#622: Body Composition Testing: Methods & Interpretation – Prof. Grant Tinsley

0:00Danny Lennon: Hello and welcome to another episode of Sigma Nutrition Radio. This is episode 622 of the podcast. My name is Danny Lennon. You're very welcome to the show. Today we're going to be talking all about body composition testing, the interpretation of those results, what they're actually telling us, and then some of the intricacies of what we're actually doing with this variety of testing, some of the things to be aware of when we're interpreting individual level data, as well as group level data within studies and then some of the things you should be aware of if you are indeed using this with yourself athletes clients patients etc or if you are more interested in interpreting the results we see from body composition measures within research studies being aware of some of those intricacies as well and to talk through this topic there's probably no one better i could think of talking to than professor grant tinsley who's professor of human performance at Texas Tech University where he is the director of its energy balance and body composition laboratory.

1:03Danny Lennon: He has done a whole range of excellent research in this area, has done more body composition analyses than I can care to even try and guess at this point through a range of different measures and is best placed to talk through some of these aspects around body composition testing, estimation, and interpretation. For those of you who are Sigma Nutrition Premium members, you will of course get a set of detailed study notes to accompany this episode, which you can get either in the description box where you're listening right now or over on the website if you go to this particular episode. You'll also receive an email with those details as well.

1:42Danny Lennon: If you're listening on the free public feed of the podcast and you're interested in getting more educational materials to supplement your podcast listening, including the study notes that we offer for each episode, as well as an edited transcript. And then every month, you also get a premium exclusive episode of the podcast not available on the public feed. For more of the information, just check the link in the description box where you're listening right now. That will tell you a bit more about what you can expect as a premium member and some of the things you may get from that. Also in the description box, I'll link up to the episode page at which you can go and find all the relevant resources for this episode, including any studies that might be referenced or anything that relates to some of the topics discussed.

2:26Danny Lennon: You'll also get a bit more about Professor Tinsley's background and places to find him online. All of those resources that relate to this episode will be linked up in the episode page, so you can find that linked in the description box where you're listening right now, or of course, just by going to this episode on sigmanutrition.com. So with that out of the way, let's get into this conversation between myself and Professor Grant Tinsley.

3:03Danny Lennon: A very big welcome to the podcast to Dr. Grant Tinsley, thank you so much for taking the time to join me. Absolutely. It's my pleasure. Thanks, Danny. Very much looking forward to this. And as maybe regular listeners to this podcast will know, your work has reared its head on several occasions on previous episodes. So for me, it's a particular honor to be able to talk to you directly about some of that today. Before I get to my questions, though, can you give people a bit of a background to your academic background, your research interests, your current work, and anything else that might be relevant for them to hear?

3:34Yes, I'd be happy to. So my academic background started with studying physiology and nutritional sciences in my undergraduate work. I had always loved science. I've been a science nerd my whole life. Increasingly fell in love with exercise and sport and nutrition through adolescence. So it felt natural to study the body through a physiology degree and add in that nutrition component. From there, I got a master's in biomedical sciences, which was a lot of anatomy and physiology. I got to dissect cadavers for a year, which is a huge honor, really, is one of my best years of my education, just because it gave me a different appreciation for the human body and kind of continued to lay these foundations of body composition, which I'll mention is my major area of interest.

4:13Seeing the human body taken apart physically really gave me some direction towards what I wanted to study further beyond that. So in my PhD, I studied kinesiology and exercise nutrition. And after that, I came out here to Texas Tech. So actually, as of a few weeks ago, I've been out here 10 years. So I'm now a professor of human performance at Texas Tech University, and I direct the energy balance and body composition lab. So we have multiple lines of research, but the big umbrella interest is the assessment and modification of body composition. So that includes on the modification side, nutrition, exercise.

4:49In the last few years, I've gotten pulled more into the pharmaceutical space as well, particularly with the substantial interest in GLP-1 related medications. And kind of related to that, in addition to my academic role, I'm the chief science officer for Vineyard Health, which is an online medical clinic that provides comprehensive care for patients with obesity and cardiometabolic concerns that provides them with nutrition support, exercise support, in physical therapy, in addition to the traditional medical support. beyond that i do some scientific advising for different companies and whatnot but yeah that's

5:21Danny Lennon: that's the gist of me and my background fantastic and as people will see if they go and take a look at your not only publications but your extensive background in this area really at the forefront and there it's hard find someone better pressed to talk about the topic we're going to at hand today which of course body composition and as you mentioned components around assessment and then almost modification but if we think about body composition because this is a term literally everyone listening will have heard of it's they'll hear it colloquially used as in the kind of fitness industry realm but in a specific sense maybe people don't think too much about exactly what that encompasses and all the different type of sub components that would come in under body composition so when we're using that term as you would look at it in the lab and the different ways to assess that and different ways to chop that up what can what are we actually talking about with body composition?

6:13Yes. So it is, I mean, really body composition is simply just the makeup of the body. So it is, you know, at surface level, somewhat simple, the composition of the body, the makeup of the body. It does get more nuanced though, as you were alluding to, because there are different lenses through which we can view this really every lens we're starting with body mass, total body mass, and we're trying to split this up into different components that are meaningful in some way, maybe physiologically or meaningful from the perspective of something we can actually measure. And going back to, say, the cadaver dissection, there's a different perspective if you could physically dissect and weigh out different anatomical body components as compared to you have someone stepping on a bioimpedance scale and you're passing some current through them and collecting data.

7:00But really, you're making several steps from what you can actually assess in a living human to what we're actually interested in, which, again, is the makeup. And when we say the makeup or components, we're usually talking about actual mass of these different components. It can get hairy though, because sometimes we'll have these components people are maybe familiar with, like skeletal muscle, fat-free mass, that they might know there's some relationship, but they're really coming from different lenses or perspectives from which we can view the body. So when they're conflated or kind of combined, the math doesn't always work out and it gets kind of confusing for people just because I think though it is simple at face value, it is actually, again, fairly complex, and we need some internal consistency on what we call this the level, the level at which we assess the body, and there are five primary levels.

7:46We need some consistency there if we want to talk about this in an intelligible way and avoid confusion.

7:51Danny Lennon: And that's a perfect jumping off point, I think, because we obviously want to be able to be precise in our terminology, and there's a requirement for that. Sometimes there's some confusion about what those terms mean and often they're used erroneously in an interchangeable way and that can sometimes throw people off because oftentimes people have an interest from a health or performance perspective of principally looking at things like maybe the fat mass within the body muscle mass and then beyond that though people might pull up research and are using maybe these other types of measures that you mentioned that are informative but using them interchangeably with some of those.

8:29Danny Lennon: One that's probably most common to see is when people are referring to, say, the skeletal muscle mass, but then also looking at things like lean soft tissue, or they will say things like fat-free mass that they've seen in a study. So these different things that they are, maybe there's a bit of confusion around how they relate to each other and how those things are actually measured. For those three in particular, let's say, can you maybe give some clarity over what precisely they are and then how we get to arriving at those measures or why that might explain why those different measures are actually used.

9:03Yes, it's a fantastic question and it is very important. So for, let's start with fat-free mass. Fat-free mass is, I just mentioned a minute ago, there are five different levels at which we could break down body mass. So fat-free mass is part of what we call the molecular level. So the molecular level of body composition assessment is really what most techniques that listeners will be familiar with use. So it's very common level. We can get into the specific techniques later if you'd like, but what it, what this level is doing is kind of viewing your, your body as molecular soup. So if we could just melt you down and separate you out, say with different solvents into these molecular categories, that's really what the molecular level is doing.

9:42So it's not respecting anatomy. So at the molecular level, fat mass would really be all of our non-polar lipids. So again, going to like chemical extraction for anyone who, you know, has a background in chemistry or remembers hopefully favorably some, some chemistry labs in their past. That's really talking about the fat mass. Fat free mass is everything else. So everything that is not these non-polar lipids. So that includes lots of body compartments. That's, you know, water, protein, mineral, glycogen, and so on, but it's the water, protein, mineral, glycogen, and so on everywhere in your body.

10:17So it's not just contained within your skeletal muscle. It's not just contained within your organs. It's everywhere it could be found. And where it gets tricky is that take adipose tissue, for example, adipose tissue is mostly molecular fat, but it does have some protein and water in it. So even in adipose tissue, there are actually some components of it that are contributing to fat-free mass at the molecular level. So that's fat mass, fat-free mass. You mentioned lean soft tissue. It's fat-free mass once you've taken out bone mineral content. And the reason why lean soft tissue, I think is a phrase that's out there is because this is frequently provided by DEXA, dual energy X-ray absorbed geometry.

10:55And again, just because DEXA has the ability to estimate bone mineral content, you can pull that out. So you now have lean soft tissue, which again, is everything except fat mass in bone mineral content. But all of these terms we're talking about right now, molecular level. Now, if we go to skeletal muscle mass, this is at a whole different level, different paradigm that we're using. And that's called the organ tissue level. The organ tissue level, I think, is what most people tend to think in because it respects anatomy. So going back to my cadaver dissection, if I'm dissecting off adipose tissue, if I'm isolating certain muscle groups, that's really the organ tissue level.

11:30So skeletal muscle mass then would be the mass of all these anatomically defined skeletal muscles. So these muscle groups are attached to the skeleton. So again, that's very intuitive for us. Whereas fat-free mass is less intuitive because it's really spread throughout the entire body and does not respect anatomy in the same sense as something like skeletal muscle mass.

11:51Danny Lennon: And just so people can get a grasp of this then, because they're following along, seeing that there's these different levels we can think about body composition on, each of those examples we've just given are essentially measuring different things. And so when we think about the typical or the different tools that we currently have now to measure body composition in some way, some of those are directly measuring some things, indirectly measuring others, or we're using calculations. How does that fit with what we've just discussed of these different levels of thinking about body composition? Are there some of those tools that are best suited to looking at one of those levels, others for another?

12:26Danny Lennon: How do maybe some of the ones people have heard of fit into what we've discussed so far? Yeah, so it's a good question. And I think it is important here for us to separate the fact that there is a true physical quantity. So there is an absolute number for you and I right now, we have an actual fat mass. If we could assess this, if we could be dissecting chemically, we would have this actual value of fat mass, fat-free mass, skeletal muscle, and so on. So these are real physical quantities that exist at any point in time. However, our ability to measure them is essentially zero to measure them.

12:58Our ability to estimate them is really what we're getting at here with these different devices where, as you mentioned correctly, that we'll measure something and then we're trying to leverage some type of biophysical relationship between what we can actually measure, what we can actually access from any given technique and this real but kind of unknown to us physical quantity that would be are true, say, body composition at that moment. So I would say the majority of techniques, as mentioned, do use the molecular level, meaning that that is what they've been calibrated to. Obviously, this is not typically back to cadaver dissection, though some methods like DEXA have had some cadaver research in the past.

13:37But if you take, you know, your average bioimpedance scale, you can get at home bifat scale, they're certainly not doing like cadaver dissections and standardizing their measurements relative to a criterion like a cadaver dissection. Typically, they'd be using comparing to a laboratory method. So just running through those, I guess, starting kind of at the baseline level, anthropometry would be a very common, more accessible technique. This would include things like skinfold assessments, as well as like circumference-based estimates. We now have digital circumference-based estimates. So things like 3D scanning either from a smartphone or point of care device.

14:12All of those are, say on the circumference-based estimates, these are leveraging the fact that we know the shape of the body does reflect the internal composition. However, of course, there are some assumptions here. This is not a perfect relationship, but waist circumference being an easy example. In general, as someone's waist circumference gets larger and larger, that's more attributed to increases in adiposity than say muscle mass or fat-free mass here. Skin folds are kind of an interesting one. So this is, there are some assessments we take that don't fall easily within one of our levels.

14:44So I guess that to zoom out, just to, when I say most methods are at the molecular level, any method giving you a body fat percentage. So body fat percentage is using the molecular level at some point. Some take kind of an interesting route to get there. So taking skin folds, what we're actually assessing, we're grabbing this double layer of skin and subcutaneous tissue. We're trying to get out there is the subcutaneous adipose tissue. So that's kind of interesting because it sounds kind of organ tissue-ish when we talked about that level because it is kind of anatomical, but it's just at these certain points in the body.

15:16But then what we do with that data, we kind of add up those skin folds. We predict body density from body density. We predict body fat percentage. So we have something that's kind of like a regional or segmental organ tissue quantity we're assessing. But then by nature of what we do to it, we end up getting a molecular level total body estimate. So again, body fat percentage, fat mass, fat-free mass. Moving on from there, bioimpedance, very common technique. It's a really interesting technology category because we have everything from wrist-worn wearables, very inexpensive at-home scales, up to research-grade devices, some of which are over$30 ,000 in US dollars currently.

15:56So a huge spectrum of devices, but they all operate based on this principle of electrical conductivity, largely through body fluids. So this is still at the molecular level, but kind of the approach it's taking is how easily electrical current passes through the body tells you something about the water content and the lipid content of the body. From there, we can kind of infer the total amount of water in the body and estimate the total amount of fat-free mass. So something very different is assessed, but we will still end up with similar appearing outputs in terms of body fat percentage, fat-free mass, fat mass, and so on.

16:29Now, where things get interesting, and this will, I will circle back and connect your question about whether certain types of assessments are better for a certain level. Moving on from here, actually, I'm going to do one more. Densitometry is an important one here that I'd put in this category. This would include underwater weighing or hydrostatic weighing, as well as air displacement, plethysmography, or the bod pod. And this is looking at these kind of whole body characteristics of the mass and the volume of the body. From there, we get density of the body and can predict things like body fat percentage, fat mass, and fat-free mass.

17:02So all of these ones we've talked about, they're measuring something on the body, inserting that information into a series of equations. None of these have been overly anatomical, I'd say. When we transition to imaging techniques, it's kind of an interesting jump. So moving on to DEXA, which again is dual energy X-ray absorptometry. Many listeners may be familiar, but this technique operates just by passing really a broad spectrum of x-rays through the body, but separates it out in sort of different bands, a higher energy and a lower energy. And based on differences in how those beams are attenuated or sort of slowed down as they pass through different body tissues, it can create a visual representation of the body and separate out body mass into lean soft tissue, bone mineral content, and fat mass, both for the total body and because it is an imaging technique for different segments of the body as well.

17:53So DEXA is still a molecular level technique, but it's getting closer to organ tissue techniques we'll mention momentarily because we are getting to actual imaging. So again, it's a very well accepted standalone device. It's not perfect and no method is, but it has a strong theoretical basis in the sense that we're actually imaging and able to separate out these different molecular categories based on their attenuation. Now, when you go to other imaging techniques like magnetic resonance imaging, so MRI, computed tomography, CT, and then even ultrasound. These are the ones where we're really focused on the anatomy and where we're mostly assessing things at that organ tissue level.

18:32So if we did a whole body MRI, we could actually get skeletal muscle volume or mass for the whole body where we're looking at those anatomically defined muscle groups. We could look at adipose tissue depots in three dimensions. Something like ultrasound might not be in three dimensions, but we could get something like a skeletal muscle cross-sectional area. So for say tracking exercise induced changes in body composition, we could look at the cross-sectional area of muscle groups actually changing over time. So this is organ tissue, again, anatomical, even if it's not for the whole body. So feel free, if you want more on any of those, let me know, or if you want less, can't go back in time, but feel free to move on if that's too much there.

19:10Danny Lennon: No, that's absolutely perfect. And I think obviously people should appreciate that even for any one of these techniques, we could probably spend the whole rest of the hour discussing the real nuances of that and maybe best left for another day. But what we have so far, I think, is really useful for people to get a grasp of these different techniques, essentially what each of them is doing. But also, I mean, there's much confusion because we sometimes have this question that's maybe not a very useful question of people wondering just for themselves, what is the best to use? And obviously that question kind of is meaningless unless we put some parameters around it, right?

19:45Danny Lennon: So we could think of, is there a universal goal standard in terms of accuracy? That might not be the same thing as weighing up the pros and cons for a given use case and then determining based on that. So given that all of these things that you've mentioned have some positives and negatives and pros and cons, when we are thinking about their various applications and what might be best to use or why one would choose one of these tools, what is some of the decision-making process that goes into that, that would lead you to use or recommend one in a particular context. Given that I realized there's many different contexts we could be talking about.

20:24Yes. No, I love how you frame that because you're absolutely right. You know, I could tell you on paper, oh, everyone, you know, if you want the most accurate body composition assessment, go get a whole body MRI, go to research lab and get a four compartment model of your body composition, but they'll be accessible to virtually no one. So, so I love how you frame that. So So yeah, I would always start at number one. And I've talked to a variety of people about this, including dieticians working professional teams, high-level athletes or casual people, just like you said, all different contexts.

20:51And the number one question is always, what do you have available? Sometimes that provides the full answer. It's like, well, we only have this one method available. It makes it pretty simple. It's like, hey, use that method. Here are some strengths of this method, some limitations. Here's the way you can maximize the quality of the data you get from the method. that often relates to testing procedures. So actual pre-assessment standardization, understanding the amount of technical error in a measurement. So, you know, when a true measurement has, has occurred and those principles would be true across methods, but again, different methods are susceptible to different degrees.

21:25So yeah, again, first I'd say what's available to you. The testing frequency matters as well. There might be some people who can gain access to a DEXA, but either because of cost, you know, location, even regulations, they may not be able to have that performed on a cadence that would be helpful to them as they try to track a body composition change. So the availability, the cost, I think is a huge factor. Now, for those who do have access to everything, you know, a lot of a good argument could be made for DEXA being a very, very much a preferred device in that it is relatively robust against assessor error.

22:06So it's fairly automated. As long as someone is positioned correctly, they have the same model, the same software used over time. The accessibility here in the States is decent because there are a number of fee for service locations. So it could be cost prohibitive for some individuals, but for some individuals who have the finances for this and are interested, you know, maybe it would be a hundred dollars every six months or three to six months where they could go in and get a scan. If they can do this at one particular location, that may be a very good method for them. Others, it's like that that's not accessible.

22:37I want something at home. And then you have to get on the accessible side. You have to get into this conversation of, do you have some type of trained assessor? Something like skin folds could be a great method. If you have a trained assessor, if you have standardization there, if not, then you may have to think about more automated method, be that phone-based 3D scanning, an at-home by impedance scale. But as you get into some of those consumer devices, you definitely would like to see some research support, and this is part of what our lab does, some research support for the validity and the precision of these individual instruments to make sure that the data is actually helping you as opposed to hurting you and having you base, you know, body composition changes off something very practical and not really measurable, but saying like, okay, how my clothes fit, how I look in the mirror, how I feel, because there are some devices that are worse, worse than that, that they could be providing information that's maybe actually more harmful than beneficial.

23:28Danny Lennon: So when we think about that, and again, I do later want to return to those particular practical questions many people should ask of whether they need to go down that route or not. But in the case that someone is going to use some type of assessment and they're thinking about this concept of accuracy, as you already mentioned, every method is going to come with some degree of inaccuracy. We can't have a perfect number that we have certainty over in any of these. And I think sometimes maybe there's a lack of appreciation of that difference between the accuracy on that individual level versus a method that, let's say, has group validity.

24:04Danny Lennon: So can you maybe just explain to people how we could have a method that is well validated at a group level, but still doesn't necessarily mean that it has this high degree of accuracy or the ideal amount of accuracy that this person might be striving for and just how to think about that practically? Yes, absolutely. So I'll start kind of with an example, a hypothetical example. But I will preface it by saying that on the research side, there are essentially different metrics we look at that will answer these different questions of the group level accuracy and individual level accuracy. So if you are really getting into this and you're wanting to look at, say, for a consumer device that has been researched, there might be different metrics you look at for individual level accuracy if you're wanting to employ this for yourself, for your own monitoring, as compared to, you know, you're using this in a research setting with lower resources and you're just trying to know if the method can track a whole group.

24:59Yeah. So for example, let's take a method. We'll just say for the sake of easy comparison, say we're taking an at-home body fat scale, so bioimpedance scale, and we're running a study, we're comparing it to DEXA. So say DEXA is our reference method we have available. At the end of the study, we test that 100 people. At the end of the study, we find that the average body fat percentage with DEXA is 25.0. Average body fat percentage with the at-home bioimpedance is 25.2. So 0.2 % different on average. This looks great. We look at the correlation. There's a very, very high correlation. So we have a correlation coefficient of 0.97 with one being perfect.

25:36So like very strong correlation. We do a pair T test. There's no significant difference. We do something called equivalence testing. We see that these are equivalent. The issue is all of these are group level assessments. So what you'd really want to see here, what's very illuminating is if you look at, again, there's some metrics for this, but if you looked at a plot of the data, the data visualization, if you just plotted on the X and Y axis, each of these methods, so DEXA and the consumer by impedance, you might see that there's a strong linear relationship overall. But as you look at the individual points, it could be very messy.

26:07There could be a large number of individuals who are overestimated by 10%, a large number of individuals who are underestimated by 10%. And it just so happens that some of these large overestimations of body fat and some of these large underestimations essentially cancel out. So on average, this looks good. But when you look at how many individuals actually had a very similar value on their little data point with DEXA and the consumer by impedance, it's a relatively small number. And again, this cloud of data looks fairly diffuse, fairly spread out. That would be an example where it's like, okay, it looks like group level validity.

26:39And some researchers, you know, either just mistaken or maybe trying to present a more positive view of a method could just focus on those group level results and say, there was no significant difference. These average values are really similar. This is a good method, but through the data visualization and looking through some other metrics, some examples here would be the standard error of the estimate, or even better, what we call the total error or root mean square error from Bland-Daltman analysis, which is a really common analysis. When you're looking at method agreement, there's something called the 95 % limits of agreement.

27:10That's virtually always calculated. And it's kind of a way to quantify what I was just talking about on that spread of the data or the spread of the differences. So all that to say, yes, you could certainly have a device that looks or that is valid at the group level. But for you as an individual, the hard thing is you don't know what data point you are. You don't know if you're that data point that's being would be measured just the same with DEXA as this at home body fat scale, or if you're one of those data points that's way off. And this is all kind of based on one point in time, we can get into a conversation if you'd like about how much this matters in the context of tracking over time.

27:43But I love that you brought this up because it is a really underappreciated point when we're talking about body composition.

27:48Danny Lennon: And we will certainly revisit that concept of tracking over time. But one of these things that I did want to ask before we move on is that you've mentioned that essentially we're looking at estimates here. And anytime we're estimating something, there's going to be a set of assumptions built into that. Given that in many of these applications where we might want to look at body composition, often that's in, let's say, elite level sport, maybe, where we can oftentimes have individuals that are very muscular or very lean or at the extremes of body mass just generally, that would be different maybe to a general population case.

28:24Danny Lennon: And so I'm just wondering, in those situations, or really any situation where an individual has an extreme in terms of any type of body composition relative to the norm, what are the assumptions that most likely are at risk of failing that are built into some of the estimates we typically make, if that makes any sense. It does make sense. And you're absolutely right. In general, when we look at devices, we'll often see from this Bland-Altman analysis I was just talking about, we'll see something called proportional bias, meaning that the level of agreement between two methods depends on level of the quantity of whatever variable you're assessing.

29:01So for example, body fat percentage, it'd be very common for devices to perform reasonably better in kind of the middle of the population, the middle of the distribution for bifat percentage, but in those who are very lean and those with very high adiposity, they may perform much worse. Those who are lean and muscular are a particular challenge because they are not typically well represented when we validate these methods in the general population, unless you specifically go out and seek them. So, so broadly, virtually always, and again, remember the background here that most of the methods we're dealing with are at the molecular level.

29:35As we talked about before, we, once we pull out fat mass, we have fat-free mass left, but there are a lot of different components in fat-free mass. So again, the water, the protein, and the mineral being particularly important. Usually where we see deviations from the assumptions these methods use, it is in the characteristics of the fat-free mass. So this would mean the proportion of water, protein, and mineral within the fat-free mass. Those directly affect the density of the fat-free mass. So if we think about something like bod pod or underwater weighing, we have this assumed density of fat-free mass.

30:11And if we have these different proportions of the components of fat-free mass, that will affect the fat-free mass density and kind of propagate that error into our final assessments. Same thing for bioimpedance. It's really heavily based on this water estimate. If someone has a higher or lower proportion of water within their fat-free mass, that will influence the estimate. So we know from, you know, historical cadaver research, what we think like chemical dissection of cadavers, what we think that the typical value is. So for example, it'd be about 73 % of fat-free mass is typical, typically total body water.

30:45However, we do see certain athlete groups where it's higher, some where it's lower, but in general, again, broadly, if I had to say, you know, whether it be it obesity, be it kind of growth and development, be it elite athletics, typically where the variations are in these fat-free mass properties because it really is a variable component. And virtually all methods have some type of assumptions baked in regarding the characteristics of fat-free mass.

31:09Danny Lennon: So given some of the things you've already mentioned that can influence some of these, for example, you mentioned the role of fluids, therefore we can think about someone's hydration or glycogen levels, so therefore someone's carbohydrate stores at any one particular time. Among those, what are some of the other things that are most likely to have a role here that we need to account for? Or maybe put another way, if we ideally want to try and mitigate random fluctuations or noise in our data, what things would we ideally like to standardize in people that are undergoing some of these, for example, ADEXA?

31:47Yeah, so great question. So here we're transitioning. We've been talking about errors and the estimate kind of inherent to the technology. So these have been kind of like technical errors we've been talking about. Now we're transitioning to an important point that applies to virtually every method, and that's biological errors. So as you mentioned, things like water and glycogen are, they're dynamic. So these are not static quantities, particularly throughout the day. We have things like changes in blood flow due to physical activity and exercise that can influence methods to varying degrees. And this is where understanding a little bit about the underlying method can help.

32:21But yeah, so the perfect scenario, so like in research, when we're doing this, we want individuals to report to our lab after an overnight fast from food and fluid. Actually, we try to have them hydrate, well hydrated from the night prior. So they'll start their fasting period. But before that, we try to have them ingest some extra water to promote tissue hydration. But we want to avoid actual acute water consumption in the hours leading up to their assessment, particularly with devices that have an integrated body mass scale. So like these modern bioimpedance devices, like an in-body, for example, that are, have this scale built in.

32:56We've done research showing that it can influence the measurements meaningfully if someone has consumed water within a few hours, because it's immediately detected as the increase in body mass, but the electrical currents don't always fully appreciate that. So anyways, we'd have people report after an overnight fast, ideally eight to 12 hours from both food and fluid. typically we ask for abstention for the whole prior calendar day from vigorous physical activity and exercise meaning that we're hopefully getting at least a 36 hour abstention from physical vigorous physical activity and exercise and this can be due to a variety of things very acutely this would be related to things like changes in blood flow so if you think about and we've done some research in this area someone going in and doing a lower body resistance training session they have the pump their legs are pumped up and say you know sometime shortly after that they have a bioimpedance test performed.

33:46You can understand how that increased blood flow, the change in volume of the leg itself would influence these parameters. But even stretching out longer than that, we want to avoid situations where we would have potential edema or muscle damage, particularly from unaccustomed exercise. Now, of course, we have practical constraints. If we're doing research with athletes, sometimes it's not possible to have them abstain from exercise for a whole calendar day. So of course, we work within the constraints we have, but generally facet from food from fluid and fluid, other substance ingestion, and the rest from exercise are the major components.

34:19Out in the real world, when that's not possible, typically we recommend is that you just standardize what you do at every assessment. So if we're working at the clinic and they have patients coming in in the afternoon and it's not possible for them to do an eight to 12 hour fast, having some procedure, like even reminding them saying, try to eat similar meals on the days of your visits each time. If you can write down what you eat, if you can fast for at least three hours before your visit, if you cannot exercise that day, you're still taking some steps towards reducing this biological noise, even if you can't do it perfectly.

34:50The worst case scenario is you provide no input. So someone walks in for an assessment at 4 p.m. and you have no idea what they've done that day. Maybe at one assessment, they were just kind of hanging out at home. They actually pretty much would have followed the restrictions you gave them. Another day, they exercise visit vigorously. they ate much higher sodium foods, a number of factors were different. That can cause an artificial change in body composition, or it could mask a real change in body composition and make it look like one hasn't occurred. So these are particularly important for this longitudinal tracking.

35:20At one point in time, it would produce some error, but the bigger issue is if you're trying to track particularly relatively small changes in body composition, some of these errors are large enough to completely obscure the changes you're actually trying to detect.

35:32Danny Lennon: And that was something I think I was actually going to touch on that, given that we have some degree of noise in our data, we want to do all we can to minimize that. At an individual level, that is very tricky to do, as you've outlined, that there's many things we can do within research at a group level that really can help. At an individual level, it's a bit trickier. And so one of the things you mentioned is the importance of having multiple testing over time, as opposed to relying on just one particular data point. And then between those different tests, having standardization. But as you mentioned, if we have athletes and we're looking at some of these components of body composition where changes over time may be relatively small, given that there is some of this measurement error, for you when you are doing some of these assessments or what you might recommend to people who are working with teams or athletes that might be doing this over time, what would be the amount of change we would need to see in order to be confident that is a true change or there was some change relative to measurement noise or how do you account for those things over time?

36:37Yeah so this is a fantastic question and one people probably don't think about enough. The answer on what amount of change you'd need to see is specific to the technology, the specific model, the procedures implemented in a facility, and essentially every unique characteristic of the assessment. So the way I recommend, so again, if I'm talking to a dietician for a professional team, they're trying to get at this idea. What I recommend is doing some, what we would call between day reliability testing. So ideally let's, we'll make this simple. If you could take a group of 10 people and following the procedures that they're going to be following longitudinally.

37:16So if that's an eight hour fast, say it's just an eight hour fast and eight hour exercise abstention, say that's all that's reasonable. And you're going to try to assess them in the morning. So you have them conduct those pre-assessment procedures. You assess them in the morning. You have them go about their business. You have them come back the next day or two days later, same thing. They follow the same procedures. You assess them in the morning. And you do this with a group of people. You will see that we're performing these assessments on back-to-back days or maybe one day in between, it is too short of a time period for a true detectable change in body composition to occur.

37:48However, because this is on separate days, instead of bringing someone in and just testing them twice back-to-back, we know that there is some biological variability in the individual's day-to-day based on what they're eating, what they're doing, and so on. Of course, we've implemented the fast and rest to try to reduce that, but it won't be perfect. So what we'll see, say from those 10 individuals or say even better, 20 individuals, we'll see these differences, say in body fat percentage between these days, you could just look at those. If you didn't want to run any stats on this, you could just look at it and say, okay, between days, the largest difference in body fat percentage we saw was 2%.

38:23We know there was not a 2 % change in body fat. All the other changes were less than that. You could be very conservative and say like, okay, any change less than 2%, we're going to say, we know that amount could happen just within a day or two, even following our procedures. So if we see a change of 1 % after eight weeks in someone, we're going to interpret that as no change. We're going to say this was within the error of our facility. Now, of course, from those differences, you can run some actual stats on it. You could get different technical error measurements that would give you not just the worst case scenario, but what would be more of a typical scenario.

38:53So say from that, you got 1.25%. Then same thing, any change, gain or loss, lessen that amount. You could kind of be the gatekeeper, so to speak, and say like, okay, for my athlete, for my client, I'm going to interpret this as, you know, there was no change in body composition. Everything was like within the air of our device. Now, conversely, you see a change in of 3%. You're like, okay, the largest we've ever seen from these kind of between day biological errors was the largest was 2%. And say, maybe from one of these other metrics, we're looking at like 1.25%. We're now feeling quite a bit more confident.

39:25We're like, okay, this has exceeded what we saw, the largest amount we saw in these days, it's exceeded kind of our between day error metrics, then you feel more confident. And you'd still have the caveats that, you know, this isn't perfect. It can be influenced, blah, blah, blah. But it looks like you have actually lost body fat more than what we'd expect for the error of the device. So because it's so specific to the facility's procedures and the device you have, I always hesitate to give a number and say like, oh, in general, you know, 3 % body fat, because the tighter your procedures are, the lower that number can become, particularly with a good device.

39:57The messier procedures are, you know, the worse, the larger change you'll need, or the worse your device is, the larger change you will need in order to be confident that a real change has actually taken place.

40:07Danny Lennon: Fantastic. And speaking of advice that you give to sports dieticians and people working in practice, one maybe more specific question on the actual measurement that I had from one of our regular listeners, Emily McKay, was asking about this. I thought you might be the best person to address it, specifically in relation to the use of BIA device so it in this case i think she's using a four electrode bia device and was wondering about how to interpret or the the utility of looking at the phase angle within this so maybe for other people coming from outside that maybe first you can explain what we're talking about here with phase angle as it relates to this device and then what would be the best way you would recommend to clinicians or dieticians who are using this how they interpret that within this broader measures that they're getting.

40:58Yeah. So phase angle is very interesting for, yeah, for anyone who's not familiar, phase angle would be considered what we call a raw bioimpedance metric. So this means it is calculated based on the actual raw information that's obtained by someone when they perform a bioimpedance test in contrast to something like getting a body composition estimate from bioimpedance, where you would take that raw data and plug it into a series of equations that were developed in general population. So the attraction here is you're kind of just using the individual's own data. The downside is a little bit less interpretable.

41:32If I tell you, you have a phase angle of seven degrees, that doesn't necessarily mean a lot to you immediately. But phase angle is calculated from two different individual electrical components called reactance and resistance. Reactance is roughly the ability of the cell membrane to act as a capacitor. So to temporarily hold and then release an electrical current. And then resistance is maybe what we traditionally think of with impedance, which is just kind of the opposition to electrical flow through body tissues. So phase angle is a calculation based on that. You do get the output is in degrees and a higher number is better.

42:09A lower number is worse. Roughly on the interpretation, the current view is that phase angle is essentially this non-invasive metric of cellular integrity in cellular health. So where it has been best established in the research is in kind of clinical care, intensive care, surgery, those types of applications where it is a pretty good prognostic indicator with those having higher phase angles, having say lower mortality, quicker discharge from the hospital, better recovery and so on. I would still say a higher number is better like in the wellness area, but I'd say it's a little bit less established how much unique information phase angle provides beyond like a body composition estimate.

42:52But in principle, I do like that you're using the raw, someone's raw data. In terms of how you interpret it, we've done some research on this with different bioimpedance devices. I'm glad you mentioned the type of device. So if this is, you know, a traditional like four contact points, this may be one of the supine analyzers where you have the adhesive electrodes you stick. We found that, of course, between devices, we see differences in phase angle, we've seen some pretty large differences with supine versus standing analyzers. So a major point here would be that you can interpret phase angle relative to reference data, but it needs to be from similar devices.

43:26So there's some large, there are publications that pooled across a bunch of different studies and produced reference values for those traditional supine analyzers with the adhesive electrodes. Some of the modern vertical analyzers, again, like, you know, Embody, Cica, Tanita, and so on, they will often have a reference database built in, which is nice so that you will get your phase angle and they will, from a large group of people assess with their same device, give you something like a percentile. So they would tell you whether this, you know, what percentile, this seven degree phase angle falls in.

43:57So if you are interpreting it, I'd say you have a couple options. One is interpreting the change in individual over time. If you're like, okay, we do like this metric as a non-invasive indicator of cellular integrity. I'm going to track this over time. Everything we said about standardization would still be true. But if you see this metric go from seven degrees to 7.2, that'd be viewed as a good thing. The other option would be like at a single point in time, trying to compare to reference data and saying, okay, where does this person fall within the population? That might be more relevant to the general population.

44:27Again, in athletes, you would typically see like more favorable phase angle. So this is again, where I'm getting where I'm not, I like phase angle, but I'm not 100 % sure how much unique information it provides beyond looking at this person like, okay, this is an athlete. I can tell they have above average body composition, say lower body fat, higher muscularity. I see that in my assessment also, how much additional information you get by also knowing they have a good phase angle. I'm not entirely sure, not entirely convinced of that, but there's certainly nothing wrong with looking at it as one of, you know, several metrics you're interpreting for a client or an athlete.

45:02Danny Lennon: So there's these different levels that we've talked about one is one specific conversation could be had around the measurement that goes on within research and the important nuances within that then we can think about at the level of people who are doing testing for groups of athletes or for organizations now what we're seeing has always been the case but now even more so with people be becoming more interested in trackable data for themselves and with more and more direct to consumer different devices available when it comes to body composition specifically are we potentially at a risk where as more devices are more available there's more access to them each of them promising more than the last that rather than getting people cleaner or more usable or interpretable data let's say that we're adding just noise in situations where those people don't have the background to interpret all the data that these are coming from, or at least understand some of the things we've discussed, right?

46:05Danny Lennon: Measurement error and then how to place that in appropriate context. How do you feel about the increasing accessibility of some of the typical advices that are most readily available at large scale to the population? Yeah. So this is an active area of research in our lab. So I'll start with kind of just an overview of some technical results, and then I'll bridge into like whether or not this is a good thing. So a few years ago, we did a trial where we included 14 different at-home body fat scales. So BIA scales that are consumer grade. So ranging from about 20 US dollars to maybe 250 or 300 US dollars.

46:39And it is really interesting. I was actually surprised at the results I was going into. I was kind of expecting these are all going to be terrible. And they looked very similar in terms of the hardware. Some were only foot-to-foot electrodes, some were foot and hand electrodes, but within those categories looked very similar. we saw enormous range in the results. So there were some that were predictably terrible, like worse than not having the information. There were some that were really good approaching or in some cases even exceeding what we'd see on like a laboratory grade biopédense device.

47:10And sometimes like if you looked at the two of them as a consumer, they'd be indistinguishable. They were different manufacturers, different model numbers, but there was not a defining characteristic where it's like, oh, all the ones that look like this were pretty good. The ones that look like this aren't. So a major conclusion from that is that really the devices have to be evaluated individually. We just performed a follow-up study in over 200 individuals with, because this was the first study was a couple of years ago. And as you know, devices fall off the market, get introduced to the market and so on.

47:37So we did this trial again, and we are about to submit that for publication. And similarly saw that in this case, we tried to only focus on more established manufacturers because those ones tend to perform better in the first study. but even there we again saw this this huge spread where we we don't have characteristics of the method itself for these at-home bioimpedance scales that could reliably tell you whether or not they they are accurate enough to potentially be useful so again this is a focus of my lab we'll probably continue doing this for a long time because it'll continue to be new devices but not that not every consumer will be able to do this or like think to do this but certainly maybe the listeners of this podcast that put you know like in the the well-informed like interested in these topics, I encourage you to look and see like, has this been tested?

48:21Because there are a number of labs that are just, you know, purchasing these devices and testing them in a laboratory context. We've also done tests with various phone-based 3D scanning, which would be another consumer accessible method. Now, kind of going back to your question, I think this is really important because the same way that we can talk to some individuals who maybe have kind of a body weight fixation and they're like weighing themselves multiple times throughout the day, even though as like scientists and practitioners, we know this is not helpful. We know that it's like, yeah, you, you eat and you drink and you do things, your body weight will go up during the day.

48:51This is not like a valid measurement, but people will fixate on that in a negative way. People can do the same things with the body composition readings and sometimes mistakenly think that it's like, oh, well, it's actually measuring my body composition. So like it's, you know, it knows. And also we have this added component that it's, it's giving you a very precise looking estimate. It might tell you you're 22.37 % body fat. And that gives the appearance that the machine is precise enough to provide that level of specificity on the results, which we know it's really not. Again, ideally we would have this presented as like, you know, this is 22 plus or minus 3 % is your actual range you're in.

49:30Interestingly, on the consumer side, we've seen that some companies are actually trying to prevent some of these issues. And this has been a challenge in research, we found out from these trials, there are some devices that it seems like the manufacturers have baked in, like we don't know, this is speculative, but from what we see in the data, it seems that they've baked in algorithms where it won't let you get a different body composition result within a certain amount of time. So sometimes when you've brought people in, tested hundreds of people on the same device like two times in a row, it'll be like the exact same each time.

50:01And the devices that are truly taking independent measurements won't do that because there's random variation in how well the feet are contacting the electrodes, all kinds of factors. But it seems like it's so consistent that I think there are some manufacturers that if they detect, okay, this is on the same profile, it's the same person, we're not going to give them a different result. And this could be, you know, protecting the consumers, it could also be in response to a common consumer complaint, which is, I have this at home body fat scale, and the number bounces all around. So it could be that they're smoothing it out.

50:29There's other methods that do like take into account your last five measurements, and it's kind of just trying to smooth out changes. So point being, from the research side, it's a challenge for us because we want each measurement to be truly independent. But in terms of like the consumer experience, something to be good for people to be aware of is that some of these devices are appearing to bake in some type of algorithms to eliminate those short-term changes or kind of smooth changes over time so that the numbers bounce around less than they did traditionally.

50:55Danny Lennon: Given that in research, it's very obvious that we want to have these different measures, have them as accurate as possible. And there's real utility to collecting a lot of these body composition data. Similarly, we could say the same thing about certain applications in elite level sport, maybe in clinical context, but for the average, let's say health conscious person, there's more of a debate then of how much is some of this information providing us beyond what we might just be able to surmise from someone's typical habits. Maybe they're the things you mentioned earlier, just their general body weight or even without body weight, their waist circumference, their general habits, and just looking to see if their body composition is trending in a positive direction or not.

51:36Danny Lennon: And then how much additive benefit we are getting from this. It is a great question. I think there's definitely at least a subset of individuals who are very aware of their body, their fitness goals, their nutrition, how they're close fit, how they look. There are people probably at this certain level of body awareness where you could probably make a strong argument that they will know sooner than a device can confidently detect if they are trending in a certain direction on body composition. I think there are other groups and maybe other body phenotypes, maybe people that are less in the fitness realm, where it might be quite a bit more useful to have this information.

52:14The weight loss context is a good example where a current issue that's been highlighted, though it's, you know, it's always been a consideration is an idea of the composition of weight loss. If someone's losing appreciable amount of weight, where's this coming from? We're now say with like modern pharmaceuticals, seeing magnitudes of weight loss where we can track these things more easily than say an athlete who's like losing three pounds and trying to peak. And we're trying to track these tiny changes in body composition. That's a different scenario and much more difficult to track than an individual who's losing like 10, 20, 30, 40 pounds or kilos for our metric listeners.

52:49So I think there would be groups of people where they would benefit from that information and say an initial flag where it's like, okay, you know, 50 % of your weight loss is coming from fat-free mass. We know fat-free mass isn't specifically muscle, but we also know that's quite a bit higher than like a normal benchmark we'd look at. Maybe that'd be, you know, warrant conversation about mitigation measures to try to protect skeletal muscle, even though it's not directly what we're measuring. So I think, again, you could, yeah, you could certainly make a case where it's like, okay, body composition is important.

53:16Maybe body composition assessment isn't important. I think there are lots of people. And again, in the fitness realm, I think there are lots of people who are very in tune and maybe don't have access to the most precise devices. You can make a case that they never need to measure. If you take an extreme example, like physique sports, you could argue, it's like, well, surely it's most important for them. They're like getting graded visually, you know, on their physique, but you know, many high level physique athletes don't use, don't need, or even don't like body composition assessment, but from their expertise, from their coaches and so on, they know what they're looking for.

53:46They know the level of leanness they need to get to. The number doesn't really matter, but it's like, okay, we're looking for this level of muscular definition and conditioning and whatnot. So again, I think especially in the fitness aware, there's some people that you could definitely not use it if you don't like it, if it's anxiety producing, if it's just not beneficial to you. But I think there are other segments of the population where there's probably less body awareness, different body phenotypes, different expectations, different things going on where the body composition assessment might be more beneficial than say just tracking body weight changes.

54:14Danny Lennon: So maybe on that note, and to finish with this, if we're thinking about people who aren't going to take some type of measures and maybe they are using those methods that either they can use at home or maybe they're going down the route of like you said, every so often getting a DEXA or a BODPOD at a local facility. What are some of the final things you would leave them with of when they do get hold of this data, how to use that in an informative way as opposed to falling for some of the potential risks we mentioned earlier related to that noise and i particularly enjoy that what you mentioned around understanding that there's really ranges here that we're talking about because that could be a point we could apply to any type of data point we're seeing with wearable devices nowadays that they give as you mentioned this kind of illusion of precision to because they get down to a decimal point whereas as opposed to a range of multiple percentage points whether that's a sleep score or whatever the case may be we see that across any of these data points that it's given as a very specific number and sometimes we we maybe fall into the trap of thinking it's as specific as that so with all that said if there are some things you could leave people with of how to use the data they're collecting in a most productive way what are some of the maybe pitfalls to avoid or some things you tell them to look out for?

55:31Yeah, so first I would say just appreciate that whatever values you're getting are dependent on the specific technology you're using. Not only broad technology like DEXA, BIA, BODPOD, but the specific model, the specific procedures and so on. So just be aware the absolute number is influenced by those things. Now, say you get a DEXA scan at a local facility, often they will have things like reference data from the same scanner built in there and it will give you something like a percentile. saying, you know, your body fat percentage is lower than 70 % of age, sex and race matched individuals. That is a helpful data point at one point in time.

56:10So like, if this is your first assessment and they provide something like that, I think there can be some helpful context there because those reference values from a device are typically produced with, with the same device. What I wouldn't do is like go online, find some random calculator and be like, okay, my body fat percentage is 25%. Is this good or bad? Or how does this compare? Cause it really depends on the technology. So for a first assessment, if they provide you with this, this can be some good context. DEXA, another example would be like with the bone mineral density. This is something that you can't really get from most other devices.

56:39That may be very helpful. Just that single point in time, be like, okay, in general, say like you're middle-aged now, in general, is this, do I have high bone density? Do I have like marginal bone density? Is it low? Just because that's something that doesn't change quickly and that would be good to have awareness of. So you can glean some information from that one point in time. If you are going to perform serial assessments over time, only compare the values if they're obtained from the same method. So say you got that DEXA one time, you're like, you know, I can't, I don't really want to pay for this again, I'm going to get at home scale.

57:10And you know, I was 29 % on the DEXA, I got an at home scale a few months later, and I'm 22%. I've lost, you know, 7 % body fat, you really should not compare across devices. So if you are transitioning to a new device you're tracking with, just treat that first assessment as your new baseline, as tempting as it could be to compare, it often causes problems in one direction or the other, either saying like, yeah, I lost all this body fat when maybe there's just a systematic difference. Or conversely, someone has been tracking at home, and they go in and get a DEX and the DEX is much higher and they feel like they've, you know, their body composition has deteriorated.

57:41So again, if tracking, use the same method over time, then the items we talked about earlier with preassessment standardization, just be as particular as possible, especially if you're doing it at home, We're talking like first thing in the morning, you know, same clothing or no clothing, haven't eaten yet, haven't had anything to drink yet. Just everything you can standardize, even if you're not positive exactly why each of these factors can just reduce some biological noise and make it more likely that you get clean data. And then I would say, even if you do all those things, I would interpret your data cautiously.

58:12So I think about how you're feeling, how you're looking, if you're performing the way you want to in terms of exercise, if you have other health markers, say from regular checkups, I would, I would consider all those things with at least as much weight as the body composition. So this should really just be one, one, one data point. If you are like, okay, I feel good. I feel like my nutrition has been dialed in my performance in gym feels good. Like I feel like I'm looking better. My clothes are fitting better. And you see a body composition value that moves in the other direction. I wouldn't, you know, jump ship, abandon ship, change your whole program.

58:43I would, I would think about that holistically and be like, Hmm, maybe, maybe this measurement was off. You could take another measurement, you know, standardized in a few days, see if it's different, maybe if that was an erroneous reading. But even if it wasn't, I'd interpret holistically and just understand there may be times you want to de-emphasize the body composition result. And this is particularly true with a small result. So again, that same idea, even if you can't perform a study of 10 or 20 people seeing how different the day-to-day values are, you could even do some self-experimentation.

59:11If you have a scale at home, be like, okay, I'm going to the same way every morning assess body composition every morning for a week. And I understand my body composition isn't really changing, but I'll see the range of these variables over week, maybe even average them and be like, okay, this is kind of where I'm at. And you can have that context moving forward, seeing that those values may have jumped around day to day, even though you weren't having true changes in body composition over that time. So it's kind of a lot of points, but big zooming out to the big picture, I'd say body composition is important, but if the measurement produces anxiety or isn't informative, doesn't seem helpful or doesn't add any information you don't already have, then it's certainly not necessary.

59:46With that said, some do benefit from it and can find it to be a useful either motivator or an actual useful data point that would give them information that they wouldn't otherwise have.

59:55Danny Lennon: Fantastic. Grant, with that, for people who do want to keep up with anything that you've got going on, stuff that your lab is producing, any publications that you have, where are some of the places on the internet they can find you and your work? Yes. So Instagram and LinkedIn would be the best places. So on Instagram, my handle is grant underscore Tinsley underscore PhD. And I'll post about our research, some occasional like, you know, fitness lifting type things, just other kind of scientific collaboration stuff with my students on there, as well as LinkedIn, which is just my name, Grant Tinsley.

1:00:25And then I also have a personal website, which is just my name, granttinsley.com, where you can see my CV research, read some information about me, and I'll have links to these same social media sites.

1:00:37Danny Lennon: Fantastic. And for everyone listening, that will be linked in the description box. And you can go and click through and check that out now. With that, that brings us to the final question I always end the podcast on, which can be to do with anything even outside of what we've discussed today. Broad questions, apologies for putting you on the spot, but it's simply, if you could advise people to do one thing each day that would have a positive impact on any area of their life, what might that one thing be? Oh, that's great. You know, I remember you asking that question from years ago, but I've forgotten about it when I listened.

1:01:08Yeah. So I would say probably my biggest advice here be to, not to sound morbid, but to slow down and kind of think about our own mortality, to think about how small we are in the scope of the entire universe, to think about how short our lives are in the scope of the age of the universe. And to just think about how that should inform what we're thinking, how we're living, how we're treating others. I think it's some really good context that doesn't have to be morbid and sad, but really helps us grapple or it helps me, I'll say it helps me grapple with my worldview. How do I actually view the world?

1:01:41Why am I making the decisions I make? What am I prioritizing? What am I choosing to care about a lot? What things am I choosing not to care about? So that's probably what I'd advise. I think in today's day and age, it's so easy to get distracted with the pace, the fast pace of life with constant access to email and social media and entertainment. I think slowing down and having time of like quiet and reflection and just thinking about your place in the universe and grappling with those hard, you know, metaphysical questions of, you know, why we're here, what is our purpose? What are we doing with our lives?

1:02:12I think that is enormously beneficial and has a payoff, even if there is some sometimes distress involved through the process. I think ultimately it will lead to a place of more awareness and hopefully a greater search for truth and also living in alignment with truth in our own lives.

1:02:27Danny Lennon: Fantastic. What a brilliant way to finish. Dr. Grant Tinsley, thank you so much for taking the time out to do this, for the fantastic work that you've done and continue to do. It's very much appreciated for everything you've put out into the field. So thank you for doing this. I really appreciate it. Of course. It's an absolute pleasure, Danny. Thank you.

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