in incidence, interestingly. Between 2014 and 2018, there was a statistically significant increase in incidence. Mortality, though, has been going down and it has been going down for some time. This is what it looks like, this is what it looks like, what incidence and mortality look like by race and ethnicity. So no comparison by sex, clearly. But I think that the difference in breakdown between incidence and mortality on a race and ethnicity standpoint is quite interesting, right? So we see similar, if not lower, incidence in non-Hispanic Black women in terms of incidence, but in terms of mortality, huge differences, right? Between non-Hispanic Black women and women of other races and ethnicities. This is what it looks like geographically. So no real specific pattern, but wanted to be consistent and show you maps whenever I could. And so there they are. Risk factors for breast cancer are, there's a lot of them. The most important risk factor is age. So the highest incidence of breast cancer is in women over the age of 50. There's, of course, also family history and genetics. We are all familiar with the two genetic markers. Early menses and late menopause are risk factors. Being nulliparous or primiparous after the age of 50, or excuse me, after the age of 30 is a risk factor. There's risk with specific hormonal therapies, lack of physical activity, overweight or obesity, particularly after menopause, excessive alcohol use. And then there are some breast-specific factors as well. So prior breast cancer, some other types of breast diseases. I did want to flag, there is amongst all of this bad news and risk factors, there is a protective factor. Breastfeeding has been shown to be a protective factor. That may or may not come up in the test. You never know, so I threw it in. And then radiation therapy to the chest is also a risk factor. The other risk factor that I think is important, but isn't, I don't think on here, is DES exposure during gestation. So DES was used between 1940 and 1971 to prevent miscarriages. So if mom of patient took DES while pregnant, then there's an increased risk factor for breast cancer in the child. Okay, prostate cancer. So prostate cancer is the leading cause of cancer in men, number one cause of cancer in men. It's the second cause of cancer death in men. Incidence rate is about 112 cases per 100,000. So over 200,000 new cases in 2019. There's a 96% five-year relative survival rate. And the mortality rate is around 18. This is what it looks like over time. So lots of decreasing sort of in the early 2000s. That's all sort of stabilized recently. So no statistical changes in incidence or mortality in recent years. And then this is what it looks like by sociodemographics. Clearly no comparison by sex here, but when we're talking about race and ethnicity, huge disparities in both incidence and mortality in non-Hispanic black men. This is what prostate cancer incidence looks like by age. Different, right? So not the usual pattern of continuous increase with age. We see an incidence peaking between the ages of 65-ish and 75-ish, and then actually declining with age. So super interesting there. Different than the usual pattern. But mortality looks similar, right, to the usual pattern with continuous increase with age. This is what it looks like geographically, incidence and mortality. Again, sort of nonspecific pattern. But again, I wanted to show you the maps wherever I could, so there they are. Risk factors for prostate cancer. Again, age, most important risk factor. And like we already talked about, non-Hispanic black men are more likely to get prostate cancer, and they're also diagnosed at a younger age, which I think plays into some of this and is an important thing to know. They do tend to have more advanced disease at diagnosis, are more likely to have this severe type of prostate cancer when diagnosed, and are more likely to die as a result. And then family history is a risk factor as well. Okay, shifting to colorectal cancer. So colorectal cancer is the number four cause of cancer in men and women together. It is the number four cause of cancer death as well. Incidence rate is about 36 per 100,000, so 140,000 new cases in 2019. Mortality rate is around 13. The five-year relative survival rate is around 64%. This is what it looks like over time. Some good news here, incidence and mortality continue to decline and statistically tested between these years still going down. Breakdown by sociodemographic factors, or rather by sex and race ethnicity. Again, men, higher incidence and mortality than women, and some variation along race and ethnicity lines with, I don't know if it's a statistically significant difference or not between non-Hispanic black populations and others in either incidence or mortality, but not those huge disparities we were seeing necessarily with prostate cancer. This is what incidence looks like by age. So not much different than the usual pattern with continuous increasing in incidence with age, and mortality is similar increases with age. Geographically, a little bit different, right? It's not completely nonspecific. There's maybe some hotspots in the Southeast, but similar patterns between incidence and mortality. And then risk factors for colorectal cancer. You guessed it, age. Most important risk factor, about 90% of cases are in adults older than 50. That explains our screening guidelines a lot, right? Family history is a risk factor. Overweight or obesity, lack of physical activity, diet, alcohol, smoking, all the things that we've already talked about play into this. There's also some gastrointestinal factors that are risk factors. So for example, personal history of colorectal cancer, IBD diagnosis, and then of course, there's those genetic syndromes that we all had to learn for step one, which I'm not gonna read to you, but there they are just in case you forgot them like I did and need to stick them back in your brain for the test. Okay, so that's those top four. Now let's talk about some other cancers. We'll segment this part two. We'll start with cervical cancer. So cervical cancer doesn't make that top 10 list on either incidence or mortality, and I just want to flag, you know, the scale change here, we had been talking about hundreds of thousands of new cases and tens of thousands of deaths. With cervical cancer, now we're talking about tens of thousands of new cases and thousands of deaths. So really just sort of a different impact scale, but an impact nonetheless and an important one. So about 13,000 new cases in 2019, about 4,000 deaths, and the five-year relative survival is about 67%. This is what it looks like over time. So the incidence is largely unchanged in the past several years and really honestly going back quite a ways. Mortality has been decreasing some, which is good news. This is what it looks like by race and ethnicity. So you can see here, there is some variation and the pattern is somewhat different between incidence and mortality. This is what it looks like by age, super different, right, than what we've been seeing before. So we're actually seeing cervical cancer peak in the early 40s and then decrease with increasing age, really different than the patterns that we'd been seeing before. Mortality, though, you know, sort of increases until you're about, until like the 50s and then sort of stabilizes, and so it increases with age but not as dramatically as some of the other cancers that we've been looking at. This is what it looks like geographically. So again, we're seeing a bit of a hot spot. The pattern, geographic pattern, is similar between incidence and mortality. And then risk factors for cervical cancer, again, I'm sure most of us just, this is just refresher because we all had to remember these for step one and step two, but HPV, most cervical cancers are associated with HPV. Cigarette smoking is a cause of cervical cancer. HIV is associated and is a risk factor. Using oral contraceptives for more than five years, you know, the the thing to note about that is that the risk actually goes back down after stopping and returns to normal within years of stopping. Having multi-paris over three births, the theory there is that there are hormonal changes during pregnancies that make, that may make women more susceptible to HPV infection or to cancer growth, and that pregnancy may, you know, result in a weaker immune system which may allow HPV infection growth. Shifting to ovarian cancer, so ovarian cancer is the number five cause of cancer death in women. The mortality rate of six per 100,000, about 13,000 women died due to ovarian cancer in 2019. Incidence rates around 10, so almost 20,000 new cases in 2019. And the five-year relative survival rate is not great, right, it's around 50%. This is what the trends look like, so incidence and mortality have been decreasing over time, so that's good news. And this is the breakdown by race and ethnicity, so you can see, you know, the sort of a non-specific pattern. There are some differences here, but not huge ones. This is what incidence looks like by age, so again, you know, a little bit different, right, we're peaking around 75 to 80 years of age instead of a continuous increase with age, but nothing huge, nothing hugely different. Mortality, very similar to the usual pattern with a continuous increase in age. From a geographic standpoint, not a ton of, like, it's sort of non-specific, right, and the incidence rate and mortality rate look largely similar in terms of geographic pattern, but nothing that you can, like, put a big red circle around, right, in terms of, oh, that's the hot spot, so a bit non-specific. Risk factors for ovarian cancer include age, family history, there's all of those genetics that we all had to learn and are now remembering, personal history of a variety of cancers, breast cancer, uterine cancer, and colorectal cancer, all risk factors for the development of ovarian cancer. There are some specific race and ethnicity risk factors, endometriosis is a risk factor, and then some risk factors with respect to nulliparousness or difficulty with fertility. Shifting to uterine cancer, so uterine cancer includes endometrial cancer but is not exclusive to endometrial cancer. It is the number four cause of cancer in women, it's the most common gynecological cancer. Uterine cancer is the number six cause of cancer death in women, so six leading cause of cancer death. The five-year relative survival rate is 80%, but still, you know, about 60,000 new cases in 2019, about 11,500 deaths or so in 2019. This is what it looks like over time, so incidence has been fairly stable, but mortality has been quite low, so we're seeing a lot of mortality. So, incidence has been fairly stable, but mortality has been going up. And then by race and ethnicity, so this one, you know, like, look at the pattern, this one should make you sit up, right? So, some differences in incidence, but a discrepancy in mortality among non-Hispanic Black women. Age, a little bit different, right? So, now we're peaking sort of in the 60s in terms of age, not decade, but in terms of age, between age 60 and 75 is when the peak is, and then it decreases with age after that. But mortality increases somewhat continuously with age, so not much different from our usual pattern. And then this is what it looks like from a geographic standpoint, so now our hotspot is in the northeast, and that hotspot occurs both for incidence and for mortality. Risk factors for uterine cancer, age, of course, obesity, we've talked about. Estrogen hormone replacement during menopause without progesterone, so without that counter. There are some fertility-related factors, tamoxifen certainly associated, and then some family history pieces, including family history not just for uterine cancer but also for ovarian and colorectal cancer. Shifting to testicular cancer. So, testicular cancer, the incidence and mortality are both relatively low, right? A little more than 8,500 cases, new cases of testicular cancer in 2019, but less than 500 deaths. The five-year relative survival rate is 95%. And in terms of incidence and mortality, in terms of incidence and mortality, you know, incidence has been going up a bit between 2014 and 2018. The mortality rate is so low that there's no statistical testing that was done on this data. So, but, you know, it's the same number in 1999 as it was in 2019, quite low mortality. This is what it looks like by race and ethnicity, so you can see here that it's a little bit different, right, than what we've seen, but kind of hard to say. You know, I mean, it looks like there's this huge gap, but really it's just the scale, so be careful and mindful of that. Age variation in testicular cancer, super different than what we've seen before, right? So now we're seeing a peak in incidence between the ages of 25 and 35, and then some decreasing incidence with age after that, so really very different than a lot of the other cancers that peak much later in life. Mortality, also quite different. Note the scale, right, like one is the top of the scale because the mortality is so low, and it's pretty consistent with age, like there's no real variation on age. And this is what it looks like geographically. Now, I know this mortality map is really not very helpful or useful. This is my sort of memory cue to you, my take-home message. Rates of mortality are so low across the board that the data is unstable, and so the estimates have to be suppressed because they're so small, so that's what the take-home message is from this very otherwise not particularly useful map. Risk factors for testicular cancer, cryptorganism. With this one, you know, it's unclear if ectopic position is the risk factor, or if there's something else that some sharing of environmental or genetic risk factors between testicular and cryptorganism, like is it the combination of the two, or is there some shared risk factor that they seem to come together. The reason for some of this confusion and sort of the big red flag is that orchopexy may not actually prevent cancer, but it's still important because it allows for clinical surveillance, right, so some interesting tidbits. Certainly, personal history of testicular cancer is a risk factor for testicular cancer. There's family history, and then, of course, there's an association with Klinefelter syndrome. Moving to bladder cancer. So bladder cancer is the seventh leading cause of cancer, but has a five-year relative survival rate of about 75%, so does mortality, the top 10 mortality. There are about 75,000 new cases of bladder cancer in 2019, about almost 17,000 people who died in 2019 because of bladder cancer. This is what it looks like over time, so both incidence and mortality going down. And then breakdown by sex and race ethnicity, so both incidence and mortality higher in men than in women, and higher in non-Hispanic white adults. I guess not just adults, this is all ages, so I misspoke, in non-Hispanic white individuals. This is what it looks like by age, so it's basically adults, right? So incidence increases with age in a similar fashion as we've seen with some of those others. And then this is mortality increasing, mortality with age as well. Geographically, a couple of interesting, you know, hot spots sort of in that Ohio area, both for incidence and mortality, but otherwise a fairly non-specific pattern. Risk factors for bladder cancer to be aware of, family history, there are some genetic syndromes to be aware of, PTEN and the RB1, the retinoblastoma gene. There are chemicals, so occupational exposure, important to remember for bladder cancer, particularly the ones I have listed here, and I'm sure you've heard about these ones in the AHRQ Health review as well. There are some medications that are associated with bladder cancer, there are some chemotherapeutic agents like cyclophosphamide, radiation therapy to the pelvis, cigarette smoking associated with bladder cancer, and then also chronic UTIs. Okay, one more part, one more cancer piece to get through. We are in the homestretch. So we'll talk about pancreatic cancer first. So pancreatic cancer is the fifth cause of cancer death in the United States. There are about 54,000 new cases in 2019, nearly 50,000 people who died of pancreatic cancer in 2019. The five-year relative survival rate, I think, is one of the lowest we've seen so far today, around 12%. This is what it looks like over time. Unfortunately, we are seeing increases in both incidence and mortality for pancreatic cancer. And so, you know, we've been talking a lot about things that have been decreasing, you know, the things that are increasing, maybe take note of those. I'm just guessing here, I don't really know. But if I was studying for this test, I'd probably take a look at the ones that were increasing to remember that those ones were increasing. Differences in sex by sex and race ethnicity in terms of pancreatic cancer, men a little bit higher than women, some variations by race and ethnicity. And this is what it looks like geographically. Again, this sort of hotspot in the northeast and sort of the eastern part of the Midwest. This is what incidence looks like by age, so not a whole lot of difference from the usual pattern. Mortality is similar, just continuous increase with age. Risk factors for pancreatic cancer, so smoking, obesity, diabetes, chronic pancreatitis. There's also a slew of genetic risk factors, you know, all of those genetic syndromes that are associated with pancreatic cancer, including like MEN1 and neurofibromatosis 1 and things like that. Liver cancer is the number six cause of cancer death. There were almost 28,000 people who died from liver cancer in 2019. The incidence rate is about eight per 100,000, with 35,000 or so new cases in 2019. Five-year relative survival rate is low, it's around 21%. This is what the incidence and mortality look like. So for a while, their liver cancer incidence was increasing. Now it's stabilized some in men, still going up a bit in women. Mortality rate has stabilized. This is what it looks like by sex and race and ethnicity. So a big difference, right, between men and women, men higher in incidence and mortality. And then some variations in race and ethnicity in terms of incidence with, this is different, right, we've been seeing all along some, sorry, just lost my train of thought. We've been seeing a lot of higher incidence in non-Hispanic white or non-Hispanic black populations. This is just a little bit different than what we've been seeing. Mortality isn't much different between those groups. This is what it looks like by age. So somewhat different, right, we sort of peak around 65 or 70 and stay there. So not that continuously increasing pattern that we've seen with some of the other cancers, but mortality is that continuously increasing with age. This is what it looks like geographically, super different, right? There's this hotspot that we haven't really seen before. And so maybe take note of that. And the incidence and mortality hotspots are different, or excuse me, are the same, but together are somewhat different than some of the other patterns that we've seen already. Risk factors for liver cancer. So certainly chronic viral hepatitis, excessive alcohol use, liver cirrhosis. Liver cirrhosis can be from a variety of causes. So certainly chronic hepatitis infection, chronic excessive alcohol use, non-alcoholic steatohepatitis, primary biliary cirrhosis can all lead to liver cirrhosis. And then the liver cirrhosis is the risk factor for the cancer. Overweight or obesity, diabetes, smoking, non-alcoholic steatohepatitis or NASH is kind of interesting. So liver cancer is associated both with NASH-related cirrhosis and also NASH without cirrhosis. So that's why I listed liver cirrhosis and NASH separately. Aflatoxin, of course, is the classic board question, right? So, but I'm sure you remember that from step one. And then there's genetic syndromes as well. Wilson's disease, glycogen storage, that alpha-1 antitrypsin deficiencies, you know, the more classic board question is the alpha-1 antitrypsin deficiency and liver cancer as opposed to COPD. But again, that's probably more like step one or step two. I don't know if it'll be on this one. I have no idea. Oral cavity and pharyngeal cancer. So almost 50,000 new cases of oral cavity and pharyngeal cancers in 2019, about almost 11,000 people who died. Five-year relative survival rate is around 65%. This is what it looks like from a trend standpoint. So the incidence has been fairly stable for men, has been increasing some in women. Mortality has been fairly stable. From a breakdown by sex and race and ethnicity, so men much higher in incidence than women and somewhat higher in mortality. Remember, the scales are a little bit different, so don't let the, like, differences in bars fool you. The race and ethnicity breakdowns, you can see here, this is what it looks like from an age standpoint. So, you know, a little bit different than that continuous increase, but still increasing with age. Mortality has that same continuous increase with age that we've seen before. Geographically, you know, there's that similar hotspot related that we've seen with tobacco use and cardiovascular disease and other cancers. And then these are the risk factors. So 70% of oropharyngeal cancers are HPV-related. Tobacco use is also a big risk factor, both cigarette smoking and smokeless tobacco use. Alcohol, there's some occupational exposures as well, which are, this should be reviewed from your Ock Health board review, but things like formaldehyde and asbestos and nickel. Radiation therapy to the head and neck, UV exposure, EBV. Shifting to leukemias, so leukemia is the 10th leading cause of cancer and the 8th cause of cancer death. You can see the incidence and mortality rates here. The five-year survival is about 60%. From a trend standpoint, the incidence has been stable and mortality has been decreasing. This is what it looks like broken down by sex and race and ethnicity. So again, men higher than women and some differences by race and ethnicity. From an age variation standpoint, you can see, you know, there's this teeny little peak down here in the kids, less than nine. And then you have that continuous increase with age. Mortality is just a continuous increase with age. And then this is what it looks like geographically, incidence similar to mortality in terms of where folks are, in terms of where the hot spots are. Risk factors for leukemia. So remember, there's a wide variety of leukemias, right? Leukemia isn't just one disease process. There's the acute leukemias and there's the chronic leukemias, and it's sort of this menu of leukemias. For public health surveillance, we tend to squish them all together. But remember, clinically, they're each individual fact, they're each individual entity and each of them have their own unique risk factors. Some of those risk factors are here. So for example, AML is associated with benzene, ionizing radiation, either history of radiation therapy or high levels of environmental exposure. AML is also associated with cigarette smoking. There are some genetic syndromes that are associated. About a third of patients who have myelodysplastic syndrome may develop leukemia, so also a risk factor. Shifting to lymphoma, so two flavors of this, right, Hodgkin and non-Hodgkin. We'll talk about them together. So non-Hodgkin lymphoma is the eighth leading cause of cancer and the 10th leading cause of cancer death. Hodgkin lymphoma, much less common. And you can see here the incidence rates and the mortality rates. Survival, five-year relative survival is similar between the two. I don't have statistical testing for you on incidence and mortality, but in general, things seem to be going, they're lower in 2019 than they were in 1999. This is Hodgkin lymphoma specifically. There are variations by sex and by race and ethnicity, but not a ton, right? Notice the scale. So really this big gap here between men and women isn't really a big gap, right? There's not really much difference. This is the big one, right? This is the classic. So this bimodal peak in terms of age variation is classic for Hodgkin lymphoma. So you have that first peak in the early 20s and then the second peak in the late 70s and early 80s. So if you see a bimodal peak age distribution for cancer incidence, you should automatically know it's Hodgkin lymphoma. Mortality looks the same though. This is what geographically it looks like. Again, the mortality rate is low, so low as to be suppressed, right? And so it's one of those non-helpful helpful types of maps. Non-Hodgkin lymphoma is a little bit different. So there are differences between men and women, men having a higher incidence of mortality. There's some variations by race and ethnicity. And then the age distribution is very similar to the sort of classic picture with increasing incidence with increasing age. Mortality similar, increasing mortality with increasing age. This is what the geographic pattern for non-Hodgkin lymphoma looks like. So there's this sort of hotspot in the Midwest. Risk factors. So for Hodgkin lymphoma, family history and infections, HIV and EBV both associated. Non-Hodgkin lymphoma, ionizing radiation, that same association, HIV and EBV, but also HHV-8 and T-cell lymphotrophic virus. And then also non-Hodgkin lymphoma, iatrogenic immune suppression, right? So transplant and the immune suppression related to that is a risk factor for non-Hodgkin lymphoma. Shifting to skin, we're almost there, I promise. So the most common type of skin cancer is our basal and squamous cell. Both of those types of cancer are highly curable and most cancer registries don't collect information on basal and squamous cell carcinomas. So I'm not gonna be able to present you epidemiologic information about those two, but I think it's important for you to sort of nugget in your brain, remember that basal and squamous cell are the most common types of skin cancer. Melanoma of the skin is the sixth most common cause of cancer overall. There are about 88,000 new cases of melanoma in 2019. Relative survival rate is 92% or so. This is what it looks like from a trend standpoint. So again, we're seeing some increases in female populations, but in males, it's been stable. Mortality has been decreasing. Breakdown here, men have a higher incidence in mortality than women. And then this huge difference, right, in non-Hispanic white populations in both incidence and in mortality. This is what it looks like by age. So not much different than what we've seen in sort of the typical picture. And then this is mortality. This is what the geographic distribution looks like. So kind of nonspecific, but further, sort of in the middle and Midwest, or West and Midwest. And then these are the risk factors. So we all know these pretty well at this point, I hope. So UV exposure, personal history, family history, sunburn, and then pigmentation that lends itself to sunburn, skin that burns or freckles or becomes painful in the sun, lighter skin coloration. Thyroid cancer. So thyroid cancer, remember I told you that it had been number 10 incident cancer until 2017 when leukemias bumped it off the top 10 list. Still about 45,000 new cases in 2019. The mortality rate is pretty low, one per 100,000. The five-year survival rate is pretty high, over 95%. This is what it looks like in terms of over time. The incidence has been going down. Mortality rate, the same as in 1999, between 1999 and 2019. Variations by sex and race ethnicity. So all this time when we've had cancers that have both men and women that can get them, men have generally been higher or the same than women. This is the different one, right? So in thyroid cancer, women have a much higher incidence than men. Mortality is about the same for everything. There's some variations by race and ethnicity in incidence. Also different age breakdowns for thyroid cancer where we sort of increase until the 40s, until the fourth decade of life, and then it sort of stabilizes in incidence and not much increase. It just sort of hangs out there. Mortality, though, similar pattern increasing with age. This is what it looks like from a geographic standpoint, pretty nonspecific. And then risk factors for thyroid cancer. Radiation to the head and neck is a big one, particularly radiation to the head and neck during childhood. And then there's the slew of genetic factors, right? All of these different genetic syndromes that are associated with thyroid cancer. Okay, last part of cancer, pediatric cancer, which is an important topic. Pediatric cancer is the second leading cause of death in children aged one to 14. So it's important. Even though pediatric cancers are less than 1% of all incident cancers, because it's such a high cause of death in the pediatric population, it's super important. Pediatric cancer incidence for children under the age of 15 has really stabilized, which is good news. And other good news is that the survival rate is high. More than 85% of children with cancer survive five years or more. These are the top types of pediatric cancers. I think the take home here is that the top two cancers in the pediatric population account for over half of the total, right? So leukemias, again, there's several kinds, but they sort of are lumped together here. And then cancers of the brain and central nervous system. Okay, so we are in the home stretch. This is the last section. This last section is actually a variety of disease processes, hence the potpourri section name, that have really been either in the exam content outline or still in the more nebulous content outline now, that really didn't fit nicely into one of the other buckets. And so I stuck them all together here at the end. So we're gonna talk about chronic kidney disease. We're gonna talk about chronic liver disease, osteoporosis, arthritis, and glaucoma. So let's start with chronic kidney disease. So about one in seven, or around 15% of US adults are estimated to have chronic kidney disease. It's a little bit tricky to get at this estimate because almost 40% of people with severely reduced kidney function and who aren't already receiving dialysis don't even know that they have chronic kidney disease. About nine in 10 adults with chronic kidney disease don't know they have CKD. And that's problematic, right? Because chronic kidney disease, I mean, not only is it associated with premature death, but there's also, there's a fair amount of public health and health impact of this illness. We know about three out of four new cases of kidney failure are due to diabetes or hypertension. So those are the two big risk factors. And the other thing that I would say is that as far as we can tell, the prevalence has been pretty stable since 2008 or so. Chronic kidney disease prevalence varies by sociodemographics, of course, as everything has in our talk today. Females a tiny bit higher than males. Is this statistically significantly different? I don't know. Hard to say. It's not very big a difference. Increases with age, as with many of our chronic diseases. And then not a ton of variation by race and ethnicity in terms of prevalence. When we want to look at state and county level, there's no real state level data for chronic kidney disease for all ages. So to look at geographic variants, we have to look at end stage, which is stage five chronic kidney disease. That's effectively renal failure, right? So where we are treating with dialysis or transplant. And so this is what end stage renal disease looks like from a geographic standpoint. Risk factors for CKD. The two big ones, like we already talked about, are diabetes and hypertension. And then age, heart disease, which is not hypertension, and family history, obesity, personal history of kidney damage of one form or another. And then there are some immune disorders like lupus that are associated with CKD. When we look at specifically at stage five, so end stage renal disease, and we look at causes, the big piece of the pie is diabetes. And then combine that with hypertension and you have over half of end stage renal disease being caused by diabetes and hypertension together. The blue wedge, the other cause wedge, includes things like polycystic kidney disease. And so don't get fooled by like a polycystic question that makes you want to answer that that's the more common reason. It's really the most common reasons of end stage are diabetes and hypertension. Okay, chronic liver disease and cirrhosis. We'll talk about those together. So chronic liver disease in 2019 was the 11th leading cause of death. So falls off that top 10 list that I had presented earlier, but I just wanted to flag for you that, I mean, the mortality rate is fairly high, 13 and a half deaths per 100,000. About 2% of adults were living with diagnosed liver disease in 2018. And so it's not super common, but it's not uncommon and common enough to lead to the 11th leading cause of death. This is what it looks like over time. This is mortality over time. Mortality generally increases with age. I'm not showing you that, but what I am showing you is that mortality rate in men is much higher than in women and has been over time. This is what mortality looks like by state. So pretty nonspecific, right? Geographic variation, not like one big hotspot where you could just put a big red circle around it. Risk factors for cirrhosis. We've talked about this a tiny bit when we were talking about liver cancer, but the most common, the three most common risk factors for cirrhosis, excessive alcohol use, non-alcoholic fatty liver disease and chronic infectious hepatitis. So hepatitis B and C. Other less common risk factors, but important ones nonetheless, autoimmune hepatitis, biliary cirrhosis, some genetic disorders like Wilson's and alpha-1 antitrypsin deficiency, some meds and then heart failure as well. Cirrhosis, of course, is also a risk factor for a variety of other issues, many of which we've already talked about. So cancer, diabetes, osteoporosis, which we will talk about, liver failure, some coagulopathies. Speaking of osteoporosis, let's talk about that just a bit. So important to know your definition. So osteoporosis defined, this is from NIH and is the clinical definition also, bone density greater than or equal to two and a half standard deviations below the mean for the reference group. And then osteopenia on the way to osteoporosis is that bone density one to two and a half standard deviations below the mean. Osteoporosis is more common in women. So more than one in four women over the age of 65 have osteoporosis as opposed to, or in contrast to only about one in 20 men over the age of 65. Lots of people don't even know they have osteoporosis. We know that about 43% of US adults over the age of 50 have low bone mass, 12% or so over 50 have osteoporosis as opposed to low bone mass. But many people just don't know. This is what prevalence looks like. You know, we've already talked about it, but women way more than men, right? Much higher prevalence in women, much higher prevalence as we age. And then some variations in race and ethnicity. So non-Hispanic or excuse me, Hispanic adults with higher prevalence than non-Hispanic white and non-Hispanic black. This is what it looks like over time. So this is prevalence overall and then by sex. So again, men more than women and have been seeing some increase sort of early in the late 2000s and then a little bit of a leveling off overall. Men may be going down, women may be going up. Is this statistically significant? I'm not sure, but I think the overall trend is that it's been relatively stable, but higher in 2018 than 2007. Risk factors for osteoporosis, there's a multitude of them, right? Age, sex, we already talked about that. Some ethnicity, family history, low BMI as opposed to all of the other chronic diseases we've been talking about where obesity is the risk factor. Now low BMI is the risk factor. Low estrogen and low testosterone. There's some key targets for prevention. So excessive alcohol use, smoking, lack of physical activity and diet where we can really target modifiable risk factors to help decrease prevalence. Since we're on the topic of bones, let's talk about arthritis and talk about joints. So arthritis is also not uncommon. 24% of US adults report that they've been diagnosed by a doctor with some form of arthritis. Arthritis is, there are a lot, there's like a hundred or more rheumatic diseases that sort of fit under the umbrella of arthritis. The most common is osteoarthritis that affects about 32 and a half million adults or so. There's also, of course, rheumatoid arthritis and fibromyalgia, lupus and gout all have arthritic components. And so can fit under this umbrella as well. The other thing to know about arthritis is that it not only is a chronic disease, but it also tends to run with other chronic diseases. So I think this has a lot of implications for risk factor reduction. So here you can see that 49% of adults who have heart disease also have arthritis, 47% of adults who have diabetes also have arthritis and about 30% of adults with obesity have arthritis. This is what it looks like by sociodemographics. So increasing with age, somewhat higher in men than women. And then you can see the race and ethnicity breakdowns here. Variations by state. So that same geographic hotspot, this one I can't explain with cigarette smoking or cardiovascular disease for that matter. But remember, a lot of, as we just saw, arthritis tends to run with other chronic diseases. And we know that for some of those other chronic diseases, this is also the hotspot. So maybe that makes a little bit of sense. Risk factors for arthritis, overweight and obesity, joint infection and injury. Cigarette smoking is for rheumatoid arthritis specifically. There are some familial components. We've already talked about age and sex. And then don't forget your occupational risk factors. So there's repetitive stress, particularly in the knee or occupational injuries that can lead to in the long-term arthritis. Arthritis itself is also a risk factor. So we know that there are adverse outcomes. Adverse outcomes are more likely if arthritis is one of multiple chronic conditions. So things like serious psychological distress, social participation restriction, work disability. There's also higher risk of falls and injury amongst individuals who have arthritis. And then I think with huge implication about what we were just talking about was with arthritis running with other chronic diseases, physical inactivity is really high among adults with arthritis. About 25% of adults with arthritis report physical inactivity. And another quarter of them report insufficient physical activity. So if you combine that with comorbidity with adults with obesity or cardiovascular disease, this sort of joint pain and functional limitation may contribute to the lower rates of physical inactivity among adults with those other chronic conditions. Okay, and then glaucoma. So we know about, you know, glaucoma is the second leading cause of blindness worldwide. About 3 million adults in the US over the age of 40 have glaucoma. Nearly half of them don't know. There's no early symptoms of glaucoma. I think that's an important piece here that these prevalence estimates may be underestimate. Variations by socio-demographics. This is a bit of a busy slide. Sorry about that. I couldn't find a nice simple way, nice simple data to present to you. Take homes increases with age. And there is a significant disparity among non-Hispanic black adults in terms of glaucoma prevalence. The other thing that's not on this slide, well, not in this data, but I put it on the slide for you to remember that women account for about 61% of glaucoma cases in the US. Risk factors for glaucoma, age, we've already talked about race and ethnicity. We've talked about some family history of glaucoma and then diabetes can double the risk. And that's it. Oh my gosh, we actually made it through. So hopefully in this time we've spent together, you've gotten a good sense of the burden and distribution of chronic diseases, some variations in disease by age, by race and ethnicity, by sex and geography, and gotten a lovely laundry list that you can now shove into your brain with respect to risk factors for chronic disease. So now it's up to you, right? It's your turn to study. I hope that this has been helpful. As you're studying and you're reviewing these slides and also slides for others and the content for the other areas, remember, broad strokes, general trends, patterns, where are things different, and risk factors. And one step at a time, you're gonna get there. It's gonna be okay. Make sure you get some rest. Make sure that you get some hydration. And good luck. You're gonna be okay. Really, really, you're gonna be fine. It's been a pleasure. I hope that this has been helpful. And thank you.

chronic disease epidemiology

Brenna Van Frank

CDC

public health

cardiovascular diseases

respiratory diseases

metabolic disorders

cancer

chronic kidney disease

risk factors

socio-demographic variations

disease prevalence

age and gender distribution

geographic location

public health intervention