WEBVTT 00:13.760 --> 00:17.680 Prof: The topic today is the nutrition transition and 00:17.676 --> 00:19.066 global food issues. 00:19.070 --> 00:25.300 When you talk about how food affects people, 00:25.300 --> 00:28.720 enters the body, has an impact on health, 00:28.720 --> 00:30.620 on economies, and things like that, 00:30.620 --> 00:34.420 things get really interesting when you take a global point of 00:34.417 --> 00:34.857 view. 00:34.860 --> 00:40.560 The global politics affect food as you heard when we talked 00:40.556 --> 00:42.026 about hunger. 00:42.030 --> 00:45.580 Global economics affects the availability of food in the 00:45.578 --> 00:48.948 prices around the world, and at one point food was so 00:48.948 --> 00:52.438 local that what happened to the food world in one part of the 00:52.437 --> 00:56.037 world didn't really affect very much what happened elsewhere in 00:56.042 --> 00:58.312 the world but those days are gone. 00:58.310 --> 01:01.850 Now things like American subsidies to the corn farmers 01:01.853 --> 01:05.403 have enormous impact on what's happening worldwide. 01:05.400 --> 01:08.420 We'll talk more about that in the economics lecture. 01:08.420 --> 01:11.610 Today we're going to talk about what the picture looks like 01:11.611 --> 01:14.641 around the world and how diets have changed in countries 01:14.640 --> 01:15.520 outside the U.S. 01:15.521 --> 01:18.491 and what are some of the driving factors that have made 01:18.494 --> 01:19.544 this happen. 01:19.540 --> 01:23.220 Today we're going to talk about how there are changes in the 01:23.215 --> 01:24.705 global disease burden. 01:24.709 --> 01:27.579 As I've alluded to in earlier classes, 01:27.580 --> 01:31.370 the nature of diseases that cultures are exposed to and 01:31.372 --> 01:35.732 countries must confront because of the impact of disease on the 01:35.726 --> 01:37.956 economy, on healthcare costs, 01:37.955 --> 01:40.685 on productivity, on the size of the workforce 01:40.691 --> 01:43.741 when you have major diseases killing a lot of people, 01:43.739 --> 01:47.179 you see how important these are and the global burden, 01:47.180 --> 01:49.440 the global distribution of diseases have changed. 01:49.440 --> 01:52.210 We're going to talk about changes in diet and obesity in 01:52.208 --> 01:55.328 particular, and then I'd like to give you four case studies. 01:55.330 --> 01:58.210 We'll talk about China, India, South Africa and 01:58.212 --> 02:01.412 Finland, all different from each other in some ways, 02:01.408 --> 02:04.728 but all affected by the same world market forces. 02:04.730 --> 02:07.690 It'll be interesting to go through this. 02:07.688 --> 02:10.928 Certainly world health is in transition. 02:10.930 --> 02:16.450 The non-communicable diseases, NCD, are now overriding the 02:16.454 --> 02:18.784 communicable diseases. 02:18.780 --> 02:21.930 In some countries there's a double burden where both occur 02:21.931 --> 02:23.261 in very large numbers. 02:23.258 --> 02:27.218 Now as I've mentioned before, communicable diseases would be 02:27.215 --> 02:31.095 traditional infectious diseases where people get a specific 02:31.103 --> 02:34.123 disease from an agent in the environment. 02:34.120 --> 02:37.560 The non-communicable diseases are ones that people don't catch 02:37.563 --> 02:40.333 from something in the environment or from some--or 02:40.330 --> 02:43.550 from another person but diseases that are caused mainly by 02:43.550 --> 02:46.410 lifestyle, which can also be toxic as I've 02:46.413 --> 02:47.523 described before. 02:47.520 --> 02:50.600 The diets are changing around the world, but not only are 02:50.595 --> 02:53.065 diets changing, physical activity patterns are 02:53.066 --> 02:53.776 changing. 02:53.780 --> 02:57.490 This in turn affects diet, it certainly affects body 02:57.494 --> 02:58.154 weight. 02:58.150 --> 03:01.630 The aging of the population, especially in certain countries 03:01.631 --> 03:04.641 of the world is changing the healthcare picture, 03:04.639 --> 03:08.339 and globalization is having a massive impact. 03:08.340 --> 03:10.940 As we'll talk about later in the class, 03:10.938 --> 03:13.698 if you take something like food marketing, 03:13.699 --> 03:17.089 there was once a time when if a country had the will to do 03:17.087 --> 03:20.987 something about food marketing, it could control what was going 03:20.992 --> 03:24.402 on within its borders because there wasn't much marketing 03:24.395 --> 03:28.265 leaking in from the outside, or overwhelming what a country 03:28.265 --> 03:29.995 might be doing on its own. 03:30.000 --> 03:32.380 But those times are different with the internet, 03:32.378 --> 03:35.808 satellite television, etc., the ability of a country 03:35.809 --> 03:39.709 to even control what's going on on the airwaves or over the 03:39.709 --> 03:41.659 computer is very limited. 03:41.660 --> 03:43.350 Some people may say that's a good thing, 03:43.348 --> 03:46.468 say in countries that don't have much freedom, 03:46.470 --> 03:49.740 that the leakage from the internet from the outside 03:49.740 --> 03:53.600 actually helps inform people and is a good thing overall. 03:53.598 --> 03:56.808 But there may be some negative consequences in terms of food 03:56.812 --> 03:58.612 marketing and things like that. 03:58.610 --> 04:02.380 The global picture is changing to be sure. 04:02.378 --> 04:05.118 Now some of the changes are pretty obvious and we've 04:05.117 --> 04:06.887 discussed or alluded to before. 04:06.889 --> 04:10.969 The world is changing from local eating to global eating 04:10.974 --> 04:14.174 and that change has had profound impacts. 04:14.169 --> 04:17.279 As I said before, the relationship people used to 04:17.278 --> 04:20.778 have with food was that they were close to where it was 04:20.776 --> 04:23.196 grown, they might know the person who 04:23.197 --> 04:25.087 grew it; if not they knew the person who 04:25.089 --> 04:26.869 bought it from the person who grew it, 04:26.870 --> 04:30.200 and then they prepared it and they and their families ate it 04:30.197 --> 04:33.467 and there weren't many steps between the origination of the 04:33.466 --> 04:35.776 food and the metabolism of the food, 04:35.779 --> 04:39.309 but now many steps lie in between and more and more people 04:39.310 --> 04:42.900 in the world are dependent on food from outside their local 04:42.901 --> 04:43.461 area. 04:43.459 --> 04:46.599 This is affected by national and international policies to 04:46.598 --> 04:47.368 some extent. 04:47.370 --> 04:49.980 We'll give you some examples of that today. 04:49.980 --> 04:55.280 The local traditions have yielded to families eating out, 04:55.279 --> 04:58.849 eating large amounts of food, and subsisting on an abundance 04:58.851 --> 05:02.931 of food when it's available, usually at low cost and this 05:02.930 --> 05:07.020 has pretty--by now pretty predictable consequences. 05:07.019 --> 05:10.379 The markets have changed, where people buy foods has 05:10.379 --> 05:14.039 changed a lot around the world, so in many parts of the world 05:14.040 --> 05:16.880 you still see the kind of pictures that are on the left, 05:16.879 --> 05:19.949 but more and more you're seeing the pictures on the right. 05:19.949 --> 05:24.109 Now, it's a very interesting issue about whether having 05:24.110 --> 05:28.270 access to what you see on the right is a good thing. 05:28.269 --> 05:32.429 We will talk in this class about how in the United States 05:32.428 --> 05:36.658 poor people tend not to have access to what you see on the 05:36.661 --> 05:40.411 right, nor to what you see on the left. 05:40.410 --> 05:44.460 But what they have access to are small markets in inner city 05:44.461 --> 05:48.651 neighborhoods that charge high prices for low quality food. 05:48.649 --> 05:52.429 That access becomes a problem and so bringing in something 05:52.432 --> 05:55.422 like you see on the right becomes an asset. 05:55.420 --> 05:58.570 In the developing world it appears, from what little we 05:58.569 --> 06:01.779 know about this so far, the picture may be different. 06:01.778 --> 06:06.368 That large markets that have many choices of processed, 06:06.370 --> 06:10.770 packaged, and in many cases imported foods tend to undermine 06:10.766 --> 06:14.136 local food traditions, get people away from eating 06:14.141 --> 06:16.661 what they might have been eating naturally, 06:16.660 --> 06:20.280 and give them access to a wide variety of foods that are less 06:20.281 --> 06:23.121 desirable than what they were eating before, 06:23.120 --> 06:27.230 because they're more nutrient poor and more calorie dense. 06:27.230 --> 06:30.350 There are differences depending on where you live in the world. 06:30.350 --> 06:34.410 The issue of choice is interesting. 06:34.410 --> 06:37.870 As I mentioned before in class, very often when people come to 06:37.867 --> 06:41.377 the United States--in fact one of our students in the videotape 06:41.380 --> 06:44.840 mentioned this before--they're amazed by the number of choices 06:44.839 --> 06:48.239 and by the size of things that they were exposed too, 06:48.240 --> 06:50.180 but people come to the U.S. 06:50.178 --> 06:53.908 and they see a hundred different salad dressings in a 06:53.911 --> 06:56.811 supermarket, 50 different yogurts, 06:56.812 --> 07:01.412 cereals that would fill up a whole aisle with dozens and 07:01.406 --> 07:03.156 dozens of choices. 07:03.160 --> 07:05.730 When people come and are confronted by this, 07:05.725 --> 07:08.285 it's interesting to see how they respond. 07:08.290 --> 07:10.190 Very often people from other countries say, 07:10.192 --> 07:12.052 well why do you need that many choices? 07:12.050 --> 07:15.720 I mean what's wrong with five salad dressings and what's wrong 07:15.720 --> 07:18.250 with six yogurts, and what's wrong with ten 07:18.247 --> 07:18.967 cereals? 07:18.970 --> 07:22.320 We have so many that we have this flood of choice that 07:22.324 --> 07:25.874 Americans believe is a good thing because the word choice 07:25.870 --> 07:29.670 gets connected conceptually with freedom and all that sort of 07:29.670 --> 07:32.470 thing; that the idea of restricting 07:32.471 --> 07:35.681 choice becomes pretty taboo in our country. 07:35.680 --> 07:38.600 In fact, there is some researchers who have studied 07:38.596 --> 07:39.936 this issue of choice. 07:39.940 --> 07:43.960 Very often people confronted by choices, where they have too 07:43.963 --> 07:46.153 many choices, don't function well 07:46.146 --> 07:47.506 psychologically. 07:47.509 --> 07:50.999 It becomes more difficult to make good decisions in the face 07:51.002 --> 07:54.382 of a vast array of choices, when a small number of choices 07:54.375 --> 07:55.555 would have done. 07:55.560 --> 07:58.820 So this paradox of choice confronts Americans because we 07:58.817 --> 08:01.757 have so many choices, but it's beginning to happen 08:01.759 --> 08:04.849 elsewhere in the world and people around the world are now 08:04.851 --> 08:08.161 facing this sort of paradox of choice where at first glance it 08:08.161 --> 08:10.611 seems like a good thing, but in fact, 08:10.613 --> 08:14.253 may not be, especially when it erodes local customs. 08:14.250 --> 08:17.940 Transportation is changing a lot and this is changing the 08:17.942 --> 08:19.792 physical activity picture. 08:19.790 --> 08:23.770 Getting around like this has yielded to getting around like 08:23.769 --> 08:27.959 this, and the number of people in the world who are now moving 08:27.956 --> 08:31.856 by motorized transport; even in countries like China 08:31.863 --> 08:33.113 has gone way up. 08:33.110 --> 08:38.490 And this has had a major effect on physical inactivity. 08:38.490 --> 08:42.330 Here's an example of this again, so if you look at China 08:42.331 --> 08:46.591 on the left you see pictures of everybody on a bicycle for the 08:46.591 --> 08:49.171 most part; and on the right vast numbers 08:49.171 --> 08:51.551 of people in cars, but even more so on motor 08:51.547 --> 08:52.207 scooters. 08:52.210 --> 08:55.760 There's some research done in China showing that when families 08:55.759 --> 08:59.369 secure a motor scooter--which is more and more possible because 08:59.366 --> 09:02.676 of the increasing wealth in the country--the likelihood of 09:02.683 --> 09:05.713 people being overweight in the family goes up. 09:05.710 --> 09:08.970 Even people that are not the primary users of the scooter, 09:08.967 --> 09:12.397 so these things tend to have these cascading effects that are 09:12.399 --> 09:13.599 very interesting. 09:13.600 --> 09:16.960 Now let's talk about physical activity in our own lives and 09:16.961 --> 09:20.441 you can see how this is going into the modern environment. 09:20.440 --> 09:24.170 I mean, my guess is that very few of you have ever even been 09:24.171 --> 09:27.901 inside an automobile where you have to crank the window with 09:27.902 --> 09:29.422 something like this. 09:29.418 --> 09:33.098 Mainly everything's done with an electronic button. 09:33.100 --> 09:36.850 There used to be a time when to tune the radio you actually had 09:36.846 --> 09:39.806 to turn a knob rather then just press a button. 09:39.808 --> 09:43.638 Of course, think of the remote control that saves you many, 09:43.642 --> 09:47.672 many, many trips a year from a chair to a television to change 09:47.672 --> 09:48.732 the station. 09:48.730 --> 09:51.240 Each of those, in their own right, 09:51.240 --> 09:53.220 may not add up to a lot. 09:53.220 --> 09:56.710 But if you take the cumulative effect of all those type of 09:56.707 --> 09:58.757 things, and those are just examples, 09:58.756 --> 10:01.836 you have an enormous amount of energy people used to spend in 10:01.836 --> 10:03.886 day to day life that they're now not. 10:03.889 --> 10:08.059 Add to that the fact that many jobs now are not physically 10:08.057 --> 10:12.587 demanding because of the use of technologies and computers, 10:12.590 --> 10:15.100 and robots and manufacturing, and on and on, 10:15.102 --> 10:15.632 and on. 10:15.629 --> 10:19.839 You see that the population physical activity has declined a 10:19.842 --> 10:23.702 lot in the United States and elsewhere in the world. 10:23.700 --> 10:27.350 In the United States, it used to be the case that you 10:27.346 --> 10:29.026 were paid to exercise. 10:29.029 --> 10:31.699 It was called your job. 10:31.700 --> 10:35.410 Now people pay to exercise in several ways. 10:35.408 --> 10:38.068 You join a club, you buy exercise equipment, 10:38.072 --> 10:41.912 but you pay an opportunity cost because of the crazed lifestyle 10:41.910 --> 10:43.150 everybody lives. 10:43.149 --> 10:46.269 If you take time to be physically active it's time that 10:46.274 --> 10:48.824 you could otherwise be doing other things. 10:48.820 --> 10:52.230 You could do other leisure things, you could rest, 10:52.230 --> 10:54.730 you could spend time with your family, 10:54.730 --> 10:57.250 you could get more work done, there are a lot of different 10:57.251 --> 10:58.891 things that compete with exercise, 10:58.889 --> 11:02.019 so the fact that it used to be crammed into your day to day 11:02.018 --> 11:04.768 life by necessity is no longer the case so much, 11:04.769 --> 11:07.069 and this is happening around the world. 11:07.070 --> 11:10.020 The number of people in countries like China who have a 11:10.015 --> 11:12.615 television, who have motorized transport 11:12.623 --> 11:16.773 has increased a lot and this is combining with the changing food 11:16.769 --> 11:19.139 environment to create great risk. 11:19.139 --> 11:22.619 If we look at things that really--the lifestyle factors 11:22.615 --> 11:25.445 that drive the non-communicable diseases, 11:25.450 --> 11:28.090 the three big ones are smoking, obesity, 11:28.090 --> 11:31.130 and physical inactivity; and then diet would fall under 11:31.129 --> 11:32.249 the obesity thing. 11:32.250 --> 11:36.480 In the developing world you're basically seeing these changes 11:36.481 --> 11:40.361 happen and then we can't be surprised that diseases fall 11:40.361 --> 11:41.351 from this. 11:41.350 --> 11:44.660 So these are big problems around the world. 11:44.658 --> 11:48.178 We're not talking about tobacco in this particular class, 11:48.177 --> 11:51.377 but boy if we did would there be a story to tell. 11:51.379 --> 11:54.419 Vast numbers of people smoking in the developing world, 11:54.418 --> 11:56.548 just like they are eating a bad diet, 11:56.548 --> 11:59.258 being physically inactive, and getting the same diseases 11:59.255 --> 12:01.955 that have plagued the United States and that's happening 12:01.961 --> 12:03.391 around the world as well. 12:03.389 --> 12:06.469 We'll also talk about food industry behavior, 12:06.470 --> 12:09.580 because a lot of the growth of some of the American food 12:09.582 --> 12:11.532 companies, especially the fast food 12:11.532 --> 12:14.042 restaurants, are occurring outside the 12:14.041 --> 12:16.061 U.S. It's not as if the U.S. 12:16.058 --> 12:20.238 market is completely saturated, because there's always more 12:20.238 --> 12:24.348 space to cram in fast food restaurants, but we're probably 12:24.346 --> 12:26.576 approaching saturation. 12:26.580 --> 12:29.360 Each of the companies is having trouble building a lot because 12:29.360 --> 12:32.140 they're competing with all the other fast food restaurants. 12:32.139 --> 12:35.679 But that's not true overseas, so a lot of the growth in some 12:35.682 --> 12:37.912 of these companies is outside the U.S. 12:37.905 --> 12:41.325 border as exactly happened with the tobacco industry. 12:41.330 --> 12:44.610 The tobacco industry got hammered by lawsuits and by 12:44.610 --> 12:48.730 government regulations and bad publicity in the United States; 12:48.730 --> 12:52.480 they took their business overseas and have made enormous 12:52.482 --> 12:56.512 amounts of money imperiling the health of people outside the 12:56.509 --> 12:56.779 U.S. 12:56.782 --> 12:57.672 borders. 12:57.668 --> 13:01.438 The food industry has been accused by some people of doing 13:01.443 --> 13:02.573 similar things. 13:02.570 --> 13:06.930 Let's look at the changing burden of disease across the 13:06.932 --> 13:07.582 world. 13:07.580 --> 13:11.500 If you look at how disease is spread--the diseases are spread 13:11.495 --> 13:14.035 across different parts of the world, 13:14.038 --> 13:16.518 and this graph will be a little hard to see because it's not 13:16.515 --> 13:18.025 that big, but you can see it when you 13:18.028 --> 13:18.888 pull it up on the web. 13:18.889 --> 13:23.689 The red represents high mortality developing countries, 13:23.690 --> 13:27.850 low mortality developing countries are the white, 13:27.850 --> 13:30.920 and then the medium blue are developed countries. 13:30.918 --> 13:34.798 At the top of the list you see up there the total burden 13:34.804 --> 13:38.554 is--that's yellow in the middle--is blood pressure. 13:38.548 --> 13:41.788 Now high blood pressure and we'll come back to some 13:41.791 --> 13:45.421 more--some recent data on this is contributing to lots of 13:45.421 --> 13:49.311 different diseases and seems to be the number one factor that 13:49.309 --> 13:53.389 one might intervene (second with tobacco following close behind) 13:53.394 --> 13:56.964 that you could do something about to lower the number of 13:56.958 --> 13:58.708 deaths worldwide. 13:58.710 --> 14:03.010 These various things are spread across different countries or 14:03.009 --> 14:06.879 different parts of the SES spectrum with countries, 14:06.879 --> 14:10.249 socioeconomic class, spectrum across different 14:10.251 --> 14:12.651 countries in interesting ways. 14:12.649 --> 14:15.139 If you look at all the things here, 14:15.139 --> 14:16.539 the top things, blood pressure, 14:16.537 --> 14:17.977 tobacco, cholesterol, 14:17.977 --> 14:19.987 underweight, unsafe sex, 14:19.990 --> 14:22.730 fruit and vegetable intake, high body mass index, 14:22.730 --> 14:25.710 physical inactivity, alcohol, all those things are 14:25.711 --> 14:27.051 driven by lifestyle. 14:27.048 --> 14:31.048 Now the hunger less so because that's a--that can be a problem 14:31.048 --> 14:34.128 with food access, but the rest of the things are 14:34.125 --> 14:37.705 driven by choices people make in their lives and those in turn 14:37.714 --> 14:40.954 are affected by government policy and a variety of broad 14:40.950 --> 14:42.480 and powerful factors. 14:42.480 --> 14:45.460 So it certainly makes sense if we want to make the world 14:45.458 --> 14:48.708 healthier to think about these chronic diseases and about the 14:48.710 --> 14:51.040 diseases that are driven by lifestyle, 14:51.038 --> 14:53.848 and in the case of our class we're talking about this with 14:53.854 --> 14:54.204 diet. 14:54.200 --> 14:58.070 Here's a very interesting graphic that depicts this 14:58.066 --> 15:00.846 changing global burden of disease. 15:00.850 --> 15:06.690 This is a chart that shows the leading causes of death in rural 15:06.686 --> 15:07.436 China. 15:07.440 --> 15:11.580 Total population 813 million people-very large numbers of 15:11.582 --> 15:12.252 people. 15:12.250 --> 15:15.260 I'm going to show you this graphic that has little people 15:15.264 --> 15:18.124 figures and each figure represents a certain number of 15:18.116 --> 15:18.706 deaths. 15:18.710 --> 15:21.250 It doesn't matter so much exactly how many deaths, 15:21.246 --> 15:24.096 but you'll just see the relative number of little people 15:24.095 --> 15:25.385 figures show up here. 15:25.389 --> 15:28.069 First we'll take communicable diseases; 15:28.070 --> 15:32.210 again, the sort of things that you thought would kill people in 15:32.211 --> 15:35.421 a country like China, only 2.6% of the deaths. 15:35.418 --> 15:39.528 Next are injuries which are multiples of the communicable 15:39.529 --> 15:43.569 diseases, so 11% of the people who die in China die from 15:43.565 --> 15:46.275 injuries, in rural China that is. 15:46.279 --> 15:49.459 But if you look at the non-communicable diseases, 15:49.456 --> 15:52.236 the chronic diseases produced by lifestyle, 15:52.236 --> 15:54.286 here's how the chart looks. 15:54.288 --> 15:57.818 An absolutely amazing difference. 15:57.820 --> 16:01.970 One would have never thought this was possible in a country 16:01.974 --> 16:04.414 like China, but it certainly is. 16:04.408 --> 16:08.608 This leads down some interesting roads about what we 16:08.610 --> 16:11.740 might do in these various countries. 16:11.740 --> 16:14.850 A paper that came out quite recently talked about blood 16:14.850 --> 16:17.730 pressure and I would like to loop back to that, 16:17.730 --> 16:22.320 and made the case that 80% of high blood pressure is occurring 16:22.315 --> 16:24.265 in the developing world. 16:24.269 --> 16:27.379 Now of course if you calculate--if you take into 16:27.380 --> 16:32.170 account that China and India, they're very large populations 16:32.172 --> 16:35.292 would be included in this number, 16:35.288 --> 16:38.568 you can see why you'd get a large percentage occurring 16:38.567 --> 16:40.487 outside countries like the U.S. 16:40.485 --> 16:43.635 just because the populations are not in balance. 16:43.639 --> 16:46.829 But still, this shows where the world health burden is 16:46.831 --> 16:48.941 occurring, and what's driving it. 16:48.940 --> 16:53.100 This particular study used the global burden of diseases study 16:53.104 --> 16:56.654 that's done by the WHO, the World Health Organization 16:56.654 --> 16:57.614 in Geneva. 16:57.610 --> 17:00.660 What they did was these investigators looked at the 17:00.664 --> 17:04.154 number of deaths from stroke and the number of deaths from 17:04.148 --> 17:07.098 hypertensive diseases, and compared high income 17:07.098 --> 17:09.698 countries with low and middle income countries. 17:09.700 --> 17:12.370 Here are the number of deaths from stroke. 17:12.368 --> 17:16.278 Quite a difference between those different types of 17:16.280 --> 17:17.220 countries. 17:17.220 --> 17:21.850 Then the number of deaths from hypertensive disease look like 17:21.848 --> 17:22.388 this. 17:22.390 --> 17:25.410 Again, orders of magnitude difference. 17:25.410 --> 17:28.450 So these countries do have to worry about these diseases. 17:28.450 --> 17:31.910 They're happening in very large numbers and they are a huge 17:31.913 --> 17:35.733 burden to the healthcare systems in these countries and I'll play 17:35.734 --> 17:38.904 you a couple of audiotape clips that get at this. 17:38.900 --> 17:42.270 It's a very interesting issue. 17:42.269 --> 17:45.549 Something that--where some kind of action definitely needs to be 17:45.553 --> 17:45.973 taken. 17:45.970 --> 17:49.010 So that's the down side, the upside is that there are 17:49.011 --> 17:52.231 opportunities that if these countries see it coming, 17:52.230 --> 17:55.610 if they say well let's look to our developed country brethren 17:55.606 --> 17:58.926 and see what they've done and what's happened to them and we 17:58.928 --> 18:01.858 don't want to get that way, what can we do about it? 18:01.858 --> 18:06.028 They may have an opportunity to get involved before business 18:06.032 --> 18:09.242 interests take over; before the economic drivers of 18:09.242 --> 18:12.392 this are just so profound that the countries can't turn it 18:12.385 --> 18:15.855 around--and even then it may be difficult because global factors 18:15.858 --> 18:18.448 are occurring that are helping drive this; 18:18.450 --> 18:21.060 but they at least have the opportunity. 18:21.058 --> 18:23.938 Thankfully, some of the countries are beginning to think 18:23.939 --> 18:24.619 about this. 18:24.618 --> 18:28.568 Countries like Thailand and Brazil have a great deal of 18:28.567 --> 18:31.417 concern about growing obesity rates, 18:31.420 --> 18:34.660 poor diet deteriorating, physical inactivity, 18:34.660 --> 18:36.880 and they want to do something about it, 18:36.880 --> 18:39.860 so maybe this early attention in some of the countries will 18:39.859 --> 18:42.429 create opportunities for doing some good things. 18:42.430 --> 18:46.250 In this context, the term nutrition transition 18:46.248 --> 18:49.678 becomes important, and this has been defined by 18:49.681 --> 18:52.981 the people who study it as population shifts in diet that 18:52.982 --> 18:56.462 contribute to increased risk of obesity and chronic diseases 18:56.462 --> 19:00.162 such as diabetes, cancer, cardiovascular disease 19:00.156 --> 19:01.556 and hypertension. 19:01.558 --> 19:04.738 This transition, if you read the papers by the 19:04.743 --> 19:07.933 people who have really developed the term, 19:07.930 --> 19:11.170 has several phases, and various countries in the 19:11.169 --> 19:13.719 world are in different phases here. 19:13.720 --> 19:17.450 The person who is most well known for using this term and 19:17.448 --> 19:21.108 has probably done more work on it than anybody else, 19:21.108 --> 19:24.548 is Barry Popkin who's at The University of North Carolina and 19:24.546 --> 19:26.776 a well-known figure in public health. 19:26.778 --> 19:29.228 One of the papers that were in your reading, 19:29.227 --> 19:32.357 the one that's referenced down here was--deals with this 19:32.356 --> 19:33.776 nutrition transition. 19:33.779 --> 19:36.829 He's been talking about this for many years and he's 19:36.829 --> 19:39.999 collaborated with researchers in China and Brazil, 19:40.000 --> 19:42.620 and other countries, to really find out what's 19:42.616 --> 19:46.336 happening in these countries and to identify the factors that are 19:46.338 --> 19:49.708 driving the profound dietary change in various parts of the 19:49.711 --> 19:50.411 world. 19:50.410 --> 19:54.260 Popkin's quite a good researcher, if you Google him, 19:54.259 --> 19:57.129 if you're interested in exploring this more you'll pull 19:57.131 --> 19:59.951 up his website at The University of North Carolina. 19:59.950 --> 20:04.850 His institute or center there has a variety of resources that 20:04.848 --> 20:10.318 you can look at on the nutrition transition and related problems. 20:10.318 --> 20:14.278 People have talked about the dual burden that the nutrition 20:14.275 --> 20:16.385 transition has helped create. 20:16.390 --> 20:20.150 The dual burden is when undernutrition and overnutrition 20:20.147 --> 20:23.857 exist in the same country, or in a smaller unit of a 20:23.855 --> 20:26.415 country like the same city, the same town, 20:26.415 --> 20:30.835 or as we mentioned before, even the same family. 20:30.838 --> 20:33.618 In some countries, as many as 60% of the 20:33.624 --> 20:37.414 households suffer from this dual burden where you have 20:37.407 --> 20:42.117 undernutrition and overnutrition going on in the same family, 20:42.118 --> 20:46.678 and the most often cited case of this, 20:46.680 --> 20:51.200 but it's not the only one, is where you have an obese 20:51.200 --> 20:54.330 mother and an under it shows how, 20:54.328 --> 20:57.008 in some ways, sick, the food relationship is 20:57.005 --> 21:00.795 around the world when you see this kind of thing happening. 21:00.798 --> 21:04.408 When you add together the under nutrition in the world, 21:04.410 --> 21:07.160 which is a major problem, and the over nutrition, 21:07.160 --> 21:10.410 and then layer on top of that the fact that somebody may not 21:10.405 --> 21:13.815 be particularly overnourished or undernourished by they're just 21:13.817 --> 21:16.017 not eating a health array of foods, 21:16.019 --> 21:20.119 then a great deal of the world is affected by this. 21:20.118 --> 21:23.228 So changing the world's relationship to food and 21:23.233 --> 21:27.343 changing the foods that people have access too and they wish to 21:27.343 --> 21:30.303 eat, can make a big difference in 21:30.297 --> 21:32.737 the well being of the world. 21:32.740 --> 21:37.980 This slide will show overweight and underweight prevalence in 36 21:37.980 --> 21:43.140 developing countries and break it down by urban women and rural 21:43.137 --> 21:43.967 women. 21:43.970 --> 21:47.230 When I pull up this graph it's going to--you're going to see 21:47.232 --> 21:50.942 lots of bars and data and it'll be hard to decipher all at once, 21:50.940 --> 21:53.070 but I'm going to bring your attention to one particular part 21:53.070 --> 21:53.360 of it. 21:53.358 --> 21:58.168 The urban women will be on the left, the rural women on the 21:58.167 --> 22:01.897 right, and this is done country by country. 22:01.900 --> 22:05.590 You can look to see how big of a problem undernutrition is and 22:05.590 --> 22:09.280 overnutrition with--is within a given country and then you can 22:09.282 --> 22:12.792 look to see whether there are differences between urban and 22:12.792 --> 22:13.522 rural. 22:13.519 --> 22:17.219 Given that we're going to use India as one of the case 22:17.224 --> 22:20.374 examples here, I've circled the data for India 22:20.372 --> 22:22.332 that you see in the red. 22:22.328 --> 22:28.518 If you look at the--the bars circled by the red on the left 22:28.523 --> 22:32.693 you have undernutrition on the left, 22:32.690 --> 22:36.200 that bar and then overnutrition on the right, 22:36.200 --> 22:37.420 the darker bar. 22:37.420 --> 22:39.750 The numbers aren't too different. 22:39.750 --> 22:42.340 In urban women you have a lot of undernutrition, 22:42.336 --> 22:44.316 you also have a lot of overnutrition, 22:44.317 --> 22:46.517 but the numbers seem about the same. 22:46.519 --> 22:48.709 If you go to the rural women on the right, 22:48.710 --> 22:51.570 the differences are really not--they're really quite 22:51.566 --> 22:54.866 striking differences where there are large numbers of people 22:54.868 --> 22:58.168 suffering from undernutrition, relatively small numbers 22:58.166 --> 22:59.836 suffering from overnutrition. 22:59.838 --> 23:03.788 This has implications for the urbanization of countries like 23:03.791 --> 23:07.611 India and the fact that people in many of these developing 23:07.612 --> 23:11.772 countries are fleeing from the countryside into the urban areas 23:11.766 --> 23:15.786 changes the risk profile that they suffer and changes whether 23:15.786 --> 23:19.936 overweight and underweight is the predominant problem. 23:19.940 --> 23:23.670 There will be some sense of that in an audio clip I'll show 23:23.673 --> 23:24.063 you. 23:24.058 --> 23:28.248 You can look at the countries in the UK and look at the 23:28.250 --> 23:33.140 percentage of children who are overweight in these countries. 23:33.140 --> 23:36.240 Each number shows the percentage of people who--the 23:36.240 --> 23:38.970 percentage of children who are overweight. 23:38.970 --> 23:43.670 It varies a lot from country to country in--as low as, 23:43.667 --> 23:49.077 let's say 12% in some countries and then you get down to Italy 23:49.076 --> 23:50.846 and you get 36%. 23:50.848 --> 23:54.238 You've got some very large differences, but pretty high 23:54.240 --> 23:55.370 numbers overall. 23:55.368 --> 23:59.448 It was once thought that obesity was a pretty peculiarly 23:59.450 --> 24:02.640 American problem but obviously not the case, 24:02.640 --> 24:05.830 so this is a pretty dispiriting number. 24:05.828 --> 24:09.748 Another graph breaks it down by type of countries and where they 24:09.753 --> 24:13.053 are in the world, so this would be the number of 24:13.053 --> 24:17.233 children in this case who are overweight or obese by region. 24:17.230 --> 24:22.480 The total height of the bar shows the combination of these 24:22.477 --> 24:23.027 two. 24:23.028 --> 24:26.328 The Americans by far have the largest number, 24:26.327 --> 24:29.847 Europe is catching up, and then you have smaller 24:29.851 --> 24:32.851 numbers in other parts of the world. 24:32.848 --> 24:35.728 The question is will those other countries in the world 24:35.732 --> 24:37.712 ever catch up to the United States? 24:37.710 --> 24:41.430 And if they do, what kind of consequences will 24:41.432 --> 24:43.172 this have for them? 24:43.170 --> 24:47.090 Here are trends showing the prevalence of overweight 24:47.090 --> 24:51.320 children from 1987 to 1997 in a variety of countries. 24:51.318 --> 24:54.018 In each case, you're seeing increases; 24:54.019 --> 24:57.939 in some cases you're seeing quite significant increases. 24:57.940 --> 25:01.970 Mexico is now the second most obese country in the world after 25:01.973 --> 25:05.813 the U.S., so they're suffering from a lot of these kinds of 25:05.809 --> 25:06.669 problems. 25:06.670 --> 25:08.810 These trends don't look very good. 25:08.808 --> 25:12.928 Clearly the world is having trouble with its eating and with 25:12.930 --> 25:16.980 its diseases that follow from it, and the trends don't look 25:16.981 --> 25:17.961 very good. 25:17.960 --> 25:20.470 They don't look good in the U.S., they don't look good 25:20.473 --> 25:21.663 elsewhere in the world. 25:21.660 --> 25:24.880 We've got a big problem on our hands, so it becomes very 25:24.882 --> 25:27.462 interesting to ask what do we do about it. 25:27.460 --> 25:30.780 If we take obesity as one of the diet related diseases and 25:30.776 --> 25:34.326 ask where it's increasing the most, you get a chart that looks 25:34.325 --> 25:35.135 like this. 25:35.140 --> 25:38.420 On the left, the left two bars are the males 25:38.420 --> 25:42.250 and females in the U.S., and these are data showing the 25:42.251 --> 25:45.801 prevalence of obesity and then we'll block out other parts of 25:45.796 --> 25:48.076 it, so you see Morocco entered into 25:48.076 --> 25:50.626 the bottom there, we'll take Brazil so the 25:50.625 --> 25:53.025 numbers are starting to get pretty high; 25:53.029 --> 25:57.009 China, now these are the--this is the increase in rates of 25:57.010 --> 25:57.710 obesity. 25:57.710 --> 26:01.650 You have Thailand here and then you have Mexico here. 26:01.650 --> 26:03.860 The prevalence is increasing in the U.S. 26:03.855 --> 26:06.735 but it's increasing much more as a percentage of the 26:06.738 --> 26:09.338 population in some of the other countries. 26:09.338 --> 26:12.448 So there are places in the world that face significant 26:12.445 --> 26:13.555 issues with this. 26:13.558 --> 26:16.508 I mentioned we were going to do four case studies, 26:16.512 --> 26:19.472 so let's start that out, we're going to talk about 26:19.467 --> 26:21.027 China, India, South Africa, 26:21.034 --> 26:22.124 and Finland. 26:22.118 --> 26:25.988 Obviously different parts of the world facing many different 26:25.989 --> 26:30.649 circumstances from one another, but in some ways converging on 26:30.648 --> 26:34.938 a common theme that is pretty representative of what's 26:34.940 --> 26:37.370 happening around the world. 26:37.368 --> 26:39.908 In these cases, significant issues are 26:39.906 --> 26:40.726 happening. 26:40.730 --> 26:44.180 Now, one of the students in the class was kind enough just the 26:44.180 --> 26:47.690 other day to send me a copy of a photo she took when she was in 26:47.688 --> 26:51.938 southern China, showing the KFC lighted on the 26:51.941 --> 26:53.711 street at night. 26:53.710 --> 26:58.300 KFC is the most--second most widely recognized corporate logo 26:58.304 --> 27:01.754 in China now outside of Chinese companies, 27:01.750 --> 27:06.020 so it's a very big presence in that country, 27:06.019 --> 27:09.649 1700 outlets and growing at the moment. 27:09.650 --> 27:14.250 In China, using that as an example, we have pretty 27:14.246 --> 27:17.056 important changes occurring. 27:17.058 --> 27:20.868 Something that one would have never guess would ever happen 27:20.869 --> 27:24.809 now is, and so there are now treatment clinics in Beijing for 27:24.810 --> 27:26.060 obese children. 27:26.058 --> 27:28.978 The health authorities are concerned about this greatly. 27:28.980 --> 27:31.300 The schools are starting to deal with it, 27:31.298 --> 27:34.138 so it has become a real problem in the country. 27:34.140 --> 27:39.560 The rate of obesity has doubled in China in ten years. 27:39.558 --> 27:44.288 There was a particular study that surveyed 270,000 adults in 27:44.287 --> 27:45.487 that country. 27:45.490 --> 27:49.180 They found--they estimated that there was 60 million obese 27:49.180 --> 27:52.160 people, 200 million overweight in that country, 27:52.159 --> 27:54.489 20 million people with diabetes. 27:54.490 --> 27:57.680 Vast numbers of people with a disease that has terrible 27:57.678 --> 28:00.388 consequences for the people who suffer from it, 28:00.394 --> 28:03.174 especially if the healthcare is inadequate; 28:03.170 --> 28:06.550 160 million have high blood pressure and you saw from the 28:06.548 --> 28:10.348 previous chart what that can do, and then vast numbers of people 28:10.351 --> 28:11.801 are smoking as well. 28:11.798 --> 28:15.208 Now I'm tempted to start talking about the tobacco 28:15.208 --> 28:18.828 picture in these countries because it's so appalling, 28:18.826 --> 28:21.396 but that's a little bit off task. 28:21.400 --> 28:24.660 Let's talk about obesity and cardiovascular disease in the 28:24.661 --> 28:25.921 Asia Pacific Region. 28:25.920 --> 28:29.510 There's strong associations between body mass index and 28:29.507 --> 28:32.957 stroke, as well as heart disease, in countries spread 28:32.961 --> 28:35.221 across that part of the world. 28:35.220 --> 28:37.950 Now the interesting part of this, and I may have mentioned 28:37.951 --> 28:40.731 this before, but there are certain ethnic 28:40.734 --> 28:44.134 groups that seem to be especially vulnerable to 28:44.127 --> 28:47.587 metabolic and disease consequences of increasing 28:47.594 --> 28:48.484 weight. 28:48.480 --> 28:52.400 So far, the research suggests that people of Asian descent 28:52.404 --> 28:56.334 have the greatest vulnerability to increases in weight. 28:56.328 --> 29:00.028 Let's say you take Caucasian people in the U.S. 29:00.025 --> 29:04.675 or other developed countries and they gain a certain amount 29:04.683 --> 29:07.063 of weight, let's call that X, 29:07.059 --> 29:10.639 and then at that point the disease risks really kicks in 29:10.636 --> 29:14.536 and they start getting increased risk for heart disease, 29:14.538 --> 29:16.468 stroke, hypertension, all the other problems. 29:16.470 --> 29:22.310 In people of Asian descent that same degree of risk kicks in at 29:22.307 --> 29:25.977 a lower number, let's just say 75% of X, 29:25.979 --> 29:28.709 or 65% of X, or 80% of X. 29:28.710 --> 29:32.160 So a much smaller degree of weight gain is producing the 29:32.157 --> 29:35.857 same health ramifications that people in other cultures have 29:35.855 --> 29:36.855 experienced. 29:36.858 --> 29:40.408 That makes intervention or prevention in particular parts 29:40.405 --> 29:43.485 of the world, an especially pressing issue, 29:43.491 --> 29:47.141 and it's why the expected rates of diabetes are just 29:47.136 --> 29:50.206 astronomical in some parts of the world. 29:50.210 --> 29:54.260 That statistic that you see in the bottom bullet point, 29:54.259 --> 29:58.229 that the mean age of strokes and heart attacks were ten years 29:58.227 --> 30:01.857 younger in China than Australia gives some sense of that 30:01.864 --> 30:04.514 particular biological vulnerability. 30:04.509 --> 30:08.099 Using India as a case study, we get a very interesting 30:08.102 --> 30:08.782 picture. 30:08.778 --> 30:12.848 We have to ask ourselves questions like from that chart I 30:12.845 --> 30:15.675 showed before, why do hunger and obesity 30:15.675 --> 30:16.615 co-exist? 30:16.618 --> 30:19.458 Why does it differ from urban to rural areas? 30:19.460 --> 30:22.560 What can we learn from this about agriculture and food 30:22.558 --> 30:24.078 supply around the world? 30:24.078 --> 30:28.658 Now, I showed you this slide before when we were discussing 30:28.659 --> 30:31.159 hunger in India, and in this case, 30:31.159 --> 30:34.799 the darker colors represent the parts of the country where they 30:34.804 --> 30:37.454 have the most significant rates of hunger. 30:37.450 --> 30:40.790 Now in the rural areas of this part of India, 30:40.788 --> 30:44.348 you'll have less obesity but in the urban areas, 30:44.354 --> 30:48.684 you'll have more and these problems tend to co-exist. 30:48.680 --> 30:52.690 Now, I'd like to play you a clip from National Public Radio 30:52.691 --> 30:56.841 on this because I think it's very telling and interviews some 30:56.840 --> 31:00.230 people in India about this particular issue . 31:00.230 --> 36:18.730 36:18.730 --> 36:21.280 Well, there's several interesting things about that 36:21.282 --> 36:21.642 clip. 36:21.639 --> 36:26.219 First it shows some of the human beings who are affected by 36:26.217 --> 36:28.547 this; it talks about the potential 36:28.554 --> 36:31.744 healthcare costs of this in a country like India. 36:31.739 --> 36:35.389 But it covers certain things and other things it doesn't, 36:35.389 --> 36:39.649 and they're--embedded in this conversation that we have, 36:39.650 --> 36:43.690 is a trap that America fell into, and it's possible that a 36:43.686 --> 36:48.006 country like India will as well and it's the idea that you can 36:48.005 --> 36:50.125 treat these problems away. 36:50.130 --> 36:53.600 Now in the United States, the traditional approach--and 36:53.597 --> 36:57.257 we'll cover this when I come back and do a lecture for you 36:57.257 --> 37:00.527 guys on the issue of public health and public health 37:00.532 --> 37:04.452 models--the traditional approach in the United States, 37:04.449 --> 37:07.959 when there is some kind of a disease that affects health is 37:07.963 --> 37:11.363 you treat it and the typical model that we hope works for 37:11.355 --> 37:14.985 many diseases would be like an ear infection in a child. 37:14.989 --> 37:17.719 There is a disease, it's easily diagnosed, 37:17.719 --> 37:20.659 fairly easily treated, you give people the medicine, 37:20.659 --> 37:23.139 the patients are happy, the parents are happy, 37:23.139 --> 37:25.419 the doctor feels good about it, everybody wins. 37:25.420 --> 37:27.850 That's the traditional model. 37:27.849 --> 37:31.629 That model just does not apply to chronic diseases and it 37:31.632 --> 37:35.892 doesn't apply to obesity or diet related problems in general. 37:35.889 --> 37:39.759 I'll show you some information later in the class about how we 37:39.755 --> 37:43.935 approach this--have approached this issue in the United States, 37:43.940 --> 37:48.360 which is to spend billions of dollars on research to treat 37:48.356 --> 37:51.386 obesity, very little money in comparison 37:51.385 --> 37:53.275 on preventing the problem. 37:53.280 --> 37:56.230 That is a trap, it's like the quicksand is 37:56.228 --> 37:57.378 sitting there. 37:57.380 --> 37:59.280 Is India going to walk into it? 37:59.280 --> 38:04.250 Now, whether this particular radio clip typifies what the 38:04.248 --> 38:09.128 thinking in India is, you can't make that assumption. 38:09.130 --> 38:11.880 In fact, there are some very progressive people in India who 38:11.880 --> 38:14.960 are paying a lot of attention to the prevention of the problem, 38:14.960 --> 38:18.920 but at least in this radio clip, it was about clinics; 38:18.920 --> 38:21.970 it was about treatment; it was about the people with a 38:21.967 --> 38:25.327 problem going to some expert that would deliver help once the 38:25.326 --> 38:27.636 problem exists, but there was really very 38:27.639 --> 38:30.589 little talk in there about the prevention of the problem and 38:30.590 --> 38:32.440 that's a whole different approach. 38:32.440 --> 38:36.180 So we have to hope that countries like India will avoid 38:36.181 --> 38:40.481 the trap that America fell into and take a different kind of an 38:40.478 --> 38:41.378 approach. 38:41.380 --> 38:45.340 I showed you I believe in the very first class a slide that is 38:45.336 --> 38:49.356 the projected increases in diabetes in different countries, 38:49.360 --> 38:51.990 and I'd like to show you a few more to help round out that 38:51.985 --> 38:52.535 knowledge. 38:52.539 --> 38:56.819 If we look in the next 25 years or so about--that are 38:56.817 --> 39:01.747 projections on the number of cases of diabetes--and as I said 39:01.751 --> 39:04.511 before, nearly all of these cases are 39:04.507 --> 39:07.307 driven by poor diet and physical inactivity, 39:07.309 --> 39:11.509 and then the obesity they cause--the numbers are really 39:11.510 --> 39:12.990 quite staggering. 39:12.989 --> 39:17.069 We're expecting 13 million new cases of diabetes in the U.S. 39:17.074 --> 39:20.334 in the next 25 years, that's a very high number, 39:20.327 --> 39:21.917 an alarming number. 39:21.920 --> 39:25.850 But in China the numbers are multiples--is twice that and 39:25.851 --> 39:29.931 then it's even more then that in India and so the number of 39:29.925 --> 39:34.065 millions of people to be affected is really quite high. 39:34.070 --> 39:37.140 Now of course there is a denominator issue here because 39:37.139 --> 39:40.659 the populations are so large in India and China compared to the 39:40.664 --> 39:40.894 U.S. 39:40.893 --> 39:44.253 that you would expect even a low base rate of the problem to 39:44.246 --> 39:47.826 turn into high numbers because of the large populations. 39:47.829 --> 39:51.579 But if we look at the percentage increase in diabetes 39:51.579 --> 39:54.749 in these countries, you see the picture still 39:54.751 --> 39:56.701 remains pretty similar. 39:56.699 --> 40:02.719 As the audio clip suggested, the increase expected in India 40:02.717 --> 40:06.867 in particular, is very, very alarming. 40:06.869 --> 40:10.319 If we collapse data across all the developed and all the 40:10.324 --> 40:13.844 developing countries--and I believe I showed you this one 40:13.842 --> 40:16.672 before--you see what the picture is like. 40:16.670 --> 40:20.100 Certainly, the health burden is changing around the world, 40:20.099 --> 40:23.839 the diet is changing a lot and it's happening in ways that are 40:23.844 --> 40:25.874 having a big impact on disease. 40:25.869 --> 40:29.469 So it's not just an academic matter, it's a very important 40:29.474 --> 40:33.144 matter for even the well being of the healthcare systems in 40:33.143 --> 40:34.413 these countries. 40:34.409 --> 40:37.879 I'd like now to talk about--turn our attention to two 40:37.882 --> 40:42.022 other case studies that we were going to discuss today and talk 40:42.021 --> 40:44.361 about South Africa and Finland. 40:44.360 --> 40:48.910 There was a five part series that I urge you to listen too on 40:48.907 --> 40:53.607 Public Radio International that was co-produced with the BBC on 40:53.606 --> 40:54.286 this. 40:54.289 --> 40:57.609 If you go to the website that I--the two web addresses that I 40:57.614 --> 41:01.054 give you here it's for parts I and II and we're going to listen 41:01.048 --> 41:04.368 to those right now but I urge you to listen to all five parts 41:04.373 --> 41:06.483 because it's a very good series. 41:06.480 --> 41:11.550 So PRI International and the BBC decided to do a series of 41:11.554 --> 41:15.564 discussions about the global obesity issue. 41:15.559 --> 41:18.569 And very interesting about the way they broke this down into 41:18.568 --> 41:21.218 different topics, and as you'll see from these 41:21.215 --> 41:24.115 particular clips, there is discussion on the 41:24.119 --> 41:26.819 impact on individuals of the problem, 41:26.820 --> 41:29.970 but then when the attention turns to Finland there's more 41:29.974 --> 41:33.474 discussion about what might be done to prevent the problems and 41:33.467 --> 41:35.887 what kind of interventions might occur. 41:35.889 --> 41:40.269 Not necessarily through medical care but through public policy 41:40.266 --> 41:42.846 that can have a beneficial impact. 41:42.849 --> 41:45.899 Okay, here we go . 41:45.900 --> 43:36.720 43:36.719 --> 43:40.139 I'll stop in a few places and just insert a few editorial 43:40.137 --> 43:40.807 comments. 43:40.809 --> 43:45.259 What's interesting about this little example in South Africa 43:45.255 --> 43:49.095 so far, is the impact of moving to an urban area. 43:49.099 --> 43:52.999 The other thing is the interesting concept of how could 43:52.998 --> 43:57.258 somebody who's living in dire poverty in the slums of a city 43:57.260 --> 44:01.660 in South Africa have the money to secure that many calories to 44:01.664 --> 44:05.914 gain that much weight, as this particular woman has. 44:05.909 --> 44:09.209 As we'll talk about in our class on economics, 44:09.213 --> 44:13.183 poverty drives people towards certain types of food. 44:13.179 --> 44:16.889 It used to be the case that poverty drove people towards 44:16.885 --> 44:20.785 certain local food selections, which were fine for the most 44:20.793 --> 44:21.403 part. 44:21.400 --> 44:24.400 It may not have been the best possible food but still it 44:24.398 --> 44:26.468 wasn't going to be overnourishment, 44:26.469 --> 44:29.599 but now in many parts of the world poverty leads people to 44:29.599 --> 44:32.779 the foods that provide the cheapest calories and those tend 44:32.782 --> 44:34.872 to be the most energy dense foods. 44:34.869 --> 44:37.939 A very similar picture to what we see in the United States. 44:37.940 --> 44:41.250 When you look at the foods that the poor have access too they 44:41.253 --> 44:43.633 tend to be the very calorie dense foods . 44:43.630 --> 46:51.570 46:51.570 --> 46:55.030 Now one interesting part of that discussion right there is 46:55.027 --> 46:58.667 that when people move from the rural areas to the urban areas 46:58.666 --> 47:02.426 and starting eating a worse diet and start gaining weight there 47:02.427 --> 47:06.187 may be way of--might be a way of compensating for that, 47:06.190 --> 47:09.220 namely increased physical activity to offset the increased 47:09.224 --> 47:09.814 calories. 47:09.809 --> 47:11.769 But in fact, people tend to become less 47:11.768 --> 47:14.758 physically active in those environments and then you have a 47:14.759 --> 47:16.769 double whammy going on if you will. 47:16.768 --> 47:19.618 More calories, a worse partitioning of the 47:19.623 --> 47:21.983 diet, that is, more things like fat, 47:21.980 --> 47:24.860 sugar and salt and less physical activity so less 47:24.860 --> 47:28.460 ability to compensate for the dietary insult that's occurring 47:28.460 --> 47:28.820 . 47:28.820 --> 48:48.700 48:48.699 --> 48:52.949 Let's look just at that little discussion about the social 48:52.952 --> 48:53.552 norms. 48:53.550 --> 48:57.990 Embedded in this case study of people in the urban areas of 48:57.985 --> 49:02.415 South Africa you have migration from the rural to the urban 49:02.420 --> 49:06.070 areas playing a role, poverty plays a role, 49:06.067 --> 49:08.827 physical inactivity plays a role, 49:08.829 --> 49:11.659 access to certain foods plays a role, 49:11.659 --> 49:14.199 and in this little discussion that just occurred, 49:14.199 --> 49:16.099 social norms play a role too. 49:16.099 --> 49:20.979 This perception that if you're not overweight it means that you 49:20.976 --> 49:25.456 haven't made it or that you're infected with a stigmatized 49:25.460 --> 49:26.720 disease HIV. 49:26.719 --> 49:28.909 All these things are extremely interesting; 49:28.909 --> 49:31.399 all play a complicated role in the process . 49:31.400 --> 53:09.080 53:09.079 --> 53:11.989 Now before we move onto the next segment which deals with a 53:11.987 --> 53:14.847 different country altogether, let's just conclude a little 53:14.846 --> 53:16.196 bit about South Africa. 53:16.199 --> 53:20.289 You get a very clear picture in this scene about how dire the 53:20.289 --> 53:22.879 problem is of obesity and poor diet. 53:22.880 --> 53:26.820 Wasn't it interesting to hear about this special risk posed by 53:26.815 --> 53:29.975 under nourishment to later development and how the 53:29.978 --> 53:33.718 undernourishment at point of life make create elevated risk 53:33.722 --> 53:34.822 in another. 53:34.820 --> 53:38.770 Now we can hope that the world health authorities and other 53:38.773 --> 53:42.463 countries and South Africa itself will pay attention to 53:42.456 --> 53:45.316 this impending crisis and take novel, 53:45.320 --> 53:47.640 creative and bold action to deal with it, 53:47.639 --> 53:51.039 but again, there are traps that countries could fall into, 53:51.039 --> 53:52.069 there are opportunities. 53:52.070 --> 53:54.990 It'll be very interesting to see how this takes place. 53:54.989 --> 53:58.509 Now let's hear about how a different country has dealt with 53:58.512 --> 54:00.642 this issue, in this case Finland. 54:00.639 --> 54:04.989 One of the people interviewed in this particular clip is a 54:04.989 --> 54:09.109 well-known scientist from Finland named Pekka Puska. 54:09.110 --> 54:13.080 He was an incredibly innovative scientist at a time when very 54:13.081 --> 54:16.721 few people were caring about community interventions for 54:16.722 --> 54:20.892 things like heart disease and he pushed and pushed against great 54:20.893 --> 54:23.743 odds to make some changes in Finland. 54:23.739 --> 54:26.389 After he did this, he spent time in Geneva at the 54:26.391 --> 54:29.711 World Health Organization and then more recently has returned 54:29.708 --> 54:33.078 to Finland and he is Minister of Health for the country, 54:33.079 --> 54:36.269 but a very interesting player in this whole picture and he has 54:36.269 --> 54:39.089 helped change to some extent the way the world looks at 54:39.094 --> 54:41.034 intervening with these problems . 54:41.030 --> 57:39.340 57:39.340 --> 57:43.350 That's one key about this project in North Karelia that 57:43.349 --> 57:47.729 Puska ran: that not only are they focusing on the individual 57:47.728 --> 57:50.828 and education, and the sort of typical change 57:50.827 --> 57:53.457 people would think about; but he's talking about 57:53.461 --> 57:56.181 intervening in the environment and making changes. 57:56.179 --> 58:00.339 This is one of the ways that Puska's program differed from 58:00.338 --> 58:04.858 similar programs in the United States that were not having very 58:04.864 --> 58:07.934 impressive results at the time he was. 58:07.929 --> 58:10.519 We'll play this out and you'll hear more about that . 58:10.519 --> 1:04:03.309 1:04:03.309 --> 1:04:08.189 Just you wait, we will see what happens. 1:04:08.190 --> 1:04:11.530 Later in the class we'll talk about what some of these global 1:04:11.527 --> 1:04:12.637 solutions will be. 1:04:12.639 --> 1:04:17.119 You see in a country like North Karelia how--or Finland and that 1:04:17.117 --> 1:04:20.887 North Karelia area in particular--how vexing a problem 1:04:20.885 --> 1:04:25.015 this is because even they, with the amount effort that 1:04:25.018 --> 1:04:28.348 they put in, are having trouble controlling 1:04:28.349 --> 1:04:29.359 the problem. 1:04:29.360 --> 1:04:31.960 Two things I'd like to draw your attention to, 1:04:31.960 --> 1:04:34.620 and then we'll end with today's comedy clip. 1:04:34.619 --> 1:04:39.789 One sign of the change of the diet around the world, 1:04:39.789 --> 1:04:42.919 is what's happening in the Mediterranean part of the world 1:04:42.916 --> 1:04:44.996 and the erosion of that diet which, 1:04:45.000 --> 1:04:47.490 as we explained before, has considerable health 1:04:47.485 --> 1:04:48.075 benefits. 1:04:48.079 --> 1:04:50.829 A number of you--by the way when you guys see things in the 1:04:50.827 --> 1:04:53.667 press or interesting photos or things that you think might be 1:04:53.670 --> 1:04:56.350 helpful for the class, please send them to me--and a 1:04:56.347 --> 1:04:59.097 number of you noted an article that was in The New York 1:04:59.096 --> 1:05:02.226 Times last week that talked about the erosion of the diet. 1:05:02.230 --> 1:05:04.460 In this case the story in the Times, 1:05:04.460 --> 1:05:07.260 which was really quite good, talked about a particular 1:05:07.262 --> 1:05:10.442 island in Greece called Kasteli and what had happened in that 1:05:10.438 --> 1:05:11.018 island. 1:05:11.018 --> 1:05:14.178 They talked about how the traditional food culture that 1:05:14.179 --> 1:05:17.159 had the components of the Mediterranean diet that we 1:05:17.163 --> 1:05:20.503 talked about earlier has been eroded and now there is much 1:05:20.498 --> 1:05:24.128 more imported food, but also Greek versions of the 1:05:24.126 --> 1:05:24.896 fast food. 1:05:24.900 --> 1:05:27.850 So in this case you can see pizza, hamburgers and other 1:05:27.847 --> 1:05:31.177 things on the menu of this place on that particular island. 1:05:31.179 --> 1:05:33.719 That was an interesting anecdotal story, 1:05:33.719 --> 1:05:35.679 The New York Times sent somebody, 1:05:35.679 --> 1:05:37.619 they went there, they talked to people and they 1:05:37.621 --> 1:05:39.861 saw what was happening on the ground in that area, 1:05:39.860 --> 1:05:41.780 but there's also research on this. 1:05:41.780 --> 1:05:45.280 There was a report published in July of this year by the Food 1:05:45.280 --> 1:05:48.780 and Agriculture Organization, which as I mentioned before; 1:05:48.780 --> 1:05:50.950 it's in Rome, but it's part of the United 1:05:50.947 --> 1:05:51.487 Nations. 1:05:51.489 --> 1:05:55.479 This compared 15 European--looked at 15 European 1:05:55.476 --> 1:05:58.806 Union countries, but it took the Mediterranean 1:05:58.813 --> 1:06:01.373 countries that were in this sample Spain, 1:06:01.369 --> 1:06:03.719 Greece, and Italy and compared it to the others. 1:06:03.719 --> 1:06:06.839 If you'd like to see the whole report the website is listed 1:06:06.838 --> 1:06:07.268 there. 1:06:07.268 --> 1:06:10.248 They looked at how things were changing in those particular 1:06:10.251 --> 1:06:12.731 countries, so if you look at all the EU 1:06:12.728 --> 1:06:16.668 countries combined on the left and the Mediterranean countries 1:06:16.670 --> 1:06:20.670 on the right, and then you see what happened 1:06:20.673 --> 1:06:24.743 between 1963 and 2003 was sodium intake, 1:06:24.739 --> 1:06:26.949 was salt intake, here is the picture that you 1:06:26.947 --> 1:06:27.247 get. 1:06:27.250 --> 1:06:32.050 In 1963 the Mediterranean countries were looking better 1:06:32.045 --> 1:06:37.725 then the rest of the EU as a group in terms of sodium intake, 1:06:37.730 --> 1:06:41.340 but in 2003 you can see what's happened in both sets of 1:06:41.338 --> 1:06:42.138 countries. 1:06:42.139 --> 1:06:44.319 The sodium intake has gone way the heck up. 1:06:44.320 --> 1:06:46.130 That's a really remarkable increase. 1:06:46.130 --> 1:06:48.670 The number is much higher then health authorities would 1:06:48.666 --> 1:06:49.226 recommend. 1:06:49.230 --> 1:06:53.340 The advantage of the Mediterranean diet is--or the 1:06:53.335 --> 1:06:57.855 people living in those countries is still apparent, 1:06:57.860 --> 1:07:01.640 but not nearly what it was before, and so there are real 1:07:01.641 --> 1:07:02.811 problems there. 1:07:02.809 --> 1:07:07.379 That represents a 50% increase, 64% increase over here. 1:07:07.380 --> 1:07:11.090 So the Mediterranean part of the EU is starting to catch up 1:07:11.094 --> 1:07:12.124 to the others. 1:07:12.119 --> 1:07:15.409 If you look at the number of calories per day, 1:07:15.411 --> 1:07:20.021 per person in these countries you get interesting phenomenon. 1:07:20.018 --> 1:07:22.628 Let's look at these three countries Italy, 1:07:22.630 --> 1:07:25.690 Greece, and Spain, to see what happened over that 1:07:25.688 --> 1:07:26.898 period of time. 1:07:26.900 --> 1:07:30.540 Here's Spain, the number of calories per day, 1:07:30.539 --> 1:07:33.539 per person--now again that's happening at the same time 1:07:33.539 --> 1:07:37.149 physical activity is declining, so we can't be surprised by 1:07:37.146 --> 1:07:38.606 problems with disease. 1:07:38.610 --> 1:07:43.600 The numbers for Italy look like this, and then the numbers for 1:07:43.603 --> 1:07:45.573 Greece look like this. 1:07:45.570 --> 1:07:50.440 1:07:50.440 --> 1:07:52.480 When you put all this together--I'm going to skip this 1:07:52.480 --> 1:07:54.290 but it'll be in--you'll see it in the slides. 1:07:54.289 --> 1:07:57.729 There are a number of hypothesized reasons for it. 1:07:57.730 --> 1:08:00.480 Things that we talked about some today but we'll talk about 1:08:00.476 --> 1:08:01.846 later in the class as well. 1:08:01.849 --> 1:08:07.089 There are now many studies on this particular topic. 1:08:07.090 --> 1:08:10.430 This one in particular talks about North India and it talks 1:08:10.431 --> 1:08:14.001 about how men in the rural areas of North India have five times 1:08:14.003 --> 1:08:17.323 the physical activity, more obesity in the urban areas 1:08:17.322 --> 1:08:19.542 as the clip on South Africa suggested. 1:08:19.538 --> 1:08:23.188 Here's another example of a study that was done in the 1:08:23.185 --> 1:08:24.695 Amazon area of Peru. 1:08:24.698 --> 1:08:28.458 They found, in this case, that the more people adhered to 1:08:28.456 --> 1:08:31.806 a traditional diet the healthier their diet was. 1:08:31.810 --> 1:08:35.560 And then this was a paper that was in your readings that talked 1:08:35.561 --> 1:08:39.071 about the New World Order and how colonization is having an 1:08:39.073 --> 1:08:42.773 impact and there's a quote that I don't need to repeat because 1:08:42.765 --> 1:08:45.975 it was in the paper, but it shows pretty clearly 1:08:45.979 --> 1:08:47.619 what's happening worldwide. 1:08:47.618 --> 1:08:50.578 I hope what we've painted today is a picture that shows that 1:08:50.577 --> 1:08:53.477 there's great reason to be concerned about what's happening 1:08:53.484 --> 1:08:55.744 worldwide: opportunities and challenges, 1:08:55.738 --> 1:08:57.968 but certainly places where we can intervene. 1:08:57.970 --> 1:09:03.000