The Henselmans PT Course is 96% full! mennohenselmans.com/online-pt-course/ By the way: just like Romanian deadlifts aren't just for Romanians, the Henselmans PT course isn't just for PTs. Out of the 1000s of students we have had, many have joined because they were interested in the most optimal, science-backed strategies for building muscle, losing fat, and optimizing health for themselves. Of course, you're welcome to take the certification exam, but many students take the course purely for their own knowledge and development. We're almost full, but as long as this link works, you can still join: mennohenselmans.com/online-pt-course/
Dearest Martha, the protein war continues. They keep promising the end is near, but no one on the front line has any idea. This last deployment however, feels colder. The mood has grown grim. I will be brought home soon one whey or another. More than anything i miss the how you would laugh. If only you could see me now, boy have I changed
Lol true but you ever see the 1980 Mr. Olympia or read Arnolds autobiography? The world of bodybuilding has always been a soap operate full of absolute divas.
@@PlumagedBowAnd? You are going to be taking care of your health until you aren't here anymore. So you will have plenty of time to work out what kind of nutrition you function best on.
Its just diminishing returns curves, breakpoint is more of a linear version of that. If you do 3 stage breakpoints or 4 stage breakpoints, you'll start to see more and more of that curve take shape. Using linear models for these things pretty much violates the general principles of how biological systems work. I don't know why anyone would do that. It's a sort of reckless naivete, or as menno would say it "Doesnt make sense". I can't thing of any things to do with bodies where linear inputs result in linear adaptations ad infinitum. At a certian point its is absolutely not worth people ramping their protien intake and their grocery bill for 3% better gains, when the gains are like 5 lbs of muscle a year. Congrats your protien went from 150g per day to 200 g of protien a day this year and gained 5 lbs of muscle instead of 4.9lb ! That's just a foolish tradeoff.
@@ChristopherHall-r2gYep. I'll get 80-100g a day, take it or leave it. As if I'm training hard enough to use the max daily synthesis rate. Like seriously, this shit is silly. You gotta do it forever anyways if you want the full benefits. Who caress if you lose even a month of progress in a year by eating less shitty food every day.
I’m as sciency as the next guy (okay, quite a bit more), but the variation in these studies suggests that personal trial and error will be much faster and more accurate than waiting for the golden study that accounts for all variables. 😄
@ Not at all. Better still, the results are incontrovertible. The conclusions from the studies bounce all over the place over the course of years. I know if I’m getting stronger on a week-to-week basis.
@ from changing one little variable that at best will give you a few % more growth…I doubt it I would rather say you notice a placebo effect which is also fine but the effect will dissapear over time.
That’s actually crazy. RP did the same exact thing. It’s some of the most important data of this video - people read it, note it down as truth in their heads then move onto the next vid. There needs to be better proofing and fixing up fast if science communicators want to not be ridiculed by bro science, because it’s not a good look the constant contradictions and inaccuracies.
If people just stick to SI units when talking about anything remotely scientific we would not have this issue. g/lb is especially weird, combining two units from different systems.
I feel this shouldn’t be concluded too seriously until we get more and better RCT’s within the higher protein intake realm. They did an episode of their MASS research UA-cam podcast where they addressed all of this
I'm a sportsdietitian. The science on protein synthesis has already existed for at least 20 years. It's 1.6. It has always been 1.6. Studies were replicated, systematic reviews were done. It's never been anything else in nutritional science. It has only ever been something else when people with no nutritional science degree do the research. And every time it has been incomplete at best.
Thank you for addressing the question of whether one should base their protein intake on fat-free mass or total body weight. I've probably watched at least 30 videos on protein intake over the past couple years, and this is the first time I've seen this nuance discussed, with evidence.
I think there might be some misunderstanding about quadratic and cubic models. On a given interval, those can actually resemble a "diminishing returns" curve! They do not consist of ONLY the quadratic/cubic term, but of a mixture of linear and nonlinear terms. If the analysis found no evidence for the nonlinear terms being important, then this is probably because the "diminuation effect" was so weak, that statistically, it did not matter. Look up taylor series for more info on those higher-order models!
Agreed, I program carbs at 2g/lb bw, and I think that's a minimum. I can tell in the gym when I eat fewer carbs, especially if it's for several days in a row.
Great video, you consistently present the most well-researched perspective in the fitness sphere imo. Learned a lot from you that I don't see other fitness UA-camrs cover to the same extent.
@@Osprey1994 I'm sure I've seen or even regularly watch most of them, Menno definitely knows his stuff. I don't always agree with his analysis, but I think it's almost always a perspective worth considering.
this is why you dont argue with an analyst.. people want to be original and provide novel information for recognition and thats why peer review is a thing, good peer review done here
I love your content but your math failed you here. When someone tries to fit a quadratic model, it doesnt mean the independent variable should increase AND decrease. It just means the data could fit *part* of a parabola, *any* part. The diminishing returns you are looking for can very well be captured by polynomial models of any degree.
Awesome discussion. Aside from this, can we repeat what both theirs and yours (Morton meta-analysis) agree with? RESISTANCE TRAINING IS THE MOST IMPORTANT STIMULUS for muscle gains. More than protein. So don't over think about that if you are an amateur.
It's funny sometimes watching this kind of videos reviewing some sort of analysis because some mistakes seem weird for folks that have some sort of training with data analysis. I come from a physics background, and when proposing a model for some sort of experimental data we've collected, we are taught that a physically relevant model is what is important, not model that best fits the data per se. What we want from a model is to extract information to test a hypothesis. In this case, we have a clear hypothesis, we know that we can't just force-feed muscle growth with more and more protein consumption, and we also know from various experiments that dietary protein intake is necessary for muscle growth. Therefore it is clear that a model where the more protein the more muscle growth we expect, but the rate of change of muscle growth also should be going down as one consumes more protein at least as a first order approach. These sort of break-point analysis are very common when the data is not very good (we have a lot of variance), and when we don't know the mechanisms very well or they are too complicated to model. When looking at the data from this more recent analysis I notice that the variance is clear that the range of protein intake that we are analyzing is very small compared to the variation that is expected. I'd consider to have just one group of people that are given a ridiculous amount of protein just to test what is the max amount of muscle growth, with that we'd get a good idea of where the asymptote lies. Sorry for this sort of incoherent comment I just left, it's just that this has been on my mind for quite some time and wanted to leave a (sort of) explanation/my 2 cents.
Instead of examining the variance and maybe finding something interesting, which I understand wasn't the goal of the study, they came up with a useless model. I guess it's difficult to get published if you get no results.
we need studies that clearly control pure increased protein while maintaining total calories versus increasing protein while only adding calories from protein versus adding the equivalent calories of the second group in balanced calories including fiber, carbs, etc. It still seems confounding to me what amount of the additional benefit at higher protein intake, beyond 1.6g/lb, is due to or could be closely replicated by additional healthy and well balanced calories.
For the past five years, I was bulking and cutting around 75 kg to 80 kg and all I ate was 100 g of protein while the rest came from carbohydrates and a little bit of fats
@Antonio_Serdar a "low" amount is never unnecessary. Anyways, 100g of protein is perfectly adequate for someone 75 - 80 who isn't looking to maximise muscle growth.
@@Antonio_Serdar 100g of protein is honestly a pretty decent amount. If you're 75kg at 10% body fat, 100g of protein is roughly 1.5g per kg of lean mass. Could probably eat a little more easily but that's hardly a limiting factor for muscle growth or maintenance.
The ISSA, known as the 'International Sports Science Association', has recommended for years, between 0.8 grams to 1.0 grams per pound of Body Weight! And it works GREAT!!! 💪🙂👍
The fittest I've ever been was 180 and decent muscle, never shredded because I didn't care but low body fat and a flat stomach. I base my .8-1g/lb on that because I wasn't shredded at 180 but I was leaner so I aim for 150g/day minimum but often hit 180 so as long as I'm in that range I don't trip. I'm 200 now after years of not taking things seriously so I don't see a point to suddenly go to 200g when I know for a fact I'm not 200 lean. Its a guess for sure but if you were fit at a certain weight in your life its a pretty good guess.
With a quadratic relationship where the maximum is higher than the maximum dosis in the samples it would show a decreasing impact of increased intake similar to an asymptotic model. When taking a constant caloric intake one can even expect a decrease in muscle mass when the intake of protein starts decreasing the fats and carbs below thresholds.
Mr. Henselmans makes it sound like the authors only compared the first terms of linear, quadratic, and cubic, which I find very hard to believe as the only thing that makes sense would be to define quadratic and cubic to include all terms up to power two and three respectively. If my suspicion is correct, Mr. Henselmans' criticism would be invalid. Maybe he knows for a fact what they did, but that would be crazy! Just like he said. But would researchers really do that?
I tried clicking on the link for "Table 1.2, Supplemental Digital Content 1", I think my browser blocked pop-ups or something. I can't access it at the moment.
So, my point is, if they did consider all terms, first of all, of course cubic is better than quadratic which is better than linear, but maybe they report that the improvement is not significant. Or there is some regularization to detect overfitting. In any case, saying linear is good enough when quadratic and cubic options have been looked at is tantamount to saying they didn't observe much diminishing returns as protein increases. Although, that's also impossible. Hmmmm.... what happened?
I find it ridicolous that people obsess so much over hitting their protein goal to maximize gains. As long as you are not preparing for Mr. Olympia and don't need the extra 3,7% muscle gain for whatever it takes, just keep it above 100g per day and you would get like over 80% of the result with way less stressing about it and much cheaper and you don't have to eat a whole chicken breast everyday.
Yes but you can say that for a lot of things: caloric intake, rir, stretch of the musicals, timing of cardio, number of meals, getting enough sleep etc etc etc combined it can however make a substantial difference.
Imagine you like to do motor racing with your car. You can't make a Ferrari out of your Renault Clio. But you can still make it faster and better by changing the tires, chiptuning, making it lighter by removing the interior and optimizing the fuel. You will not double your max speed, but still you will increase your lap time significantly by optimizing everything you can together. It's the same with your body and training/nutrition. Is the additional effort worth it? That’s something everyone has to decide for themselves.
So it would be ridiculous for YOU to obsess. Imagine obsessing so much you obsess about how much obsessing is not too much obsession. Sometimes people like to do A rather than B if A is marginally better.
IAAO method is also stronlgy influenced by habitual protein consumption (you usually consume more, you usually oxidise more). A washout of at 3+ days is requiered, what simply does not happen in most studies.
In research trials we try to minimize variation in variables outside of those we are investigating in order to improve statistical power. We then use regression methods on this abnormally homogeneous data to make predictions about future responses. If we get similar values in future controlled studies, we take it as confirmation of our previous findings. But how good is this method really for predicting responses in subjects that are different from those in our trials. Data science methods take a very different approach by collecting data with a high degree of variability to create more robust models that are better at predicting outcomes from a wider variety of test subjects. The data science approach would seem to offer a better basis for modeling than controlled, randomized studies. The problem is, of course, getting large datasets including a sufficient number of relevant factors.
Do I have to look at the leucine content of my meals to maximize MPS when targeting the 20g-30g of protein? are 100g of raw weight chicken breast enough protein in one meal?
Linear vs. Quadratic vs. hyperbolic doesn't fit the whole shape of the curve nor does it have to. It/they simply add in one or more free variables with which to fit the data. A set of linear data with a breakpoint would be better fitted by a quadratic equation than by a strictly linear one (because the extra parameter represents some sort of underlying biological phenomenon). The fact that the linear model fit better than more complicated models indicates that the or any additional parameters don't offer any predictive power. To wit, 1.6 is almost certainly not *the* value for everyone and it's almost certainly something more like 1.5-1.8 or more. Edit: And, yeah, somewhere north of 5g/lb./day I expect the gains to come back down, even with a breakpoint.
that makes a lot of sense that's why a lot of pro body builders seemed to requite higer protein becouse they where on gowth hormone so not just their muscles where bigger but most organs as well
1:42 No, it's not. 1.5 g/kg is 0.024 oz/lb, which is actually 32% less than 1 g/lb (which is equal to 0.035274 oz/lb). 50% more would be 0.052911 oz/lb (or 3.3 g/kg). Also I have no idea why you keep confusing yourself by mixing units. Just stick to one system!
Here’s my thoughts. As long as daily protein intake consistently meets the requirements for staying at one’s natural limit (meaning at the lowest possible body fat percentage of current body weight, or at the highest possible body weight of current body fat percentage) while maintaining a calorie balance (i.e., maintaining current body weight), along with appropriate training volume, the protein demand will be sufficient in the long term. This is true as long as one is not constantly in a state of weight gain or weight loss ("not constantly in a state of weight gain or weight loss" means gaining weight and then maintaining weight long-term, or then losing weight and reaching a balance point, or losing weight and maintaining weight long-term, or then gaining weight to a balance point). However, if one wants to stay closer to or reach the natural limit during a period of weight gain or weight loss, more protein will be needed. The greater the calorie surplus or deficit, the more protein is required to stay closer to or achieve the natural limit during weight gain or loss. The same applies to training volume. Moreover, there is a threshold effect between training volume and protein intake, meaning that whether one can stay at the natural limit or how close one can get depends on the limiting factor between the two. More experiments on well-trained individuals are needed. Control their protein intake and training volume, and make them stay at their current body weight for a period of time, then test their body composition. The closer one gets to the natural limit, the higher the minimum protein intake and training volume in terms of maintaining current body weight and body composition is required, but the actual amount may be lower than what most people currently think.
This. A regular person uses about 30 grams a day of protein. Give them more and.. nothing happens, they burn it for fuel. Exercise a bit and you might use 60g a day to rebuild the muscle and build a little. Exercise more, 100g before it's burned for energy, etcetera. If you're constantly sore from Doms and going to the gym twice a day, I guess go nuts, but you better be eating enough so it doesn't just get burned. There's no such thing as optimal. Even if you work hard and don't get the maximal quantity of protein you could've used, you'll still grow, anything over that 30g is usable. Even people given low protein diets for kidney disease with only a mere 43 grams of protein a day BUILT muscle with resistance training, when they weren't limited in protein before going into the study.
@@mikafoxx2717 My thinking is this: If training volume is extremely high, and an extremely large amount of protein is consumed while maintaining no calorie surplus or deficit (with the condition that other essential nutrients, such as adequate fiber and fat sufficient to prevent gallstones, are also consumed), then a trainee who is far from their natural limit will experience rapid changes in body composition (with weight remaining the same, but body fat percentage rapidly decreasing). In this case, the more protein consumed, the faster the body composition changes. On the other hand, a trainee who has reached their natural limit will see no changes in body weight or composition. Therefore, even if not enough calories are consumed, the protein will not be wasted and burned, unless the natural limit has been reached (at which point, it’s possible to replace some protein with carbohydrates and fats, as long as enough protein is consumed to maintain the natural limit, making the diet more flexible).
What Ive learned being a mathematician: A ton of studies use random cheap ass mathematical assumptions and even researches often have confusingly bad statistical knowlegde.
given the massive spread of the data (on the Y axis), even of a linear model fits the data best, the are extremely strong questions about effect size and confounders.
Just train hard and eat when hungry, lol. It's good to "know" what optimal is but as is shown by the anabolic window benefitting from more protein ,AKA being hungry post-workout, your body will always notify you on if you need more protein. If you can and want to minmax muscle gains you could consider that new analysis, but the side effects of that recommendation might be miriad indeed.
Menno, you are great, but you made an error at 1min41sec into the video -- you said, and your big red insert said, that the new meta-analysis recommended a huge amount of: "1.5g/kg" but what you *meant* to say was 1.5gm/lb, which is vastly more than current recommendations.
I'm sorry if you answered this but I might have misinterpreted it somewhere... Does the fat free mass recommendation include organs including skin? If organs need protein, is that taken into consideration with the 1.6g per kg of bodyweight?
I haven't read their meta. If by quadratic and cubed they literally meant x^2 and x^3 then fully agree that doesn't make much sense. If they meant a+bx+cx2 and a+bx+cx^2+dx^3, those would have had the expressive power to capture a breakpoint but then it would be surprising that linear was the best fit, as more expressive power normal gives a lower rmse.
Thanks for your videos, they have helped on my journey for sure! I think maybe @1:40 there may be a kg/lb issue with either what you are saying or with what you show on the screen... saying that 1.5 g/kg is 50% more than the conventional 1 g/lb (not kg) yet @5:45 your hypothetical shows 5g/kg being aprx 2 g/lb which is much closer. But I am still pretty new to this and may be misunderstanding something.
Unless you're a student, the issue here is not that protein is expensive. Chicken and ground beef isn't. It's more that I want to take in carbs. I'm sticking with 1.8 per kg. I think that seems more likely to be true. I find it really hard to keep protein below 200 g, though.
I wonder if you were able to see the recent mass office hours before making this post. All of your points were already addressed there and so the timing of this feels a bit sloppy considering the researchers went to great lengths to cover all of your arguments
You were very nice about it, but forgoing a logistical model like the one you mentioned and instead testing quadratic or cubic laws is pretty out there. It makes zero sense to do that. Almost all metabolic processes follow logistical growth laws. You can try to linearize that for simplicity, but quadratic or cubic isn't simpler. It's fine to test unusual fits as long as you don't overfit, but forgoing the obvious, very likely mechanic for the unusual one just doesn't make sense.
It may not be as far-fetched as it seems. I had the same reaction as you, so I wanted to check the paper. In the supplementary materials, you can see the shapes of the quadratic and cubic models-one quadratic model is almost a linear fit, with the end slightly resembling logistic growth, while one cubic model basically follows a logistic growth curve for the most part. They also modeled "dietary protein (g) per kilogram of fat-free mass (FFM)" instead of just "dietary protein (g) per kilogram of body mass (BM)", and the resulting model look solid. This is only the second video I've watched from Menno, but dismissing the study just because of the model choice doesn't seem particularly serious to me, in this particular case.
The only people I see worrying about how much protein to eat are small people. All the big boys just eat 5-6 meals a day with at least 50 grams of protein per meal.
I will never understand why these studies only look at a very small handful of very simple models like linear, quadratic, break point, etc. It takes a lot of time, money, and energy to put these studies together and collect the data. It takes literally less than 10 minutes to add a python import (like sklearn) and run TONS of different models on the data ranging from extremely simple to very complex.
Bayesian statistics tend to favor simpler models. The quadratic (a+bP+cP²) and cubic (a+bP+cP²+dP³) models "fit the data better" than the linear one, but at the price of over-fitting.
@ There still seems like better models to try like any flavor of splines (which I supposed the break point analysis is like a spline but it’s a very simple version), logarithmic fitting, logistic regressions, etc. Shoot why not even set up neural networks with limited nodes, limited depth, and try arbitrary activation functions.
@ Researchers (whether Bayesian or frequentist) tend to favor interpretability and robustness over raw predictive power. This isn't just a preference; it's grounded in solid mathematical principles. Overfitting, lack of generalizability, and reduced explanatory value are real concerns when dealing with more complex models. Note that a model like a + bP + cP² + dP³ has only four parameters but already offers a lot of expressive power. You can approximate many variations of sigmoidal curves with it. Many studies are designed to test specific hypotheses rather than maximize fit. This isn't a data science or ML competition. It's about drawing meaningful conclusions from the data.This isn't a data science or ML paper. That said, more complex models like the ones you mentioned, could be explored... if there were enough data to support them. With hundreds of thousands of participants in well-designed studies, we could infer some really interesting dynamics. But we're not there yet.
If people tracked their food and work outs over long periods of time more and reached their own conclusions the result would be more accurate for the individual than a "one fits all" rule of thumb
Study: "Dietary Protein Intake (g) - Per Kilogram of Body Mass" "Very serious trainees who care a lot about their muscle mass should consume the higher end of this range. So bodybuilders, for example, should consume as much as 1.5grams per kilogram. 50% more than even the pro bodybuilding wisdom of one gram per pound." 90kg bodybuilder - 1.5g per kg = 135g protein. 90kg bodybuilder - 1g per lb = (90*2.2) 198g protein. Did someone on Menno's team misread the study or something, or doesn't understand the conversation from kilo's into lbs? In what world is 1.5g per kg extreme?
A good rule of thumb for biological systems is that X (whatever you're investigating) is optimized and not maximized. This fits with your objection to the linearization comments.
Laziness or intellectual dishonesty-you decide. If this "science-based fitness influencer" had bothered to click the link right next to the mention of quadratic and cubic models in the meta-analysis, he would have immediately seen that these models aren't FFM(P) = P² and P³, but a+bP+cP² and a+bP+cP²+dP³. I can't fathom how he didn't stop and think, "wait, that can't be right, let's investigate for two minutes before making a 25-minute video about this study". Not to mention the blatant unit error at 1:40, both on-screen and in the script. Deeply unserious.
Im worried that maybe the body adjusts over time to the amount of protein you’re consistently eating. I want to see studies on people who have been eating 2g/lb protein for a few months to see just how high the upper limit really is.
I trust the guy that tells me to save money. Remember any scientist makes money by you by influencing your purchasing decisions. Like those sugar scientist blaming fats instead of sugar
Can they take the same trainees profile for a studies ? Same years of training, same weight, same age, same height, etc... At least we would have a good comparison point for a range of protein intake from 0.8 to 3gr/kg for example. But maybe I'm saying shit here as i'm not a scientist 😅
If you listen to a guy like Mike Mentzer, he never gave an exact amount for protein intake. Always just said to have about 25% of intake to be comprised of protein. Muscle building is an extremely slow process for naturals and this amount seems right to me.
So menno recommends 1.8g/per kg/per day to maximise hypertrophy or a range from 1.6-2g/per kg/per day. Is this based on overall bodyweight or based on fat free mass? Also what if you are very overweight, how would you calculate this?
Total body weight. Most people aren't consistent in their application with BF measuring tools or don't have access to 5C body comp machines to accurately assess their BF%. And for obese and very overweight individuals, he uses Eric Helms' recommendation of 2.3g/kg LBM (lean body mass) per day, if you have a reasonable estimate of someone's BF%, or 1.8g/kg/day. Whichever one is lower.
Basing it on target/goal body weight makes the most sense. Most people underestimate how lean they actually need to get anyways so it skews high. Its also important to note that the benefits of high protein are incredibly marginal in the grand scheme of things so I wouldn't fret too much either way. Find an acceptable range and get near it with high quality sources and you are likely good.
You made a few mistakes in this video regarding the units. You said g/kg a few times when g/Lb was applicable. Sometimes g/kg was the correct unit but other times based on the numbers, g/Lb was the right one yet you said g/kg. I'm suprised you didn't notice it. It might confuse some people because the difference between those units is huge (x2.2). Maybe you should pick one unit only and stick with it so you don't confuse yourself.
We are gifted to have such a mind establishing the real facts on maximum gainZ. It's a real wild west of egos, skewed data and shadowy agendas in scientific literature world and especially so in human performance. It's almost impossible to pick apart if you're not a highly motivated science/data expert. Thank you for cutting through the crap
"The range from 1.2 to 3.2 is only 1.3. So if you do 1.3 * 0.07, we're getting close to a 0.1 effect size, which is close to half of a small effect size... So now we're talking about almost a small effect size to go from the bottom of our highest range to the top." -Helms
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Out of the 1000s of students we have had, many have joined because they were interested in the most optimal, science-backed strategies for building muscle, losing fat, and optimizing health for themselves.
Of course, you're welcome to take the certification exam, but many students take the course purely for their own knowledge and development.
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I would love to see papers start to include causal graphs. As said by Richard McElreath's: "No causes in, no causes out".
Dearest Martha, the protein war continues. They keep promising the end is near, but no one on the front line has any idea. This last deployment however, feels colder. The mood has grown grim. I will be brought home soon one whey or another. More than anything i miss the how you would laugh. If only you could see me now, boy have I changed
😂😂💀
Nicely done.
😂
"More than anything i miss the how you would laugh."
He's fading fast boys. First goes the spelling. Soon he'll be mumbling nonsense.
This is awesome! Every time I think the comment section is cesspool something like this pops up, maintains my faith in humanity
I’m cutting my daily protein intake to 0g/day until a consensus is reached between Milo and Menno
Should be fine, just increase sugar intake to cover it.
The fitness industry is like a soap opera these days.
Lol true but you ever see the 1980 Mr. Olympia or read Arnolds autobiography? The world of bodybuilding has always been a soap operate full of absolute divas.
The scientific community in all its mediums has always been this way. Always.
Because it’s all eyeballs and clicks. It’s the only way to make money in the “fitness industry” besides being a personal trainer
Research gives you a range but YOU (the individual) you still don’t know where you would fit into this range. Just do what works for you…
There are even a lot of tears (sweating is when muscles cry 😁)
And this is how you professionally debate a topic well articulated, and great job
When will the meta-meta-meta analysis come out and settle this argument for good, tired of changing my life everytime lol
You know… you could experiment on yourself to see what actually works lol
@@bannanaizationthat would take years of experience lol
@@PlumagedBowAnd? You are going to be taking care of your health until you aren't here anymore.
So you will have plenty of time to work out what kind of nutrition you function best on.
Have you considered not being a hypothesis based lifter?
@@PlumagedBowunless you plan on only weight lifting for a year, why is this an issue?
I'm guessing 1:40 was supposed to be 1.5g/lb?
Sounds like we need another high quality study that compares linear vs breakpoint models for protein intake
Its just diminishing returns curves, breakpoint is more of a linear version of that. If you do 3 stage breakpoints or 4 stage breakpoints, you'll start to see more and more of that curve take shape.
Using linear models for these things pretty much violates the general principles of how biological systems work. I don't know why anyone would do that. It's a sort of reckless naivete, or as menno would say it "Doesnt make sense". I can't thing of any things to do with bodies where linear inputs result in linear adaptations ad infinitum.
At a certian point its is absolutely not worth people ramping their protien intake and their grocery bill for 3% better gains, when the gains are like 5 lbs of muscle a year. Congrats your protien went from 150g per day to 200 g of protien a day this year and gained 5 lbs of muscle instead of 4.9lb ! That's just a foolish tradeoff.
@@ChristopherHall-r2gYep. I'll get 80-100g a day, take it or leave it. As if I'm training hard enough to use the max daily synthesis rate. Like seriously, this shit is silly. You gotta do it forever anyways if you want the full benefits. Who caress if you lose even a month of progress in a year by eating less shitty food every day.
I’m as sciency as the next guy (okay, quite a bit more), but the variation in these studies suggests that personal trial and error will be much faster and more accurate than waiting for the golden study that accounts for all variables. 😄
That goes for pretty much everything when it comes to programming/diet
That have always been the case
Don’t you think muscle growth happens too gradually for personal trial and error to be fast and accurate?
@ Not at all. Better still, the results are incontrovertible. The conclusions from the studies bounce all over the place over the course of years. I know if I’m getting stronger on a week-to-week basis.
@ from changing one little variable that at best will give you a few % more growth…I doubt it I would rather say you notice a placebo effect which is also fine but the effect will dissapear over time.
There's a mistake at 1:41. I think you wanted to say 1.5 g/ lb.
That’s actually crazy. RP did the same exact thing. It’s some of the most important data of this video - people read it, note it down as truth in their heads then move onto the next vid. There needs to be better proofing and fixing up fast if science communicators want to not be ridiculed by bro science, because it’s not a good look the constant contradictions and inaccuracies.
this happens in the last few minutes as well (a kg/lb figure should have been g/lb)
If people just stick to SI units when talking about anything remotely scientific we would not have this issue. g/lb is especially weird, combining two units from different systems.
@@trontor.6711its not that big of a deal if you just use common sense you'd know something doesn't add up
again at 6:18 shud be 3g/lb (5g/kg)
I feel this shouldn’t be concluded too seriously until we get more and better RCT’s within the higher protein intake realm. They did an episode of their MASS research UA-cam podcast where they addressed all of this
I'm a sportsdietitian. The science on protein synthesis has already existed for at least 20 years. It's 1.6. It has always been 1.6. Studies were replicated, systematic reviews were done. It's never been anything else in nutritional science. It has only ever been something else when people with no nutritional science degree do the research. And every time it has been incomplete at best.
Thank you for addressing the question of whether one should base their protein intake on fat-free mass or total body weight. I've probably watched at least 30 videos on protein intake over the past couple years, and this is the first time I've seen this nuance discussed, with evidence.
The optimal protein intake is all of it
I think there might be some misunderstanding about quadratic and cubic models. On a given interval, those can actually resemble a "diminishing returns" curve! They do not consist of ONLY the quadratic/cubic term, but of a mixture of linear and nonlinear terms. If the analysis found no evidence for the nonlinear terms being important, then this is probably because the "diminuation effect" was so weak, that statistically, it did not matter. Look up taylor series for more info on those higher-order models!
ALSO, We're not working with infinite calories, what about the anabolic cost of replacing grams of carbs with grams of protein above 2g/Kg bodyweight?
Agreed, I program carbs at 2g/lb bw, and I think that's a minimum. I can tell in the gym when I eat fewer carbs, especially if it's for several days in a row.
Thank you Menno , we need this type of discussion !
Im very happy to have found this channel.
Great video, you consistently present the most well-researched perspective in the fitness sphere imo. Learned a lot from you that I don't see other fitness UA-camrs cover to the same extent.
You don't watch that many science based fitness youtubers...
@@Osprey1994 I watched a lot actually
@@Osprey1994 I'm sure I've seen or even regularly watch most of them, Menno definitely knows his stuff. I don't always agree with his analysis, but I think it's almost always a perspective worth considering.
It feels like research continues hunting for a silver bullet when it is simply genetics, fundamentals, or steroids tbh.
Yes but if you don’t want to do steroids you can not change set parameters (genetics) so optimize things to get the best results for yourself.
this is why you dont argue with an analyst.. people want to be original and provide novel information for recognition and thats why peer review is a thing, good peer review done here
I love your content but your math failed you here. When someone tries to fit a quadratic model, it doesnt mean the independent variable should increase AND decrease. It just means the data could fit *part* of a parabola, *any* part. The diminishing returns you are looking for can very well be captured by polynomial models of any degree.
But they picked a linear model anyways
We (I) need a video about muscle memory where people trained for years and stopped for 1-10 years after that.
I personally feel that Milo is one of the worst researchers in the space
Awesome discussion. Aside from this, can we repeat what both theirs and yours (Morton meta-analysis) agree with? RESISTANCE TRAINING IS THE MOST IMPORTANT STIMULUS for muscle gains. More than protein. So don't over think about that if you are an amateur.
This video was awesome!
It's funny sometimes watching this kind of videos reviewing some sort of analysis because some mistakes seem weird for folks that have some sort of training with data analysis.
I come from a physics background, and when proposing a model for some sort of experimental data we've collected, we are taught that a physically relevant model is what is important, not model that best fits the data per se. What we want from a model is to extract information to test a hypothesis. In this case, we have a clear hypothesis, we know that we can't just force-feed muscle growth with more and more protein consumption, and we also know from various experiments that dietary protein intake is necessary for muscle growth. Therefore it is clear that a model where the more protein the more muscle growth we expect, but the rate of change of muscle growth also should be going down as one consumes more protein at least as a first order approach.
These sort of break-point analysis are very common when the data is not very good (we have a lot of variance), and when we don't know the mechanisms very well or they are too complicated to model.
When looking at the data from this more recent analysis I notice that the variance is clear that the range of protein intake that we are analyzing is very small compared to the variation that is expected. I'd consider to have just one group of people that are given a ridiculous amount of protein just to test what is the max amount of muscle growth, with that we'd get a good idea of where the asymptote lies.
Sorry for this sort of incoherent comment I just left, it's just that this has been on my mind for quite some time and wanted to leave a (sort of) explanation/my 2 cents.
Instead of examining the variance and maybe finding something interesting, which I understand wasn't the goal of the study, they came up with a useless model. I guess it's difficult to get published if you get no results.
we need studies that clearly control pure increased protein while maintaining total calories versus increasing protein while only adding calories from protein versus adding the equivalent calories of the second group in balanced calories including fiber, carbs, etc.
It still seems confounding to me what amount of the additional benefit at higher protein intake, beyond 1.6g/lb, is due to or could be closely replicated by additional healthy and well balanced calories.
For the past five years, I was bulking and cutting around 75 kg to 80 kg and all I ate was 100 g of protein while the rest came from carbohydrates and a little bit of fats
400 calories from protein? I am guessing you were eating around 2500 calories, that low protein is so unnecessary
@Antonio_Serdar a "low" amount is never unnecessary. Anyways, 100g of protein is perfectly adequate for someone 75 - 80 who isn't looking to maximise muscle growth.
@@Antonio_Serdar 100g of protein is honestly a pretty decent amount. If you're 75kg at 10% body fat, 100g of protein is roughly 1.5g per kg of lean mass. Could probably eat a little more easily but that's hardly a limiting factor for muscle growth or maintenance.
PROOOTEIIIN WARSSSS!!! Menno vs Helms & Wolf tag team. Dr Mike as the referee. LFG!
Only an octagon can scientifically resolve this debate.
Lol. But then UFC and One Championship will fight over which octagon
The ISSA, known as the 'International Sports Science Association', has recommended for years, between 0.8 grams to 1.0 grams per pound of Body Weight! And it works GREAT!!! 💪🙂👍
The fittest I've ever been was 180 and decent muscle, never shredded because I didn't care but low body fat and a flat stomach. I base my .8-1g/lb on that because I wasn't shredded at 180 but I was leaner so I aim for 150g/day minimum but often hit 180 so as long as I'm in that range I don't trip. I'm 200 now after years of not taking things seriously so I don't see a point to suddenly go to 200g when I know for a fact I'm not 200 lean. Its a guess for sure but if you were fit at a certain weight in your life its a pretty good guess.
With a quadratic relationship where the maximum is higher than the maximum dosis in the samples it would show a decreasing impact of increased intake similar to an asymptotic model. When taking a constant caloric intake one can even expect a decrease in muscle mass when the intake of protein starts decreasing the fats and carbs below thresholds.
Mr. Henselmans makes it sound like the authors only compared the first terms of linear, quadratic, and cubic, which I find very hard to believe as the only thing that makes sense would be to define quadratic and cubic to include all terms up to power two and three respectively. If my suspicion is correct, Mr. Henselmans' criticism would be invalid. Maybe he knows for a fact what they did, but that would be crazy! Just like he said. But would researchers really do that?
I tried clicking on the link for "Table 1.2, Supplemental Digital Content 1", I think my browser blocked pop-ups or something. I can't access it at the moment.
So, my point is, if they did consider all terms, first of all, of course cubic is better than quadratic which is better than linear, but maybe they report that the improvement is not significant. Or there is some regularization to detect overfitting. In any case, saying linear is good enough when quadratic and cubic options have been looked at is tantamount to saying they didn't observe much diminishing returns as protein increases. Although, that's also impossible. Hmmmm.... what happened?
I find it ridicolous that people obsess so much over hitting their protein goal to maximize gains. As long as you are not preparing for Mr. Olympia and don't need the extra 3,7% muscle gain for whatever it takes, just keep it above 100g per day and you would get like over 80% of the result with way less stressing about it and much cheaper and you don't have to eat a whole chicken breast everyday.
You do realize that chicken breasts are not 100% protein?
Yes but you can say that for a lot of things: caloric intake, rir, stretch of the musicals, timing of cardio, number of meals, getting enough sleep etc etc etc combined it can however make a substantial difference.
Imagine you like to do motor racing with your car. You can't make a Ferrari out of your Renault Clio. But you can still make it faster and better by changing the tires, chiptuning, making it lighter by removing the interior and optimizing the fuel. You will not double your max speed, but still you will increase your lap time significantly by optimizing everything you can together. It's the same with your body and training/nutrition.
Is the additional effort worth it?
That’s something everyone has to decide for themselves.
@@highsoflyify Good take
So it would be ridiculous for YOU to obsess. Imagine obsessing so much you obsess about how much obsessing is not too much obsession.
Sometimes people like to do A rather than B if A is marginally better.
i never thought i'd see my math exam content in an optimal protein intake video
IAAO method is also stronlgy influenced by habitual protein consumption (you usually consume more, you usually oxidise more). A washout of at 3+ days is requiered, what simply does not happen in most studies.
What Mic and Camera do you have? great video btw
Yes! I fully agree with you!
P.S.: Look forward to your meta.....
In research trials we try to minimize variation in variables outside of those we are investigating in order to improve statistical power. We then use regression methods on this abnormally homogeneous data to make predictions about future responses. If we get similar values in future controlled studies, we take it as confirmation of our previous findings. But how good is this method really for predicting responses in subjects that are different from those in our trials. Data science methods take a very different approach by collecting data with a high degree of variability to create more robust models that are better at predicting outcomes from a wider variety of test subjects. The data science approach would seem to offer a better basis for modeling than controlled, randomized studies. The problem is, of course, getting large datasets including a sufficient number of relevant factors.
Do I have to look at the leucine content of my meals to maximize MPS when targeting the 20g-30g of protein? are 100g of raw weight chicken breast enough protein in one meal?
No (leucine), yes (100g = 30g)
Linear vs. Quadratic vs. hyperbolic doesn't fit the whole shape of the curve nor does it have to. It/they simply add in one or more free variables with which to fit the data. A set of linear data with a breakpoint would be better fitted by a quadratic equation than by a strictly linear one (because the extra parameter represents some sort of underlying biological phenomenon). The fact that the linear model fit better than more complicated models indicates that the or any additional parameters don't offer any predictive power. To wit, 1.6 is almost certainly not *the* value for everyone and it's almost certainly something more like 1.5-1.8 or more. Edit: And, yeah, somewhere north of 5g/lb./day I expect the gains to come back down, even with a breakpoint.
that makes a lot of sense that's why a lot of pro body builders seemed to requite higer protein becouse they where on gowth hormone so not just their muscles where bigger but most organs as well
1:42 No, it's not. 1.5 g/kg is 0.024 oz/lb, which is actually 32% less than 1 g/lb (which is equal to 0.035274 oz/lb). 50% more would be 0.052911 oz/lb (or 3.3 g/kg).
Also I have no idea why you keep confusing yourself by mixing units. Just stick to one system!
Here’s my thoughts. As long as daily protein intake consistently meets the requirements for staying at one’s natural limit (meaning at the lowest possible body fat percentage of current body weight, or at the highest possible body weight of current body fat percentage) while maintaining a calorie balance (i.e., maintaining current body weight), along with appropriate training volume, the protein demand will be sufficient in the long term. This is true as long as one is not constantly in a state of weight gain or weight loss ("not constantly in a state of weight gain or weight loss" means gaining weight and then maintaining weight long-term, or then losing weight and reaching a balance point, or losing weight and maintaining weight long-term, or then gaining weight to a balance point). However, if one wants to stay closer to or reach the natural limit during a period of weight gain or weight loss, more protein will be needed. The greater the calorie surplus or deficit, the more protein is required to stay closer to or achieve the natural limit during weight gain or loss. The same applies to training volume. Moreover, there is a threshold effect between training volume and protein intake, meaning that whether one can stay at the natural limit or how close one can get depends on the limiting factor between the two. More experiments on well-trained individuals are needed. Control their protein intake and training volume, and make them stay at their current body weight for a period of time, then test their body composition. The closer one gets to the natural limit, the higher the minimum protein intake and training volume in terms of maintaining current body weight and body composition is required, but the actual amount may be lower than what most people currently think.
This. A regular person uses about 30 grams a day of protein. Give them more and.. nothing happens, they burn it for fuel. Exercise a bit and you might use 60g a day to rebuild the muscle and build a little. Exercise more, 100g before it's burned for energy, etcetera. If you're constantly sore from Doms and going to the gym twice a day, I guess go nuts, but you better be eating enough so it doesn't just get burned. There's no such thing as optimal. Even if you work hard and don't get the maximal quantity of protein you could've used, you'll still grow, anything over that 30g is usable. Even people given low protein diets for kidney disease with only a mere 43 grams of protein a day BUILT muscle with resistance training, when they weren't limited in protein before going into the study.
@@mikafoxx2717 My thinking is this: If training volume is extremely high, and an extremely large amount of protein is consumed while maintaining no calorie surplus or deficit (with the condition that other essential nutrients, such as adequate fiber and fat sufficient to prevent gallstones, are also consumed), then a trainee who is far from their natural limit will experience rapid changes in body composition (with weight remaining the same, but body fat percentage rapidly decreasing). In this case, the more protein consumed, the faster the body composition changes. On the other hand, a trainee who has reached their natural limit will see no changes in body weight or composition. Therefore, even if not enough calories are consumed, the protein will not be wasted and burned, unless the natural limit has been reached (at which point, it’s possible to replace some protein with carbohydrates and fats, as long as enough protein is consumed to maintain the natural limit, making the diet more flexible).
excellent video. Thanks
What Ive learned being a mathematician:
A ton of studies use random cheap ass mathematical assumptions and even researches often have confusingly bad statistical knowlegde.
given the massive spread of the data (on the Y axis), even of a linear model fits the data best, the are extremely strong questions about effect size and confounders.
but how about increased cancer risk by increased igf-1?
NAH
What about foamy urine as an indication of eating too much protein??
I'm pretty sure that's an indication of kidney failure.
Just train hard and eat when hungry, lol. It's good to "know" what optimal is but as is shown by the anabolic window benefitting from more protein ,AKA being hungry post-workout, your body will always notify you on if you need more protein. If you can and want to minmax muscle gains you could consider that new analysis, but the side effects of that recommendation might be miriad indeed.
The stats don't need to fit the theory; the theory needs to fit the stats.
I think the exponential curve they used is already what you name the logarithmic curve.
Logistic curve must be the answer (“S curve”)
Menno, you are great, but you made an error at 1min41sec into the video -- you said, and your big red insert said, that the new meta-analysis recommended a huge amount of: "1.5g/kg" but what you *meant* to say was 1.5gm/lb, which is vastly more than current recommendations.
not bored, but maybe a bit depressed. Good breakdown! Thanks!
Think about how all the bodybuilders and general gym bros have not been eating 3+g/kg and still get jacked. Menno is right
I'm sorry if you answered this but I might have misinterpreted it somewhere...
Does the fat free mass recommendation include organs including skin?
If organs need protein, is that taken into consideration with the 1.6g per kg of bodyweight?
1. Both ffm and tbw make recommendations of protein intake for your whole body. If you dont workout the advice is 0,8 grams per kg of tbw.
2. Yes
I haven't read their meta. If by quadratic and cubed they literally meant x^2 and x^3 then fully agree that doesn't make much sense. If they meant a+bx+cx2 and a+bx+cx^2+dx^3, those would have had the expressive power to capture a breakpoint but then it would be surprising that linear was the best fit, as more expressive power normal gives a lower rmse.
It's a+bx+cx^2 and a+bx+cx^2+dx^3
I suspect the relationship is probably square root or logarithmic, or maybe logistic
best Rescource ♥
Thanks for your videos, they have helped on my journey for sure!
I think maybe @1:40 there may be a kg/lb issue with either what you are saying or with what you show on the screen... saying that 1.5 g/kg is 50% more than the conventional 1 g/lb (not kg) yet @5:45 your hypothetical shows 5g/kg being aprx 2 g/lb which is much closer. But I am still pretty new to this and may be misunderstanding something.
Unless you're a student, the issue here is not that protein is expensive. Chicken and ground beef isn't. It's more that I want to take in carbs. I'm sticking with 1.8 per kg. I think that seems more likely to be true. I find it really hard to keep protein below 200 g, though.
Can't wait for the Milo Wolf PROTEIN SUPPLEMENT !!!
You know it's coming 😏
@@ImBarryScottCSS He just ranked whey protein as S tier in supplement tierlist, so...
I would only buy it if it gives me the required protein amount per day in a single scoop!
@ With 5% better bioavailability
It looks like the graphic is wrong early in the video it claims the new research suggests 1.5 g per kilogram
Menno, do you recommend 1.8g/kg based on our current body weight or goal weight for those of us who are on a bulk or cut?
I wonder if you were able to see the recent mass office hours before making this post. All of your points were already addressed there and so the timing of this feels a bit sloppy considering the researchers went to great lengths to cover all of your arguments
They didn’t cover all of his points
@@ctcpcp which points did they not cover?
I’ve always gone with the 1gm per pound of body weight and that’s were I am staying.
anyone here who noticed that more protein cause constipation? thanks
@1:44 1.5 g/kg is not 50% more than 1 g/lb. Take a 100 kg person. At 1.5 g/kg they’re taking in 150g. At 1 g/lb they’re over 220g.
So they didnt compare it to a log graph? Weak study
But what about definition period?
You were very nice about it, but forgoing a logistical model like the one you mentioned and instead testing quadratic or cubic laws is pretty out there. It makes zero sense to do that. Almost all metabolic processes follow logistical growth laws. You can try to linearize that for simplicity, but quadratic or cubic isn't simpler. It's fine to test unusual fits as long as you don't overfit, but forgoing the obvious, very likely mechanic for the unusual one just doesn't make sense.
It may not be as far-fetched as it seems. I had the same reaction as you, so I wanted to check the paper. In the supplementary materials, you can see the shapes of the quadratic and cubic models-one quadratic model is almost a linear fit, with the end slightly resembling logistic growth, while one cubic model basically follows a logistic growth curve for the most part.
They also modeled "dietary protein (g) per kilogram of fat-free mass (FFM)" instead of just "dietary protein (g) per kilogram of body mass (BM)", and the resulting model look solid. This is only the second video I've watched from Menno, but dismissing the study just because of the model choice doesn't seem particularly serious to me, in this particular case.
Did those studies control for fat gain?
1g per lb is more than 1.5g per kg. Was it sarcasm or getting them mixed up? 1:43
Nah he was just being sarcastic, one kg is 2.2lbs, and yk 2.2 is bigger than 1 so lbs is definitely larger than pounds.
Is kg bigger than kilograms?
(Couldnt help myself, lol)
The only people I see worrying about how much protein to eat are small people. All the big boys just eat 5-6 meals a day with at least 50 grams of protein per meal.
I will never understand why these studies only look at a very small handful of very simple models like linear, quadratic, break point, etc. It takes a lot of time, money, and energy to put these studies together and collect the data. It takes literally less than 10 minutes to add a python import (like sklearn) and run TONS of different models on the data ranging from extremely simple to very complex.
Bayesian statistics tend to favor simpler models. The quadratic (a+bP+cP²) and cubic (a+bP+cP²+dP³) models "fit the data better" than the linear one, but at the price of over-fitting.
@ There still seems like better models to try like any flavor of splines (which I supposed the break point analysis is like a spline but it’s a very simple version), logarithmic fitting, logistic regressions, etc. Shoot why not even set up neural networks with limited nodes, limited depth, and try arbitrary activation functions.
@ Researchers (whether Bayesian or frequentist) tend to favor interpretability and robustness over raw predictive power. This isn't just a preference; it's grounded in solid mathematical principles. Overfitting, lack of generalizability, and reduced explanatory value are real concerns when dealing with more complex models.
Note that a model like a + bP + cP² + dP³ has only four parameters but already offers a lot of expressive power. You can approximate many variations of sigmoidal curves with it.
Many studies are designed to test specific hypotheses rather than maximize fit. This isn't a data science or ML competition. It's about drawing meaningful conclusions from the data.This isn't a data science or ML paper.
That said, more complex models like the ones you mentioned, could be explored... if there were enough data to support them. With hundreds of thousands of participants in well-designed studies, we could infer some really interesting dynamics. But we're not there yet.
If people tracked their food and work outs over long periods of time more and reached their own conclusions the result would be more accurate for the individual than a "one fits all" rule of thumb
Not to mention all the nutrition you’re missing out on because all that extra protein crowds it out
Study:
"Dietary Protein Intake (g) - Per Kilogram of Body Mass"
"Very serious trainees who care a lot about their muscle mass should consume the higher end of this range. So bodybuilders, for example, should consume as much as 1.5grams per kilogram. 50% more than even the pro bodybuilding wisdom of one gram per pound."
90kg bodybuilder - 1.5g per kg = 135g protein.
90kg bodybuilder - 1g per lb = (90*2.2) 198g protein.
Did someone on Menno's team misread the study or something, or doesn't understand the conversation from kilo's into lbs?
In what world is 1.5g per kg extreme?
Change it to 1.5g per ibs not kg and you got it
@@ctcpcp The study he's referencing is using kg, and that's what he himself says.
Seems like an unusual mistake for Menno to make.
A good rule of thumb for biological systems is that X (whatever you're investigating) is optimized and not maximized. This fits with your objection to the linearization comments.
Laziness or intellectual dishonesty-you decide. If this "science-based fitness influencer" had bothered to click the link right next to the mention of quadratic and cubic models in the meta-analysis, he would have immediately seen that these models aren't FFM(P) = P² and P³, but a+bP+cP² and a+bP+cP²+dP³. I can't fathom how he didn't stop and think, "wait, that can't be right, let's investigate for two minutes before making a 25-minute video about this study". Not to mention the blatant unit error at 1:40, both on-screen and in the script. Deeply unserious.
The analysis can best be described as reaching. Menno here to cut through the bs as ever, appreciate your efforts dude.
how big would you say is the diffrence of potantial gains on a lean bulk if everything else is optimized. 1.8g/kg = 100% and 1 g/kg = x% ?
Im worried that maybe the body adjusts over time to the amount of protein you’re consistently eating. I want to see studies on people who have been eating 2g/lb protein for a few months to see just how high the upper limit really is.
I trust the guy that tells me to save money. Remember any scientist makes money by you by influencing your purchasing decisions. Like those sugar scientist blaming fats instead of sugar
Why don’t you reanalyse their data in my field it is common that the raw data can be downloaded so peers can reevaluate it.
here we are again
Can they take the same trainees profile for a studies ? Same years of training, same weight, same age, same height, etc... At least we would have a good comparison point for a range of protein intake from 0.8 to 3gr/kg for example. But maybe I'm saying shit here as i'm not a scientist 😅
S-tier thumbnail
1:41 1.5 g/kg ≈ 0.68 g/lb which is significantly lower than bro-bodybuilding wisodom 😉
1:45 I think you mixed the units.
1.5g/Kg is less than 1g/pound
If you listen to a guy like Mike Mentzer, he never gave an exact amount for protein intake. Always just said to have about 25% of intake to be comprised of protein. Muscle building is an extremely slow process for naturals and this amount seems right to me.
So menno recommends 1.8g/per kg/per day to maximise hypertrophy or a range from 1.6-2g/per kg/per day. Is this based on overall bodyweight or based on fat free mass?
Also what if you are very overweight, how would you calculate this?
Total body weight. Most people aren't consistent in their application with BF measuring tools or don't have access to 5C body comp machines to accurately assess their BF%.
And for obese and very overweight individuals, he uses Eric Helms' recommendation of 2.3g/kg LBM (lean body mass) per day, if you have a reasonable estimate of someone's BF%, or 1.8g/kg/day. Whichever one is lower.
Basing it on target/goal body weight makes the most sense. Most people underestimate how lean they actually need to get anyways so it skews high. Its also important to note that the benefits of high protein are incredibly marginal in the grand scheme of things so I wouldn't fret too much either way. Find an acceptable range and get near it with high quality sources and you are likely good.
12:56 he touches on this here
Ah, the protein wars rage on! After the armistice, I do expect Wolf and Henselmans to collab.
You made a few mistakes in this video regarding the units. You said g/kg a few times when g/Lb was applicable. Sometimes g/kg was the correct unit but other times based on the numbers, g/Lb was the right one yet you said g/kg. I'm suprised you didn't notice it. It might confuse some people because the difference between those units is huge (x2.2). Maybe you should pick one unit only and stick with it so you don't confuse yourself.
18:40 Bayesian bodybuilding haha never thought my math brain would be tickled like this in a body building video
We are gifted to have such a mind establishing the real facts on maximum gainZ.
It's a real wild west of egos, skewed data and shadowy agendas in scientific literature world and especially so in human performance. It's almost impossible to pick apart if you're not a highly motivated science/data expert. Thank you for cutting through the crap
So taking 1 scoop instead of 2 kept me small.
"The range from 1.2 to 3.2 is only 1.3. So if you do 1.3 * 0.07, we're getting close to a 0.1 effect size, which is close to half of a small effect size... So now we're talking about almost a small effect size to go from the bottom of our highest range to the top." -Helms
20:54 Long training days or non training days?