WEBVTT

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Prof: The topic today is
the nutrition transition and

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global food issues.

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When you talk about how food
affects people,

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enters the body,
has an impact on health,

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on economies,
and things like that,

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things get really interesting
when you take a global point of

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view.

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The global politics affect food
as you heard when we talked

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about hunger.

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Global economics affects the
availability of food in the

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prices around the world,
and at one point food was so

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local that what happened to the
food world in one part of the

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world didn't really affect very
much what happened elsewhere in

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the world but those days are
gone.

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Now things like American
subsidies to the corn farmers

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have enormous impact on what's
happening worldwide.

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We'll talk more about that in
the economics lecture.

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Today we're going to talk about
what the picture looks like

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around the world and how diets
have changed in countries

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outside the U.S.

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and what are some of the
driving factors that have made

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this happen.

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Today we're going to talk about
how there are changes in the

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global disease burden.

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As I've alluded to in earlier
classes,

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the nature of diseases that
cultures are exposed to and

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countries must confront because
of the impact of disease on the

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economy,
on healthcare costs,

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on productivity,
on the size of the workforce

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when you have major diseases
killing a lot of people,

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you see how important these are
and the global burden,

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the global distribution of
diseases have changed.

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We're going to talk about
changes in diet and obesity in

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particular, and then I'd like to
give you four case studies.

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We'll talk about China,
India, South Africa and

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Finland, all different from each
other in some ways,

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but all affected by the same
world market forces.

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It'll be interesting to go
through this.

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Certainly world health is in
transition.

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The non-communicable diseases,
NCD, are now overriding the

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communicable diseases.

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In some countries there's a
double burden where both occur

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in very large numbers.

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Now as I've mentioned before,
communicable diseases would be

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traditional infectious diseases
where people get a specific

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disease from an agent in the
environment.

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The non-communicable diseases
are ones that people don't catch

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from something in the
environment or from some--or

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from another person but diseases
that are caused mainly by

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lifestyle,
which can also be toxic as I've

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described before.

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The diets are changing around
the world, but not only are

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diets changing,
physical activity patterns are

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changing.

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This in turn affects diet,
it certainly affects body

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weight.

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The aging of the population,
especially in certain countries

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of the world is changing the
healthcare picture,

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and globalization is having a
massive impact.

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As we'll talk about later in
the class,

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if you take something like food
marketing,

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there was once a time when if a
country had the will to do

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something about food marketing,
it could control what was going

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on within its borders because
there wasn't much marketing

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leaking in from the outside,
or overwhelming what a country

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might be doing on its own.

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But those times are different
with the internet,

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satellite television,
etc., the ability of a country

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to even control what's going on
on the airwaves or over the

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computer is very limited.

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Some people may say that's a
good thing,

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say in countries that don't
have much freedom,

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that the leakage from the
internet from the outside

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actually helps inform people and
is a good thing overall.

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But there may be some negative
consequences in terms of food

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marketing and things like that.

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The global picture is changing
to be sure.

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Now some of the changes are
pretty obvious and we've

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discussed or alluded to before.

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The world is changing from
local eating to global eating

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and that change has had profound
impacts.

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As I said before,
the relationship people used to

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have with food was that they
were close to where it was

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grown,
they might know the person who

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grew it;
if not they knew the person who

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bought it from the person who
grew it,

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and then they prepared it and
they and their families ate it

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and there weren't many steps
between the origination of the

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food and the metabolism of the
food,

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but now many steps lie in
between and more and more people

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in the world are dependent on
food from outside their local

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area.

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This is affected by national
and international policies to

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some extent.

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We'll give you some examples of
that today.

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The local traditions have
yielded to families eating out,

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eating large amounts of food,
and subsisting on an abundance

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of food when it's available,
usually at low cost and this

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has pretty--by now pretty
predictable consequences.

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The markets have changed,
where people buy foods has

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changed a lot around the world,
so in many parts of the world

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you still see the kind of
pictures that are on the left,

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but more and more you're seeing
the pictures on the right.

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Now, it's a very interesting
issue about whether having

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access to what you see on the
right is a good thing.

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We will talk in this class
about how in the United States

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poor people tend not to have
access to what you see on the

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right,
nor to what you see on the left.

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But what they have access to
are small markets in inner city

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neighborhoods that charge high
prices for low quality food.

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That access becomes a problem
and so bringing in something

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like you see on the right
becomes an asset.

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In the developing world it
appears, from what little we

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know about this so far,
the picture may be different.

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That large markets that have
many choices of processed,

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packaged, and in many cases
imported foods tend to undermine

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local food traditions,
get people away from eating

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what they might have been eating
naturally,

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and give them access to a wide
variety of foods that are less

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desirable than what they were
eating before,

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because they're more nutrient
poor and more calorie dense.

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There are differences depending
on where you live in the world.

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The issue of choice is
interesting.

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As I mentioned before in class,
very often when people come to

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the United States--in fact one
of our students in the videotape

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mentioned this before--they're
amazed by the number of choices

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and by the size of things that
they were exposed too,

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but people come to the U.S.

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and they see a hundred
different salad dressings in a

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supermarket,
50 different yogurts,

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cereals that would fill up a
whole aisle with dozens and

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dozens of choices.

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When people come and are
confronted by this,

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it's interesting to see how
they respond.

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Very often people from other
countries say,

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well why do you need that many
choices?

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I mean what's wrong with five
salad dressings and what's wrong

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with six yogurts,
and what's wrong with ten

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cereals?

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We have so many that we have
this flood of choice that

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Americans believe is a good
thing because the word choice

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gets connected conceptually with
freedom and all that sort of

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thing;
that the idea of restricting

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choice becomes pretty taboo in
our country.

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In fact, there is some
researchers who have studied

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this issue of choice.

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Very often people confronted by
choices, where they have too

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many choices,
don't function well

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psychologically.

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It becomes more difficult to
make good decisions in the face

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of a vast array of choices,
when a small number of choices

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would have done.

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So this paradox of choice
confronts Americans because we

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have so many choices,
but it's beginning to happen

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elsewhere in the world and
people around the world are now

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facing this sort of paradox of
choice where at first glance it

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seems like a good thing,
but in fact,

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may not be, especially when it
erodes local customs.

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Transportation is changing a
lot and this is changing the

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physical activity picture.

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Getting around like this has
yielded to getting around like

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this, and the number of people
in the world who are now moving

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by motorized transport;
even in countries like China

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has gone way up.

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And this has had a major effect
on physical inactivity.

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Here's an example of this
again, so if you look at China

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on the left you see pictures of
everybody on a bicycle for the

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most part;
and on the right vast numbers

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of people in cars,
but even more so on motor

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scooters.

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There's some research done in
China showing that when families

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secure a motor scooter--which is
more and more possible because

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of the increasing wealth in the
country--the likelihood of

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people being overweight in the
family goes up.

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Even people that are not the
primary users of the scooter,

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so these things tend to have
these cascading effects that are

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very interesting.

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Now let's talk about physical
activity in our own lives and

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you can see how this is going
into the modern environment.

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I mean, my guess is that very
few of you have ever even been

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inside an automobile where you
have to crank the window with

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something like this.

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Mainly everything's done with
an electronic button.

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There used to be a time when to
tune the radio you actually had

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to turn a knob rather then just
press a button.

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Of course, think of the remote
control that saves you many,

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many, many trips a year from a
chair to a television to change

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the station.

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Each of those,
in their own right,

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may not add up to a lot.

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But if you take the cumulative
effect of all those type of

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things,
and those are just examples,

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you have an enormous amount of
energy people used to spend in

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day to day life that they're now
not.

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Add to that the fact that many
jobs now are not physically

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demanding because of the use of
technologies and computers,

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and robots and manufacturing,
and on and on,

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and on.

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You see that the population
physical activity has declined a

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lot in the United States and
elsewhere in the world.

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In the United States,
it used to be the case that you

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were paid to exercise.

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It was called your job.

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Now people pay to exercise in
several ways.

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You join a club,
you buy exercise equipment,

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but you pay an opportunity cost
because of the crazed lifestyle

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everybody lives.

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If you take time to be
physically active it's time that

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you could otherwise be doing
other things.

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You could do other leisure
things, you could rest,

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you could spend time with your
family,

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you could get more work done,
there are a lot of different

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things that compete with
exercise,

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so the fact that it used to be
crammed into your day to day

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life by necessity is no longer
the case so much,

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and this is happening around
the world.

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The number of people in
countries like China who have a

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television,
who have motorized transport

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has increased a lot and this is
combining with the changing food

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environment to create great
risk.

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If we look at things that
really--the lifestyle factors

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that drive the non-communicable
diseases,

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the three big ones are smoking,
obesity,

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and physical inactivity;
and then diet would fall under

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the obesity thing.

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In the developing world you're
basically seeing these changes

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happen and then we can't be
surprised that diseases fall

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from this.

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So these are big problems
around the world.

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We're not talking about tobacco
in this particular class,

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but boy if we did would there
be a story to tell.

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Vast numbers of people smoking
in the developing world,

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just like they are eating a bad
diet,

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being physically inactive,
and getting the same diseases

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that have plagued the United
States and that's happening

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around the world as well.

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We'll also talk about food
industry behavior,

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because a lot of the growth of
some of the American food

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companies,
especially the fast food

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restaurants,
are occurring outside the

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U.S. It's not as if the U.S.

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market is completely saturated,
because there's always more

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space to cram in fast food
restaurants, but we're probably

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approaching saturation.

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Each of the companies is having
trouble building a lot because

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they're competing with all the
other fast food restaurants.

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But that's not true overseas,
so a lot of the growth in some

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of these companies is outside
the U.S.

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border as exactly happened with
the tobacco industry.

12:41.330 --> 12:44.610
The tobacco industry got
hammered by lawsuits and by

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government regulations and bad
publicity in the United States;

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they took their business
overseas and have made enormous

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amounts of money imperiling the
health of people outside the

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U.S.

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borders.

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The food industry has been
accused by some people of doing

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similar things.

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Let's look at the changing
burden of disease across the

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world.

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If you look at how disease is
spread--the diseases are spread

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across different parts of the
world,

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and this graph will be a little
hard to see because it's not

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that big,
but you can see it when you

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pull it up on the web.

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The red represents high
mortality developing countries,

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low mortality developing
countries are the white,

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and then the medium blue are
developed countries.

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At the top of the list you see
up there the total burden

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is--that's yellow in the
middle--is blood pressure.

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Now high blood pressure and
we'll come back to some

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more--some recent data on this
is contributing to lots of

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different diseases and seems to
be the number one factor that

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one might intervene (second with
tobacco following close behind)

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that you could do something
about to lower the number of

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deaths worldwide.

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These various things are spread
across different countries or

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different parts of the SES
spectrum with countries,

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socioeconomic class,
spectrum across different

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countries in interesting ways.

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If you look at all the things
here,

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the top things,
blood pressure,

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tobacco,
cholesterol,

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underweight,
unsafe sex,

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fruit and vegetable intake,
high body mass index,

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physical inactivity,
alcohol, all those things are

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driven by lifestyle.

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Now the hunger less so because
that's a--that can be a problem

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with food access,
but the rest of the things are

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driven by choices people make in
their lives and those in turn

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are affected by government
policy and a variety of broad

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and powerful factors.

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So it certainly makes sense if
we want to make the world

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healthier to think about these
chronic diseases and about the

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diseases that are driven by
lifestyle,

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and in the case of our class
we're talking about this with

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diet.

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Here's a very interesting
graphic that depicts this

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changing global burden of
disease.

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This is a chart that shows the
leading causes of death in rural

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China.

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Total population 813 million
people-very large numbers of

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people.

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I'm going to show you this
graphic that has little people

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figures and each figure
represents a certain number of

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deaths.

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It doesn't matter so much
exactly how many deaths,

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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.

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I hope what we've painted today
is a picture that shows that

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there's great reason to be
concerned about what's happening

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worldwide: opportunities and
challenges,

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but certainly places where we
can intervene.

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