Alan Aragon: In order to truly be scientific, you can't have a closed mind. And you have to realize that science and its conclusions are tentative. And that's why we use language like may and might all the time, because we try to avoid absolute certainty on any position. So anytime that you find yourself absolutely certain of something, a claim or a belief, then you kind of automatically close the door to further investigation and that's not good as far as the march of knowledge goes.
Andres Preschel: There is only one supplement that I think almost everyone on this planet should be taking and that's a full-spectrum and highly bioavailable magnesium supplement because, well, let's face it, ever since the industrial revolution, our soil has been depleted. of magnesium and therefore our food is depleted of magnesium and on top of that our modern environments which are inherently overstimulating and stressful are constantly depleting our body of magnesium and unlike other nutrients this is not something your body can produce on its own it literally needs to get it from the diet. And one individual kind of magnesium alone is not enough. You actually need seven different kinds to support over 300 biochemical reactions that help regulate your nervous system, red blood cell production, energy production, managing stress and emotions, etc. And so the folks at Bioptimizers have made it very easy and convenient to add back in what the modern world leaves out. They've created Magnesium Breakthrough. Now I've been taking this for the past two years and the biggest benefits that I've seen are related to my evening wind down sessions and my sleep. I tend to be pretty overactive in the evenings, just totally overthinking everything that I do. And this has helped me wind down and get more restorative, more efficient to sleep. So I wake up feeling way more refreshed, more energized, more clear, more ready for the day. And the way that I see it, sleep is upstream of essentially every other health and wellness related habit and decision. Because if you're sleeping better automatically, you're gonna have more regular cravings. You're gonna have higher insulin sensitivity You can derive more of all these inputs like fitness, right? You make more gains you gain more muscle you burn more calories and you wake up feeling refreshed so that you can do it again and again and again and And then beyond the fitness, you have more energy to go for a walk, to do fun activities with friends. You are less stressed, so you can socialize anxiety-free. And you're also going to be retaining, refreshing, and refining your skills and information much, much better, so you won't forget any names. And, yeah, I mean, like I said, over 300 biochemical processes that you're supporting with magnesium. Then sleep, I mean, wow, better sleep is just a better life in general. So, I found it extremely helpful on a personal level and I'm sure that you guys will find it helpful too. Your mind and body and maybe even your spirit will thank you. So anyway, if you want to get a sweet little discount off of this amazing, amazing magnesium supplement from Bioptimizers, all you have to do is visit the show notes. So you scroll down right now, takes just a couple seconds and boom, you'll have access to all seven different kinds of magnesium that your body needs. All you have to do is hit the link and use code KYP from Know Your Physio. KYP. That's all. Enjoy 10 to 22% off depending on the package you choose, whether or not you subscribe. I'm obviously subscribed because I don't even want to think about whether or not I'm going to get this essential supplement in the mail. And yeah, hope you guys enjoy that awesome stuff. And that's all for now. I'll see you guys on the show. Alan, it's a pleasure to have you back on the Know Your Physio podcast. We had you on here last year, and it was one of our most viral episodes. I think that was something that I honestly expected considering that your ability to take research, make it so actionable, so accessible, And really, frankly, so sexy is a really fun way for us to do right by our intentions and find a process with regards to our health and well-being that makes sense while still reflecting what the research says, what the research stands for. So I think you are a master of finding that blend. You inspire me so much. And since that episode, I've had a chance to dig into your newsletter, research review on a on a weekly basis, a monthly basis. And it's been incredibly helpful for me, you know, to stay on top of the best and latest and the most established. So thank you so much for taking the time to join us back on the podcast and excited to dig into some cool stuff today.
Alan Aragon: Thank you so much for having me back, Andrew. And I appreciate that you're a true student of the game, a true connoisseur of the sport, so to speak. And it's great to see that you're continuing to learn, despite the fact that you're at the level that you're at. And I think it's really important for people to really never stop digging and never stop learning. And you're a great example of that. And I really appreciate you having me on the show.
Andres Preschel: Making me blush, man. It's an honor and pleasure, man. Seriously. So I'll tell you what, there's a lot of topics that we want to cover today. But I think one of the most important thing for us to cover for the folks tuning in is this new year and all the stuff that we're going to get into this year regarding our health and well-being, you know, everybody sets big goals. And I think that one of the things that holds most people back from attaining them is following the right process and also being held accountable and developing that discipline and consistency. But I think that if you can find a process that makes sense to you, so for example, a process that is supported by research and data, then the follow-up steps, the subsequent steps that you take become a whole lot easier. So that being said, what are some, let's say trends, both online and social media and in the research that you want more people to be aware of? Then what are some trends that you want to see less of perhaps either on social media or in the research or both?
Alan Aragon: Okay, so the trends that I want to see people getting more involved with, one of them would be simplifying their approach to nutrition and training. And this is directed at coaches as well as enthusiasts and coaching clients as well. It's like Just because something is more complex or more fancy or has more rules doesn't mean it's necessarily better. And oftentimes it's a lot more of a pain in the butt and therefore it's less sustainable. And this goes for nutrition as well as training protocols. Training protocols that are, for example, overly detailed, overly periodized, and overly micromanaged. And the same thing goes with nutrition, where when you're looking at very rigid rules with respect to food choices, very rigid rules with respect to macronutrient composition, very rigid rules with respect to the timing of macronutrition or food groups or food sources according to the time of the day or the time of the week. Very rigid rules with respect to the linearity or non-linearity of intake through the course of the day of the week. Very rigid rules with respect to the length of the time window during the day. Very rigid rules about when that time window should exist in the day. All of these things All of these rules, they can really bog people down, especially, and it is unfortunate because most of them don't matter beyond the overall diet by the end of the day, what you're consuming in terms of food choices and whether that total composition of the diet is conducive to your specific goals. And of course, specific goals range the gamut from the general population person, this archetypical general pop person who just wants to be reasonably healthy and functional for activities of daily living and working, versus a competitor in some sort of a sport, whether it's a performance sport or whether it's an aesthetic sport. So I think simplification is important, but that's individualizing the program is always going to be important. Okay. So moving towards simplifying as much as possible, but not oversimplifying would be the thing that I want people to gravitate more towards.
Andres Preschel: How do we find that? How do we find that compromise that like that, that sweet spot? How do we find that?
Alan Aragon: Just being honest about where you are presently. Like as coaches in various disciplines, we try to meet the client where they're at and then progress from there. So what a lot of people don't have a good grip on is where they're at. So for example, if we take something that we can apply a simple number to, if somebody is used to sleeping five hours a night and they know that this is compromising their health and their quality of life and their performance and their ability to think and do what they need to do. It might not be realistic to try to jump all the way to eight hours a night right off the bat. So there can be an incremental progression there to find out what may be the convergence of optimal and doable for this person getting five hours of sleep a night. You'll have to break through a certain amount of barriers in their habits and routines in order to get them to get an extra hour in, for example. So meeting the people where they're at, realizing where you're at, and taking an honest look at where you are so you can progress from that point. I think that's really important. So the stuff in the industry that I feel is holding people back, well, there's a few things. Number one, general science illiteracy. So you can call it science literacy or scientific literacy, but what that is, is just a functioning or working ability to discern good information from bad information. And people need to, number one, want to have a working degree of science literacy and recognize the importance of that. And that is a challenge in and of itself. When you tell somebody, hey, you're scientifically illiterate, It's not a great way to start dialogue and get somebody interested in your point of view. But when you position it like science literacy is important for distinguishing good from bad information, because when you're able to do that at a fundamental foundational level, you don't have to be an expert in science. But when you have a working ability to be able to discern good information from bad information, then what ends up benefiting you is you now have saved yourself a lot of time and energy and resources and potentially risk to health. Just by having a basic ability to sniff out what's questionable information, what's likely to be high quality information after you read it through versus what is just flat out highly dubious, just bad information that's potentially dangerous. So it's important to be able to do that because once again, you save time, you save money, you lower your risk for health, either catastrophically or just insidiously over time. And so if people can embrace the importance of being able to save time, money, and lower health risk, then they can begin to see the value of being scientifically literate, not necessarily an expert, but just literate.
Andres Preschel: And more importantly, they'll have the peace of mind to engage like adults in common sections of these posts on social media. That's what everybody really cares about.
Alan Aragon: Can I relay something really? I just want to relay a little story. So I have a friend named Alan Bacon, Dr. Alan Bacon. He and his wife Beth run Maui Athletics, which is a coaching company, fitness, personal training, nutrition. And I've been doing collaborations regularly with him on Instagram. And he's really good with putting together these videos where you, in essence, peer review some viral clip from a guru who is, to us, obviously spouting off information passionately and with a tone of authority. And it's very convincing and it's obviously it's very shocking material that strikes all of the emotional cords. And when somebody is spouting off these really big claims that really touch the emotions, then these clips go viral. People send them to their aunts and uncles and moms and dads. Oh, gosh, did you see this? You got to see it. It's usually fear based. It's usually scaremongering against really dangerous foods like, you know, broccoli, oatmeal.
Andres Preschel: Oatmeal is peasant food viral video, huh? By a guy named Dave, and I'm not even gonna think everybody else knows what his last name is, but I'm with you, man. So what do you think is an effective way, in your opinion, and I don't think that there is a perfect answer for this, but what do you think is a good way to kind of Find the right blend of let's say virality. Like how do you make the right information viral? And how do you discern whether viral information is right or wrong? Like let's say let's put it this way. You mentioned previously the scientific literacy. Like what are some things that people should and maybe even need to see in a scientific study? Just at a basic level to know that, all right, there is some legitimacy to this. Like, is it a matter of saying, all right, this is a random match control trial versus systematic review? Like, what are some of the basics that need to be there so that we can tell whether the viral stuff is right or wrong?
Alan Aragon: Well, it's just a really, at the, you know, at a very high aerial view, people need to be able to kind of picture in their mind a hierarchy of evidence. with anecdote and non-peer-reviewed media being at the very lowest level, lowest tier of evidence.
Andres Preschel: So it's like, for example, in layman's terms, like, Oh, it works for me. It'll work for you. That's a red flag or saying, Oh, look, you know, making sure that like who's investing in the study or who's saying this and what might their conflict of interest be. Um, so kind of having that, that, that, that, that approach.
Alan Aragon: Think of it like this. Think of this lower tier of evidence, the lowest tier of evidence being like locker room gossip, like gym gossip, like just bros talk, bros talking. Okay. That's, that's right down there. Another, another, um- Wait, wait, wait.
Andres Preschel: Sorry. I, I, I'm, I'm promised this is one of the last times I interrupt you today, but hey, we're just two bros talking. So what are you trying to say? Right? This is the lowest possible level, right?
Alan Aragon: Take everything with a grain of salt. A grain of salt, man. No, but that is a great point, Andrew, because podcast conversations are low level evidence, you know? Okay, variable level evidence, depending on the guest. So somebody like myself who does research 24 hours a day and has been involved with that aspect of the field, gosh, for the last 10, 15 years, the research part, I probably have more value, my opinion has more value than somebody else who just has not been involved with it all. Uh, so now if I were to go ahead and pontificate about the finer points of, um, contest prep, I would say that, well, you know, take my observations with a grain of salt because that's not my specialty. I would point you to somebody like Chris Barakat or, yeah, competitive physique stuff.
Andres Preschel: Yeah, right, right, right. Okay.
Alan Aragon: Right.
Andres Preschel: Like while you're pushing components that might help someone achieve their goal, in a general view, you can't address every single point, everything to do with that kind of, you know, goal or incentive the way you can about, you know, nutrition, just in isolation, for all things health, longevity, and performance.
Alan Aragon: Yeah. A colleague of mine named Scott Stevenson or Chris Barakat or any of the other guys who specialize in that. So yeah, there's different subspecialties within this thing. So when you're looking at layers or the hierarchy of evidence and you're looking at these layers, what you and I are doing, we're discussing stuff and it is a variable. variable strength of evidence depending on who the guest is and what the topic is. So at the very bottom of the evidence hierarchy is non-peer-reviewed media, which disqualifies as non-peer-reviewed media. Another thing that qualifies as non-peer-reviewed media is blog articles, articles in the lay press, Editorials, opinion pieces that have not gone through the ringer of peer review. And so a step up from there on the hierarchy of evidence would be the stuff that does make it into the science journals. So the range of publications that make it into the science journals, everything from observational research, sort of the epidemiological research, under the umbrella of observational research, you have things like cohort studies, case control studies, cross-sectional studies, all the types of research that do not have an intervention component, where you're running a experimental group and comparing it with a control group, and there is a direct hand in the control of the variables, all the way to experimental research, which are randomized control trials. So within that mix, in the middle part of the hierarchy of evidence, you have the individual studies, whether they're observational or experimental. And arguably at the highest part of the evidence hierarchy is scientific consensus. The way that we get scientific consensus is we take a look at the evidence as a whole, not necessarily choosing our favorite studies or our favorite bits of evidence that support our preexisting beliefs. And we look at the evidence as a whole and we see whether it leans in one way or another. You know, we see whether this effect is significant or not, or meaningful or not, as it applies to whatever question we're looking at. And the way that we can kind of gain consensus is by looking at things in a systematic review type of way, or a meta-analytical type of way where we're pooling the data together and kind of seeing it for what it is and Is it a mixed bag of things where we're still kind of unsure or is there a consistency of findings in one particular direction as they apply to the question at hand? And so that is a snapshot of just having an awareness of what evidence is strong and what evidence is weak. So opinions, blog posts, random freaking podcast media, That's all questionable weak evidence that might as well be locker room gossip that falls on the lowest tier of the evidence hierarchy because it's not peer-reviewed by a panel of experts. It's not peer-reviewed by people in the field who are putting a red pen through the information for accuracy. verifiability according to the larger body of peer-reviewed evidence. None of that goes on with this lower tier of just basically hearsay, gossip, opinion pieces, blog posts, that sort of thing. And then you have the upper tiers of evidence that are peer-reviewed. And when I say peer-review, I mean essentially refereed or graded for accuracy. And the highest level of evidence really is the weight of the evidence or the consensus. Scientific consensus is important. And people who are untrained in this area will say, oh yeah, the consensus is not important because it's been wrong. Okay, well, yeah, we've been wrong. The consensus of a given opinion on one topic or another has been wrong. but at least it is a collective effort at the highest levels for objectively judging what the evidence is. At the very least, that's what it is, rather than a cherry-picked opinion based on emotion and hearsay. So that's the evidence hierarchy, really. And it's not the sexiest topic, it's not the most exciting topic, but people need to know it. because it's an important aspect of science literacy. And then it gets more and more granular as you decide to dive in and figure out how to judge information. So how do we judge information specifically if it is research that's being batted around in the news headlines? That's when it kind of becomes important to have a little bit more awareness than merely the evidence hierarchy where you have an actual ability to critically appraise research. And yeah, there's a method to that madness as well.
Andres Preschel: It sounds like a long-winded way of saying that you want to join me on the podcast at least another 30 times.
Alan Aragon: Sure, we can do that.
Andres Preschel: Research justice. No, but on a serious note, let's talk a little bit about these observational and experimental studies. You know, put simply, is this a matter of, let's say, looking at something like a correlation for the observational studies and then the causation for the experimental? Can that be, you know, down to the basics in that manner?
Alan Aragon: I wouldn't say it can be distilled down to it. I think it's more accurate to look at it like this. Observational research. So we can just sort of interchange observational research, which is called epidemiology. So you have strengths and limitations with observational research, with EPI. And with experimental research, true experimental research, in other words, the randomized control trials where you're running some sort of parallel arm experiment where you're comparing a intervention with a control condition. Those two have their strengths and limitations. So you have observational research here, experimental research here. We absolutely need both types. And I wouldn't necessarily place one type above the other on the evidence hierarchy. I wouldn't necessarily do that because I think just from a perceptual construct standpoint, I think it's more important to know that we need both and this is why. Experimental research is really good at looking at the processes and mechanisms that underlie the manifestation of whatever condition we're looking at. So experimental research, randomized controlled trials, they're capable of looking at the variables in isolation. And like you mentioned, establishing cause and effect between the variables. So now here's what randomized control trials are bad at. They're bad at looking at very large amounts of people for very long periods of time. Because with randomized controlled trials, there's a lot of manpower involved. There's a lot of attempts at controlling human animals involved. And there's just a lot of logistical challenges with randomized controlled trials. And so if you can get a group of humans to comply with a protocol for a few days, then hallelujah, that's a big accomplishment. If you can get a group of humans to comply with a protocol for a few weeks, then wow, you got pretty lucky. If you can get a group of humans to comply with a protocol for a few months, that's a miraculous achievement. And so with experimental research, those are colossally challenging from a logistical standpoint to pull that off. Now with observational research, you have a much greater opportunity to follow very large numbers of people, thousands of people, for longer periods of time, for months and years and decades. But what you do is you lose the level of the control of the variables. You kind of give up that control in order to be able to study disease endpoints and able to study habits over time that may or may not lead to disease and or death. So we need the experimental research to look at things closely, but we can't look at them for very long and we can't look at very many people at a time. We need the observational research to look at large groups of people for long periods of time and actually investigate endpoints like disease and death, whereas we wouldn't be able to ethically run those questions through people in experimental trials. However, we are giving up essentially we're giving up a lot of control and a lot of ability to infer causality when we're looking at observational research. So that's why we need both. And that is really the role of both. You can't follow disease and death very well through randomized control trials, but at the same time, you cannot establish cause and effect very well with observational or epidemiological research.
Andres Preschel: Thank you so much for describing the nuance there and the differences. And my follow-up question is, you know, if we look at, let's say, adherence to a program or lifestyle changes, like the North Star for us to realistically accomplish meaningful change in our lives. And then we look at the difficulty in these experimental trials, right? Like even in a clinical laboratory setting with the best scientists and the best equipment, even then it's difficult to really see a meaningful, measurable change in isolation. That being said, what should the average person, how should the average person interpret the process and the data in these experimental trials? in order to follow up with the research while still engaging in something that is realistic and that they can adhere to. So how do we form, put simply, how do we find the best blend of looking at these super rigorous control trials, but then also finding something that we can adhere to in isolation with no scientists around us, or very little testing.
Alan Aragon: Okay. So, these are really good questions. So, the challenge on my end is to be able to answer them without confusing people while putting them to sleep. And I'm up for that challenge. So, I'm here to help. Awesome. Thank you. So, one of the ways that you can do this, anybody can do this really, is to just kind of take a step back and say, all right, we're looking at a study. Is it a short-term response study? Is it an acute response study? So acute means short-term, the effect of hours or within a 24-hour period. Or is it a longitudinal study, meaning are we looking at adaptations over a period of weeks and months? So generally speaking, acute response studies are really good for generating hypotheses that are subject to further study and dragged through weeks and months in the longitudinal study process. So if something is just a short-term study, then you kind of say, oh, that's interesting. And there may be some mechanistic data we can glean from it. But are there any studies in this vein that look at the effects over a period of weeks or months? Because that's really what counts. It's always interesting to gain short-term data. And it's much easier to tightly control and look at micro mechanisms in short-term data. But what you really kind of want to know, if at all possible, is what are the chronic adaptations of this protocol or this product? So yeah, short-term versus long-term. And then you also want to take a step back And this is something that is pretty easy to remember or memorize. And this is maybe a first technical step into becoming scientifically literate, especially with experimental research. If you can memorize the acronym PICO, P-I-C-O, if you can memorize that and then you fill in the gaps, then you have begun to take a step into understanding research. So P stands for population. Who's being studied? Are these elderly folks? Are these folks with some sort of disease? Are these healthy folks? Are these young folks? Are these athletic folks? Are they untrained folks? Who's being studied? That's the P, population. And then I of the PICO acronym, I is the intervention. So what is being tested? What protocol is being tested? What agent is being tested? Is it creatine that's being tested? Is it a high protein diet that's being tested? Is it high reps or low reps, heavy load being tested? What is the intervention? What are we looking at? What are we testing? That's the I part, the intervention. And then the comparator. The comparator is what our experimental agent is being compared against. Is it being compared against nothing at all? Or is it, ideally, is it being compared against some sort of placebo? Or in the training realm, are high reps being compared with low reps? Or in the nutrition realm? Is high protein being compared with low protein? Are high carbs being compared with low carbs? So the C part of the PICO acronym is, what is the comparator? And it's either going to be some sort of alternative condition or protocol or agent, or it's going to be a placebo. Now, the O part of PICO is outcome. What effect are we anticipating? What outcome measures are we assessing? Like, for example, in the diet realm, if we're comparing a ketogenic diet with a high-carb diet, the O part, the outcome we may be looking at is either body composition, or it might be performance, whether it's strength or endurance, Or it might be both, if the study is ambitious enough. Or it might be some sort of health parameter, like blood lipids, blood glucose, cardiometabolic effects, any one of the very many parameters we can look at within the indexes of health. So that's the outcome. What effect are we assessing? What are we anticipating here? Is it body composition? Is it health? Is it importance? Or rather, is it performance? And what aspect of those things might we be looking at? That's the outcome. So P-I-C-O. We're looking at population, intervention, comparator, outcome. And some people add an S to the end of that, meaning study design. So what kind of design are we looking at? Are we looking at some sort of short-term acute response trial or are we looking at a longitudinal trial? And with the S study type, we can also ask the question, okay, is this an observational study or is it an interventional or experimental study like a randomized controlled trial. So when you ask those questions about a study that you see on social media, you can start with the population and go, oh, they're looking at obese sedentary people. Okay. What's the question I want? And is this population relevant to my personal interests or questions? Well, that depends on who you are and what you're asking, right? We can look at the intervention. Okay, they compared creatine versus a placebo. for gaining size and strength. You can ask, okay, is that important to my interests or not? And you can kind of go down the list to see whether the research study is even relevant to yourself or your clients or whatever debate you're having at the time. But when you run through the PECO acronym, then you can kind of begin to see the components of research and how they might fit in in terms of relevance to your interests. And I think that's where you can start.
Andres Preschel: Right. So, it's really, if you understand this acronym and you understand all these different criteria and, and how to look for these in the research, then you can understand what's relevant for you, why, when, and how. So, so it makes it really easy to understand.
Alan Aragon: Yeah. And what people will do What this is what you'll see a lot, Andrew, you'll see people waving around a study saying, Oh, look at this study. I got to change. Everybody has to change their entire protocol and way they live because of this study.
Andres Preschel: Yeah.
Alan Aragon: And that's, that's never ever true on a universal basis.
Andres Preschel: I mean, a lot of, I see a lot of biohackers treating themselves like drosophila, you know, like, like fruit flies, because they're one of the easiest populations to study, to reproduce and to see meaningful effect sizes. And so I, I, I frequently tell my biohacker friends, I mean, I'm a biohacker too. I like to imagine that I, well, I actually look at the studies, but I treat myself like a human being, not like a fruit fly.
Alan Aragon: That is a really good point you're bringing up because a lot of people, that goes back to the P of Picos. What's the population? All right. So let's imagine that the study is looking at rodents. Okay. Looking at rats or mice. Number one, you shouldn't discount a study on the sole basis of it looking at rodents instead of humans. But number two, you have to ask the question, are there any human studies on this question, on this topic? And if there are, then you can safely ditch all of the rodent data and move on to looking at the human data because A, rodent physiology, especially with regard to macronutrient metabolism, is so very much different from rodent physiology as far as macronutrient metabolism goes. And B, humans aren't rodents. If we have humans to look at, then let's look at the humans. And so, and a great example of this is the effect of carb restriction on rats and mice. There are several studies that look at zero carb diets on mice, low carb diets, ketogenic diets on rodents, and it really messes them up. It makes them accumulate fat in the liver. It makes them accumulate fat in the ectopic space where it shouldn't be accumulating. And it causes insulin resistance and all these things that you don't see when you put humans on a carb restricted or zero carb or ketogenic diet. And so there are profound differences in, um, carbohydrate and fat metabolism between humans and rodents. And it even goes all the way to, um, the receptors on key organs that play roles in nutrient metabolism, uh, between rodents and humans. You can, if you are really bored and you want to fall asleep, you can look up the liver X receptor difference between rodents and humans and you'll find just very obvious and drastic differences there at the receptor level between rodents and humans. And so that's why, to your point, Andrew, the population part of PICO is often where it stops. is often where the relevance starts or stops, whether you continue on with seeing whether the study is worth worrying about.
Andres Preschel: And I think it's really important to note as well how, I mean, you mentioned this earlier, how, you know, the science really goes through a ringer, like it quite literally gets beat up, right? When it's, when it's a peer reviewed, it gets beat up. It goes through several rounds. Sometimes it gets knocked out, right? Sometimes it prevails.
Alan Aragon: Don't I know it.
Andres Preschel: It really goes through those rounds. And that's something that you don't see on social media. So that's something that you don't see that doesn't appeal to the algorithm the way that, you know, that stuff that you're sharing with your family typically does. So, I mean, I think that alone really separates the men from the boys and the girls from the women. And, you know, I mean, I'm trying best to be politically correct here, but you get the point.
Alan Aragon: But I bite my tongue through that topic my man. Yeah.
Andres Preschel: Yeah, so so you're gonna say nothing on that so so anyway, I Think that alone will help a lot of people make the best decision about what they're gonna do and how they're gonna do it To honor these new goals that they might have especially this time of year You know the new year when they want to embark on some meaningful change in their lives they want to do right by their intentions and and they want to unlock these you know, improved abilities to look, to perform, to feel, to be, to live a long healthy life, etc. And then this, I definitely want to jump into some of the, maybe the stuff that most people might be tuning in to this podcast for, like the protein stuff and the muscle building, more of the sexy stuff, but I think it's so important that we cover this first. But I have one last question regarding this topic and it's actually some advice that one of my top mentors shared with me. His name is Dr. Wes Smith. He's the head of the nutrition and physiology program at the University of Miami. This guy is someone that I hold very dear to my heart and has changed my life and my standards for science in so many ways. And he shared with me this line and it goes, Um, just because something is lacking in evidence doesn't mean evidence is lacking. I don't know if he coined this line or not, but the point is like we might not have the, all the evidence to prove that something works doesn't mean that the evidence isn't there to eventually prove that it works. So what do you have to say about this and how can people maybe incorporate this into the science that they're looking at if they're not seeing something that maybe is what they want to see or that might be relevant for their, you know, individual case?
Alan Aragon: This is a good concept to raise. And I don't know if he came up with that quote. So the more traditional quote in that direction is absence of evidence is not evidence of absence.
Andres Preschel: Yeah, I think that's actually I think that's verbatim what he said. And that was my spin on it, which is pretty much the same thing. But
Alan Aragon: Yeah, yeah. So that is kind of an age old concept, which basically is saying that in order to truly be scientific, you can't have a closed mind. And you have to realize that science and its conclusions are tentative. And that's why we use language like may and might all the time, because we try to avoid absolute certainty on any position. So anytime that you find yourself absolutely certain of something, a claim or a belief, then you kind of automatically close the door to further investigation and that's not good as far as the march of knowledge goes. And another thing along the lines of what you raised is that research studies, we study groups of people, there's always going to be a different responses across individuals. So while you read the conclusion of a study, you read the results of a study on an abstract, for example, it's reporting the group average response. And so within any group, there's going to be individuals who hyper respond and individuals who hypo respond. and people who respond everywhere in between those two points. So it's a mixed bag of responses. And so study results, at best, can give you a starting point from which the individual can adjust after assessment over time. They don't give you a gospel number. And I'll give you an example with the protein research. Currently, the group mean for effectiveness, upper daily dosing effectiveness for resistance training adaptations appears to be right around 1.6 grams per kilogram of body weight or 0.7 grams per pound of body weight. But going back to the PICO acronym, the population study for that is generally recreationally trained individuals who are not particularly lean. So if you are an advanced trainee, if you're an athletic trainee who happens to be on the leaner side, then you may be undershooting an optimal protein intake if you view 1.6 grams per kilo as the gospel and the ceiling of effective daily dosing. So yes, to your point, The absence of evidence is not necessarily evidence of absence because number one, science can only look at one thing at a time and we're evolving very slowly. There is a lot of gray area we don't know, number one. And number two, which is maybe on par with number one, is that individuals respond differently to protocols and agents. So, it's very important to take research as, at best, a starting point from which to adjust to individual response.
Andres Preschel: Right. And I hope that in this world of, you know, novelty being what goes viral, I hope that people like you and me can make skepticism and open-mindedness go viral. So, that's my promise is to help us do that, you know, the evidence-based community. So and then moving moving into some of the let's say Protein and body composition. I know that that's important for so many of the people that are tuning in, you know, they want to Accomplish meaningful change in their body composition. Let's say what does some of the latest, but also most established research have to say about, you know, optimal dosing and timing of protein. And again, let's try to take this from a perspective of what can most people tuning into this, how can most people tuning into this derive as much value from this answer as possible? Like what's the most realistic approach as far as dosing and timing of protein for improved body composition?
Alan Aragon: Okay, another great question. So you first have to start off with the big picture. And the big picture involves having in your mind a hierarchy of importance. So at the top tier of the hierarchy is consuming targeted total daily amount of protein for the day. That is by far and away the most important and that will get you 90, 95-ish percent of your results is hitting the total by the end of the day. So I call that the cake. Now the icing on the cake is how you distribute that protein through the day. So for individuals whose goal it is to maximize muscle gain specifically, then that distribution may be important. For those who just mainly want to lose body fat or just kind of maintain an average amount of muscle mass, average healthy amount of muscle mass, then the distribution side of things matters very little. It's like anything goes. You want to eat your 120 grams of protein over the course of 20 meals a day? Do it. Want to eat it all in one sitting? Do it. Now, for those specifically trying to gain muscle, then one of the principles would be to maximize the in quotes anabolic effect per protein feeding. So in other words, maximize net muscle protein synthesis per feeding. And there appears to be a ceiling effect on dosing per meal to max out muscle protein synthesis. And keep in mind, there's a new line of research, a new study by John Tromelin and his colleagues, which compared 25 grams versus a hundred grams of milk protein over a 12 hour period. And it showed the superiority of a hundred grams of milk protein versus the 25 gram comparator. And I believe that a zero grams was compared in there as well. This is not to automatically jump to the conclusion that an optimal dose of protein per sitting is 100 grams, because they did not include in that comparison a more realistic dose of protein, let's say 40 to 60 grams, which in previous literature lasting more than 12 hours has shown a ceiling effect as far as acute anabolic response or muscle protein synthesis goes. And you know what, that brings me to another important principle as I think of science literacy. There's no such thing in most cases as a single study that can upset the entire previous body of studies that came before it. It's better to think of individual studies as pieces to a larger puzzle. And so when Tromelin study came out, a lot of the fitness influencers jumped to the conclusion that, oh, well, protein distribution doesn't matter. Look, 100 grams dosing caused greater muscle protein synthesis than 25 grams. And this was over a 12-hour period, unlike some of the previous studies, which were looking at four to six-hour periods. Well, there's still studies looking at 24-hour periods seeing a maximum of 30 grams max out muscle protein synthesis. So it's still pieces to a puzzle. Given that backdrop, I want to pull it all back to A narrative review that I wrote with my friend Brad Schoenfeld, this was in 2018. And it's pretty funny to be able to say back in 2018. as if it's a long, long time ago. And increasingly, it is becoming kind of a long time ago. But back in 2018, we wrote a narrative review. We reviewed all of the studies on the topic of muscle protein synthesis response with protein dosing across various age groups. And it turns out that roughly 0.4 to all the way to 0.6 grams per kilogram of body weight so roughly 0.2 to 0.25 grams per pound, appears to maximize the muscle protein synthesis response for protein dosing. So you're looking at 30 to 50 grams-ish for most people.
Andres Preschel: And so if somebody, well, go ahead, by milk protein, do you mean like whey or casein or a combination, or is it just like pure powdered milk? Okay. All right. So like whole milk. And then that's with the fat. It's not just the protein, it's also the fat, maybe a little bit of carbohydrate.
Alan Aragon: It went through some filtration, so there's, it's not the amount of fat you'd see in whole milk. So usually with that process, you're looking at a low fat product that's 80% casein, 20% whey. Okay. And those things affect the results too, the different proteins that you look at, whether it's just straight whey in some studies. This study with milk protein has to be a slower digesting thing because it had 80% casein, which is the slow digesting fraction of milk protein with whey being the fast digesting fraction. So there can be differences there. But generally speaking, looking at the research as a whole, it appears that the muscle protein synthesis ceiling in the short term appears to be 0.4 to 0.6 grams per kilogram of body weight or about 0.2 to 0.25 grams per pound in order to maximize the muscle protein synthesis response. And if you were to look at the hierarchy I just spoke about with total daily protein being the most important element of programming, And when you look at the body of research showing that somewhere between 1.6 to 2.2 grams per kilogram of body weight or 0.7 to 1.0 grams per pound of body weight looks like the sweet spot that would maximize muscle growth from just looking at total daily protein, then these constituent doses of that total would amount to roughly 0.4 to 0.6 grams per kilogram consumed four times a day in order to reach 1.6 to 2.2 grams per kilogram of body weight by the end of the day. So the wrinkle or the little bit of nuance that I would throw in there, and this is an important bit of nuance, is that we do not have the studies asking the question, What number of protein feedings a day maximizes muscle growth in resistance trainees? So in order to ask that question and set up the experiment correctly, you would choose resistance-trained subjects, and you would put them in a slight caloric surplus, at least, or at least eucaloric conditions or maintenance conditions, preferably a slight surplus, in order to maximize the potential for muscle growth. And then you run the experiment. You compare either two protein feedings a day with, for example, four protein feedings a day. Or you would compare three protein feedings a day with six protein feedings a day. And this is within a regular, full-blown, realistic diet with all the rest of the macros and a mix of food sources and the whole bit. Unfortunately, we don't have that research. So, you know, when I talk about maximal protein dose or protein dosing to maximize the acute anabolic response, how many, how many protein doses a day, this is speculating based on circumstantial bits and pieces of evidence, because unfortunately, there's not a lot of interest in running experiments that ask the questions bros like you and me want to know about.
Andres Preschel: Right. There aren't enough cavemen having these conversations to give us a meaningful effect in that capacity.
Alan Aragon: That is a majorly excellent way to put it, sir.
Andres Preschel: Hey man, my number one priority, besides the caveman conversation that we're having, is just to make you laugh, honestly. That's why I got you here on the show today. Hey, but I'll tell you what, let me ask you this. Oh, he succeeded. So, I noticed one of your last studies in the AARR, which I recommend that everyone, you know, subscribe to, it's an absolutely amazing way to keep up and see what's relevant and what's accurate and what's evidence-based. If we look at, let's say, a trained population, not necessarily elite athletes, but a trained population of, let's say, younger individuals. So I'm trying to really kind of capture my listeners. Like I'd say most of my listeners are probably 25 to 45. They're moderately trained, if not very, you know, more a little more active. And my question is, if you take a population like this, And you provide three conditions post-exercise or just general protein consumption. If you look at, let's say carnivores versus omnivores and then plant-based slash vegan, which population tends to have the best ability to kind of, you know, generate a muscle? Is there a meaningful difference? Definitely. I think if I'm not mistaken from what I saw in the research review, the omnivorous folks do really well.
Alan Aragon: Yeah, that would be the gold standard. That would be the gold standard, the omnivores. The reason why vegans, I wouldn't call them the gold standard for muscle anabolism, is because on a gram-for-gram basis, the highest quality animal proteins have a higher proportion of essential amino acids than the highest quality vegan protein sources. And there are a couple exceptions you can point to in that body of literature. Like, for example, Monteen's acute MPS response research on mycoprotein or fungal-based proteins. Some interesting things happened there where the fungus-based protein outperformed milk protein for muscle protein synthesis. And then there's this kind of this one-off, one-hit wonder study by Babalt and colleagues where pea protein supplementation outperformed whey protein for increasing muscle thickness. But that's a little bit far-fetched and it's really difficult to judge a study that's comparing just a single dose of protein in the day versus another single dose of protein in the day within two omnivorous groups. So there could be spurious findings there, and it's just really difficult to hang your hat on those kind of results unless they're replicated. That's another point of science literacy, like studies that are one-hit wonders, you have to view with a considerably higher degree of caution than studies that have been replicated, where the results are a little bit more reliably produced. So back to my point, I would give the omnivores the edge, for sure, as far as muscle growth. I would have to mention that there are a couple of studies recently that came out, one of them by Hevia Lorraine and colleagues, and then the next one by Monteen and colleagues, showing similar benefits in terms of muscle size and strength gain from vegan groups and omnivorous groups consuming an in quotes optimized amount of protein. But there are issues with those studies that still leave questions open as far as what is truly optimal. And the issues with those studies really center around one of the studies using completely untrained subjects, and then the other study using sort of recreationally trained subjects, but introducing a potentially rogue variable there of creatine use with both of the groups. So there are still unanswered questions about vegan versus omnivores once you optimize protein intake within the context of a program designed to maximize muscle hypertrophy. At this point in the game, I would still give the edge to omnivores. But then the question becomes, with any nutrition question, you can ask, who are we talking about? What's the population? And what's the goal? And then the third question, which is important, is what are the stakes? What are the competitive stakes? Are we looking at Olympic gold versus Olympic silver? Or are we looking at looking decent at the family reunion or feeling kind of embarrassed and shameful at the family reunion, you know?
Andres Preschel: So, there's high stakes. And some numbers would say blue stake.
Alan Aragon: They would literally think of animal flesh when you're asking what the stakes are. They would think dry aged or wet aged. So yeah, what are we talking about? What are the stakes? Who are we talking about? What's the population? What's the goal? What's the stakes? with the question of omnivore nutrition versus vegan nutrition for muscle growth, it almost boils down to, okay, what's, what's the stakes here? What are the competitive stakes here? Are you, are you working with a state level or national level or pro level bodybuilder? In which case you'd be kind of running a gamble if you vegan to him and people can point to Um, a few outliers who are doing well in the competitive, uh, physique realm as vegans, but still gamble.
Andres Preschel: So the bottom line is fun guy isn't always so fantastic. And, uh, vegan is also a verb.
Alan Aragon: You can turn almost anything into a verb these days if you first know the rules and then you break them.
Andres Preschel: Oh my gosh. Well, I hope that your research reviews don't lead us all to become vegan. So, hey, I don't know if you've watched the new movie on Netflix, You Are What You Eat, the twin experiment, the Harvard study. Have you had a chance to watch that yet?
Alan Aragon: Yeah. I have not watched that. Yeah, me neither. A documentary. I tend to avoid watching these. I was going to say. Yeah. Documentary. I, I just avoid them because I know, I, I know documentary makers. I have friends who make documentaries and, um, by far and away that the main objective is to keep the audience enwrapped in the, in the content, keep them entertained, make sure you have a gripping story first and foremost. Right. And so a lot of time, even with journalists, you know, they don't let facts and boring contradictions and nuances get in the way of a good story. So that same thing goes with documentaries. You know, their primary goal is to entertain. So I I haven't seen it, but I am aware of the JAMA study on the twins. It's not all that surprising that whatever group you feed a, in quotes, higher quality diet and get them more weight loss is going to result in the better outcomes. One of the aspects of a high quality diet is a diet that includes plant matter and enough fiber, a certain amount of fiber. So typically higher fiber diets will tend to be more satiating, will tend to more favorably affect blood biomarkers of health. And of course, they also tend to provide more bulk and satiety in the diet and lead to more weight loss too.
Andres Preschel: Right. And hey, before we continue, because I do have a couple more questions, I want to be mindful of your time. How much more time do you have for our show?
Alan Aragon: I can go 10 more minutes. I can hold my workout off.
Andres Preschel: I will do it for this show. I really, I really appreciate that, man. Thank you so much. Um, so let's, let's, let's go through a few, let's say more like rapid fire style questions. Um, when it comes to trends online, let's say, cause a lot of people unfortunately stick to their Instagram feed to stay up to date with the best and latest, right. Which isn't really the best and latest. Um, it's just the more novel stuff. Um, what do you have to say about seed oils in 2024? What should our general interpretation of these seed oil trends look like? Um, yeah, just if you want to fire away at the seed oil stuff.
Alan Aragon: Unless your diet consists of deep fried foods at local diners and such. and contains a lot of highly processed, engineered, packaged snacks, then the seed oil concern is really a non-issue and a non-concern. And the people who are fixating on seed oils are usually the people who are unaware of the weight of the evidence on this issue. And one way to spot either a noob or a charlatan or a wacko One of those three is when somebody's scaremongers about seed oils.
Andres Preschel: And something else that I've, you know, recently dug into is that they're not all made the same, right? Like cold expeller press, I believe is a lot, a whole lot better and actually can be healthy compared to like, you know, the really super highly processed stuff at high temperatures, the stuff that goes rancid. Have you looked at any research supporting one or the other that is meaningful and significant?
Alan Aragon: Yeah, yeah, but it's it's that research is typically acute effect. And not only that, but it's not in vivo research. So it's not within the organism within the human organism, it's within the test tube, it's in vitro. When you look at in vivo data, then you don't see, you don't see much concern at all for sedols used for cooking. And in fact, when you compare the head-to-head effects for seed oils used for cooking versus things like lard and things like butter, so these high saturated fat animal sources for cooking, then you see superior health effects with the seed oils used for cooking. So a lot of times it's not necessarily even a matter of you know, how we're heating them or not, because you're going to be heating the beef tallow and the butter and the lard as well. And when you compare those health outcomes from those sources with the seed oils, then you see a lot less cardiovascular disease and death with the seed oils compared to butter and lard and fatty beef. So if that wasn't the evidence, if those were not the findings, then I'd have quite a different opinion of seed oils. But the findings are what they are. Everything from intermediate end points like blood lipids all the way to hard end points like heart disease and death. Seed oils always outperform things like butter and lard.
Andres Preschel: Great. And then with regards to oatmeal, is oatmeal peasant food or is it evidence-based caveman raw food? It's both.
Alan Aragon: You know, there's a little bit of charm in the peasant food thing because, you know, you want to somehow try to stay humble. You want to keep a humble attitude. So, I want to say like peasant humility with like, Brojacked. Nice.
Andres Preschel: Nice, nice, nice, nice blend there. And then what are some what are some trends you want to see less of specifically online and social media trends you want to see less of with regards to nutrition in 2024?
Alan Aragon: It'll be a sort of a combination of nutrition and exercise. So People are obsessed with thinking they can look at a singular aspect of physiology and judge their entire state of health based on it. One of the things that came into popularity, it comes in and out of popularity, is postprandial glucose response and continuous glucose monitoring. And while there are potential applications of that, clinical applications of it, The majority of the normal glycemic and physically active and lean populations, they don't need to let a continuous glucose monitor run their lives. And this also goes with wearable devices. Some people put a little bit too much emotional stock into the numbers spit out by wearable devices without remembering that there's a margin of error there in some devices and methods more than others. And so while it can be fun and motivating, you have to be able to see it for what it is. and not necessarily completely invest your, your view or your perception of reality on what's going on with the wearable devices.
Andres Preschel: Yeah. I've seen a lot of people sacrifice their quality of life on just trying to get the perfect sleep score and fitness score. And I've been guilty of this too. I actually stopped using devices every single day because they were like totally, you know, taking over my, my life. And then I actually really love a book by Andy Galpin unplugged that kind of helps you Develop the right relationship with these devices and kind of just get you back in nature and living your life like human beings are in In a way supposed to live, you know So sticking to the fundamentals and having a good like Andy yeah, and he's awesome and And then last question for you here. It's good guy. So we can wrap up is if you had to put let's say a word Sentence or phrase on a billboard somewhere in the world right now What would it say and where would you put it? Ideally, maybe following a theme that people can really cherish for this new year
Alan Aragon: Wow, bro, that is just such a loaded and difficult question.
Andres Preschel: Besides subscribe to my research review, which is probably what most people should do.
Alan Aragon: Oh my goodness. I'll choose a… Okay, so there is a quote by Calvin Coolidge on persistence. And I don't have it memorized, but I know I love it. Basically, I would say don't give up on the things in your life that you're passionate about. So don't give up on your pursuits of passion. Because even if you fail at them, then these unforeseen, wonderful doors will swing open. So I think that people just sort of half-ass it and don't go all in with their goals in life without realizing that even if and when you fail, there are unforeseen benefits to that in quotes failure. So just go ahead, go hard, put a hundred percent into it and, you know, just don't, don't ever give up. I think that the quote, as long as you enjoy it, I mean, if you don't enjoy something by all means get the hell out. Right. But if it's something that you enjoy and your plan isn't working out, find, find ways to make it work out because you always want to be swimming in the space that you are passionate about. That's the only way you'll do your best work. I mean, you're living proof. And I'm living proof, dude. I am living proof. I have the narrowest niche ever, ever, ever.
Andres Preschel: I love my life. I love what I do. I can tell, man. And I think everyone, I know everyone tuning in can tell. You know, the way that you approach this with such an open mind, so much skepticism and like what you preach isn't a bias or a claim or anything novel. It's just real science. And that is just so wonderful to get the chance to tune into. And yeah, man, I'm excited to step into this year being even more skeptical and standing for that. No matter what the algorithm wants, I'm not going to give in to novelty. And I hope that the folks tuning in don't make the same mistake. And by the way, the quote verbatim, I think you did an incredible job at describing this in your own words and making it even more relevant for people, but the quote verbatim for those who are curious, and correct me if this is wrong, I don't know if this is exactly the quote, so there could be another. It goes, nothing in this world can take the place of persistence. Talent will not. Nothing is more common than unsuccessful people with talent. Is that it?
Alan Aragon: Hell yeah, bro. Hell yeah. That is it. That's it. That is it for sure. Just with any field. I mean, it's easy to look at people and say, oh, he's got this or he's got that. He's brilliant this way. He's got this or that attribute or she's got this or that attribute that I don't have. That's nonsense. Nonsense. You have no other choice. in life, but to pursue your interests and passions. You know, the alternative is just to sit there and count the seconds until you expire.
Andres Preschel: Yeah. Hey, man, I really can't thank you enough. Thank you again for joining us. And I might take you up on having you on another 28 times. I mean, that's the minimum sample size, right? So, so that we're not just two bros having a conversation over a campfire.
Alan Aragon: We need adequate powering for the sample.
Andres Preschel: Awesome, man.
Alan Aragon: It's been an honor and pleasure. I love the questions that you ask. I really enjoy it, dude. I really enjoy the energy and the questions you ask open up a lot of dialogue for stuff that I think is important for people to hear, even if it's weird, esoteric and stuff. And to your audience, I appreciate you guys for listening in and having the discernment and vision to follow Andrew.
Andres Preschel: Awesome, man. Thank you so much. So that's all for today's show. Thank you so much for tuning in today. For all of the show notes, including clickable links to anything and everything that we discussed today, everything from discount codes to videos, to research articles, books, tips, tricks, techniques, and of course, to learn more, about the guest on today's episode, all you have to do is head to my website, AndresPeruchel.com, that's A-N-D-R-E-S-P-R-E-S-C-H-E-L.com, and go to podcasts. You can also leave your feedback, questions, and suggestions for future episodes, future guests, so on and so forth. Thanks again for tuning in, and I'll see you on the next one. Have a lovely rest of your day.