Muscle for Life with Mike Matthews - Grant Tinsley on the Science of Measuring Your Body Fat
Episode Date: August 3, 2022Are all body fat scales equally inaccurate? Are some accurate enough to actually be useful when tracking our body composition? That’s what Dr. Grant Tinsley wanted to test in the latest study out of... his lab, and he’s discussing the surprising results in this interview. Many fitness enthusiasts want to track their body fat levels and body composition to keep tabs on their progress and ensure their training and diet are on the right track. So it’s no surprise that many have been tempted to buy relatively inexpensive body fat scales and home devices that claim they can assess your body composition just by stepping on a scale or holding special electrodes. I’ve never recommended these devices due to their inaccuracy, but are some bio-electrical impedance analysis (BIA) devices good enough to actually help people keep track of their body composition? That’s exactly what Dr. Grant Tinsley wanted to find out and what he and his team put to the test in their latest study. Grant and his colleagues bought some of the most popular BIA devices off of Amazon and compared their results with current gold-standard methods and expensive devices to determine how useful these tools really are. So, how accurate are BIA body fat scales, why do some work better than others, can they actually be useful for tracking your body composition, and how can you get consistent and accurate readings with them? You’re going to find out in this podcast. In case you’re not familiar with Grant, he’s an Associate Professor at Texas Tech University, the Director of the Energy Balance & Body Composition Laboratory, and is a Certified Strength and Conditioning Specialist (CSCS) and Certified Sports Nutritionist (CISSN). He has over 150 peer-reviewed journal articles and abstracts, with his major research interests being sports nutrition strategies, body composition assessment techniques, and intermittent fasting in active populations. So, he’s the perfect guest to talk all about body composition measurement and discuss his new research on BIA devices. Press play to listen to our discussion! --- Timestamps: 0:00 - Try Pulse today! Go to https://buylegion.com/pulse and use coupon code MUSCLE to save 20% or get double reward points! 4:30 - What is body composition and how accurately do home devices assess that? 21:09 - Do you recommend these devices? 30:17 - Did you come across any useful devices doing your experiments? 35:04 - What are other methods to accurately calculate body composition at home? 46:23 - What is three dimensional optimal imaging? 47:37 - What are your thoughts on the expensive machines found at gyms? 51:01 - What is the accuracy of the army body fat equation? 56:31 - What are some controlled factors we can practice for consistent readings? 59:08 - Where can we find you and your work? --- Mentioned on the show: Try Pulse today! Go to https://buylegion.com/pulse and use coupon code MUSCLE to save 20% or get double reward points! Grant’s Instagram: https://www.instagram.com/grant_tinsley_phd Grant’s Website: www.granttinsley.com Pre-registered study: https://clinicaltrials.gov/ct2/show/NCT05026697
Transcript
Discussion (0)
Hello and welcome to another episode of Muscle for Life. I am Mike Matthews. Thank you for
joining me today to learn about measuring your body fat percentage, measuring your body
composition. This is a topic I have been writing and speaking about intermittently now for many years, but that I continue to get asked about because it's just
one of those perennial topics, I suppose. And to deliver some content that is a little bit
different than the stuff that I have produced on measuring body composition in the past,
I invited my buddy, Dr. Grant Hinsley to come on
the show and talk about the good, bad and ugly in measuring body composition. And in this interview,
Grant talks about how effective all of the most popular devices and methods are. And you know,
I was pleasantly surprised to learn that there are some consumer
grade devices that are pretty dang good at determining just how fat we are. And in case
you are not familiar with Grant, he is an assistant professor at Texas Tech University.
He is the director of the Energy Balance and Body Composition Laboratory, and he is a certified strength and conditioning specialist and certified sports nutritionist. Grant has over 150 peer
reviewed journal articles and abstracts with his major research interests being sports nutrition
strategies, body composition assessment techniques, and intermittent fasting in active populations.
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Hey Grant, welcome to my podcast. Thank you for taking the time to come educate us on body
composition. Absolutely. Thanks for having me. Yeah. And for people who are watching this on
YouTube, or I guess there's video on Spotify as well. It looks like I'm recording this with a
potato because I basically am. This is my laptop.
I think this laptop's like five years old.
It still works fine.
But the camera, this is what that camera looks like.
And my normal web camera, fancier one, doesn't want to work today.
So this is what we've got.
Anyway, we are here to talk about body composition.
I'm excited to have you on the show to talk about this because this is something that you and your lab specializes
in in your research. And I suppose where we could start is maybe just a quick definition of the term
body composition, just for people who aren't familiar. It's different than just body weight.
And then I'd love to hear about this study that I believe you said it's submitted. So it'll be, I think that's what you said, but
it's the work of it's complete on these by, I don't want to throw out terms people won't understand
yet, but on these devices like scales, handheld devices that you can just buy on Amazon and how
accurate are those really at assessing body composition? Yeah. So I'd love to dive into
all of that. As you mentioned, I think it's always good
to kind of get terminology straight. You know, in the fitness community, people usually think
something when they hear body composition, probably often they're picturing like a body fat percentage
or the percent of your weight that's body fat. And that is one of the variables we often look at.
But really from a broad perspective with body composition, we're just talking about how you
break up your body weight. So most people have this understanding that body weight as a metric is not the most
informative. Maybe you personally have been the same body weight at different times in your life,
but you've looked a lot different. You've felt a lot different. You've been able to perform
a lot different. So really body composition, just broad principle, how do we break up the body
at a simple level? Most of the methods we have access to, we'll be doing something like
trying to split all of our body mass into fat mass and fat-free mass, which would just
be everything else.
But we can build more advanced models.
We can look at things from more of an anatomical perspective where we look at true skeletal
muscle, adipose tissue, bone, things
like that. So it can get fairly complicated, especially in a research setting where we do
have access to devices that can sort of slice up the body in different ways, so to speak.
But in terms of consumers, as you mentioned, many of these simpler devices really are giving you a
body fat percentage, which again is just related to the amount of fat you have, fat mass, and the amount of fat-free mass you have.
So yeah, if you'd like, I'm happy to go ahead and dive in and elaborate a little bit more on our
body fat scale study. Yeah, that'd be great.
Yeah. So as you mentioned, we haven't quite submitted it. If we were recording this in
another week or two, it may be submitted, but we do have the research done. We're just finalizing a few parts of the manuscript. We have published a good chunk of this in abstract form at
a few conferences over the last year or so. From the outset, and I'll probably say her name again,
I want to give a huge shout out to a doctoral candidate in my lab, Madeline Siedler, who led
the day-to-day of this study and has been involved from day one. You know, we had conversations in my office
talking about this idea and she's done a fantastic job rolling with it. She's starting the third year
of her PhD here at Texas Tech. So from a big picture perspective, we were interested in taking
kind of some of the rigorous methods we use for body composition assessment in the lab,
but really producing results that would be more useful to
consumers, just people interested in fitness, even personal trainers or people trying to assess the
body composition of their clients. And, you know, as you know, Mike, one of the really popular
categories of body composition tools are these home body fat scales. So for anyone listening,
if you've seen these scales, they often have kind of like silver plates on them,
like little circles you step on.
Most of these scales are using a technology called bioelectrical impedance analysis.
And they're essentially passing very small, imperceptible electrical currents through
your body.
And the device essentially knows what it's injected into you in terms of electricity,
and then it measures what it receives back.
into you in terms of electricity, and then it measures what it receives back. And it uses that information along with quite a few assumptions to estimate things like the fluid content of your
body, and from there estimate your body fat percentage. So there's error involved in every
step of this process. But nonetheless, these are really popular devices. They're affordable. So in
the study that we're kind of starting to discuss now,
we looked at 15 different devices. 14 of these were consumer grade devices. We essentially went
to amazon.com, looked at some of the best selling home body fat scales because we wanted these
results to be applicable to a wide range of consumers. And with those scales, the price
ranged from about $24 up to $350, with the majority of those falling below $100. So a reasonable price point for a consumer who's really interested in this, or again, for, you know, someone like a trainer who doesn't may not have a large budget for body composition testing, but wants some device they can use with their clients.
wants some device they can use with their clients. As a side note, I've talked to others about this before, but one of the devices we use is one that you see kind of sitting around on the counter of,
you know, half the gyms in America. And that's the little handheld body fat device where you
grab it and you're just kind of like squeezing it as hard as you can. And you're like,
I think that was the first I've had of any of these devices or methods of assessing body
composition that I, that's the first I can remember at least. these devices or methods of assessing body composition that I,
that's the first I can remember at least. Yes. Yeah, no, it's, it seems to be a common
experience in the fitness realm that, you know, there's that one sitting on the counter and
I don't know, they use it with clients as they're beginning a personal training program or something
like that. So we did actually include that, that device. But from the big picture perspective,
we were looking at all these consumer grade devices. And the plan for this study was to bring in individuals, test them with all these devices,
and then also test them with our laboratory methods using our gold standard laboratory
method, which I'll describe in a moment, and essentially look at a few items.
One, at a single point in time, how accurate are these devices compared to our gold standard
method?
But then even more importantly, how can these devices track changes over time? So these individuals,
after we'd assessed them in the lab, left and kind of continued living their life for a few months.
And then we brought them back into the lab, repeated all the assessments, both the gold
standard and these other body fat scales. And we were able to really see how well these devices
could track changes over time. Because most people who have these scales, you know, they're assessing periodically
over time, maybe even more frequently than they should to see. And, you know, they're hoping to
see that body fat percentage number go down or that fat-free mass number go up. So just to get
into the study a little bit more, we essentially recruited healthy adult females and males.
we essentially recruited healthy adult females and males. We ended up with 73 individuals with a really even split between males and females. These were all generally healthy
individuals. We didn't require them all to be physically active because we wanted this to
kind of span the range of activity levels. So we had some individuals who were just,
you know, recreationally active. And we had some individuals who were higher level athletes. So we got a pretty wide range of body compositions and activity
levels represented in our sample. So prior to our first assessment of these individuals, we of
course, you know, screened them for some eligibility criteria. We had everyone abstain from exercise
and vigorous physical activity for at least 24 hours before they came in.
We had them fast from food and fluids.
We recommended a certain amount of fluid intake the night before.
We did all these control measures so that when they were poor after an overnight fast, we were fairly confident their body was, you know, rested, fasted.
There weren't any strange fluid disturbances, which is particularly important with this type of technology that relies on body fluids. So once we had them in the lab, we performed our gold
standard method, which is called a four compartment model. And really, we have to use multiple
different devices to build this model. So some people may be familiar with DEXA. DEXA, or dual
energy x-ray absorptiometry is one of those methods.
Another method we use is the BODPOD or air displacement plethysmography, which just gives
a view of the three-dimensional space the body takes up. We use the calibrated scale and we got
a body water measurement with a technology called bioimpedance spectroscopy, which uses mathematical modeling
to estimate body fluids. So we have all these kind of complicated research grade devices that
we assess individuals with, and we kind of pull different variables from each of those, put them
into this validated equation, and we get what's called our four compartment model body fat
percentage. So that was our gold standard. So we assessed that. And
in the same visit, in a randomized order, we assessed individuals on all 15 of these
bioimpedance devices. So 10 of these were what we call foot-to-foot scales. So these are the
ones that look just like a body weight scale, and they have those typically silver electrodes on the
surface. Someone steps on there. And in addition to taking
a body mass measurement, again, these scales are injecting a little electrical current,
quantifying what they receive back, and then plugging that information typically into some
type of black box proprietary algorithm and spitting out the body fat percentage.
So we had 10 of those that were foot to foot. We had four that were hand to foot, so devices that had both electrodes that were in contact
with your feet and your hands.
So these would often have a little pull-out handle where individuals are grasping onto
this handle in addition to standing on the platform.
And the idea here is that the current is being injected not only into the feet and kind of
completing that electrical circuit through the lower body, but also through the arms. And the idea is that you can get a better picture of the total body
here. And then the last device, the one we were just joking about was the little handheld device
looks almost like an old, I don't know, some type of video game controller or steering wheel or
something like that. So we had these 15 devices. We had everyone assessed by those devices two times.
So back to back to just get a simple test, retest reliability, which is looking at how
much can a value vary if someone gets on the scale, steps off and steps back on.
And if you've ever looked at Amazon reviews for any of these products, or if you've messed
around with them yourself, there are some disgruntled users who will say like, you know,
I stepped on, I was 24% body fat. I stepped off and I stepped back on and I was 26% body fat. You know,
they're disgruntled about that. So it is an important point to consider just the test,
retest reliability. So that was one component. Again, the second component was just at this
one point in time at this first visit, how accurate was each device compared to our gold
standard. And then after this visit, again, we let people leave the lab.
We did not control what they did, but they had the option to return 12 to 16 weeks later.
And we had 37 individuals who agreed to come back.
So they came back, they were tested.
We didn't know for sure what we'd get, but it actually turned out really nicely.
Essentially, it was an almost perfect split.
Half the individuals gained body fat by our gold standard method, half lost body fat,
which is really what we wanted to see.
We just wanted the natural variability in body composition.
You know, people are changing lifestyle, you know, exercise, different stress levels.
Some of these were college students.
We just wanted natural variability to take place.
And that's what we saw.
So they came back in, we performed all the assessments again, and then we were able to
look at the actual change. So we could look at it and say like, okay, for this individual,
if our gold standard method said they gained 2% body fat, what do all these other methods
say happened? So I'll pause there for a second. That's kind of the data collection.
And there were a lot of results. I'll try to distill it down. But do you have any
questions or comments at this point?
Kind of now that we've discussed the setup of the study?
No, that was a great introduction to the results
and just a comment that I know
just from many people reaching out to me.
So the two questions I've been asked the most
with these BIA devices are,
one, are they accurate? And then if they're not, are they at least consistently inaccurate? Okay, fine. If they're not perfectly accurate, then maybe an individual reading doesn't mean that much. Maybe you can understand it more as a range, but if they were at least consistently
inaccurate, then if you wanted to watch it, you could look for trends, just how you could watch
your body weight and pay attention to trends. But of course, if they are just inconsistently
inaccurate, then that would make them just useless. Like why even bother, right?
Absolutely. So yeah, you hit the nail on the head of what we were trying to get at here.
So yeah, that one point in time, and that's where most studies stop. And you know,
we've done studies like this in the past. It's a lot easier to get someone to come to your lab
one time, test them, and then you never see them again, rather than come to the lab and be like,
okay, please come back in 16 weeks. We really want to see what happened to you. But yeah,
that's what we're trying to get at with that second visit is just what you said. Some of
these devices, you know, at the
group level, maybe they're just systematically overestimating body fat. But like you said,
if you're doing that consistently, we might still be able to answer the more important question of,
has my body fat increased or decreased over time? So from the big picture perspective,
and I'm going to do my best to summarize here because we have 15 specific devices. Once the study is published, I'm happy to share. And I mean, I could even list them out
now, but many of the best selling body fat scales on Amazon. We have all these devices. We have lots
of metrics. We looked at lots of different things. So I'll paint with kind of some broad strokes
here. From a big picture perspective, and this is exciting to me as a researcher, we did see
a lot of separation really between the performance of devices. So there were some
that are definitely in the category of bad across the board. They're inaccurate,
maybe they're inconsistently inaccurate, they're not really useful. The magnitude of errors are
so large that you would need someone to have their body fat before it's like, oh yeah,
you saw a change in body fat. So's like, oh yeah, you know,
you saw a change in body fat.
So that's about half the devices.
The other half had performance that depending on the context could be acceptable.
So there were devices, even cheap devices, say sub $100 devices that performed surprisingly
well.
I was actually a little bit shocked.
For comparison, we had, for comparison,
we had a $12,000 bioelectrical impedance device in there, kind of as a lab laboratory grade
comparison that was thrown in with all these consumer devices. And there were some of these
cheap consumer devices that performed nearly identically to this $12,000 lab grade device.
So that as a, you know, as a general finding is encouraging for
these home body fat scales, but it's very important that the results are looked at on a case by case
basis. Cause we, we had some devices that if you look at them, if you look at the price, if you
look at how they're described and marketed, they seem like they should perform similarly. And we
had some that were incredibly different in their performance.
So there were several ways we looked at the performance. Some were what are called like group level metrics. We're just saying overall, did this device overestimate or underestimate
body fat? That's often where studies stop. And that can be useful. But again, we want this to be
kind of maximally benefit the consumer. And most consumers, most users of these devices, they don't care if we tracked 20 of them doing the same nutrition
exercise program. They care about the one N equals one. They care about themselves. Did I
gain or lose body fat? So we also looked at a variety of individual level metrics and something
that, again, my doc student Madeline had this very good idea was to generate all these rankings.
So we have all the devices ranked first through 15th in different categories. So like individual
level accuracy at one point in time, individual level accuracy, if you're trying to actually
track a change in body composition over time. So all this will be available in the manuscript,
and hopefully will be very helpful to consumers where they can find their particular device.
Or if they're in the market for device, they can look and say like, okay, the category I care about most is accuracy and
tracking in one individual because I'm going to use this in myself or my clients. And they can
look through and find, say, the top ranked device at the price point that works for them and use
that device. I would say in general, the devices that have electrodes in contact with the hands
and feet, those tended to usually be in the top half of the performers.
But surprisingly, there were some just foot-to-foot devices that just look like the scale you step on that were also near the top in terms of performance.
So, you know, I know these are all broad statements.
And for those who have a specific scale, I definitely encourage you to follow up on this. We'll try to share this widely as soon as it's published, because we think it
will be of interest to really anyone using these scales. But again, from the big picture, some of
these, you know, not worth using will probably add more confusion than benefit. But there is
actually promise in this category of technology, even on these relatively cheap consumer grade
devices, that if you pick the right device, you could actually get some useful data.
Interesting. And are there any details you can share on why you think some of these devices,
because I'm a little bit surprised to hear that. I basically wrote these devices off some time ago
and didn't bother using them myself and, uh, didn't recommend them. I tell people
just pay attention to your weight, maybe pay attention to, uh, the, your waist circumference.
There are a few things if you want to take some measurements, but, um, from the research that I
had seen, I, again, I haven't looked into this in some time, but from the research I had seen,
I was like, these, these things are all over the place.
So I just kind of wrote them off. And so I'm a little bit surprised to hear that some of these scales in particular, I was expecting the four points to outperform for obvious reasons. But
do you have any thoughts to share as to why some of these devices actually performed well and maybe better than
other scales or just two-point devices? I do have a few thoughts and I'll start out by saying that
I completely agree with what you said about tracking body mass and circumferences, some of
those other metrics, even with the best performing devices here. I think for the longitudinal
tracking, one of the best performing devices had, if there are any like stats nerds in
there, it had 95% limits of agreement of about three and a half percent. For others, this would
essentially mean if you saw a change in body fat, it'd be reasonable for the real change in body
fat to be about three and a half percent higher or lower than that. So that's a pretty large range.
If someone's interested, like did I gain or did I lose 2% body fat? And you go, you know, three and a half percent above or below that, you're clearly looking at
some reasonable values that could be negative or positive. Like you actually lost body fat,
you actually gained body fat. So that's a big caveat. Even the better performing devices
have a margin of error. It's incredibly difficult to be very precise and accurate when you're
tracking body composition of one person over time.
So that's a caveat. So I completely recommend what you were saying, Mike.
Yeah, that's a good point, especially for fit people, right? Even for women, even for if women, let's say, you know, they're fit women and they're around 20% body fat, give or take,
and they want to, you're still talking about enough air to confuse somebody, you know, where
they're like looking in the mirror and
they're feeling their clothes, but this thing says they got fatter. Like, how does that work?
Yeah, no, you're absolutely right. In a good proportion, it was depending on whether it's
the cross section, like the one point in time or the tracking analysis, 40 to 50% of the devices
systematically overestimated body fat in lean individuals and underestimated body
fat and those with higher body fat. So essentially there were a lot of devices that were kind of
pulling people towards the middle. So you might be really lean stepping on there and it was showing
you at a higher body fat than you really are. Conversely, if you have a higher body fat
percentage, you might be stepping on there and it's kind of like pulling the body fat percentage
down. So there were a whole category of devices that displayed this characteristic I'm'm describing which is called proportional bias it's bad it's something we don't
want um so again many of these devices you look at like okay no this is bad this is bad it's kind of
whittling it down to a select number that um were potentially useful and again then i would still
pair with what you said with body mass with circumferences and say does this make sense
like you were saying if you're like, you know, I look better,
my clothes fit better, whatever, my performance is up, but this scale showed body fat changed
in the wrong direction, then I would not put too much, you know, weight on that.
But yeah, in terms of the reasons, something we saw kind of emerging is some of the
manufacturers that have been around longer. so like Tanita is an example,
manufacturer that's been around a long time.
They've had a lot of research and development personnel
look at their equations over the years.
Some of those seem to perform much better
than some of these newer companies.
There are lots of kind of companies
that just do consumer tech type products
that they're like, oh yeah, we can do this body fat scale.
And they produce a device
and the device itself maybe is similar
to say like a cheap Tanita device
or one of these other devices.
But I think there are some cases probably
where the people putting the equations together,
I want to say didn't do it right.
I don't want to be too negative,
but they might not have known the best way
to put the equation together
to where it would scale
outside of their validation population. And they also might have known the best way to put the equation together to where it would scale outside of their validation population.
And they also might have validated the scales in like a very homogenous, like small group
with some of those issues, like I was just saying, where lean individuals and individuals
with higher body fat were systematically miscategorized that could speak to an issue
with how well the equations were validated.
So I think part of it, you know, the scale itself is one component.
Some might use better quality components.
They might be getting cleaner data.
But the other component that I also strongly suspect is how good of a job their scientists
did developing these body fat equations.
And as I mentioned a little bit earlier, the hard thing here is that none of the manufacturers
will disclose equations.
We have a table put with article about like whatever information we could glean about
each device.
Madeline, I know, contacted a number of companies trying to get information.
And most of the time, you know, the person you can get in contact with, one probably
doesn't know, but also won't disclose.
And they're like, oh, you know, this is proprietary.
But, you know, from these hints, I think that some equations, some people kind of maximize the utility of that bioelectrical data they get.
And others are just like, oh, yeah, we'll throw this in equation like this. This seemed to check
out in our sample of like 20 people. We tested this on. Let's go ahead and mass produce this
and sell it. And, you know, the consumer won't know any different. And brands, I would guess,
at least in many cases, brands are actually not
doing any of that work. They're just going to a manufacturer and the manufacturer says, oh,
yeah, sure, we can make that for you. And if they do even ask questions beyond if that, you know,
in many cases, that's probably the OK, here's my here's the order. Right. And we're going to slap
our brand on this. Then, yeah, maybe, maybe they would ask for some validating information.
But I mean, I'm speaking from experience, I guess, maybe more in the supplement world. But
especially if you look around on Amazon, I'm sure you guys and gals ran into this, that you have
a lot of, I mean, there are a lot of Chinese companies now that they've spawned. I've seen
so many random brands, especially in electronics. And these are not
brands you would recognize, but there are a lot of these products now that have just flooded Amazon,
particularly with electronics. And so like, if you don't recognize the brand name, if it's just,
it might even sound like something legitimate. It might just be some random company over in China that's just throwing their stuff up
on Amazon and they might not care about the quality of the thing. That's a growing problem
on Amazon. Yeah, no, that's certainly fair. And, you know, there were, you know, some trends
emerged like the more reputable companies, but there were the occasional oddballs where there's
a scale where we're like, yeah, the scale, we're not too optimistic, where it actually came out like,
you know, more highly ranked than we'd expect. So, you know, we saw some of those trends, but
again, I'd go back to, you know, it's a little bit of a case by case basis based on what we saw,
even ones that appear similar. So yeah, lots of interesting kind of wrinkles here. And, you know,
I wish every
company was completely transparent with what they did or didn't do to develop their equations and
just would show us the equation, but that's not the nature of it. We just wanted to, you know,
test what we could test and report what we found. So consumers and practitioners can make more
informed decisions. Yeah. And for people listening who want to read the paper and they want to see the ranked lists, do you know approximately when it will be available?
We're submitting to a fairly reputable journal.
Well, a very reputable journal, a very highly ranked journal.
So we hope that, you know, they'll expedite everything.
There are a few abstracts that are already available that I know I've posted about my social media, if any of that is linked.
I'll grab them and I'll put them in the show notes or whatever is available.
Yeah.
No, that sounds great.
And I'll definitely share widely once this is fully available.
We also actually already have a public listing. This study was not funded by any of these companies. We just
used, you know, my own research funds from Texas Tech to purchase these devices. And, you know,
there's nothing inherently wrong with industry funded research, but for this particular one,
none of these companies played any role. So we have this registered on clinicaltrials.gov. So if
individuals are curious, I can also send a link to that.
The full list of every device we looked at is already posted publicly.
And we did that just for openness and accountability.
So it's not like we're dropping some device off the list because, you know, the manufacturer, whatever, pressured us or anything like that.
So the full list is out there.
If you're someone that uses one of these devices and you're curious, you can look at the list.
If you're someone that uses one of these devices and you're curious, you can look at the list.
And if you see your home body fat scale on there, then you can wait with bated breath until it's published and you can see all the results.
And last question about that paper before we move on. So are there any devices that emerged from the analysis that you think could be useful?
You implied that this was the case, but then you had
mentioned these margins of error. So I just wanted to follow up with a question of, for people who
are into their fitness enough to want to track their body composition, were there any devices
in the 25 or so that you purchased that you feel would be useful for that?
that you purchased that you feel would be useful for that?
Yes, I think there are.
And I'll consult my spreadsheet over here because there are so many different rankings.
So we did ultimately get to an overall ranking,
like considering the cross-sectional,
so the one point in time accuracy,
both for groups and individuals
and kind of the long-term tracking accuracy
for groups and individuals and the reliability. Which is what most people that at least who have reached out
to me, that's what they care the most about is of course it's, it would be great if, if it were
very accurate in an individual reading, but minimally it needs to be consistently accurate
ish enough so that they can just, you know, throw it in their spreadsheet. They can
take their readings once a week or whatever. Yeah, no, absolutely. So, yeah, looking at my
list here for the individual tracking. So again, just tracking changes, looking at that one domain
rather than our overall rank. The top few were those, what we call octopolar they have eight points so that the hand electrodes and
the foot electrodes some of the best performing ones one was actually an omron device so not just
the handheld one but the omron hbf 516 so it's still very affordable i think it was under 60
dollars but has hand and foot electrodes the next next couple, there was a Tanita device
that also had the Tanita BC568 inner scan.
So another one that utilize those
had the hand electrodes also.
One other one that I thought was really interesting
that was actually ranked in the overall rankings,
second highest out of all of them. And the first
highest was our $12,000 device. So we were a little bit glad to see like, okay, that at least
holds up. Imagine the $60 device beats that, you know? Okay. Yeah. I'd be like, oh, didn't spend
that money well. But one device that's really interesting that was a little bit higher price
point is $350. So it's the most expensive of the consumer grade devices, but it was new and it's from a very good manufacturer was the InBody H2ON. So those involved in researcher
who have been in like a bunch of supplement stores, have them in some gyms, maybe familiar
with these InBody devices. InBody, you know, it's a good manufacturer. I know a little bit about
small amount about what they do under the hood from communications with their science staff.
And I'd say it's a reputable company. So they have this, again, the price point's a little
bit higher at $350, but this InBody H2O-N, which was another one that had both the feet electrodes
and hand electrodes, it performed well. And I'm actually involved in some other data analysis
from a separate university looking at the same device and it's performing well there also. So
I think it'd be a nice one that's a little bit higher end,
maybe a personal trainer or something that's wanting to have these reports
for their clients,
have a little bit of a nicer device,
kind of a, not that looks or everything,
but kind of a classy, nice, solid looking device.
Yeah, it performed really well.
It was in those top few
for tracking individual changes.
And again, it was ranked second out of all of them,
second just behind the research grade device
in the overall ranking. So that's one I like. I'll disclose that InBody
had no involvement in this study. Several years ago, they loaned the device to our lab just as a
loan, not research funding or anything that we used for a study or two. And then it's been long
since returned. But I'll give that just as a disclaimer because I have had interactions with
that company before. But anyway, so yeah, across Tanita, Omron, and InBody, like we were talking about,
common thing is all those are pretty well-established body composition manufacturers.
Each of those had both a hand and foot electrodes.
So those performed really well.
But once you go past there, you do get some that are just foot-to-foot,
including one of the Tanita devices.
But yeah, it's kind of initial glimpse on specific results.
Those three are ones that performed pretty well
for the individual tracking.
That's great.
That's great.
Hey there, if you are hearing this,
you are still listening, which is awesome.
Thank you.
And if you are enjoying this podcast
or if you just like my podcast in general
and you are getting at least something out of it,
would you mind sharing it with a friend or a loved one or a not so loved one even who might want to learn
something new? Word of mouth helps really bigly in growing the show. So if you think of someone
who might like this episode or another one, please do tell them about it. Let's shift gears now and talk about some other
methods of assessing body composition. So something that I will get asked fairly often is just,
what's the best method? What's the most accurate method, right? So the four compartment analysis
is something that's done in the lab. So we can probably exclude that.
You described that.
But for something that people can do at home,
people will ask me about calipers.
How about that?
Or they will ask about these devices that you discussed.
They'll ask about different measurements that you can take
and plug them into calculators.
Can you talk a little bit about,
and, you know, even though it's not accessible, people will ask me about DEXA or, you know,
somebody will show, maybe it's a video of somebody getting a DEXA scan and it'll say 10% and the dude
looks absolutely shredded, you know, maybe even striated glutes shredded. I mean, I'm exaggerating
a little bit, but where there just seems to be a little bit of a disconnect, like really 10, 10% when,
when he's like covered in veins. Yeah. I'll answer the main question, but since you finished on it,
I'll mention the, the DEXA question. So one important thing to realize is, you know,
I think sometimes from the outside, DEXA is a perfect example because, you know, kind of the
evidence-based community, they're familiar with Dexa.
They've either had a Dexa done or seen it.
You know, they're aware.
It is a really good method.
But, you know, when you're on the inside, I've used multiple different manufacturers of Dexa across multiple universities, multiple different software versions.
And you realize that there are quite a few things you can do in the software that change the results.
And I'm not talking about willful manipulation, but things like settings. and you realize that there are quite a few things you can do in the software that change the results.
And I'm not talking about willful manipulation, but things like settings, you can change different settings that could reliably change the body fat percentage by say 5%.
And 5% absolute, right? Just so people understand.
Yeah. So really, you know, meaningful changes where you could have the same
shredded striated glutes person jump on one DEXA, you know,
get it, get the scan done. They have the results. You could change some of the settings and
reprocess the same scan and you'd have quite different results.
So that could be the 5% turns into 10 or something.
Yep. It certainly could be. So there, there are some of those settings,
you know, there's some error in every device. Even like the pre-assessment standardization,
we talked about a little bit with fasting fluids, all this.
We've done studies where you can trick DEXA, so to speak,
by carbohydrate and creatine and fluid manipulation.
So depending on where someone's assessed
or how depleted or replete they are
at the time of assessment,
that could affect their readings beyond just what you
would see visually. And I've seen what I think is some manipulation as well. On the other side,
I can think of a fitness influencer too who has used DEXA scans to try to promote their programs.
And DEXA scans are often represented as the gold standard, infallible.
And so he'll hop on the DEXA and get a reading of five and a half percent. It's like, no, dude,
he's lean, but he's not five and a half percent. That's a nice maybe eight or nine percent,
but that is not getting ready to step on stage. And so that's just a good thing to point out that for people listening, don't
just take DEXA readings at face value. They might be right. They might not be right.
Yeah. And the same principles we were talking about with the BIA apply that it's really hard
to accurately track an individual. So even in that case, maybe the person's not willfully
manipulating, but they might be that person who, because of some of the characteristics in their
body, they're systematically underestimated by DEXA. So they're like, they're happy. They're
not going to argue if it's saying they're five and a half percent body fat, even if, you know,
they may be in their heart of hearts, think they might not be five and a half percent body fat.
That would mean that they would have to step on stage at like 1%, but.
Yeah. Yeah. So anyway, it's just, yeah, point being, you know, there's error involved,
there's settings, this and that. Transitioning, I guess, kind of to the main question you're asking about, kind of best
method, you know, I think you alluded to this already, but I'd say the best method, you
know, certainly depends on the context.
If you're talking to someone who has a flexible tape measure and some $10 calipers and you're
saying, oh, yeah, go, you know, pay $200, go drive five hours and pay $200 to get a
DEXA scan done somewhere, that's the best method. You know, that's probably not the best method for their context. It's certainly not the
best method for repeating frequently over time. I'm a big proponent, as others are. I know Bill
Campbell often says this, which coincidentally enough, Madeline Seidler, who helped so much and
really led the BIA study, she studied with Bill Campbell before she came to study with me. So she's had a lot of body comp stuff, but I'm a big proponent of those practical measures
and not doing too much with them. So for example, if you're interested in fat loss and you can take
these raw skin fold thicknesses at different sites on your body, it might be best to just
keep those raw and interpret them as much as you want to plug those into equation and distill all that down to 13% body fat, it might be more informative
to watch those over time and say like, okay, I have a lot of skin fold sites that are not changing,
but I see like this abdominal skin fold, this is actually decreasing over time. That's something
that I want that's consistent with my goals that might get washed out when you're pooling all of
these together and throwing it into a body fat equation. Similarly, circumferences, like you said,
you know, if you're seeing your waist circumference go down over time, the scale is not budging.
Maybe it's even a home body fat scale and that number is not changing or it's kind of just
randomly oscillating around. That's an encouraging sign. You're like, okay, waist circumference is
decreasing. Maybe my upper arm circumference is increasing. Maybe I have some amount of, you know,
so-called recomposition going on right now.
I've, you know, increased my protein intake recently.
I've, you know, increased the intensity of my training
and so on.
And as you know, the more trained someone is,
you know, you're dealing with small margins
and it's, you're not going to see large changes
and it's hard to track those small changes you do see
because of the, you know, little bits of error.
But I'd say there's certainly nothing wrong.
I've stopped bothering with that because I mean, take calipers, right?
I mean, I wouldn't say that it requires a lot of skill to take caliper readings,
but there are right and wrong ways to do it, right?
Even the amount of skin that you pinch,
if you're not consistently pinching the right amount of skin,
there are spots too that are kind of hard to do yourself.
And really, it's probably better if somebody else does them. And then, like you said, also the margins of
improvement are so small that they kind of overlap with the margins of error.
And so I've found just as a random comment that what has been more useful for me,
if we're talking about tracking muscle gain is just using performance in the gym
as a proxy and watching my performance with given working weights progress first in reps and reserve
where, okay, that weight felt a little bit heavier a month ago. That's a good sign. Eventually that
turns into being able to get an extra rep or two with the working weight. Eventually that turns
into some extra weight on the bar.
And of course I just go, hey, if that's happening,
I'm gaining, I know I'm gaining at least a little bit of muscle
and it might not show up if I were to take measurements
because we are talking about such small amounts.
And if I mess it up a little bit, it's not gonna show.
Yeah, no, I think that's completely fair. And I
don't think there's, I mean, I certainly don't think there's anything wrong with a method like
that. Even if you wanted to periodically, and even if it's every several months, every six months,
every year, if you're just one big picture, like, you know, I'm, you know, I'm wanting to maintain
this, whatever I'm at for the next decade, two decades, three decades, I think a periodically
check and say like, okay, within, you know, reasonable marginal margin of error, is there anything I'm just not realizing that I didn't realize? Cause you know,
general population wise, maybe not fitness community quite as much, but general population
wise, things tend to drift over the years and decades in a direction you don't want. So even
something as simple as that, you know, ideally your general practitioner, someone might do it,
but maybe not, you know, a simple waist circumference every six months or something,
just to make sure something's not creeping, uh, you know, way you don't want to.
And again, I'm getting kind of more general population there and less, you know, like peak fitness.
But yeah, no, that's a good point.
But I guess you could, like you said, I mean, you could do even in the case of someone like you or me, maybe we would we could do check in measurements every so often.
We could do check-in measurements every so often if we were so inclined. I suppose for me, it's to that point of maintenance where I've accepted that this is about as big and strong as I'm going to be no matter what I do.
If I really wanted to push for more, of course, there's a little bit more to be had, but I'm pretty happy with where I'm at.
but I'm pretty happy with where I'm at. And, and this is, I'm getting ahead of myself because something that, um, you know, I've gone through the whole experience of body fat percentage and
being really into trying to get to the number. And eventually it's just, do I like what I see
in the mirror? If I feel like I'm too fat, cool. I'm just going to restrict my calories for a month
or two. And now I like what I see in the mirror. Okay, great. What number is that? I don't know. It's in the range of what I like the most
is probably between eight and 11% or something like that. And exactly where I'm at in that range,
I don't care. As long as I'm in that range, that's what I like.
Yeah, that's completely fair. And it's funny, as a researcher who does a ton of work in this area,
there are definitely times I kind of zoom out and think about that and like, does this matter?
And, you know, it does.
And some of the research we do is for other contexts.
And, you know, there are lots of health and, you know, disease implications, other things
we do with body comp.
But yeah, at a certain fitness level, you definitely can legitimately question like,
okay, how much does this truly matter at this point?
What does the number I'm getting matter?
So yeah, I would say, you know, circling back around for anyone, you know, interested in
body comp assessments, certainly, you know, there's nothing wrong in being interested
in them, but I'd interpret everything as a grain of salt.
I'm always a proponent of multiple metrics, especially, you know, if you're doing some
of these potentially less accurate tests.
But if you were, if you do have even one of these better home body fat scales, pairing
that with tracking your weight, considering your performance in the gym,
maybe periodic circumferences or skin folds, kind of getting that holistic look.
Cause again, just, I think I said this earlier, but say again, if you're getting some number
that's tracking the wrong way, but everything else is good, you feel better, clothes fit better.
Say, you know, like your method with performance is better. All of that. You certainly wouldn't
want to make some large programming change.
They're like, okay, I need to scrap everything and start over because, you know, my home body fat scale said I went up 2%.
Or get, just get, yeah, or just be demotivated or discouraged by it.
Right.
I mean, I understand that again, that that wouldn't be the case now, but there was a
time when I just wasn't informed enough and maybe would have been discouraged because it's just conflicting information. And if you place too much credence in, it could be a device or a method like, you know, skinfold. I know a lot of bodybuilders will swear by the skinfold method.
whereby the skin fold method. And, and if, if that gives you a number that is discouraging,
you know, it might lead you to question some of these other methods of assessment.
Yeah, no, I agree. As one random side note I was mentioning, cause it's another class of technology we haven't talked about, but that our lab has done a lot of work in and we're really
interested in is I think there's a lot of promise in terms of just reliable assessments and easy assessments. There's a lot of promise
for three-dimensional optical imaging. Oh, that's good. I wanted to ask you about that.
Okay, great. Yeah. So there are lots of these standalone scanners like Stycu, Fit3D,
SciStream, and so on that you could actually, like here in town, our Crunch Fitness, for example,
has a Fit3D. And those are showing up, I think, in more and more facilities. But with phone applications, we've recently been evaluating some of these. Their phone cameras are good enough and the technology is getting good enough on 3D scanners that there are some free phone apps where you can set up your phone and rotate in front of your phone and it builds a little 3D avatar of your body.
3d avatar of your body and the nice thing there is that it can pull circumferences very reliably so it'll have some definition based on the pixels it's seeing on where your waist circumference is
so there's no guesswork really of like am i measuring this in the same way or like can i
really measure this particular circumference if i'm trying to measure my chest circumference do
i have it this flexible tape measure at the same point in my back if i'm measuring it by myself
so i think there's some some promise there for like simple things, even if it's for a periodic
check-in where technology can assist even in a free capacity without like purchasing a particular
device, but could assist with tracking some of those basic metrics. What have you seen with
some of the more expensive devices, like what you'd find in a gym? My gym has one,
I haven't bothered with it, but. Yeah, so I mean, the test-retest reliability
is very, very good.
In general, from our lab and literature,
most devices would be comparable
to like a trained tailor in terms of the reliability.
So the only times I've seen like a manual assessor
outperform the reliability
of these circumference assessments
is if the study is using, yeah, again, someone trained equivalent to a tailor.
So if you're talking about, you know, your random gym buddy or something who's just like
slapping on and measuring might be better quality than that. This is another example where I think
the raw inputs, the circumferences in this case, would be potentially more useful than plugging
into a body fat equation. The body fat equations have a little bit of work to do, and it makes
sense. They're trying to estimate something internal, your body fat, just based on surface
metrics and not even getting like a skin fold or something like calipers. So there's some
challenges there, but in terms of the circumferences, if you're like, okay, I want to
track my upper arm circumference, my thigh circumference, and my waist circumference over time, I want my arms and
thighs to get bigger and I want my waist circumference to get smaller. They're sufficiently
reliable that if you assess the same way, so not after a big meal one time and fasted the next time
and all of that, if you assess the same way, they do have pretty small margins there where they could
track small but real changes in these circumferences.
So I would say I'm generally optimistic on them.
But again, with some caveats, like if it's spinning out the body fat percentage, say
the one at your facility, I wouldn't put too much weight on that.
But if you're interested in tracking some individual circumferences, I would say it's
a decent technology for that.
If it's consistently tracking those circumferences, even if the body fat percentage were wrong,
I suppose if it were consistently wrong, at least could show you a trend, right?
It could. And the hard thing on there is it's sort of similar to BIA, but I've seen a little
more under the hood because I've been involved with a couple of companies helping them develop
some of these equations, but it just depends on
what circumferences they're pulling. So I was even advocating, you know, like there's some,
there are even different versions of the waist circumference, you know, depending on if they're
doing the narrowest or the navel or, you know, halfway between where they think the ribs are
and the hips are, you know, all this. So it kind of depends, different companies pull different
circumference inputs because it can measure anything on the body.
It has a 3D avatar.
There are all kinds of weird ones.
It's like I can measure from like the tip of this shoulder down to like your opposite butt cheek,
just all this random stuff.
They can pull any input they want
because they're not actually there with a tape measure.
It's just, you know, based on the avatar.
So I think there's a lot of room for growth
for like what inputs are pulled,
how they're weighted in equation and all that.
So yes, you're right.
I think you get track there.
A hard thing is it's such an early technology that some of these devices are like pushing
a body fat equation update like every few months, which is not helpful to the consumer.
It's like all of a sudden it's different by like 5%.
They're like, oh yeah, we changed the equation.
We don't use like this circumference anymore.
We use this one.
So that's another reason why they don't do that as much with actual raw circumferences.
It's usually just what they're doing with their circumferences.
So yeah, the relative use of the technology is another reason why I kind of am more of
a proponent of the circumferences.
Now, you spoke, I think, implicitly about this already, but I think it would be worth
just explicitly commenting on it. And that is the
accuracy or the usefulness of what's the name of the method. So you're supposed to take some
measurements. This is for body fat percentage. And I haven't done it in a while, so you could
tell me. I don't remember the exact measurements, but you take a few measurements, you plug them
into a calculator and it spits out. I believe it was, is it a Navy thing or a military thing?
Oh yeah. Like the army body fat equation. Yeah. I know there's, there's one of these
things out there that makes it seem very simple. And I know then many, many people
turn to it because it seems so simple. Yeah. That's a really interesting question. I had
another student just defend
his dissertation and it focused a lot on military and military relevant populations with like that
equation you're describing and 3D scanners and four compartment, all the things we've talked
about kind of rolled up into one. Okay, so it's not perfect. We know that like for, you know,
if you're just looking at like neck circumference and waist circumference in males and like neck,
waist and hips and females, this is certainly not a perfect measurement.
Like we were just talking about with 3D scanners, we're not measuring anything internal to the body,
but we're trying to measure something internal to the body. So you already have a little bit
of a disconnect there. But surprisingly, when you look at it, there's a reason why it's hung
around. And, you know, of course, from say the military perspective, they need something simple.
They use like height for weight tables and then this body fat equation like as needed.
But they need something really simple. We've had some discussions with personnel there about
whether even just moving to 3D scanners, they could at least eliminate some of the
like tester to tester variability and how these are assessed. But the equation does okay. It's
not as bad as you'd expect. We kind of went into this big project and over a hundred individuals
looking at this equation and many others.
And we kind of expect it to be like,
oh, you know, there's the antiquated,
you know, Navy, Army, military equation.
And it did pretty well for the people who developed it
were, I don't know, onto something like this.
Scaling with the neck circumference is weird,
but like neck circumference matters
for like just kind of a natural build, like kind of correcting the waist circumference for someone's
natural build. So anyway, I certainly wouldn't take it and like have someone plug it in there.
And, you know, and this is funny, but an anecdote, even when the military people were talking about
is how people would like train their neck really aggressively and try to get all this neck
hypertrophy to like trick the equation. That's, that's neck training seems a little bit of a thing. I've been asked more about it recently
than in the past. It just seemed that in the fitness world, you know, people asking how,
how do I make my neck as thick as possible? I'm like, why, what do you mean? Just do more squats.
Come on. What are you doing? Yeah. Yeah. So anyway, it, you know, it certainly isn't like
the best method, but it's all, you know, context dependent. If you're screening thousands of people and just trying to like have some rough cutoffs in this night, it does pretty well. You know, we'd never say like, oh yeah, you don't need a DEXA scan ever. Just like, yeah, give me your neck circumference, your waist circumference. That'll tell you like for sure your body fat percentage. So I don't know. That's just a random collection of thoughts. Yeah. Yeah. It sounds like it's maybe similar to BMI in that regard, but for body comp where,
yeah, sure. At a population level, it's pretty useful. At an individual level,
it can underestimate, it can overestimate body fatness. Depends on how fit you are,
blah, blah, blah. How much you've trained your neck, all that good stuff.
So then I'm assuming the thicker the neck, if you're training your neck
explicitly to try to trick it, then that brings your body fatness down. That's the point.
Yeah, yeah.
So you can be overweight. If I just get a really thick neck, then I'm going to pass this test.
I think that's the idea. So how successful people have been when they try to do that, I'm not sure.
Yeah, yeah. How much neck hypertrophy does it take?
That's funny, but no, that's great.
And that's all the questions that I had for you.
Is there anything that is still kind of sitting in the back of your head that we haven't discussed
that you think we should cover before we wrap up?
I don't think too much.
I just reiterate that I don't think there are many methods that are just complete trash. I think every method you should take with a grain of salt, you can maximize the benefit of any method you're using by being rigorous with how you standardize before assessments, not just doing these haphazardly.
for things like taking multi-day averages. So like if you're able to perform the same assessments on a couple of days in a row and average across those days, that can help reduce some of that
day-to-day random error. So yeah, I think whatever method you use, if you use any,
just apply it consistently. Ideally, look at a couple of different metrics. Don't read too much
into each one. Just kind of take it with a grain of salt. Consider performance. What are your goals?
Is body comp your number one goal and you'll sacrifice performance for it? Or is it performance and you're
hoping body comp kind of comes along for the ride? So yeah, for anyone who's like really in the weeds
on body comp or obsessing over it, I would just, you know, think about how you could use it to
benefit you in some way without, again, basing all your decisions on it or placing all your value in a number being spit out by a $35 scale that you got from Amazon.
And again, for anyone interested in the consumer grade BIA devices, we'll certainly share that.
But hopefully that will help inform decisions because some people might be using a scale
where they'll look at that and say, okay, we actually need to get rid of this.
This is worse than nothing.
But some people might have scales where it's like, okay, this isn't everything, but it's
a piece of the puzzle that can help myself or my clients or so on. So yeah, I think
those would be my only parting thoughts here. Cool. And one follow-up question on that actually
is if you are going to be using one of these BIA devices, let's say you have a good BIA device.
You had mentioned previously a couple of the things that, a couple of the factors that you
controlled for to get
consistent readings, but maybe we could just wrap up if you want to share with people at home.
All right, here are the important things to make sure that you're getting consistent readings
and also accurate readings. Yes. No, that's a great question. So I'd say at a minimum,
you want an overnight fast from food and fluid
um sometimes well i won't get in all the weeds here but we've done some studies just looking
at simply someone comes in the lab and ingests water and how much does that affect their
biomedicine measurements and it it can be meaningful depending on the type of technology
so i'd say at a minimum eight plus hour overnight fast from food and fluids. So ideally, you know, the morning is the ideal time to do this. Avoid your urinary bladder if you need to
defecate or if you have a normal morning bowel movement, go ahead and do that. Just everything
you can standardize. Of course, rested overnight, ideal would be longer. Like in our study,
we had a 24 hour abstention from exercise. So if you do incorporate rest days or active rest days,
assessing body comp the following morning might be an ideal time to do this. Doing that consistently,
so you wouldn't necessarily want to assess sometimes the morning after a heavy leg day
the previous evening and other times assess after a rest day. So consistency even on what you did
the day prior is important. General awareness of dietary patterns. If you track or if you're
just consistent on your diet over time, you may have this address, but just be aware, especially
if you're doing carbohydrate manipulation or if you're changing up your diet in a way that
dramatically affects the water content of your foods. Some of those things, even the preceding
days can affect measurement. So I would just be aware if you are tracking, try to think not only
overnight,
but the previous day and kind of habitual diet, what things could you be doing that might be
influencing this? And I'd say the more of those things you button down, the more noise you
eliminate and kind of the cleaner your signal or the actual value you're trying to get comes
through. So those would be the main things, food and fluid, rest, kind of awareness
of your overall dietary pattern, exercise patterns, and so on. And I think if you do
have someone else involved, for example, helping with skin folds, circumferences, and so on,
having the same person do that over time and apply that consistently would be the ideal scenario.
Great tips. Great tips. Well, this was a great discussion, Grant. I really,
really enjoyed it. Very informative. And why don't we wrap up with where people can find
you? You're active on social media, share a lot of great educational information there.
And then anything else you'd like people to know about? Let's let them know.
Yeah. So I'd say if you want information on me, I have a personal
website. That's just my name, granttinsley.com. I have my academic CV up there. I have information
about our lab equipment, our research team, my home gym, just all that type of stuff on the
personal website. In terms of social media, I'm probably most active on Instagram. And my handle there is just grant underscore Tinsley, T-I-N-S-L-E-Y underscore PhD.
And I typically share new research on Instagram.
And my website also has links to PubMed and other websites that kind of keep track of
all the research output from our lab.
Awesome.
Well, thanks again for doing this, Grant.
And I look forward to the next one. Well, thanks again for doing this, Grant. And
I look forward to the next one. We should brainstorm something else we can talk about.
Absolutely. Thanks for having me on, Mike. you don't miss new episodes. And it also helps me because it increases the rankings of the show a
little bit, which of course then makes it a little bit more easily found by other people who may like
it just as much as you. And if you didn't like something about this episode or about the show
in general, or if you have ideas or suggestions or just feedback to share, shoot me an email,
mike at muscleforlife.com, muscleforlife.com, and let me know what I could do better or just feedback to share, shoot me an email, mike at muscleforlife.com,
muscleforlife.com, and let me know what I could do better or just what your thoughts are about maybe what you'd like to see me do in the future. I read everything myself. I'm always looking for
new ideas and constructive feedback. So thanks again for listening to this episode, and I hope
to hear from you soon.