A

This week on the Training Science podcast, we sit down with Dr. Jess Rothschild, sports nutritionist, data scientist, endurance athlete, and freshly minted PhD. Jess just completed one of the most rigorous bodies of work on pre exercise nutrition and athlete monitoring we've seen in a while. In the podcast, we cover what actually triggers training adaptation at the cellular level, whether fasted training does what athletes think it does, and why nutrition advice that works for the group may be completely wrong for your athlete. Another conversation with a pioneer in this. So without further ado, I now bring you Jeff Rothschild. I'm here with Jeff Rothschild. Jeff, welcome to the podcast.

B

Thank you. It's good to be here.

A

Good to have you on. When did. I'm sure we've met before in person when I was. Because it must have been around the time I was leaving and you were going.

B

Or maybe I think we missed each other in person. You talked to the group not too long ago. I was on one of those calls, but I don't think we met. But I guess it's worth saying that your work was one of the things that really put A and T and sprints on my radar when I was looking at PhD programs or even beforehand.

A

So that is cool.

B

Wanna let you know that that's cool.

A

Well, yeah, I mean it looks like you're working with Andy Kilding, Dan Plews, probably others there as well that we've both connected with. So that's super cool. Can I ask you what work in particular caught your interest to drive your PhD topic that we'll talk about here today?

B

Yeah, I mean the topic came from, you know, before I did the PhD, I had previously done a Master's in nutritional science and as a registered dietitian. And so I was working kind of in a private practice setting in the US for several years and it just kind of, I was definitely still always interested in research and did a little bit in my master's and just kind of kept a close eye on it. But I kind of found, you know, as much as you try to be an evidence based practitioner, there was so many like key questions that people would be asking that you just like you could kind of guess but you really, you didn't know. Like, I mean something as simple as what should I eat before exercise was like, like we, we kind of. Well, I felt like especially like eight years ago, like you could kind of tell but you, you couldn't really. Like there's just so many caveats and there still is. But like that, that kind of general sense of like, wow, there's some I can either sit around and kind of wait for other people to, to answer some of these questions that I was most curious about, or I could just kind of add some, you know, try to contribute something. So that, that was kind of what led to wanting to do a PhD and kind of focus in on like these kind of core questions. Like said like, what should I eat before exercise?

A

Yeah, that's awesome. I was up in Dallas talking to some investors in the Athletica space and we were just chatting with an investor who's a, who's a cyclist. And he asked exactly that. He said, well, will your, will your program tell me what to eat? I just want to know what to eat. I don't know what to eat. So it's, you know, I don't think it's, we've, we've answered that yet, but maybe we'll dig a little bit deeper in it, into it today in terms of what the evidence that you've drawn up will maybe tell us a little bit more about that. So, so that's a great, that's a great intro. So you're, I know you're, I'm talking to you in New Zealand right now, but you are, but you're originally from, is it California?

B

Well, I lived in Los angeles for about 20 years before moving here, but I grew up on the east coast in Buffalo, New York.

A

Okay, awesome. So a little bit all over. That's super cool. But based in NZEDRA at the moment.

B

Yeah.

A

Yeah. And you're a kick ass athlete yourself, aren't you?

B

Oh, no, not like you and Blues in that category. I've dabbled and now I'm more just trying to hold it together. But you know, like, I, I, Cycling is kind of my preference and I've done a few triathlons, but, you know, just very, very mediocre by, by most standards.

A

But I, I mean, I, I love, Honestly, I don't see too many, if any, skill sets out there like you, you seem to have. Jeff, when I'm researching your profile, not only are you a nutritionist, dietician and have that, that skill set from the practical standpoint, but then you have this incredible tech set, skill set as well. Right. And you're, I think you do performance and technique analysis for HBS and zed. I mean, that is so rare.

B

Yeah. And it's kind of funny that when I was getting ready to come for the PhD, you know, in the six or eight months before, you kind of, you know, want to prep as best you can and so I would, I didn't really know anything about statistics. And so I tried to take a few like online courses, you know, on Coursera or those free classes. And I every week, you know, you watch the lecture and then the first always be like a lab exercise. And it would be kind of some Introduction to R. And I literally could not wrap my head around it. And it actually became like my biggest concern. Moving to New Zealand wasn't like moving with my wife and young kid at that time to a different country. I'd never even been to. Starting a PhD at age 40, like, not that was not my biggest concern. My biggest concern was actually that I was going to be forced to use R in my PhD. Which is funny in hindsight because one, you can certainly do a PhD without using R. But that was kind of like the thing I was worried about. And then a couple months in, during my first study, it was this, we did a survey and I was analyzing most of it in Excel, but there was just kind of one thing that came up that kind of this guy, Tom Stewart, who I'll be eternally grateful for, he said, you know, this is actually just easier if we just do an R. So he gave me just click through this and we can get the thing we need. It's like, okay. And then really from then on, like I probably used R almost every day, except maybe 10 days total since in the last seven years, you know, I just like kind of just started dabbling and it just kind of. I saw how valuable that as a broad skill set could be, basically general statistics and analysis. And I just made it a real point to double down on learning that and bringing that aspect into my PhD, which then has affected my nutrition practice certainly. So I spent three years after the PhD as a performance nutritionist at a high performance sport, New Zealand. Then I transitioned about six months ago to like I said, performance and, and analysis role there. And so it's been an interesting kind of journey, for lack of a better term.

A

Yeah, that's awesome. We certainly didn't have that at HBS and Z when I was there. So it's really very, very cool that you were doing that to become more evidence informed in terms of some of these decisions. So what question do you want us to start with? What was the key underlying question? Was it what do I eat today? Like, what do I eat to help my performance? And that is just such a loaded question, right? And like depend, right. Like on so much stuff. But where do you, where did you

B

start with the PhD? Yeah, I mean, I Think that the thing I wanted to focus on was around training. You know, so much of nutrition, rightfully so, is based around like, what should I eat on race day? That's what a lot of people focus on. But, you know, there's, I don't know, some percentage you can, you can influence things during races and obviously the longer the race, the more you can influence it with nutrition. But think about how much improvements people get across training even just from within a season, from the start of a training, you know, from the start of the year to the kind of their peak time, let alone across many years. And so that the, the ability for nutrition to, let's say impact and, and compliment the training you're doing, I think was, is pretty interesting. And that kind of then dovetails, of course into this whole world of carbohydrate periodization and things like that. And so that I really wanted to kind of focus on training adaptations as best as I could, just try to narrow, narrow the focus down.

A

Oh, well, that's a good, that's a good place to start because I've, you know, I've read through some of your papers. One of the ones you did in terms of training adaptation was you looked at a meta analysis or a meta reg question on the key signal. One of the key signals for mitochondrial biogenesis downstream to PGC1 alpha is AMPK, and you did a huge meta analysis on that, if I'm not mistaken. Is that one of the areas you started with?

B

Yeah, exactly. Because I thought, okay, if we think about, we're doing some exercise and as you well know, there's these different signaling pathways and you've done some great papers and I can't remember which ones, but I know I definitely read associate your name with some of these. You know, you've got the contraction induced signaling and there's the reactive oxygen species and then there's kind of the energy sensing. And so this, I think this, this is a really. People, it's something overlooked because this is why you can get these contrasting findings. Like you can do a study where you could show that let's say vitamin C and vitamin E blunts the reactive oxygen species signaling pathways, but people still can get improvements in training. You go, well, okay, why is that? Well, that's because there's a lot of, I don't know if redundant is the right word, but these kind of overlapping mechanisms that you can get mitochondrial biogenesis in a whole bunch of different ways. So that's, Yeah, I think that's important to keep in mind. So I just chose, I thought, okay, let's just look at some of the signaling pathways because that's kind of a reason people might do fasted training or you know, high or low carb or something, or be afraid of carbs around training. And so AMPK is just one of the signals. But it is like you said, it's a key signal. And so we focused in on that and I looked at kind of does what's affecting it basically. And I tried to think, is pre exercise nutrition affecting it during exercise? Is it the exercise intensity what really matters? And I think the big takeaway from that for me was if you're doing high intensity training. So basically anything over critical power, just intervals or anything. And this, I guess this would, is how I'm generally seeing things in the big picture, not just with ampk, but like if, if you're doing hard training, I don't think it matters like what you eat beforehand. If you want to be fasted, you can. If it's not that long of a workout or if you want to eat, I don't think you're blunting anything or attenuating anything. If it's low intensity training, that's a different story. And that's where glycogen probably matters more in terms of the signaling. So I guess to rephrase that, the high intensity exercise is going to increase ADP and amp and that's what's going to elicit this turn on ampk AMP kinase. And so yeah, it doesn't matter if you're fed or fasted. You'll find studies that show, oh, the more AMPK signaling in the fasted state or something like that, or with low glycogen. But again that's generally speaking that'll be at low intensity. So if you're not driving the signal via like intervals and you're just doing low intensity training, there probably is a role of being having lower glycogen. It's kind of where you end is what matters. So if you start with medium glycogen levels and do a long enough easy ride, well, you'll get kind of low by the end. And I think that's the key thing. So basically where you end or how hard you're going is kind of how I see the, what it boil down to.

A

Nice, nice. Um, yeah, so the, the prac. What's the practical message? Just on that one is number one, if you're doing high intensity doesn't matter. And if you're, and then if you're doing, if you want to amplify potentially the ampk signal on the, on the prolonged run or prolonged ride, potentially you, you have the option to go faster there and you might, you might amplify for the long duration. Is that right?

B

Yeah, potentially, yeah. And the other thing people kind of mix up, I think it's easy to do with fasted training is like we got muscle and liver glycogen, as you know, and so fasting is only really lowering your liver glycogen. So our muscle glycogen, wherever it is, when we go to sleep, it's more or less there at the same level in the morning. So that's where thinking about what you've just done, like the prior day's workout and how much carb you're having after that workout before that next workout is relevant.

A

Okay, cool. So let's, that's moves nicely into another one of your papers where you're looking at sort of the pre meal beforehand in nutrients in 2021 where it's like carbohydrate or protein or fasted. And what were you doing there? Is that more of a. Yeah, you're not really doing meta analysis here now as well. It looks like you're using real people.

B

Yeah, yeah, no, absolutely. That was a real, real people study, acute crossover design. So was it 12 or 15 people or so were in the lab and they did three trials. So basically we looked at fat, oxid substrate use, fat oxidation is what people care about. And then some intervals, kind of your best, best work on your intervals, best performing intervals in terms of fat oxidation. Again, people will typically go fasted if they want to increase fat used during exercise. And whether or not like the downstream effects of that, you know, is probably worth a separate conversation. But it's pretty clear that if you're fasted, you'll burn more fat during an easy ride than if you're, if you're fed. But the really interesting thing that there was a couple, this wasn't the first study to show, but there's a couple others that showing pre exercise protein essentially lets you burn the same amount of fat. So you can get something in. You could arguably maybe protect, protect your muscles and things without, you know, sacrificing or changing how much fat is being used. So that is pretty relevant because sometimes people are just hungry. They want, they might want to, they might want to have a ride where they're burning a lot of fat, but they're hungry or something like that. So protein is a fine option. And again also going long periods of time without Protein or in the fastest state could be arguably catabolic. So getting some protein in can protect you from that standpoint without sacrificing any of the fat burning. So that was, you know, it was nice to show that and give people the option for protein pre exercise protein. And then from a performance standpoint, the workout. Oh God, I'm forgetting now, but it was like eight by three minute intervals or something like that five years ago now or six years ago. But basically performance didn't matter. So saying total work done during these intervals, giving your best efforts, you know, does it matter if you've eaten or not? And the, the answer in this case was no, it didn't matter. The big caveat is the workout. The total session was 60 to 75 minutes, something like that. If the workout was two hours, two and a half hours, I do expect we'd see a difference in terms of what you could, you know, produce. But for most workouts someone's doing like on a weekday, especially non professional that are going to be in that like less than 90 minute range, I don't think it matters.

A

Yeah, what about, were you looking at fat oxidation in those, in those trials? Fast.

B

Not during the, not during the intervals, only during the early stages. Kind of the low intensity warmup part.

A

So basically takeaway is that you can eat whatever you want, performance won't suffer, but fat oxidation is going to be suppressed if you, if you eat carbohydrate.

B

Yeah, yeah, exactly.

A

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B

Yeah. So I mean the PSU were kind of walking through more or less chronologically. I mean the first one was a survey of which is pretty good, about 2,000 athletes. And this was before COVID Just before COVID But like I think everyone got surveyed out during COVID A lot of athletes probably got asked to fill out a lot of surveys. So this. But basically looking at like what are people kind of how, you know, a typical kind of start to a PhD. Like what are people actually doing? And this was kind of surprisingly unknown like how many people actually do fasted training? It's one of those things that you know, gets talked about a lot but there really wasn't much data on like a large scale. Like how often is that practiced? Um, there was a few, there's a few small studies of elite athletes and things. But like. So that was a pretty good novel contribution. And it was about, you know, about 2/3 of athletes do some type of facet training. And we also looked at, you know, how often people think about periodizing their nutrition and things like that. So it was nice to kind of set a stage of what. Yeah. What people are actually doing. Which kind of then yeah I guess highlights the direction to go in for the rest of the PhD. I just jumped to the end the most recent study I published, interestingly that the actual like what people actually do in practice based on the 12 weeks of recording their food lined up really, really well, really really closely with survey different people in the studies. But like it seems like about 2/3 of the athletes do fasted training and yeah, it was interesting to see that alignment between studies.

A

Yeah, that's, that's awesome. I'm. I'm certainly for whatever reason, I love fasted training personally myself. Right. Like it's just this morning it was, it was a swim workout this morning I woke up, you know, Moving around the house, I had all the options in the world to, to eat, but all I wanted to do is drink my coffee and then get out the door and go have my swim workout. And I just had like zero desire to, to feed. So you know, and that's, you know, it's an easy swim but, or you know, with a few intervals and stuff that are in there. But it's like I know myself personally, I've got all the energy on board that's going to be. It's all I need to do that swim workout. And then I came home and I was. Breakfast was amazing. Right. Like I just, that just that's kind of the practice. I love the fact that two thirds of your, of your sample or thereabouts seem to be sort of similar. I'm not that much of a freak as I thought I was.

B

Yeah, yeah, that's right. Yeah. I think, yeah, it's largely personal preference. I mean I think people don't seem to fight. At least I haven't seen as much fighting about it anymore as Maybe there was five or 10 years ago. And the feeling is it kind of doesn't matter too much. I mean there's maybe like we talked about it already, like a few small instances where it might matter a little bit, but largely it's like if you want to cool and if not, don't. But I think one, one caveat, maybe this is a segue like for athletes that have a big aerobic capacity and a high training volume, that's the time I would kind of most caution against facet training because you can just create such a deficit. Um, someone who's not fit or rides, you know, 45 minutes in the morning. Yeah, it's, it's just doesn't matter. You know, training five to seven hours a week, an hour a day, like you're just not going to create that much of a deficit. But you got someone with a big engine training even 10 to 15 hours a week, let alone 20 or 30. A fasted training session is just going to dig such a hole for you that I think it can become a challenge to dig out of. And something that wasn't directly part of my Ph.D. but I think is really interesting is this within day energy balance concept. And that's not spending too much, basically spending less time, not spending too much time in a really huge deficit. And so someone riding fasted for a few hours in the context of a big training week, you can basically dig yourself a big hole.

A

Totally. So yeah, Luke Evans is an athlete that One Ironman Canada, who I'm kind of coaching now and helping him with his nutrition. And ultimately it's a learning process for me as much as it is for him. I'm just working with him and we're just constantly trying different things. But he says exactly. We've come to the realization after the last year, that's about exactly how he operates. He operates with fasted. If the session's less than 90 minutes and it's in the morning early, he prefers just to kind of go fasted for it. But anything longer than that, he wants to just kind of, like you said, he doesn't want to dig himself a deficit. And he pauses the execution of that workout to feed beforehand, let things settle, and then execute the workout. And that's what, that's what works best for him through a lot of various different trials. Trial and error.

B

That's cool. Yeah, it doesn't surprise me.

A

Yeah. So what's next on your list of questions that you're trying to unpackage with your PhD, Jeff?

B

Yeah, so I guess thinking through it. So again, we figured out first, what are people actually doing? And we did that acute study and then the AMPK analysis. I also did kind of a similar thing for rer, the respiratory exchange ratio or more substrate oxidation. And that was another one just to kind of go, God, you know, just challenge some assumptions. And the other aspect of it was, we know this is very clear. Like if you're fasted, like we said, and it's not high intensity exercise, you're going to be burning more fat than if you're fed. If it's a high intensity, you're going to be burning more carbs than if it's low intensity. Like, there's some things that are really obvious. If your glycogen is lower, you're going to be burning more fat. Like all those things. But what I was curious about was, was kind of pulling more than one lever at the same time. So what happens if it's, you know, if it's, I don't know, low glycogen and, you know, and you eat during exercise or these kind of things. So I try to do this another analysis that essentially kind of tells you what happens if you pull this lever and not this lever or how they kind of work together. And one of the big takeaways was that estimating fat oxidation, or rer, the percentage of fat being used, it's not very clean. Like, even if you know what someone had beforehand and their glycogen levels and the exercise Intensity, like there's still this huge variation in it, which is not necessarily good or bad, but it's, I think it's interesting that so many people kind of put so much stake in like, okay, I'm going to do this. People think they can assume that they can guess what it's going to be more than it really is. So that was one big takeaway and the other one was kind of going what is having the biggest impact on, on, you know, on what we're burning. And so, you know, the big ones was, you know, the longer, the longer you go, meaning the longer your training session is, the more fat you're going to burn. So for example, I think it's a mistake for that people that want to focus on fat burning rides, but they're riding three or four or five hours and kind of being afraid to have carbohydrate. You know, three or four hours you could be having I think a reasonable amount of carbohydrate and call it even if it's a gel or an hour, 30 to 50 grams an hour and still be burning a lot of fat.

A

Yep.

B

If you want, if you have a decent, you know, engine. And again, you're, you're three, four hours into a ride, you don't have to like be afraid and just drink water the whole time. So it's like people can overcorrect based on this. Like, you know, the focus is fat burning on this endurance rides. And yeah, you probably could get through it with just water or with very minimal carbs. But again, I think one of the takeaways from that kind of the avenue of research was going, gosh, yeah, duration really, I would say trumps all and daily fat intake matters. And then if pre exercise, if you have a bunch of carbs beforehand, that's going to change it. So it's kind of figuring out what's shifting it one way, what's shifting it the other way. And then what happens when you, like I said, pull those levers together.

A

But that's a nice myth that you kind of mentioned there. Like you're not going to necessarily blunt your fat oxidation level if consuming carbohydrate in the middle of your session. Right. I think it was James Morton did a nice tweet there the other day. Maybe you two were exchanging. I can't remember where I saw it but he was pulling out some data where it was showing exactly that. Where the different levels of the carbohydrate during were still associated in well trained individuals with I guess fat oxidation rates of 0.8 or, or above. Right.

B

So yeah, that's right, yeah. Especially like the more trained you are, those are the bigger kind of engine you have. And then like gosh, yeah you could have. I think it's Mark, one of Mark Fell's studies, like a bunch of stuff from Liverpool they've been like, they're cranking carbohydrates in and still having these huge, huge fat oxidation numbers because they're riding for three hours at like the threshold or something like that.

A

Yep, yep, yeah. Which, which is, I mean I don't think we necessarily always knew that but you know we're getting more and more data around this but yeah there was that, you know there was that kind of belief or thinking at some point where yeah we don't want to, don't want to sabotage the fat burning kind of thing mid ride or whatever, you know, as you're, as you're doing not. I mean that being said, I've, I've seen some phenomenal outputs from some of my, you know, Ironman winning athletes. Andy Buescher, Kyle Chuckingham, they've done eight hour fasted rides they, they actually loved and they, they got, they actually felt this extra kick from about three hours onwards where you know, I hypothesized potentially ketones kick off and they just, they feel great, they, they're like, it's weird but I've actually felt stronger as I went on. You know, it's.

B

Yeah, that's interesting. I don't doubt it at all. Is that like, though, is that, is it like a catecholamine release and they're just getting, is it a bigger stressor? I mean do you find in those cases they could recover?

A

Well yeah, they did. And again if you follow some of that, which I know you do, you follow some of the ketone science. Well it's actually quite a, you know, quite a useful little signal molecule. All the various different ketones that are out there that do have a lot of recovery amplifications from both a signaling standpoint and an energetic standpoint. And again I think this is probably the point where we need to go to some of the heterogeneity findings. The fact that this, we are living, you know, we are talking in a minefield of inter, like individual, you know, responses that are out there. Right. Like I'm telling you about Andy and Kyle and they had their experience but you, the listener that might totally not relate to you and how you are. And I think your data at least the last study that really blew My mind was just how variable it kind of it is across different individuals. Um, which means that everyone's right and everyone's wrong. So I'll let you just, yeah. Kind of spin on that.

B

Yeah, yeah, no, I mean that that's a segue into. I guess the, the next part of the PhD is we had like this epic training study set up. You know, because when we talked about the acute study and then, but really want to know, like, okay, if you do fasted rides more often, are you going to get better training adaptations? Right. And so we started a great study with biopsies and like a three week training intervention. And there was a mix of, of fed and fasted training sessions with like the high intensity ones were, were fed and the, the low intensity ones were either fasted or had carbohydrate or protein only. So there's really a logical extension from that acute study. Then Covid happened. So you know, well, the COVID the second round in New Zealand. So that kind of halted. So I had about four, five subjects or something like that. And again, this would have been the study that we all kind of wanted the answer to. Trained subjects doing like a real good training program and not just like all fasted training or all carb training like it was. And then some of those other fasted training studies they would give like just ridiculous amounts of carbs. So and, and understandably for, you know, sometimes it's just mechanistic studies or you want to have a proof of concept. But we had this epic study laid out and started had this like all of a sudden with like 24 hours notice, oh, we're going to this lockdown. And this was like what, 2021? So a couple months ago, we don't really know. Everyone knows the history of what happened, but maybe not for New Zealand. It was kind of getting towards the end of my PhD and I was like, if we were coming up on the beginning of the new year, I guess it would have been 2022. Then we didn't really know what was happening with the lab. I didn't know if I was gonna be able to finish the study or not though, maybe because I needed to have a few people in the lab at the same time. And long story short, I was like, I think we gotta just pull the plug on this. So what, what can I do? So I thought, well, okay, I know this. It surprised me. There's, there's some, there's a couple people that have been in my studies going, oh, I track my food all the time. And I try, you know, people have the training peaks and like, you know, those people like that, that just enjoy tracking, it's like, God, if there's, if there's one guy like this, there must be more. So I thought, well, maybe we could just design a remote study where, you know, people just track everything and we can kind of get. Get that information. And so that led to what, you know, what you reached out about to this. This new paper is, is the third of three papers that were all really from the same study. And really we had people that were training at least it was eight hours a week minimum, regularly tracking their hrv, their training and their nutrition. And then we had them track everything for 12 weeks. And, you know, it's, it's crazy. So we ended up with about 4,000 days of training and diet and, and, you know, it's, it sounds, it's. It's a big ask. You can't just take someone who doesn't track and ask him to track everything for 12 weeks. But when you actually take people who are already wired to track everything and already kind of, some people enjoy it. I mean, this one guy had tracked every day for like three years prior to the study, just for his own, you know, for his own benefit. And so it's hard to find those people, but because we could look around the world, you know, I was able to get about 50 people through that. And so there was a couple of big, you know, kind of endpoints. And so we had to split it up into a few different papers. The one that just came out was really like, largely like, what are people actually doing? Um, so we, we focus on the carbohydrate intake in relation to the training. Um, there was another paper where we kind of predicting daily recovery, like using HRE and a perceived recovery status. So kind of knowing, like, okay, if can, can we get a sense of, like, how someone's going. Um, it's important to know, like, is there HRV going to start tanking at the end of this week? Or, you know, is there. Can we take what we know with their diet and their training load and all these things and kind of get a sense of can we predict their daily recovery? And then what we mentioned, there's this thing called ergodicity which I came across, which is basically this general principle when group results don't translate to the individual. So there's something called Simpson's paradox. So an easy example to think of this is if you plotted a whole bunch of people on the X axis. Imagine typing words Per minute. And on the Y axis, typos. So you might see a very negative correlation. So that means as all the dots together are looking, if you look at them all together, what it's telling you is as people type faster, they're having fewer typos. But of course, that doesn't make any sense. And once you actually plot them by individual, you'll see that within each individual, the faster they type, the more typos they make. But the people that can type faster generally make less typos. This is a lot easier if someone's probably listening. It's hard to visualize. You gotta have to have your mind's eye working funny with this. But put simply, you can't always assume that what applies at the group level applies to the individual.

A

Yes.

B

So we took that concept and kind of looked at it in terms of carbohydrate and basically daily recovery. And the big takeaway was that is you might think that just more carbs equals better recovery. But that big picture, it was quite variable and that wasn't always the case. So I realized that there's a lot there and then we could dive into any one of those three kind of, I guess, avenues. So you tell me.

A

Yeah, well, yeah, I mean, I think that's the key one, is that even though there may be general guidelines, right. And I think us as an industry, you know, we produce position statements, for example, as scientists. And these position states, statements are, you know, this is like we're creating the Bible or whatever, right? Like this is the law, this is the way it works. And ultimately, I think your data around this organicity is showing, well, that law doesn't apply necessarily to every single individual and that maybe it applies to the mean, but you better be open to considering that it might not apply to you. And you better be a little bit like Luke Evans in your practice and your approach where you're willing to experiment. We all do need to start somewhere and maybe the guidelines are a good place to start. But don't be afraid also to kind of tinker, tinker back. So I'm already getting to the. To the practical element as I see it. But it's like, you know, that's. Yeah. Is that.

B

Yeah, I don't disagree. I don't disagree at all.

A

Because your data supports that, right?

B

Yeah, yeah, exactly. And so, yeah, maybe that. So that's a good segue into, like, how you're recovering. So the one aspect of that was we looked at can we predict the daily recovery? And the same thing kind of I think group level you can get a pretty good sense of how people are recovering. But what I found, there's hundreds of kind of variables that you consider like use a machine learning approach, taking this big data set. But one of the interesting things was at the individual level, if you just know about four or five things for each individual, then you can get a really good prediction of how your recovery is going to go. Like not just like tomorrow and the next day. The thing is those four or five things are different for each person. So which is, so it's yeah, good news and bad news. But like for example, like if we know muscle soreness and sleep index, which is like both sleep duration and quality and how stress level your training load, soreness from two days ago, like these things can help us at the group level again predict what people are gonna, how they're gonna go tomorrow. But again it's at the individual level that, that it's, you know, for you it might be soreness and sleep index and resting heart rate and then for someone else it might be like seven day protein intake and, and calorie intake yesterday and you know, a few other things that really are the, the few things to, to key in on. So while it's not easy to find those things, I think get it kind of supports probably what most people find is like or maybe not most people find. What most people could find is a few key things are the, you know, the find finding the few key things, you know, and those are the things to really make, make sure they're optimized for. And that's what's going to like as your sleep goes, so goes your recovery, for example. But maybe not for everyone. Maybe it's making sure you don't fall behind on your calorie intake. And that's the key thing. So it's kind of, you know, ultimately I, I believe between coach and practitioner athlete you can find the few things to the, the big rocks that are important to that person. But again that's the art of coaching and using the data to go, okay, what are those big rocks for this athlete and this athlete.

A

That's so well said, Jeff. I love it. Kind of reminds me, what you're describing reminds me of that. I'm sure you've come across it. It's like this classic continuous glucose monitor study where it was fairly early on in the evolution of CGMs, but they got the individuals to ingest a cookie and a banana and in one individual they had a big spike with the cookie, nothing with the banana. And the other individual, they had a big spike with the banana and nothing in the cookie. And it was just, it just kind of highlighted like, you know, if glucose with a surrogate of insulin potentially, you know, is, is completely variable, it's up to you to, to sort of figure out what, what works and doesn't work for, for you across the board because we're all so individual. That's amazing data.

B

Yeah, no, that's, that's bang on. I think that's, that's the key. The other thing that, you know, jumped out. So we think about this carbohydrate periodization and I think it's kind of hard to argue with eating more carbs or food in general when you're doing more and eating less when you're doing less. But I think what's a real open gap and it's kind of like taking that information to the next level. Like, because if you tell five athletes, oh like maybe everyone agrees that yeah, we should eat more when we're doing more and less and reading less. But like, what is more carbs for someone it might be like, you know, adding a potato and for someone saying add more carbs is like, you know, the whole plate of pasta. And so kind of one of the things was like, kind of seeing how, how people do that on their own, like meaning. So what we did was looked at training load relative to their daily carbohydrate intake. And that's one of the things again that at the group level, generally people are eating more, more carbs on days when they have more training. But at the individual level, that's another thing that just varied so wide. And some people matched it really well, probably unintentionally because we didn't tell them this is something we were looking for. And when I would actually ask, no one really kind of purposely was, was quantifying their training load versus their carb intake. But, but some people actually lined up really nicely and then some people is just completely random.

A

Yeah, for sure. We haven't even talked about the age of the athlete too and how that likely matters in terms of the carb periodization or just the carb preferences. Right. And my daughter is becoming a bit of a high performance swimmer and it's fascinating to watch her carb ingestion versus mine. Right. She's just so hungry for it. And I think something different is going on at that high growth and athletic sort of standpoint than compared to me where I've, you know, I think I probably, I blew out that that pathway A long, long time ago when I was you know, through my 20s and my 30s and far one, one too many bottles of coke and, and gels and, and I'm now I work a lot better on the lower carb kind of approach. Right. So it's. Yeah, but it's, yeah, it's just interesting right across the board we're so individual.

B

Yeah. I do think there's something. There's not a ton of data like so, so in terms of the fat burning and age, I did look at that in that, that substrate oxidation meta regression but there's some real gaps. Like there's a lot of data in people age like say 20 to 40 and then there's like the sporadic studies in like the 50 year olds and a few and older. But there's, there's not really like there's a huge gap in age. But I do think this is I guess more just, just theory of my personal theory of what I'm seeing like really crank be able to be a big fat burner like not just from going on low carb diet but, but you know, as an athlete that's years of athlete development. So I do think there's something about like, I mean obviously fiber types can change gradually over time and I think yeah, I mean there's teenagers but even like people in their 20s, I mean if you look at like some of the fast like young ironman guys and girls, like they're definitely going to be, probably need to be just throttling the carbs and I think it's, I do think it's just a machinery over time that not like one training season but like 10, 20 years of training that really can only, only at that point can you really, you know, kind of facilitate that kind of low carb fueling with that kind of competitive level.

A

Yep, yep, for sure. Yeah. Context always we as we say. Hey team, big news. We have just launched the new Athletica athlete app, what We've been calling App 2 and it's the closest thing yet to having a sports scientist in your pocket. So this isn't another static training plan, it's an AI coach that you can actually talk to. Ask it how recovered am I today or should I change this session? Why is the week set up as it is? And it answers based on your training files, your history and your load response over time. Under the hood. It's powered by the same HIIT science principles that we talk about on the show. Individualized interval training, critical power and pace, HRV guided load management and polarized training distribution. On top of that, you get a completely new sleek interface and a full training experience. Integrated community in App help and Athletica U Education built right into the platform so that you understand the why behind every session, not just the what. There's very little out there that can read and analyze your files, keep tabs on your recovery and and coach you using proven sports science. But that's exactly what we've built in Athletica's new app 2. Head on over to Athletic AI and check it out today with a free trial. Hey team. At Hitscience, we've learned that the best knowledge doesn't just come from books or labs. It grows through conversations with other coaches, practitioners and athletes in the field. And that's why we've created the Hitscience community, a global space to connect, share and turn sport and coaching science into practice. Inside you'll find free courses applied to skills and a worldwide network of professionals who push each other forward. So don't just keep up with the science, be part of shaping it. Join the Hitscience community today for free. Simply access through our website, our socials, or click the link in our show notes. Look forward to working with you on the inside. Jeff, I got some questions around fueling during and I'd love to get into, but is there any, before we go to that, is there any other key pieces of the PhD that you wanted to highlight that we haven't. That haven't yet?

B

No. I mean that was kind of a. I think we got through the big bits as kind of a whirlwind tour of the Ph.D. but I think that we found the bits that are relevant.

A

Perfect. Well, I mean I'm sure you've seen some of the debates and the thinking around the 180-200 gram per hour ingestions rates is certainly this seems to be a little bit of a practice that is out there yet there's a, you know, we've certainly had lots on the podcast, Phil Prince, Andrew Kutnik, Tim Noakes that you know, really presenting evidence that it's, you know, we can't see the oxidation rates that are supporting those. So. But you know, you're in the same space as I am where we have to acknowledge the practice that we. The practice that's going on and that we as scientists just haven't probably figured figured out what. What is actually going on. So what. What's your thinking there as an expert in this space?

B

Yeah, I mean to some degree I've just been kind of on the sidelines with Some popcorn, watching the zombies. But no, I, I think one thing we did just publish in a few months ago, a meta analysis looking at carb ingestion during exercise. And it's, you know, the, the long, you know, if you'd asked me six months, up until six months ago, if you ask pretty much anyone to say, does carb ingestion during exercise spare muscle glycogen, really the answer is no. Pretty much everyone will say no because every study showed some numerical difference, but no statistical difference. But those kind of things are right for a meta analysis because the effect was small. But it takes pooling 40 studies together to actually show that there is a significant effect. It's a small but significant effect that requires a sample size of 200 plus people to show, which most biopsy studies are like six to eight people. So there was actually a significant effect, but again it's small. So that's one aspect of it. So there's probably some degree of glycogen net glycogen sparing. Another big one is like I had a triathlete in the lab, I had him ride for three hours and he was taking in his typical race take intake was 150 grams an hour. So we had him doing that. He's only about 60s, low 60s kilograms. But he's riding his, his Ironman paces, you know, 280 to 300 watts. When you're, when someone is, can, can just be having a conversation at 280 watts, as you well know, like that is an engine that can, like the flux in that system is extremely high. And so you know, to me, him taking 150 grams an hour, no gut issues. And then we had them up for an hour on the treadmill after that running, you know, I think it was 16Ks an hour. I get with like, maybe it was 80 or 90 grams an hour, but again, all good from a gut standpoint and with that kind of energy production, like that is probably reasonable. It's really hard to get studies of those people. So, you know, someone that's riding 200 watts an hour or 250 watts at their threshold or something is totally different than someone just like who can cruise at 300 watts. And so I just like the flux in the system. I mean, I think there's just a lot of open questions. So I wouldn't doubt, I wouldn't condemn what some of these guys are doing in the 150 plus range. The other side, they make some interesting points about the minimum amount required for hypoglycemia. To prevent hypoglycemia.

A

Yeah. So it was Philprins that led it and it was basically they used low carb and high carb diets for six weeks repeated measures design and it was irrespective of the diet. It was basically time to exhaustion. I think it was at 70% of VO2 max was enhanced with only 10 grams per hour in either kind of condition supporting the small pool importance in terms of liver glycogen and blood glucose over muscle glycogen percent.

B

That's fine. But I think then the high group wasn't. Was taking. I mean I feel like there was a missing kind of. You'd want to see one more comparison of like someone crank, like cranking, you know, which to my point being like that's a great study but then it's not like a nail in the coffin from my perspective I guess is really the big one. It's like going oh, there's still definitely like comparisons that you'd want to see. So yeah, I think again figuring out context dependent, I mean kind of find how much where you're going to get some gut issues, find out how long you're, you're, you know, the sessions are or that the races are.

A

But why don't we, why don't we take that back? I mean this is where you're an expert. You're, you know, you, you're working with athletes and coaches every day. Like where do you take. You've got, and you've got all this knowledge. How do you set someone up to figure this sort of stuff out for themselves? Like where do you start advising? And like imagine a coach and an athlete on the podcast here listening, listening to your advice. Like where, where should they begin to start figuring out for themselves?

B

Yeah, I mean I guess to think of that, that one guy mentioned who we had in the lab. I mean, I guess a little bit spoiled to be able to put someone sometimes in the lab just to measure these things. But you know, it depends if someone. I guess. Yeah, let's walk through it. If we have. Let's just imagine you have a competitive ironman athlete. Are they bonking, you know, late in a race or is their energy good? Is there, Are they having gut issues of any kind? Okay, so then think of your decision tree that way if they're bonking, then probably not having enough. So say we raise more obviously triangulated with how much are they actually having and if it's kind of on the lower end of what you might expect, then there's maybe an easy answer. If someone is having gut issues, I might definitely look to low FODMAP the week before or something. So is there something in the system that way?

A

Can you describe what that is for the user?

B

Oh, sorry, yeah. So FODMAP is an acronym for these fermentable, basically fermentable types of fibers. And there's some pretty good evidence showing that basically they can help reduce GI issues. Of a range of GI issues, that's not the only culprit. But for someone that struggles with GI issues, working with a sports nutritionist and considering a targeted low FODMAP diet is what it's called, is definitely something to investigate.

A

Is that different fermentation issues that are causing the gut issues?

B

Yeah, basically the fiber, you know, fiber by definition is non digestible. It works as a prebiotic fiber, which means it feeds our gut bacteria. And for some people certain types of fibers feed certain types of gut bacteria and it can emit gas, it can cause bloating, all kinds of GI issues. So again, it's not the only cause of them, but it's a really handy solution in that people can get some really good benefit from it. Even just going to low fodmap a week out from a race or something like that?

A

Yeah, yeah, yeah. Just look to any Ironman event and you just, just see people holding their stomach at about mile 22 of the, of the marathon. And, and yeah, it's, it's, it can be, it can be pretty bad.

B

Yeah, so, so that's okay one angle to look at. But then if, if let's just assume that someone's not balking and they're not having GI issues is kind of, then where are they, where should they land on this spectrum? And there, there probably is a pretty big Runway in terms of what might work for, for a given person, like 90 is not necessarily between 80 and 90. It probably doesn't matter an hour, but, but if we can kind of get a sense of, well, how much they're burning. So if you have some lab data to know like kind of how much you can even estimate this without being in the lab and just knowing what the energy cost with some basic efficiency calculations is like to go whatever your wattage is, if it's 200, two 50 or 300, and then you can kind of like you want to get to the end of the race before you get to the end of the gas tank. And so I kind of think of it that way. If you kind of have a sense of how tilted towards fat and carboxation they are. Although I do think an important caveat is that could be misleading because if you glycogen depletes someone, they're going to be really big fat burners. So one of your Andreas studies showed even people that are not what we might consider fat adapted, they can have really high rates of fat oxidation when their glycogen depleted.

A

Yeah.

B

So important caveat. But then it's, it's then angling towards, okay, should it be at 120 or 130 or 150 an hour? You know, if someone can get in the lab or at that rate at their ironman pace with some intervals in there, see what they're burning. I like is there a lot of, are they not burning a lot or. Yeah, if it feels like it's, they're taking in their stomach if they, if they're not using it, if they're still burning a high amount of fat with, with at 150 grams an hour, you should be burning a high amount of carbs. So if, if the, if the carb, if the RER starts going down, then it probably is just sitting there in your stomach and not being used. Now I realize as I'm saying this there's, there's nuance and so doesn't mean what you're seeing in an RER is exogenous or endogenous. We don't know. There's other tests for that. But I guess as a, the most available type of testing that most people might be able to do, I think it's a reasonable kind of place to start looking nice. Does that make sense? I feel like I'm jumping around now and there's lots of caveats.

A

No, I think it's great. My next question kind of is related, but I'm curious, as a dietitian, nutritionist, what is your thinking around background diet and its importance for I guess everything else that we measure? And I'll just give you an example. I was coaching an open water swimmer. It was, it was fun, fun little project that I took on and we did like a diet analysis and I was appalled that this young man was basically eating takeout, you know, every, he was kind of the, the variety was, you know, going back and forth between Maccas and KFC and pizza takeaway, you know, every day. Like it was just, I couldn't believe it was even possible. But this is, and this is one of the top, you know, open water swimmers in the world. So it's just amazing. Like in that 20 something what, what you can actually do. Right. But it's. Yeah, I don't know. And I kind of wonder like, you know, because he does, he was reporting various different, you know, issues later on that, you know, does that potentially kind of kick back to some of the problems that we're seeing elsewhere?

B

Yeah, yeah, I would think so. I mean, it's a funny one because I sometimes, sometimes end up thinking a diet doesn't matter as much as some people think it does. But I think that's almost as naive. It's like assuming you're eating actual food. So there's some table stakes of meaning just cooking at home most of the time. So if someone is eating fast food all the time, there's definitely a lot of, I think they have a lot to gain from stepping that up. But then, so once you get to this reasonable level of just going to the grocery store and I would say what most people might think of as normal, but there's probably no normal. But again, making most of your food at home eating actual food, then people will take this extra step of micromanaging. Should it be chicken or turkey, what kind of fish is best? I don't think that really matters. You want variety and things like that. So probably in that case though, there's going to be some inflammation things and it might be fine for a while. And it's also another one of those just because can you. Should you eat just like complete garbage? So I think when you started asking this question, I thought you were going to say like kind of general, you know, high fat or low, you know, low fat or something like that. But just in terms of diet quality. Yeah, I think everyone would be do well just to like eat out less, you know, not that often. And that would probably take care of most of it. Mixing up the veggies and fruits and eating seasonally also I think is pretty important.

A

Yeah, no, I couldn't agree more. I mean, obviously I've, you know, personally I love my, my own little low carb version of, of what I like to like to eat. Personally, I feel better that way. But I think it, you know, when I'm advising people, it's just a whole food diet at the end of the day for you. You almost can't go wrong with that. But, and where you've, where, where we have problems is like you're sort of saying the ultra high processed and you know, these are going to be inflammatory diets and that's, that's. But you know, if you can stick close to, like you said, Whole food and seasonal. You're, you know, you're, you're most of the way there probably on everything that you want to do. So that's very cool. We're aligned. Jeff, we're getting close to the end of the hour. Is there anything that we've missed here in this, this profile and have we answered the question? The key question that you set out to ask is what should I eat?

B

What should I eat before exercise? Yeah, I mean, I guess maybe we could just kind of. I'll summarize my feelings on what should I eat before exercise. I would say, you know, we can split about, split the workout, the upcoming workout into duration, intensity. So if I, I guess 90 minutes is a good cutoff and it's kind of tends to be weekdays or weekend rides for, for, you know, many people. So if it's less than 90 minutes, I don't think it really matters what you eat. So go with what works for you. If it's longer than 90 minutes and it's gonna be high intensity, I definitely think getting a decent whack of carbs, you know, it's a protein, like a, like a mixed meal, like something reasonable. If it's longer than 90 minutes and it's low intensity, I think, you know, generally still something. And even if it's kind of like an eggs and avocado, like a, you know, something is probably good. Obviously again you can do it fasted, but you know, comes with, with caveats and then also not being afraid of taking something, enduring those again, longer than 90 minute rides, even if it's, you know, low intensity. And that could just be even a light, light sports strength, like something like a scratch, you know, 25, 30 grams an hour probably is, is sensible. And it's not gonna like, I think people can rest easy that it's not gonna like offset anything or attenuate anything. And that's like people get so freaked out if it's shorter than 90 minutes. Again, probably don't eat anything if you want. If it was high intensity and you were feeling like, I don't know, either hungry or you under fueled and you may be popping a gel if you wanted in the middle, but, but again, I don't think it's necessary. But I also don't think it's harmful if it's short and it's low intensity, you know, if you wanted to do it fasted that, you know, like first thing in the morning, I roll out of bed and jump on the trainer most pretty much every day. And that's Fine with nothing in water. If you wanted to have nothing beforehand and have just a light sports drink during, I think that would be okay. So it's kind of just, you know, there's, there's a, there's a reasonable range of what I, what I would consider are best practiced. Um, but yeah, I, I, I think, I think that's a good way to think of it.

A

Yeah. That's awesome. And, and it is, you know, we, we definitely can conclude that it is individual and it's up to you, the listener, the athlete, the coach, to, to work towards experimenting as you're probably doing already. But just don't forget to continue to experiment and, and figure out what works best for you because that's, yeah, that's probably going to be, probably going to be best.

B

Well said, Jeff.

A

Where can people find out more information about you or get in touch?

B

Yeah, good question. I guess LinkedIn or Twitter or. I have a website for the kind of the, some of the consulting I do eatsleep fit, so you can reach me through there or my email is. Jeff Sleep.

A

I've seen that you have some very cool little apps on there as well that you've invented through your artwork and your tech work, which is very impressive. Various different predictor tables and whatnot. I've played with them and they're outstanding. So yeah, we'll include those links, Jeff, and make sure people go to those. We'll include links to your incredible papers. Congratulations for all the work that you've done, Dr. Rothschild. And yeah, look forward to more work that you're doing in the future. Great topic, important one. And yeah, on behalf of Martin, myself and the team, thank you so much for the work that you do and look forward to around two in the future.

B

My pleasure. Thanks, Paul.