ALAN MATHIOS: Hello everyone. Thank you all for coming. I hope you're having a great, great weekend. We've been planning this weekend for a long, long time. So we're really excited that we have some cooperative weather today. And it's going to be a great, great weekend.
My name is Alan Mathios. I'm the Dean of the College of Human Ecology. And it's my great pleasure to introduce to you our speaker today, Professor John Cawley. I think back, I was on the search committee that managed to convince John to come to Cornell, so I'm living with that wonderful decision every day as dean, and it's great.
So John is a professor in the Department of Policy Analysis and Management and in the Department of Economics at Cornell. He is co-director of the Cornell's Institute on health economics, health behaviors and disparities. In addition to his affiliation with Cornell, John was a visiting professor at the School of Economics at the University of Sydney, Australia.
He was also an honorary professor at the JE Cairns School of Business and Economics at the National University of Ireland in Galway. He is a research associate at the National Bureau of Economic Research, which is commonly known by the profession as the NBER, and a research fellow of the Institute for the Study of Labor
He was a member of the Institute of Medicine Committee, Prevention of Obesity in Children and Youth, and has served on advisory boards and expert panels for the Centers of Disease Control and Prevention, and other government agencies. For his research on the economics of obesity, John certainly is known as one of the world's top people on obesity research. He has received the Investigator Award in Health Policy Research from the Robert Wood Johnson Foundation, the John D Thomas prize for young investigators from the Association of University programs in Health Administration, and the Charles Shepherd Science Award in Prevention and Control from the Centers for Disease Control and Prevention.
John is also a recipient of advising awards from the college. And then prior to arriving at Cornell when we recruited him successfully, he was a Robert Wood Johnson Foundation Scholar in Health Policy Research at the University of Michigan from 1999 to 2001. So I served on that [? serve ?] committee in 2001.
He received his PhD in economics from the University of Chicago, and his undergraduate degree is in economics from another accredited institution. I believe Harvard University. So without further ado, it's my great, great pleasure to introduce both a phenomenal economist, but also I've gotten to know John very well as a colleague, and I do research of my own with John.
He's a phenomenal guy, and I know you're going to enjoy hearing about obesity. So, thank you.
JOHN CAWLEY: Thanks everybody Thank you for coming to Charter Day weekend, and thank you for choosing this session. And thank you for your interest in this topic. So what I'll be speaking on today, this topic's called the price per pound, exploring the economics of obesity. And this has been my primary research interest since I was in graduate school 20 years ago.
And I'd just first like to thank the agencies that have funded this research, so importantly the College of Human Ecology here at Cornell University. Alan has created the Institute for Health Economics, Health Behaviors, and Disparities, which has been an incredible help and a great sort of community builder for all the health economists on campus. Also, the Robert Wood Johnson Foundation, the National Institutes of Health, and the US Department of Agriculture.
So here's what I'll cover in the next 15 minutes. So I just wanted to first start out by giving you some basic background about obesity, just defining what I mean by obesity, how it's measured, what the thresholds are, and then describe how the prevalence of obesity differs across countries, and how that prevalence has changed. What have been the trends in obesity in the past several decades?
You may be aware that the prevalence of obesity has really skyrocketed, not just in the United States, but in many other countries in the world in the past few decades. Then, I'll give you a little bit of an introduction to how economists think about topics like risky health behaviors and obesity. So I'll justify why is economics a useful discipline or perspective to use.
And I'll give you the intuition behind a basic economic model of obesity and explain what kind of implications arise from even just simple intuition. And then finally, I'll review what we know from the research literature, what we know about the economic causes of obesity, what we know about the economic consequences of obesity, and then finally, what do we know about using economics to improve treatment and prevention and public policy as concerns obesity.
So it's always a good idea to start out by defining your terms. The standard measure of fatness in epidemiology in medicine is body mass index, or BMI, which is just your weighting kilograms divided by your height in meters squared. Then that BIT index is used to classify people as either obese or not obese.
So for youth, a BMI that exceeds the 95th percentile of the historic weight for height distribution is the threshold for obesity. For adults, you can classified to be obese if your BMI exceeds 30, is equal to or exceeds 30. So it's kind of hard to think through what that number means, so one way to think about it is that for a man of average height-- and in the US, the average height of a man is 5 foot 9, the threshold for obesity would be roughly 203 pounds.
For a woman of average height-- in the US that's 5 foot 4-- the obesity threshold would be roughly 175 pounds. This is a table that just shows you more sort of comprehensibly how weight and height translate into a specific value of BMI. So on the vertical axis here, you can see the height in feet and inches.
And on the horizontal axis, you can see the weight in pounds. So for example, a 6 foot tall male who weighs 190 pounds would have a BMI of 26. And that green color indicates that that's in the overweight category, and all the yellow boxes indicate a weight height combination that's in the obese category of BMI.
Now BMI, even though like I said, it's the standard measure of fatness, in epidemiology and medicines, it's used by the CDC, the World Health Organization. It's a very flawed measure of fatness, because it doesn't measure fat. Right? It's just your weight for your height. And so it treats a kilogram of muscle the same way it treats a kilogram of fat.
And this actually has some really important consequences. So in some research that I've done with my colleague, Rich Burkhauser, what we've found is that the use of BMI instead of more accurate measure of fatness leads us to overestimate the extent of obesity among African-American women relative to white females. And also BMI is a worst predictor of things like heart attacks and mortality.
Now what would be a more accurate measure of fatness is something like your fat mass, so just the number of kilos of fat in your body, or a relative measure like percent body fat, the amount of your body mass that's composed of fat. And you can measure that through various technological devices. So what's shown here is called BodPod.
And you would sort of get into a bathing suit and step into the BodPod, and it uses air displacement technology to measure your body composition. This is actually the device that, for the past 10 years, has been used by the NFL at its scouting combine. They have all their potential NFL recruits get into the BodPod, and then they can actually measure how much muscle mass they have and how much fat mass they have.
Another device they can use is dual x-rays absiorptionmetry, which uses two different wavelength of x-rays to measure body composition. And this is what the federal government uses in its national surveys to measure and track the prevalence of fatness and obesity.
And another possible device is the biological impedance analysis device, which uses low levels of electricity. And that works because fat is an insulator and water's a conductor. So based on the resistance of your body to these low levels of electricity, they can calculate your body composition, the amount of fat and fat free mass of your body.
So even though in an ideal world, I would like to see a lot more research use these more accurate measures of fatness, much of the research to date uses BMI, because it's just a lot easier to collect. All you need to know is weight and height, and you can collect BMI. So much of what I'm going to discuss today is based on BMI, which is admittedly a limited measure.
So as I mentioned, you may be aware that the prevalence of obesity has risen dramatically in the United States in the past several decades. So this is showing you the prevalence of obesity as it was documented in the National Health and Nutrition Examination surveys. So these are fantastic data sets.
So periodically, the US government sends mobile examination vans, which are vans that are just packed with scientific and medical equipment, to roam the country. And for a nationally representative sample of people, they bring them in and do all sorts of medical tests, including weighing them and measuring their height, which allows us to track the prevalence of obesity using measurements of weight and height over several decades.
So as you can see from 1960, there's three lines here. The middle line is men and women pooled together. The top line are women by themselves. And the bottom line are men by themselves. They're pretty parallel lines though. And you can see for all three, the prevalence of obesity rose slightly from 1960 to 1980, but it was very gradual.
But starting in 1980, there's been a very rapid and dramatic increase in the prevalence of obesity, which has decreased since then, since the year 2000, but has not completely leveled off. So this is incredibly remarkable in historical terms. We've never before seen in American history or in any other countries before the past several decades such a dramatic rise in the prevalence of obesity.
What makes it even more striking is that this occurred at the same time as many other trends that are much more healthy. So this occurred at the same time that the prevalence of smoking was decreasing dramatically, the prevalence of binge drinking and heavy drinking decreased dramatically. And even teenage drug use decreased. So it's really fascinating that this obesity trend is in opposition to a great number of other more healthful trends in the United States.
I want to give you a better sense of this dramatic increase in the prevalence of obesity, so I'm going to switch to a different data set. This is data from the behavioral respecter surveillance system, so a disadvantage of this data is that it's not based on measurements of weight and height. This is a telephone survey, so we've only got self-reported weight and height. And that's a problem, because people quite notoriously tend to under-report their weight.
So the prevalences of obesity that are listed here are undoubtedly underestimates. But the really nice thing about the BRFSS, as it's called, is it's conducted every single year, which the end [INAUDIBLE] isn't, and also, they are able to survey many, many more people through this telephone survey, enough that they can generate state specific-estimates of the prevalence of obesity.
So what I want to show you is just how the prevalence of obesity has changed state by state from 1985 to 2010. So the prevalence of obesity is indicated by colors in this map. But don't be distracted by the white, because the white just means they don't have any data for that state yet.
In this map, some states have a prevalence of obesity of under 10%. That's the light blue. And some had a prevalence between 10% and 14%, which is the darker blue. So I'll just go through and show you year by year how the prevalence of obesity has changed over time and across states.
So this is 1985, '86, '87, '88, '89, '90, '91. So now we need a new category. Obesity has risen enough that now there are states that have a prevalence of obesity between 15% and 19%. So that's '91, '92, '93, '94, '95, '96, '97. We need a new category. Prevalence of obesity bewteen 20% and 24%. '97, '98, '99, 2000, 2001.
We need a new category. This is a prevalence of obesity between 25% and 29%. So what's the lightest state?
JOHN CAWLEY: Right. Colorado. And it's interesting, because in all sorts of different data sets, in all sorts of different years, Colorado robustly has the lowest prevalence of obesity of any state. How about the highest obesity state?
JOHN CAWLEY: Mississippi. So a funny thing is like, so I go to different universities and speak on the economics of obesity. And it's really amusing how many states I've been to where people have said-- like, you know, we have the highest prevalence of obesity, right? Like, that's happened in Wisconsin, West Virginia, Alabama.
And unlike Colorado, which is consistently the lightest state, the highest obesity state does fluctuate. But Mississippi is one of the few states that's consistently up in that category. OK. This is 2001, 2002, 2003, 2004, 2005. Now we need another category for a prevalence of obesity of over 30%. 30% or higher. 2006, 2007, 2008. Colorado's holding out. 2009, we lost Colorado.
So that's 2010. So looking at the map for 1990 for 2000 and 2010, you can see that there is no state in 2010 that's in the same category it was in 1998. And in fact, the highest prevalence state in 1990 would be by far the lowest prevalence state in 2010. So like I said, this is really unprecedented in public health history to see this kind of dramatic change.
Another thing that happened in 2010, by the way, is that the White House Task Force and Childhood Obesity described childhood obesity as a national health crisis for the United States. And these have all been maps for adults, but similar increases have been witnessed for children.
It's not just the United States where the prevalence of obesity has risen. This is some data for some OECD countries. OECD countries tend to be the more economically developed ones. The top line here is for the US using [INAUDIBLE] data. This broken line is another form of US data. But you can see for a variety of other countries-- England, Hungary, Australia, Canada, and so on, there was a significant increase in the prevalence of obesity in those countries as well.
These data are for women. These data are for men. You can see if anything, men's slope is a little bit steeper. So a lot of countries have dealt with this increase in the prevalence of obesity. It's not just the United States. The World Health Organization estimates that worldwide, there's over half a billion obese adults. So that's billion with a B. In other words, over 12% of adults in the world.
The Institute of Medicine and the World Health Organization both say that current rates of obesity are epidemic. And one thing that's interesting is the extent to which the prevalence continues to vary across countries, even economically developed countries. So this is showing the prevalence of obesity, adult obesity, for OECD countries, which again, tend to be the more economically developed ones. They're ordered in terms of the prevalence.
But there's an important distinction to make, which is that these colors are showing you something important. The colors in dark blue, the countries in dark blue, those are the countries for which we have measurements of weight and height, and therefore, it's more accurate. And the light blue are the countries for which the weight and height measurements are just self-reported.
So undoubtedly, those light blue ones are underestimates. Mentally, you should sort of adjust them downward. But you can see here that of the OECD countries, the United States does, in fact, have the highest prevalence of obesity. In these data, it was 35.3%.
But what's interesting is in that top dozen of countries, it's a very diverse set of countries. It's the US, Canada, and Mexico. It's Australia, New Zealand. It's the UK, Ireland, Luxembourg. It's also Turkey. So very diverse countries are struggling with this problem of obesity.
The countries with some of the lowest prevalences of obesity in terms of the measured data are Japan and China, but India and China-- sorry Japan and Korea, and then China and India undoubtedly have very low prevalences as well, even after one adjusts for self-reporting error.
So even though the United States is listed here as being the country with the highest prevalence of obesity in the OECD, we are not the country with the highest prevalence worldwide. So this may be something you've heard. You might have hard that America has the highest prevalence of obesity. And that's actually not true.
So this is showing you more comprehensively for all the countries in the world for which we have data what's the prevalence of obesity. And the dark red indicates that the prevalence is 30% or higher. And so you can see that the countries in the highest category of obesity include the US and Mexico, Venezuela, South Africa, a large number of countries in the Middle East, actually-- so Libya, Egypt, Saudi, Arabia, UAE, Qatar-- and then a number of Pacific Island countries. And it's actually those smaller Pacific Island countries that you can barely see on the map that have the highest prevalence of obesity.
So these are some data from the World Health Organization. And the top four countries in terms of the prevalence of obesity are all small Pacific Island nations. So Nauru, for example, over 2/3 of all the adult men in Nauru are clinically obese and almost three quarters of all the women in Nauru are clinically obese.
So this is a problem that the Pacific Island nations are struggling with. But you can see there are still sort of larger countries that are higher than the US, at least in terms of some measures of the prevalence of obesity-- Kuwait, Czech Republic, and a few others. So our prevalence of obesity's very high, but we're not the absolute highest.
So that's the first part of our chat, is just talking about the basic facts about the prevalence of obesity and the recent trends. But, next I want to talk about, why economics? Why is that a useful perspective to use to think about obesity? Well, one thing that makes it interesting is that it's really been applied only recently to the study of obesity.
Many other fields, like sociology, genetics, epidemiology, have been setting obesity for generations. But it's really only been in the past 15 or 20 years that economists have begun studying obesity. So in that time, there's definitely built up a very large literature that it's useful to summarize and synthesize, but there's still also a lot of low hanging fruit. Still a lot of interesting questions yet to be asked.
And I'm happy to say that there's a lot of faculty and graduate students here at Cornell who are pushing forward this frontier on research on the economics of obesity. I think economics is also kind of interesting because I think many people have a mistaken impression of what economics is, and what it's focused on. And that may be because people think about like, well, the business section of the newspaper, right? There's sort of stock market quotes and there's discussions of exchange rates, and trade deficits, and things like that.
And economics, you know, that's part of it. But to me, the heart of economics relates to the fact that it's a social science. Right? It's the study of people. It's the study of human decision-making. And so to me, there's no more interesting topic than studying why people make decisions, how people make decisions, about their risky health behaviors, like smoking, suicide, obesity, and so on.
So I just want to clarify that even though I think economics is a very valuable perspective to use to study obesity, I'm not in any way claiming that economics has all the answers as concerns obesity. Obesity is inherently a multi-disciplinary problem. All sorts of different perspectives are necessary. Like I said, genetics, epidemiology, sociology, and psychology.
I'm not even claiming that economics is the most important perspective. All I want to argue is that it's just one valid perspective. And hopefully, that seems uncontroversial now, and by the end of the talk, it'll be even more so. But when I first started out 15, 20 years ago, it was considered completely weird that an economist would think they had anything to contribute to the study of obesity.
But just to prove I put my time where my mouth is, this is a book that I edited. It's called "The Oxford Handbook of the Social Science of Obesity." And the goal behind this book was to provide basically sort of a Rosetta Stone to get people who are good writers and assessable writers from all the different disciplines that study obesity to write summaries of how their discipline studies this topic, and what they've learned in their discipline about obesity. So there's a contributions in here not just from economics, but also sociology, political science, sociology, psychology, epidemiology, anthro, and so on.
So what is it about economics that makes it useful for studying obesity? So I'll mention three things. So first of all, economics has a very widely accepted theoretical framework for how people make decisions. And compared to other fields, economists sort of ask different questions, and their models generate different predictions.
So just as an anthropologist would look for explanations that lie in the area of culture and a sociologist would look for explanations that lie in the area of family and society, economists look for explanations that relate to prices, and income, and changing trade-offs.
Another nice thing about economics is that it offers some very clearly defined rationales for how and when the government should intervene in the marketplace. So with that rapid rise in obesity, it's resulted in a lot of confusion. People wondering, well, does this mean the government should do something, and if so what? If the government did do something, would that make it a nanny state? There's sort of this ambivalence and confusion about when should the government intervene and how.
And the nice thing about economics is it has a very clear rationale for when the government should intervene. So in general, economics has a great respect for consumer sovereignty. If the free markets are functioning perfectly, why should the government intervene and interrupt a mutually beneficial transaction?
But economics has a rationale for government intervention, which is if the markets are failing, if there is market failures-- for example, like imperfect information, then there is a rationale for the government to step in. And I'll elaborate on this, because there are definitely market failures as relate to obesity. And I'll explain what they are in just a bit.
And then finally, another contribution of economics is it relates to methods. So relative to other fields and disciplines, economics puts a big premium on estimating causal effects, not just correlations. So for example, you might look at the correlation that sumo wrestlers tend to be morbidly obese, but that would give you a very misleading impression about the causal effect.
Right? So if we all started sumo wrestling, that wouldn't make us gain hundreds of pounds. Right? There's a sort of selection. There's omitted variables at work here. And so in economics, there's a big emphasis put in estimating causal effects and not just correlations. And that's actually really important if we want to understand what variables are really causing obesity, and then what are the consequences of obesity, and how effective are different government policies and different interventions to prevent and reduce obesity?
So the way that economists and others measure these causal effects are with two major approaches. The first is randomized controlled experiments, which I'm sure you're all familiar with. And then the second is by exploiting natural experiments. So there's some research questions we have where it wouldn't be ethical to conduct a randomized controlled trial.
So for example, if I want to see how does obesity or morbid obesity affect a person's health, their risk of a heart attack, it would be unethical for me to cause people to become morbidly obese so I can see if they have a heart attack. Right? That's unethical. But we could look for natural experiments, some kind of variation in weight that maybe it wasn't manipulated by the researcher, but also at the same time, wasn't really chosen by the subject either.
And so one example of that, for example, would be genetics. Right? So geneticists have identified certain genes, certainly alleles, that do predisposed certain people to being obese. Right? So some of us were just born by the luck of the draw with a higher probability of being obese than others. So that represents a natural experiment that we can use to measure what's the causal effect of obesity on outcomes of interest. And I'll explain some natural experiments when I describe the research literature on economics.
So let me just give you like, the intuition behind a very basic economic model of obesity. And I'll just make two points. So the first would be that economists assume that individuals are choosing their diets, and what they choose could be the quantity of foods, the quality of foods, the types of foods, and then they also choose their physical activity patterns and. Those could be work-related. They could be leisure time activities.
And what they're trying to do is maximize their happiness, or what economists call utility. So unfortunately, we can't choose our body weight directly. Right? Life would be so much simpler if we could just say, look, it's bikini season, I want to weigh this amount, and you could instantly make that happen.
We can't really choose our weight. We can only affect our weight indirectly and slowly over time by the dietary patterns we pursue and the physical activity regimens that we engage in. And another unfortunate fact is that money and time are scarce. We can't buy everything we want. We don't have time to do everything we'd like. And so in order to make themselves as happy as possible, people weigh the costs and the benefits of different approaches. They weigh the costs and benefits of different diets, including things like taste and cost, and they weigh different physical activity regimens when deciding what physical activity patterns to engage in. So in other words, economists think tradeoffs are really important.
So those are just the two points behind a basic economic model of obesity. You can make them a lot more complicated, but that's the basic idea behind it. And it actually yields several useful implications. So one interesting implication is that individuals may accept a higher weight in exchange for other things that they value.
Right? So? I'll give you an example from my own life, which is that when my kids were just little babies, I stopped going to the gym because if I didn't have to be at work, I wanted to be at home with my babies. Right? Because it was a special time of their life and my life, and so I became less fit. Right? I gained weight. I might have been in worse health. I might have looked worse.
But I willingly did that, because giving up the gym got me something else that I value. Right? So another way to put this or another way to make it more extreme is to say the fact that a person is clinically obese doesn't mean that they're irrational. Rights?
So sometimes, the public health discussion, the media discussion is, oh, my gosh, look, there's obese individuals. They're doing something wrong. What do we do about that? But I think if we really want to understand obesity, then we need to understand why people thought it was optimal to engage in the health behaviors that lead to obesity.
So was it the fact that they have low incomes, and they had very limited choices for diet? Could it be that they face very high prices for healthy foods? Could it be maybe not the money cost of healthy foods, but the time cost? Maybe the only way to get to a grocery store that sells fresh fruits and vegetables is to take two buses and transfer, which would make it very hard to get everything home.
Or maybe it's that they have a high opportunity cost of their time, meaning alternate ways of spending their time, like the example I gave of your children, or maybe somebody wants to make a law partner, and so they have to spend a lot of time at the office, and they have to cut back on exercise or discretionary physical activity.
So another important implication is that when the costs and benefits of different dietary patterns and different physical activity regiments change, people will alter their choices. And this actually helps us think through some of the things, some of the factors, that might have led to that rise in obesity. So possible explanations are that there was a fall in real prices of energy dense food.
So by real prices, I mean inflation-adjusted. And by energy dense foods, I mean foods that are high in calories and low in nutrients relative to their weight. So it could be that it became cheaper to have a worse diet, or more expensive to have a healthy diet. Another possibility is that there's increased entertainment options. Right? So I mean, not to sound like a grandpa, but when I was a kid, there were four channels. You had the three networks and PBS.
And now literally, we have hundreds of channels. And on top of that when I was a kid, like I remember our parents bought us the video pong. Like that's what a video game was. It was ricocheting a ball back and forth. And nowadays, there's incredibly realistic first person shooter games, massive multiplayer online games. With Netflix, you've got thousands of movies right at your fingertips.
So it's become incredibly cheaper, both in money and time, to have a lot of great entertainment. And people have probably rationally shifted to engage in more of it, because it's become more enjoyable and cheaper.
Another possibility is that employment has become more sedentary. This is probably a better explanation for changes in weight over the past 100 years. Relative to when the US was a more agrarian society, work was pretty physically demanding, whereas nowadays, I spend almost all my time in an office chair. Compare that to what our grandparents or great grandparents had to do.
So one other implication that comes out of this very basic economic model is simply telling people that they should behave differently isn't really expected to have any effect. And you sometimes do see these government information campaigns or PR campaigns that basically just tell people to live their lives differently.
And the economic model suggests that that's not going to have any effect, because people are doing what they're doing because of the trade-offs that they face. And if you want to change people's behavior, then you need to make it in their interest to change their behavior. You need to incentivize behavior change.
So now let me shift gears now that we've had this introduction to the economic perspective and talk about what we know from the research literature about the economic causes of obesity, the economic consequences of obesity, and then policies, economic approaches to treatment and prevention. So there has been an incredibly breathtakingly wide range of possible explanations for both the rise in obesity and cross-sectional differences in obesity.
And some of these explanations include things like decreased sleep, exposure to certain chemicals, the argument that because we have air-conditioning now, we're not spending the whole summer sweating off all sorts of calories to cool our bodies, Increased consumption of anti-depressants and anti-anxiety medications, and in general more prescription drugs. The fact that women are giving birth at older ages has been argued that be a contributing factor. Even viruses and changes in gut microbes-- all these are things that very responsible researchers have advanced as possible explanations.
But what I'm going to focus on are the expert economic explanations, things like prices, income, and even peers. So I showed you that really dramatic rise in obesity, so I want to manage expectations. I actually don't think that we're ever going to be able to say with any kind of certainty what factors led to that dramatic rise in obesity.
And part of reason has to do with the fact that the daily calorie surplus that explains that rise in obesity is pretty small. So it's estimated that it took just an additional 220 calories a day for adults and just 41 additional calories per day for kids to fully explain the rise in obesity, that dramatic more than doubling of obesity in the past several decades.
Now, our historic data aren't very good. So the data that we have on calories consumed, for example, often comes from dietary recall data, where people are asked, tell us exactly what you've eaten and the portion size in the last 24 hours. And researchers who have looked at the accuracy of dietary recall data estimate that men under-report their calorie intake by over 280 calories a day, and that women under put their calorie intake by about 350 calories a day.
So you'll notice that that error in the data is actually greater than the daily calorie surplus that led to the rise in obesity. And the data is actually so noisy that this same researcher concluded for a majority of subjects, self-reported food intake was not physiologically plausible, which is a nice way of saying that they're lying so much they should be starving to death if that was accurate.
So I actually don't think we're ever going to be able to say, like because the historic data just aren't very good, we're never going to be able to say like, OK, you know, this factor caused 10% of rise in obesity, and this other factor explains 15%. But that's OK, because better understanding the causes of obesity is still important for today. We want to understand today what's contributing to increases in obesity and cross-sectional differences in obesity.
So maybe the number one economic variable you might think of that would partly explain obesity are food prices. And it actually is true that during the period that obesity rose in the US that it became relatively more expensive to eat a nutritious diet and much cheaper to eat a relatively poor diet.
So for example, between 1990 and 2007, the real-- that just means inflation adjusted, price of a two liter of Coke fell 34.9%, and the real price of things like fast food pizza fell 18%. At the same time, the prices of fresh fruits and vegetables actually rose even faster than inflation. So it did become cheaper to eat a worse diet.
Now to better understand people's responsiveness to changing food prices, I conducted a randomized control trial with some my colleagues here at Cornell, David Just, Brian Wansink. And what we did is we increased the price of non-nutritious food 10% relative to the price of nutritious food. We did this in a supermarket chain in upstate New York.
And what we find is that even with a 10% change in prices, there was really no significant change in people's grocery purchases. So we weren't able to observe consumption. But even a 10% price change didn't really budge much people's purchases.
Now other people have exploited a natural experiment. I mentioned this sort of method of estimating causal effects before. What these researchers wanted to know is, how does the price of fast food influence people's consumption and people's weight. And they explored it in a natural experiment, which is the fact that in the US, states at different times have different minimum wages, and they raise those minimum wages at different times as well.
So there's variation across states and over time in the minimum wage. So the reason the minimum wage is relevant is because the price of fast food is heavily based on labor costs. And obviously, the labor used to make fast food is mainly minimum wage labor. And so when minimum wages are raised in a state, it gets passed onto consumers in the form of higher fast food prices.
And what they found is that, [? explored ?] that natural experiment, is there's no evidence that fast food prices affect the consumption of fast food. So this isn't to say that prices don't matter at all. It's just that people's responsiveness to prices is so limited that it's very hard to detect. And that kind of makes sense. If you think about your own day to day diets, there's probably strong habitual component to it and probably very strong brand preferences to it. If the price of Coke went to 10%, you might not switch to generic soda. Because to you, there's still a big difference. So that's probably what we're picking up here.
Now another possibility is that low income leads to obesity. So interestingly for women in the United States, there is a clear socioeconomic gradient, that higher income women are less likely to be obese than low income women. Interestingly for men, there really isn't that pattern. So you might think that low income plays a role.
So one way that we answered the question of what's the causal effect of income on people's weight is to exploit a natural experiment. So with a colleague, [INAUDIBLE], who used to be here , but what exploited is a natural experiment known as the Social Security Benefits Notch.
So this is a legislative accident. Congress literally made a mistake when it was writing the law that updates people's Social Security benefits for inflation, and certain birth year cohorts of retirees were doubly compensated for inflation. So if that happened at a time like now, it wouldn't really matter, because inflation's very low. But this actually happened during the 1970s, when inflation was really high.
And so certain birth year cohorts of retirees just started getting windfall Social Security payments. So Congress caught on, and they ended the program for later birth year cohorts of retirees, but they didn't want to anger the people who'd benefited, so they grandfathered them in.
So even today, there are certain birth year cohorts of retirees, who their entire lives, who their entire retired lives, have been receiving these windfall Social Security benefits. So that's a great example of a natural experiment. It's wonderful, because for completely random reasons, certain people got showered with money, and other people got no money.
Right? And we can identify who's who. And it had nothing to do with their work history, their diets, their health, or anything else. It was like randomly distributed money. So we use that to measure what's the impact of extra income on weight, and we found no detectable effect at all for the retirees of that extra income.
Now another graduate student here at Cornell, Max Schmeiser, he exploited different natural experiment to measure the impact of income on weight, and that concerned variations across states and over time in what's called the Earned Income Tax Credit. So that's a program that gives low income workers extra money. And what he found is that an additional $1,000 a year raises the weight of low income women by about a pound, with no effect for men.
And then one final natural experiment in this category used new casinos as a natural experiment. So these were Native American casinos, and the profits were returned to tribal members, their profits were given to them. And so it's a great natural experiment, because people didn't used to get any money. And then all of a sudden, because the casino opened, people just start getting checks in the mail. And only Native Americans get them, not their neighbors. So it's a great natural experiment.
And what they find is that extra income raises the weight of lower income adolescents, but didn't have any impact on higher income adolescents. So some real heterogeneity here, but in no case was there a very big effect of income on weight.
Now another possibility is low education. So in the United States, college graduates have a significantly lower prevalence of obesity than any other educational group, any lower educational group. This is particularly strong for women, but it also exists for men. So you might think that lower educated people just might sort of be disadvantaged in processing information, using nutrition information, and so on.
So what some researchers have done is exploited a natural experiment, which is that governments periodically raise the minimum amount of education that a person has to have before they can legally drop out of school. So most places in the US now, it's 16, where you can't drop out of high school legally until that age. But it used to be 14 or even earlier when we were more agrarian.
So [? Damon ?] Clark, who used to be on the faculty here at Cornell and his colleague, Heather Royer, they used that kind of legislation, exploited as a natural experiment, and what they found is no detectable impact of education on obesity, overweight, or BMI. However, their estimates were a little bit imprecise, so there might be some effect there that they just weren't able to precisely measure.
Other researchers have used the same approach for other countries in Europe, and they found for women, that an additional year of education decreases the risk of obesity quite a lot, by 14.3 percent, but for men, there was no detectable effect.
Let me mention one other possible economic cause of obesity, and that's peer effects. So you might imagine that going for a run would be more enjoyable if you had a friend who do it with. Or conversely, it might be more fun to have a pizza and a beer if your friend was having one too.
So peers can actually affect each other. And maybe that could be something where there's sort of increasing momentum that keeps the obesity prevalence rising. So in this case, we do have evidence from one randomized control trial. So the federal government actually conducted a randomized control experiment where they incentivized poor households to move to higher income neighborhoods.
They were afraid of ghettos developing or high rises filled with poverty stricken individuals. And so they wanted to incentivize people to move to the suburbs. And what that experiment showed is that after five years, the treatment group, the people who were incentivized, the low income people who were incentivized to move to nicer, high income neighborhoods, they were 4.8 percentage points less likely to be obese.
After 12 years, that treatment group was between 3.4 and 4.6 percentage points less likely be morbidly obese. So there's something about neighborhoods that seems to causally affect our probability of obesity. What we don't know from that study is what it is. So it could just be you're close to the grocery stores that sell fresh fruits and vegetables. It could be that it's lower crime, so you're outdoors more, you let your kids play outside more.
It might just be like sort of your neighbor's jogging, and you're going along with them. We really don't know from that study alone. And then another study took advantage of a natural experiment, which I think is really interesting, which is randomly assigned college roommates.
Right? So when you come to college as a freshman, your roommate is somewhat randomly assigned. Like, they're obviously going to the same gender, and there might be a few other variables that are used, but other than that, it's a random draw. And this study actually used data from Cornell. And what they found is that for girls, being assigned a roommate who is heavier in high school leads that girl to gain more weight during freshman year. And the roommates who are more influential are the girls who enter lighter and who are from higher income households. They have a greater influence on their roommate. For boys, there was no evidence of peer effects in this regard.
So just to summarize, what do we know about the economic causes of obesity? It really seems like there's no single economic factor that has a huge impact on obesity. Instead, it looks like many different factors have modest effects, and that these effects may actually be idiosyncratic. So if you notice, there was a lot of cases where the results differed by gender, or differed by income. And so it seems like we may not all be equally influenced by the same factors. There might be factors that influence me, but not you.
So let's move to the second category of the research, which concerns the economic consequences of obesity. So to think about the economic consequences of obesity, it's necessary to think about the medical consequences of obesity. So this is an image provided by the Center for Disease Control, and it just shows you the medical complications that result from obesity and morbid obesity. And it's an incredibly broad range of consequences.
So you might wonder, what are the mechanisms? Like, what is it that about obesity that causes all these different things? So I used to think of fat, the fat in our bodies, as just extra stuff, just dead weight that we carried around with us. But actually, fat cells are collectively an endocrine organ that secrete hormones, and many of these hormones harm our bodies.
So for example, our fat cells release resistin, which causes insulin resistance, or diabetes. The pancreas, which produces insulin in response to insulin resistance by producing even more insulin, and that additional insulin causes cancer. So it's one of these curious situations where like, the ghost makes the poison. So obviously, we have to have certain levels of insulin to live.
But when we have very high levels of insulin in our body, it's carcinogenic, and it can cause cancer in all these different sites. Fat cells also release a hormone called leptin, which damages our cardiovascular system, causes heart disease and lung disease. For other conditions like arthritis, osteoarthritis, It's really driven directly by increased weight on our joints.
So it's a really broad array of consequences due to obesity and morbid obesity. And when you look at what's called the population attributable risks, the amount of these conditions that is explained by obesity, it's actually startlingly high. So it's estimated that obesity is responsible for 61% of all the Type 2 diabetes in this country, 17.3% of all the cardiovascular disease, and almost a quarter of all the osteoarthritis, and 42.5% percent of all kidney cancer.
And the list goes on and on. So it's really striking, what influence morbid obesity has on our health. And not surprisingly, given that it affects all these serious conditions, it also translates into a higher probability of early mortality.
So the World Health Organization estimates that obesity and overweight combined worldwide are responsible for 2.8 million deaths per year. So just in the United States, it's estimated that obesity is responsible for 365,000 deaths per year. So the way that was described to me by a researcher at the CDC is that this is equivalent to three fully loaded jumbo jets crashing every single day just in the United States. That would be 1,000 people a day, 365,000 people a year.
And what this researcher at the CDC said is, imagine that that's the way these people were actually dying, three fully loaded jumbo jets crashing every day, killing 1,000 people. She said, imagine like the outcry there would be to do something about airline safety. And because people who die from obesity related illnesses are dying behind closed doors and from a wide variety of conditions-- dying from diabetes, dying from heart disease, cancer, stroke-- it's just not a salient. It's just not as visible. And as a result, we don't have the same kind of demand for change.
So given these incredible medical complications of obesity, one thing that I've done in my research with Chad Meyerhoefer, who got a Ph.D. Here at Cornell University, is estimated the medical care costs of obesity. In other words, what does it cost our medical, our health care system, to be treating all these obesity-related illnesses.
And what we do here is-- obviously, we can't run a randomized experiment. As I mentioned before, it would be unethical to force people to become obese so we can see how much sicker they would get. But we can take advantage of a natural experiment, and that's that heritability of weight, that sort of genetic component of weight and obesity.
And exploiting that natural experiment, what we find is that obesity raises annual medical care costs by $3,508 a year. And it increases the costs across the board. It matters for inpatient hospital visits. It matters for outpatient doctor visits, and for prescription drugs.
If you add up all those costs of obesity across the whole country, it amounts to $315.8 billion , dollars or over 27% of US national health expenditures. Or in other words, out of every $4 that we spend on health care in the United States, one of those $4 is spent treating obesity-related illness-- the strokes, cardiovascular disease, cancer, and so on, diabetes.
So this is a graph that we produced from our research. And what it shows you is the annual medical care expenditures. These are expenditures per year on a person on average given their BMR. And the predicted medical care expenditures are given to you by this black line here. And the dashed lines around that line are giving you our 95% confidence interval.
In other words, based on our statistical model, we're 95% sure that the true estimate lies in between these two dashed lines. So in some cases, these are very precise estimates. The dotted line is just showing you the distribution of BMI in our sample that was used to create these numbers.
So one thing that's really striking about this graph is that the expected medical care costs are really flat over a wide range of BMI. So remember that 30's the threshold for obesity. But it's not like you see this big discontinuous jump in medical care costs at 30. Instead, the cost of somebody who's BMI is 31 are basically identical to somebody who's BMI is 27, or even 25.
So it's not obesity per se that's expensive. What's really expensive is what's called morbid obesity, obesity with a BMI of 40 and above. That's where you see these astronomically high medical care costs, costs that are tens of thousands of dollars higher than the medical care costs of people of even overweight and low obesity.
And remember that this is a dotted line that's showing you the distribution of BMIs in our sample, there's actually very few people in the sample who have a BMI that high, that they're incurring these incredibly high medical care costs. So based on this figure, the challenge for our health care system is not reducing obesity per se, because obesity, early obesity, or moderate obesity is not very expensive.
The real challenge is decreasing the morbid obesity that's experienced by actually a very small fraction of individuals. That's what's really expensive for the health care system. And when you look at graphs of mortality risk over BMI, they're actually pretty similar. It's the case that like, a BMI of 31 does not really have a significantly elevated mortality risk. It's people whose BMI is in the range of 40.
Now another economic consequence of obesity concerns labor market outcomes. So for example, what do you earn in the labor market? So here, this is some of the earliest work that I did in this area as part of my dissertation, work that I did shortly after finishing graduate school. And again, measured the causal effect of obesity on wages by taking advantage of this natural experiment of the heritability of weight, the genetics of weight.
So what I found in this research is that the causal effect of weight on wages in the US really varies by race and gender. And it has its greatest impact for white females. So among white females, an additional 10 pounds of weight lowers wages by 2.8%. And I really don't find any significant impact for men.
In fact, other workers found that overweight men actually earn more in the labor force. And some researchers called this the portly banker effect, and said that when you're middle aged man, having some extra weight is actually a sign of success that you've made it. You don't need to look good for anybody. Whereas we don't see any evidence of that for women.
At different ages, all along the BMI distribuation, it seems to be the case that heavier women earn less. And that's controlling for all sorts of factors like education, intelligence, test scores, amount of time they've been working, and so on.
Others have found something similar for European countries. For example, these researchers found that a 10% increase in BMI lowers the wages of women in Europe by 1.8% and lowers the wages of men by 3.27%. So whereas I didn't find anything for men in the US, they actually got a bigger impact from men in Europe than women.
So I think a really interesting question is, OK, we've got evidence for the US and Europe that shows for women, weight lowers wages. But? Why what is the reason for that? So one argument would be that when someone's obese or morbidly obese, they're in worse health, and that worse health might affect their job absenteeism, it might affect their job performance, it might affect their job productivity.
So that sort of makes sense at its face. But the problem is that if you look at the graph of wages over BMI for women, the wages are falling starting with incredibly low BMI levels, BMI levels of like, 20 to 23, which is almost underweight. Right? So it can't be that there's health consequence of obesity causing all of this.
Might it be discrimination? And I think here, there's unambiguously evidence that it is at least in part discrimination. So one interesting study that was done in Sweden sent-- it was an audit study. So they sent almost identical resumes to real job openings. So they were fake resumes, but real job openings. And in Sweden, it's convention to attach a photo when you send a job application. And
So the researchers took pictures of people, and then they used software to manipulate the people's faces to make them look sometimes obese and sometimes skinnier. And what they found is that the obese versions of the same people were six to eight percentage points less likely to get a job interview. So the record is the same, the qualifications are the same. It is the same person. But when the employer thinks the person is heavier, they're significantly less likely to get a call to interview for the job.
So unambiguously, it seems like there is some discrimination at work explaining why heavier women earn less in the US than other countries. So let me move to the last category of research findings, and that concerns treatment and prevention. How can we use economics to improve public policy as concerns obesity?
But I think actually an important preliminary question to ask is, is this really any of our business? So if people want to engage in a dietary pattern that they find optimal, if they want to watch TV whereas someone else wants to go for a jog, is that really any of our business? Or is a government that tried to manipulate that sort of behavior a nanny state?
And as I mentioned, economics really does have a great respect for consumer sovereignty and not interfering with mutually beneficial transactions. But as I mentioned too, economics does recognize a rationale for government intervention when there are market failures. And as far as obesity is concerned, there absolutely are market failures.
So one very important market there is negative externalities. So that describes a situation where there are costs that result from a decision that are not borne by the decision maker, but spill over onto other people. So there are significant negative externalities as concerns obesity, and part of that has to do with our health insurance system.
So when a morbidly obese individual has a hospital stay and incurs a $20,000 bill, it's estimated that 88% of all the medical care costs of obesity are paid for by public or private health insurance. So if it's a public health insurance, it's picked up by Medicare if the person's elderly-- and that's funded with payroll tax revenue-- or it's paid for by Medicaid, and that's funded with general tax revenue.
If it's a child, then it's paid for with the State Children's Health Insurance Program. Now all of these are tax revenue based, and they're not based on how heavy you are, the funding of these programs. Alternatively , some of the costs are paid for by private health insurance. But again, the premiums that we pay for our health insurance don't depend on our weight, and so through both of these mechanisms, public health insurance and private health insurance, the contributions of non-obese individuals are paying for the medical care costs of morbidly obese individuals, and that represents the negative externality, and that is an economic rationale for intervention.
So what should we do about it? So you might think, well, the problem is these high levels of fat and morbidly obese individuals, maybe we should just tax such individuals. So I'm just going to set that aside as kind of inhumane and politically unfeasible. But surprisingly, there are countries that have come close to that. So no country has really taxed individuals on the basis of their body fat, but Singapore had what they called the trim and fit program, where all school children in the country were weighed, and schools that had an excessive prevalence of obesity were punished, and apparently, the schools passed that onto the kids by making the heavier kids run stairs, and had to stay to do extra punishment and exercise.
Japan has implemented what they call the Metabo Law, where older Japanese individuals have their waist circumference measured. And if a local area or a business has an unusually high percentage or prevalence of high waist circumference, then those employers or those local governments get punished.
So not the individuals who are heavy, but a sort of intermediary gets punishment. Again, they may use carrots and sticks to get those people to change their behavior. Probably the most commonly recommended policy for the United States to deal with obesity and the negative externalities of obesity are taxes on energy dense foods-- those high calorie, low nutrient foods. Especially soda pop. That gets singled out a lot.
And many countries have recently enacted such taxes. So for example, Denmark, Hungary, Finland, France, Norway, and Mexico. So researchers have studied the variation in these taxes across states and over time. And what they find is really no detectable impact of these taxes on people's weight.
And the problem, though, may be that these taxes in the US are just too small, because they average just 3% to 4%, these taxes on energy dense foods. So like I mentioned, my colleagues and I here at Cornell, David Just and Brian Wansink, we did this randomized experiment where we imposed a 10% tax on non-nutritious food, and what we found is, again, no detectable impact on grocery purchases.
So even if we moved from having taxes that were 3% to 4%, more than doubled that to make it 10%, there probably might not be any detectable impact on consumer decisions. So you might think, well, that just means we need to have an even bigger tax. And yes, at some point, like larger taxes will have an effect on people's behavior. But you also have to be wary of unintended consequences.
So one example of an unintended consequence is cross-border shopping. So when the District of Columbia years ago instituted a a tax on food, people just drove to Virginia to buy their food. They circumvented it. And this actually was very relevant in Denmark. So Denmark's tax was a tax on foods high in saturated fat. And it was evaded because Denmark's a small place. People drove down to Northern Germany to buy their cheeses and their yogurts. And it was actually the grocers of Denmark that appealed to the government to repeal the tax, which they did just two years later.
Another unintended consequence can be if the taxes are really high on just a few energy dense foods, people will switch to untaxed energy dense foods. So for example, if we tax soda pop, these laws frequently exempt any product with milk in it, because of the milk lobby, and so that means people could switch to things like Yahoo or bottled Starbucks drinks to get their caffeine and their sugar fix.
Now another approach to internalizing these external costs would be to offer financial rewards to morbidly obese individuals that lose weight. And these have a pretty mixed record of effectiveness. Now, some studies that have been conducted with very small samples in academic research centers do you find quite promising results.
But along with a former graduate student here at Cornell, Josh Price, we analyzed a workplace wellness program that included thousands of people from across the country. And what we found is really high attrition. So even though this program cost people nothing and was voluntary, and all these people were overweight or obese and wanted to lose weight, the majority of them dropped out before the first three months were over in a year-long program.
And by the end of the year, more than 75% had dropped out. And we also saw very modest weight loss. Now another approach is to subsidize physical activity. And we actually do do this. Right? Public schools offer sports teams, gyms, physical education and recess.
But in some research that I did with Chad [INAUDIBLE] at Cornell Grad, what we found using a variation across states and over time in their minimum PE requirements for school children, we found very little evidence that higher PE requirements lower kids' weight. So PE could work. But as it's currently constituted, it doesn't do a very good job.
So the department of Health and Human Services has criticized gym programs in the US as too often consisting of gym teachers rolling out balls and letting the kids play. Not being structured, and not trying to develop habits. So that's something that could potentially work, but not as it's currently constituted.
But I do think that at a minimum, even if people are not very responsive to prices, there are some simple things the government can do to stop subsidizing bad diets. So for example, the US agriculture policy not only costs us hundreds of billions of dollars, but it generally lowers the prices of energy dense foods. Very few of the agricultural subsidies in the US go for fresh fruits and vegetables. They tend to go for energy dense commodities. Some exceptions are milk and sugar, which are more expensive than they would be otherwise. But other things are much cheaper.
Another easy thing of us could do is cease to allow food stamps, the Supplemental Nutrition Assistance Program, to be used to buy energy dense foods. So SNAP benefits, food stamps, can currently be used to buy any packaged food in a grocery store, including soda pop, Doritos, cookies and things. And one researcher estimated that $2 billion of soda pop is bought every year using SNAP benefits. So several states and municipalities have asked the USDA for a waiver to ban the use of SNAP benefits to buy energy dense foods, and the USDA has denied all those waivers.
Let me just quickly mention two other economic rationales for government intervention, which concern market failures. So one is imperfect information. Obviously, when people are making decisions about what to eat, they don't always know the fat content and the calorie content of what they're considering eating. So there is an economic rationale for the government to step in and provide consumers with that missing information.
So back in the 1990s, the NLEA, Nutrition Labeling Education Act, mandated that every packaged food in the US have a Nutrition Facts panel. So this is sort of panel that you see on every candy bar and bag of chips in the United States. Alan Mathios has actually done a lot of the research evaluating that law. And what he finds is that that provision of information did have an effect on consumer purchases.
So specifically, people were less likely to buy the high fat versions of items that weren't already revealing their nutritional content. So when there's new information, people do respond. Now we're actually going to have a nationwide restaurant menu label law. This is part of the ACA, the Affordable Care Act, or Obamacare. It hasn't taken effect yet. But New York City implemented one years ago, and so we can look at that as a model.
And so two researchers evaluated the New York City law. And what they found-- one researcher got access to the Starbucks database. And so they were able to compare purchases at Starbucks before and after this law took effect in New York City compared to a control city. And this database had over 100 million transactions. So they have really accurate estimates.
And what they found is that the New York City menu label law caused purchases of calories at Starbucks to fall by 500%. And interestingly, that decrease wasn't with drinks. It was all with sort of extra food items that people were getting. But other researchers looked at fast food, and they found no impact of menu label law in New York City on people's calorie purchases as regarded fast food.
But one other thing to point out is that these label laws actually had a really nice unintended consequence, which is that they can lead manufacturers and restaurants to reformulate their products. So a great example of this is that after trans fats were required to be listed on the Nutrition Facts panels, many food manufacturers reformulated their products, because they didn't want to be embarrassed by having this very unhealthy ingredient in their products.
And the federal government has found that these circulating levels of trans fats in our blood declined 58% shortly after the government required just listing it. So the government didn't tell the food manufacturers they couldn't use the ingredient. They voluntarily stopped using it once they just had to reveal that information.
Others have found that menu label laws in certain municipalities have lead restaurants to make their food more healthy. So the one final market failure that I want to talk about is that there's an economic rationale for government intervention when people aren't acting rationally.
Now this is a very dangerous rationale to invoke, because it can be a slippery slope to paternalism, right? I don't want people looking at my decisions and just concluding I'm irrational and can't be trusted to make their decisions. But I think when it comes to young children, we can agree that kids can't appreciate the full consequences of their actions. That's why we don't let kids buy tobacco. We don't let them buy alcohol.
And so on that same rationale, there's been several countries and jurisdictions that have banned or limited food advertising to children. So Quebec, Norway, Sweden, and South Korea have all done this. There have been calls for the United States to do the same thing, but one obstacle-- and I'm very sympathetic to that call-- but one obstacle that we face is that in the United States, we recognize a wide latitude for what's called commercial speech.
So in 1978, the Federal Trade Commission tried to regulate the advertising of sugary cereals to kids. And it wasn't about obesity because that wasn't something that was on people's radar screen in 1978. It was about tooth decay. They were trying to stop sugary cereals from causing cavities.
And so the FTC tried to regulate advertising. And what happened is that Congress was outraged and almost defunded the Federal Trade Commission. So the FTC learned its lesson, and it does not try and interfere with commercial speech after that. Also, the Supreme Court in 1980 had a ruling that commercial speech is an actual right, that companies have a right to free speech. So that's an obstacle that we have to overcome if we want to limit or reduce advertising to children.
But it seems to me one easy thing that we can do is we can have the USDA and their checkoff program. The checkoff program collects money, and it is then used to advertise, to be used for research and development to develop new menu items that use energy dense commodities, and then to advertise those products.
So USDA checkoff dollars were given to Pizza Hut, for example, to develop pizzas that carried more cheese than usual, and then to advertise those products. The McRib sandwich. R&D was funded with checkoff dollars, and advertising it was probably funded by checkoff dollars. So it seems to me that's a program we can do without.
So just in summary, what do we know from the literature? Well, as far as causes go, there's really no single dominant economic cause of obesity. Many factors, like income and peer effects, may have modest effects. As far as consequences go, there really are very clear economic consequences to obesity, really high costs associated with morbid obesity in terms of medical care, expenditures, and lower wages for women across the whole BMI spectrum.
And then prevention and treatment. So just like there's no single economic cause of obesity, unfortunately there's no magic bullet. There's no one single policy that's going to reverse this epidemic of obesity. But taxes on energy dense foods, financial incentives for weight loss, and menu labels may have modest effects.
If you have any questions, feel free to hang around and talk afterwards. If you would like copies of any of the papers I mentioned, please feel free to email me, email@example.com, or go to my website. And thank you again for being here for Charter Day Weekend and for [INAUDIBLE]. Thank you.
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Obesity has risen dramatically in many countries of the world in the past several decades. John Cawley, professor of policy analysis and management and of economics, provides insight into the obesity epidemic using the lens of economics. He explains the economic causes and consequences of obesity, and how economics can be used to help prevent and treat obesity. Part of Cornell's sesquicentennial celebration, April 24-27, 2015.