Can Your Phone Replace a $100K DEXA for Body Fat and Physique Tracking? (Jason Moore) | Ep 367 - Wits & Weights | Fat Loss, Nutrition, & Strength Training for Lifters

Episode Transcript
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Philip Pape (00:01):
Can a smartphone app match the accuracy of a
$100,000 DEXA scanner for bodycomposition?
My guest today discusses newtechnology that uses your
phone's camera to measure bodyfat percentage, your Android to
gynoid or AG ratio and HRV, allwithout additional hardware.
Learn how weekly measurementscompare to daily and monthly

(00:22):
tracking, how professionalcoaches are integrating this
technology with elite athletes,and how you can better track
progress to achieve your healthand physique goals.
Welcome to Wits and Weights,the show that helps you build a
strong, healthy physique usingevidence, engineering and

(00:45):
efficiency.
I'm your host, philip Pape, andtoday we're discussing a new
way to measure body compositionusing your smartphone.
You guys know I like tech, Ilove data, I love precision and
I was excited to have JasonMoore here today.
He is my guest.
He's the founder and CEO ofSpren, a company that is turning
your phone into a precisionbiometric tool and linking to

(01:07):
lots of other amazing thingsthat we can get into.
Spren has already helped over amillion users measure body comp
, the AG ratio which we're goingto explain what that is HRV and
soon other things like VO2 maxand even, I think, mental stress
load, using nothing but yourphone's camera.
Today, you're going to learnhow this technology's accuracy
compares to other everydaymeasurements like calipers, like

(01:28):
tape, as well as clinicalequipment like DEXA, why
additional metrics like the AGratio that I just mentioned
might be more helpful than someothers like body fat percentage
alone and how the timing of yourmeasurements and other
process-related improvements candramatically affect your
results.
So, jason, thank you so muchfor coming on the show.

Jason Moore (01:45):
Hey, philip, happy to be here, thank you, thanks
for hosting, and I love that I'min good company with a bunch of
nerds that are ready to dig inon data and technology.
So, yeah, excited to be here.

Oh, 100%, man, this is cool stuff, I love this
stuff.
And when you look at thehistory of how we measure body
composition which, by the way,some people don't even know what
we're talking about when we saybody comp, right, we're talking
about the percentage ofdifferent types of tissue in
your body, like fat to muscle,and we care about that because
just losing weight isn't theonly marker of health right,
it's your overall bodycomposition.

(02:16):
And when you look at theevolution of, okay, we've got
scale weight, then we have BMI,then we have BMI, then we have
measuring body fat in alldifferent ways, lots of
confusion, and now we have fatdistribution.
Even so, if a healthy physiqueis really important to somebody
who's listening, what is thebest way to think about body
composition before we get intothe details?

of measuring it.
Yeah, I mean, that's a supercritical kickoff point.
So thanks for bringing it up,because if you've ever worked
with clients, if you're a coachout there or something like that
, and you ask people like what'syour goal, they might say, like
lose 20 pounds, and you're like, well, why right?
And it's like, well, I don'tknow, I just need to lose 20
pounds.
And if you really kind of startto unpack it, usually it's

(02:58):
either because they may knowthat they're kind of you know,
carrying a little extra fat, orthey don't like how they look,
or they don't like how they feel, or there's some health or
longevity reason.
You know, potentially they gotdiagnosed with prediabetes or
something like that.
Right, like they kind oftriggered this.
A lot of times it's looks andor even if it's not, a lot of

(03:19):
times the outcome can be tied tolooks, because that we're just
very visual creatures and soinstead of asking them, you know
how much weight you want tolose.
If you show pictures of likedifferent looking physiques and
say, like point to the one thatyou think that you want to be
like, you know, in the nextreasonable amount of time, let's
say six months or somethinglike that and they point to one.

(03:41):
You might actually say, hey,you don't actually need to lose
any weight on the scale to looklike that, and what really might
just need to happen is we needto just prioritize, you know,
our lean mass, like our muscle,a little bit more and trade some
of that fat for lean mass.
You might actually end up beingthe same weight on the scale,
but look a lot better, look orlike more like your goal, so to

(04:05):
speak.
But look a lot better, look orlike more like your goal, so to
speak, also feel a lot betterand then have a lot of your
health markers get into range.
And so body composition.
Maybe this is about a roundaboutanswer here, but body
composition looks way beyondthat scale weight and looks at
the composition from a fat andmuscle and water perspective,
but also the distribution aroundyour body, because it matters

(04:28):
where you carry fat and muscle.
Generally speaking, more muscleis better for most people.
There's some diminishingreturns at the top of that, but
when it comes to fat, being likea little bit soft is really not
that big of a deal from ahealth perspective.
Like a little bit soft isreally not that big of a deal
from a health perspective.
There's no real evidence thathaving a little extra fat is

(04:53):
unhealthy.
It's where that fat is on yourbody that really matters from a
health perspective.
But in any case, too, there's alooks portion of that that body
composition gives us a windowinto.
So does that kind of cover it.

you think, yeah, no , you hit on some really good
points.
I want to reiterate forlisteners the first is just the
weight loss versus fat loss, andI like that you use the
language there, because a lot ofpeople don't, especially with
marketing in this industry.
Your website if you go throughthe onboarding to figure out
what the best way to use the appis, right off the bat it talks
about fat loss and I was happyto see that.
Right, I know you guys use theterm weight loss in articles and

(05:26):
stuff, but still, the look andfeel versus the health right,
they're not mutually exclusive.
I love that you mentioned thatas well, because you know we
talked about on the show.
It's okay to have vanity goals,it's okay to care about how you
look, because ultimately that'san expression of your health
and it's not that we're lookingfor external validation so much
as there's an internalconfidence and self-image

(05:46):
associated with that, and Ithink it's a mentally healthy
place to be when it's tied toyour health and the process, as
opposed to tied to weight lossat all costs.
You then said the two differentphysiques, so what came to my
mind was a little bit of alitmus test when you ask, let's
say, a woman.
You ask her what is a idealphysique and she points to an
athlete who's pretty lean.
And then you ask her to guessthe scale weight and invariably

(06:09):
they're going to be off.
You know, not everybody.
If they know I'm trying totrick them, they'll go higher.
But they're generally like 20or 30 pounds heavier than you
think right Because of thedensity differences and the lean
mass and all that.
And then you mentioned thedistribution of fat, which I
want to get into.
One of your competitors keepsadding different metrics like
booty score and physique score,and I'm like it's pretty funny

(06:33):
because it looks likealgorithmically it tries to be
tied to where the fat is, justlike when you get a DEXA or when
you get an InBody or something,and they try to measure
visceral fat, right.
So I want to talk about that.
First of all, how can asmartphone measure all this?
Because I want to understandthat.
And then let's get into whatit's measuring and body fat

(06:54):
distribution, all that goodstuff.

Yeah for sure.
Yeah, I mean, it's interesting.
I'm a technologist and I'vedone some inventions on my own
and stuff, but the things thatwe're doing now just kind of
blow my mind with the phone andthe camera, because there's a
lot of different ways to do it.
One of those would be like ifyou were to look at an image of
an individual standing and youcould see their whole body right

(07:17):
, you could kind of go andmeasure like okay, if you knew
their height, you could gomeasure their waist, and you
could go measure like theirshoulders and things like that,
and you could start to get anidea of their body composition.
That way, it'd be a roughestimate, but you know, that's
kind of what we do.
Again, if you're a coach andyou're looking at somebody like
a client standing right in frontof you, you can kind of gauge

(07:39):
their height, you can kind ofgauge their shape, and you can
kind of start to make someguesses at their body
composition.
So that's one way.
And then what we've done, though, is, you know, dexa is kind of
the gold standard, so to speak,of what consumers have access to
.
Of course, mri is really more ofthe gold standard and like
autopsy or something, but that'sa one way, you know,

(08:01):
measurement.
So in any case, we benchmark offof DEXA and what we've done is
we've had thousands andthousands of people do DEXA
scans and also take images withtheir phones of their body, and
then we train machine learningmodels to start to see what the
DEXA sees by predicting thatoutcome using different machine

(08:22):
learning models.
And so for us, I mean, that'san expensive way to develop
these estimating technologies,and some companies have spent
dozens and dozens of millions ofdollars trying to figure out
how to do that, and we've beenvery fortunate to have some
major unlocks that have reallymade the accuracy essentially
comparable to DEXA, bycollecting enough ground truth

(08:44):
data and pairing it with adiverse population, and then
some in-house expertise of we'vejust been working with sensors
and physiology measurements forover a decade.
So that's kind of how we do it.
It's a little bit of a blackbox underneath the hood, you
know.
There's probably some thingslike that going on that like a
human could start to do, butthen the machine learning models

(09:07):
just take all of that to thenext level.

Yeah, no man, I'm nerding out on this because I
love that stuff.
Before we got on the call, youwere talking about how you guys
have been using AI machinelearning long before ChatGPT
existed and people don't realizethat that kind of technology
has been probably two decades inthe making across a variety of
fields.
Right and so taking real-worldof technology has been probably
two decades in the making acrossa variety of fields right and
so taking real world data thathas been validated after the

(09:30):
fact with higher qualitymachines like a DEXA, and then
reversing that back into okay,what can we infer from the data?
I love that.
When you take that compared to,let's say, a very simple way to
measure fat that I have clientsdo or suggest to people, is the
Navy formula, neck and waist,or for females, neck, waist,
hips right, and there's supposesthat there's some sort of ratio

(09:53):
going on there.
And I tell people look thenumber, don't trust the number,
trust the trend over time of thenumber.
Is your technology giving you anumber that you think is
actually reasonably accurate, ordo you also have some
reservations on that?

No, yes, so insofar as much as you trust DEXA.
And so DEXA is not perfect.
In fact we're within the marginof error of DEXA itself.
So if you take multiple DEXAmachines and compare them to
each other and then you kind oftake like a weighted average or
something like that, then we'reactually closer to the weighted
average than the individualmachines sometimes are, and so

(10:30):
the accuracy is very high forthe actual number.
But then the precision is evenhigher because we have some
advantages in the sense that wehave software and you know the
whole infrastructure behind thesoftware to then calibrate.
So one of the neat things aboutour algorithm is that every
time you do a scan it calibratesto you and your body, and so

(10:51):
the precision actually goes upwith the more scans that you do.

Oh, the internal precision for you.
Yeah, okay, the internalprecision of the algorithm.

That's right, and so the other thing that that
does is allows you to startwashing out things like water
weight fluctuations, and so theother thing that that does is
allows you to start washing outthings like water weight
fluctuations, and so even DEXAis sensitive to changes in water
and bioimpedance and theseother technologies are as well,
and by being able to do thescans frequently over time, we
actually can isolate out thosevariables and get even more

(11:22):
accurate with the numbers.

Oh man, let's dig into that because you got ahead
of my next question, which wasahead of my notes.
Conditions like fluid, right,because that's the big thing.
I tell people if they're goingto get a DEXA.
Try to replicate exactly whatyou did same time of day, like
before you drink and eat allthis fun stuff.
You're saying because of yourown frequency of data collection
, it can smooth those out.
Is that like so?
If I did it in the morning oneday, afternoon, the other day

(11:45):
after eating a bunch?

you know, fat loss versus muscle gain it can
account for that I mean, so wewould still recommend that you
try to do it in a consistent way, but the short answer is that,
yes, at least better thanalternatives can, right, and so
you know that's you're hittingon.
A really important point is thata lot of people like, let's say
, if you're a member of a gym oryou know something like that,

(12:07):
you go in and you do a workoutand then you're like, oh, I
guess I'll do a body scan whileI'm here, and it's just like
completely random what the stateof your body might be.
You may be super dehydrated oryou may be more hydrated if
you've been chugging water thewhole time you were working out,
and then it depends what youate and when the last time you
ate was and all of these otherfactors.

(12:27):
So what we find is that, evenif there are facilities in a gym
to do this, people end upliking doing it at home because
it's just easier to beconsistent and so you can like.
The average that people do forus is they measure once a week,
and so it's like a Sundaymorning kind of routine or
something.
You get up, you do your scanbefore you do other things.

(12:50):
You know you can like take asip of water.
It's not, it's not going to bethat sensitive, but and then,
yeah, and so you can create thatconsistency a little bit easier
if you're able to just do itwherever you are with your phone
.

And there's no special suit required, like one
of your competitors.

No special suit.

No yeah that's I have that, I have that, and I'm
like it's annoying to have toput that on, even though it's
cool.
Yeah, yeah.

And it's yeah, it's interesting, I think it's
clever and I think all of thesethings are just good for the
consumer to have options andthing that works for you.
And, honestly, I think you alsohit on a really important point
at the beginning of thisquestion, which is that as you
track over time, the directionmatters even more, unless you're

(13:32):
in an absolute where that's atone of the extremes right.
So if you're like extremelyobese, for example, then yes,
that's very important to knowand you probably already know
that if you're in that state,and then the trend away from
that state is really where themagic starts to happen.

Cool, all right.
So we know about or we, Ishould say the general public
generally when I talk to them,knows about lean mass versus fat
mass and how lean mass iscomprised of fluid and glycogen,
as well as organs and bonetissue and muscle Muscle.
We can't forget muscle and thatyou're trying to reduce your

(14:13):
overall body fat and that aloneis going to correlate very
highly with health and yourphysique.
But there's other things youmeasure, and that's what I want
to get into how they measurethem for one, because I'm very
curious, whatever you're able toreveal, but the AG ratio, the
distribution, visceral fat, youknow.
Maybe give us a hierarchy ofeach of these.

(14:34):
And then what's most importantand why should we care about
these?

Yeah, yeah, I mean, I think, like you hit on, like
knowing your lean mass and yourlean mass index, which is
basically indexed against yourheight, these are really
critical things, you know.
I think Dr Gabrielle Lyon she'skind of says we have a
sarcopenia problem, you know,not an obesity problem, and it's
basically that muscleespecially is just this precious

(15:01):
metabolic tissue that does somany beneficial things for the
body and for your brain functionand your longevity.
So that's a critical one thatwe obviously provide.
You know, over time, if youwere to measure changes in lean
mass which you said includeswater, organs, bones and then of
course muscle and other thingsreally over time, the thing that

(15:23):
changes muscle and other thingsreally over time, the thing
that changes that you can changethe most is muscle, right, and
so water is what you seechanging day to day.
You know, if people aremeasuring their body weight on a
scale and they're like I lostfive pounds yesterday and then I
gained it all back the next day, it's like no, that was just
water, right, you know for themost part.
And but then over the longerperiods of time, you know that

(15:49):
noise kind of washes out andmuscle is really the thing that
is the primary driver of changein lean mass.
Hopefully you're not.
You know decreasing andincreasing bone weight that much
.
It's very light compared to themuscle tissue.
So that's one.

Can we actually interrupt on that one?
Because people who really nerdout on this stuff and I actually
came up with my own spreadsheetfor this about a year ago,
trying to infer the actualmuscle because the skeletal
muscle there's no way to do itand maybe you're going to
correct me if I'm wrong otherthan to say, okay, studies have
determined it's roughly thispercentage and now you can infer

(16:21):
against how you gain or loselean body mass and try to, like
you know, based on your wristsize.
There's like some otherinteresting factors that go into
trying to estimate and at theend of the day, you kind of
don't care really, because whatmatters is the lean mass changes
, your fat mass changing.
But what are your thoughts onthat, on like skeletal muscle
itself and measuring that?

Yeah.
So it's a great question, anddifferent companies who create
measurement tools have kind oftheir proprietary formula, so to
speak, that they claim is likebetter than anything else out
there, and we have formulasinternally that we also use,
that we start always from thescientific research, and so most
of the time the hard part forus is getting all the sensing

(17:02):
algorithms working, and that'swhere our secret sauce is.
But then, when it comes tocalculating changes in the
physiology, we try to stay asclose as we can to the
scientific literature, and soyou know, like you did, probably
as your starting point for yourspreadsheet, and but then from
there it's exactly the mentalitythat we have is, again, it
comes back to then the changesover time, Right.

(17:24):
That we have is, again, itcomes back to then the changes
over time, right.
And so, again, making it sothat you can measure more
frequently allows us to start toisolate out that kind of what
is a normal, let's say, like astandard deviation for your
daily weight fluctuation, right,as a very simplistic kind of
way of describing changes inwater Fluid.

Yeah, yeah, that's great.

Exactly so.
That allows us to establish abaseline and understand like
what your coefficient ofvariation is on changes in fluid
, and then from there we canstart to see the macro level
trend occurring.
That is more likely.
There's just a higherprobability that that's changing
skeletal muscle actually.

Okay, and a tangent off.
The tangent, before we get backto the list of things, is
different phases, right?
So we talk a lot aboutperiodization.
You get a muscle gain phase orfat loss phase, and in a muscle
gain phase you just have a lotmore gut content, a lot more
carb consumption, a lot moreglycogen in your muscle mass and
your liver and everything, andthen the opposite direction.
So can you account for that?
Is there a way for the user toinput data on that, or do you

(18:26):
just again the weekly?
Just will work it out over time.

It's getting more and more sophisticated.
The weekly kind of works itselfout over time.
But you know, another exampleof that is like going on or off
of creatine, for example, right.
So you know, right now, just tobe transparent, that will
pretty much count as a boost toyour lean mass or your muscle
when you cycle on to creatine,if you were not using it
previously.

(18:50):
Now, the good news is is, again, you'll know when you do that
and we provide some ways thatyou can kind of log that you're
starting creatine, for example,and then from there the trend is
still very meaningful, right,yes, and then from there the
trend is still very meaningful,right?
And so that's kind of how we'rehandling it right now.
But we're always trying to getmore sophisticated with those
things.
But it is tricky and to yourpoint, from a practical

(19:17):
perspective, at the end of theday, what we're really needing
is to know that our behaviorsare translating to a positive
trajectory, and so, yeah, we'redialing that in more and more.

Yeah, it reminds me a lot of you know you're
familiar with macro factor.
Are you stronger by science?
So we use that, like all myclients use it.
I talk about it all the timebecause they have a similar
philosophy of with theirexpenditure algorithm, of trying
to smooth it out, avoidovercorrection, handle all these
transitions and handle discretethings that lifters are doing,
like creatine, that you canreally point out and that is a

(19:45):
big one, because that is asource of frustration for people
.
I say look, expect anywherefrom two to like five or six
pounds of you just don't know.
Some people are over-respondersand they're so over-responding
that like it takes a month ortwo to work itself out and then
it looks like you're burning wayfewer calories and, like you
said, it looks like you have allthis extra lean mass.
That's just fluid, so it's goodto be aware of that.

(20:07):
So back to the hierarchy.
So you just talked about leanmass versus fat mass.
What's next, or what's the nextlevel down?

Yeah, so then you can get really really deep on
distribution of fat and musclearound the body From a muscle
perspective.
Like I mentioned earlier,generally more is better for
most people, for most things,but if you're going for a
specific look, then you may carea little bit about more of the
distribution of that muscle,depending on the audience.

(20:37):
I mean that I would say formost people doesn't matter until
you're at the more advancedstages of muscle development,
matter, until you're at, like,the more advanced stages of
muscle development, and that formost people it's just like, hey
, let's develop the entire body,you know, from a muscle
perspective.
And in any case, though for fat, this is where it kind of
bridges into like are yourpriorities looks?

(20:57):
Are your priorities health andlongevity?
For, again, most people theoverlap is very high between
those things, but then at somepoint, you know, they do diverge
a bit.
What we really care about froma health perspective is visceral
adipose tissue, which isbasically the fat that's around
the organs and in your abdominalregion.
That is the really big, youknow, red flag for health and

(21:21):
longevity and health outcomes,and it also isn't helpful for
aesthetics either.
It tends to be a really highcorrelation between visceral
adipose tissue and body shapesthat people don't like.

Yes, yes, yeah, exactly, Muffin top, menopause,
belly beer, gut, all the phraseswe know right, yes, yes,
exactly.

And so for us we offer this thing called
android-gynoid ratio and androidfat, and gynoid fat
specifically, can be measured.
But this is sort of it's not adirect measure of visceral
adipose tissue, because what itis is android is the trunk,
essentially how much fat are youcarrying in the trunk and

(22:03):
gynoid is the lower, like thehips, in the lower limb region
of the body.
And this is there's, theseratios like you just mentioned,
like neck, waist and hips, forexample, or waist to hip ratio,
these things that are kind ofnice, simple markers that are
very useful in fact, if no one'sbeyond the scale, if somebody
is like wants a really easything to start with, if you have

(22:27):
a tape measure, you can startmeasuring your waist and your
hips and your neck, right, andit doesn't cost anything.
You can just and you can startto get an idea of whether or not
you're moving in the rightdirection.
But in any case, we measurethose things you know,
automatically now, andthe-gynoid ratio is basically
the best proxy indicator ofvisceral adipose tissue other

(22:51):
than directly measuring thevisceral adipose tissue.
The correlation in the researchis anywhere from like 0.7 to
0.95, depending on kind of thepopulation and the measurement
methods, but in any case, it's avery high correlation between
the android-gynoid ratio and thevisceral adipose tissue number.
So again, this kind of comesback to what we just said about

(23:15):
body shapes that you don't wanttypically correlate with high
visceral adipose tissue or fataround those organs.
With high visceral adiposetissue or fat around those
organs, and it may not, as apercentage, be that much of your
body fat, right?
So the visceral adipose tissueas a percentage of your total
body fat may not be that much,but it's the dangerous stuff.

(23:37):
And so you know.
Regular exercise, lots ofwalking, anti-inflammatory
lifestyle whether that's gettingenough recovery and sleep,
managing stress, having eatinghigh quality foods with lots of
nutritious choices versus kindof more, like you know, rich
processed foods All of thesethings not only help us feel

(24:00):
more energetic and like lookbetter, but those are the things
that happen to also improvevisceral adipose tissue as well.
So, yeah, we just try to helpmake that easy for people to
measure.
We are not, so the camera can'tsee inside your body and that's
why we need to be very like,clear about what we're measuring
right.
And similarly, bioimpedance andother tools don't directly

(24:24):
measure visceral adipose tissueunless you were to place the
measurement tools directly onthat area of the body right, and
x-rays can see inside rightLike a dex as an x-ray, and so
all of these tools areestimating, and as are we, but
that's how we present it to,let's say, the end user, because

(24:45):
really it's a win-win.
If you're just improving yourAndroid gynoid ratio, it's
something you can measure now,whenever you want, using our app
, and then you'll get anindication not only of the
aesthetic goal but, if you'relikely, improving the visceral
adipose tissue as well.

Yeah, the fact that it presents itself visually
obviously seems to be a plus interms of being able to measure
it.
When you're taking an image andyou're sensing these things
Because I was going to ask youabout that it's like how do you
infer fat mass?
You said you have all thisvalidated kind of reverse
engineered data Then you must becorrelating that with the
outward appearance of someoneeffectively.

(25:23):
Is that a simple way to put it?

Yes, yeah, and we so we require you to get in your
underwear usually, or, or, ifyou, certain fitness attire
works to like sports bra andlike tight fitted biking shorts
or something like that.
But yeah, it's really amazingwhat machine learning and
computer vision can do and whatit can see that the human eye
can't really see.
And because there's differentgradients on the skin, you know,

(25:50):
depending on this is anotherthing too that we've had to
develop, and why it's soexpensive to develop this stuff
is changes in lighting actuallycan change your appearance quite
a lot, right, and so we tellpeople you've got to have
adequate lighting.
You can't do our measurement inthe dark, but the cool thing is
is that once you reach acritical mass of volunteers and

(26:11):
training data and ground truthdata, it actually can account
for the changes in lighting.
Interesting.

Like self-driving cars kind of that's what I'm
thinking of, how they can handlejust about any environment.
Yeah, Okay.

Yeah, and so the cool thing too is we can even
detect, like, okay, last timethat you did a scan you were
standing six feet from the phoneand this time you're standing
six and a half feet from thephone.
We don't just assume that yougot shorter since the last time
that you did a scan.
Right, we can actually detectthat and account for that and

(26:43):
correct for that.

You know, as we were talking, I was rudely
Googling something that came tomind as you were mentioning
visceral fat, because there'ssomething called the body
roundness index.
You must be familiar with thisBody roundness index, which
calculates visceral fat based ongender, ethnicity, age, height,
weight, waist, hips, and ittries to determine your adipose
tissue.
And I don't know how validatedit is, but it sounds similar,

(27:08):
right?
It's using again outwardmeasures and I suspect you have
a lot more fidelity becauseyou're able to use more.
Is that the case?
I guess, when you're measuringfat mass and visceral fat and
everything, have you found thatthere's a kind of complex web of
data points and it's like ahuman wouldn't really be able to
comprehend it because themachine learning has gotten to
that point, or can it be kind ofproxied and simplified in some

(27:31):
way?
To admit, that's pretty good.

Yeah.
So I mean like to your point.
Yes, you can start like it'skind of like we were saying
earlier where you can like, as acoach, you can look at a client
and see, like, generallyspeaking, I know they're in this
range, right, and you may beplus or minus some amount, and
as you learn more about them youmay get a little bit more
accurate.
The body roundness index isintended to be a replacement or

(27:56):
an improvement to BMI, and sobody mass index is essentially
just your weight and your heightcompared, right, and
essentially what you know.
Let's say.
Let's take the military, forexample.
The military used to excludepeople from qualification for
duty based on BMI, so you couldhave a really strong individual
that's got high muscle densitybe excluded from, you know,

(28:20):
qualification for duty.
The very people you want in themilitary big, strong guys from
qualification for duty, the verypeople you want in the military
big, strong guys, exactly, yeah, and so BMI is just really not
that useful for a lot of things,and we're finding that out more
and more.
Bri is sort of an answer tothat.
It's something that you canmeasure with low tech, basically
, and get a much betterindication directionally of

(28:42):
somebody's health or theirmetabolic health and ability,
and so it's better predictor fora lot of different risks.
But it still is not the same asdoing a DEXA scan or
understanding your visceraladipose tissue a little bit more
closely or, in our case, yourandroid-gynoid ratio.
That is the best estimate ofthat.

Cool.
Yeah, I knew you would knowabout that.
It's just one of those newthings on the scene because
people talk about BMI a lot andhow awful it is, even though it
still has some validity at theextremes.

I mean it's definitely like look, you know,
if you're really jacked, right,so like if you measure your BMI
and it's like too high, and youlook at yourself and you're like
I'm jacked, then you know.

That's all my clients, man, that's all my
clients.
No, you use your intuition inthat scenario right.

Otherwise, the BMI might be telling you something
that you know there's somethingto improve there.

Yeah, no, that's funny.
You mentioned that Cause.
Yeah, but most people I knowwho have been lifting a while,
they do get to that point wherethey're carrying extra weight on
purpose and they have moremuscle.
So it's like you're in thateasily in that what looks like
obese category and it's likedon't worry about it.
The apple and pear shapediscussion that we've talked
about over the years is thatrelevant here?
Is that related to the AG ratioas well?

Yes, so if you have a higher android-gynoid ratio,
which means the android numberis higher typically than the,
gynoid one yeah, so that's thatapple shape.
And then if you have the reverse, where your gynoid number is
higher and that's a lower ratio,that's more of that pear shape.
And so men typically have alittle bit more of an apple

(30:17):
shape.
Just, you know, stereotypicallycarry fat more around the
midsection and women, morestereotypically, carry it more
in the hips, the butt, thethighs, etc.
And have more of the midsection, and women, more
stereotypically, carry it morein the hips, the butt, the
thighs, et cetera, and have moreof that pear shape.
And so you know, generallyspeaking it's you can get really
into the weeds for anyindividual right?
Yeah, makes sense, but thoseare kind of the general ranges.

So if it's top to bottom and that's the ratio, do
we care about a number on ascale or do we care about change
again?

really strong, especially like.
Take the difference between abodybuilder and like a strong
man.
Right and strong men,competitors tend to have very

(31:10):
thick trunks but it's like hugeamounts of muscle, you know,
whereas a bodybuilder can havetons of muscle but have a pretty
narrow waist, and a strong manwould then have a higher AG
ratio versus the bodybuilder,and it's difficult to say in
those extreme cases.
I guess which one is more orless healthy?

(31:32):
Right, Right, Because it kindof just depends.
If they're recreationallypursuing those sports, then they
both might be perfectly healthy, but at some point they're both
sacrificing health to prettyhigh degrees in chase of
performance.
And so, in any case, if you'relooking at the AG ratio, the

(31:54):
reference ranges are based on,like the mean population norms,
and so you don't want to be outof range most of the time,
unless again you're super jackedand you know it Got it.
So yeah, high AG ratiogenerally means more adipose
tissue, more visceral adiposetissue in the midsection and

(32:18):
again, isolating out fat frommuscle as well, because in that
strongman bodybuilder example alot of that was lean mass.
But we're wanting to look atfat distribution really.

Okay, yeah, no, that's fascinating stuff.
I'm just curious behind thescenes what it all means,
because I think of how we're allso different and I've always
said I have a bigger butt thanthe average man.
Most guys have flat butts and Ihave a big one, so my AG ratio
is probably going to be a littlebit wonky to start, but then it
matters how it changes overtime.
Measurement a couple times Idid want to address that because

(32:55):
when it comes to measuring lotsof different things, we have
different scales.
We measure right From daily toweekly to monthly to quarterly,
depending on what it is Usuallylike food and weight.
I generally recommend people dodaily if they're trying to be
precise about it, and then theyuse averages and trends.
I think you mentioned weekly onSundays, which also sounds like
pretty much aligns with generaladvice when it comes to body
measurements just basic metrics,but why wouldn't you do it more

(33:17):
frequently or less frequentlythan that?

So you can, and that's just kind of where the
average, where people land, andso some people do it daily and
then kind of, you know, again,we just strongly caution.
This this all kind of basicallycomes back to is we don't,
since we're not selling a deviceand we don't have all these
costs tied to that.
Our goal is to not get you tojust do measurements for the

(33:42):
sake of doing measurements, soto speak.
Sure that we're sellingoutcomes, right.
So basically it's like themeasurement tool is just one
thing that is important ingetting you to the outcome that
you're looking for, and sothat's important context that we
can dig into.
But then the other piece is themindset of the individual doing

(34:04):
the measurements, right.
So if you really want to be anoptimizer, then you could do
these every day and you willjust know and we will try to
educate you as well that thosedaily fluctuations that you may
see are a little bit more tiedto you know, water changes and
things like that.
And then we're trying to lookat the macro trend a little bit

(34:26):
more there, Right?
And and then again, you coulddo it less frequently once a
month, once a quarter, Peoplewho do DEXA scans usually are
doing them, maybe once a year ormaybe twice a year or something
like that.
The problem is, there is again.
It's like doing a blood testonce a year.
That's great.
It's better than never doing ablood test.

(34:47):
But certain markers, even inblood biomarkers, heavily depend
upon what you ate the daybefore.
Yes, yes, yes.

Stephanie (34:56):
The most value that I got from this was the fact that
I had someone that I could talkto about anything and that
there was going to be nojudgment.
It was just well, here are yourgoals, here's the best way that
you're going to achieve it, andthen let's work together to
help you feel inspired andmotivated to do that and there's
a lot of people out theretrying to be coaches and not all

(35:19):
of them have done the work andalso just be a genuine person
that is positive and coming fromthe heart in terms of wanting
to help, and Philip reallyembodied all of those qualities.
I would recommend him to justabout anyone that's looking to
achieve goals in that realm oftheir nutrition and building new
habits that you only did twomeasurements.

Well then, if you're on like a down slope on
one measurement and you're on anupslope on the other
measurement, you might be like,oh, my weight hasn't changed at
all, or something, when inreality your mean weight over
the course of, let's say, acouple weeks, that baseline
might be 10 pounds differentactually.
And so what we're trying to dois kind of zero in on what's a
frequency that allows us to makedecisions and make informed

(36:18):
choices but not overwhelmourselves.
You know, depending on what ourmindset is or capacity for
isolating out variables.

Yes, and that's a really important point, is the
psychological and the fatiguethat comes along with any of
these systems.
I mean, same thing goes withfood and tracking and everything
else.
It's like that balance betweenprecision and going crazy, like
you know.
Where's the fine point?
I think it's a fascinatingtopic because in the scale
weight world right there havebeen a lot of studies on this.

(36:48):
There's a fascinating one thatcompared five days, compared
zero, like once a week, to fivedays a week, to seven days a
week, and found that the sevendays a week tracking had the
best adherence andsustainability results.
And I mentioned macro factorbefore and they use a
exponential 20 day exponentialmoving average for weight, which
is like okay, over a three weekperiod.

(37:09):
That's long enough to know thatyou've accounted for water
weight fluctuations and becauseyou're weighting the more recent
measurements more heavily, thatalso gives you a good
confidence that you're eithergoing up or going down.
So that's why I think it'sfascinating with measurements,
because I've never recommendedmore than once a week only
because your body can't changethat fast in terms of
measurements.

(37:30):
But when you have this level ofprecision you guys have, I
wonder if that changes theequation where, like if you
don't mind doing it every day.
Does that give you any sort ofedge?
Does it help the app?
Does it help it learn about youand all that?
Or is it kind of is there asweet spot for people who are
willing to do it more frequently?
That's what I'm asking.

Yeah, I would put it more in the optimization camp
to do that.
So yes, the algorithm getsbetter if you do it frequently
that way, but not that muchbetter.
And also from a practicaldecision-making point of view,
you know you're probably notmaking big changes in your.
So it's like measuring likesleep or HRV or something like
that.
You can measure that on a dailybasis and look at these kind of

(38:11):
weighted moving averages andthings and say like, oh, I got a
little bit of a light sleep.
I'm not really going to changemy whole routine for the day
based on that, but if you have amajor red flag come up you
might right.
That doesn't happen typicallywith body composition and so,
unless you're just extremelydehydrated.

(38:32):
So that is one.
Actually let's part the curtain, I guess, a little bit on.
One reason why some of ourmembers have started to measure
more frequently is as we startisolating out the changes in
fluid.
That does give us a little bitof a window into hydration, and
so we're kind of studying thatstill, because I think it would

(38:54):
be kind of easy to overextrapolate that.
But in any case there might besome guidance that would be
useful on how much to prioritizehydration or electrolyte
balance or things like that.
Based on some of these likemore daily changes or short term
changes.
But yeah, from body compositionpoint of view, to your point,

(39:14):
once a week is great.
You know, at the end of theweek you can see some of the
change happening and start tohave that like directional trend
forming, even after just oneweek, and start to make choices
of like are my protein targetsor are my macros or are my
calorie targets, kind of keepingme in the direction or range

(39:34):
that I want to go in.
Right, Fascinating.

You keep bringing up topics that I would love to
go down in the future, like thehydration because immediately my
mind goes to the amount ofwater you're carrying at any
given moment isn't as simple ashow much hydration you've had
right.
It's also what you've eaten andhow much sodium you've had.
And menstrual cycle for womenand inflammation from your heavy
leg day yesterday.

(39:57):
It's insane how much effectsfluid containing your body and
you might drink the exact sameamount day to day.
So that's fascinating.
Hrv you mentioned it, so youopened the door to that.
Because you guys measure HRVand I know you're working on VO2
max or inferring VO2 max.
Tell us about those.
Let's start with HRV VO2max orinferring VO2max.

Tell us about those .
Let's start with HRV.
Yeah, so I mean overall, ourmission is basically to take
meaningful data points that areused in lab settings and to
break down the barriers so thatpeople can just measure them,
while keeping the quality high.
Hrv is actually where ourcompany spent.
You know, basically the firsthalf of our existence was
focused on HRV, and so we have along history with it.
We worked with the polar cheststraps, the Garmin chest straps

(40:38):
and using Bluetooth and whenthat was innovative a decade ago
.
And then we created our ownhardware, a medical grade sensor
that we distributed to 80countries around the world and
then discovered that we could docountries around the world and
then discovered that we could doagain kind of cannibalized
ourselves in that regard bysaying we had all this ground

(40:59):
truth data coming from validatedsensors like chest straps and
ECG based sensors, and we coulduse that data to train models,
to then detect heart rate, hrvand respiration using just the
camera of the phone.
And so we have that technologynow it's in the Sprint app as
well, and you can track resting,heart rate, hrv and respiration

(41:22):
just by touching your fingertipto the camera on the back of
your phone and doing heart ratethat way is not actually that
novel.
There's a lot of companies thathave been looking at that and
it's a similar technology thatwearables use.
So you know, ppg is this wholerabbit hole we could talk about.
But essentially wearables areshining light into your skin and

(41:45):
as the blood flows through thatarea of the skin, the color and
different features of thatcamera signal change as the
blood flows through anddifferent features of that
camera signal change as bloodflows through, and you can
calculate what's called pulse,wave volume and things like that
from that data.
So similarly, the camera can dothat too.
If you open the camera app, youdon't even need a different app

(42:06):
to see this.
But if you open the camera appon your phone and just cover the
camera with your fingertip, thewhole camera will turn red and
as light shines through yourfinger you have to be in a
bright room or whatever, right?

Which I am, and I'm doing it yes.

And so some people, if you look closely enough, can
actually see their pulse inthat in the camera, and so it's
pretty cool, I did it.

Right now, guys, I'm seeing it like yeah, yeah,
oh man, that's cool, Isn't thatcool, right?

So that you know again, you could sit there and
count your pulse like on a clockand come up with your heart
rate from that number.
But a heart rate variabilityneeds a much higher degree of
accuracy and granularity,precision.
Hrv is essentially calculatingthe time in between, the
variation in time in betweeneach heartbeat, and it's

(42:57):
measured in milliseconds.
So you need really moreprecision than the human eye can
offer to measure HRV.
But the really fascinatingthing is once you get HRV and
you have resting heart rate, ofcourse, and then respiration can
be extrapolated from heart rateand HRV.
Respiration can be extrapolatedfrom heart rate and HRV because

(43:19):
one of the primary contributorsto changes in your HRV is your
respiration.
It's called respiratory sinusarrhythmia and we could go in
this whole rabbit hole for that.
But as you breathe in, yourheart rate increases and as you
breathe out, your heart ratedecreases.
Unless you're exerting yourselfheavily, then it's kind of
imperceptible, basically.
But in any case, these threethings give you a lot of

(43:41):
information.
People will typically do thisfirst thing in the morning.
Every morning you just wake up,touch your camera for 60
seconds.
You'll get that resting HRV,heart rate and respiration data,
which then translates intoalgorithms that we had developed
over the last 10 years thatallow you to get that readiness
and recovery scoring.
Some people, who might have awhoop or an aura ring, you know,

(44:03):
might be used to having areadiness score or recovery
score.
That's something that we weresome of the pioneers of, but we
went in a different direction.
Instead of doing the continuousmonitoring through a wearable,
these are point-in-timemeasurements that you don't need
a wearable for and I have justas much utility, and we have a
ton of scientific studies nowthat we can point to predicting

(44:25):
injury, predicting recovery,predicting inflammatory
conditions and things like that.
Just doing these morning spotcheck-ins, that is awesome.

I mean the way you could use a camera and some just
having this in our pocket,because I love looking at
history and like the history ofcomputing and computers and just
the space program andeverything that we have since
then, just to be able to do thisis awesome.
Look, I know we only have acouple of minutes.
Do you have like a few minutespast the hour just to wrap up?
Okay, cause the VO two max.
I'm really curious about that.
I did my first ever, my only sofar VO two max in the lab test,

(44:58):
which is miserable for anybody,especially if you don't like
cardio, which I don't, likeeverybody knows.
Like I love walking andsprinting, but not going all out
for until you die on a on a ona treadmill, which is what they
do, guys.
It's tough and it was.
You know I was carrying excessweight because I was at the top
of a bulking phase which thenslams the number down,

(45:18):
unfortunately, and then I don'thave very, I'll say, as high
cardiovascular fitness as Iwould like to have and can work
on it.
So VO2 max we see it assomewhat of a gold standard of
cardiovascular fitness.
How do you guys measure?
How do you guys plan to measurethat?
Or infer it, I guess.

The underlying data is tied to this measuring
resting, heart rate, HRV andrespiration and so, with some
other context pulling in, thingslike activity level, exercise
and some performance stats canenhance the accuracy of the
estimate.
But even with just those dailyphysiological measurements,
there's actually some prettygood literature now showing that

(45:58):
it's essentially looking at thecorrelation between those and
VO2 max.
And so we have seen just look,digging into the data, you know
we have seen some ways to kindof refine that a little bit more
to where we feel comfortable.
We tend to have a pretty highbar of like, like you said, like
somebody might put out like abooty score or something like

(46:18):
that, and that's, that's cool.
It talks to people like.
Some people are like oh, I wantmy booty score to go up or down,
I don't know, I'm not sure, butin any case we tend to kind of
err on the side of like.
Is this related to somethingthat's valid?
You know that we've seen prooffor, and so VO2 max estimates
from these kind of longitudinalcardio respiratory markers are

(46:43):
something that we're reallyexcited about because we're
getting pretty close on that andfrom a longevity perspective,
or even a performanceperspective for many sports, you
know, strength, VO2 max, likethese are like top of the list
things that people should becaring about.
From a health, it's like ifyou're looking for looks, you're
looking for health or you'relooking for performance, you

(47:06):
know.
Vo2 max, strength, mobility,balance, muscle mass these are
the top of the list.

Okay, and that actually brings up one quick
question then, with muscle mass,are you able to give somebody
sort of a physique scoresymmetry, something like that,
or is that coming in the future?

It's a good question.
Yeah, I mean basically, yes,it's coming in the future, and
partially just because, too,these types, as you start to
collect all this data, evensomebody like you and I, I mean,
I don't know, maybe we'repretty off the charts when it
comes to our appetite fordigging into the data, but 95 to

(47:43):
99% of people are like I wantto know that the underlying data
is there and that it's credible.
But I also just want to see,like this summary score or this
like tell me what to do, kind ofthing, Right, and so we're
always looking for ways to makeit easier.
Again, that booty score is agood example of like some people
are, just like I.

(48:03):
Just that's all I want to knowis, is my booty going to get
more peach perky or you knowwhatever?
And so yes is the short answer,Love it.

Yeah, I can see the skies are living on this,
especially the way technology isgoing.
I'm sure you guys' capabilityis just going to continue to
increase.
All right, so as we wrap up, isthere anything else you wish
I'd asked, or anything aboutwhat you guys are doing with the
population of Spren users thatwe should know about that?
I haven't asked because I don'tknow to ask it Anything like
that.

Yeah Well, I'd mentioned that we're selling
outcomes and that people kind ofscratch their head a little
when I say this.
But these measurement tools andthe data that you get out of
them is just this tiny slice ofthe pie when it comes to the
overall health and wellnessjourney or the performance
journey, and I obviously thinkit's an important slice because

(48:53):
I'm devoting my life to itjourney, and I obviously think
it's an important slice becauseI'm devoting my life to it.
But all the ways that youtranslate that into action for
your nutrition, for yourexercise, for your sleep, for
your stress, for recovery, for,you know, relationships and
navigating all of that stuff,that's where really all the
magic happens, and the datashould just be in support of all
of that.
And so the first question thatwe always get when people do our

(49:17):
body scans and other things islike wow, I did not know this
about myself, now, how do Iimprove it?
Right, and so we're not theexperts at everything in the
entire world.
We can guide you generally inthe right direction.
But we also now partner withcoaches and experts and fitness
and wellness facilities andwe're excited about that because

(49:40):
these brands appreciate thesebrands and these experts
appreciate our scientificcredibility and our proof points
and quality, but then they canalso help bring a lot of the
expertise and the guidance andthe individual services that
people need to actually get theresults.
So I just wanted to share that,because that's how we see

(50:03):
ourselves fitting into theuniverse, and actively.
That's a big part of theplatform that we're expanding
right now.

Well then, we're aligned because I'll let you in
on a secret I only like to havepeople on the show who are going
to teach me something new, thatamplify a slice of that pie
that we haven't covered too muchand that the listener can learn
something new.
And then the rest of thispodcast tries to cover all those
other things as well.
So I totally feel you, man,because we need them all, but we
also need to take action andimplement the information.

(50:31):
But I love informed decisionmaking and that's what we're
trying to do here.
I appreciate you, I appreciateyour genuine passion for this.
I can tell you know there's alot of different types of folks
in the world and I can tell youyou're in this and it's
important and you want to helppeople.
So thank you so much, jason,for the conversation.
This is a lot of fun.
I could keep going, but it'sand Waits.
Where can folks find you?

(50:51):
Where do you want to send themto?

Yeah, thanks Sprencom S-P-R-E-N, or you can
search for Spren in the appstore.
We're there as well, so we lovehearing from people.
So shoot us a message if you'velearned something or you have
feedback for us or if we canimprove in any way.
You can find us a little bit onsocials.
I'm going to be honest and saythat we're not the best at

(51:13):
keeping like a big social mediapresence or anything, I like you
even more, man, since you saidthat, because I'm not a huge fan
of social either.
Yeah, I mean, it's a great toolfor some things, but people also
scratch their head when I sayover a million people have
actually used our tools, but weonly have a few thousand
followers on social becausewe're just not that active there

(51:33):
.
But we only have a few thousandfollowers on social because
we're just not that active there.
But we learn genuinely a lotfrom the community and that's
one of our secrets.
That's not so secret, butanyways, thank you, philip.
This has been awesome and yeah,I can tell by the way you lead
all of this, that there's a lotof people in your audience we
could learn from as well, sothat's exciting.

I love it.
Yeah, I'm going to be digginginto this more.
We're going to we're going tostay in touch, because it's
pretty cool when things likethis come up, and I wasn't
really aware of it, which iscrazy, cause I I look into this
stuff all the time and somehow,so now we're going to make
people aware of it, at least inmy community.
And again, thanks, jason, forcoming on.

Thanks, bill Bye.

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Can Your Phone Replace a $100K DEXA for Body Fat and Physique Tracking? (Jason Moore) | Ep 367

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.css-14f5ked{margin:0;word-break:break-word;display:-webkit-box;-webkit-box-orient:vertical;box-orient:vertical;-webkit-line-clamp:2;overflow:hidden;}Can Your Phone Replace a $100K DEXA for Body Fat and Physique Tracking? (Jason Moore) | Ep 367