Can Your Phone Replace a $100K DEXA for Body Fat and Physique Tracking? (Jason Moore) | Ep 367
Want to build muscle, lose fat, and train smarter? Join the new Physique University for just $27/month and get your custom nutrition plan FREE (limited time).
—
Can your smartphone really rival a $100,000 DEXA scan? What if the same device you use to scroll Instagram could also reveal your body fat percentage, fat distribution, and even your HRV?
I sit down with Jason Moore, founder and CEO of Spren, a company turning your phone into a precision biometric tool. We talk about how Spren compares to gold-standard lab equipment, why body composition tells you more than scale weight ever could, and why tracking trends is often more important than chasing perfect numbers. This conversation will show you how technology can bring lab-grade insights straight to your pocket.
Today, you’ll learn all about:
0:00 – Intro
2:36 – Why body composition matters
6:56 – How a phone measures fat
10:55 – Accuracy versus precision explained
14:38 – Lean mass and muscle changes
20:15 – Why fat distribution is key
29:56 – Apple versus pear body shapes
33:20 – How often should you measure
40:15 – Using your phone for HRV
45:34 – Predicting VO₂ max with data
48:32 – Turning numbers into outcomes
Episode resources:
Website: spren.com
LinkedIn: linkedin.com/in/thehumanjason
Instagram: @thehumanjason
Can Your Phone Really Track Body Fat Like a $100K DEXA Machine?
If you care about building muscle, losing fat, and improving health, you have probably heard of the DEXA scan. It is considered the gold standard for measuring body fat, lean mass, and fat distribution, but at more than $100,000 for the equipment and a hefty fee per scan, it is not practical for most people. Enter smartphone-based body composition apps that claim to give you DEXA-level accuracy with just your phone’s camera.
Jason Moore, founder of Spren, joined me to talk about how this technology works, why it matters, and what metrics beyond body fat percentage could transform how you approach your physique goals.
The Evolution of Body Composition Tracking
For decades, the scale has dominated how people think about progress. Later came BMI, calipers, tape measures, InBody scans, and of course DEXA. Each has its benefits and drawbacks. What makes smartphone technology unique is that it combines accessibility with validated accuracy.
By training machine learning models on thousands of side-by-side scans with DEXA, Spren has created algorithms that can analyze images of your body and estimate fat mass, lean mass, and fat distribution. Every scan improves its calibration to your individual body, which increases precision over time.
Why Fat Distribution Matters More Than Body Fat Percentage
We often think the number itself is what matters: 18 percent body fat, 25 percent body fat, and so on. But Jason points out that where you store fat is more important than the total amount when it comes to health risks.
Gynoid fat (hips, thighs, butt) is generally less harmful.
Android fat (trunk and midsection) correlates with visceral fat, which surrounds your organs and is tied to heart disease, diabetes, and inflammation.
Spren’s Android-Gynoid ratio (AG ratio) is one of the best available proxies for visceral fat. Improving that ratio not only changes how your body looks but also improves health markers.
Lean Mass: The Most Valuable Tissue You Have
Spren also tracks lean mass, which includes water, bones, organs, and most importantly, skeletal muscle. Over time, the biggest changeable factor is muscle. And since muscle mass is one of the strongest predictors of longevity, performance, and metabolic health, monitoring it alongside fat loss is critical.
This makes Spren useful not just for people chasing aesthetics but also for anyone prioritizing healthspan. As Dr. Gabrielle Lyon often says, we do not have an obesity problem so much as a muscle deficiency problem.
Frequency of Measurement: Weekly is Best
Like weight tracking, consistency matters. DEXA scans can be thrown off by hydration and food intake, and smartphone scans are no different. But because you can measure frequently at home, the algorithm smooths out these variables.
Most users find that once per week works best. It balances accuracy with sustainability and avoids the psychological fatigue of obsessing over daily fluctuations. If you prefer daily scans, you can, but the improvements in precision are marginal compared to the mental load.
Beyond Body Fat and Muscle: HRV and VO2 Max
Spren is not stopping at body composition. Using the phone’s camera and fingertip measurements, the app can track heart rate variability (HRV), resting heart rate, and respiration. These markers are powerful indicators of recovery, readiness, and stress.
Soon, Spren will roll out validated estimates of VO2 max, a key measure of cardiovascular fitness. By combining body composition, HRV, and VO2 max, your phone will give you a well-rounded view of both health and performance, without the need for expensive lab tests or wearables.
Why This Matters for Everyday Lifters
Most lifters and everyday athletes do not need bodybuilding-level precision. What they need is reliable, repeatable data that tells them if their training and nutrition are working. Smartphone-based tracking can provide:
Confirmation that lean mass is being maintained during a cut
Evidence that muscle is being built during a bulk
Insights into whether fat loss is coming from the midsection (android fat) or less concerning areas
Recovery data to adjust training intensity and stress management
All from the same device you carry everywhere.
The Takeaway
While no method is perfect, the technology behind smartphone body composition apps is now accurate enough to rival clinical tools like DEXA. When used consistently, it can track fat loss, muscle gain, fat distribution, and even recovery metrics in a way that is practical and affordable.
If you want better insight into whether your hard work in the gym and kitchen is paying off, it might be time to put your phone to work.
Have you followed the podcast?
Get notified of new episodes. Listen on Apple, Spotify, or all other platforms.
Then hit “Follow” and you’re good to go!
Transcript
Philip Pape: 0:01
Can a smartphone app match the accuracy of a $100,000 DEXA scanner for body composition? My guest today discusses new technology that uses your phone's camera to measure body fat percentage, your Android to gynoid or AG ratio and HRV, all without additional hardware. Learn how weekly measurements compare to daily and monthly tracking, how professional coaches are integrating this technology with elite athletes, and how you can better track progress to achieve your health and physique goals. Welcome to Wits and Weights, the show that helps you build a strong, healthy physique using evidence, engineering and efficiency. I'm your host, philip Pape, and today we're discussing a new way to measure body composition using your smartphone.
Philip Pape: 0:52
You guys know I like tech, I love data, I love precision and I was excited to have Jason Moore here today. He is my guest. He's the founder and CEO of Spren, a company that is turning your phone into a precision biometric tool and linking to lots of other amazing things that we can get into. Spren has already helped over a million users measure body comp, the AG ratio which we're going to explain what that is HRV and soon other things like VO2 max and even, I think, mental stress load, using nothing but your phone's camera. Today, you're going to learn how this technology's accuracy compares to other everyday measurements like calipers, like tape, as well as clinical equipment like DEXA, why additional metrics like the AG ratio that I just mentioned might be more helpful than some others like body fat percentage alone and how the timing of your measurements and other process-related improvements can dramatically affect your results. So, jason, thank you so much for coming on the show.
Jason Moore: 1:45
Hey, philip, happy to be here, thank you, thanks for hosting, and I love that I'm in good company with a bunch of nerds that are ready to dig in on data and technology. So, yeah, excited to be here.
Philip Pape: 1:56
Oh, 100%, man, this is cool stuff, I love this stuff. And when you look at the history of how we measure body composition which, by the way, some people don't even know what we're talking about when we say body comp, right, we're talking about the percentage of different types of tissue in your body, like fat to muscle, and we care about that because just losing weight isn't the only marker of health right, it's your overall body composition. And when you look at the evolution of, okay, we've got scale weight, then we have BMI, then we have BMI, then we have measuring body fat in all different ways, lots of confusion, and now we have fat distribution. Even so, if a healthy physique is really important to somebody who's listening, what is the best way to think about body composition before we get into the details?
Jason Moore: 2:36
of measuring it. Yeah, I mean, that's a super critical kickoff point. So thanks for bringing it up, because if you've ever worked with clients, if you're a coach out there or something like that, and you ask people like what's your goal, they might say, like lose 20 pounds, and you're like, well, why right? And it's like, well, I don't know, I just need to lose 20 pounds. And if you really kind of start to unpack it, usually it's either because they may know that they're kind of you know, carrying a little extra fat, or they 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 got diagnosed with prediabetes or something like that. Right, like they kind of triggered this. A lot of times it's looks and or even if it's not, a lot of times the outcome can be tied to looks, because that we're just very visual creatures and so instead of asking them, you know how much weight you want to lose. If you show pictures of like different looking physiques and say, like point to the one that you think that you want to be like, you know, in the next reasonable amount of time, let's say six months or something like that and they point to one. You might actually say, hey, you don't actually need to lose any weight on the scale to look like that, and what really might just need to happen is we need to 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 being the same weight on the scale, but look a lot better, look or like more like your goal, so to speak. But look a lot better, look or like more like your goal, so to speak, also feel a lot better and then have a lot of your health markers get into range. And so body composition.
Jason Moore: 4:12
Maybe this is about a roundabout answer here, but body composition looks way beyond that scale weight and looks at the composition from a fat and muscle and water perspective, but also the distribution around your body, because it matters where you carry fat and muscle. Generally speaking, more muscle is better for most people. There's some diminishing returns at the top of that, but when it comes to fat, being like a little bit soft is really not that big of a deal from a health perspective. Like a little bit soft is really not that big of a deal from a health perspective. There's no real evidence that having a little extra fat is unhealthy. It's where that fat is on your body that really matters from a health perspective. But in any case, too, there's a looks portion of that that body composition gives us a window into. So does that kind of cover it.
Philip Pape: 5:03
you think, yeah, no, you hit on some really good points. I want to reiterate for listeners the first is just the weight loss versus fat loss, and I like that you use the language there, because a lot of people don't, especially with marketing in this industry. Your website if you go through the onboarding to figure out what the best way to use the app is, right off the bat it talks about fat loss and I was happy to see that. Right, I know you guys use the term weight loss in articles and stuff, but still, the look and feel versus the health right, they're not mutually exclusive. I love that you mentioned that as 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's an expression of your health and it's not that we're looking for external validation so much as there's an internal confidence and self-image associated with that, and I think it's a mentally healthy place to be when it's tied to your health and the process, as opposed to tied to weight loss at all costs.
Philip Pape: 5:55
You then said the two different physiques, so what came to my mind was a little bit of a litmus test when you ask, let's say, a woman. You ask her what is a ideal physique and she points to an athlete who's pretty lean. And then you ask her to guess the scale weight and invariably they're going to be off. You know, not everybody. If they know I'm trying to trick them, they'll go higher. But they're generally like 20 or 30 pounds heavier than you think right Because of the density differences and the lean mass and all that.
Philip Pape: 6:22
And then you mentioned the distribution of fat, which I want to get into. One of your competitors keeps adding different metrics like booty score and physique score, and I'm like it's pretty funny because it looks like algorithmically it tries to be tied to where the fat is, just like 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 a smartphone measure all this? Because I want to understand that. And then let's get into what it's measuring and body fat distribution, all that good stuff.
Jason Moore: 6:56
Yeah for sure. Yeah, I mean, it's interesting. I'm a technologist and I've done some inventions on my own and stuff, but the things that we're doing now just kind of blow my mind with the phone and the camera, because there's a lot of different ways to do it. One of those would be like if you were to look at an image of an individual standing and you could see their whole body right, you could kind of go and measure like okay, if you knew their height, you could go measure their waist, and you could go measure like their shoulders and things like that, and you could start to get an idea of their body composition. That way, it'd be a rough estimate, but you know, that's kind of what we do. Again, if you're a coach and you're looking at somebody like a client standing right in front of you, you can kind of gauge their height, you can kind of gauge their shape, and you can kind of start to make some guesses at their body composition. So that's one way.
Jason Moore: 7:46
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.
Jason Moore: 7:53
Of course, mri is really more of the gold standard and like autopsy or something, but that's a one way, you know, measurement.
Jason Moore: 8:02
So in any case, we benchmark off of DEXA and what we've done is we've had thousands and thousands of people do DEXA scans and also take images with their phones of their body, and then we train machine learning models to start to see what the DEXA sees by predicting that outcome using different machine learning models. And so for us, I mean, that's an expensive way to develop these estimating technologies, and some companies have spent dozens and dozens of millions of dollars trying to figure out how to do that, and we've been very fortunate to have some major unlocks that have really made the accuracy essentially comparable to DEXA, by collecting enough ground truth data and pairing it with a diverse population, and then some in-house expertise of we've just been working with sensors and physiology measurements for over a decade. So that's kind of how we do it. It's a little bit of a black box underneath the hood, you know. There's probably some things like that going on that like a human could start to do, but then the machine learning models just take all of that to the next level.
Philip Pape: 9:09
Yeah, no man, I'm nerding out on this because I love that stuff.
Philip Pape: 9:13
Before we got on the call, you were talking about how you guys have been using AI machine learning long before ChatGPT existed and people don't realize that that kind of technology has been probably two decades in the making across a variety of fields. Right and so taking real-world of technology has been probably two decades in the making across a variety of fields right and so taking real world data that has been validated after the fact with higher quality machines 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 clients do or suggest to people, is the Navy formula, neck and waist, or for females, neck, waist, hips right, and there's supposes that there's some sort of ratio going on there. And I tell people look the number, don't trust the number, trust the trend over time of the number. Is your technology giving you a number that you think is actually reasonably accurate, or do you also have some reservations on that?
Jason Moore: 10:06
No, yes, so insofar as much as you trust DEXA. And so DEXA is not perfect. In fact we're within the margin of error of DEXA itself. So if you take multiple DEXA machines and compare them to each other and then you kind of take like a weighted average or something like that, then we're actually closer to the weighted average than the individual machines sometimes are, and so the accuracy is very high for the actual number. But then the precision is even higher because we have some advantages in the sense that we have software and you know the whole infrastructure behind the software to then calibrate. So one of the neat things about our algorithm is that every time you do a scan it calibrates to you and your body, and so the precision actually goes up with the more scans that you do.
Philip Pape: 10:55
Oh, the internal precision for you. Yeah, okay, the internal precision of the algorithm.
Jason Moore: 10:59
That's right, and so the other thing that that does is allows you to start washing out things like water weight fluctuations, and so the other thing that that does is allows you to start washing out things like water weight fluctuations, and so even DEXA is sensitive to changes in water and bioimpedance and these other technologies are as well, and by being able to do the scans frequently over time, we actually can isolate out those variables and get even more accurate with the numbers.
Philip Pape: 11:23
Oh man, let's dig into that because you got ahead of my next question, which was ahead of my notes. Conditions like fluid, right, because that's the big thing. I tell people if they're going to get a DEXA. Try to replicate exactly what you did same time of day, like before you drink and eat all this fun stuff. You're saying because of your own frequency of data collection, it can smooth those out. Is that like so? If I did it in the morning one day, afternoon, the other day after eating a bunch?
Jason Moore: 11:46
you know, fat loss versus muscle gain it can account for that I mean, so we would still recommend that you try to do it in a consistent way, but the short answer is that, yes, at least better than alternatives can, right, and so you know that's you're hitting on.
Jason Moore: 12:01
A really important point is that a lot of people like, let's say, if you're a member of a gym or you know something like that, you go in and you do a workout and then you're like, oh, I guess I'll do a body scan while I'm here, and it's just like completely random what the state of your body might be.
Jason Moore: 12:16
You may be super dehydrated or you may be more hydrated if you've been chugging water the whole time you were working out, and then it depends what you ate and when the last time you ate was and all of these other factors. So what we find is that, even if there are facilities in a gym to do this, people end up liking doing it at home because it's just easier to be consistent and so you can like. The average that people do for us is they measure once a week, and so it's like a Sunday morning kind of routine or something. You get up, you do your scan before you do other things. You know you can like take a sip of water. It's not, it's not going to be that sensitive, but and then, yeah, and so you can create that consistency a little bit easier if you're able to just do it wherever you are with your phone.
Philip Pape: 13:02
And there's no special suit required, like one of your competitors.
Jason Moore: 13:05
No special suit.
Philip Pape: 13:05
No yeah that's I have that, I have that, and I'm like it's annoying to have to put that on, even though it's cool. Yeah, yeah.
Jason Moore: 13:11
And it's yeah, it's interesting, I think it's clever and I think all of these things are just good for the consumer to have options and thing that works for you. And, honestly, I think you also hit on a really important point at the beginning of this question, which is that as you track over time, the direction matters even more, unless you're in an absolute where that's at one of the extremes right. So if you're like extremely obese, for example, then yes, that's very important to know and you probably already know that if you're in that state, and then the trend away from that state is really where the magic starts to happen.
Philip Pape: 13:52
Cool, all right. So we know about or we, I should say the general public generally when I talk to them, knows about lean mass versus fat mass and how lean mass is comprised of fluid and glycogen, as well as organs and bone tissue and muscle Muscle. We can't forget muscle and that you're trying to reduce your overall body fat and that alone is going to correlate very highly with health and your physique. But there's other things you measure, and that's what I want to get into how they measure them for one, because I'm very curious, whatever you're able to reveal, but the AG ratio, the distribution, visceral fat, you know. Maybe give us a hierarchy of each of these. And then what's most important and why should we care about these?
Jason Moore: 14:38
Yeah, yeah, I mean, I think, like you hit on, like knowing your lean mass and your lean mass index, which is basically indexed against your height, these are really critical things, you know. I think Dr Gabrielle Lyon she's kind of says we have a sarcopenia problem, you know, not an obesity problem, and it's basically that muscle especially is just this precious metabolic tissue that does so many beneficial things for the body and for your brain function and your longevity. So that's a critical one that we obviously provide. You know, over time, if you were to measure changes in lean mass which you said includes water, organs, bones and then of course muscle and other things really over time, the thing that changes muscle and other things really over time, the thing that changes that you can change the most is muscle, right, and so water is what you see changing day to day.
Jason Moore: 15:31
You know, if people are measuring their body weight on a scale and they're like I lost five pounds yesterday and then I gained it all back the next day, it's like no, that was just water, right, you know for the most part. And but then over the longer periods of time, you know that noise kind of washes out and muscle is really the thing that is the primary driver of change in lean mass. Hopefully you're not. You know decreasing and increasing bone weight that much. It's very light compared to the muscle tissue. So that's one.
Philip Pape: 16:00
Can we actually interrupt on that one? Because people who really nerd out on this stuff and I actually came up with my own spreadsheet for this about a year ago, trying to infer the actual muscle because the skeletal muscle there's no way to do it and maybe you're going to correct me if I'm wrong other than to say, okay, studies have determined it's roughly this percentage and now you can infer against how you gain or lose lean body mass and try to, like you know, based on your wrist size. There's like some other interesting factors that go into trying to estimate and at the end of the day, you kind of don't care really, because what matters is the lean mass changes, your fat mass changing. But what are your thoughts on that, on like skeletal muscle itself and measuring that?
Jason Moore: 16:41
Yeah.
Jason Moore: 16:41
So it's a great question, and different companies who create measurement tools have kind of their proprietary formula, so to speak, that they claim is like better than anything else out there, and we have formulas internally that we also use, that we start always from the scientific research, and so most of the time the hard part for us is getting all the sensing algorithms working, and that's where our secret sauce is.
Jason Moore: 17:04
But then, when it comes to calculating changes in the physiology, we try to stay as close as we can to the scientific literature, and so you know, like you did, probably as your starting point for your spreadsheet, and but then from there it's exactly the mentality that we have is, again, it comes back to then the changes over time, Right. That we have is, again, it comes back to then the changes over time, right. And so, again, making it so that you can measure more frequently allows us to start to isolate out that kind of what is a normal, let's say, like a standard deviation for your daily weight fluctuation, right, as a very simplistic kind of way of describing changes in water Fluid.
Philip Pape: 17:42
Yeah, yeah, that's great.
Jason Moore: 17:43
Exactly so. That allows us to establish a baseline and understand like what your coefficient of variation is on changes in fluid, and then from there we can start to see the macro level trend occurring. That is more likely. There's just a higher probability that that's changing skeletal muscle actually.
Philip Pape: 18:03
Okay, and a tangent off. The tangent, before we get back to the list of things, is different phases, right? So we talk a lot about periodization. You get a muscle gain phase or fat loss phase, and in a muscle gain phase you just have a lot more gut content, a lot more carb consumption, a lot more glycogen in your muscle mass and your liver and everything, and then the opposite direction. So can you account for that? Is there a way for the user to input data on that, or do you just again the weekly? Just will work it out over time.
Jason Moore: 18:30
It's getting more and more sophisticated. The weekly kind of works itself out over time. But you know, another example of that is like going on or off of creatine, for example, right. So you know, right now, just to be transparent, that will pretty much count as a boost to your lean mass or your muscle when you cycle on to creatine, if you were not using it previously. Now, the good news is is, again, you'll know when you do that and we provide some ways that you 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're handling it right now. But we're always trying to get more sophisticated with those things. But it is tricky and to your point, from a practical perspective, at the end of the day, what we're really needing is to know that our behaviors are translating to a positive trajectory, and so, yeah, we're dialing that in more and more.
Philip Pape: 19:25
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 my clients use it. I talk about it all the time because they have a similar philosophy of with their expenditure algorithm, of trying to smooth it out, avoid overcorrection, handle all these transitions and handle discrete things that lifters are doing, like creatine, that you can really point out and that is a big one, because that is a source of frustration for people. I say look, expect anywhere from two to like five or six pounds of you just don't know. Some people are over-responders and they're so over-responding that like it takes a month or two to work itself out and then it looks like you're burning way fewer calories and, like you said, it looks like you have all this extra lean mass. That's just fluid, so it's good to be aware of that. So back to the hierarchy. So you just talked about lean mass versus fat mass. What's next, or what's the next level down?
Jason Moore: 20:15
Yeah, so then you can get really really deep on distribution of fat and muscle around 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 care a little bit about more of the distribution of that muscle, depending on the audience. I mean that I would say for most people doesn't matter until you're at the more advanced stages of muscle development, matter, until you're at, like, the more advanced stages of muscle development, and that for most 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 your priorities looks? Are your priorities health and longevity?
Jason Moore: 21:00
For, again, most people the overlap is very high between those things, but then at some point, you know, they do diverge a bit. What we really care about from a health perspective is visceral adipose tissue, which is basically the fat that's around the organs and in your abdominal region. That is the really big, you know, red flag for health and longevity and health outcomes, and it also isn't helpful for aesthetics either. It tends to be a really high correlation between visceral adipose tissue and body shapes that people don't like.
Philip Pape: 21:34
Yes, yes, yeah, exactly, Muffin top, menopause, belly beer, gut, all the phrases we know right, yes, yes, exactly.
Jason Moore: 21:42
And so for us we offer this thing called android-gynoid ratio and android fat, and gynoid fat specifically, can be measured. But this is sort of it's not a direct measure of visceral adipose tissue, because what it is is android is the trunk, essentially how much fat are you carrying in the trunk and gynoid is the lower, like the hips, in the lower limb region of the body. And this is there's, these ratios like you just mentioned, like neck, waist and hips, for example, or waist to hip ratio, these things that are kind of nice, simple markers that are very useful in fact, if no one's beyond the scale, if somebody is like wants a really easy thing to start with, if you have a tape measure, you can start measuring your waist and your hips and your neck, right, and it doesn't cost anything. You can just and you can start to get an idea of whether or not you're moving in the right direction. But in any case, we measure those things you know, automatically now, and the-gynoid ratio is basically the best proxy indicator of visceral adipose tissue other than directly measuring the visceral adipose tissue. The correlation in the research is anywhere from like 0.7 to 0.95, depending on kind of the population and the measurement methods, but in any case, it's a very high correlation between the android-gynoid ratio and the visceral adipose tissue number. So again, this kind of comes back to what we just said about body shapes that you don't want typically correlate with high visceral adipose tissue or fat around those organs.
Jason Moore: 23:26
With high visceral adipose tissue or fat around those organs, and it may not, as a percentage, be that much of your body fat, right? So the visceral adipose tissue as a percentage of your total body fat may not be that much, but it's the dangerous stuff. And so you know. Regular exercise, lots of walking, anti-inflammatory lifestyle whether that's getting enough recovery and sleep, managing stress, having eating high quality foods with lots of nutritious choices versus kind of more, like you know, rich processed foods All of these things not only help us feel more energetic and like look better, but those are the things that happen to also improve visceral adipose tissue as well.
Jason Moore: 24:06
So, yeah, we just try to help make that easy for people to measure. We are not, so the camera can't see inside your body and that's why we need to be very like, clear about what we're measuring right. And similarly, bioimpedance and other tools don't directly measure visceral adipose tissue unless you were to place the measurement tools directly on that area of the body right, and x-rays can see inside right Like a dex as an x-ray, and so all of these tools are estimating, and as are we, but that's how we present it to, let's say, the end user, because really it's a win-win. If you're just improving your Android gynoid ratio, it's something you can measure now, whenever you want, using our app, and then you'll get an indication not only of the aesthetic goal but, if you're likely, improving the visceral adipose tissue as well.
Philip Pape: 25:02
Yeah, the fact that it presents itself visually obviously seems to be a plus in terms of being able to measure it. When you're taking an image and you're sensing these things Because I was going to ask you about that it's like how do you infer fat mass? You said you have all this validated kind of reverse engineered data Then you must be correlating that with the outward appearance of someone effectively. Is that a simple way to put it?
Jason Moore: 25:25
Yes, yeah, and we so we require you to get in your underwear usually, or, or, if you, certain fitness attire works to like sports bra and like tight fitted biking shorts or something like that. But yeah, it's really amazing what machine learning and computer vision can do and what it can see that the human eye can't really see. And because there's different gradients on the skin, you know, depending on this is another thing too that we've had to develop, and why it's so expensive to develop this stuff is changes in lighting actually can change your appearance quite a lot, right, and so we tell people you've got to have adequate lighting. You can't do our measurement in the dark, but the cool thing is is that once you reach a critical mass of volunteers and training data and ground truth data, it actually can account for the changes in lighting. Interesting.
Philip Pape: 26:17
Like self-driving cars kind of that's what I'm thinking of, how they can handle just about any environment. Yeah, Okay.
Jason Moore: 26:23
Yeah, and so the cool thing too is we can even detect, like, okay, last time that you did a scan you were standing six feet from the phone and this time you're standing six and a half feet from the phone. We don't just assume that you got shorter since the last time that you did a scan. Right, we can actually detect that and account for that and correct for that.
Philip Pape: 26:45
You know, as we were talking, I was rudely Googling something that came to mind as you were mentioning visceral fat, because there's something called the body roundness index. You must be familiar with this Body roundness index, which calculates visceral fat based on gender, ethnicity, age, height, weight, waist, hips, and it tries to determine your adipose tissue. And I don't know how validated it is, but it sounds similar, right? It's using again outward measures and I suspect you have a lot more fidelity because you're able to use more. Is that the case? I guess, when you're measuring fat mass and visceral fat and everything, have you found that there's a kind of complex web of data points and it's like a human wouldn't really be able to comprehend it because the machine learning has gotten to that point, or can it be kind of proxied and simplified in some way? To admit, that's pretty good.
Jason Moore: 27:33
Yeah. So I mean like to your point. Yes, you can start like it's kind of like we were saying earlier where you can like, as a coach, you can look at a client and see, like, generally speaking, I know they're in this range, right, and you may be plus or minus some amount, and as you learn more about them you may get a little bit more accurate. The body roundness index is intended to be a replacement or an improvement to BMI, and so body mass index is essentially just your weight and your height compared, right, and essentially what you know. Let's say. Let's take the military, for example. The military used to exclude people from qualification for duty based on BMI, so you could have a really strong individual that's got high muscle density be excluded from, you know, qualification for duty.
Jason Moore: 28:21
The very people you want in the military big, strong guys from qualification for duty, the very people 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 to that. It's something that you can measure with low tech, basically, and get a much better indication directionally of somebody's health or their metabolic health and ability, and so it's better predictor for a lot of different risks. But it still is not the same as doing a DEXA scan or understanding your visceral adipose tissue a little bit more closely or, in our case, your android-gynoid ratio. That is the best estimate of that.
Philip Pape: 29:02
Cool. Yeah, I knew you would know about that. It's just one of those new things on the scene because people talk about BMI a lot and how awful it is, even though it still has some validity at the extremes.
Jason Moore: 29:12
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 you look at yourself and you're like I'm jacked, then you know.
Philip Pape: 29:23
That's all my clients, man, that's all my clients. No, you use your intuition in that scenario right.
Jason Moore: 29:29
Otherwise, the BMI might be telling you something that you know there's something to improve there.
Philip Pape: 29:34
Yeah, no, that's funny. You mentioned that Cause. Yeah, but most people I know who have been lifting a while, they do get to that point where they're carrying extra weight on purpose and they have more muscle. So it's like you're in that easily in that what looks like obese category and it's like don't worry about it. The apple and pear shape discussion that we've talked about over the years is that relevant here? Is that related to the AG ratio as well?
Jason Moore: 29:56
Yes, so if you have a higher android-gynoid ratio, which means the android number is higher typically than the, gynoid one yeah, so that's that apple shape.
Jason Moore: 30:06
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 a little bit more of an apple shape. Just, you know, stereotypically carry fat more around the midsection and women, more stereotypically, carry it more in the hips, the butt, the thighs, etc. And have more of the midsection, and women, more stereotypically, carry it more in the hips, the butt, the thighs, et cetera, and have more of that pear shape. And so you know, generally speaking it's you can get really into the weeds for any individual right? Yeah, makes sense, but those are kind of the general ranges.
Philip Pape: 30:40
So if it's top to bottom and that's the ratio, do we care about a number on a scale or do we care about change again?
Jason Moore: 30:48
really strong, especially like. Take the difference between a bodybuilder and like a strong man. Right and strong men, competitors tend to have very thick trunks but it's like huge amounts of muscle, you know, whereas a bodybuilder can have tons of muscle but have a pretty narrow waist, and a strong man would then have a higher AG ratio versus the bodybuilder, and it's difficult to say in those extreme cases.
Jason Moore: 31:29
I guess which one is more or less healthy? Right, Right, Because it kind of just depends. If they're recreationally pursuing those sports, then they both might be perfectly healthy, but at some point they're both sacrificing health to pretty high degrees in chase of performance. And so, in any case, if you're looking at the AG ratio, the reference ranges are based on, like the mean population norms, and so you don't want to be out of range most of the time, unless again you're super jacked and you know it Got it. So yeah, high AG ratio generally means more adipose tissue, more visceral adipose tissue in the midsection and again, isolating out fat from muscle as well, because in that strongman bodybuilder example a lot of that was lean mass. But we're wanting to look at fat distribution really.
Philip Pape: 32:30
Okay, yeah, no, that's fascinating stuff. I'm just curious behind the scenes what it all means, because I think of how we're all so different and I've always said I have a bigger butt than the average man. Most guys have flat butts and I have a big one, so my AG ratio is probably going to be a little bit wonky to start, but then it matters how it changes over time. Measurement a couple times I did want to address that because when it comes to measuring lots of different things, we have different scales. We measure right From daily to weekly to monthly to quarterly, depending on what it is Usually like food and weight. I generally recommend people do daily if they're trying to be precise about it, and then they use averages and trends. I think you mentioned weekly on Sundays, which also sounds like pretty much aligns with general advice when it comes to body measurements just basic metrics, but why wouldn't you do it more frequently or less frequently than that?
Jason Moore: 33:20
So you can, and that's just kind of where the average, where people land, and so some people do it daily and then kind of, you know, again, we just strongly caution. This this all kind of basically comes back to is we don't, since we're not selling a device and we don't have all these costs tied to that. Our goal is to not get you to just do measurements for the sake of doing measurements, so to speak. Sure that we're selling outcomes, right. So basically it's like the measurement tool is just one thing that is important in getting you to the outcome that you're looking for, and so that's important context that we can dig into. But then the other piece is the mindset of the individual doing the measurements, right. So if you really want to be an optimizer, then you could do these every day and you will just know and we will try to educate you as well that those daily fluctuations that you may see are a little bit more tied to you know, water changes and things like that. And then we're trying to look at the macro trend a little bit more there, Right? And and then again, you could do it less frequently once a month, once a quarter, People who do DEXA scans usually are doing them, maybe once a year or maybe twice a year or something like that.
Jason Moore: 34:40
The problem is, there is again. It's like doing a blood test once a year. That's great. It's better than never doing a blood test. But certain markers, even in blood biomarkers, heavily depend upon what you ate the day before. Yes, yes, yes.
Stephanie: 34:56
The most value that I got from this was the fact that I had someone that I could talk to about anything and that there was going to be no judgment. It was just well, here are your goals, here's the best way that you're going to achieve it, and then let's work together to help you feel inspired and motivated to do that and there's a lot of people out there trying to be coaches and not all of them have done the work and also just be a genuine person that is positive and coming from the heart in terms of wanting to help, and Philip really embodied all of those qualities. I would recommend him to just about anyone that's looking to achieve goals in that realm of their nutrition and building new habits that you only did two measurements.
Jason Moore: 35:57
Well then, if you're on like a down slope on one measurement and you're on an upslope on the other measurement, you might be like, oh, my weight hasn't changed at all, or something, when in reality your mean weight over the course of, let's say, a couple weeks, that baseline might be 10 pounds different actually. And so what we're trying to do is kind of zero in on what's a frequency that allows us to make decisions and make informed choices but not overwhelm ourselves. You know, depending on what our mindset is or capacity for isolating out variables.
Philip Pape: 36:26
Yes, and that's a really important point, is the psychological and the fatigue that comes along with any of these systems. I mean, same thing goes with food and tracking and everything else. It's like that balance between precision and going crazy, like you know. Where's the fine point? I think it's a fascinating topic because in the scale weight world right there have been a lot of studies on this. There's a fascinating one that compared five days, compared zero, like once a week, to five days a week, to seven days a week, and found that the seven days a week tracking had the best adherence and sustainability results.
Philip Pape: 37:02
And I mentioned macro factor before and they use a exponential 20 day exponential moving average for weight, which is like okay, over a three week period. That's long enough to know that you've accounted for water weight fluctuations and because you're weighting the more recent measurements more heavily, that also gives you a good confidence that you're either going up or going down. So that's why I think it's fascinating with measurements, because I've never recommended more than once a week only because your body can't change that fast in terms of measurements. But when you have this level of precision you guys have, I wonder if that changes the equation where, like if you don't mind doing it every day. Does that give you any sort of edge? Does it help the app? Does it help it learn about you and all that? Or is it kind of is there a sweet spot for people who are willing to do it more frequently? That's what I'm asking.
Jason Moore: 37:48
Yeah, I would put it more in the optimization camp to do that. So yes, the algorithm gets better if you do it frequently that way, but not that much better. And also from a practical decision-making point of view, you know you're probably not making big changes in your. So it's like measuring like sleep or HRV or something like that. You can measure that on a daily basis and look at these kind of weighted moving averages and things and say like, oh, I got a little bit of a light sleep. I'm not really going to change my whole routine for the day based on that, but if you have a major red flag come up you might right. That doesn't happen typically with body composition and so, unless you're just extremely dehydrated. So that is one. Actually let's part the curtain, I guess, a little bit on.
Jason Moore: 38:37
One reason why some of our members have started to measure more frequently is as we start isolating out the changes in fluid. That does give us a little bit of a window into hydration, and so we're kind of studying that still, because I think it would be kind of easy to over extrapolate that. But in any case there might be some guidance that would be useful on how much to prioritize hydration or electrolyte balance or things like that. Based on some of these like more daily changes or short term changes. But yeah, from body composition point of view, to your point, once a week is great. You know, at the end of the week you can see some of the change happening and start to have that like directional trend forming, even after just one week, and start to make choices of like are my protein targets or are my macros or are my calorie targets, kind of keeping me in the direction or range that I want to go in. Right, Fascinating.
Philip Pape: 39:37
You keep bringing up topics that I would love to go down in the future, like the hydration because immediately my mind goes to the amount of water you're carrying at any given moment isn't as simple as how much hydration you've had right. It's also what you've eaten and how much sodium you've had. And menstrual cycle for women and inflammation from your heavy leg day yesterday. It's insane how much effects fluid containing your body and you might drink the exact same amount day to day. So that's fascinating. Hrv you mentioned it, so you opened the door to that. Because you guys measure HRV and I know you're working on VO2 max or inferring VO2 max. Tell us about those. Let's start with HRV VO2max or inferring VO2max.
Jason Moore: 40:15
Tell us about those. Let's start with HRV. Yeah, so I mean overall, our mission is basically to take meaningful data points that are used in lab settings and to break down the barriers so that people can just measure them, while keeping the quality high. Hrv is actually where our company spent. You know, basically the first half of our existence was focused on HRV, and so we have a long history with it.
Jason Moore: 40:35
We worked with the polar chest straps, the Garmin chest straps and using Bluetooth and when that was innovative a decade ago. And then we created our own hardware, a medical grade sensor that we distributed to 80 countries around the world and then discovered that we could do countries around the world and then discovered that we could do again kind of cannibalized ourselves in that regard by saying we had all this ground truth data coming from validated sensors like chest straps and ECG based sensors, and we could use that data to train models, to then detect heart rate, hrv and respiration using just the camera of the phone. And so we have that technology now it's in the Sprint app as well, and you can track resting, heart rate, hrv and respiration just by touching your fingertip to the camera on the back of your phone and doing heart rate that way is not actually that novel. There's a lot of companies that have been looking at that and it's a similar technology that wearables use. So you know, ppg is this whole rabbit hole we could talk about.
Jason Moore: 41:40
But essentially wearables are shining light into your skin and as the blood flows through that area of the skin, the color and different features of that camera signal change as the blood flows through and different features of that camera signal change as blood flows through, and you can calculate what's called pulse, wave volume and things like that from that data. So similarly, the camera can do that too. If you open the camera app, you don't even need a different app to see this. But if you open the camera app on your phone and just cover the camera with your fingertip, the whole camera will turn red and as light shines through your finger you have to be in a bright room or whatever, right?
Philip Pape: 42:18
Which I am, and I'm doing it yes.
Jason Moore: 42:21
And so some people, if you look closely enough, can actually see their pulse in that in the camera, and so it's pretty cool, I did it.
Philip Pape: 42:28
Right now, guys, I'm seeing it like yeah, yeah, oh man, that's cool, Isn't that cool, right?
Jason Moore: 42:34
So that you know again, you could sit there and count your pulse like on a clock and come up with your heart rate from that number. But a heart rate variability needs a much higher degree of accuracy and granularity, precision. Hrv is essentially calculating the time in between, the variation in time in between each heartbeat, and it's measured in milliseconds. So you need really more precision than the human eye can offer to measure HRV. But the really fascinating thing is once you get HRV and you have resting heart rate, of course, and then respiration can be extrapolated from heart rate and HRV. Respiration can be extrapolated from heart rate and HRV because one of the primary contributors to changes in your HRV is your respiration. It's called respiratory sinus arrhythmia and we could go in this whole rabbit hole for that. But as you breathe in, your heart rate increases and as you breathe out, your heart rate decreases. Unless you're exerting yourself heavily, then it's kind of imperceptible, basically. But in any case, these three things give you a lot of information.
Jason Moore: 43:42
People will typically do this first 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 into algorithms that we had developed over the last 10 years that allow you to get that readiness and recovery scoring. Some people, who might have a whoop or an aura ring, you know, might be used to having a readiness score or recovery score. That's something that we were some of the pioneers of, but we went in a different direction. Instead of doing the continuous monitoring through a wearable, these are point-in-time measurements that you don't need a wearable for and I have just as much utility, and we have a ton of scientific studies now that we can point to predicting injury, predicting recovery, predicting inflammatory conditions and things like that. Just doing these morning spot check-ins, that is awesome.
Philip Pape: 44:35
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 of computing and computers and just the space program and everything that we have since then, just to be able to do this is awesome. Look, I know we only have a couple of minutes. Do you have like a few minutes past the hour just to wrap up? Okay, cause the VO two max. I'm really curious about that.
Philip Pape: 44:53
I did my first ever, my only so far VO two max in the lab test, which is miserable for anybody, especially if you don't like cardio, which I don't, like everybody knows. Like I love walking and sprinting, but not going all out for until you die on a on a on a treadmill, which is what they do, guys. It's tough and it was. You know I was carrying excess weight because I was at the top of a bulking phase which then slams the number down, unfortunately, and then I don't have very, I'll say, as high cardiovascular fitness as I would like to have and can work on it. So VO2 max we see it as somewhat of a gold standard of cardiovascular fitness. How do you guys measure? How do you guys plan to measure that?
Philip Pape: 45:34
Or infer it, I guess.
Jason Moore: 45:36
The underlying data is tied to this measuring resting, heart rate, HRV and respiration and so, with some other context pulling in, things like activity level, exercise and some performance stats can enhance the accuracy of the estimate. But even with just those daily physiological measurements, there's actually some pretty good literature now showing that it's essentially looking at the correlation between those and VO2 max. And so we have seen just look, digging into the data, you know we have seen some ways to kind of refine that a little bit more to where we feel comfortable. We tend to have a pretty high bar of like, like you said, like somebody might put out like a booty score or something like that, and that's, that's cool. It talks to people like.
Jason Moore: 46:21
Some people are like oh, I want my booty score to go up or down, I don't know, I'm not sure, but in any case we tend to kind of err on the side of like. Is this related to something that's valid? You know that we've seen proof for, and so VO2 max estimates from these kind of longitudinal cardio respiratory markers are something that we're really excited about because we're getting pretty close on that and from a longevity perspective, or even a performance perspective for many sports, you know, strength, VO2 max, like these are like top of the list things that people should be caring about. From a health, it's like if you're looking for looks, you're looking for health or you're looking for performance, you know. Vo2 max, strength, mobility, balance, muscle mass these are the top of the list.
Philip Pape: 47:12
Okay, and that actually brings up one quick question then, with muscle mass, are you able to give somebody sort of a physique score symmetry, something like that, or is that coming in the future?
Jason Moore: 47:23
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, even somebody like you and I, I mean, I don't know, maybe we're pretty off the charts when it comes to our appetite for digging into the data, but 95 to 99% of people are like I want to 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 of thing, Right, and so we're always looking for ways to make it easier. Again, that booty score is a good example of like some people are, just like I. Just that's all I want to know is, is my booty going to get more peach perky or you know whatever? And so yes is the short answer, Love it.
Philip Pape: 48:12
Yeah, I can see the skies are living on this, especially the way technology is going. I'm sure you guys' capability is just going to continue to increase. All right, so as we wrap up, is there anything else you wish I'd asked, or anything about what you guys are doing with the population of Spren users that we should know about that? I haven't asked because I don't know to ask it Anything like that.
Jason Moore: 48:32
Yeah Well, I'd mentioned that we're selling outcomes and that people kind of scratch their head a little when I say this.
Jason Moore: 48:39
But these measurement tools and the data that you get out of them is just this tiny slice of the pie when it comes to the overall health and wellness journey or the performance journey, and I obviously think it's an important slice because I'm devoting my life to it journey, and I obviously think it's an important slice because I'm devoting my life to it.
Jason Moore: 48:56
But all the ways that you translate that into action for your nutrition, for your exercise, 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 data should just be in support of all of that.
Jason Moore: 49:13
And so the first question that we always get when people do our body scans and other things is like wow, I did not know this about myself, now, how do I improve it? Right, and so we're not the experts at everything in the entire world. We can guide you generally in the right direction. But we also now partner with coaches and experts and fitness and wellness facilities and we're excited about that because these brands appreciate these brands and these experts appreciate our scientific credibility and our proof points and quality, but then they can also help bring a lot of the expertise and the guidance and the individual services that people need to actually get the results. So I just wanted to share that, because that's how we see ourselves fitting into the universe, and actively. That's a big part of the platform that we're expanding right now.
Philip Pape: 50:10
Well then, we're aligned because I'll let you in on a secret I only like to have people on the show who are going to teach me something new, that amplify a slice of that pie that we haven't covered too much and that the listener can learn something new. And then the rest of this podcast 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 and implement the information. But I love informed decision making and that's what we're trying to do here. I appreciate you, I appreciate your genuine passion for this. I can tell you know there's a lot of different types of folks in the world and I can tell you you're in this and it's important and you want to help people. So thank you so much, jason, for the conversation. This is a lot of fun. I could keep going, but it's and Waits. Where can folks find you? Where do you want to send them to?
Jason Moore: 50:53
Yeah, thanks Sprencom S-P-R-E-N, or you can search for Spren in the app store. We're there as well, so we love hearing from people. So shoot us a message if you've learned something or you have feedback for us or if we can improve in any way. You can find us a little bit on socials. I'm going to be honest and say that we're not the best at keeping like a big social media presence or anything, I like you even more, man, since you said that, because I'm not a huge fan of social either.
Jason Moore: 51:21
Yeah, I mean, it's a great tool for some things, but people also scratch their head when I say over a million people have actually used our tools, but we only have a few thousand followers on social because we're just not that active there. But we only have a few thousand followers on social because we're just not that active there. But we learn genuinely a lot from the community and that's one of our secrets. That's not so secret, but anyways, thank you, philip. This has been awesome and yeah, I can tell by the way you lead all of this, that there's a lot of people in your audience we could learn from as well, so that's exciting.
Philip Pape: 51:51
I love it. Yeah, I'm going to be digging into this more. We're going to we're going to stay in touch, because it's pretty cool when things like this come up, and I wasn't really aware of it, which is crazy, 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 in my community. And again, thanks, jason, for coming on.
Jason Moore: 52:08
Thanks, Bye.
