00:00:36.556 --> 00:00:40.014
[MUSIC PLAYING]

00:00:40.014 --> 00:01:08.560


00:01:08.560 --> 00:01:11.805
So I'm going to
start on the lasagna.

00:01:11.805 --> 00:01:16.010
For the noodles
we have marinated

00:01:16.010 --> 00:01:19.400
zucchini, fresh
oregano, and thyme.

00:01:19.400 --> 00:01:24.720
It's getting layers of pistachio
basil pesto, sun-dried tomato

00:01:24.720 --> 00:01:25.220
marinara.

00:01:25.220 --> 00:01:27.860


00:01:27.860 --> 00:01:32.490
Dinnertime, the sights, the
smells, the tastes, of foods

00:01:32.490 --> 00:01:34.090
we are fond of.

00:01:34.090 --> 00:01:36.050
They are like old friends.

00:01:36.050 --> 00:01:38.330
Foods we have grown
up with that are

00:01:38.330 --> 00:01:41.600
central to our social
experiences, and part

00:01:41.600 --> 00:01:44.376
of the pleasure of
our daily lives.

00:01:44.376 --> 00:01:46.250
Food is a love we all share.

00:01:46.250 --> 00:01:54.950


00:01:54.950 --> 00:01:57.890
Our ravioli is one
our signature dishes.

00:01:57.890 --> 00:02:00.830
Flax crackers and reduced
tomato with a very sweet

00:02:00.830 --> 00:02:02.300
white vinaigrette
under the bottom.

00:02:02.300 --> 00:02:03.280
Enjoy.

00:02:03.280 --> 00:02:05.350
But not all love
affairs are good for us.

00:02:05.350 --> 00:02:10.000
And sometimes too much of a
good thing comes at a cost.

00:02:10.000 --> 00:02:11.760
While chefs compete
to please our ever

00:02:11.760 --> 00:02:14.330
demanding palates and farmers
strive to keep our dinner

00:02:14.330 --> 00:02:18.620
plates full, others are worried
about the impact of all this.

00:02:18.620 --> 00:02:21.986
Is our love affair with food,
in particular our love of meat

00:02:21.986 --> 00:02:26.196
and dairy, good for our health
and the future of the planet?

00:02:26.196 --> 00:02:29.830
What we've got here is a
seitan in a mushroom stock.

00:02:29.830 --> 00:02:32.940
And it gets served with
mushrooms, peppers, tomatoes,

00:02:32.940 --> 00:02:35.660
onions on a skewer,
mashed potatoes,

00:02:35.660 --> 00:02:37.950
roasted with cabbage
with strawberry jam,

00:02:37.950 --> 00:02:40.620
and red wine, served
with a mushroom sauce,

00:02:40.620 --> 00:02:42.660
and sprouting broccoli.

00:02:42.660 --> 00:02:51.354


00:02:51.354 --> 00:02:57.170
[MUSIC PLAYING]

00:02:57.170 --> 00:03:03.040
I got into nutrition with
certain ideas in mind.

00:03:03.040 --> 00:03:08.290
More or less the same as
what the public tend to have.

00:03:08.290 --> 00:03:11.170
But I've been around quite a
while, seeing a lot of things.

00:03:11.170 --> 00:03:13.662
Had a research program at
Cornell University and Virginia

00:03:13.662 --> 00:03:14.745
Tech for many, many years.

00:03:14.745 --> 00:03:18.430


00:03:18.430 --> 00:03:21.720
For about 20 years I was on
various and sundry expert

00:03:21.720 --> 00:03:25.400
panels in Washington,
in London, and helping

00:03:25.400 --> 00:03:29.050
to write national policy.

00:03:29.050 --> 00:03:32.170
And I have to tell you
that my views today

00:03:32.170 --> 00:03:37.230
are dramatically different than
what they were 51 years ago.

00:03:37.230 --> 00:03:40.370


00:03:40.370 --> 00:03:42.580
In the '60s I had an
opportunity of being

00:03:42.580 --> 00:03:44.580
a coordinator of a
nationwide program of feeding

00:03:44.580 --> 00:03:46.514
malnourished children
in the Philippines,

00:03:46.514 --> 00:03:48.180
working with a senior
colleague, and was

00:03:48.180 --> 00:03:51.720
with the US embassy at the time.

00:03:51.720 --> 00:03:53.890
I went to the
Philippines to help

00:03:53.890 --> 00:03:57.230
to deal with the childhood
malnutrition problems.

00:03:57.230 --> 00:04:00.530
In my early days I was
enamored with the idea

00:04:00.530 --> 00:04:03.580
that protein was very important.

00:04:03.580 --> 00:04:06.570
In particular
animal-based protein,

00:04:06.570 --> 00:04:09.300
protein from animal sources.

00:04:09.300 --> 00:04:13.170
And so when I went to the
Philippines, of course,

00:04:13.170 --> 00:04:15.675
we are interested in making
sure the Philippine children got

00:04:15.675 --> 00:04:16.300
enough protein.

00:04:16.300 --> 00:04:20.430


00:04:20.430 --> 00:04:24.030
My surgeon colleague
told me one day

00:04:24.030 --> 00:04:28.295
that he was operating on
children four years of age

00:04:28.295 --> 00:04:30.315
and younger for
primary liver cancer.

00:04:30.315 --> 00:04:34.140


00:04:34.140 --> 00:04:37.290
This cancer almost entirely
occurs in older people

00:04:37.290 --> 00:04:39.820
not children.

00:04:39.820 --> 00:04:40.870
I started asking around.

00:04:40.870 --> 00:04:44.560
And I got the impression,
mostly an impression.

00:04:44.560 --> 00:04:46.550
I got the impression
that the children most

00:04:46.550 --> 00:04:49.770
likely to get the
liver cancer were

00:04:49.770 --> 00:04:53.280
coming from the few families
who were consuming the most

00:04:53.280 --> 00:04:54.720
protein.

00:04:54.720 --> 00:04:58.490
You can understand,
that's in stark contrast

00:04:58.490 --> 00:05:01.420
to what I believe.

00:05:01.420 --> 00:05:04.607
That's why I wanted
to do the research.

00:05:04.607 --> 00:05:08.100
[MUSIC PLAYING]

00:05:08.100 --> 00:05:18.580


00:05:18.580 --> 00:05:21.490
I have actually traditional
cooking background.

00:05:21.490 --> 00:05:24.910
I worked in French oriented
restaurants, Italian,

00:05:24.910 --> 00:05:26.650
and I came here
because as a chef

00:05:26.650 --> 00:05:29.060
it's amazing to have the
opportunity to always

00:05:29.060 --> 00:05:31.370
be working with the
most vibrant, colorful,

00:05:31.370 --> 00:05:34.147
beautiful vegetables.

00:05:34.147 --> 00:05:35.730
Most of the dishes
we're creating here

00:05:35.730 --> 00:05:40.700
are reworking some traditional
dishes from different cuisines.

00:05:40.700 --> 00:05:44.930
We have lasagna, we have
biryani, we have sushi.

00:05:44.930 --> 00:05:47.000
This is our sushi
rice, which is made

00:05:47.000 --> 00:05:51.750
from jicama and a little
bit of brown rice vinegar.

00:05:51.750 --> 00:05:52.875
There's shiitake mushrooms.

00:05:52.875 --> 00:05:56.775


00:05:56.775 --> 00:05:59.650
Put a few purple
daikon sprouts in here.

00:05:59.650 --> 00:06:02.608
[MUSIC PLAYING]

00:06:02.608 --> 00:06:20.740


00:06:20.740 --> 00:06:23.330
I grew up on a
kibbutz in Israel.

00:06:23.330 --> 00:06:28.480
I had a beef cattle
ranch, farm operation.

00:06:28.480 --> 00:06:35.330
And I was certain that my life
is going to be feeding cows.

00:06:35.330 --> 00:06:39.290
At the University I fell in love
with the applied mathematics,

00:06:39.290 --> 00:06:42.810
and spend the next
15 or so years

00:06:42.810 --> 00:06:45.095
doing nothing but traditional
[INAUDIBLE] physics.

00:06:45.095 --> 00:06:49.510


00:06:49.510 --> 00:06:53.670
It dawned on me that I can
combine my agricultural past

00:06:53.670 --> 00:06:55.680
and my [INAUDIBLE]
physical present

00:06:55.680 --> 00:06:58.220
into a single line
of research, that

00:06:58.220 --> 00:07:00.600
addresses the integrity of
the natural environment.

00:07:00.600 --> 00:07:03.708
[MUSIC PLAYING]

00:07:03.708 --> 00:07:12.140


00:07:12.140 --> 00:07:15.510
Food is an important
contributor to global warming.

00:07:15.510 --> 00:07:20.630
Is an important contributor
to surface water pollution.

00:07:20.630 --> 00:07:23.800
It is an important
contributor to air pollution.

00:07:23.800 --> 00:07:27.510
So whenever you eat
something you indirectly

00:07:27.510 --> 00:07:31.950
exert burden on
the natural world.

00:07:31.950 --> 00:07:36.130
It is clear that we cannot
continue the way we have.

00:07:36.130 --> 00:07:38.190
So what do we go after?

00:07:38.190 --> 00:07:40.150
What do we change first?

00:07:40.150 --> 00:07:42.730


00:07:42.730 --> 00:07:45.845
[MUSIC PLAYING]

00:07:45.845 --> 00:07:54.800


00:07:54.800 --> 00:07:57.320
I would say the most
important ingredients

00:07:57.320 --> 00:08:00.990
for this kitchen, organic
fresh vegetables I think is,

00:08:00.990 --> 00:08:04.580
of course, and probably the
most also important ingredient.

00:08:04.580 --> 00:08:10.170
All our produce that we use
here is sourced locally,

00:08:10.170 --> 00:08:11.290
as organic as possible.

00:08:11.290 --> 00:08:17.190


00:08:17.190 --> 00:08:21.410
I'm a South African so we
use a lot of red meats.

00:08:21.410 --> 00:08:25.530
And then about three
years ago I fell in love

00:08:25.530 --> 00:08:27.350
with a woman that
was a vegetarian.

00:08:27.350 --> 00:08:29.270
And I saw the good
side of vegetarians.

00:08:29.270 --> 00:08:30.500
I gave up meats.

00:08:30.500 --> 00:08:32.919
I don't touch any
animal products at all.

00:08:32.919 --> 00:08:33.580
And I love it.

00:08:33.580 --> 00:08:36.555
It's been a challenge for
me, but it's been amazing.

00:08:36.555 --> 00:08:40.293
[MUSIC PLAYING]

00:08:40.293 --> 00:08:50.925


00:08:50.925 --> 00:08:55.470
OK, this is my favorite dish
on the menu, root veg tart.

00:08:55.470 --> 00:08:58.310
We've got to tart shell here,
which we make up every day.

00:08:58.310 --> 00:09:01.120
We do about 40 of them a day.

00:09:01.120 --> 00:09:04.000
The bases of them are
buckwheat, and all the root

00:09:04.000 --> 00:09:07.215
veg you can think of in England,
turnips, sweets, carrots.

00:09:07.215 --> 00:09:11.300
And then we'll fill it
with cashew, spinach cream.

00:09:11.300 --> 00:09:15.020
And then we'll top them
with a herb tomato.

00:09:15.020 --> 00:09:18.450
[MUSIC PLAYING]

00:09:18.450 --> 00:09:33.650


00:09:33.650 --> 00:09:37.250
In 1975 Colin Campbell
returned from his work

00:09:37.250 --> 00:09:40.380
in the Philippines to embark
on a groundbreaking research

00:09:40.380 --> 00:09:44.700
program that would continue
for nearly 30 years.

00:09:44.700 --> 00:09:48.650
I organized a proposal for the
National Institutes of Health

00:09:48.650 --> 00:09:52.290
to explore the
relationship specifically

00:09:52.290 --> 00:09:56.150
between protein intake and
the formation of primary liver

00:09:56.150 --> 00:09:58.010
cancer in rats.

00:09:58.010 --> 00:10:00.520
Does protein, as it's
increased, does that

00:10:00.520 --> 00:10:01.824
increase cancer growth rates?

00:10:01.824 --> 00:10:02.740
That was the question.

00:10:02.740 --> 00:10:07.231
[MUSIC PLAYING]

00:10:07.231 --> 00:10:09.850
In a series of
experiments rats were

00:10:09.850 --> 00:10:12.260
exposed to a cancer
causing chemical

00:10:12.260 --> 00:10:14.530
and put on a controlled diet.

00:10:14.530 --> 00:10:18.790
They were alternately fed 20%
or 5% of their total calories

00:10:18.790 --> 00:10:20.440
from protein.

00:10:20.440 --> 00:10:23.090
When the rats are
fed 20% protein

00:10:23.090 --> 00:10:25.650
their tumors started to grow.

00:10:25.650 --> 00:10:28.420
When they were switched
to a 5% protein diet

00:10:28.420 --> 00:10:31.440
their tumors
dramatically reduced.

00:10:31.440 --> 00:10:34.430
These experiments were conducted
with different carcinogens,

00:10:34.430 --> 00:10:37.550
different species, and
focused on different cancers.

00:10:37.550 --> 00:10:40.630
And Campbell kept
getting similar results.

00:10:40.630 --> 00:10:43.220
We could essentially turn on
and turn off experimental cancer

00:10:43.220 --> 00:10:47.660
development, just by modest
changes in nutrient intake.

00:10:47.660 --> 00:10:48.820
In this case protein.

00:10:48.820 --> 00:10:51.750
Now I think you would agree
that's pretty striking.

00:10:51.750 --> 00:10:55.000
The protein that we
were using was casein.

00:10:55.000 --> 00:10:58.240
Casein is the chief
protein in cow's milk.

00:10:58.240 --> 00:11:00.690
Oh my gosh, I'm mean I'm
talking about something here

00:11:00.690 --> 00:11:02.230
very sacred now.

00:11:02.230 --> 00:11:04.400
In contrast if we use
soy protein and wheat

00:11:04.400 --> 00:11:06.630
protein, even when we
were feeding at the higher

00:11:06.630 --> 00:11:09.590
level, the 20%, we couldn't
turn on the cancer.

00:11:09.590 --> 00:11:12.510
Campbell's experiment
showed this in rats protein

00:11:12.510 --> 00:11:15.260
from dairy products
promoted cancer growth.

00:11:15.260 --> 00:11:19.230
But protein from plants
like soy and wheat did not.

00:11:19.230 --> 00:11:21.340
Even when fed at the same level.

00:11:21.340 --> 00:11:24.000
All plant proteins
are somewhat limiting

00:11:24.000 --> 00:11:25.910
in certain amino acids.

00:11:25.910 --> 00:11:28.840
And so we said, OK wheat
doesn't turn on cancer,

00:11:28.840 --> 00:11:30.740
for example, wheat protein.

00:11:30.740 --> 00:11:33.450
It misses an amino
acid called lysine.

00:11:33.450 --> 00:11:35.950
Let's put the lysine
back in there.

00:11:35.950 --> 00:11:39.080
So that it's amino acid
profile is like the casein.

00:11:39.080 --> 00:11:41.420
When we did that we
turned on cancer.

00:11:41.420 --> 00:11:44.065
From that perspective
there's a good hypothesis

00:11:44.065 --> 00:11:46.780
say that animal proteins
as a cluster, as a group,

00:11:46.780 --> 00:11:49.885
promote cancer, like casein
did, as opposed to the plant

00:11:49.885 --> 00:11:50.385
proteins.

00:11:50.385 --> 00:11:53.030


00:11:53.030 --> 00:11:58.480
This is striking for me, because
I came from a dairy farm.

00:11:58.480 --> 00:12:01.448
And I milked cows until
I want away to school.

00:12:01.448 --> 00:12:04.373
[MUSIC PLAYING]

00:12:04.373 --> 00:12:08.240


00:12:08.240 --> 00:12:09.790
My father had been
a dairy farmer.

00:12:09.790 --> 00:12:12.965
And all the people in my family
were farmers and dairy farmers

00:12:12.965 --> 00:12:15.270
from Northern Ireland
and Scotland essentially.

00:12:15.270 --> 00:12:19.080
So I mean, I was just totally
into the farm life, 100%.

00:12:19.080 --> 00:12:20.640
We butchered our own animals.

00:12:20.640 --> 00:12:22.040
We collected our own eggs.

00:12:22.040 --> 00:12:23.450
I did some fishing.

00:12:23.450 --> 00:12:23.976
I hunted.

00:12:23.976 --> 00:12:26.698
[MUSIC PLAYING]

00:12:26.698 --> 00:12:30.085


00:12:30.085 --> 00:12:32.320
And then I went away
to graduate school

00:12:32.320 --> 00:12:35.080
to try to promote that
idea, that finding ways

00:12:35.080 --> 00:12:38.230
to produce animal protein more
effectively and efficiently

00:12:38.230 --> 00:12:39.505
was a good idea.

00:12:39.505 --> 00:12:42.230
We could help to solve
problems in the world.

00:12:42.230 --> 00:12:46.820
And what my research became
was quite counter to that.

00:12:46.820 --> 00:12:49.790
[MUSIC PLAYING]

00:12:49.790 --> 00:12:54.740


00:12:54.740 --> 00:12:57.160
It was hard to just
accept the animal studies.

00:12:57.160 --> 00:12:59.510
And then turn around and say
it's something really major

00:12:59.510 --> 00:13:00.740
about human health.

00:13:00.740 --> 00:13:03.710
But we could not have
done this study in humans.

00:13:03.710 --> 00:13:08.020
Impossible,
absolutely impossible.

00:13:08.020 --> 00:13:12.720
It's like tobacco smoking
and lung cancer, for example.

00:13:12.720 --> 00:13:15.310
We've never really
done the study.

00:13:15.310 --> 00:13:16.860
To take a group
of people and say,

00:13:16.860 --> 00:13:18.320
you smoke for the next 10 years.

00:13:18.320 --> 00:13:20.296
You smoke as much
as you possibly can.

00:13:20.296 --> 00:13:21.670
Then take another
group of people

00:13:21.670 --> 00:13:23.860
and say, no you don't smoke.

00:13:23.860 --> 00:13:25.890
We haven't done
that kind of study.

00:13:25.890 --> 00:13:29.340
In theory that's
what science demands.

00:13:29.340 --> 00:13:31.720
What Campbell needed
was the chance

00:13:31.720 --> 00:13:34.750
to study a human
population to see

00:13:34.750 --> 00:13:39.000
if there was the relationship
between diet and cancer.

00:13:39.000 --> 00:13:42.005
And soon he was
going to get to it.

00:13:42.005 --> 00:13:42.995
Guys, we're open.

00:13:42.995 --> 00:13:46.460
[MUSIC PLAYING]

00:13:46.460 --> 00:13:53.400


00:13:53.400 --> 00:13:56.120
I have sensitivities to dairy.

00:13:56.120 --> 00:13:59.750
And there really wasn't anything
out there for me to have,

00:13:59.750 --> 00:14:02.450
and especially no
bakery for me to go to.

00:14:02.450 --> 00:14:04.410
And I knew that I wasn't alone.

00:14:04.410 --> 00:14:06.880
And I knew that there were
plenty of other people

00:14:06.880 --> 00:14:09.020
who wanted to eat
desserts that taste good.

00:14:09.020 --> 00:14:13.610
[MUSIC PLAYING]

00:14:13.610 --> 00:14:16.480
We're free of all animal
products and by-products.

00:14:16.480 --> 00:14:20.392
So all casein, lactose, dairy,
everything under that umbrella.

00:14:20.392 --> 00:14:24.310
[MUSIC PLAYING]

00:14:24.310 --> 00:14:26.440
I didn't know
anything about baking.

00:14:26.440 --> 00:14:27.730
I taught myself.

00:14:27.730 --> 00:14:31.040
And they were not delicious
is the beginning, I must say.

00:14:31.040 --> 00:14:32.990
But I ate them anyways.

00:14:32.990 --> 00:14:36.880
But I think that if people
have an intuitive connection

00:14:36.880 --> 00:14:41.780
with ingredients, and baking,
and making food in general,

00:14:41.780 --> 00:14:42.730
there's always a way.

00:14:42.730 --> 00:14:47.510
[MUSIC PLAYING]

00:14:47.510 --> 00:14:49.710
I just put in baking powder.

00:14:49.710 --> 00:14:51.536
And now I'm putting in salt.

00:14:51.536 --> 00:14:54.570


00:14:54.570 --> 00:14:58.454
There are no eggs in
the recipes so I'll also

00:14:58.454 --> 00:15:00.700
put a little xanthan gum in.

00:15:00.700 --> 00:15:03.296
It's actually a bacteria that
binds the liquids and the dries

00:15:03.296 --> 00:15:03.796
together.

00:15:03.796 --> 00:15:07.240
[MUSIC PLAYING]

00:15:07.240 --> 00:15:15.630


00:15:15.630 --> 00:15:18.300
People will come in and they're
really skeptical, because of,

00:15:18.300 --> 00:15:21.020
oh there's no sugar in
it, there's no-- you know,

00:15:21.020 --> 00:15:22.130
what's in it?

00:15:22.130 --> 00:15:23.180
No flavor?

00:15:23.180 --> 00:15:26.590
And you just sort of coax
them into, well just try it.

00:15:26.590 --> 00:15:28.780
And then I don't
have to talk anymore.

00:15:28.780 --> 00:15:30.530
Because you put it in
your mouth, and then

00:15:30.530 --> 00:15:31.552
they're like, oh, OK.

00:15:31.552 --> 00:15:35.038
[MUSIC PLAYING]

00:15:35.038 --> 00:15:55.970


00:15:55.970 --> 00:15:59.130
Nothing changes the face of
the planet as much as the way

00:15:59.130 --> 00:16:00.670
we produce our food.

00:16:00.670 --> 00:16:05.440
And since that has such a big
impact on the environment,

00:16:05.440 --> 00:16:08.630
on other people, and
of course on billions

00:16:08.630 --> 00:16:10.710
of non-human
animals, I think you

00:16:10.710 --> 00:16:12.560
have to think of this
as an ethical issue.

00:16:12.560 --> 00:16:14.940
You have to think of the
choices that you are making,

00:16:14.940 --> 00:16:17.650
in terms of what
you eat, as choices

00:16:17.650 --> 00:16:19.880
of ethical consequences.

00:16:19.880 --> 00:16:23.500
And so I think that's
why we should regard this

00:16:23.500 --> 00:16:25.990
as one of the central
ethical issues.

00:16:25.990 --> 00:16:29.421
After all, it's something we
all do two or three times a day.

00:16:29.421 --> 00:16:33.190


00:16:33.190 --> 00:16:37.320
In 2006 Pam Martin
and I compared

00:16:37.320 --> 00:16:39.360
the average American
diet, purely

00:16:39.360 --> 00:16:41.770
in terms of greenhouse
gas emissions,

00:16:41.770 --> 00:16:43.710
to alternative diets.

00:16:43.710 --> 00:16:46.430
Gidon Eshel wanted
to identify which

00:16:46.430 --> 00:16:50.170
diet has the biggest
impact on global warming.

00:16:50.170 --> 00:16:54.570
The average American diet
consists of plants, eggs,

00:16:54.570 --> 00:16:58.440
dairy, poultry,
fish, and red meat.

00:16:58.440 --> 00:17:00.310
The most significant
greenhouse gas

00:17:00.310 --> 00:17:03.220
associated with the production
of food for this diet

00:17:03.220 --> 00:17:04.710
is methane.

00:17:04.710 --> 00:17:06.230
Cows are ruminant.

00:17:06.230 --> 00:17:09.020
Methane is a by-product of that.

00:17:09.020 --> 00:17:10.770
They burp it, mostly.

00:17:10.770 --> 00:17:12.240
Some of it comes the other end.

00:17:12.240 --> 00:17:15.180
But most of it
comes through burps.

00:17:15.180 --> 00:17:19.834
A poultry diet is made up
of plants, eggs, dairy,

00:17:19.834 --> 00:17:20.750
and chicken or turkey.

00:17:20.750 --> 00:17:24.319


00:17:24.319 --> 00:17:27.280
Poultry is a pretty
efficient little animal.

00:17:27.280 --> 00:17:29.730
But there is the
CO2 just related

00:17:29.730 --> 00:17:31.440
to fossil fuel combustion.

00:17:31.440 --> 00:17:35.080
In addition to that,
chicken or turkey manure

00:17:35.080 --> 00:17:37.870
undergo chemical
decomposition that

00:17:37.870 --> 00:17:40.150
results in the emissions
of nitrous oxide

00:17:40.150 --> 00:17:41.690
to the atmosphere.

00:17:41.690 --> 00:17:44.480
A lacto-ovo vegetarian
diet consists

00:17:44.480 --> 00:17:47.650
of plants, eggs, and dairy.

00:17:47.650 --> 00:17:50.610
Interestingly poultry
diet is actually

00:17:50.610 --> 00:17:52.730
superior to
lacto-ovo vegetarian.

00:17:52.730 --> 00:17:56.220
The reason for that is
that lacto-ovo vegetarians

00:17:56.220 --> 00:18:01.180
have been shown to eat
more animal-based dairy

00:18:01.180 --> 00:18:04.320
and egg it their diet.

00:18:04.320 --> 00:18:07.010
Eshel compared the
average American diet

00:18:07.010 --> 00:18:11.610
to a diet completely based
on food from plant sources.

00:18:11.610 --> 00:18:14.060
If you eat the
mean American diet

00:18:14.060 --> 00:18:17.270
you are responsible for
the emissions of a ton

00:18:17.270 --> 00:18:19.250
and a half of CO2 equivalent.

00:18:19.250 --> 00:18:22.930
Above and beyond what
your fellow plant eaters

00:18:22.930 --> 00:18:24.870
are responsible for.

00:18:24.870 --> 00:18:27.480
To put this in
perspective if you

00:18:27.480 --> 00:18:32.650
switch to the most
efficient car in the market

00:18:32.650 --> 00:18:37.660
that switch will result in the
reduction of your emissions

00:18:37.660 --> 00:18:38.680
by one ton.

00:18:38.680 --> 00:18:41.644
[MUSIC PLAYING]

00:18:41.644 --> 00:18:48.080


00:18:48.080 --> 00:18:49.660
When we emit all
these greenhouse

00:18:49.660 --> 00:18:52.530
gases we're contributing
to global warming,

00:18:52.530 --> 00:18:53.980
we're contributing
to the melting

00:18:53.980 --> 00:18:56.950
of the ice in the Arctic
and the Antarctic,

00:18:56.950 --> 00:18:59.620
and therefore we're
causing sea levels to rise.

00:18:59.620 --> 00:19:02.420
And we will be
inundating the farmlands

00:19:02.420 --> 00:19:06.250
of people in Bangladesh,
for example, or in Egypt,

00:19:06.250 --> 00:19:08.970
where there are a lot of people
living very close to sea level.

00:19:08.970 --> 00:19:11.160
So we're really responsible
I say for drowning them.

00:19:11.160 --> 00:19:14.010
Not just for not saving them.

00:19:14.010 --> 00:19:17.370
[MUSIC PLAYING]

00:19:17.370 --> 00:19:26.550


00:19:26.550 --> 00:19:31.880
Red meat is, in some sense, the
worst offender, so to speak,

00:19:31.880 --> 00:19:35.210
when it comes to
greenhouse gas emissions.

00:19:35.210 --> 00:19:41.870
At the same time other
forms of animal-based foods,

00:19:41.870 --> 00:19:46.500
while superior to
red meat, are not

00:19:46.500 --> 00:19:53.800
as advantageous as
plant-based foods still.

00:19:53.800 --> 00:19:58.330
So you have
plant-based foods here.

00:19:58.330 --> 00:20:02.220
They are the least
environmental impactful.

00:20:02.220 --> 00:20:04.590
You have red meat here.

00:20:04.590 --> 00:20:07.370
And that's the most impactful.

00:20:07.370 --> 00:20:14.620
And you can ask yourself,
where are my choices located?

00:20:14.620 --> 00:20:16.720
Some people think
that plant-based food

00:20:16.720 --> 00:20:17.549
is a bit boring.

00:20:17.549 --> 00:20:18.715
We like to prove them wrong.

00:20:18.715 --> 00:20:23.590
[MUSIC PLAYING]

00:20:23.590 --> 00:20:26.170
The biggest challenge
for the plant-based food

00:20:26.170 --> 00:20:28.670
is forgetting the
whole classical idea

00:20:28.670 --> 00:20:30.290
of having one meet and two veg.

00:20:30.290 --> 00:20:31.290
You've only got the veg.

00:20:31.290 --> 00:20:33.831
So you've got to try and make
the whole dish the centerpiece.

00:20:33.831 --> 00:20:36.900


00:20:36.900 --> 00:20:39.350
When people come in and they're
like used to eating meat,

00:20:39.350 --> 00:20:41.040
they don't know
really what to expect.

00:20:41.040 --> 00:20:43.248
And they're sort of like,
oh, it's like a light salad

00:20:43.248 --> 00:20:44.040
all the time.

00:20:44.040 --> 00:20:47.380
When they have the food, they're
like, the texture, the flavors,

00:20:47.380 --> 00:20:48.230
they're like, wow.

00:20:48.230 --> 00:20:49.220
This is amazing.

00:20:49.220 --> 00:20:50.770
Sometimes they don't even
know that there is absolutely

00:20:50.770 --> 00:20:51.520
no animal product.

00:20:51.520 --> 00:20:53.010
And they're just
like, absolutely

00:20:53.010 --> 00:20:55.080
love it-- the [INAUDIBLE]
and everything.

00:20:55.080 --> 00:20:55.920
So it's really good.

00:20:55.920 --> 00:20:59.329
[MUSIC PLAYING]

00:20:59.329 --> 00:21:10.530


00:21:10.530 --> 00:21:13.800
Professor Campbell spent years
investigating the connection

00:21:13.800 --> 00:21:18.320
between dietary protein and
cancer promotion in rats,

00:21:18.320 --> 00:21:24.240
but wasn't sure how far his
discoveries applied to humans.

00:21:24.240 --> 00:21:28.350
Even if I was pretty
confident in the applicability

00:21:28.350 --> 00:21:31.560
of the animal study data
for the human population

00:21:31.560 --> 00:21:34.980
my college wouldn't
agree with that.

00:21:34.980 --> 00:21:39.010
They would want to see more
confirmation, especially

00:21:39.010 --> 00:21:41.830
with humans.

00:21:41.830 --> 00:21:43.930
And for me that's
entirely reasonable.

00:21:43.930 --> 00:21:46.060
Because that's the
way I think too.

00:21:46.060 --> 00:21:49.580
In the early 1980s Campbell
had the opportunity

00:21:49.580 --> 00:21:53.190
to conduct a study with a
human population in China.

00:21:53.190 --> 00:21:56.610
It was to be the first
collaboration between Beijing,

00:21:56.610 --> 00:22:00.380
Cornell, and Oxford University,
and would take over 20 years

00:22:00.380 --> 00:22:01.660
to complete.

00:22:01.660 --> 00:22:04.150
The study was highly
acclaimed at the time

00:22:04.150 --> 00:22:07.340
by one of the world's leading
epidemiologist Sir Richard

00:22:07.340 --> 00:22:07.840
Doll.

00:22:07.840 --> 00:22:13.420
This is remarkable work which
Doctor Campbell initiated.

00:22:13.420 --> 00:22:15.870
It really was making
use of the fact

00:22:15.870 --> 00:22:22.240
that China was the last medical
frontier to cross and to where

00:22:22.240 --> 00:22:24.820
one could discover new things.

00:22:24.820 --> 00:22:27.260
In the 1970s there was
a systematic survey

00:22:27.260 --> 00:22:29.930
of who died of what
all over China.

00:22:29.930 --> 00:22:32.031
And every disease that
was common in one place

00:22:32.031 --> 00:22:33.030
was rare somewhere else.

00:22:33.030 --> 00:22:35.363
You could find one county
where more than 10% of the men

00:22:35.363 --> 00:22:36.756
would die from liver cancer.

00:22:36.756 --> 00:22:38.630
Then you could go to a
few hundred miles away

00:22:38.630 --> 00:22:40.610
and you'd find that
less than 1% of the men

00:22:40.610 --> 00:22:41.370
would die from liver cancer.

00:22:41.370 --> 00:22:43.400
You could do the same
with cancer of the throat.

00:22:43.400 --> 00:22:44.774
You could do the
same with having

00:22:44.774 --> 00:22:46.210
strokes, death from stroke.

00:22:46.210 --> 00:22:48.072
Every disease that is
common in one place

00:22:48.072 --> 00:22:49.030
is rare somewhere else.

00:22:49.030 --> 00:22:50.470
And that means that
all of the diseases

00:22:50.470 --> 00:22:52.011
that are common in
China, or at least

00:22:52.011 --> 00:22:54.500
the diseases in middle age
that are common in China,

00:22:54.500 --> 00:22:57.280
and largely avoidable by
some humanly practicable way

00:22:57.280 --> 00:22:58.182
of living.

00:22:58.182 --> 00:22:59.640
So the next question
was, well, how

00:22:59.640 --> 00:23:00.570
are they going to be avoided?

00:23:00.570 --> 00:23:02.695
And that's where the
collaboration between Beijing,

00:23:02.695 --> 00:23:05.900
Cornell, and the Oxford came in.

00:23:05.900 --> 00:23:09.060
The researchers chose 65
of the Chinese counties

00:23:09.060 --> 00:23:12.270
with unusually high or
low disease death rates,

00:23:12.270 --> 00:23:15.900
and collected data from
thousands of Chinese citizens.

00:23:15.900 --> 00:23:18.320
Urine and blood
samples were taken.

00:23:18.320 --> 00:23:20.330
Hormonal factors
and viral factors

00:23:20.330 --> 00:23:22.220
were measured,
along with exposure

00:23:22.220 --> 00:23:25.000
to toxic chemicals
like pesticides,

00:23:25.000 --> 00:23:28.220
heavy metals, and mycotoxins.

00:23:28.220 --> 00:23:29.840
The researchers
studied differences

00:23:29.840 --> 00:23:33.615
in lifestyle smoking,
exercise habits, and diet.

00:23:33.615 --> 00:23:36.810
[MUSIC PLAYING]

00:23:36.810 --> 00:23:40.240


00:23:40.240 --> 00:23:41.710
[SPEAKING CHINESE]

00:23:41.710 --> 00:23:57.390


00:23:57.390 --> 00:24:00.410
Laboratories around the
world analyzed the data.

00:24:00.410 --> 00:24:02.900
And over the years the
findings were published.

00:24:02.900 --> 00:24:04.690
Studies looked to
the relationship

00:24:04.690 --> 00:24:07.600
between, for example,
fat and breast cancer,

00:24:07.600 --> 00:24:10.050
or between colon
cancer and fiber.

00:24:10.050 --> 00:24:13.210
One study that really stood
out was the relationship

00:24:13.210 --> 00:24:16.960
between heart disease and
blood cholesterol levels.

00:24:16.960 --> 00:24:19.305
We in the West regard
heart attacks as just as

00:24:19.305 --> 00:24:20.120
a normal thing.

00:24:20.120 --> 00:24:21.410
It's what happens when
you get middle-aged.

00:24:21.410 --> 00:24:22.120
You have a heart attack.

00:24:22.120 --> 00:24:23.744
And maybe you could
something about it.

00:24:23.744 --> 00:24:25.880
But anyway it's normal for
the heart to degenerate.

00:24:25.880 --> 00:24:27.713
At least these that's
how we think about it.

00:24:27.713 --> 00:24:29.000
And it's not normal.

00:24:29.000 --> 00:24:30.500
And it's the Chinese
experience that

00:24:30.500 --> 00:24:32.140
shows that it is not normal.

00:24:32.140 --> 00:24:34.560
The Chinese peasants eat plants.

00:24:34.560 --> 00:24:37.190
And they have very little
cholesterol in their blood.

00:24:37.190 --> 00:24:40.810
And they have far fewer heart
attacks than the lowest risk

00:24:40.810 --> 00:24:42.180
that you would find in the West.

00:24:42.180 --> 00:24:44.760
So I think we can learn
from them that there

00:24:44.760 --> 00:24:47.727
is no such thing as
a normal Englishman.

00:24:47.727 --> 00:24:50.060
I'm trying to say what the
normal cholesterol in America

00:24:50.060 --> 00:24:53.140
or England, it's like taking
lots and lots of people who all

00:24:53.140 --> 00:24:56.280
smoke cigarettes,
and then saying well

00:24:56.280 --> 00:24:57.530
what's a normal smoking habit?

00:24:57.530 --> 00:24:59.113
Well it must be a
normal smoking habit

00:24:59.113 --> 00:25:00.530
is 15 or 20 cigarettes a day.

00:25:00.530 --> 00:25:03.490
But of course really a normal
smoking habit is not smoking.

00:25:03.490 --> 00:25:05.661
Humans were not evolved
to smoke cigarettes.

00:25:05.661 --> 00:25:08.160
And there may be many aspects
of the way of life of the poor

00:25:08.160 --> 00:25:09.535
that the rich
would not willingly

00:25:09.535 --> 00:25:11.710
emulate, even to
avoid heart attacks.

00:25:11.710 --> 00:25:14.910
But if you eat the sort of
food which is based mostly

00:25:14.910 --> 00:25:18.490
on plants, then you'll
have very few heart attacks

00:25:18.490 --> 00:25:19.230
in middle-age.

00:25:19.230 --> 00:25:25.950


00:25:25.950 --> 00:25:30.180
In this book, a rather
large body of data-- in fact

00:25:30.180 --> 00:25:32.200
the New York Times
called this the most

00:25:32.200 --> 00:25:34.770
comprehensive
collection of data ever.

00:25:34.770 --> 00:25:36.780
And I think it
was, and may still

00:25:36.780 --> 00:25:42.190
be in some ways-- We collected
data so that we ended up

00:25:42.190 --> 00:25:46.170
with a total of 367 items of
information, as we call it,

00:25:46.170 --> 00:25:47.810
or variables.

00:25:47.810 --> 00:25:49.490
We had about four
dozen different kinds

00:25:49.490 --> 00:25:51.279
of disease rates.

00:25:51.279 --> 00:25:53.070
That meant about a
dozen different cancers,

00:25:53.070 --> 00:25:56.160
and another three dozen or
so other kinds of diseases.

00:25:56.160 --> 00:26:00.300
And we ended up with two
aggregates of disease types.

00:26:00.300 --> 00:26:02.920
One group we've
often call diseases

00:26:02.920 --> 00:26:07.810
of poverty, infectious
diseases, inadequate nutrition.

00:26:07.810 --> 00:26:09.800
The other group of
diseases turned out

00:26:09.800 --> 00:26:12.980
to be the cancers,
heart disease, diabetes.

00:26:12.980 --> 00:26:15.040
Those are the kind
of diseases that

00:26:15.040 --> 00:26:18.830
tended to appear in the
more affluent areas.

00:26:18.830 --> 00:26:23.600
With that in mind I hypothesized
that if all these diseases that

00:26:23.600 --> 00:26:26.690
tender occur in a common
area, is there something

00:26:26.690 --> 00:26:29.340
we measured in this
book, and the studies.

00:26:29.340 --> 00:26:30.970
There's something
there that might

00:26:30.970 --> 00:26:32.480
associate with those diseases.

00:26:32.480 --> 00:26:35.010
So we started looking
for some things.

00:26:35.010 --> 00:26:36.570
And one thing that
really stood out

00:26:36.570 --> 00:26:38.570
was blood cholesterol levels.

00:26:38.570 --> 00:26:41.010
Diseases of affluence
heart disease, cancer,

00:26:41.010 --> 00:26:42.360
diabetes, and so forth.

00:26:42.360 --> 00:26:45.470
Those diseases
would tend to rise,

00:26:45.470 --> 00:26:47.800
their mortally rates
would tend to go up,

00:26:47.800 --> 00:26:50.500
when blood cholesterol
started to go up.

00:26:50.500 --> 00:26:54.660
And so we found as cholesterol
would go up like this,

00:26:54.660 --> 00:26:57.250
it was highly associated
with the consumption

00:26:57.250 --> 00:27:00.410
of animal-based
foods, animal protein.

00:27:00.410 --> 00:27:03.810
It would tend to go up when more
animal protein was consumed.

00:27:03.810 --> 00:27:06.350
And it tended to go
down when more plant

00:27:06.350 --> 00:27:07.570
protein was consumed.

00:27:07.570 --> 00:27:10.200
So there was sort of a signal.

00:27:10.200 --> 00:27:10.995
There was a signal.

00:27:10.995 --> 00:27:13.640


00:27:13.640 --> 00:27:16.156
This led to this.

00:27:16.156 --> 00:27:18.390
The evidence from
the China study

00:27:18.390 --> 00:27:21.226
was a major turning
point for Campbell.

00:27:21.226 --> 00:27:24.410
It led him to investigate
the work of other researchers

00:27:24.410 --> 00:27:28.780
on animal and plant-based diets.

00:27:28.780 --> 00:27:30.860
Recommendation number one.

00:27:30.860 --> 00:27:33.320
This is the one that says
to eat a plant-based diet.

00:27:33.320 --> 00:27:34.445
First one that's said that.

00:27:34.445 --> 00:27:38.303


00:27:38.303 --> 00:27:41.796
[MUSIC PLAYING]

00:27:41.796 --> 00:27:44.270


00:27:44.270 --> 00:27:45.103
[NON-ENGLISH SPEECH]

00:27:45.103 --> 00:27:51.890


00:27:51.890 --> 00:27:55.085
A lot of people think that
[INAUDIBLE], but we don't.

00:27:55.085 --> 00:27:55.995
I don't [INAUDIBLE]

00:27:55.995 --> 00:27:59.490


00:27:59.490 --> 00:28:02.815
[MUSIC PLAYING]

00:28:02.815 --> 00:28:07.570


00:28:07.570 --> 00:28:12.450
[INAUDIBLE] And as you can
see, we have [INAUDIBLE]

00:28:12.450 --> 00:28:15.580
and mashed potatoes
with garlic onion.

00:28:15.580 --> 00:28:20.221
You have the seitan,
onions, with a tomato base.

00:28:20.221 --> 00:28:20.720
[INAUDIBLE]

00:28:20.720 --> 00:28:26.210


00:28:26.210 --> 00:28:28.810
We put this really,
really rich mustard gravy.

00:28:28.810 --> 00:28:31.202
We had like a [INAUDIBLE].

00:28:31.202 --> 00:28:36.636


00:28:36.636 --> 00:28:37.140
Wonderful.

00:28:37.140 --> 00:28:39.420
Greatest plates.

00:28:39.420 --> 00:28:40.890
Depending on the
seasons, we get--

00:28:40.890 --> 00:28:43.630
[CRASHING]

00:28:43.630 --> 00:28:46.426
Like right now, we have some
pork with cauliflower, which

00:28:46.426 --> 00:28:51.150
is great for that extra
color. [INAUDIBLE]

00:28:51.150 --> 00:28:53.900
We have like purple cauliflower
and yellow cauliflower.

00:28:53.900 --> 00:28:55.820
That is good in this season.

00:28:55.820 --> 00:28:57.028
I was like, that's beautiful.

00:28:57.028 --> 00:29:00.514
[MUSIC PLAYING]

00:29:00.514 --> 00:29:10.180


00:29:10.180 --> 00:29:13.610
[MUSIC PLAYING]

00:29:13.610 --> 00:29:18.010


00:29:18.010 --> 00:29:18.510
[INAUDIBLE]

00:29:18.510 --> 00:29:27.330


00:29:27.330 --> 00:29:31.740
[MUSIC PLAYING]

00:29:31.740 --> 00:29:36.800
Raising animals is involved with
a lot more environmental issues

00:29:36.800 --> 00:29:39.130
than simply greenhouse
gas emissions.

00:29:39.130 --> 00:29:43.770
Another very important aspect is
the contribution to dead zones.

00:29:43.770 --> 00:29:46.340
There are some places where
the oceans are greatly

00:29:46.340 --> 00:29:49.040
affected by pollution
from agriculture.

00:29:49.040 --> 00:29:51.040
One of the best
examples is the Gulf

00:29:51.040 --> 00:29:54.320
of Mexico off the southern
United States, which

00:29:54.320 --> 00:29:56.430
takes the drainage from
the Mississippi River.

00:29:56.430 --> 00:30:00.470
And so it's basically
the drainage

00:30:00.470 --> 00:30:02.920
from a heartland
of the US, which

00:30:02.920 --> 00:30:06.390
is where most of US
agriculture is located.

00:30:06.390 --> 00:30:09.450
And there's sufficient
nutrients running

00:30:09.450 --> 00:30:12.250
into the Gulf of Mexico,
especially nitrogen

00:30:12.250 --> 00:30:17.390
and phosphorus from agriculture
that every year the Gulf

00:30:17.390 --> 00:30:20.280
of Mexico has a
dead zone, sometimes

00:30:20.280 --> 00:30:22.060
the size of, say, the
state of New Jersey.

00:30:22.060 --> 00:30:23.740
It's quite vast.

00:30:23.740 --> 00:30:29.740
And in this dead zone the
waters don't have any oxygen

00:30:29.740 --> 00:30:32.090
or have very low
levels of oxygen.

00:30:32.090 --> 00:30:34.100
So that virtually
all the creatures

00:30:34.100 --> 00:30:36.280
are killed, or can't live.

00:30:36.280 --> 00:30:39.970
When you have swordfish
that happened to wander in,

00:30:39.970 --> 00:30:45.010
well maybe it can swim
fast enough into open ocean

00:30:45.010 --> 00:30:46.040
and survive.

00:30:46.040 --> 00:30:49.450
But most small fishes
are unable to achieve

00:30:49.450 --> 00:30:54.320
that, because the spatial
extent of those dead zones

00:30:54.320 --> 00:30:56.400
it's just vast.

00:30:56.400 --> 00:30:59.980
So they just die.

00:30:59.980 --> 00:31:02.400
One of the main
causes of dead zones

00:31:02.400 --> 00:31:07.660
is the discharge of reactive
nitrogen from farms.

00:31:07.660 --> 00:31:10.660
Eshel has been investigating
how our diet affects

00:31:10.660 --> 00:31:15.910
the amount of reactive nitrogen
released into the oceans.

00:31:15.910 --> 00:31:19.360
Each one of the dots, of which
there are 1,000 here and 1,000

00:31:19.360 --> 00:31:24.910
here, represent the
annual diet of one person.

00:31:24.910 --> 00:31:30.080
To further up you go, the
more your food choices

00:31:30.080 --> 00:31:34.940
contribute to the
scope of the dead zone.

00:31:34.940 --> 00:31:38.480
The thing that is so
striking about this

00:31:38.480 --> 00:31:43.070
is the average American diet
releases into the environment

00:31:43.070 --> 00:31:46.930
about three and a half times
as much reactive nitrogen

00:31:46.930 --> 00:31:51.030
as the plant-based diet.

00:31:51.030 --> 00:31:52.880
These are not
subtle differences.

00:31:52.880 --> 00:31:55.300
We're not talking
here about improving

00:31:55.300 --> 00:31:59.540
your environmental
footprint by 20%.

00:31:59.540 --> 00:32:01.900
We're talking here
about dropping it

00:32:01.900 --> 00:32:03.530
to a third of what it was.

00:32:03.530 --> 00:32:06.410
[MUSIC PLAYING]

00:32:06.410 --> 00:32:10.250


00:32:10.250 --> 00:32:13.769
Arguments about the
oceans being limitless,

00:32:13.769 --> 00:32:15.310
so we can't harm
them, are a bit like

00:32:15.310 --> 00:32:17.402
the old-fashioned
arguments that have

00:32:17.402 --> 00:32:18.610
to do with the air pollution.

00:32:18.610 --> 00:32:20.700
Well, we'll just build
taller smokestacks.

00:32:20.700 --> 00:32:23.359
And the pollution will
go up so high in the air

00:32:23.359 --> 00:32:24.900
that we won't have
to worry about it.

00:32:24.900 --> 00:32:26.900
And now, of course, we
know that that's rubbish.

00:32:26.900 --> 00:32:29.880
If you build taller smokestacks
the pollutants are still there.

00:32:29.880 --> 00:32:31.460
They still affect us.

00:32:31.460 --> 00:32:36.230
So we have to treat the
oceans as an integral part

00:32:36.230 --> 00:32:37.290
of our planet too.

00:32:37.290 --> 00:32:41.830
Not just some vast
dumping ground.

00:32:41.830 --> 00:32:45.880
The large scale problem of
reactive nitrogen discharge

00:32:45.880 --> 00:32:50.120
into the environment has to
do with the cows and manure

00:32:50.120 --> 00:32:51.540
management problems.

00:32:51.540 --> 00:32:55.600
And the effluent from a
perfectly organic large scale

00:32:55.600 --> 00:32:59.240
feeding operation
will contribute

00:32:59.240 --> 00:33:03.480
to the scope of the dead
zone, as effectively

00:33:03.480 --> 00:33:08.085
as the effluent from a
conventional large-scale

00:33:08.085 --> 00:33:08.835
feeding operation.

00:33:08.835 --> 00:33:18.900


00:33:18.900 --> 00:33:20.190
I had lots of publications.

00:33:20.190 --> 00:33:21.990
I've had 300 and
some publications

00:33:21.990 --> 00:33:22.970
were peer-reviewed.

00:33:22.970 --> 00:33:26.570
And I had already been
offered the top position

00:33:26.570 --> 00:33:32.310
full professor with tenure
when I was only 40 years old.

00:33:32.310 --> 00:33:33.530
I had everything I wanted.

00:33:33.530 --> 00:33:34.946
I mean, I didn't
need a promotion.

00:33:34.946 --> 00:33:38.330


00:33:38.330 --> 00:33:41.920
And I knew that if I started
to follow what I believe

00:33:41.920 --> 00:33:44.920
to be true my
professional reputation

00:33:44.920 --> 00:33:47.180
was going to take a hit.

00:33:47.180 --> 00:33:51.940
But science is supposed
to be engendering debate.

00:33:51.940 --> 00:33:54.571
So it was a matter of the truth.

00:33:54.571 --> 00:33:55.820
It was what the evidence said.

00:33:55.820 --> 00:33:57.500
Do I believe this,
or don't believe it?

00:33:57.500 --> 00:34:00.240


00:34:00.240 --> 00:34:04.480
After decades of research in
his own laboratory and in China

00:34:04.480 --> 00:34:07.860
Campbell began to study the
findings of other researchers

00:34:07.860 --> 00:34:10.780
who were investigating the
relationship between diet

00:34:10.780 --> 00:34:12.761
and disease.

00:34:12.761 --> 00:34:14.469
This, I think, this
study here is perhaps

00:34:14.469 --> 00:34:16.560
one of the greater studies,
most important studies

00:34:16.560 --> 00:34:19.570
of the last century.

00:34:19.570 --> 00:34:23.160
It was done by a man by the name
of, Doctor Caldwell Esselstyn

00:34:23.160 --> 00:34:23.659
Junior.

00:34:23.659 --> 00:34:26.431
[MUSIC PLAYING]

00:34:26.431 --> 00:34:28.989


00:34:28.989 --> 00:34:30.739
Doctor Esselstyn and
was a famous surgeon.

00:34:30.739 --> 00:34:34.010
He was once listed as
one the top 100 doctors.

00:34:34.010 --> 00:34:37.030
He got to a point in the
1980's and said, wait a minute.

00:34:37.030 --> 00:34:38.440
I'm doing all this surgery.

00:34:38.440 --> 00:34:40.239
What am I doing?

00:34:40.239 --> 00:34:43.335
He really started thinking, he's
not really accomplishing much.

00:34:43.335 --> 00:34:45.210
So he decided to do a
nutritional experiment.

00:34:45.210 --> 00:34:49.000


00:34:49.000 --> 00:34:50.360
I retired from surgeries.

00:34:50.360 --> 00:34:53.510
But what has
personally motivated

00:34:53.510 --> 00:34:59.180
me to continue in
medicine was, it

00:34:59.180 --> 00:35:03.420
was very clear, that my
research with patients

00:35:03.420 --> 00:35:05.150
with severe
cardiovascular disease

00:35:05.150 --> 00:35:08.080
was really sort of
sprouting wings.

00:35:08.080 --> 00:35:12.620
The fact that there were really,
there was very little else

00:35:12.620 --> 00:35:17.270
of this type of
research going on,

00:35:17.270 --> 00:35:20.620
made me feel that it
was just too exciting.

00:35:20.620 --> 00:35:25.510
[MUSIC PLAYING]

00:35:25.510 --> 00:35:27.660
If you were a
cardiac surgeon today

00:35:27.660 --> 00:35:30.480
and you want to go to rural
China, or Central Africa,

00:35:30.480 --> 00:35:33.310
or the Tarahumara Indians
in northern Mexico,

00:35:33.310 --> 00:35:34.810
and earn a living, forget it.

00:35:34.810 --> 00:35:37.050
You better plan on
selling pencils.

00:35:37.050 --> 00:35:40.210
There is no heart disease there.

00:35:40.210 --> 00:35:45.230
So it didn't seem like too much
in the way of rocket science

00:35:45.230 --> 00:35:49.120
to say look, if these cultures,
which are plant based,

00:35:49.120 --> 00:35:50.960
don't ever have
coronary artery disease.

00:35:50.960 --> 00:35:57.810
Wouldn't it be a rational thing
to ask patients who already

00:35:57.810 --> 00:35:59.760
have established
heart disease, can we

00:35:59.760 --> 00:36:01.210
get them to go plant-based?

00:36:01.210 --> 00:36:03.340
And see if we can't
arrest their disease,

00:36:03.340 --> 00:36:06.134
or perhaps even reverse it.

00:36:06.134 --> 00:36:08.740


00:36:08.740 --> 00:36:11.070
In the late '80s
Esselstyn gathered

00:36:11.070 --> 00:36:13.980
together a group of
18 patients, seriously

00:36:13.980 --> 00:36:15.630
ill with heart disease.

00:36:15.630 --> 00:36:19.860
Who collectively had a total
of 49 heart attacks, bypass

00:36:19.860 --> 00:36:22.516
surgery, and angioplasties.

00:36:22.516 --> 00:36:24.700
They were all eating a
typical Western diet.

00:36:24.700 --> 00:36:27.095
[MUSIC PLAYING]

00:36:27.095 --> 00:36:43.106


00:36:43.106 --> 00:36:44.088
How are you doing?

00:36:44.088 --> 00:36:44.588
Good.

00:36:44.588 --> 00:36:46.080
You look great.

00:36:46.080 --> 00:36:49.080
I was waiting for your
call until yesterday.

00:36:49.080 --> 00:36:52.640
I had to change my
haircut appointment.

00:36:52.640 --> 00:36:55.930
So my barber's going to be mad.

00:36:55.930 --> 00:36:58.750
Anthony was one of the
actual original group

00:36:58.750 --> 00:37:00.890
of patients with
my original study.

00:37:00.890 --> 00:37:04.040
When he first came to see me,
he had severe coronary artery

00:37:04.040 --> 00:37:05.070
disease.

00:37:05.070 --> 00:37:06.840
It was New Year's
Eve party, you know.

00:37:06.840 --> 00:37:09.470
And I was so
enjoying my dancing.

00:37:09.470 --> 00:37:15.590
Suddenly, my god, it
was just like that.

00:37:15.590 --> 00:37:17.740
That's when I saw this doctor.

00:37:17.740 --> 00:37:21.480
Don't worry about,
he says, we are

00:37:21.480 --> 00:37:26.530
well-known in this area
of surgery called bypass,

00:37:26.530 --> 00:37:28.210
in the layman term.

00:37:28.210 --> 00:37:33.090
And he said, you most likely
will need five of them.

00:37:33.090 --> 00:37:38.100
Anyway I have open-heart,
five bypass surgery done.

00:37:38.100 --> 00:37:44.320
A week and a half later, I have
the same funny feeling again.

00:37:44.320 --> 00:37:46.020
You know what they told me?

00:37:46.020 --> 00:37:49.280
They say looks like one
is already shut down.

00:37:49.280 --> 00:37:51.520
And the other one
wasn't doing too well.

00:37:51.520 --> 00:37:52.420
In a week and a half?

00:37:52.420 --> 00:37:52.920
Yeah.

00:37:52.920 --> 00:37:56.450
The one that was weak
also was shut down.

00:37:56.450 --> 00:37:59.540
And I said, how about
the other three?

00:37:59.540 --> 00:38:00.740
They couldn't answer me.

00:38:00.740 --> 00:38:04.590
They said, that's something
we just couldn't answer.

00:38:04.590 --> 00:38:07.620
My mind went through
about everything.

00:38:07.620 --> 00:38:09.550
What did I do wrong?

00:38:09.550 --> 00:38:12.860
Nobody told me I
did anything wrong.

00:38:12.860 --> 00:38:15.860
I was doing a little exercise.

00:38:15.860 --> 00:38:18.620
I was drinking the milk,
like I was supposed to.

00:38:18.620 --> 00:38:23.320
Calcium and protein,
every single day.

00:38:23.320 --> 00:38:24.660
And I was very healthy.

00:38:24.660 --> 00:38:28.740
I'm not going to wait for the
three other vein to shut down.

00:38:28.740 --> 00:38:32.760
That's when depression sets in.

00:38:32.760 --> 00:38:35.710
Caused by severe fears.

00:38:35.710 --> 00:38:40.670
And so like hopeless, you're
ready to give your life up.

00:38:40.670 --> 00:38:43.090
So the psychiatrist
said, he said,

00:38:43.090 --> 00:38:46.549
before you do that
it's a messy thing.

00:38:46.549 --> 00:38:48.340
He said, before you
would do that, I really

00:38:48.340 --> 00:38:54.070
want you to go to see a fellow
that he is working and doing

00:38:54.070 --> 00:38:55.500
the research.

00:38:55.500 --> 00:38:56.700
So he wrote it down.

00:38:56.700 --> 00:38:58.090
I couldn't even spell it.

00:38:58.090 --> 00:39:00.240
I couldn't even pronounce it.

00:39:00.240 --> 00:39:01.690
What is that?

00:39:01.690 --> 00:39:03.080
Esselstyn?

00:39:03.080 --> 00:39:04.670
What is this?

00:39:04.670 --> 00:39:07.850
Anthony joined Doctor
Esselstyn's study.

00:39:07.850 --> 00:39:09.710
Along with the other
patients he was

00:39:09.710 --> 00:39:12.370
put on a plant-based diet
and cholesterol lowering

00:39:12.370 --> 00:39:14.069
medication.

00:39:14.069 --> 00:39:15.610
Their health with
carefully monitored

00:39:15.610 --> 00:39:18.680
over the following years.

00:39:18.680 --> 00:39:25.790
This happens to be a
54-year-old security guard,

00:39:25.790 --> 00:39:28.510
where when we first
saw his-- this

00:39:28.510 --> 00:39:29.770
is the right coronary artery.

00:39:29.770 --> 00:39:31.910
And where that
arrow is was defined

00:39:31.910 --> 00:39:37.000
in our coronary angiography core
laboratory as a 30% blockage.

00:39:37.000 --> 00:39:39.930
And then several
years later you can

00:39:39.930 --> 00:39:43.600
see the blockage
has disappeared.

00:39:43.600 --> 00:39:45.302
In the 12 years on
this study, which

00:39:45.302 --> 00:39:47.760
made it the longest of its
type, in the medical literature.

00:39:47.760 --> 00:39:51.880
We found that 17 of the 18 had
no further coronary events.

00:39:51.880 --> 00:39:55.800


00:39:55.800 --> 00:40:01.830
One little sheep after six
years wondered from the flock.

00:40:01.830 --> 00:40:05.680
Got into all the wrong foods.

00:40:05.680 --> 00:40:07.130
Got a recurrence of angina.

00:40:07.130 --> 00:40:08.480
Ended up having a bypass.

00:40:08.480 --> 00:40:11.228
But now he's back
with the flock.

00:40:11.228 --> 00:40:16.480
[MUSIC PLAYING]

00:40:16.480 --> 00:40:19.620
I don't really know how to
explain that, other than I'm

00:40:19.620 --> 00:40:21.520
walking with my two feet.

00:40:21.520 --> 00:40:23.190
I sleep normal.

00:40:23.190 --> 00:40:25.140
And I have all my life.

00:40:25.140 --> 00:40:27.200
I'm looking at all
the beautiful girls.

00:40:27.200 --> 00:40:30.020
I get excited like a teenager.

00:40:30.020 --> 00:40:30.790
And normal.

00:40:30.790 --> 00:40:32.970
Is that normal, or not?

00:40:32.970 --> 00:40:35.500
But nobody even knew
that in two more years,

00:40:35.500 --> 00:40:37.962
I'd be 80 years old.

00:40:37.962 --> 00:40:40.860
They should be thinking
about setting me aside.

00:40:40.860 --> 00:40:41.910
But no.

00:40:41.910 --> 00:40:44.720
Except I still continue
to lose my hair.

00:40:44.720 --> 00:40:47.750
And I want to ask
you about that too.

00:40:47.750 --> 00:40:48.810
I'm still alive.

00:40:48.810 --> 00:40:51.490
That's the important
thing though.

00:40:51.490 --> 00:40:52.910
Now I want to clarify something.

00:40:52.910 --> 00:40:57.410
As I mentioned, this was a
very, very intensive shepherding

00:40:57.410 --> 00:41:01.050
of these people in the
early research group.

00:41:01.050 --> 00:41:03.180
And that was sort of, I
think, at least I felt,

00:41:03.180 --> 00:41:05.540
it was essential.

00:41:05.540 --> 00:41:08.250
So that we could find
out whether or not

00:41:08.250 --> 00:41:15.730
we could actually
demonstrate proof of concept.

00:41:15.730 --> 00:41:21.230
Namely that you are able
through appropriate nutrition

00:41:21.230 --> 00:41:23.805
to not only halt, but
to arrest this disease.

00:41:23.805 --> 00:41:26.830
[MUSIC PLAYING]

00:41:26.830 --> 00:41:40.670


00:41:40.670 --> 00:41:44.010
Professor Eshel has come
to visit Martin Ping, who

00:41:44.010 --> 00:41:47.110
runs a small-scale organic
farm in upstate New York.

00:41:47.110 --> 00:41:50.056
[MUSIC PLAYING]

00:41:50.056 --> 00:41:53.010


00:41:53.010 --> 00:41:55.730
These are really good just
raw, sliced up in the salad.

00:41:55.730 --> 00:41:57.674
Oh, it's good.

00:41:57.674 --> 00:42:00.104
Yep.

00:42:00.104 --> 00:42:02.048
I have a real
fondness for these.

00:42:02.048 --> 00:42:06.908


00:42:06.908 --> 00:42:08.350
That's so good.

00:42:08.350 --> 00:42:08.850
Yeah,

00:42:08.850 --> 00:42:12.145
Actually here too.

00:42:12.145 --> 00:42:12.840
For sure.

00:42:12.840 --> 00:42:14.900
Well I know which way
I'm walking home tonight.

00:42:14.900 --> 00:42:16.650
Have to stop and get
a little feta cheese.

00:42:16.650 --> 00:42:20.600


00:42:20.600 --> 00:42:23.810
I have a hankering
for Greek salad.

00:42:23.810 --> 00:42:27.912
I actually will admit that--
oh, here comes the girls.

00:42:27.912 --> 00:42:31.370


00:42:31.370 --> 00:42:33.360
Professor Eshel has
been investigating

00:42:33.360 --> 00:42:36.160
how this small-scale
organic farm compares

00:42:36.160 --> 00:42:38.850
to a large-scale
organic farm, in terms

00:42:38.850 --> 00:42:41.470
of its contribution
to oceanic dead zones.

00:42:41.470 --> 00:42:44.850


00:42:44.850 --> 00:42:47.340
You can measure the composition
of the water entering

00:42:47.340 --> 00:42:48.990
the system over there.

00:42:48.990 --> 00:42:49.750
Which we did.

00:42:49.750 --> 00:42:51.270
And you can measure
the composition

00:42:51.270 --> 00:42:53.840
of the water exiting
the system over there.

00:42:53.840 --> 00:42:56.410
And you can see that
the effluent coming

00:42:56.410 --> 00:43:00.780
out of this farm is dramatically
better than the effluent coming

00:43:00.780 --> 00:43:04.111
out of an industrial-scale farm.

00:43:04.111 --> 00:43:07.580
This is my commute to work.

00:43:07.580 --> 00:43:09.370
Some people wade
through traffic.

00:43:09.370 --> 00:43:12.117
And I wade through a stream.

00:43:12.117 --> 00:43:12.950
It's really awesome.

00:43:12.950 --> 00:43:15.130
I love it.

00:43:15.130 --> 00:43:17.450
The reason why this
small-scale farm

00:43:17.450 --> 00:43:20.280
is better in terms of the
amount of reactive nitrogen

00:43:20.280 --> 00:43:22.760
released into the
oceans, is because it

00:43:22.760 --> 00:43:25.150
uses the land less intensively.

00:43:25.150 --> 00:43:27.520
The amount of fertility
we have for our garden

00:43:27.520 --> 00:43:30.300
is dependent on the
number of cows we have.

00:43:30.300 --> 00:43:32.801
The number of cows we have
is dependent on the amount

00:43:32.801 --> 00:43:35.400
of pasture land we have,
in order for those cows

00:43:35.400 --> 00:43:38.150
have a grass-based
diet, without having

00:43:38.150 --> 00:43:41.220
to import any kind of feed
or supplement for them.

00:43:41.220 --> 00:43:43.500
So you have this system.

00:43:43.500 --> 00:43:45.000
We would say you
actually couldn't

00:43:45.000 --> 00:43:47.360
have long-term sustainable
vegetable garden

00:43:47.360 --> 00:43:50.214
without having the animals for
their fertility, some animals.

00:43:50.214 --> 00:43:53.060


00:43:53.060 --> 00:43:54.340
Let's take a look at this.

00:43:54.340 --> 00:43:57.190
This is the essence
of it all, cow cake.

00:43:57.190 --> 00:43:59.400
There is no industrial
process that

00:43:59.400 --> 00:44:02.840
can have such a perfect
balance of the nutrients

00:44:02.840 --> 00:44:04.740
as we see here.

00:44:04.740 --> 00:44:08.770
So that's why cows are
really, really essential.

00:44:08.770 --> 00:44:13.090
It's black gold, farmers gold.

00:44:13.090 --> 00:44:16.550
The way modern, conventional
agriculture works

00:44:16.550 --> 00:44:21.000
is high input, high
throughput, high output.

00:44:21.000 --> 00:44:26.180
Hawthorn Valley and small-scale
bio-dynamic or organic farms,

00:44:26.180 --> 00:44:28.990
offer an alternative to that.

00:44:28.990 --> 00:44:34.540
They readily accept lesser
throughput, lesser output,

00:44:34.540 --> 00:44:39.000
lesser productivity, producing
almost no reactive nitrogen

00:44:39.000 --> 00:44:40.635
discharge into the environment.

00:44:40.635 --> 00:44:43.360


00:44:43.360 --> 00:44:47.160
Small-scale organic farming may
help to save the environment.

00:44:47.160 --> 00:44:49.120
But to feed the
world we will have

00:44:49.120 --> 00:44:53.510
to change more than just
our farming practices.

00:44:53.510 --> 00:44:56.390
There's a heck of a lot of
people to feed in this world.

00:44:56.390 --> 00:44:58.000
If industrial
agriculture isn't going

00:44:58.000 --> 00:45:01.010
to be able to do it and
the small niche farming,

00:45:01.010 --> 00:45:04.170
as it stands now, isn't
going to be able to do it.

00:45:04.170 --> 00:45:07.420
But if you extend that to
how you see your diet, how

00:45:07.420 --> 00:45:10.400
much of your food is
vegetable and grain.

00:45:10.400 --> 00:45:12.529
If the meat is a small
part, the equation

00:45:12.529 --> 00:45:13.570
would change quite a bit.

00:45:13.570 --> 00:45:16.262


00:45:16.262 --> 00:45:18.220
I don't remember ever
eating anything so tasty.

00:45:18.220 --> 00:45:18.720
Yeah.

00:45:18.720 --> 00:45:21.516


00:45:21.516 --> 00:45:24.492
[MUSIC PLAYING]

00:45:24.492 --> 00:45:30.940


00:45:30.940 --> 00:45:34.641
I've been cooking all my
life, natural, food-based.

00:45:34.641 --> 00:45:37.798


00:45:37.798 --> 00:45:40.798
You'll have to excuse me, but
I do have a couple tickets up.

00:45:40.798 --> 00:45:44.670


00:45:44.670 --> 00:45:47.790
And this is our classic sundae.

00:45:47.790 --> 00:45:50.450
It's a little take on
a traditional banana

00:45:50.450 --> 00:45:54.210
split, chocolate and
vanilla ice cream.

00:45:54.210 --> 00:45:57.580
Our ice cream, dairy-free.

00:45:57.580 --> 00:46:04.290
And its base is cashew and young
coconut meat, agave, vanilla,

00:46:04.290 --> 00:46:07.890
a touch of salt, and water.

00:46:07.890 --> 00:46:11.750
The cashews and coconut meat
gives it its creaminess.

00:46:11.750 --> 00:46:16.110


00:46:16.110 --> 00:46:21.560
And then it's just a matter
of flavoring, chocolate syrup,

00:46:21.560 --> 00:46:24.035
and some candied almonds,
with a little bit

00:46:24.035 --> 00:46:26.890
of salt and some agave nectar.

00:46:26.890 --> 00:46:28.260
We use a lot of agave nectar.

00:46:28.260 --> 00:46:30.310
It comes from agave cactus.

00:46:30.310 --> 00:46:34.470
Probably more commonly
known for making tequila.

00:46:34.470 --> 00:46:37.790
But it has a great
raw application.

00:46:37.790 --> 00:46:42.800


00:46:42.800 --> 00:46:44.010
Amazing texture.

00:46:44.010 --> 00:46:47.492
That rich, creamy
texture that you're

00:46:47.492 --> 00:46:49.450
going to find in the best foods.

00:46:49.450 --> 00:46:53.147
The dairy ice cream,
without so much guilt.

00:46:53.147 --> 00:46:59.350


00:46:59.350 --> 00:47:01.810
Since Doctor Esselstyn's
original study

00:47:01.810 --> 00:47:04.360
he has treated a
further 200 patients

00:47:04.360 --> 00:47:06.490
by changing their diet.

00:47:06.490 --> 00:47:09.350
The stents, the angioplasties,
and the bypass surgery

00:47:09.350 --> 00:47:12.100
can be absolutely life saving.

00:47:12.100 --> 00:47:14.210
The challenge to
us as a profession

00:47:14.210 --> 00:47:18.390
is to do what we can, so that
the illnesses that today are

00:47:18.390 --> 00:47:20.880
requiring surgery,
never get to that point.

00:47:20.880 --> 00:47:24.160


00:47:24.160 --> 00:47:28.560
This happened to be
a young physician.

00:47:28.560 --> 00:47:31.250
44 years of age, he
had a heart attack.

00:47:31.250 --> 00:47:33.090
And you could see
this artery suddenly

00:47:33.090 --> 00:47:36.060
gets to be moth-eaten
and diseased.

00:47:36.060 --> 00:47:41.360
This was narrowed over
such a long segment

00:47:41.360 --> 00:47:43.940
that he was not a candidate
to have these stents just

00:47:43.940 --> 00:47:46.140
stuffed in one after the other.

00:47:46.140 --> 00:47:49.090
And it was too far down the
artery for a bypass operation.

00:47:49.090 --> 00:47:54.100
So I said, you know, why don't
you consider going plant-based?

00:47:54.100 --> 00:47:55.172
He said OK, I'll do it.

00:47:55.172 --> 00:47:57.630
But I'm not going to take any
of these cholesterol-lowering

00:47:57.630 --> 00:47:58.299
statin drugs.

00:47:58.299 --> 00:47:59.090
I don't trust them.

00:47:59.090 --> 00:48:00.720
There's too many
side effects, I feel.

00:48:00.720 --> 00:48:03.650
So I said not a problem.

00:48:03.650 --> 00:48:05.190
So he just did it.

00:48:05.190 --> 00:48:08.510
And 30 months later he
had a repeat angiogram.

00:48:08.510 --> 00:48:11.325
And as you can see over here
it's completely resolved.

00:48:11.325 --> 00:48:15.720


00:48:15.720 --> 00:48:17.480
Obesity can contribute to this.

00:48:17.480 --> 00:48:20.280
And metabolic syndrome
can contribute to it.

00:48:20.280 --> 00:48:23.650
But that doesn't spare the
patients who are slender.

00:48:23.650 --> 00:48:26.970
I mean, we treat many
patients who are slender.

00:48:26.970 --> 00:48:30.260
We treat many, actually
fascinating, athletes.

00:48:30.260 --> 00:48:32.730
I mean athletes
who run marathons.

00:48:32.730 --> 00:48:36.200
And yet they're crumbling
from disease of their arteries

00:48:36.200 --> 00:48:39.110
because of the horrible
food they're eating.

00:48:39.110 --> 00:48:41.120
This is not to
discredit exercise.

00:48:41.120 --> 00:48:43.120
And exercise is a
marvelous bonus.

00:48:43.120 --> 00:48:48.000
[MUSIC PLAYING]

00:48:48.000 --> 00:48:50.660
When you embark
on research where

00:48:50.660 --> 00:48:52.270
everybody is
extremely skeptical.

00:48:52.270 --> 00:48:54.650
I mean, god, how in
the world can food

00:48:54.650 --> 00:48:56.410
have this kind of
medicinal value,

00:48:56.410 --> 00:48:59.790
when we have all the
sophisticated drug companies.

00:48:59.790 --> 00:49:05.120
There's a certain competitive
spark that is lit.

00:49:05.120 --> 00:49:07.170
It's the challenges in
life that are exciting.

00:49:07.170 --> 00:49:09.930
[MUSIC PLAYING]

00:49:09.930 --> 00:49:14.490


00:49:14.490 --> 00:49:16.650
It wasn't out of the blue.

00:49:16.650 --> 00:49:19.110
We'd been talking about
it for a long time.

00:49:19.110 --> 00:49:21.210
And we didn't eat meat one time.

00:49:21.210 --> 00:49:24.220
We eat dairy a little later.

00:49:24.220 --> 00:49:27.510
And we-- did we
give up oil in '84?

00:49:27.510 --> 00:49:28.010
Oh yeah.

00:49:28.010 --> 00:49:30.180
Yeah, But, you know, I cooked.

00:49:30.180 --> 00:49:31.340
I did that.

00:49:31.340 --> 00:49:32.220
It was hard.

00:49:32.220 --> 00:49:34.922
And we weren't perfect.

00:49:34.922 --> 00:49:39.370
But it was-- I
knew it was right.

00:49:39.370 --> 00:49:42.310
[MUSIC PLAYING]

00:49:42.310 --> 00:49:47.220


00:49:47.220 --> 00:49:49.010
What is agreed in the
scientific community

00:49:49.010 --> 00:49:52.680
is at the initiation of
cardiovascular disease,

00:49:52.680 --> 00:49:55.850
heart attacks, coronary
artery disease,

00:49:55.850 --> 00:50:00.670
is it the magnificent
carpet of endothelial cells

00:50:00.670 --> 00:50:06.740
that lines our blood vessels
becomes progressively injured.

00:50:06.740 --> 00:50:09.700
And really it's only
in about the last 10,

00:50:09.700 --> 00:50:14.570
15 years that we
understand, in hindsight,

00:50:14.570 --> 00:50:17.930
why it was that our
program was working

00:50:17.930 --> 00:50:21.120
even earlier than these
discoveries have shown.

00:50:21.120 --> 00:50:28.060
Namely that we now know
that certain foods will

00:50:28.060 --> 00:50:31.940
injure the endothelial cells.

00:50:31.940 --> 00:50:35.540
Processed oils
injure endothelium.

00:50:35.540 --> 00:50:38.960
Dairy products
injure endothelium.

00:50:38.960 --> 00:50:44.710
Meat, fish, chicken, animal
protein injures endothelium.

00:50:44.710 --> 00:50:47.650
It seems so logical,
in patients who

00:50:47.650 --> 00:50:52.940
are severely ill with what is
an endothelial disease, to take

00:50:52.940 --> 00:50:55.670
away all the products
that are causing there

00:50:55.670 --> 00:50:56.610
endothelial disease.

00:50:56.610 --> 00:51:01.090


00:51:01.090 --> 00:51:03.470
I have not heard any of
our most severe critics

00:51:03.470 --> 00:51:06.550
say we're penalizing or
injuring the patient.

00:51:06.550 --> 00:51:10.634
Even many of our greatest
critics agree this will work.

00:51:10.634 --> 00:51:12.550
But it's only the rare
patient who will do it.

00:51:12.550 --> 00:51:14.250
Nonsense.

00:51:14.250 --> 00:51:15.100
Give them a chance.

00:51:15.100 --> 00:51:16.266
And they absolutely rejoice.

00:51:16.266 --> 00:51:20.150


00:51:20.150 --> 00:51:22.960
About a year ago I
started noticing symptoms

00:51:22.960 --> 00:51:24.860
were consistent
with heart disease.

00:51:24.860 --> 00:51:27.325
The doctor really wanted
me to go into the hospital

00:51:27.325 --> 00:51:29.890
and have a catheterization.

00:51:29.890 --> 00:51:32.260
I asked that they step on
the brakes a little bit,

00:51:32.260 --> 00:51:35.920
before we did that.

00:51:35.920 --> 00:51:38.210
So I could consult
Doctor Esselstyn.

00:51:38.210 --> 00:51:42.420
I wanted him to go in and
have a catheterization.

00:51:42.420 --> 00:51:46.970
I wanted him to go
through the procedure.

00:51:46.970 --> 00:51:49.440
I was scared for him.

00:51:49.440 --> 00:51:52.160
And he's off and
his-- I'm thinking,

00:51:52.160 --> 00:51:54.370
he's off on this crazy thing.

00:51:54.370 --> 00:51:55.430
Oh my gosh.

00:51:55.430 --> 00:51:58.060


00:51:58.060 --> 00:52:00.560
We are both in our '50s.

00:52:00.560 --> 00:52:02.940
And we have children
and grandchildren.

00:52:02.940 --> 00:52:04.700
And I want to see them grow up.

00:52:04.700 --> 00:52:09.890


00:52:09.890 --> 00:52:13.820
We all agreed that we would
try Doctor Esselstyn's program

00:52:13.820 --> 00:52:18.990
before I actually went in for
any surgery or procedures.

00:52:18.990 --> 00:52:21.160
I was a meat and
potatoes person.

00:52:21.160 --> 00:52:23.090
Most of the time when I
ate my vegetables they

00:52:23.090 --> 00:52:26.340
were covered with
butter and cheese.

00:52:26.340 --> 00:52:31.770
We stopped all of that,
all in one afternoon.

00:52:31.770 --> 00:52:33.190
And went grocery shopping.

00:52:33.190 --> 00:52:35.130
And went-- yes, we
went grocery shopping.

00:52:35.130 --> 00:52:36.766
Tell them about your stress.

00:52:36.766 --> 00:52:41.380
OK, Doctor Esselstyn
we're anxious to see

00:52:41.380 --> 00:52:47.360
some quantitative number
as to my improvement.

00:52:47.360 --> 00:52:51.990
So I scheduled the
second stress, echo test,

00:52:51.990 --> 00:52:53.550
started walking.

00:52:53.550 --> 00:52:56.650
Bottom line is that I
doubled the amount of time

00:52:56.650 --> 00:52:59.400
that I spent on the treadmill.

00:52:59.400 --> 00:53:02.580
Of course, my
cholesterol is way down.

00:53:02.580 --> 00:53:05.190
My blood sugar's normal.

00:53:05.190 --> 00:53:07.360
I had high triglycerides
in the past.

00:53:07.360 --> 00:53:10.070
And that's dropped.

00:53:10.070 --> 00:53:13.260
And after nine months
on a plant-based diet I

00:53:13.260 --> 00:53:15.040
still have heart disease.

00:53:15.040 --> 00:53:19.930
But I'm making great,
great improvement.

00:53:19.930 --> 00:53:23.754


00:53:23.754 --> 00:53:27.100
[MUSIC PLAYING]

00:53:27.100 --> 00:53:53.940


00:53:53.940 --> 00:53:57.040
None of this could have
happened without Anne.

00:53:57.040 --> 00:54:00.585
Because I may tell them
the why of their disease.

00:54:00.585 --> 00:54:04.570


00:54:04.570 --> 00:54:07.410
But then they're left like
a puppy in the deep grass.

00:54:07.410 --> 00:54:08.170
How?

00:54:08.170 --> 00:54:10.696
And Anne comes along
and says, here's how.

00:54:10.696 --> 00:54:13.990


00:54:13.990 --> 00:54:16.340
It's a kale sandwich.

00:54:16.340 --> 00:54:19.690
Kale has got thick stem,
which makes it hard to eat.

00:54:19.690 --> 00:54:21.470
So you put your right hand here.

00:54:21.470 --> 00:54:22.700
And you take your left hand.

00:54:22.700 --> 00:54:23.500
And you pull.

00:54:23.500 --> 00:54:26.330
And then you have
a handful of kale

00:54:26.330 --> 00:54:29.470
that looks just like, I mean,
it's like spinach with heft

00:54:29.470 --> 00:54:30.871
when you cook it.

00:54:30.871 --> 00:54:32.440
And it's so much fun.

00:54:32.440 --> 00:54:33.610
In two seconds.

00:54:33.610 --> 00:54:35.090
I mean it's crazy.

00:54:35.090 --> 00:54:36.260
No time.

00:54:36.260 --> 00:54:40.350
And in the meantime over on
the stove I have water boiling.

00:54:40.350 --> 00:54:42.700
And I'm going to cover it.

00:54:42.700 --> 00:54:46.680
And it's going to cook
for about four minutes.

00:54:46.680 --> 00:54:51.330
Mestemacher bread, I like
it really toasted well.

00:54:51.330 --> 00:54:52.970
So it turns into a cracker.

00:54:52.970 --> 00:54:56.100
And then it is so good.

00:54:56.100 --> 00:55:00.281
Cilantro, and the
thing that I love

00:55:00.281 --> 00:55:03.650
the most about this
sandwich is the lemon.

00:55:03.650 --> 00:55:07.740


00:55:07.740 --> 00:55:10.540
I'm going to get all
this zest off this lemon

00:55:10.540 --> 00:55:14.070
so I can put it on that kale.

00:55:14.070 --> 00:55:17.340
And these stems, they'd
be nice right in here.

00:55:17.340 --> 00:55:18.849
You can do anything with them.

00:55:18.849 --> 00:55:27.340


00:55:27.340 --> 00:55:29.015
And just cut up
this a little more.

00:55:29.015 --> 00:55:34.990


00:55:34.990 --> 00:55:37.115
But it's ready.

00:55:37.115 --> 00:55:40.760
Let it all drain out here.

00:55:40.760 --> 00:55:44.820
So we have lemon
zest and lemon juice.

00:55:44.820 --> 00:55:49.660
Makes everything tastes so
much better without any fat.

00:55:49.660 --> 00:55:51.070
OK, let's see about this toast.

00:55:51.070 --> 00:55:54.580


00:55:54.580 --> 00:55:56.670
So now.

00:55:56.670 --> 00:55:57.500
Here we go.

00:55:57.500 --> 00:56:00.260


00:56:00.260 --> 00:56:03.560
Hummus, this is
hummus without tahini.

00:56:03.560 --> 00:56:07.120
Chickpeas, lemon, and garlic,
there's no oil in this .

00:56:07.120 --> 00:56:10.240
So you can just slather
this on nice and thick.

00:56:10.240 --> 00:56:11.840
So we love that.

00:56:11.840 --> 00:56:16.280
And then I'm going to
sprinkle some green onions,

00:56:16.280 --> 00:56:22.350
and some cilantro, you
can use parsley instead.

00:56:22.350 --> 00:56:24.840
And then my lemons.

00:56:24.840 --> 00:56:28.310
And I cut them in little pieces.

00:56:28.310 --> 00:56:29.730
Essy makes me so mad.

00:56:29.730 --> 00:56:36.960
He does not like lemon in his,
so I will leave his without.

00:56:36.960 --> 00:56:41.105
Hand fulls of kale
on top of here.

00:56:41.105 --> 00:56:42.620
It looks crazy.

00:56:42.620 --> 00:56:45.630
And you will not
believe how good it is.

00:56:45.630 --> 00:56:48.970
I'm going to just sprinkle a
little of lemon pepper on top.

00:56:48.970 --> 00:56:54.250
That's ready to
go, after I cut it.

00:56:54.250 --> 00:56:57.740
OK, kale sandwiches.

00:56:57.740 --> 00:57:05.548


00:57:05.548 --> 00:57:07.500
[MUSIC PLAYING]

00:57:07.500 --> 00:57:09.710
The standard
American diet is only

00:57:09.710 --> 00:57:12.770
a variety of about
13 fruits and veg.

00:57:12.770 --> 00:57:14.556
Isn't that sad?

00:57:14.556 --> 00:57:15.930
You can do like
13 in a row here.

00:57:15.930 --> 00:57:18.360
I know.

00:57:18.360 --> 00:57:21.040
In the winter it's really nice
to highlight squashes and have

00:57:21.040 --> 00:57:22.670
a nice hot cooked soup.

00:57:22.670 --> 00:57:26.994
Next I have a nice
beautiful buttercup squash.

00:57:26.994 --> 00:57:28.160
I was raised in restaurants.

00:57:28.160 --> 00:57:30.820
My grandmother, my mom,
my brother, all of them

00:57:30.820 --> 00:57:32.630
have been really in the food.

00:57:32.630 --> 00:57:34.040
This is okra.

00:57:34.040 --> 00:57:34.540
Really?

00:57:34.540 --> 00:57:35.577
That's how okra grows.

00:57:35.577 --> 00:57:37.010
Yeah, this is okra.

00:57:37.010 --> 00:57:38.240
I have never seen okra grow.

00:57:38.240 --> 00:57:41.055
Well, there it is.

00:57:41.055 --> 00:57:42.200
Yeah, it's pretty nuts.

00:57:42.200 --> 00:57:47.180


00:57:47.180 --> 00:57:49.970
I was looked at as a black
sheep for a long time.

00:57:49.970 --> 00:57:53.020
Because I was on
this quest of health.

00:57:53.020 --> 00:57:54.390
I must be on drugs.

00:57:54.390 --> 00:57:55.690
I must be completely crazy.

00:57:55.690 --> 00:57:58.760
Because why is he
eating just plant food?

00:57:58.760 --> 00:58:01.080
Take a bit of that, Chad.

00:58:01.080 --> 00:58:02.700
Oh my gosh.

00:58:02.700 --> 00:58:05.820
My grandma would make an
escarole soup that was so nice.

00:58:05.820 --> 00:58:06.790
That's great.

00:58:06.790 --> 00:58:07.790
It's great for escarole.

00:58:07.790 --> 00:58:10.320


00:58:10.320 --> 00:58:12.970
It wasn't until a
few years ago that I

00:58:12.970 --> 00:58:14.710
started opening my
own restaurants.

00:58:14.710 --> 00:58:17.360


00:58:17.360 --> 00:58:20.050
My family was just like, maybe
he is doing something right.

00:58:20.050 --> 00:58:20.591
You know.

00:58:20.591 --> 00:58:22.465
Especially when they
visited the restaurants.

00:58:22.465 --> 00:58:25.610


00:58:25.610 --> 00:58:26.450
What are you making?

00:58:26.450 --> 00:58:27.570
I'm going to make dinner.

00:58:27.570 --> 00:58:28.403
Do you need my help?

00:58:28.403 --> 00:58:29.956
No.

00:58:29.956 --> 00:58:31.080
OK, I figured.

00:58:31.080 --> 00:58:34.070
When I cook it's
very predictable.

00:58:34.070 --> 00:58:35.070
And the house is a mess.

00:58:35.070 --> 00:58:36.881
If she's making
something with flour

00:58:36.881 --> 00:58:38.255
there's flour all
over the place.

00:58:38.255 --> 00:58:40.320
And my daughter is frustrated.

00:58:40.320 --> 00:58:41.860
When is Papa coming back home?

00:58:41.860 --> 00:58:45.560
When is he going to
start cooking again?

00:58:45.560 --> 00:58:47.725
Right before it's
finished I'm going

00:58:47.725 --> 00:58:50.400
to add some parsley in there.

00:58:50.400 --> 00:58:53.170
And this is just a
nice comforting Sunday

00:58:53.170 --> 00:58:54.305
afternoon soup here.

00:58:54.305 --> 00:58:57.588
[MUSIC PLAYING]

00:58:57.588 --> 00:59:08.720


00:59:08.720 --> 00:59:13.090
This is what, when I was a
boy, a very young boy in Israel

00:59:13.090 --> 00:59:17.260
growing up in a kibbutz, this
is what an individual family

00:59:17.260 --> 00:59:18.570
farm looked like.

00:59:18.570 --> 00:59:22.810
12, 15 cows, a few calves,
and that was enough.

00:59:22.810 --> 00:59:25.800
But I don't think,
I could be wrong,

00:59:25.800 --> 00:59:28.480
but I don't think
that this represents

00:59:28.480 --> 00:59:31.425
the new way we will
feed the masses.

00:59:31.425 --> 00:59:34.035
[MUSIC PLAYING]

00:59:34.035 --> 00:59:36.830


00:59:36.830 --> 00:59:39.720
In the last 50 years
the world's population

00:59:39.720 --> 00:59:44.760
has increased from 2.5 to
more than 6.5 billion people.

00:59:44.760 --> 00:59:47.180
And as the population
grows and demand

00:59:47.180 --> 00:59:50.570
for animal products
grows, more and more land

00:59:50.570 --> 00:59:53.150
is needed for food production.

00:59:53.150 --> 00:59:55.104
So how are we to feed the world?

00:59:55.104 --> 00:59:58.478
[MUSIC PLAYING]

00:59:58.478 --> 01:00:04.670


01:00:04.670 --> 01:00:06.930
In the last few
decades we've turned

01:00:06.930 --> 01:00:10.120
to industrial farming
for the solution.

01:00:10.120 --> 01:00:12.790
Well one of the oldest arguments
in favor of industrial farming

01:00:12.790 --> 01:00:15.380
is that we needed to feed
a growing population.

01:00:15.380 --> 01:00:17.950
It's also one of the most
fallacious arguments.

01:00:17.950 --> 01:00:21.071
Because industrial
farming reduces

01:00:21.071 --> 01:00:23.195
the amount of food available
for human consumption.

01:00:23.195 --> 01:00:24.790
It doesn't increase it.

01:00:24.790 --> 01:00:29.070
It relies on growing grain, and
feeding that grain to animals.

01:00:29.070 --> 01:00:31.390
Sometimes soybeans, as
well as grains, so the meat

01:00:31.390 --> 01:00:34.500
may be artificially cheap, based
on getting subsidized grain.

01:00:34.500 --> 01:00:36.170
And after feeding
it to the animals,

01:00:36.170 --> 01:00:38.270
depending on the
species, say from beef,

01:00:38.270 --> 01:00:41.800
we might get back just 10%,
just one tenth, of the food

01:00:41.800 --> 01:00:43.410
value of what we feed to them.

01:00:43.410 --> 01:00:46.380
From chicken we might
get back a third,

01:00:46.380 --> 01:00:49.120
but we're still
wasting 2/3 of the food

01:00:49.120 --> 01:00:50.330
that we are feeding to them.

01:00:50.330 --> 01:00:53.540
Even in the case of chicken,
which the chicken industry says

01:00:53.540 --> 01:00:54.730
it's amazingly efficient.

01:00:54.730 --> 01:00:59.180


01:00:59.180 --> 01:01:02.710
Professor Eshel has been
evaluating what type of diet

01:01:02.710 --> 01:01:07.110
can produce the most food
from each acre of land.

01:01:07.110 --> 01:01:08.710
This is where we are right now.

01:01:08.710 --> 01:01:12.470
This is how America
eats right now.

01:01:12.470 --> 01:01:16.320
The average American
diet comprising dairy,

01:01:16.320 --> 01:01:20.180
and beef, and pork,
and turkey, and plants

01:01:20.180 --> 01:01:24.560
consumes roughly twice
as much land per person

01:01:24.560 --> 01:01:29.400
as would be required
if that person consumed

01:01:29.400 --> 01:01:31.430
the plant-based diet.

01:01:31.430 --> 01:01:33.890
Those are dramatic
differences, not small.

01:01:33.890 --> 01:01:40.764


01:01:40.764 --> 01:01:42.237
Lyla, you OK, sweetie.

01:01:42.237 --> 01:01:45.183
Yeah, yeah I have soup.

01:01:45.183 --> 01:01:47.650
Soup is good.

01:01:47.650 --> 01:01:53.910
Most people can have no
larger spatial effect then

01:01:53.910 --> 01:01:55.830
their dietary choices.

01:01:55.830 --> 01:02:00.050
Most of us do not
clear cut vast swaths

01:02:00.050 --> 01:02:03.910
of forest or a plow vast fields.

01:02:03.910 --> 01:02:06.680
What we do is we consume food.

01:02:06.680 --> 01:02:11.470
Thereby contracting to
others those activities.

01:02:11.470 --> 01:02:12.070
Food.

01:02:12.070 --> 01:02:12.920
Food.

01:02:12.920 --> 01:02:13.560
Food.

01:02:13.560 --> 01:02:14.536
Food.

01:02:14.536 --> 01:02:18.340
Ah, so good.

01:02:18.340 --> 01:02:20.300
So good.

01:02:20.300 --> 01:02:23.310
Every acre devoted
to food production

01:02:23.310 --> 01:02:26.620
is an acre unavailable
for wildlife.

01:02:26.620 --> 01:02:30.880
Biodiversity losses and
especially extinctions

01:02:30.880 --> 01:02:31.520
are forever.

01:02:31.520 --> 01:02:32.130
That's it.

01:02:32.130 --> 01:02:36.810
Once you lost a
particular species that

01:02:36.810 --> 01:02:39.890
took 10s of millions
of years to evolve,

01:02:39.890 --> 01:02:45.370
you lost 10s of millions of
years of genetic knowledge.

01:02:45.370 --> 01:02:48.320
[MUSIC PLAYING]

01:02:48.320 --> 01:02:56.350


01:02:56.350 --> 01:02:59.000
After a lifetime of
study Colin Campbell

01:02:59.000 --> 01:03:01.040
has developed a
controversial theory

01:03:01.040 --> 01:03:03.941
about the way in which an
animal-based diet affects

01:03:03.941 --> 01:03:04.440
our health.

01:03:04.440 --> 01:03:07.330


01:03:07.330 --> 01:03:09.820
Meat and dairy and
other animal-based foods

01:03:09.820 --> 01:03:11.790
do not initiate cancer.

01:03:11.790 --> 01:03:14.320
I had to go back to
the model for cancer.

01:03:14.320 --> 01:03:19.220
Cancer gets initiated, which
involves chemicals or viruses

01:03:19.220 --> 01:03:20.760
attacking the DNA.

01:03:20.760 --> 01:03:23.000
That's where the cancer starts.

01:03:23.000 --> 01:03:27.740
These kind of foods do not
initiate cancer in that sense.

01:03:27.740 --> 01:03:31.710
What they do is they have all
the nutrients and other factors

01:03:31.710 --> 01:03:35.150
in there that creates
a condition, a culture,

01:03:35.150 --> 01:03:37.100
for the growth of these cancers.

01:03:37.100 --> 01:03:41.680
It creates the condition for
the rise of blood cholesterol.

01:03:41.680 --> 01:03:44.160
And it creates the condition
for the development

01:03:44.160 --> 01:03:48.950
of basically atherogenesis
leading to heart disease.

01:03:48.950 --> 01:03:52.130
In other words, these things
and these kind of foods

01:03:52.130 --> 01:03:53.640
are actually like fertilizer.

01:03:53.640 --> 01:03:59.300
[MUSIC PLAYING]

01:03:59.300 --> 01:04:02.900
There recent level of evidence
that you accept or don't

01:04:02.900 --> 01:04:06.690
accept, depending on
what you want to do next.

01:04:06.690 --> 01:04:08.520
Can you make a
prediction from the level

01:04:08.520 --> 01:04:11.150
of knowledge you have?

01:04:11.150 --> 01:04:14.690
And I will predict that
people consuming animal foods

01:04:14.690 --> 01:04:16.075
are going to
experience problems.

01:04:16.075 --> 01:04:18.800


01:04:18.800 --> 01:04:20.540
In the process of
food production

01:04:20.540 --> 01:04:23.160
what is the single
distinction I can

01:04:23.160 --> 01:04:25.920
draw that separate the
wheat from the chaff?

01:04:25.920 --> 01:04:30.030
That's separates that which is
extremely important from that

01:04:30.030 --> 01:04:32.520
which is truly
secondary or tertiary?

01:04:32.520 --> 01:04:36.900
The answer is the dividing
line between plant

01:04:36.900 --> 01:04:38.640
and animal-based diets.

01:04:38.640 --> 01:04:42.770
The plant-based diet consume
dramatically less land,

01:04:42.770 --> 01:04:46.050
release dramatically
less reactive nitrogen,

01:04:46.050 --> 01:04:49.180
and emit dramatically
less greenhouse gases,

01:04:49.180 --> 01:04:52.940
than the animal-based diet.

01:04:52.940 --> 01:04:55.140
Some people think that
really what we should do

01:04:55.140 --> 01:04:58.225
is just focus on pressuring
the government to make changes.

01:04:58.225 --> 01:04:59.600
And, of course,
it would be great

01:04:59.600 --> 01:05:01.141
if the government
would make changes.

01:05:01.141 --> 01:05:03.840
The government should stop
subsidizing factory farming.

01:05:03.840 --> 01:05:05.920
That would be a big deal.

01:05:05.920 --> 01:05:09.130
But we should not
ignore the difference

01:05:09.130 --> 01:05:11.840
that we can make ourselves.

01:05:11.840 --> 01:05:14.450
Even if it seems small.

01:05:14.450 --> 01:05:17.690
People might say, well it's a
difference you can't notice.

01:05:17.690 --> 01:05:18.940
But in the end it does add up.

01:05:18.940 --> 01:05:22.530
[MUSIC PLAYING]

01:05:22.530 --> 01:05:27.590
It's so easy to
fall back and say,

01:05:27.590 --> 01:05:29.980
well people really won't change.

01:05:29.980 --> 01:05:32.420
They love some of
these bad habits.

01:05:32.420 --> 01:05:34.110
But we can make this happen.

01:05:34.110 --> 01:05:38.940
[MUSIC PLAYING]

01:05:38.940 --> 01:05:43.180
In the next decade the paradigm
will change, maybe less.

01:05:43.180 --> 01:05:46.990


01:05:46.990 --> 01:05:50.950
Science enjoys such a
status in our society.

01:05:50.950 --> 01:05:52.710
People rely on science.

01:05:52.710 --> 01:05:53.530
And we're paid.

01:05:53.530 --> 01:05:58.206
You know, we use the public's
money to do the things we do.

01:05:58.206 --> 01:06:03.480
And so I think we
have a responsibility

01:06:03.480 --> 01:06:06.570
to go back and tell them.

01:06:06.570 --> 01:06:08.862
Policy people, always
wanting to pull back.

01:06:08.862 --> 01:06:10.320
Don't say what they
really believe,

01:06:10.320 --> 01:06:12.170
because it would have
upset the industry.

01:06:12.170 --> 01:06:16.200
I'm not going to be inhibited
by anything or anybody.

01:06:16.200 --> 01:06:19.370
And because it's
far too important.

01:06:19.370 --> 01:06:21.740
far too important.

01:06:21.740 --> 01:06:24.250
Plant-based diets is
where the health is.

01:06:24.250 --> 01:06:25.980
Animal-based diets are not.

01:06:25.980 --> 01:06:28.750
But I also want to put
a second thing on that.

01:06:28.750 --> 01:06:30.555
It's whole plant-based foods.

01:06:30.555 --> 01:06:32.490
What do I mean by that?

01:06:32.490 --> 01:06:37.000
You know, you can be a vegan
and consume plant-based foods,

01:06:37.000 --> 01:06:38.610
and do it all wrong.

01:06:38.610 --> 01:06:39.980
Here's a way to do it.

01:06:39.980 --> 01:06:41.680
You take the whole food.

01:06:41.680 --> 01:06:43.970
Take the sugar out.

01:06:43.970 --> 01:06:46.547
You take the white flower out.

01:06:46.547 --> 01:06:48.880
You take some fat out, because
it's supposed to be good.

01:06:48.880 --> 01:06:50.420
Plant oil is
supposed to be good.

01:06:50.420 --> 01:06:54.510
You put it all together and
you get a danish or a donut.

01:06:54.510 --> 01:06:56.505
That's a plant-based
diet, right.

01:06:56.505 --> 01:06:58.960
But that's not health.

01:06:58.960 --> 01:07:00.740
That gets us in trouble.

01:07:00.740 --> 01:07:02.960
So what I'm really
driving toward here

01:07:02.960 --> 01:07:06.490
is that the whole food,
eating it in tact.

01:07:06.490 --> 01:07:09.200
Figuring out ways how to prepare
it and eat it in the whole food

01:07:09.200 --> 01:07:10.783
is where you get the
real health from.

01:07:10.783 --> 01:07:12.810


01:07:12.810 --> 01:07:15.460
It's all about whole grains,
not processed grains.

01:07:15.460 --> 01:07:18.330
So whole grains, whole legumes,
and then the biggest part of it

01:07:18.330 --> 01:07:21.010
is fruit and veg, in
their most unaltered state

01:07:21.010 --> 01:07:23.440
as you can prepare them.

01:07:23.440 --> 01:07:25.104
Cooking animal
proteins comes very

01:07:25.104 --> 01:07:26.270
familiar to a lot of people.

01:07:26.270 --> 01:07:28.480
Because that's the way that
most of us were raised.

01:07:28.480 --> 01:07:30.950
Getting to know the plant
kingdom a little bit better

01:07:30.950 --> 01:07:32.430
is what I find very exciting.

01:07:32.430 --> 01:07:35.280
When I find a new mushroom,
when I find a new veg, when I

01:07:35.280 --> 01:07:36.490
find a new fruit.

01:07:36.490 --> 01:07:38.240
Look at how beautiful
these mushrooms are.

01:07:38.240 --> 01:07:40.780
I mean, you can't go wrong
with how gorgeous these are.

01:07:40.780 --> 01:07:41.655
And they're so meaty.

01:07:41.655 --> 01:07:44.776
[MUSIC PLAYING]

01:07:44.776 --> 01:07:48.419


01:07:48.419 --> 01:07:50.210
Shifting the way we
think about vegetables,

01:07:50.210 --> 01:07:52.020
making vegetables as
the center of the plate,

01:07:52.020 --> 01:07:53.310
rather than an animal product.

01:07:53.310 --> 01:07:54.870
Or just reconfiguring the plate.

01:07:54.870 --> 01:07:56.494
If you're going to
eat animal products,

01:07:56.494 --> 01:07:57.920
have a little bit
smaller portion.

01:07:57.920 --> 01:08:01.317
Add much more
vegetables to the plate.

01:08:01.317 --> 01:08:02.650
We're going to make some seitan.

01:08:02.650 --> 01:08:04.650
Seitan is a wheat protein.

01:08:04.650 --> 01:08:06.610
Whole wheat flour,
all right, and then I

01:08:06.610 --> 01:08:09.600
have nutritional yeast, I have
some onion powder, a little bit

01:08:09.600 --> 01:08:13.960
of chipotle seasoning, some
veg stock, Marsala wine,

01:08:13.960 --> 01:08:16.071
for sweetener I'm using
a little bit of maple.

01:08:16.071 --> 01:08:17.529
And I'm not using
oil in this, so I

01:08:17.529 --> 01:08:18.695
want to cook it in a liquid.

01:08:18.695 --> 01:08:23.510


01:08:23.510 --> 01:08:24.910
Delicious on their own.

01:08:24.910 --> 01:08:26.229
Seitan is done now.

01:08:26.229 --> 01:08:28.000
It's a great
substitution for a roast.

01:08:28.000 --> 01:08:30.200
If you're going to have a roast
dinner, that's just so nice.

01:08:30.200 --> 01:08:31.830
Some lettuce, tomato,
throw it in a wrap.

01:08:31.830 --> 01:08:33.310
You can throw some
barbecue sauce on it.

01:08:33.310 --> 01:08:34.268
Throw it in a sandwich.

01:08:34.268 --> 01:08:37.485


01:08:37.485 --> 01:08:38.500
We've got some stuffing.

01:08:38.500 --> 01:08:40.200
We have a little bit of mashers.

01:08:40.200 --> 01:08:43.060


01:08:43.060 --> 01:08:47.122
Get some of that seitan roast,
and serve some of this gravy,

01:08:47.122 --> 01:08:47.830
piping hot gravy.

01:08:47.830 --> 01:08:50.439


01:08:50.439 --> 01:08:51.790
Holiday feast, right there.

01:08:51.790 --> 01:08:55.241
[MUSIC PLAYING]

01:08:55.241 --> 01:09:12.120


01:09:12.120 --> 01:09:15.939
Our relationship with
food is complicated.

01:09:15.939 --> 01:09:20.620
It's part of who we are,
what makes our culture,

01:09:20.620 --> 01:09:22.559
and it creates a
sense of community.

01:09:22.559 --> 01:09:27.740


01:09:27.740 --> 01:09:32.029
But really food is a choice.

01:09:32.029 --> 01:09:38.090
And every one of us can choose
to repeat old eating habits,

01:09:38.090 --> 01:09:41.924
or to make the next
dinner a new one.

01:09:41.924 --> 01:09:45.417
[MUSIC PLAYING]

01:09:45.417 --> 01:10:01.590


01:10:01.590 --> 01:10:03.381
Hey Anne, would you
give me a little salad?

01:10:03.381 --> 01:10:08.870


01:10:08.870 --> 01:10:11.380
My favorite
vegetable is carrots.

01:10:11.380 --> 01:10:13.590
Then my favorite
berry is raspberries.

01:10:13.590 --> 01:10:16.052
The corn that Anne
gets at the farm.

01:10:16.052 --> 01:10:24.034
Quinoa, rice,
black beans, water.

01:10:24.034 --> 01:10:26.700
You mean, bok choy, swiss chard,
kale, collards, collard greens,

01:10:26.700 --> 01:10:28.310
beet greens, mustard greens,
turnip greens, cabbage,

01:10:28.310 --> 01:10:30.726
brussel sprouts, broccoli,
cauliflower, cilantro, parsley,

01:10:30.726 --> 01:10:34.473
spinach, arugula, and asparagus.

01:10:34.473 --> 01:10:35.431
You want a box?

01:10:35.431 --> 01:10:36.368
Put it down.

01:10:36.368 --> 01:10:36.868
Pick it up.

01:10:36.868 --> 01:10:38.201
[INAUDIBLE]

01:10:38.201 --> 01:10:38.784
You want some?

01:10:38.784 --> 01:10:40.230
Here, you can have it.

01:10:40.230 --> 01:10:41.190
Oh, that's it.

01:10:41.190 --> 01:10:44.370
That's the only one
from this slice.

01:10:44.370 --> 01:10:45.878
But you are eating them.

01:10:45.878 --> 01:10:48.019
So why am I taking it home?

01:10:48.019 --> 01:10:49.560
You'll have to have
some of this too.

01:10:49.560 --> 01:10:52.450


01:10:52.450 --> 01:10:56.400
This arugula, it's
just really, there's

01:10:56.400 --> 01:11:07.700
nothing else quite so
flavorful as-- Cheers.

01:11:07.700 --> 01:11:09.140
These are peas.

01:11:09.140 --> 01:11:10.762
You know, the Chinese peas.

01:11:10.762 --> 01:11:12.220
You know, they eat
the whole thing.

01:11:12.220 --> 01:11:16.600


01:11:16.600 --> 01:11:17.880
This is really good.

01:11:17.880 --> 01:11:20.485
These are really good.

01:11:20.485 --> 01:11:23.785


01:11:23.785 --> 01:11:24.910
You want to taste the peas?

01:11:24.910 --> 01:11:56.404
[MUSIC PLAYING]