0:07

So the highest compliment I can

0:09

give somebody is inviting them back

0:11

for multiple rounds of conversation on

0:13

this show. So I'm really enjoying

0:16

this conversation with you and exploring

0:18

your way of thinking about health.

0:22

For me, it's a joy to kind

0:25

of, you know, I, let me put it this

0:27

way. I think there are so many people out there who

0:29

are sort of just

0:32

kind of regurgitating the commonly

0:34

taught stuff that's out there.

0:37

And I'm really interested in having

0:39

conversations with original thinkers and people

0:41

who are trying to put the

0:43

pieces together in new ways and

0:46

solve problems in new ways and

0:48

sort of take seemingly disparate areas

0:50

of science and knowledge and sort of

0:52

combine them to generate new

0:55

ideas and new solutions. And

0:57

I see that in you and I

0:59

really appreciate this conversation, this opportunity to

1:01

explore your way of thinking more

1:04

with you. And I hope we

1:06

can continue it probably beyond this conversation as well,

1:09

because there's so much to talk about. And

1:11

I hope our listeners, I know that our listeners from

1:13

the feedback on part one are enjoying

1:16

it as well and getting a lot of value from

1:18

it. So with that

1:21

said, I want to pick up

1:23

on where we left off in

1:25

the last conversation on brain development

1:27

and the idea of two hemispheres

1:29

and how that sort of this

1:31

seemingly sort of I

1:35

don't know what the right word is, like sort

1:37

of obvious thing that's so obvious and

1:40

so commonly taught in basic anatomy that

1:42

it's sort of overlooked as being unimportant.

1:46

You're making the claim that actually it

1:48

is really important. And this fact is

1:50

something that we ought to pay attention

1:52

to and has an impact on

1:54

adult health and how these hemispheres develop

1:56

in different ways, depending on one's.

2:00

childhood environment and other

2:02

factors. So

2:07

with that said, maybe you can give

2:09

a very brief sort of recap of

2:11

this because this will be a week

2:13

later after people listen to the last

2:16

episode. So maybe you can

2:18

kind of recap the meta level

2:20

idea of brain hemispheres and how

2:22

brain development as a child links

2:24

up with adult health. Sure.

2:28

So the high level

2:30

overview is that we all develop

2:32

and grow like a tree from

2:34

the root up through the

2:36

trunk and then through branches. So

2:40

our brain develops from the bottom

2:42

up and when we're

2:44

born, it's fairly immature. And

2:47

then it comes up from the

2:49

brain stem and first the right hemisphere preferentially

2:53

develops in utero and

2:55

in the first two or so years of life. And

2:58

then it switches over dominance to the left

3:00

hemisphere. We start to get more

3:02

complex sentences. We start to get will

3:05

and ego and differences of opinion with

3:07

our caregivers. And we have

3:09

this this back and forth sequencing as

3:13

it's developing up. It's getting

3:15

more and more specialized. So

3:17

things that neurons that were kind of general

3:19

are now doing more and more and more

3:21

specific things. And then it wants

3:24

to come back together to integrate

3:26

into a functional whole. And

3:30

there are various reasons, both

3:32

nature and nurture, why we

3:35

might have a tendency towards one or the

3:37

other. And that's not really a pathology. That's

3:42

the full richness of the human spectrum

3:44

of people. And that can

3:46

be to do with your gifts and

3:48

your personality. But if there's a

3:50

susceptibility there where there's just too much of

3:52

an unevenness, then it can

3:55

become pathology both in

3:58

physically inflammation. immune

4:00

system, psychologically in your life.

4:08

So, what I've observed

4:10

is that if someone

4:12

has a very obvious

4:16

neurodevelopmental problem, then

4:18

that gets picked up. If it's like things

4:21

are really not going well, there are

4:23

functions that are missing, there's serious

4:26

problems that get picked up. The gray areas

4:28

are less likely to get picked up, although

4:30

now more and more things are getting

4:33

assessed and looked at. But

4:35

what is, I would

4:37

say very common is that I find,

4:39

I see adults who are chronically ill

4:42

and they may never have had a

4:44

neurodevelopmental diagnosis. And

4:47

they're exploring all these different things, but what

4:49

they don't realize is that their current problems relate

4:52

back to this unevenness of development and

4:54

that you may try lots of different

4:56

things and you might get some benefit

4:59

from there. But ultimately, if this

5:01

is going on, which is to

5:03

say brainstem immaturity, retained primitive reflexes which

5:05

are never a normal finding in an adult,

5:08

then this is going to be a bottleneck because

5:10

this is your

5:13

infantile development. And if that

5:15

has not finished, even if you're in your 20s or 30s or

5:17

40s or 50s or 60s, then that's

5:20

kind of the first things first in

5:23

terms of having a regulated nervous system, which

5:25

is then leading to a happy

5:27

immune system and gut and

5:31

aspect on life. So

5:33

you kind of alluded to where

5:36

I want to go with this discussion right

5:38

at the end there, which is how this

5:40

idea of brain development during childhood links up

5:43

with the autonomic nervous system. So

5:48

this has everything to do

5:50

with the autonomic nervous system. So the autonomic

5:52

nervous system, you can also think of it

5:54

as the automatic nervous system. It's

5:56

helping us have

5:58

our vital functions. who are getting our

6:01

heartbeat and our breathing

6:03

and our circulation, all those things that

6:05

we're not, fortunately, we don't have to

6:07

think about in order for them to happen. And

6:12

most of those are housed in the bottom of

6:14

the brainstem because again, you think

6:16

of this tree, like what's the first thing first

6:18

here? Well, we need to have a beating heart

6:20

and you're breathing lungs like before we do anything

6:22

else, otherwise we don't have life. So that's gonna

6:24

be at the bottom, that's at the foundation. So

6:27

I see

6:30

people increasingly interested in things like

6:33

heart rate, heart rate variability, respiration

6:37

rate from different angles. So

6:39

I think the first folks who were interested

6:41

in this were probably athletes who were using

6:44

this data to optimize their

6:46

training schedules and to measure

6:50

recovery and things like

6:52

that, or they're using their heart rate targets

6:54

to see what zone they're in, to see

6:56

what they're doing. So that's one group of

6:58

individuals. Another group of individuals are people who

7:01

are having autonomic issues. So

7:03

people who, unless they have pots, so when

7:05

they stand up, their heart is beating too

7:07

quickly or they have low blood

7:09

pressure when they stand up or other dysautonomias, or

7:11

maybe they're fainting or coming close to fainting. And

7:14

then another group are people who

7:16

just like, innocently, like we're like, no, Apple

7:18

watches are cool or a ring or whatever,

7:21

garment, whatever device. And

7:23

they look at it and they're like, oh, huh? It

7:26

said like my HRV is 32, is that good?

7:29

And they just have this data now and they don't

7:31

quite know what to do with it. And

7:34

what I've found for a variety of

7:36

reasons is that there's a lot of

7:38

problems in how this data is interpreted.

7:41

And this is related to neurological

7:43

development, but I would say that most

7:46

people do not understand the

7:48

significance, but to accurately interpret

7:50

heart rate and heart rate variability. And I

7:52

say this because I had

7:55

my own data and I had my patients' data and

7:57

what I was finding in terms of...

8:00

explanation was not matching up to the

8:02

data we had. I took a course

8:04

on heart rate variability. I just

8:07

said I have hundreds of references on my

8:09

computer. I've contacted many of the authors. They're

8:11

not aware or they weren't aware of some

8:14

of the issues in the interpretation of

8:17

heart rate variability. And actually,

8:19

the kind of interesting part of the problem

8:21

is that I'll explain what

8:23

heart rate variability is so that I can bring everyone else

8:25

into the conversation. But so our

8:27

heart, we're used to thinking about our

8:29

heart beat and what that rate is.

8:31

But there's actually

8:34

some variation in

8:36

that rate. And that's actually a good thing. So

8:39

sometimes we think that we want it to be

8:41

steady. But if it's varying

8:43

a little bit, it's showing a dynamic

8:45

flexibility. And actually, really

8:48

what this health aspect is

8:50

is that when we breathe in, the heart rate

8:53

is supposed to increase. It's supposed to speed up.

8:55

And then when we exhale, it's supposed to go

8:57

down. And so having these two systems that are

8:59

communicating well is a really key

9:02

sign of health. That actually may be a better

9:05

marker of health than any other single

9:07

marker available, which is a big statement.

9:10

But in any clinical area,

9:12

it is the strongest predictor of all-cause

9:14

mortality. And it's also a predictor

9:17

of positive things like conscientiousness,

9:19

for example. You were saying

9:22

when we spoke before that that's one

9:24

of the biggest predictors of longevity.

9:27

And there's a relationship there with heart

9:30

rate variability and neurological development. And

9:32

something else positive you mentioned earlier, which is

9:34

athletic performance. 100%.

9:37

Yeah. And so these are all going to have... As

9:40

you said, there's pro athletes and

9:42

high level athletes and other maybe

9:45

recreational athletes who are training hard at a

9:47

high level. I've used this

9:49

for many years. Use

9:52

heart rate variability as an objective

9:54

tool to gauge, Essentially

9:56

to get a window into their body's recovery. Readiness

10:00

for hard training that day. So

10:02

if you you wake up you

10:04

take your a turvy score and.

10:07

It's hi Ah, that means okay, I'm

10:09

going to train hard today if it's

10:11

low means or maybe I pushed too

10:13

hard yesterday. Maybe I need a rest

10:15

day or a light day to day

10:18

and this has been used and and

10:20

very very well validated for. Regulating

10:23

performance and long term training in

10:25

high level athletes and bodybuilders and

10:27

and things of that nature. That's

10:30

right on. And

10:33

there's a little bit of

10:35

the an issue see the

10:37

South on that Globally higher

10:39

hari their ability is associated

10:41

with health less likely to

10:43

die, better development, better consensus

10:45

is better. the Korean performance.

10:48

But there's a small problem is that. It's.

10:51

Really am on one aspect

10:53

of heart rate variability that

10:55

is making this association. And.

10:58

That aspect is cold and respiratory sinus

11:00

arrhythmia which sounds like a bad thing

11:02

is called arrhythmia. But to succeed kid

11:04

thinks is when I described a moment

11:06

ago which is that when you breathe

11:09

in your heart rate goes up and

11:11

when you breathe out your harbingers down

11:13

that his respiratory sinus arrhythmia. That is

11:15

what. Is associated with. All.

11:18

The good thing. But. You

11:20

could have other sources that are not that

11:22

that are making your heart rate more variable.

11:25

And that's when increase your heart rate

11:27

variability but not because her healthier and

11:29

so now that kind of throws a

11:32

little bit of a spanner into the

11:34

works and interpretation but also set explain

11:36

some of the paradoxes of I was

11:39

finding in my patience and and so

11:41

for example I know into athletes Dietz

11:43

for some reason for one reason or

11:46

another the people in the athletic world

11:48

that have been tracking heart rate and

11:50

Henri Bendel the longest are on the

11:53

Scandinavians and the Pins in particular. they

11:55

developed a lot of that's an the gadgets

11:57

and the software to do it but even

11:59

there the skiing team stopped

12:02

using heart rate variability as a sign of recovery

12:04

after a while because at a certain point when

12:06

you start to get a little burnt out, your

12:08

heart rate variability can go up. With

12:10

you. Yeah, I've

12:13

seen some reference to this, some discussion about

12:15

this, but it's never been clear to me

12:17

exactly what the causes are when this kind

12:19

of, from my

12:21

perception, a sort of anomalous rise

12:25

in heart rate variability that is

12:27

a sort of deceptive high heart

12:29

rate variability. When that happens, what

12:31

are the factors that actually caused that? So

12:34

I've got, this has like been the

12:36

question that's been guiding a lot of my research

12:38

for the last few years because at first, when

12:41

I went to look, there was no acknowledgement that

12:43

this even existed. So what I was finding was

12:45

that I had patients who when they got stressed,

12:47

their heart rate variability was going up. And

12:49

once you decide that what they're reporting is

12:51

accurate, then you need

12:53

to figure out why. And what I found was

12:55

that nobody was acknowledging this as

12:57

a thing that is a phenomenon that exists. And that's actually

12:59

when I found that paper from,

13:02

I think it was the Norwegian cross country scheme.

13:05

I said, we no longer use this for this reason, but

13:08

it actually has to do

13:11

with a Holly-Vegel theory. So

13:13

we've mentioned this briefly previously,

13:16

but Holly-Vegel theory was developed

13:18

by a doctor named Steven

13:20

Porges, who realized

13:22

he'd been studying heart variability in the

13:25

vagus nerve for a long

13:27

time, since the 1960s. And

13:29

he was doing research in a neonatal

13:32

intensive care unit. And what he

13:34

found was that as the babies there

13:36

are sick, obviously that's why they're there, as

13:40

they became, as their situation worsened,

13:44

as they got kind of closer

13:47

and closer to more danger zone

13:49

of perhaps dying or

13:51

anything like that, their

13:53

heart rate would drop, but their

13:56

heart rate variability would go up. But

13:58

this was not a sign that... were

14:00

improving. This was a sign that they were in

14:03

more danger of what's called neurogenic

14:05

bradycardia, which is not, or they had neurogenic bradycardia, which

14:07

was more danger than their heart would stop. And so

14:09

it was a bit of a paradox. And

14:12

so I actually contacted him a year ago, saying, what

14:14

is going on? That there's this, there

14:17

seems to be a phenomenon where people are

14:19

getting more stressed and their heart variability is

14:21

going up. And he said, you just rediscovered

14:23

the vagal paradox that led me to develop

14:26

polyvagal theory. So I think

14:28

a lot of people are becoming

14:30

increasingly aware of polyvagal theory, especially

14:32

because it's immense importance of understanding

14:35

the autonomic nervous system and

14:37

how it responds to trauma

14:41

and trauma responses. But

14:44

what the reason why, to answer your

14:46

question, why increased

14:48

heart rate variability is usually associated

14:51

with being healthier, but sometimes

14:53

it's not, is because the, when

14:58

we have that kind of, that more

15:00

newly evolved, later developed ventral

15:02

vagal part of the, of the

15:04

vagus nerve that's associated with resilience

15:06

and recovery and good digestion, all

15:08

that sort of fitness, that will

15:10

increase heart rate variability. But so

15:12

will that shutdown of life threat

15:14

will also increase heart rate variability.

15:17

My instinct, and I'm finding some support

15:20

for this in the literature, but one

15:22

thing I would love to see happen

15:24

is if you, one way to

15:26

test whether or not your

15:29

heart rate variability measures going

15:31

to be reliable or how to interpret

15:33

it, it's to do what's called an

15:35

orthostatic tolerance test. So when

15:38

you go from lying

15:40

down or sitting to standing up, your

15:43

heart rate should go up, your

15:45

blood pressure should go up. Now, if

15:47

it goes, if your heart rate goes up too much,

15:50

that's called POTS, postural

15:52

orthostatic tachycardia syndrome. And

15:55

so that is POTS, the

15:57

vagus nerve, the break of the

15:59

vagus nerve, this nerve should come off gently

16:01

to gently allow the heart rate to go

16:03

a little bit faster. But

16:05

if the vagal tone is not that

16:08

strong, then when you stand up, it's

16:10

the brake flies off, and then your

16:13

heart starts racing too much. Conversely,

16:16

if you stand up, and your heart

16:18

rate doesn't go up, maybe even it goes down,

16:21

and your blood pressure doesn't go up, which is

16:23

a problem because you need the blood pressure to

16:25

go up to keep the brain perfused. So

16:27

if you stand up, and your blood pressure

16:29

does not go up or it even goes down, that

16:33

is a sign that the

16:36

dorsal vagal, that survival

16:38

shut-in part of the

16:40

vagus nerve is too active, and it's

16:43

not releasing that brake to allow your

16:45

body to adapt to the new situation

16:48

of standing up. So if someone is

16:50

in that camp, then I would question

16:52

the interpretation of a higher heart rate

16:55

variability, meaning that they are healthier for

16:57

that person. Very

16:59

interesting. I know there's some sort

17:03

of technical aspect of whether

17:05

the heart rate variability is taken standing,

17:07

seated, or laying down, and you can

17:09

get different numbers depending on that. I

17:12

wonder if, given what you just explained,

17:14

if one

17:16

of those options of taking

17:19

HRV might be particularly more

17:21

accurate in eliminating the

17:25

variation in people with POTS. Yeah,

17:29

I think there are different

17:31

opinions on that, and there's a lot of literature

17:33

on, there's even like a

17:36

task force paper on the

17:38

right and wrong ways of taking HRV.

17:40

What I can say is that taking

17:42

a heart rate variability measurement in

17:45

different positions is a different measurement. It's a different

17:47

thing. You don't want to compare

17:49

apples to oranges. If you're using this as

17:51

a measure as an individual, then you just

17:53

need to make sure you're consistent. So

17:56

if you're going to do it sitting, do it sitting. So

17:58

it's interesting given... And this

18:02

sort of some

18:04

demographic of people or some

18:06

instances, some scenarios, contexts and

18:09

some people where heart rate

18:11

variability goes up but

18:14

is sort of deceptive in

18:16

that way is not actually indicative of

18:18

better health. It's

18:21

interesting to acknowledge that still

18:23

despite that, heart

18:26

rate variability is robustly, as you

18:28

said, you even made the case, I would

18:31

maybe push back on this a little bit but

18:33

that's a different discussion. I think it's, I

18:36

largely agree with you that it's one of the absolute best

18:38

markers. So it's interesting

18:41

that it is so robust in predicting

18:44

health outcomes and mortality

18:47

even in spite of the fact

18:49

that sometimes you can have high

18:52

heart rate variability in instances where

18:55

it's not really painting

18:57

an accurate picture. A

18:59

hundred percent. Well to give you an example

19:01

that actually I just got from my dad

19:03

when I had a conversation with him recently

19:05

is that if you look at weight in

19:07

the population then we'll get a global trend

19:09

of as people become more overweight then their

19:12

health tends to be worse and their longevity

19:14

tends to be less. But

19:16

it's a J-shaped curve. So people

19:18

who are at the bottom end will also tend

19:21

to have health problems as well. But

19:24

if you are not, if

19:26

you're zooming out of, if your level

19:28

of zoom isn't right or if you're not asking

19:30

the right question then that relationship

19:33

between weight and longevity is going to hold as

19:35

a positive relationship even though people at the bottom

19:37

end are going to have the reverse or

19:41

they might need to gain weight to be healthier. I

19:43

might add a nuance or an additional sort

19:46

of distinction there. I would say there's a

19:48

lot of things like that where we

19:50

find a J-shaped curve

19:53

or U-shaped curve where both being on

19:55

the high end and the low end

19:57

are problematic. I mean even things like cholesterol.

20:00

all levels and LDL

20:02

levels you can find the

20:24

risk of mortality is just as high

20:30

as you can find. So, I think there's a lot

20:32

of things like this, testosterone and many other hormones. MTOR

20:35

is actually the key molecule to

20:37

signal summer metabolism. Yeah.

20:40

Okay, interesting. So, maybe we'll come back to that. Okay,

20:42

so one nuance that I

20:44

wanted to add, this is what I thought your

20:46

dad was going to say, and

20:50

I have some personal experience with

20:52

this because I have many

20:55

times in my life been told

20:57

that based on BMI, I'm overweight.

21:00

Right? And I'm, you

21:02

know, generally I hover around 9 to 12% body fat. I

21:04

have abs. Right?

21:08

So, I'm based on this

21:10

simple measurement, which is just a function

21:12

of weight over height. Rather

21:16

than taking actual body fat percentage,

21:18

it tells people who are athletes

21:20

and who are muscular that

21:23

they are more in the overweight category

21:25

often. And so, that is sort of

21:27

disrupting that metric to a large degree

21:30

by lumping in athletes with lots of

21:32

muscle mass who are highly fit with

21:34

people who are actually overweight and sedentary.

21:37

Yeah, BMI, in my opinion, is a

21:39

measurement that only makes sense to apply

21:41

to people who are obese. It

21:44

doesn't make sense to apply that measure to anybody else.

21:46

Right. Or I suppose I'm very

21:49

underweight. Yeah. I

21:51

want to go back to polyvagal theory for

21:53

a minute. And I'm just curious, since you've

21:55

explored it in depth, I

21:58

know that there is some pushback in sort of the certain

22:00

circles against this theory. And I think

22:02

there's one researcher in

22:04

particular that has really gone after

22:07

Steven Porjes and written a number of

22:09

peer reviewed papers kind of attacking him

22:12

and attacking this theory and saying that

22:14

this is a bunch of pseudoscience and

22:16

it's all, there's no such thing as

22:18

this polyvagal stuff. It's all a bunch

22:20

of nonsense. What are your thoughts on

22:23

that? Yeah, that's a

22:25

great question. When I

22:27

first came across polyvagal

22:29

theory, I

22:31

immediately found it very useful. And that's the

22:33

thing with any model, it's not so

22:36

much like, is it the ultimate

22:39

truth? Is this useful? Is this accurately

22:42

describing something in a way that

22:44

makes it helpful to navigate things

22:46

to solve problems? So when

22:49

I came across it, I thought,

22:51

wow, because what it's replacing is

22:53

this idea that it's called arousal

22:55

theory, that it's kind of this linear,

22:57

like you're more awake or you're more asleep in

23:00

terms of your nervous system. So I

23:02

was like, wow, this is really interesting. And then my next

23:04

question is, well, is this valid? Is it true? Is

23:06

it a real thing? And amongst the people,

23:09

different people I was studying with, some people said

23:11

it was BS and it wasn't a real thing.

23:15

Other people that are respected said that it was

23:17

valid. And I'm very

23:19

interested in it. So I did a

23:21

deep dive and I read most of

23:23

what that author has written and other

23:25

people have written and there are

23:27

blogs called Polyvagal Theories Dead. And so I've looked at their

23:29

critiques and they were interesting

23:31

and they were compelling. And to

23:34

his credit, Dr. Portis

23:36

has written kind of a response

23:39

to that, I think it might be a chapter in a new

23:41

book. A lot of times

23:43

they are arguing against something that he never

23:45

said, and that happens a lot. And the

23:49

key paper where he first presented

23:51

Polyvagal Theory was written in 1994 and

23:53

it's very easy to find. So there's no

23:55

like him not being honest

23:57

because it's just there. And

24:00

so sometimes it's that he never

24:02

said something. Sometimes it's like they're

24:05

arguing with a specific detail

24:07

that even if there's

24:09

validity to that criticism, it doesn't

24:12

really detangle the accuracy or usefulness

24:14

of the theory. So I think

24:17

one example was where he's talking

24:19

about the evolutionary development

24:21

of the system and

24:24

where you have the dorsal-vagal system first. And dorsal

24:26

just means, think of it like a dorsal thing,

24:29

it's just kind of on the backside. Then you

24:31

have the sympathetic nervous system and then you have

24:33

the central-vagal system and how that

24:35

evolved. And I think one of the critiques

24:37

is that they can find like a really

24:40

old fish that has a central-vagal nerve

24:42

and therefore the whole thing is

24:44

BS. And I don't wanna kind

24:46

of misrepresent Steven Ford as

24:48

a very eloquent rebuttal, but at least in

24:51

my mind, I'm like, this doesn't completely

24:54

de-bounce the whole theory, you know, and the theory is sound. I

24:58

also did a very deep dive on the

25:00

neuroanatomy of the vagus nerve because some of

25:02

these things are just really easy

25:06

to refuse or to support from

25:08

a neurophysiological

25:10

perspective. Like are there

25:12

two nuclei,

25:15

which is like kind of this, I

25:17

think it's like, you know, hooking up like an old

25:19

school stereo system. Like where you just put things in

25:21

and out and you know, and you have your speakers

25:23

and the players and stuff. So there

25:25

are two nuclei, okay. And then there's all these

25:27

studies like what happens when you either

25:30

chemically block one of them or if

25:32

you surgically block

25:34

one and you can see the differences

25:36

in response. Another one of the critiques,

25:38

which I thought was unfair was

25:41

talking about in those types of studies, you

25:43

know, if you block, I think the

25:45

ventral vagus aspect, you know, what

25:47

does the heart do? But really

25:50

a big point of

25:52

this theory is context. So

25:56

when you're under life threat

25:58

is what he's saying is that... the vagus nerve will

26:01

cause this bradycardia that's floating down in the

26:03

heart. And so for me, those studies didn't

26:05

really answer that question. So it's

26:07

not a coding question. It's an ongoing

26:09

debate. I've been following it with interest for quite

26:11

a few years. I've read both

26:14

sides of it for a long time. Um,

26:16

I think that Dr. Portis's responses

26:18

were very eloquent and like I said,

26:21

like with most of these things, they're making arguments

26:23

against something that he never said. Mm-hmm. I

26:26

want to circle back to HRV, uh, and

26:31

quote you because in one

26:34

of the presentations that I watched of

26:36

yours, you started out with a slide

26:38

that says how HRV

26:40

connects your cells to the

26:42

universe. What

26:44

the hell do you mean by that? This,

26:48

this sounds very, I know you kind of

26:50

get into the traditional Chinese medicine stuff, but

26:52

what, what does it mean that heart rate

26:55

variability connects ourselves to the universe? Yeah.

26:57

So if we step way back for

27:00

a moment, um, you know,

27:02

and there's a number of ways I can explore this,

27:04

but a lot of branches of physics are looking at

27:06

this. Uh, some of my study

27:08

with my teacher, Dr. Ed Neal, who's studied

27:11

the naging a lot, has been looking at

27:13

this, um, is this

27:15

idea of, you know, what is the universe made

27:17

of, you know, and how does the universe function?

27:19

And we're like kind of now well away from

27:21

our, uh, double blind placebo control channels. This is

27:23

like, yeah, you're, this is, I think just

27:25

based on what you just said, this is

27:27

officially the most meta we've ever gone on

27:29

this podcast. Yes. What is

27:32

the universe made of? What

27:34

is the universe? Well, it's a really good starting point

27:36

for all of these conversations. I don't know why we

27:38

don't know it starts there. Um, all

27:40

conversations should start with that question.

27:42

All my conversation. And

27:46

another researcher I want to bring in, um, is

27:48

Dr. Irv Dardich who developed something called super wave

27:50

theory, but what all these

27:52

things have in common and you know, there's

27:55

ongoing discussion for this, but there's an idea

27:57

that the universe is made of waves.

28:00

of resonance patterns, of movement,

28:03

of oscillating motion. And

28:07

of course that may sound esoteric,

28:10

maybe those folks were onto

28:12

something, but also physics

28:14

talks about this too. So we're

28:16

talking about a worldview where we

28:19

tend to think about the universe as being made

28:21

of stuff. And my table is

28:23

solid, but you know, we

28:26

will find that it's mostly made of open space. And

28:30

that's just it. So the

28:33

Ne Jing, which is a 2,500 year old

28:35

text on

28:38

which all of Chinese medicine is based, I

28:41

study with a very brilliant

28:44

human named Dr. Ed Neal, who is

28:47

a medical doctor and he was an

28:49

emergency room physician. And he spent decades

28:51

translating the Ne Jing. And when he

28:53

read it, he discovered that it doesn't

28:56

really say what most of us were

28:58

taught in Chinese medicine. And

29:00

it says a lot of really important things for

29:03

all curious people. It doesn't matter if you're an

29:05

acupuncturist or not, or if you're into Chinese medicine

29:07

or not, it doesn't matter if you're interested in

29:09

how things work and these patterns of

29:12

the universe, then if you're a curious

29:14

person or even an artist, these are

29:16

really important ideas. And

29:19

so it's really coming back to this

29:21

idea that the universe is made of

29:23

a breath motion, of an inhale and

29:25

an exhale. And we can see this

29:27

everywhere we look. So if

29:30

we understand reality from that lens, again,

29:32

I'm not saying if it's right or wrong, but let's

29:34

say, could it be potentially useful?

29:37

Then what

29:39

we are seeing is that we have waves

29:41

embedded in waves, waves

29:44

nested in waves, or as

29:46

Erb Dardik would say, waves waving within waves. I always

29:48

say when I talk about this, that we should do

29:50

like a drinking game, you know, we take a shot

29:52

every time I say wave. So

29:55

the way heart rate variability connects ourselves

29:57

to the universe is that, We

30:00

have these much larger patterns and some

30:02

might argue that the existence of the

30:04

universe is just a single inhale and

30:07

exhale like the single expansion and contraction,

30:09

but then within it we have our

30:11

Monday lives. But our heart beating

30:13

is a wave. We tend to think of it

30:15

as a rate like that boom, boom, but you

30:17

see how my motion I'm going in, out, in,

30:19

out. That's a wave. And so

30:22

heart rate variability is measuring the

30:25

coherence of that wave and it's really

30:27

the neurological regulation of the heartbeat, but

30:29

it's letting us know how

30:31

well developed our nervous system is and how

30:34

resilient our nervous system is and

30:36

how well functioning it is. And

30:38

the way it connects this

30:40

very big thing, this very small thing is

30:42

that it connects

30:44

these larger, I

30:47

said cosmological patterns, even just like an

30:49

annual cycle. So whether it's summer or

30:52

winter, it connects that to the

30:55

very, very fast oscillations in ourselves.

30:57

And the cell danger response is

31:00

really describing the healing

31:03

wave when a cell gets

31:05

injured. So we can use heart rate variability

31:07

to connect those two things. Actually, I'll go,

31:10

let me make the point a little bit further. The

31:12

reason why the heart rate variability connects

31:14

to what the cells are doing is

31:17

through the vagus nerve. So

31:20

when cells get stressed

31:22

or injured or infected, they

31:24

go through a three step healing cycle and that's

31:27

what Bob Navio called the cell danger response. And

31:29

when they're not doing that, then they're just cycling

31:32

between day and night. Okay. The

31:35

vagus nerve is a big

31:37

part of what connects

31:39

ourselves to our

31:42

brain and our heart to our

31:44

brain. When we,

31:46

let's say, have an infection, and

31:48

this is what not enough people realize it's

31:50

okay when we have an infection, our

31:54

body intentionally, let's say like

31:56

the cells, it intentionally removes them from

31:58

the network. The cells intentionally. move themselves

32:01

from the network so that they can heal. So

32:04

they're going to stop really being

32:06

like one of my cells and part of this

32:08

network. And they're going to just focus on being

32:10

an individual cell so they can go through this

32:12

response. If someone is sick enough to the point

32:15

where they don't feel well and they have to lie down and

32:17

they have symptoms, the vagus nerve is

32:19

actually going to turn itself down in

32:21

order to reduce the coherence of

32:24

the system, in order to reduce the complexity of

32:26

the system so that it can go

32:28

through this process. So

32:31

this is the connection between the heart

32:34

rate variability, because what we know from these

32:36

studies is that if you are sick, your

32:38

heart rate variability is lower. Why?

32:40

Because when you are sick, your body,

32:42

in its infinite wisdom of billions of

32:44

years of evolution, has decided that what

32:46

it needs to do in order to

32:48

go into healing mode is

32:50

to turn down the vagus nerve, turn down

32:52

the coherence of how well all of these

32:55

cells are working together so

32:57

that these parts can run these

32:59

older, more primitive programs in

33:01

order to heal. Therefore, you will

33:03

have a lower heart rate variability.

33:06

And when you are healed, then

33:08

that heart rate variability will go

33:10

up. So amongst people who

33:13

are aware of the vagus nerve, there is

33:15

a very popular trend of just stimulating it,

33:17

however you can. Like, that's that thing, and

33:19

get it on. And sometimes that is a

33:21

result of the health outcome, and sometimes it

33:24

doesn't work. But if we understand that we

33:27

get our chicken and egg going back

33:30

again, that the first step is that

33:32

it is by design that vagal tone

33:34

goes down when we are stressed or

33:36

we are sick, and that when

33:38

we complete the healing cycle, it'll come back on.

33:41

That's part of the reason why we have this

33:43

strong relationship between heart rate variability and health. Are

33:47

you ever going to answer that chicken and egg question,

33:49

by the way? Are we going to get the answer

33:51

from you? I feel like you keep debating the question.

33:54

I know. Maybe I'll put it in the book.

33:56

We'll get it. We've got to buy the

33:58

book to find out the answer. Yeah. Okay.

34:01

So let's talk that

34:04

heart rate variability and how

34:06

this is, I mean, you've

34:08

kind of just explained it, but can

34:11

you sort of concretize how this is

34:13

connecting to our risk of various diseases

34:15

and mortality? Why is it

34:17

such a strong predictor of death and or

34:21

vice versa? Why is high heart rate

34:23

variability, generally speaking, with some exceptions, generally

34:26

a very good predictor of health

34:28

and performance? So

34:31

from my perspective, it's telling us two things.

34:34

One of those things is people are more

34:36

aware of and one of those things I

34:38

want people to be more aware of. So

34:40

higher heart rate variability is associated with greater

34:42

health because it

34:45

means that the system

34:47

is more coherent. It means that the

34:51

big anti-inflammatory reflex of the body

34:53

is through the vagus nerve. And

34:55

so again, this is another measurement.

34:58

Heart rate variability is very

35:00

strongly correlated with inflammation because

35:02

heart rate variability comes from vagal tone,

35:05

the healthy version of heart rate variability comes from

35:07

vagal tone and vagal tone

35:10

has the anti-inflammatory response for

35:12

when we are stressed or infected. And

35:16

it's also telling us about

35:18

the development of higher cognitive

35:21

functions. So executive function, conscientiousness,

35:23

compassion, and all

35:25

this prefrontal cortical activity are

35:27

also associated with higher

35:30

heart rate variability. So

35:33

it's a strong relationship because we're looking at different

35:35

windows into the same system. So what I found

35:37

is very few people have kind of made

35:39

the connection of why

35:41

like oh, okay, inflammation, chronic

35:43

inflammation is a problem and vagal tone seems

35:46

to be good. But now if we look

35:48

through the perspective of cycles of healing cycles,

35:50

then it starts to make sense about the

35:53

connection with those. Now, the

35:55

other area that I won't kind

35:57

of now really putting together, but

36:00

now is making more sense and it's very relaxation

36:19

and compassion and empathy but

36:32

the sympathetic nervous system comes online

36:35

and then the ventral vagus nerve

36:37

comes online and it in

36:40

utero but it gets developed and

36:42

myelinated throughout. Melanated

36:45

means that it's getting kind of covered in

36:48

a way that makes it work faster throughout

36:50

the first year of life. If

36:52

you have a stressful start

36:55

to life, for

36:58

whatever reason there were stressful

37:01

pregnancy, illness

37:03

at birth, mom was stressed, the

37:06

whole nine, whatever it is or you don't

37:08

have a consistent and

37:11

connected and responsive caregiver or

37:14

safe environment, then

37:16

your ventral vagus nerve is not going

37:18

to develop and myelinated as well and

37:21

that's going to lead to lower heart

37:24

rate variability. I

37:26

tend to think of the lifespan, well

37:29

the lifespan is another one of these waves, inhale

37:33

and exhale. You can look at everything as

37:35

inhale and exhale and so

37:37

it may be that you do well

37:39

enough depending on your individual situation, maybe

37:41

you're okay in your 30s but

37:44

development didn't proceed optimally

37:47

so now you're starting to decline whereas it used

37:49

to be people might not decline in their health

37:51

until 50s or 60s. That's

37:54

part of it too. Heart rate

37:56

variability is associated with health because of this

37:59

more direct relationship

38:01

between inflammation and illness

38:04

and your systems of your body

38:06

working together and it's also telling

38:08

a story about how well

38:10

your development proceeded. The

38:14

way you're looking at this is very interesting and it's

38:17

to some extent novel

38:20

to me. I mean I kind of

38:22

assumed that there was some layer of

38:26

genetics and early life that

38:28

will be a determinant of

38:31

one's sort of maximal

38:34

potential heart rate variability. But

38:37

coming from the athletic performance world I'm

38:40

used to really looking at HRV in

38:42

a sort of very dynamic, malleable,

38:45

trainable way where we're

38:47

analyzing, okay, from day to

38:49

day my heart rate variability

38:51

is fluctuating a lot and

38:53

I can gain insight into my

38:55

body's recovery status and how well I can

38:58

train it today based

39:00

on what I ate yesterday, how well

39:03

I slept, how late

39:05

did I go to bed, how deep was my

39:07

sleep, how hard I

39:09

trained yesterday and these

39:11

kinds of factors and the longer

39:14

term is also understanding that

39:17

one's fitness level is a

39:19

hugely important determinant of their

39:22

sort of baseline range

39:24

of where that heart rate variability will

39:26

land. Somebody who is a

39:28

highly fit and there's lots of data on

39:30

this online, somebody who's highly

39:33

trained, very fit

39:35

athlete is going to have way,

39:37

way higher baseline HRV scores than

39:39

somebody who is sedentary. So when you're talking

39:41

about this kind of decline with age, it's

39:45

interesting that you're kind of looking to

39:48

the childhood development of the autonomic nervous

39:50

system whereas my brain would seek to

39:52

explain that by saying, well,

39:54

yeah, most people sort of become more sedentary as they

39:56

get older and lose their fitness and this is sort

39:58

of a... obvious, like

40:01

low-hanging fruit explanation of why

40:03

HRV would decline as they

40:05

get older. Yeah,

40:08

I love that. And that, everything you're saying makes

40:10

sense. So, you know, if we use this principle

40:13

of waves waving within waves, you

40:15

can look at heart rate variability and you can

40:17

change heart rate variability like this minute. Like if

40:19

we decided to just go rogue on this podcast

40:22

and do a breathing exercise and get

40:24

all zen, we could change our heart rate variability in

40:26

this minute we're together regardless of how well we slept

40:28

and what we ate. We can

40:30

also change it. It will

40:32

change from day to day based on training schedules

40:34

and, you know, how much gluten, weight and all

40:37

these lovely things. And that sort of thing.

40:39

It will also change if we come down

40:41

with a virus or that as well. And

40:44

what I want to point out is that

40:46

it can also, there's also a more of

40:48

a lifespan aspect to it. Also,

40:50

bringing this back to the right and

40:53

left hemispheres of the brain, this

40:57

bagel and brain regulation of heart

40:59

rate is more coming from the

41:01

right vagus nerve. And

41:03

so there's also a skew that people who

41:05

are a bit more right

41:07

brain dominant will tend to have higher

41:10

heart rate variability, which

41:12

may come from both healthy and unhealthy sources.

41:14

So I've had patients who are more left

41:16

brain dominant, who have just a very tend

41:19

to have a low heart rate variability. I

41:22

have patients who are more right brain

41:24

dominant and who are having autonomic dysfunction,

41:27

pressure issues, stress and anxiety. They have

41:29

a high heart rate variability. And again,

41:31

it's not coming from that zen like

41:33

connection between their breathing and

41:35

their heart rate. It's coming from, you

41:38

know, more of an activation from this

41:40

side. And so it

41:42

is, you know, interesting and important to layer

41:44

on the development, especially with athletes, where their

41:48

athletic talent might be layered

41:51

in with their development. So maybe they're more right

41:53

brain, they have more of a kinesthetic awareness, maybe

41:56

they're a dumb jock, you know, say that

41:58

without any judgment,

42:00

like maybe that's how they ended up here

42:02

and then they tend to have a higher

42:04

resting heart rate variability. Like there's a relationship

42:07

there. But also when

42:10

we think about heart rate variability, the measurements

42:12

tend to be taken from minute to minute

42:14

and it's just sort of you're sitting there

42:16

and breathing and then a software is calculating

42:18

this for you. But one of the things

42:20

that Irving Dardich who's developed super wave theory

42:22

and was looking at heart rate variability, he

42:24

has a little bit of a different take

42:27

on it, which I really liked, which is

42:29

also looking about what happens when you are

42:31

standing and then you sprint and

42:34

then you sleep. So when

42:36

you sprint, your heart rate will go up

42:38

and then when you stop, it will come

42:41

down. And this is also a completely valid

42:43

measure of your health when you're talking about

42:45

athletic performance and training. And the

42:48

folks who will have the higher heart rate

42:50

variability in general will be the sprinters rather

42:52

than the marathon runners, where we're getting

42:54

this variation between their

42:57

highest heart rate and

42:59

their lowest heart rate. And there are studies looking at

43:01

this as well, which is not just what is your

43:04

heart rate and not just what is

43:06

your heart rate variability the way we normally measure

43:08

it, but what is the difference between your resting

43:10

heart rate and your maximal heart rate?

43:13

So how well can you get your heart

43:15

rate up and how long does

43:17

it take you to get it back down? And

43:19

these are more kind of dynamic measurements, but these

43:21

are actually the really key

43:23

measurements of autonomic health and

43:26

longevity and fitness. There's

43:32

an interesting focus on heart rate,

43:35

not heart rate variability, but just

43:37

heart rate and pulse

43:39

in traditional Chinese medicine. They

43:43

measure the, you

43:46

fill in the blanks here, but they measure like the

43:48

frequency of the pulse, but they try to get a

43:51

feel for the strength of the pulse. Can

43:53

you talk about What exactly

43:55

they're doing there in a more intelligent way

43:58

than I just described? Because You. The

44:00

lot more familiarity with traditional Chinese medicine

44:02

and ah, an animal or how that

44:04

ties into the broader discussion were having

44:06

here. Yes absolutely am and

44:09

I'm not going to put my itself

44:11

for the that his assists postmaster to

44:13

such as not gonna be accurate and

44:15

and all the different styles and. Little

44:18

Bites many cases South here is really focused

44:20

more on the concrete things that we can

44:22

explain by Alpha One, it. Recognizes.

44:25

Lotta things that are going on that we

44:27

can explain a list of i can explain

44:29

and that those things are happening to and

44:32

for the want to make everything super heavy

44:34

of couldn't be just as but strips of

44:36

the pollsters along a lot. That and just

44:38

like I was saying about the gardener who

44:41

can look out at landscaping get a ton

44:43

of information. Very specific an accurate information because

44:45

the train their eyes. Similarly,

44:48

And this is someone is trained

44:50

in the art of post diagnosis

44:52

stay train their fingers to get

44:54

a ton of information about the

44:56

health and the dynamics of the

44:58

person by listening and feeling with

45:01

going with the pulse and so

45:03

some of the things that they

45:05

are feeling for have you say

45:07

it's like the race in the

45:09

rhythm and the also feelings for

45:11

like how on hobble or soft

45:13

the vessel is itself and that

45:15

again we can understand that Billie

45:17

relates. To circulating hormones and

45:19

it's a circulating and. And

45:22

other factors that via beta construction

45:24

visit dilation essentially and they're also

45:26

feeling for the shape of the

45:28

waveform and so it would you

45:31

get. It's almost like you're playing

45:33

guitar licks can put your fingers

45:35

on and listen and as you

45:37

push down do feeling or does

45:39

the relative strength of the posts.

45:42

Between that the. A

45:44

different depths and so people who

45:46

are excellent at this can get

45:48

a lot of object of li

45:51

verifiable information about their patients. Ah,

45:53

by doing this. it's

45:56

interesting that whole methodology was

45:58

even created prior to

46:00

the age

46:04

of modern humans now where

46:06

I would imagine that there

46:08

are even much larger differences

46:12

between individuals in

46:14

those sort of parameters

46:16

of pulse rate, pulse frequency, pulse strength

46:18

and these sorts of things just

46:21

by virtue of the fact that

46:23

in more ancient times people had

46:25

a more physically active lifestyle not

46:28

because they went to the gym but

46:30

because their life required maybe being out

46:32

in the fields or doing some kind

46:34

of manual labor rather than sitting at

46:37

a desk and being at a computer.

46:39

So you didn't have like in among

46:41

modern humans we have a much broader

46:44

range between sedentary humans who

46:47

really have virtually no

46:49

physical activity to high level

46:51

athletes who have an extremely

46:54

trained cardiovascular system where

46:56

they have physical adaptations at

46:59

the level of the heart where the

47:01

heart muscle the ventricle muscle thickness is

47:03

much stronger there's a much

47:06

larger ventricle much better

47:08

stroke volume decreased resting heart

47:10

rate also lots

47:13

of adaptations in the vasculature itself

47:15

and capitalization that would I would

47:17

imagine influence all of this as

47:20

far as what a practitioner would discern

47:22

by feeling a person's pulse pretty

47:24

dramatically much more so than you know

47:27

the range of differences that one

47:29

would have experienced thousands of years ago in

47:31

ancient China. That's probably I

47:33

think there's a lot of truth to what you

47:35

just said I think that in general there's just

47:37

a kind of greater spread of what humans are

47:39

up to but what you've reminded me

47:42

of which I always find to be a very comforting

47:44

thought because I think you know when you study

47:47

health from this

47:50

evolutionary biology perspective it's easy to get a little

47:52

bit down and look back on the better times

47:54

and one of the things I always find a

47:56

little bit amusing and refreshing

47:59

is it's in the first chapter of the

48:01

Nejing, which is this book I mentioned that's 2,500 years

48:04

old, it starts off by basically

48:06

saying, and I am very much paraphrasing here,

48:09

back in the good old days, people knew how

48:11

to live well. And they

48:14

lived with the patterns of nature and they didn't

48:16

stay up too late. They went to bed on

48:18

time. They got up in the morning. They didn't

48:20

drink too much. They weren't having way too much

48:22

sex and they weren't sitting around

48:24

all the time. And they lived to be like 100 years old,

48:26

120 years old. Nowadays, people

48:30

don't have any sense. And they're sat

48:32

around and they're sedentary and they're not eating

48:34

well and they're drinking too much and they're

48:36

like dying at 50 and 60. And I'm

48:38

like, oh my God, that could have been

48:40

written now. So I love that kind of

48:43

the more things change, the more things stay

48:45

the same. And my, my,

48:47

yeah, go ahead. I

48:49

think, I think it's an interesting insight. I

48:51

will point out, however, that even that, we're

48:54

talking 2000, 2500

48:56

years ago is post, post

49:00

industrial, not industrialization, post

49:02

the agricultural revolution, which was about 10,000 years ago.

49:04

So, you know, which

49:06

changed us from hunter gatherers to

49:08

a very different kind of society

49:11

where, which really was extremely deleterious

49:13

to our health. That's

49:15

exactly what I was going to say that I think that

49:17

there's probably a global human story

49:19

that when we did that, we realized that

49:22

there were good old days. Where we were

49:24

more with the patterns of nature. That's right.

49:26

Yeah. Though I've done in

49:28

writing the book that I'm working on right now, one

49:31

of the things that I'm doing, it's a bit of

49:33

a digression, but since we're on it, maybe we'll go

49:35

into this. There

49:38

is a very, very

49:42

large myth

49:44

that's been created that our

49:48

human ancestors lived much shorter

49:51

lifespans than we live today.

49:54

We're all sort of indoctrinated with this idea that, you know,

49:56

we all used to die at age 40 or 50. and

50:00

hunter-gatherers die at age 40 or 50

50:02

and a few hundred years ago in

50:04

North America and Europe everybody died at

50:06

age 40 or 50. And

50:12

there's sort of interesting nuances to

50:14

this discussion but one

50:17

of the first layers that we can look

50:19

at to see sort of how much, part

50:21

of this narrative is like oh modern medicine

50:23

just in the last 7500 years,

50:25

75 or 100 I shouldn't say 7500 but 75 or 100 years has made these

50:34

massive advancements that have

50:36

extended our lifespan we're

50:38

living much longer than we ever have before.

50:40

This is a very common belief that a

50:42

lot of people have and it's simply not

50:44

true and one of the layers of evidence

50:46

that we can look to is for example

50:49

the ancient Chinese from thousands of years ago

50:51

who had no modern medicine and no pharmaceuticals

50:53

who frequently lived into their 90s or hundreds

50:55

or there's certainly lots of cases of

50:57

that. If we look at lots of like

50:59

the ancient Greeks that we've all read about

51:01

in philosophy courses and Aristotle and

51:03

Plato and Socrates and Hippocrates and Democritus and

51:05

these kinds of people if you look at

51:07

their age of death frequently in the 80s,

51:10

90s and many of them live beyond 100

51:12

and again 2000 years ago

51:14

no modern medicine no drugs. Then

51:23

what's interesting about this is

51:25

that there

51:29

was actually so hunter-gatherers as

51:31

well tens of thousands

51:33

of years ago also frequently lived to the

51:35

same ages that us modern humans live in

51:37

the United States right now in 2024 the

51:39

average lifespan is 73 for men and 79

51:46

for women right. So if

51:48

you compare that 2000 years ago Greeks

51:50

and Chinese people were living to those

51:52

same ages and beyond it was not

51:54

uncommon we are not living longer than

51:56

we did thousands of years ago and

51:59

I will also point out that

52:02

there are studies of people

52:23

who are in their 80s and 90s. One of

52:25

the oldest participants in one of the studies was

52:27

age 94. So again, we are

52:30

not living longer than them. But what's interesting

52:32

is what confuses this

52:34

is what

52:37

they do have is very high incidence

52:40

of childhood mortality and very high incidence

52:42

of death by accident and death by

52:44

infectious diseases. And those are areas where

52:46

modern medicine has made major

52:48

advances where we have way lower incidence

52:51

of infant mortality, maternal

52:53

mortality during birth and

52:56

death by accidents. In

53:00

these populations, it's like close to 50%

53:02

of kids don't even make it to

53:05

age 15 because

53:07

violence and accidents and

53:09

infant mortality is

53:12

so high. Well,

53:14

this is like the perfect example

53:16

of saying there's lies, downsides, and

53:19

statistics. So

53:21

you just can tell wildly different

53:23

stories about this depending on how

53:25

you slice and dice the data.

53:28

Right. Yeah. And it is a statistical issue because they

53:30

use a term called life expectancy at birth, which factors

53:32

in, it's basically the average age of death. So if

53:34

you've got 10% or 20% of the population that's dying

53:37

in the first year of life or 15 years

53:39

of life, it

53:44

will massively skew that average down to 40

53:47

or 50. And then people

53:49

interpret this as saying, oh, humans used to

53:51

live to age 40 or 50 as their

53:53

maximal age, which is incorrect. So

53:56

anyway, sorry for that digression, but since we were on

53:58

it, I thought I'd do a little myth debunking. Okay.

54:01

No, very interesting. So let's

54:05

get back to resting

54:07

heart rate as the

54:09

determinant of health because like

54:12

heart rate variability, it's interesting to

54:14

note that resting heart rate itself

54:16

is also a very strong predictor

54:19

of mortality. But there

54:22

is another, I think we get another

54:24

example of this kind of scenario that

54:27

you were describing earlier where there is

54:29

a segment of the population who might,

54:32

there's maybe two different kind of segments, I

54:34

guess, of the low heart rate, low resting

54:36

heart rate that we could single out. One

54:38

would be high level athletes who have trained

54:40

themselves into a low resting heart rate, but

54:43

there might also be very ill people

54:46

who have a low resting heart rate

54:48

or maybe people who are stuck in

54:50

winter metabolism, for example. So you

54:52

explain how you see this landscape because I

54:55

found your presentation of it fascinating. Okay,

54:58

cool. So resting heart

55:00

rate and heart rate variability are related

55:02

to each other because

55:05

they are both products of

55:07

the same systems. So if

55:11

we have lower ventral vagal

55:13

tone and a higher sympathetic tone, then

55:15

we are going to have lower heart

55:18

rate variability and a higher resting heart

55:20

rate. So these two metrics

55:22

are not, they're not perfectly coupled because

55:24

there's other things that are affecting

55:27

them, but there's like similar

55:29

ingredients going into the blender to

55:32

come to make them. And so with resting

55:35

heart rate is another one that's

55:37

a strong predictor of health and

55:39

all-cause mortality and that the higher

55:42

it is suggests worse

55:44

health, that you're more

55:46

stressed. And I should say because this is resting

55:48

heart rate, we're kind of asking

55:50

how low can you go? How well can

55:53

you rest? And if it's

55:55

high, then it means that you're not able

55:57

to rest very well. So when you are

55:59

sitting, and when there shouldn't be so

56:01

much demand, your heart is still working hard

56:03

and it's not recovering

56:06

and you're not recovering well and your

56:08

ventral vagus system is not calming that

56:10

down. And actually, I

56:13

should say, in terms of just adding this

56:15

developmental component, when we were born, our resting

56:17

heart rate is quite high. So it's like

56:19

maybe about 100 beats per minute. And

56:22

then as our nervous system develops, it goes

56:24

down so that in adulthood, the resting heart

56:26

rate should be perhaps from the 60s. That

56:30

said, I found some new research, which was

56:32

quite interesting because we have all

56:34

these wearables now. Researchers can

56:37

now access these giant data sets of people

56:39

with this 24-hour data and look

56:43

at these trends that are not just sort of gone to

56:45

the doctor and sat down and taken my resting heart rate.

56:48

And what we're finding is that the average resting heart

56:50

rate is actually lower than almost all

56:52

the studies say, which

56:54

is I think perhaps partly because

56:57

if we're getting a 24-hour reading,

56:59

that includes nighttime. So the resting

57:01

heart rate should be lowest at

57:03

night. And so we're getting that

57:05

true picture. I could think

57:08

of a few confounding variables there. One would

57:10

be a sort of lab coat syndrome thing

57:12

that you see with blood pressure when people

57:14

go to the doctors. On average, they might

57:16

have some nervousness and so it would skew

57:18

higher because of that. The

57:20

nighttime is probably a big one. That might be

57:22

the biggest one. But the

57:24

other thing is demographically that the

57:26

people who are inclined to use

57:29

these wearables are on average going to

57:31

be more health-conscious, more people who are

57:33

more exercisers compared to the

57:36

average population. User

57:38

bias. I think there

57:40

might be definitely some sense to

57:42

that. However, if you also look

57:44

at BMI, you'll see that it's

57:46

a mix of people. That

57:50

people might also be wearing it because they're unhealthy. But

57:53

yeah, there's probably both going on. And

57:55

also, if you go out to the doctors, did they

57:57

really make sure that you sat quietly for five minutes?

58:00

before they did it because that actually makes a big difference. Right.

58:03

So if the resting heart rate never

58:06

really comes down properly, and you see this, for example,

58:08

in autistic kids will have a higher resting heart rate

58:11

and a lower heart rate

58:13

variability because that ventral vagus system,

58:15

that right brain never really quite

58:17

comes online. The left hemisphere is

58:19

dominant. And so that their

58:21

autonomic system, their heart rate and heart

58:23

rate variability are telling that story. So

58:26

it should, it should come down. But what we

58:29

see really when we dial in, and I

58:31

believe, and I'm very happy to be proven

58:33

wrong or to find an exception, that for

58:35

any naturally occurring thing

58:37

in the body that you want to measure, there

58:39

should pretty much always be a J-shaped curve. That's

58:42

kind of a principle. And when I

58:44

see a study with a linear relationship, I'm always

58:46

kind of asking questions. This isn't

58:48

going to be true for environmental toxins. Obviously, you want

58:50

those to be zero. But for

58:52

everything else, I'm like, well, okay, who did they

58:54

include in this or how are they measuring this?

58:56

And you'll usually find, you know,

58:58

in another data set that

59:01

was maybe more occlusive, you'll find the J-shaped

59:03

curve. So that's something to look for that

59:05

usually there's a sweet spot. And it's never

59:08

the case that higher is better or lower

59:10

is better. There's an interesting

59:12

distinction I've been writing a lot about

59:14

between sort of

59:16

traditional biomarkers and what we

59:18

would call in exercise science performance

59:21

metrics. And

59:23

performance metrics, the simple ones would

59:25

include things like muscular

59:27

strength or VO2 max.

59:30

And when you start to, so in

59:34

contrast to biomarkers, which are things like,

59:36

let's say cholesterol or blood pressure or

59:38

blood sugar levels, where if

59:40

you there's an optimal range, and to

59:42

the extent one goes out of that

59:44

range, high or low, it's indicative of

59:46

a problem. With

59:48

performance metrics, it's not like that. So

59:52

you're not going to find an

59:54

unhealthy person. Maybe

59:56

you would find one in the world or something like that. I

59:58

mean, I don't want to say in

1:00:00

blanket terms but 99.9999999% of the time

1:00:02

somebody who has a high VO2 max is going to

1:00:08

be extremely healthy. That's a

1:00:10

helpful distinction there. You're absolutely right. If

1:00:12

you're missing a performance marker there can

1:00:15

be a higher, more better performance is

1:00:17

better performance. The only demographic

1:00:20

that will disrupt that relationship is

1:00:23

people with strength or VO2

1:00:25

max people who are using performance enhancing drugs.

1:00:27

A lot of bodybuilders die young, they would

1:00:29

get very high strength scores but due to

1:00:31

their use of drugs they

1:00:34

end up causing all kinds of side effects

1:00:36

that end up killing them at young ages.

1:00:38

But people who are not chemically enhanced in

1:00:40

that way, the relationship holds up extremely well.

1:00:42

That makes sense. Yeah. So,

1:00:47

resting heart rate. So, tell me more about how

1:00:49

this matters in determining our health.

1:00:57

Yeah, so, resting heart

1:00:59

rate at night, I

1:01:02

think the wearable data showed that it was between

1:01:04

like 3 and 5 AM, is

1:01:07

going to be an indicator

1:01:09

of your body's ability to

1:01:11

rest and recover, okay,

1:01:13

in general. And so, we

1:01:16

can kind of see, clearly

1:01:18

understand why that would be a helpful thing

1:01:21

for health. And

1:01:23

then again, at the outlier end, the reason

1:01:25

why maybe that's not always the case or

1:01:27

maybe why there's exceptions, we

1:01:30

mentioned a little bit about winter metabolism that if

1:01:32

someone just doesn't have enough gas in their tank

1:01:34

to get their heart rate up or the emergency

1:01:36

break is applied, and again, this

1:01:39

is a smaller percentage of the population but it's

1:01:41

not just one or two either. It's, you know,

1:01:44

it is like millions of people, it's

1:01:46

just not the majority. Then

1:01:48

you can also get a low resting

1:01:50

heart rate that may not necessarily be associated

1:01:52

with greater health markers, but in general, it's

1:01:54

really just measuring your body's ability to regulate

1:01:57

and recover and to heal

1:01:59

it. and to balance itself out and do all of

1:02:02

those really important things that we do while we sleep.

1:02:04

And also, a lot of different things

1:02:06

are going into this mix. So we

1:02:09

can look at our stress levels and

1:02:11

then our ability to handle those. It's

1:02:14

reflecting both. So

1:02:17

when you look at resting heart

1:02:19

rate and heart rate variability, are you

1:02:21

looking at it more as, you know,

1:02:25

again, I'm sort of looking at this,

1:02:28

my context is more exercise science.

1:02:30

So I look at these as

1:02:32

like trainable, malleable entities that we

1:02:34

can gain insight from and look

1:02:36

to say, hey, relative to

1:02:38

a highly trained person, where

1:02:40

am I landing and how can

1:02:43

I train myself more so that

1:02:45

I'm more in the good

1:02:47

or elite categories of these

1:02:51

metrics. I

1:02:53

think you're looking at them more as how

1:02:55

they tie into pathology. And

1:02:58

how these are sort of determined

1:03:00

as a result of early development

1:03:02

and how our nervous system is

1:03:04

functioning as a window into autonomic

1:03:06

nervous system function. But

1:03:09

once you measure them

1:03:11

or, you know, as you

1:03:13

track them over time with people you're

1:03:15

working with, what

1:03:17

do you do with that information? Like, how

1:03:19

are you applying it practically and what are you

1:03:22

recommending to people in certain contexts? Yeah,

1:03:24

excellent question. You know,

1:03:26

what you reminded me of as well

1:03:28

is that you have this spectrum from

1:03:30

high level performance to pathology and that people

1:03:33

can kind of fluidly move it. So my

1:03:35

goal is to move people out of the

1:03:38

kind of pathological and back into going. And a

1:03:40

lot of them were athletes or are athletes and

1:03:43

they want to get back to it and being

1:03:45

able to still support them there as well. And

1:03:49

I have a little bit of a different take

1:03:51

on how to use biomarkers

1:03:53

and lab tests and these types

1:03:55

of tests. And really, in

1:03:58

this case, we're looking at, let's say, looking at

1:04:00

resting heart rate. We're looking at the output of

1:04:02

a system and it's what I

1:04:04

call an index marker, which is to say that a

1:04:06

lot of different things go into the mix to make

1:04:08

your resting heart rate. And

1:04:10

so my approach is to not and

1:04:13

this is you know I'm evolving it and adapting

1:04:16

it over time as I learned but it's to

1:04:18

not address it directly. But I think that that's

1:04:20

almost always a mistake. We think that let's say

1:04:22

if a lower resting heart

1:04:25

rate is better and I can

1:04:27

take the supplement or do

1:04:29

whatever to lower it, I

1:04:31

will be healthier and I find

1:04:34

that the cleverer we get, the

1:04:36

better we are at changing those

1:04:39

biomarkers and it almost

1:04:41

always causes problems because we're just

1:04:43

not smarter than our own system.

1:04:45

And I want to do like

1:04:47

a two-hour podcast with you just on that one

1:04:49

topic alone because I think it's so important. I'm

1:04:52

super happy to and again you know I this

1:04:55

comes from me having done that a lot to myself

1:04:57

mainly and also my patients you know. I'm like oh

1:05:00

okay well almost high homocysteine

1:05:02

is bad. Let's lower your homocysteine. Yay!

1:05:04

But then there's always something down the

1:05:06

line because we're too zoomed in and

1:05:08

we're not looking at first

1:05:10

principles and we're not smarter

1:05:13

than these individual markers.

1:05:15

So it really is about monitoring it. One

1:05:17

thing that was very eye-opening for me is

1:05:19

that I have an urring which is a

1:05:22

sleep tracker and exercise tracker and I've

1:05:24

been wearing it for like five or

1:05:26

six years now and when I

1:05:28

first started wearing it I was having

1:05:30

health crisis. You know I had chronic

1:05:33

fatigue, I had fibromyalgia, I had autoimmunity

1:05:35

to my own collagen, my brain was

1:05:37

not working very well, I had no

1:05:39

short-term memory, I had all these this

1:05:41

stuff going on. And

1:05:43

I recently went back and looked at

1:05:46

my data to get this dashboard where you can

1:05:48

kind of drag out for different time horizons

1:05:50

and so I was teaching about heart like resting heart rate

1:05:53

so I wanted to see where was my resting heart rate

1:05:55

then and where is it now like you know my pain's

1:05:58

gone down, I'm mobile, I have a I

1:06:00

have a short term memory. I'm doing

1:06:02

a lot better. My energy is a lot better. My sleep

1:06:04

is a lot better. And in those

1:06:06

two periods, let's say the first two years where

1:06:08

I was kind of in a crisis and now

1:06:10

when I'm doing a lot better, it's the same. The

1:06:13

resting heart rate is the same. What's

1:06:17

going into create that resting heart

1:06:19

rate is completely different. So

1:06:22

my nervous system is more regulated. I

1:06:25

have better energy. My sleep is better.

1:06:27

My mood is better. My memory is

1:06:29

better. My function is better. My physical

1:06:31

function is better. Everything's better. My resting

1:06:33

heart rate is the same. So fortunately

1:06:37

I was smart enough to not try to

1:06:39

change my resting heart rate because that

1:06:41

would have been a problem. That would have been distraction. I

1:06:44

would have, I don't know what I would have, it was 57. I

1:06:46

don't know, does it go up? Does it go down? Should I mess

1:06:48

with it? If I tried to mess with my resting heart

1:06:50

rate, it would not have led

1:06:52

me in a good direction. I simply note it

1:06:55

and I watching. And for patients,

1:06:57

we're just watching

1:06:59

it as an output of your system

1:07:02

to monitor in the background. And we can

1:07:04

use it depending on the person to

1:07:07

assess progress and to see where things

1:07:09

are. But I'm not recommending

1:07:11

a specific formula to change your

1:07:13

heart rate. I'm not

1:07:16

recommending a specific whatever, supplements

1:07:18

or whatever to manipulate these numbers because

1:07:20

I've learned the hard way over many

1:07:22

years that that doesn't lead to good

1:07:24

outcomes. I think, I

1:07:31

don't intend this to be in

1:07:33

any way like antagonistic. I intend

1:07:35

it to be more of an

1:07:37

addition. But what I would say

1:07:39

is almost like there's two issues

1:07:41

there that need to be sorted

1:07:43

out when we talk about modifying

1:07:45

the biomarker. So, I'll give

1:07:48

you a few examples. If

1:07:52

I'm interested in, I

1:07:56

can give a whole bunch of examples. So let's say,

1:07:58

okay, I'm interested in alter. my

1:08:01

blood pressure. I

1:08:03

can take a lifestyle

1:08:25

action through minimizing

1:08:30

right so I like I fundamental I don't

1:08:52

where we we think we're like

1:08:55

outsmarting intervention

1:09:00

or pop this pill and this chemicals going

1:09:03

to just lower that marker for us and

1:09:05

then we're healthy I think that

1:09:07

as you said I agree with you completely is almost

1:09:10

always going to not

1:09:13

result in much benefit and is

1:09:15

like very likely in principle to

1:09:17

result in side effects and I'd say

1:09:19

in the vast majority of cases the

1:09:22

side effects generally in the long term

1:09:24

outweigh the benefits which

1:09:27

is why after

1:09:30

nearly a century of allopathic

1:09:32

medicine applying that very model

1:09:35

of health it's like how can we hack

1:09:37

the body and by the

1:09:39

way that a lot of people don't

1:09:41

understand this the most advanced form of

1:09:43

biohacking of applying that principle of trying

1:09:45

to hack the system is allopathic medicine

1:09:47

they've been doing it for nearly a

1:09:49

century and they've developed through

1:09:52

trillions of dollars and hundreds of thousands

1:09:54

or millions of scientists all over the

1:09:56

world working for pharmaceutical companies they've developed

1:10:00

literally millions of drug candidates which

1:10:03

have been tested and have been further

1:10:05

refined down to 19 or 20,000 FDA

1:10:09

approved chemicals and among

1:10:11

those we don't have a single one,

1:10:14

not one that we can reliably

1:10:16

give to healthy let's

1:10:18

say a healthy 30 or

1:10:20

40 year old for decades where

1:10:23

we know that the benefits of that

1:10:25

compound will outweigh the harms. We don't

1:10:27

have a single one which it's hard

1:10:29

for me to imagine a more powerful

1:10:31

proof that this model of

1:10:33

trying to hack the body with chemicals doesn't

1:10:36

actually make us healthier. I

1:10:40

completely agree. I appreciate

1:10:43

your distinction about trying to modify these measurements.

1:10:45

I'm going to give you another example though

1:10:47

that's a little bit surprising because it's kind

1:10:49

of in between the examples that we gave.

1:10:54

When we take a measurement and then we decide if

1:10:56

it's good or bad and then what we're going to

1:10:58

do about it is really based on our understanding

1:11:01

of the system and a lot of times

1:11:03

this understanding is kind of missing context or

1:11:05

it's not really understanding why it's there in

1:11:07

the first place but the the

1:11:10

example where I saw this this kind

1:11:12

of hacking through seemingly healthy behavior

1:11:14

problematic is that increasingly people

1:11:17

are wearing continuous glucose monitors which I think

1:11:19

is a wonderful thing. You know you get

1:11:21

this like immediate feedback cycle you can take

1:11:23

a lot of the guesswork out of all

1:11:26

this like fad, you know, diet

1:11:28

advice it's brilliant but what I

1:11:30

saw is that the advice that

1:11:33

often like comes a little bit of training that

1:11:35

comes with these continuous glucose monitors in

1:11:38

terms of how to lower blood sugar or how to manage

1:11:40

it or how to hack it includes

1:11:42

sort of vigorous exercise after eating that

1:11:44

if your blood sugar goes up and

1:11:46

then you vigorously exercise you could drop

1:11:49

it down. Now you were

1:11:51

talking about improving something like blood pressure

1:11:53

through healthy habits

1:11:56

and that is great if we take someone

1:11:58

from what they're doing. doing that might be promoting

1:12:02

ill health and then move them in the direction of

1:12:04

their habits and things improve.

1:12:06

That's great. But this is more of like

1:12:08

a hacky way where we're going to try

1:12:11

to drop blood sugar by

1:12:13

stimulating certain mechanisms of like

1:12:15

insulin sensitivity in the body.

1:12:17

And overall, these

1:12:19

patients were making their systems more stressed. And

1:12:21

it wasn't really good advice

1:12:24

in general to exercise vigorously. They

1:12:26

were getting like on the rebounder

1:12:28

after eating in order to

1:12:31

drop the blood sugar. And so here we

1:12:33

get in, it wasn't a supplement, it wasn't

1:12:35

a drug. It was exercise. Isn't exercise good?

1:12:37

But we still want to understand the context,

1:12:39

which is that that's not really the best

1:12:41

time for vigorous exercise usually. But the reason

1:12:43

why we're doing it is because we're trying

1:12:45

to hack this number and kind

1:12:47

of to bring it back. What is not

1:12:49

talked about nearly enough is that yes,

1:12:52

diet will play a role in blood

1:12:54

sugar. No question, especially if we're

1:12:57

eating highly refined and glucogenic

1:13:00

foods. But for a lot of people,

1:13:02

it's their nervous system that's actually making

1:13:04

the bigger contributor to what the resting

1:13:06

glucose is and how well they can

1:13:08

handle meals and that sort of

1:13:11

thing. And going on a rebounder after exercise

1:13:13

and it was actually making that problem worse.

1:13:15

So that's also, that experience

1:13:18

also feeds into, you know what? I'm

1:13:21

not going to try to wiggle this variable. I'm

1:13:23

going to try to use first principles and adjust

1:13:25

things that I know are going to be useful

1:13:28

and then just see what happens and then

1:13:30

iterate. Yeah, yeah, it's

1:13:32

a great point. And even

1:13:35

healthy things can be unhealthy

1:13:38

if applied in the wrong context or

1:13:41

with the right, the wrong sort of

1:13:43

guiding philosophy. You

1:13:46

know, I would say in response to that,

1:13:48

I would say like, this

1:13:50

is where we need to look at ancient humans.

1:13:53

We need to look at our ancestral way of

1:13:55

life and hunter-gatherers and go, do

1:13:57

they like do vigorous exercise right after eating?

1:14:00

or do they generally rest? And you know and

1:14:04

the other animal species more broadly

1:14:06

as well. So

1:14:13

let's wrap up on this idea of heart

1:14:16

rate variability, heart rate, nervous

1:14:18

system function. Can you

1:14:21

sort of summarize

1:14:24

how this information is taken into context and how you're

1:14:26

using it with the people that you work with, that

1:14:28

you work with to guide the people that you work

1:14:30

with? To

1:14:32

guide how you

1:14:34

understand what's going on and how you approach

1:14:36

solving it. Yeah. Yeah.

1:14:39

It's, I think

1:14:41

it's helpful for most people to

1:14:44

be measuring this and

1:14:46

just it's basically like a background

1:14:48

temperature reading of their

1:14:50

autonomic nervous system. I think it's, you

1:14:53

know, also while keeping it a little

1:14:55

bit at arm's length, a little bit just like how

1:14:57

we talked about that. I

1:15:01

think that if someone is sicker,

1:15:05

then these variables are going to be

1:15:07

less responsive to the day to day. So think about

1:15:09

the difference between an athlete who over trains might just

1:15:11

need to rest more and then it comes back. Someone

1:15:13

with clinic fatigue, they're resting and they're not recovering. They're

1:15:16

in a different category. So these little hacks aren't going

1:15:18

to work anyways. They're

1:15:22

nervous system has become less adaptive or

1:15:25

on the other side, it's so reactive. So like

1:15:27

every little thing is setting it off. And

1:15:30

so then it's hard to get good feedback about individual

1:15:32

things that are affecting it. So I think it's just

1:15:35

nice to have in the background and just notice what

1:15:37

happens over time. I

1:15:40

recently had someone I was working with

1:15:42

on the other side of the world

1:15:45

and she's been monitoring

1:15:47

hers for close

1:15:49

to a year now and she's able to see how

1:15:51

it's become healthier, how she's sleeping better, her

1:15:54

blood pressure's improved and her heart rate variability.

1:15:56

But I didn't give her any specific. recommendations

1:16:00

of things to do in order to

1:16:02

change it. It's more this kind of

1:16:05

background marker of her

1:16:07

resilience that she can use

1:16:09

as another way of knowing herself, but

1:16:12

I don't and I think this is the sound

1:16:14

is to not be doing things

1:16:16

to try to manipulate it, but if you do make a

1:16:18

change and you can just notice the difference.

1:16:20

Maybe you go into a different environment and

1:16:22

you notice that your nervous system is more

1:16:24

resilient. Maybe you make a change and you

1:16:26

notice, but it's really nice

1:16:29

because I tend to work with people long term

1:16:31

so they might come for a year. They might

1:16:33

stay on longer and to have

1:16:35

that as an ongoing record of how they are doing

1:16:37

and that they learn to know themselves and

1:16:39

what's helping and what's not, but I again,

1:16:42

I think that at the moment, especially with

1:16:44

all the misinterpretations and people

1:16:47

coming to conclusions about the meanings of things,

1:16:49

I think we're safer and wiser to just

1:16:51

monitor it and let us know in

1:16:53

the background how things are doing without trying to manipulate

1:16:55

it. So what would

1:16:57

you attribute her changes in those markers to?

1:16:59

I mean even... I

1:17:05

was going to give another example, but I'll leave that out at the risk

1:17:07

of going down a rabbit hole. So

1:17:09

like you did something, you changed something

1:17:11

in what you were doing

1:17:13

some treatments and the explicit intention

1:17:17

of that wasn't hey, we're

1:17:19

going to do this to modify your heart

1:17:21

rate or heart rate variability. Nevertheless,

1:17:23

we are using resting

1:17:26

heart rate or and or heart

1:17:28

rate variability as a metric by

1:17:30

which we are inferring

1:17:32

that these

1:17:34

changes, these treatments or

1:17:36

these things that we're doing are having

1:17:38

a benefit. Exactly,

1:17:40

exactly. So, you

1:17:43

know, I took her through the process that I take people

1:17:45

through in order to reverse complex chronic

1:17:47

health issues and there's nothing I would change

1:17:49

based on her heart rate variability, but that's

1:17:51

to say I'm kind of taking a very

1:17:53

conservative view. I'm saying to

1:17:56

not jump in, but but you can if

1:17:58

you're you know, we talked about using caution, right, when

1:18:01

we're interpreting these things and when we're working

1:18:03

with them. But you can use this data

1:18:06

to ask intelligent questions. So one thing I

1:18:08

noticed when I looked back at my data

1:18:11

was I was looking at the relationship between

1:18:13

how much exercise I had done and what

1:18:16

my resting heart rate was. And when

1:18:18

I looked at it for those first two years when

1:18:20

I had chronic fatigue, the more

1:18:23

I had exercised, the higher my resting heart rate

1:18:25

was, which means I wasn't recovering, that I wasn't

1:18:27

adapting well to it. But then

1:18:30

as I was healthier in the latter

1:18:32

two years, the more I'd

1:18:34

moved, the lower my resting heart rate, which is

1:18:37

what you want to see. And that's what happened

1:18:39

in the healthy person. So that sort of seeing

1:18:41

that with my own data lets me ignore all

1:18:43

this kind of advice of what you should do

1:18:46

and lets me know this

1:18:48

is the relationship between exercise and

1:18:50

my nervous system right now. This

1:18:52

is how it's changed. Do

1:18:54

I think that I could have gone back and pinpointed

1:18:56

the moment where I could have started exercising? I don't

1:18:58

know. I think people try to do that. Because

1:19:01

of the cycles I've

1:19:03

seen of misinterpretation of lab markers, this is

1:19:06

why I'm so cautious. It's more just interesting

1:19:08

for me to note that in retrospect and

1:19:10

to use that as a positive sign that

1:19:12

is healthy for me to exercise, which I

1:19:14

can also feel in my own body anyways.

1:19:16

But I will answer it by saying that

1:19:18

I'm constantly actively working

1:19:20

on this question about how to use

1:19:23

these numbers well without making

1:19:25

the mistakes and the hubris

1:19:28

of taking a

1:19:30

number that we think we understand and

1:19:32

maybe don't understand as well as we

1:19:34

hope and trying to make decisions based

1:19:36

on that to manipulate it and causing

1:19:39

problems that we didn't intend to.

1:19:41

So I'm still on that cautious side, but I'm

1:19:43

constantly exploring

1:19:47

research and data

1:19:49

in my practice and my own

1:19:51

body to see can we

1:19:53

find things that work

1:19:55

that are helpful, that are safe, that are

1:19:58

good to use as guideposts. Very

1:20:00

interesting. Mel, I'm

1:20:03

curious if you can give a very quick, I

1:20:06

know this is a broad thing that you could

1:20:09

obviously talk for many hours on, but can you

1:20:11

give a very, very quick overview of what exactly

1:20:13

your approach, you know, when

1:20:15

you said you took this patient through your

1:20:17

approach to resolving complex

1:20:20

chronic illness, what

1:20:22

is the sort of outline of your approach? Yeah,

1:20:25

that's a great question and I definitely, I

1:20:27

am very fortunate to

1:20:29

have worked and continue to work with some really smart

1:20:32

teachers, so I always love to give them credit and

1:20:35

this is an approach that I had found in various

1:20:38

places that the person I've worked with

1:20:40

the most is Jeremy Cornish at the

1:20:42

Dan Good Doctors Club. He's a very

1:20:44

smart guy. He is an adaptation of

1:20:46

an approach that he and others

1:20:49

learned from a, in particular,

1:20:51

Chinese medicine doctor that they studied with in

1:20:54

Szechuan China, but basically this guy was

1:20:56

treating like 150 to 200 patients

1:20:59

a day and getting excellent results because

1:21:01

he had dialed in his algorithm and

1:21:03

he dialed in his way of thinking

1:21:05

so well, but this approach is essentially

1:21:07

to work step-by-step in

1:21:09

the body in it using

1:21:12

a sequence of systems, so

1:21:14

those systems are the immune

1:21:16

system, the digestive system, the

1:21:18

neuroendocrine system, the tissue repair

1:21:20

system, and then if someone

1:21:22

still is kind of lacking in energy

1:21:24

at the end of it, then we can consider boosting

1:21:26

and supplementing and conifying and

1:21:29

you know one of the questions I've had

1:21:31

over the years is order of operations when

1:21:33

working with complex chronic illness and everyone

1:21:35

I worked with had, well most people I worked with did

1:21:38

not have an order of operations, so that was just crazy

1:21:41

inducing. You would have a

1:21:43

patient who had digestive issues and mood issues and

1:21:45

skin issues, inflammatory issues and you get all the

1:21:47

state and then you need to figure out where

1:21:50

you were going to start and where you start

1:21:52

is important. Then I worked

1:21:54

with many people who say start with the

1:21:56

gut and as someone who has lifelong digestive

1:21:58

issues, I had worked on my

1:22:00

gut quite a lot and still had quite a lot of problems. And

1:22:03

then I worked with someone else who said to start with hormones.

1:22:06

When I did that, it seemed to

1:22:08

be useful like 30% of the time, which

1:22:10

I was not happy with that. For me, if

1:22:13

it's a sound order of operations, it should be

1:22:15

like at least 80% on point.

1:22:18

And this and actually the way I've been

1:22:20

trained, it's actually even higher because you

1:22:23

know, you're just asking the question, do we start

1:22:25

here? And so most of the time, the

1:22:27

answer is yes. And some of the times the answer is

1:22:29

no, which means that it's even more accurate. So

1:22:32

we start with that we have clear signs and

1:22:34

symptoms that we're looking forward to resolve before we

1:22:36

move on to the next stage. And

1:22:38

then we're moving in that step by step order. And

1:22:40

honestly, using that

1:22:43

order, I started

1:22:45

to see it in other places that this is sort

1:22:47

of embedded in human wisdom that we're going to

1:22:49

move from the outside in, and we're

1:22:51

going to move, remove load from the body

1:22:54

first before most people come

1:22:56

in trying to take B vitamins

1:22:58

and adaptogens and hormones and all this stuff

1:23:00

to boost and they've got so much gunk

1:23:02

in their system, a lot of which they're

1:23:04

feeding, you know, studies showing that

1:23:07

your dysbiotic gut bacteria love it when you

1:23:09

take iron supplements. But for them, that's like

1:23:11

an all you can eat buffet, same thing

1:23:13

with B vitamins. So working

1:23:16

in this order has just been

1:23:19

really, really sound and really has explained

1:23:22

why certain things that should work well

1:23:24

or seem to be valuable haven't

1:23:26

worked for my patients or for

1:23:29

myself really in terms of the timing of when

1:23:31

we use them. So a step

1:23:33

by step process, which in some ways

1:23:35

is a little bit agnostic to the

1:23:37

specific tools, although I do have tools

1:23:40

I recommend. But what's more

1:23:42

important is that we're really clear on

1:23:44

what we're trying to do, what we're measuring

1:23:46

going back to these first principles. Are we

1:23:48

warming? Are we cooling? Are we getting rid

1:23:50

of moisture? Are we adding moisture? And

1:23:53

what happens when I do that? I think

1:23:55

that you seem warm. So why

1:23:57

don't we do this really safe you

1:24:00

know, low amplitude thing where we remove some of

1:24:02

the warmth, do you get better or not? And

1:24:05

based on how you respond, we can

1:24:07

interpret the feedback because we've been so

1:24:09

intentional with how we've worked

1:24:12

with the system. And when you are

1:24:14

at the level of reductionist biochemistry, whether

1:24:16

that's pharmaceuticals or supplements, because you're not

1:24:18

working at that first principles level, you

1:24:21

can't interpret the feedback. All you can

1:24:23

do is repeat the lab and however

1:24:25

many months and fingers crossed up for

1:24:27

the best. And a lot

1:24:29

of times people are feeling worse and they're told

1:24:31

to stick with it. Whereas here, if we know

1:24:33

exactly what we're doing, then whether you get better,

1:24:35

you have no change or you get worse, we

1:24:38

always know what to do next. Yeah.

1:24:40

Or they're told based on their lab

1:24:42

markers that they're better, even though they

1:24:44

may feel worse. Exactly.

1:24:46

Exactly. And this is a

1:24:48

problem. Mel, I'm really

1:24:50

enjoying this conversation with you as it

1:24:53

unfolds sort of organically as we talk

1:24:56

through things, really fascinating stuff as usual.

1:24:58

I think we

1:25:00

still have more to explore in the traditional Chinese

1:25:02

medicine front. And you know, you give me a

1:25:06

bunch of ideas and I saw in your

1:25:08

presentation related to the nijing. How do you

1:25:10

say it? Nijing. I'm

1:25:12

not like a Chinese speaker, so I apologize

1:25:14

to anybody about my

1:25:16

pronunciation. We're both offending people. So

1:25:19

wonderful stuff, really. And let people know again

1:25:22

where they can reach out to you if

1:25:24

they're interested in working with you. Sure.

1:25:27

So I'm over at

1:25:29

synthesishealth.co. Wonderful. Thank you so much. I

1:25:32

look forward to the next one. Thank you.

1:25:34

I appreciate it.