Pushing Limits: Inside a Landmark Study on Female Ultra Endurance Athletes

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Hello, everybody.
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On our next episode, we brought on two incredible researchers to talk about Project Further, a study looking at women ultra runners during a six-day ultra event.
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Dr.
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Trent Stellingwerff and Susan Boegman together bring an incredible wealth of information and research on ultra endurance athletes.
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Susan Boegman is a high-performance certified senior practitioner with OWN, the podium sports scientist Canada, and is the nutrition lead for the Canadian Sport Institute Pacific in beautiful British Columbia.
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an organization that delivers health and performance solutions to Canadian Olympic and Paralympic athletes.
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She has provided integrated nutrition support as part of the CSI Pacific Sports Science and Medicine teams for many national sport organizations, including swimming, rugby, triathlon, rowing, and soccer over the past five Olympics.
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Although her work is primarily applied, she contributes to athlete-centered research as part of the national teams and in support of the CSI Pacific Innovation and Research team.
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Prior to focusing on sport, Susan worked as a nutrition counselor within a highly specialized eating disorders program.
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Susan is a registered dietician with the College of Dietitians of British Columbia and has a bachelor of science from the University of Alberta.
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Is a level two certified anthropometrist with the International Society for the Advancement of Anthropometry and is a contributing lecturer for the prestigious International Olympic Committee's Sports Nutrition Diploma.
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Dr.
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Trent Stellingwerff brings decades of leadership across various aspects of high performance sport, science and research, particularly in exercise, physio and sports nutrition to his current role as director of R &D at the Women's Health Sports and Performance Institute.
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Dr.
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Stellingwerff still retains a smaller position as a senior advisor of R &D at the Canadian Sport Institute.
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Pacific, where he has worked since 2011.
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Over the years, he has overseen multidisciplinary health and performance teams, led major R and D initiatives and supported national Olympic Paralympic team athletes in track and field, rowing, triathlon, and mountain biking.
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He's contributed to more than 160 peer reviewed publications, co-authored international consensus statements, including guidelines with international Olympic committee, world athletics, world aquatics, and Union Cycliste Internationale.
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He is a member of the International Advisory Board for the International Olympic Committee's diploma program in sports nutrition and SNC programs and currently co-chairs Canada's national working group on relative energy deficiency in sport.
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His recent work centers on advancing the science of female athlete health and performance.
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Dr.
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Stellingwerff's academic background spans leading institutions in human performance and nutrition.
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He completed his Bachelor of Science in Nutrition and Exercise Physio at Cornell University and earned his PhD in Human Exercise and Skeletal Muscle Physio from the University of Guelph, followed by a postdoctoral fellowship in Exercise and Muscle Physio at the University of Maastricht as the WHSP Director of Research.
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Dr.
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Selenworth guides the Institute's strategy, research agenda, and cross-disciplinary collaborations, helping to build the evidence base that elevates care for female athletes everywhere.
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This was a super fun episode.
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Enjoy the listen.
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Hello everybody and welcome back.
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We have for you guys, Susan Boegman and Trent Stellingwerff.
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Thank you so much for joining us.
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It's a mouthful, spelling that in kindergarten is hard.
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So yeah, we're happy to be here.
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I'm excited to have you guys.
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We are going to talk all things about the Further study, but before we dive into that, I'm going to have Susan, I'm going have you start with your two truths and a lie.
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Okay.
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Awesome.
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Okay.
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So because I am a nutritionist, a diet sport dietitian, I decided to go with food.
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So the world consumes an estimated 50 billion burgers a year.
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Yeah.
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All of the further athletes ate burgers during the event.
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Okay.
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And the classic burger, the beef patty, lettuce, pickles, and cheese is known as the California Burger.
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We were in California after all, so let's go.
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Okay.
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I love it.
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And then, okay, maybe I want, are these stumping you Trent?
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I'm just curious.
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Okay.
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Yeah.
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You are good.
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the classic burger is known as the California burger.
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Is this by a specific restaurant chain or is this like a known?
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just, I mean, it potentially is a known fact.
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Okay, okay, I see, I see.
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Don't wanna reveal anything.
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I mean, I have seen endurance athletes eat burgers and pizzas and I mean, sandwiches while they're out there doing stuff.
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So I definitely think that could be feasible for sure.
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The world consumed 50 billion burgers a year.
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I also unfortunately could see that being true.
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Yeah, I mean, maybe it's even, maybe it's more than that.
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Maybe there's a number fudging there.
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Okay, so I think maybe that's what I'll do.
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I'm going to go with the world consume 50 billion burgers a year as the lie because maybe there's like a different number situation there.
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And then Trent, I'm going to have you break down your two truths and lie.
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Yeah, mine's a lot more personal, so you're get a laugh out of this.
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during the peak of the Seattle grunge rock era 30 years ago, when I was in university, I had dreadlocks, six tattoos, and a nipple piercing.
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Are these all the truths and lies?
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All right.
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This you cannot probably find on Google, huh?
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Yes.
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Okay.
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Well, this is a tough one.
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Is this stumping you, Susan?
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I know one of them, but I'm not sure about the other two.
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Yeah.
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I this is this is a good one, Trent.
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I'm gonna again, I'm kind of like a number thing.
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I'm gonna go with the six tattoos.
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I think is a lie.
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I think maybe you did have a nipple piercing.
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Maybe you had dreadlocks.
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But maybe it's like five tattoos or something like that.
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I'm gonna think those are the lies.
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The number number ones.
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But for our listeners, we will find out if Trent had a nipple piercing at the end of the episodes.
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You're gonna have to hang on there and em how many burgers the world eats in a year.
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We'll find out.
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All right, so to kick things off today, I'd love for you guys to share and maybe we can start with Susan, your current roles and how you guys split your time between your applied work with athletes and then the research lens here.
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So I currently work as the lead for sport nutrition at Canadian Sport Institute Pacific.
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But most of my work is field work with the athletes.
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So it's applied rather than research.
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So a big job of supporting health and performance.
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And I would say that most of the work involves like assessing the athletes needs and any gaps that they might have and then helping them also make sense of all of the research that Trent is doing or maybe other people, for example.
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and just helping them understand what's actually key for them or important for them and their sport.
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And then also just a lot of GI work, helping them understand physiological data that Trent, for example, does and how that impacts their metabolic fuel use.
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And then translation of that into simple fueling strategies.
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I work with lot of endurance athletes and they have a struggle often to get enough.
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calories every day.
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And then sometimes I get the joy of jumping on a research project with Trent and I would say maybe that's about 10 % of what I do.
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for example, CSI Pacific and Trent did a REDS project, which we were part of.
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And then we recently did some altitude assessment of altitude impact on energy availability in REDS up at altitude with rowing.
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And so I was involved in that project.
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So that's.
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that's the really cool stuff as well.
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yeah, but that's about 10%.
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Yeah.
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very neat, very neat.
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And then Trent, what about you?
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Yeah, so I'm currently the Chief Performance Officer at the Canadian Sport Institute Pacific where, Susan and I have been colleagues for many years and we're just down the hall from each other.
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And we're one of the Olympic and Paralympic training centers here in Canada based in Victoria.
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And so the majority of my previous background is physiology and nutrition and working mainly in endurance sport as well.
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But then over the last three or four years, I've transitioned much more into the area of research and help lead, co-lead our research and development team at the Canadian Sport Institute.
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So adjunct to a couple of universities, we have grad students doing different projects in different places, and then also work with some industry partners to do research as well.
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Neat, okay.
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And Trent, what got you interested in the ultra endurance space?
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Yeah, I think overall this is over the last 15 years, maybe the third research project that I've been involved with in the ultra endurance space.
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ah first of all, when this came up and we'll hear a little bit more about the story, to be involved in doing a research project around a six day ultra was just so incredible and unique.
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But first of all, there's barely any six day ultras.
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Like if you look at the race calendar as a percentage, there's only a handful around the world.
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Most of the research data is based on 50, kilometer, 100 kilometer and 100 mile races, not multi-day races.
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So there's a lot of unique factors that were really interesting here.
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You know, we're to cover it a bit more later in the podcast as well, I believe, but the ability to design and support these athletes and design a research project that was going to be field-based was especially interesting and exciting.
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And then finally, You know, when we think about ultra endurance compared to other sports, there's so many other intangibles that we need to think about and measure and appreciate that influence health and performance.
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One being nutrition.
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it's nutrition is so important in ultra performance and given Susan and I's background that that's a really easy and positive fit, but also every ultra course has different terrain, different weather conditions.
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You've got to think about altitude.
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You've got to think about sleep deprivation and, nutrition and hydration challenges, overuse injuries that may happen during the event itself, strategies on pacing, circadian rhythms.
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And so when you think holistically around all the different disciplines and factors of health and performance, like every single, almost every single one of them came into this project.
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it was a big, stressful, audacious project.
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but we had an amazing group of researchers and staff to be able to.
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It is really, yeah, lot.
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Yeah, this is so fascinating.
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I think the endurance space within the ultra endurance space is getting bigger.
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And then the research on that area.
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Yeah, we just we don't know.
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We need more, which is that's why I'm super excited to have you guys here.
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So there was a study that got produced, The ad libidum diet, energy availability, body competent performance in females during a six day ultra marathon.
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And that Can you tell us about that?
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That was the further study?
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That's the information you guys collected from the further study?
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Yeah, so what you've read there is actually just a published abstract.
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So at the American College of Sports Medicine earlier this year was the first conference in May that about a year later that we've pulled together and analyzed all the data.
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And then Dr.
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Alex Coates presented that abstract at the American College of Sports Medicine.
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yeah, it was titled at Libidum diet, energy availability, body comp and performance in females over six days.
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That is but one of the questions.
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And so oh I think it's important to highlight that we had at the event 28 different research scientists and students involved to pull off six days of continuous research.
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And actually in the end, it was about 10 days of continuous research because we pre-testing and post-testing.
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And I'll just highlight that we had six different research groups involved.
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um And I do want to say a few names here.
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Alex Coates and Jamie Burr led the physiology group.
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We had Chris Napier lead the Biomech group.
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had neuromuscular and cognitive fatigue led by Dr.
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Nicky Bruce and Chris McNeil.
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The energy group by Dr.
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Sarah Purcell and Susan, and then the psych social group led by Dr.
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Erica Bennett at University of British Columbia.
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so, you know, the overall was what are the multi-dimensional, multi-factorial determinants of health and performance over six days?
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Mm-hmm.
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And again, this is pretty rare to have everything from a biomechanist, you know, numbers and math, and then Erica Bennett on psych social research, all in the same room, participating on the, the same research project.
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So there were tons of sub questions.
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I'll just highlight a couple, you know, from Erica Bennett's, Dr.
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Bennett's perspective, one of the exploring women's ultra runners, psych social experience of pain, body image, coping, and self-regulation was, was her main research agenda.
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um But then from the biomechanics perspective, that's Dr.
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Chris Napier and his crew was doing full body kinematics and kinetics evolve and change over fatigue.
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So do you're running biomechanics?
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um What do they look like between athletes, but also with within an athlete over six days?
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So again, it was a big project, um lots of um discussions.
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um And yeah, Susan was really intimately involved in the energy team and energy intake team, um helping support athletes directly in their feeling questions and their crews, but also trying to measure every single gram that they all ate throughout the whole event too.
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Gosh, that sounds like a task to measure all that.
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What was the nutrition question going into this, Susan?
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Oh, well, we were looking at um energy availability and we were looking at energy balance, energy intakes and energy deficits.
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We were trying to basically characterize um carbohydrate intake, protein intake, fat, so all of the macros, whether or not the athletes were able to support the fueling over the course of the six days, what kind of an energy deficit there was.
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So there was a lot of questions that came out of that and still some interesting things to be published for sure.
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Yeah.
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gosh, fascinating.
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OK.
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Well, we will learn shortly in the episode how all this data was collected.
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But Trent, for you, what was the reasoning behind choosing a multi-day event versus a single day event?
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And you kind of touched on it a little bit, or even a lab-controlled setting to look at some of this information.
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Yeah, I think most athletes and coaches and most applied sport researchers and sport scientists are most interested in high ecological validity and high ecological validity really is how transferable are the results to your environment and your reality.
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And so these training camp study approaches are the best, the very best we can do to measure using best practices, methods and protocols.
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what is going on, um but they're placed in the field or the field of play for athletes.
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so getting them out of the lab as much as possible and in the field of play and measuring what was happening out on this um two and a half mile loop for six days was really, really important to us.
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That said, I will highlight there was some lab based work.
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Like we have assessments done on the athletes already a year, a year and a half in advanced.
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you laboratory conditions up in Canada at our lab when the athletes came up to visit several times.
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So there was some lab-based pieces.
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In the three days leading in, we transported part of an entire lab down from our institute to the hotel, next pretty close to the course.
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And so we did all the baseline testing in a hotel conference room.
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So that was lab-controlled type testing, blood work.
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Exascans using all the best practices.
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But again, that was set up all remotely in a hotel next to the course.
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Wow.
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Gosh.
00:16:48.469 --> 00:16:52.913
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Stop guessing and get the data.
00:17:45.112 --> 00:17:53.327
And can you tell us a little bit about the study genders that were participating, age ranges, things like that?
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you bet.
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So there's very little in the literature at all on multi-day ultras, let alone multi-day ultras with just a female cohort.
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So this is, I believe, the only multi-day ultra that's not a case study in female athletes.
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So that was super unique to be able to address through multifactorial ways what was going on.
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so Leading into this though, obviously we had an industry partner involved and it's really important to highlight Lululemon's sponsored this and this project doesn't happen without an industry partner and their backing behind all the research that went into it.
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They put a lot of their own people and their own passion and their own resource into this project and these athletes were all sponsored by Lululemon to be part of the project as well.
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Beyond that, there is emerging evidence in the literature and some evidence been there for 20 or 30 years that females compared to males might have certain physiological or psychological advantages for ultra endurance.
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And therefore, the typical world record gap between males and females is in running events is about 10%.
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And perhaps there's a way that over these ultra endurance events that, know, females can bridge the gap and close the gap down to five or 7%.
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And there's certainly examples in small, smaller fields of women winning ultra races outright, over males as well.
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And, and so, you know, a big part of that without getting too deep into all the physiology and everything else is on average women have 15 to 20 % greater prevalence and are cross-sectional area of, slow twitch muscle fibers.
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so to which muscle fibers fatigue glass, they're more resilient.
00:19:38.445 --> 00:19:41.478
They result in less muscle damage and quicker recovery.
00:19:41.478 --> 00:19:45.780
They also result in less carbohydrate use, so more fat metabolism.
00:19:45.780 --> 00:19:54.526
And when you're looking at the determinants of ultra performance, just from a fiber type perspective, all of those things are really important and positive to have.
00:19:54.886 --> 00:20:01.151
But conversely with, you know, another example is there's also amazing data on that women can pace better than men.
00:20:01.232 --> 00:20:06.906
they probably have less ego involved, a little more pragmatic and realistic around their pacing, you know?
00:20:06.906 --> 00:20:07.636
So.
00:20:08.001 --> 00:20:17.729
There's several reviews that have highlighted this and so that also was part of the interest in focusing on females.
00:20:18.329 --> 00:20:27.492
And certainly to bridge the gap and there's barely any research on female health and performance and that was a big piece of it as well.
00:20:27.492 --> 00:20:29.355
Yeah, I absolutely love that.
00:20:29.355 --> 00:20:33.500
em So and there was how many participants in the study?
00:20:34.304 --> 00:20:38.296
we had 10 women and they not only did they all start, but they all completed.
00:20:38.296 --> 00:20:40.597
And so I feel like we're all pretty proud of that.
00:20:40.597 --> 00:20:48.833
And, you know, I think just to speak to the fact that they were from all over the world, like we had from the US, from Korea, China, Japan.
00:20:48.833 --> 00:20:52.586
So that was pretty exciting, although it did sometimes pose some challenges too.
00:20:52.586 --> 00:20:57.107
And we definitely had some needed an interpreter, for example.
00:20:57.107 --> 00:21:01.448
And there was a wide variety of ages, like age 27 to 48.
00:21:01.448 --> 00:21:03.988
So we had a big age span.
00:21:04.147 --> 00:21:11.528
And then we also had quite a variety of training and performance levels as well.
00:21:11.528 --> 00:21:17.980
Yeah, I'd love to know that because didn't the participants, did they set their own goal for the six days?
00:21:17.980 --> 00:21:19.834
Can you tell us about that as well?
00:21:20.012 --> 00:21:23.986
Well, so probably the best person to tell us about that would be Dr.
00:21:23.986 --> 00:21:27.608
Charlene Orr, who is our lead for mental performance at the time.
00:21:27.608 --> 00:21:32.992
And she sat down with the athletes and did chat with them about what their goals might be.
00:21:32.992 --> 00:21:36.965
So they were all individual based on where they were coming from.
00:21:36.965 --> 00:21:41.089
So, for example, we had four athletes that were professionals.
00:21:41.089 --> 00:21:49.829
Three of them were elite ultra marathoners and we had one athlete who was what we would call a tier five athlete and she was a world record holder.
00:21:49.829 --> 00:22:00.153
And then we had six athletes that we would call trained or developmental and one of them in fact had only started running for the project.
00:22:00.153 --> 00:22:07.297
She literally decided to sign on not having run a step and then she trained for an entire year beforehand.
00:22:07.297 --> 00:22:13.170
So that is so her I think every athlete had pretty audacious goals.
00:22:13.170 --> 00:22:22.184
We had one athlete who wanted to break the men's record and we had another athlete who wanted to run 50 kilometers a day every day for for six days for example.
00:22:22.184 --> 00:22:34.982
So yeah and I guess the one note I did mention tier so we had like four athletes that were tier four athletes and a tier five athlete and then we had tier two athletes.
00:22:34.982 --> 00:22:47.290
What's important about that I think is just thinking about the the athlete classification allows us when we're doing research or when we're interpreting research to understand the research better.
00:22:47.290 --> 00:22:59.469
So, you know, if you're looking at research and it's on tier one athletes or developmental athletes that might not apply to a tier four or five athlete and Trent was integral on doing that classification.
00:22:59.598 --> 00:23:12.833
And so I don't know if that's a good link to the show notes, but I think it's really important for us when we're talking about athletes to understand the caliber of athletes that we're paying attention to and evaluating.
00:23:12.833 --> 00:23:14.775
So yeah, so we had a wide range.
00:23:14.775 --> 00:23:17.479
We had a wide range of athletes participate.
00:23:17.479 --> 00:23:19.161
I love that end age range.
00:23:19.161 --> 00:23:23.365
the tiered, how, for our listeners, how would you describe that?
00:23:23.365 --> 00:23:28.794
What is a tier one athlete versus, I think you said a tier five, Susan, like, what does that mean?
00:23:28.794 --> 00:23:35.140
would be a world class athlete and a tier one athlete would be a very new developmental athlete.
00:23:35.800 --> 00:23:38.383
And then and then running in between.
00:23:40.007 --> 00:23:41.397
Gotcha, okay, that's helpful.
00:23:41.397 --> 00:23:45.269
So, and it's not necessarily based off of like a VO2 max or anything like that.
00:23:45.269 --> 00:23:46.470
No, okay.
00:23:47.111 --> 00:23:47.770
Awesome.
00:23:47.770 --> 00:23:49.971
So you guys monitored a bunch of things.
00:23:49.971 --> 00:23:53.954
Susan, you mentioned measuring all the food, energy availability.
00:23:53.954 --> 00:23:58.916
Trent, was there also like core temperature sensors or sweat testing?
00:23:58.916 --> 00:24:02.878
What other things are you guys measuring throughout this study?
00:24:05.028 --> 00:24:10.410
We threw the kitchen sink at them as much as what was feasible and possible.
00:24:11.070 --> 00:24:18.454
Well, at the same time, our number one ethos is they are there to compete and we can't be a distraction.
00:24:18.454 --> 00:24:37.896
so, yeah, like going, you know, down the list of things, it was extensive and it has become more extensive the last 10 years or so, primarily due to the fact that there's been an explosion of wearables that people can use and implement into racing.
00:24:37.896 --> 00:24:47.255
So, you know, very quickly in the two to three days leading into the event, when everyone is there at rest, did a submeximal VO2 max test.
00:24:47.255 --> 00:24:56.142
We did body composition by DEXA, blood collection, hemoglobin mask, baseline fresh, neuromuscular and cognitive fatigue testing.
00:24:56.142 --> 00:24:58.867
We used a tracer double label water.
00:24:58.867 --> 00:25:02.469
which is the gold standard to get total daily energy expenditure.
00:25:03.288 --> 00:25:18.493
There was interviews for the psych social program and then Susan and their team were sorting out all the energy intake pieces as best as possible so that once the six day event started, they were up to speed.
00:25:18.594 --> 00:25:24.236
In the race daily, there were options for blood collections, double label water, dietary intake.
00:25:24.236 --> 00:25:26.135
had GPS and heart rate.
00:25:26.136 --> 00:25:28.116
We had continuous glucose monitoring.
00:25:28.116 --> 00:25:32.058
going on core temperature monitoring with a, a squalible pill.
00:25:32.058 --> 00:25:33.861
We use it or a smart ring.
00:25:33.861 --> 00:25:35.602
We had inertial measurement units.
00:25:35.602 --> 00:25:40.186
So IMUs are little sensors on the shoe and in a pocket in the shorts.
00:25:40.186 --> 00:25:45.161
So it basically measures in a triaxial direction, the bounce.
00:25:45.161 --> 00:25:51.276
And so from that bounce, you can then assess foot strikes, foot length, number of steps taken.
00:25:52.196 --> 00:25:55.598
We had an entire biomechan tent set up.
00:25:55.598 --> 00:25:57.961
with force plates and motion capture.
00:25:57.961 --> 00:26:03.644
So they just ran through the tent that produced almost a terabyte of data.
00:26:03.963 --> 00:26:06.715
And then psych social observations throughout.
00:26:06.715 --> 00:26:12.318
So, and then there was post testing, which is pretty similar to the pre-testing I highlighted.
00:26:12.318 --> 00:26:16.090
So it was a big range of what we did.
00:26:16.090 --> 00:26:18.635
Yeah, that's a that's a ton of info.
00:26:18.635 --> 00:26:23.660
I think it's also important to say that we did that on the side of performance.
00:26:23.660 --> 00:26:29.144
Like we were actually off to the side and as unobtrusive as we possibly could be.
00:26:29.144 --> 00:26:32.087
So that the athletes really were there to run.
00:26:32.087 --> 00:26:33.067
They were there to run.
00:26:33.067 --> 00:26:34.288
So, yeah.
00:26:34.463 --> 00:26:45.167
And I might add to that, Susan, that's a really good point is at the female athlete conference earlier this year, there was a panel on this and the three athletes that showed up and came to that panel.
00:26:45.347 --> 00:26:51.931
All of them echoed that, that they felt the science program was an add on and it wasn't necessarily a distraction.
00:26:51.931 --> 00:26:59.973
And I think a huge piece to that is every athlete brought five to seven people that were part of their crew for six days straight.
00:26:59.973 --> 00:27:02.884
And we really access the athletes.
00:27:03.247 --> 00:27:06.887
and delivered almost all of this through the crews.
00:27:06.887 --> 00:27:10.868
like our crews were the, you know, we go there first, where are they at?
00:27:10.909 --> 00:27:13.150
Okay, what's the battery on the aura ring?
00:27:13.150 --> 00:27:14.500
Can we switch it out next lap?
00:27:14.500 --> 00:27:15.819
Are they going to come in for a break?
00:27:15.819 --> 00:27:18.230
Do we need to add another core temp pill?
00:27:18.230 --> 00:27:20.501
Where's the battery on the continuous glucose down?
00:27:20.501 --> 00:27:30.979
You know, so, you know, there's check-ins throughout, but that also required then 28 staff on shifts that we had three different base shifts that went.
00:27:30.979 --> 00:27:33.359
24, 24 six.
00:27:33.359 --> 00:27:35.720
So everyone had overnight shifts.
00:27:35.759 --> 00:27:51.415
Everyone had some time off to try to rotate through skills, but it's also was logistically challenging because, you know, Susan's amazing and energy intake, but we can't put her on the biomech tent and we can't take someone from the biomech tent and put them into energy intake.
00:27:51.415 --> 00:27:57.276
know, like everyone also had their own background and skills to, to be able to do what they needed to do.
00:27:57.276 --> 00:27:58.076
Wow.
00:27:58.076 --> 00:28:00.276
This is, this sounds so fascinating.
00:28:00.276 --> 00:28:01.615
Also fun.
00:28:01.615 --> 00:28:02.435
Was it fun?
00:28:02.435 --> 00:28:03.836
It sounds fun.
00:28:05.996 --> 00:28:07.457
Very cool.
00:28:07.457 --> 00:28:07.656
okay.
00:28:07.656 --> 00:28:12.517
So I'm curious, how did, how was the event, the six day event structure?
00:28:12.517 --> 00:28:18.176
these athletes like sleeping and like at the night or were some going through the night?
00:28:18.176 --> 00:28:19.374
What did that look like?
00:28:19.374 --> 00:28:20.175
Yeah.
00:28:20.175 --> 00:28:28.000
Well, I think the main thing to say here is that there was one rule, which was walk or run as far as you can over the six days.
00:28:28.000 --> 00:28:32.884
so athletes could choose to sleep and eat whenever they wanted.
00:28:33.025 --> 00:28:41.345
So the course was a loop, which allowed for the athletes to have a pit area, like a Formula One.
00:28:41.345 --> 00:28:48.482
kind of style pit area or crew where their crews supported them and they were able to go in and rest and recover as they needed to.
00:28:48.482 --> 00:28:52.747
And then also there was also another athlete aid station at the two kilometer mark.
00:28:52.747 --> 00:28:55.210
So there was a lot of opportunity for athlete support.
00:28:55.210 --> 00:29:01.816
And then they chose to run or walk or sleep or eat as they needed to.
00:29:01.816 --> 00:29:02.519
Yep.
00:29:02.582 --> 00:29:03.705
Okay, awesome.
00:29:03.705 --> 00:29:07.876
And I think it's a two, you said it was a two and a half mile loop.
00:29:07.954 --> 00:29:11.282
Yeah, or 4.1 kilometer loop if you're a Canadian.
00:29:11.520 --> 00:29:14.500
it was like 2.476, whatever.
00:29:14.500 --> 00:29:33.101
I will highlight that two different course certifiers were there to make every record eligible en route because you have 12 hour, 24, 48 multi-day records, but then you also have distance records.
00:29:33.621 --> 00:29:38.121
And you have people coming on and off the course.
00:29:38.326 --> 00:29:39.337
right.
00:29:39.337 --> 00:29:44.981
from a timing map perspective and then figuring out all those records.
00:29:45.303 --> 00:29:51.508
Even the logistics around that is quite extensive and tricky, but it was all validated, all confirmed.
00:29:51.587 --> 00:29:55.440
like, you know, there's a representative from USA Track and Field, Anti- Doping was there.
00:29:55.440 --> 00:30:01.195
did anti-doping tests pre and post as well.
00:30:01.195 --> 00:30:03.586
So it was a legit event.
00:30:03.586 --> 00:30:05.028
Incredible.
00:30:05.028 --> 00:30:08.875
And tell us a little bit about the terrain, the location, the temperature.
00:30:08.875 --> 00:30:10.478
Was this at altitude?
00:30:10.478 --> 00:30:11.259
Tell us about that.
00:30:11.259 --> 00:30:13.201
What was that like over the six days?
00:30:13.542 --> 00:30:20.767
Yeah, the event took place at Lake Cahuilla, which was in California, and it was a loop around a lake.
00:30:20.988 --> 00:30:32.855
So I think it was about 80 % gravel and about maybe 20 % paved and a little bit sloping, little not, it was mostly flat, but not completely flat.
00:30:33.435 --> 00:30:37.798
So that I would say that's the main thing about the terrain, the athletes.
00:30:38.021 --> 00:30:39.011
mostly liked it.
00:30:39.011 --> 00:31:01.298
There was a little one section I think where they didn't love it because it was a little bit soft but I think otherwise it was pretty good and Trent will probably tell you that they searched long and hard to try to find em something that fit for all 10 athletes, a course that was em high quality enough that some records could be broken.
00:31:01.433 --> 00:31:06.296
But that was also interesting and didn't cause too much neuromuscular fatigue, etc.
00:31:06.296 --> 00:31:16.619
And there's a lot of things that went into this and that was not my area, but I'm sure Trent could talk quite specifically about how long they looked for a proper location.
00:31:16.619 --> 00:31:20.571
em So Trent, did you want to say anything more about that or?
00:31:21.363 --> 00:31:24.987
You know, you're looking at a location that checks a few boxes.
00:31:24.987 --> 00:31:29.670
One in terms of terrain, environmental project, projected environmental conditions.
00:31:29.670 --> 00:31:30.496
You don't want it too hot.
00:31:30.496 --> 00:31:33.711
You don't want it too cold, kind of goldie locks.
00:31:33.893 --> 00:31:38.455
But there's some athletes that would rather do a six day ultra on a 400 meter track.
00:31:39.396 --> 00:31:45.598
And then there's, there was other athletes that would like to run in the mountains for six days straight and never cross the same path.
00:31:45.598 --> 00:31:46.448
rate.
00:31:46.720 --> 00:31:56.393
And so you're trying to thread the needle between those dynamics and then also have a place that was, and it was, it was just stunning.
00:31:56.393 --> 00:31:57.193
It was beautiful.
00:31:57.193 --> 00:32:09.028
Now, interestingly enough, and this came up in our panel and that project further, or at the FEMA Athlete Conference as well in Boston, as yeah, we were entering into their windy season.
00:32:09.028 --> 00:32:11.140
It wasn't supposed to start until April, but.
00:32:11.140 --> 00:32:23.538
two or three days before the event, was this huge massive windstorm, which actually caused like a whole bunch of damage and issues and some athletes were supposed to land that day and their flights got delayed a day.
00:32:23.538 --> 00:32:26.990
so that that's field-based research.
00:32:26.990 --> 00:32:37.277
eh The entire plan that we had and all the schedule, we just ripped it up and almost started over two days out again because we had to move the media day and we had to move interviews.
00:32:37.277 --> 00:32:39.209
We had to move course recon.
00:32:39.209 --> 00:32:42.828
We had to move where the crews were gonna see the course.
00:32:42.828 --> 00:32:49.451
had to move meeting times and while rebuilding parts of the course that were already pre-set up.
00:32:49.451 --> 00:32:51.313
I had no gray hair prior to this event.
00:32:51.313 --> 00:32:58.884
I'm kidding, I did have gray hair, but there were some times I was like, what have we gotten into here?
00:32:58.884 --> 00:33:06.941
But in the end, there were a couple of days where it did rain or get a little windy, but it was nothing like the few days before.
00:33:06.941 --> 00:33:10.192
I think the vast majority of the event, the weather was pretty good.
00:33:10.192 --> 00:33:11.237
Yeah, nice.
00:33:11.237 --> 00:33:14.268
Do you recall temperature ranges like highs and lows out of curiosity?
00:33:14.268 --> 00:33:16.032
And you can give them in Celsius.
00:33:16.788 --> 00:33:19.640
I mean, I remember the average is around 20 degrees.
00:33:19.640 --> 00:33:25.853
I think maybe it got as hot as 30, but it was full sun, so it was warm.
00:33:25.853 --> 00:33:31.256
ah And in fact, and then nights, it was in the desert, so it was also cool at night.
00:33:31.256 --> 00:33:41.662
ah But that allowed, we ended up having about 35 % of the running done at night, I think because it was full sun and it was pretty warm in the day.
00:33:41.662 --> 00:33:54.596
ah I know that I was never so happy as when one of the Lululemon support staff brought me one of their puff jackets because it was cold supporting the athletes at night.
00:33:54.836 --> 00:33:56.240
so yeah.
00:33:56.500 --> 00:33:59.413
But yeah, the multi day stuff is very fascinating.
00:33:59.413 --> 00:34:05.326
All the different and I mean, especially too, when there's like altitude involved and yeah, all the environmental conditions very fascinating.
00:34:05.326 --> 00:34:05.906
Okay.
00:34:05.906 --> 00:34:07.417
Well, I want to dive into nutrition.
00:34:07.417 --> 00:34:10.550
So Susan, we're going to do a deep dive here.
00:34:10.550 --> 00:34:13.552
You mentioned you were trying to be kind of like out of the athletes hair.
00:34:13.552 --> 00:34:20.856
Does this mean that they were allowed to fuel like whenever they wanted or were you guys providing specific nutrition throughout?
00:34:21.826 --> 00:34:23.518
Well, there were no constraints.
00:34:23.518 --> 00:34:29.362
mean, unless the athlete asked for something that we couldn't source, but we absolutely did our best.
00:34:29.362 --> 00:34:34.449
had somebody who was a runner and if we didn't bring it with us, they would maybe go look for it.
00:34:34.449 --> 00:34:45.219
But we did a lot of reconnaissance work in advance, spending some time talking with the athletes to try to find out, you know, what kinds of foods that they would like to eat.
00:34:45.275 --> 00:34:54.139
As I said, we had athletes from all over the world and so some of the food likes were different than, let's say, your typical North American.
00:34:54.139 --> 00:34:56.119
So we wanted to understand that.
00:34:56.119 --> 00:34:59.490
And then we had a wide, wide variety of sport drinks and sport foods.
00:34:59.490 --> 00:35:05.836
We had a whole shelving unit set up with sport drinks and gels and treats and snacks.
00:35:05.836 --> 00:35:17.916
And then we also encouraged the athletes to bring their own favorite foods and some of them did some of the meal prep on their own with their staff or with their crews in their tents or their trailers.
00:35:18.277 --> 00:35:23.498
But we also brought a performance chef and they had a team with them.
00:35:23.498 --> 00:35:28.440
And so we had somebody available to cook for the athletes 24 hours a day.
00:35:28.920 --> 00:35:46.730
So if the athletes, know, as they were running around had a craving for pierogies, which happened quite regularly, they would run through their They would run by their crew area and say, need some pierogies, on my next lap.
00:35:46.730 --> 00:35:54.512
And we would relay that to the chef and they would prepare that and it would be available the next time the athlete came through.
00:35:54.512 --> 00:35:59.025
yeah, they pretty much ate whatever that they wanted to.
00:35:59.025 --> 00:36:07.588
But then having said that, if an athlete was struggling, we also would give them some information and support to try to help them along.
00:36:07.588 --> 00:36:11.811
to make sure that they were trying to minimize some of the energy deficits.
00:36:11.811 --> 00:36:21.938
So yeah, we did allow them or we did support them if they had questions and often it was through the crew as Trent said, but yeah, anything went.
00:36:22.806 --> 00:36:23.706
Wow.
00:36:23.728 --> 00:36:29.824
And so how are you measuring energy going in and energy expenditure?
00:36:31.554 --> 00:36:36.159
Why don't you do energy in, and I can answer the energy out.
00:36:36.159 --> 00:36:36.780
sure.
00:36:36.780 --> 00:36:42.440
So are you asking about how we measured what the athletes were taking in?
00:36:42.639 --> 00:36:43.599
yeah, okay.
00:36:43.599 --> 00:36:52.639
So basically every single morsel of food was weighed before they ate it.
00:36:53.239 --> 00:36:59.952
So some of the foods were recorded as like each individual portion.
00:36:59.952 --> 00:37:05.894
So if it was a burrito, we measured each item that went into the burrito and then they would eat what they wanted to.
00:37:05.894 --> 00:37:09.547
And then we would pick that apart and reweigh that.
00:37:09.547 --> 00:37:21.394
If it was like a lasagna, for example, we would use the weight back system, which meant that they would, we would pre-weigh the food and then they, would measure the plate waste.
00:37:21.394 --> 00:37:37.268
And then through the day, if let's say some athletes, ate a lot of gels, their team would keep all of the wrappers and then we would get the wrappers at the end and we would note that they had, let's say, eight Morton's gels that day.
00:37:37.268 --> 00:37:39.880
And then we would log that in.
00:37:39.880 --> 00:37:48.349
And we used the researchers to do that, but we also used the crews and we used the chef and his support staff as well.
00:37:48.704 --> 00:37:54.940
where they would write down on paper or they would use an iPad and smart sheets or they would take photos.
00:37:54.940 --> 00:38:00.217
So we had lots of different available ways to track the pre and the post.
00:38:00.217 --> 00:38:02.920
So I wanted to be as accurate as possible.
00:38:02.920 --> 00:38:03.800
Yeah.
00:38:04.101 --> 00:38:04.523
Yeah.
00:38:04.523 --> 00:38:09.318
but picking apart a burrito and its components sounds like quite the job.
00:38:09.318 --> 00:38:35.204
Yeah, well, I guess if you want high quality data out or information out, you have to get high quality information in and unless you're accurate about what you're collecting, it's not worth doing because otherwise we wouldn't be able to with confidence tell you how many calories or what the total daily energy intake of an athlete was if we didn't do a good job on that.
00:38:35.344 --> 00:38:37.476
Yeah, yeah, no, this is amazing.
00:38:37.476 --> 00:38:38.175
mean, very.
00:38:38.175 --> 00:38:41.929
Yeah, I'm I'm excited to hear more and what you guys found.
00:38:41.969 --> 00:38:43.210
But Trent, I'll let you break down.
00:38:43.210 --> 00:38:45.882
How did you measure energy expenditure?
00:38:46.184 --> 00:38:52.306
Yeah, first, I want to compliment the energy team, Sarah Purcell, Sarah Craven, and Susan.
00:38:52.565 --> 00:38:54.496
The three of them really drove that.
00:38:54.496 --> 00:39:02.108
had other people helping, but I'm going to say by far, it was the biggest work of all the groups.
00:39:02.108 --> 00:39:10.990
em It's the easiest on paper, but what you've just heard, it's really challenging to consistently do for six days straight.
00:39:10.990 --> 00:39:16.572
A whole other thing to do it for a two-day project or something, but Yeah.
00:39:16.753 --> 00:39:17.594
Yeah.
00:39:18.795 --> 00:39:19.115
Yeah.
00:39:19.115 --> 00:39:23.190
I have to say though, Trent, that we had such great support from the crews, right?
00:39:23.190 --> 00:39:28.467
If they wouldn't have been able to be on board, it would have been a much bigger job.
00:39:28.467 --> 00:39:30.510
yeah, we have to kudos to the crews.
00:39:30.510 --> 00:39:31.409
Yeah.
00:39:31.952 --> 00:39:32.693
Yeah.
00:39:32.693 --> 00:39:34.434
Yeah.
00:39:35.036 --> 00:39:35.385
Yeah.
00:39:35.385 --> 00:39:36.425
were great.
00:39:36.485 --> 00:39:46.690
So on the energy balance is energy intake, which Susan just described versus energy expenditure or total daily energy expenditure.
00:39:46.690 --> 00:39:53.153
so total daily energy expenditure can be measured indirectly with double labeled water.
00:39:53.394 --> 00:39:59.847
And so what they do is they have a labeled oxygen and the labeled hydrogen in the water that you drink.
00:40:00.081 --> 00:40:13.652
And when we collect the athlete's urine, we can measure oh how much of the labeled hydrogen ends up in H2O in the urine and then make a whole bunch of calculations.
00:40:13.652 --> 00:40:21.599
oh It's quite expensive, expensive urine and expensive water to then calculate the total daily energy expenditure.
00:40:21.719 --> 00:40:25.923
Within total daily energy expenditure, there's different components.
00:40:25.923 --> 00:40:27.880
There's four different components.
00:40:27.880 --> 00:40:30.422
There's the exercise energy expenditure.
00:40:30.842 --> 00:40:37.905
There's the non-exercise activity energy expenditure, which is walking around or working or talking.
00:40:38.184 --> 00:40:45.349
There's the basal metabolic rate, which we measured pre and post in the lab resting metabolic rate.
00:40:45.349 --> 00:40:50.572
And then there's the thermic effect of food, which is the energetic cost to process food to make energy.
00:40:50.572 --> 00:40:54.072
And so there's always an estimate of about 10 % on that.
00:40:54.565 --> 00:40:56.706
We measured basal metabolic rate.
00:40:56.806 --> 00:41:00.668
We measured total daily energy expenditure with the label.
00:41:00.949 --> 00:41:02.351
We measured energy intake.
00:41:02.351 --> 00:41:05.333
We have a very strong estimate for the thermic effect of food.
00:41:05.333 --> 00:41:09.175
So the only thing left over is exercise energy expenditure.
00:41:09.175 --> 00:41:15.943
we measured the exercise energy expenditure by subtraction, but we've also done it.
00:41:15.943 --> 00:41:27.295
Indirectly by heart rate and speed bands based on the testing we did in the few days lighting in, because we had a metabolic heart, we were measuring the core cost of exercise and the heart rates.
00:41:27.295 --> 00:41:30.396
And we have walking data all the way up to running data.
00:41:30.396 --> 00:41:34.378
So we can back calculate that through the entire event for every athlete.
00:41:34.378 --> 00:41:40.762
and then we also used, some different, estimates like metabolic equivalence, heart rate equivalence and other ways.
00:41:40.762 --> 00:41:43.364
So part of the paper will be.
00:41:44.173 --> 00:41:54.815
showing the four or five different methods across all of these ways to estimate energy expenditure and then highlighting over a six day event, which one we think is most accurate.
00:41:54.815 --> 00:42:05.081
So I got a little nerdy on all the inputs there, but I think, yeah, it's important for the listener to understand the rigor that goes into doing these projects.
00:42:05.081 --> 00:42:06.041
Yeah.
00:42:06.041 --> 00:42:17.221
So with the doubly labeled water within the urine, that mean every time the athlete has to use the restroom, you're collect like they have to go to a specific location because you're collecting their entire six days worth of urine?
00:42:17.239 --> 00:42:18.402
Great, great question.
00:42:18.402 --> 00:42:22.505
No, we did it in two, three day chunks.
00:42:23.365 --> 00:42:25.367
We got that with a baseline urine.
00:42:25.367 --> 00:42:28.570
So they produced a clean sample prior to drinking the water.
00:42:28.570 --> 00:42:29.871
They drank the water.
00:42:29.871 --> 00:42:32.675
We then got a sample three to four hours later.
00:42:32.675 --> 00:42:35.777
So we had the peak amount of tracer in the urine.
00:42:36.958 --> 00:42:39.000
We got a sample on day three.
00:42:39.340 --> 00:42:43.480
So we could look at the total daily energy expenditure over the first half of the race.
00:42:43.480 --> 00:42:44.255
Mm.
00:42:44.525 --> 00:42:46.717
And then we got a sample at the end after day six.
00:42:46.717 --> 00:42:49.157
So we could look at the second half of the race.
00:42:49.259 --> 00:42:54.342
and generally speaking, double label water, you can't get energetic resolution over hours.
00:42:54.342 --> 00:43:00.750
It's usually you need a few days for, for, for the method to work so that that fit really well, well for us.
00:43:00.750 --> 00:43:01.579
Yeah.
00:43:02.021 --> 00:43:09.574
But yeah, especially at the end of the event, during the celebrations, like there was a bunch of us had, well, one, someone brought mimosas.
00:43:09.574 --> 00:43:11.695
So I have this picture of me drinking.
00:43:11.931 --> 00:43:16.132
champagne orange juice in this hand and then I had a urine sample in this hand.
00:43:16.945 --> 00:43:22.632
Oh no, hopefully the six days of fatigue doesn't like catch up.
00:43:22.753 --> 00:43:25.224
Yeah.
00:43:25.224 --> 00:43:33.945
I did have a question to doing a multi-day event with the, m was it the temperature sensor you said they swallowed?
00:43:34.867 --> 00:43:37.440
How do you know when that's out of the body?
00:43:37.889 --> 00:43:40.291
Yeah, don't, it's one single use only.
00:43:40.291 --> 00:43:41.931
Let's just be clear here.
00:43:42.152 --> 00:43:45.534
We're recycling those.
00:43:45.813 --> 00:43:46.164
Yeah.
00:43:46.164 --> 00:43:48.775
So you can also get temperature live.
00:43:48.775 --> 00:43:51.827
So there's a Bluetooth feature to it.
00:43:51.827 --> 00:44:06.086
So you can see with the sensor, as soon as you get close to the athlete for, well, it takes maybe 30 seconds or one minute, but when they come in for a break at the pit stop, our wearables team, we had a team just based on sensors, would go and see where they're at.
00:44:06.086 --> 00:44:14.592
but we also proactively gave extra swallowable sensors the size of a small, like almost like a fish oil capsule, a little bigger than normal.
00:44:14.811 --> 00:44:20.614
And so you could tell right away when they were excreted, but we then would have another one in there.
00:44:20.614 --> 00:44:30.684
So in many instances, we'd have two measuring within the intestinal tract within the system at any given time, just in different thoughts in the intestinal tract.
00:44:30.684 --> 00:44:33.644
Wow, that's so fascinating.
00:44:33.644 --> 00:44:35.364
All of this is so neat.
00:44:35.364 --> 00:44:38.164
Like nerd out on all this data.
00:44:38.565 --> 00:44:41.125
Okay, so you got tons of data.
00:44:41.125 --> 00:44:44.344
Are you guys able to share?
00:44:44.344 --> 00:44:45.644
You said it was just an abstract that's out.
00:44:45.644 --> 00:44:48.693
Are you able to share what you guys discovered so far?
00:44:49.117 --> 00:45:03.869
Yeah, like we've shown the data at two conferences now that the top level of kind of physiology data and I can highlight in the next couple of years is probably going to be eight papers published on different areas.
00:45:03.869 --> 00:45:07.311
We have an overall methods paper that we've published already.
00:45:07.432 --> 00:45:10.574
And then we have the capstone paper that's in review right now.
00:45:10.574 --> 00:45:20.135
So the capstone paper is the top level methods and overview of what we saw that integrates kind of like the highlight reel for each group, but not the details.
00:45:20.135 --> 00:45:28.824
Because in each research group, whether it's energy or biomechanics, we'll do a very several specific papers on what they found there.
00:45:28.824 --> 00:45:40.255
So from the nutrition caloric top level perspective, and in the abstract that you saw and what we presented, can give.
00:45:40.255 --> 00:45:44.396
give the listeners a little bit of a low down here and a bit of a highlight reel.
00:45:45.135 --> 00:45:57.675
So first of all, know, athletes ran anywhere from 200 to over 900 kilometers throughout the event in six days, which for all of them is just completely amazing.
00:45:57.675 --> 00:46:01.675
And there was a really neat, very tight correlation.
00:46:01.775 --> 00:46:03.755
The more you ran, the more you ate.
00:46:03.956 --> 00:46:09.255
And so people really did self-select even on a day-to-day ratio.
00:46:10.184 --> 00:46:13.034
Yeah, the more they ran, the more they knew to eat.
00:46:13.034 --> 00:46:15.786
so I think part of that is experience of athletes.
00:46:15.786 --> 00:46:17.846
Part of that is coaching from people like Susan.
00:46:17.846 --> 00:46:21.347
And I think part of it's just innate in human biology.
00:46:21.347 --> 00:46:25.289
know, when you're in an energy deficit, there's signals to eat more.
00:46:25.289 --> 00:46:37.072
m What else is new or what else we found, which should make sense is the, again, there was a very good correlation, significant correlation between total distance run.
00:46:37.552 --> 00:46:39.452
and total energy expenditure.
00:46:39.452 --> 00:46:45.074
So as I said, total energy expenditure and intake and distance all were, were related.
00:46:45.114 --> 00:46:52.931
And I should highlight that on the exercise on the energy expenditure, on average, athletes expended 7,000 calories a day.
00:46:52.931 --> 00:47:03.164
I'm double using the double label water, but we had three female athletes that recorded the highest energy expenditures ever recorded in the literature.
00:47:03.164 --> 00:47:05.315
they kind of set metabolic world records.
00:47:05.315 --> 00:47:06.106
So.
00:47:06.557 --> 00:47:12.530
Um, we had, we had one that averaged 7,600 calories a day for six days straight.
00:47:12.530 --> 00:47:16.920
One that averaged 8,800 calories a day for six days straight.
00:47:16.920 --> 00:47:23.123
And then one that averaged 11,300 calories a day for, six days straight.
00:47:23.284 --> 00:47:30.067
it was just phenomenal, phenomenal energetic output over that, over that six days.
00:47:30.367 --> 00:47:33.306
that did result in an.
00:47:33.306 --> 00:47:39.070
on average, a negative energy balance of about two and a half to 2,200 calories.
00:47:39.070 --> 00:47:41.922
Like you just can't eat that much over the six days.
00:47:41.922 --> 00:47:45.737
so, there was definitely negative energy balance throughout.
00:47:45.737 --> 00:47:56.364
a few athletes popped into the positive uncertain days that were doing less mileage, but, generally speaking, yeah, throughout the six day event, there was negative energy balance.
00:47:56.364 --> 00:48:01.487
And again, despite what I just said, athletes that went further eight more.
00:48:01.487 --> 00:48:02.257
Mm-hmm.
00:48:02.257 --> 00:48:06.697
However, athletes that went further also had more negative energy balance.
00:48:06.697 --> 00:48:22.416
So you just can't, when you're expending 11,000 calories a day, yeah, like, you know, that one athlete was still eating probably six or 7,000 calories a day, but there's still a 4,000 calorie a day gap.
00:48:22.956 --> 00:48:31.916
And so those are some of the outcomes that we're seeing that will be in this capstone paper that is in review.
00:48:32.492 --> 00:48:40.351
Once that's out and published, there's a whole bunch of other details and maybe we'll have to come onto your podcast again and talk a little more about the details.
00:48:40.351 --> 00:48:47.594
We're reticent to discuss more until the paper is accepted and those details are out in the published literature.
00:48:47.594 --> 00:48:48.445
Yeah.
00:48:48.445 --> 00:48:53.313
Are you able to share the individual that was expending over 11,000 calories a day?
00:48:53.313 --> 00:48:56.317
Was that the person that was also covering the most mileage?
00:48:57.059 --> 00:48:58.039
Okay.
00:48:58.561 --> 00:48:59.411
Okay.
00:48:59.594 --> 00:49:11.679
and, and yeah, like all this is done under, under ethics and anonymized athletes, but, they also know, and it was written into their consent forms and their ethics, you know, you're in a 10 day race with lots of media, media coverage.
00:49:11.679 --> 00:49:15.561
So people are getting that in some instances, figure out who you are.
00:49:15.561 --> 00:49:19.661
And most of the athletes were like, no, I want to promote this on social media.
00:49:19.661 --> 00:49:23.565
And so, yeah, that top top athlete, I mean, you can Google search it.
00:49:23.565 --> 00:49:25.596
It's Camille Herron and she was.
00:49:25.931 --> 00:49:36.802
It's absolutely mind blowing, phenomenal in terms of the 901 point whatever kilometers she covered in six days for a new woman's world record.
00:49:37.333 --> 00:49:38.268
Wow.
00:49:38.268 --> 00:49:42.302
Did you guys monitor fluid consumption?
00:49:43.510 --> 00:49:46.132
Well, we monitored everything.
00:49:46.134 --> 00:49:50.876
although off the top of my head, I don't know how much she actually drank.
00:49:51.038 --> 00:49:55.661
We know how many calories she ate every day and we know what her energy deficit was.
00:49:55.661 --> 00:49:57.905
We know what her macro intake was.
00:49:57.905 --> 00:50:01.637
And we probably somewhere have that data on her fluid intake.
00:50:01.637 --> 00:50:04.570
Yeah, just off the top of my head, I don't know what it is.
00:50:05.235 --> 00:50:07.306
That and did you guys I forgot to ask this.
00:50:07.306 --> 00:50:14.079
Did you guys take into consideration or observer note menstrual cycle phase?
00:50:14.688 --> 00:50:25.318
Yeah, so I'm going to raise my hand and say I'm on a whole bunch of papers highlighting how important it is to characterize every single piece of the menstrual cycle.
00:50:25.398 --> 00:50:33.668
In those same methodological papers, there is an appreciation for the challenges that present in doing that in the field and outside of the laboratory.
00:50:33.668 --> 00:50:42.487
So we do have questionnaire-based data on the athletes and where they were self-report in their menstrual cycle.
00:50:42.487 --> 00:50:51.211
But I'll also highlight that the average age of the athletes was into the early to mid 40s off the top of my head.
00:50:51.793 --> 00:50:55.135
yeah, some of the athletes were already peri and menopausal.
00:50:55.135 --> 00:50:57.596
So you can't report that.
00:50:57.596 --> 00:51:02.619
they said, yeah, they don't have a menstrual cycle.
00:51:02.619 --> 00:51:09.784
So yeah, we only ended up with a a small handful of athletes were pretty sure of their reporting.
00:51:09.784 --> 00:51:18.871
That said, what's interesting is there is a massive deficit, but it does appear from a health perspective, everyone has bounced out of it.
00:51:19.672 --> 00:51:23.197
Okay, every single athlete has undertaken races again.
00:51:23.197 --> 00:51:28.559
There's no long-term signs of any deleterious outcomes from the event itself.
00:51:29.349 --> 00:51:32.331
And so, yeah, those were really positive things.
00:51:32.331 --> 00:51:41.918
And then about a year out with the athlete screening, the Canadian Sport Institute Pacific provided holistic services to these athletes that they could opt into.
00:51:41.918 --> 00:51:46.990
you if they wanted to consult with Susan on nutrition for the year and a half leading in, they had that option.
00:51:46.990 --> 00:51:51.726
If they wanted physiological or training consults from me and our team, they had that.
00:51:51.726 --> 00:51:55.628
We did through another research project, a REDS medical screen.
00:51:55.809 --> 00:52:02.159
And yeah, generally, generally speaking, this was a pretty, pretty healthy group in terms of that screen.
00:52:02.159 --> 00:52:05.641
And, I want to reiterate what Susan highlighted earlier.
00:52:06.342 --> 00:52:14.063
and sorry, I'm verbose here, but, normally there's a 10 to 20, 30 % injury rate for every athlete in a year.
00:52:14.063 --> 00:52:17.402
The fact that we got 10 athletes, we supported them.
00:52:17.402 --> 00:52:21.382
had 10 athletes reach the line, 10 athletes finish, 10 athletes reach their goals.
00:52:21.382 --> 00:52:31.717
Several athletes set world records as Beyond all this caloric energy expenditure stuff, that is a mind blowing to me that we were able to deliver that with those athletes.
00:52:31.717 --> 00:52:35.152
yeah, that is such a neat outcome of this project.
00:52:35.152 --> 00:52:37.554
Yeah, I think that says a lot.
00:52:37.554 --> 00:52:51.211
Like when people are being supported and have a team of people who know the specifics about different aspects that they maybe don't, it can help support them for a good amount of time leading into something I think makes a big difference.
00:52:51.211 --> 00:52:53.983
So yeah, kudos to you guys.
00:52:53.983 --> 00:52:57.338
that are willing to take on the information and learn from it.
00:52:57.338 --> 00:53:06.494
Yeah, I think there's a couple of other pieces I'd like to highlight around the menstrual cycle though, for example, is the event took place when the event took place.
00:53:06.494 --> 00:53:15.048
And so really if an athlete was menstruating or not menstruating, if they were a naturally menstruating female, we don't have any control over that.
00:53:15.449 --> 00:53:22.967
So all that we can do is what Trent said is just ask the athletes to track or to fill out questionnaires.
00:53:23.228 --> 00:53:29.556
So I think that that's an important piece of the menstrual function to keep in mind.
00:53:30.340 --> 00:53:35.402
And so I imagine you got information if anybody was on hormonal birth control as well in the questionnaire.
00:53:35.402 --> 00:53:35.983
Yeah.
00:53:35.983 --> 00:53:38.264
Awesome.
00:53:38.264 --> 00:53:48.478
With the behavior piece, I know you guys weren't the behavior side of things, em was there, like, did you see any struggles throughout the six days?
00:53:48.478 --> 00:53:55.612
Or even just any physical issues em occur with the runners, GI, anything like that, cramping?
00:53:56.588 --> 00:53:57.586
Back on.
00:53:57.722 --> 00:53:59.914
We did do some GI screens.
00:53:59.914 --> 00:54:05.855
ah We didn't get data every day, but we tried to get data on a regular basis.
00:54:05.855 --> 00:54:12.239
And we definitely did see, as you do in any endurance event, some GI struggles.
00:54:12.239 --> 00:54:15.891
And we were there to support the athletes that did have that.
00:54:15.891 --> 00:54:21.744
So with making recommendations for what kinds of foods maybe to try eating.
00:54:21.744 --> 00:54:24.646
But we definitely did see some GI struggles.
00:54:24.646 --> 00:54:26.074
And Trent, you could.
00:54:26.074 --> 00:54:38.268
talk about the cramping and I know we did have one athlete that had a muscle or a hip issue that was supported throughout the event.
00:54:38.293 --> 00:54:39.248
Mm-hmm.
00:54:39.393 --> 00:54:45.487
Yeah, so I mean, with this event as well, had three separate physicians involved.
00:54:45.487 --> 00:54:49.820
I mean, that athlete to physician ratio would never be better in all three physicians.
00:54:50.019 --> 00:54:54.284
One was the head physician for Western states, Andy Pasternak.
00:54:54.284 --> 00:55:01.918
One is a lead physician at the Stanford Women's Faster Program, Emily Kraus Yeah, yeah.
00:55:01.918 --> 00:55:02.641
her on a few times.
00:55:02.641 --> 00:55:03.791
She's wonderful.
00:55:03.836 --> 00:55:04.177
Yeah.
00:55:04.177 --> 00:55:08.436
And the third physician's a Harvard physician that is one of the lead physicians at Burning Man.
00:55:08.436 --> 00:55:10.376
So he's like big event medicine.
00:55:10.436 --> 00:55:17.277
So when you think about the three skill sets, it was really awesome when they were all complimentary to each other.
00:55:18.659 --> 00:55:26.059
and because we had this research program, we're also able live in the moment monitor how the athletes were doing.
00:55:26.378 --> 00:55:36.269
So to give feedback to the physicians or their crews, like, Oh, look at their, their blood sodium's here or their creatine kinase has gone to here or what have you.
00:55:36.269 --> 00:55:43.255
So, you know, that was indirectly from the research program, another layer of kind of safety involved.
00:55:43.456 --> 00:55:48.539
And I'm pausing, Susan, you pitched me something and I totally forget what your question was.
00:55:49.202 --> 00:55:55.907
Oh, well, think your question, Kyla, was related to muscle or muscle issues.
00:55:55.907 --> 00:55:58.070
Yeah, so I did pitch that to you.
00:55:58.231 --> 00:56:05.795
for sure, there were some individuals that were working through some muscle issues and some muscle challenges.
00:56:05.918 --> 00:56:12.282
we, we on certain days brought in, physios and massage therapists to the event.
00:56:12.282 --> 00:56:22.181
then we actually had two different physiotherapists that were in the biomech team that also helped do not only biomech, but actually said, you know what, I can help here.
00:56:22.181 --> 00:56:24.614
They stepped in and helped out with some physiotherapy.
00:56:24.614 --> 00:56:31.889
And so there, I think overall some every athlete set their best distance or what they were hoping for.
00:56:31.889 --> 00:56:44.570
But I'm, I think a couple of athletes probably could have went a little further, but yeah, I mean, 10 athletes, six days, you're going to have a, have a few niggles show up, but they all finished running again together and smiling at the end.
00:56:44.570 --> 00:56:48.248
So at the end it all came together.
00:56:48.248 --> 00:56:48.971
That's great.
00:56:48.971 --> 00:56:54.568
Are you guys able to share any info on the body composition changes throughout the six days?
00:56:54.753 --> 00:56:57.277
I can speak to it a little bit.
00:56:57.559 --> 00:57:01.063
And it's mainly going to be a little bit of a technical discussion.
00:57:03.217 --> 00:57:05.077
It's going to blow you away.
00:57:05.217 --> 00:57:14.396
I know I just said, like on average, people had, you know, a negative energy balance of two to 6,000 calories a day.
00:57:15.137 --> 00:57:19.637
The body weight changes for you to post as a group were not changed.
00:57:21.550 --> 00:57:37.528
And that has been shown in several studies in multi-day ultras, or if you talk to grand tour cyclists, after a day off or when there's a, when heat comes through, there is a whole bunch of water retention that happens in multi-day ultras.
00:57:37.969 --> 00:57:51.043
And, and so when they came back in for their body composition and body weight after the event, we have another way to actually assess and indirectly look at blood volume and their blood volumes went up.
00:57:51.043 --> 00:57:53.032
anywhere from 20 to 40%.
00:57:53.032 --> 00:57:56.186
That's mainly that, that water retention piece.
00:57:56.186 --> 00:58:10.289
And what's thought is, because of extreme dehydration or heat through multiple days, yeah, your, your kidneys, send out a whole bunch of hormones, you know, renin, basopressin, aldosterone that tend to send a signal.
00:58:10.289 --> 00:58:11.650
I'm, I'm dehydrated.
00:58:11.650 --> 00:58:13.960
I better hold on to all water that I have.
00:58:13.960 --> 00:58:16.894
And, it can cause some bloating.
00:58:16.894 --> 00:58:19.387
legs are thicker, their feet are fat.
00:58:19.387 --> 00:58:23.530
so at a body weight perspective, on average, there was no change.
00:58:23.911 --> 00:58:27.494
The other way that we look at body composition is through DEXA scans.
00:58:27.494 --> 00:58:40.652
And we had DEXA pre when they're all under resting conditions, we didn't even attempt a DEXA scan post, because it violates all the methodological principles of getting a good DEXA scan.
00:58:40.943 --> 00:58:45.527
which means you should be in good neutral hydration state and in a resting conditions.
00:58:45.527 --> 00:58:52.364
Well, we're not gonna hold the athletes there for three or four days afterwards to get a DEXA scan.
00:58:52.945 --> 00:59:05.076
So long story short, they were in massive energy deficits, but it doesn't show up in body weight losses because of this acute effect of hyper hydration and pretension of fluids, yeah.
00:59:05.076 --> 00:59:10.554
oh Do you think from a recovery standpoint that that is favorable?
00:59:10.554 --> 00:59:12.416
Like the body's doing that?
00:59:12.938 --> 00:59:14.418
And does that help recovery?
00:59:14.418 --> 00:59:19.664
Or should athletes like if they feel bloated like that, should they be trying to get that water out?
00:59:21.012 --> 00:59:23.233
So it depends on the context of your question.
00:59:23.233 --> 00:59:30.456
I firmly believe through millennial that mother nature knows what she's doing just as a principle.
00:59:30.597 --> 00:59:37.599
So yes, I do think that there's a recovery piece there that that mother nature knows knows what she's doing.
00:59:37.940 --> 00:59:42.481
However, this can also happen on rest days in the middle of the tour de France.
00:59:43.402 --> 00:59:45.813
And a lot of riders on rest days don't rest.
00:59:45.813 --> 00:59:48.083
They still ride three or four hours that day.
00:59:48.083 --> 00:59:49.949
And I suspect they do that.
00:59:49.949 --> 01:00:02.309
because of this reason, they knock down, they sweat out some of the fluid, they get hyper responses on the glycogen and usually coming out of a rest day on the Tour de France, it's in the mountains and they're gonna go straight uphill the next day.
01:00:03.088 --> 01:00:09.969
having a 4 % increase in body mass due to water weight is probably not good from a performance perspective.
01:00:09.969 --> 01:00:15.204
I'm speculating here, so I think it depends on the context of the situation.
01:00:15.204 --> 01:00:17.148
Wow, yeah, so fascinating.
01:00:17.148 --> 01:00:19.625
Okay, well, I want to be mindful of your guys' time.
01:00:19.625 --> 01:00:26.463
Is there any other nuggets you want to share about the further study?
01:00:26.463 --> 01:00:29.528
I think, Susan, I think we got the highlight reel.
01:00:29.528 --> 01:00:30.530
yeah, I think so.
01:00:30.530 --> 01:00:36.972
think the main things for me were the level of energy deficit.
01:00:36.972 --> 01:00:42.614
em Obviously, you wouldn't be able to continue to sustain that over more than six days.
01:00:42.614 --> 01:00:48.496
I think you're pretty much getting close to the maximal ceiling that an athlete can be in such a deficit.
01:00:48.496 --> 01:00:54.570
em think maybe Trent, one thing that was found was that the neuromuscular fatigue piece.
01:00:54.570 --> 01:00:56.199
I don't know if you're able to speak about that.
01:00:56.199 --> 01:00:58.481
I think that was pretty fascinating.
01:00:59.402 --> 01:01:01.795
Yeah, so that's true.
01:01:01.795 --> 01:01:05.827
And that's led by Chris Napier and Nick Bruce, Dr.
01:01:05.827 --> 01:01:08.061
Nick Bruce, she just defended last year.
01:01:08.061 --> 01:01:16.427
So what they did is they had a contraption that they brought down that does maximal voluntary contraction where they actually stimulate the muscle.
01:01:16.427 --> 01:01:23.693
So it's not like a cattle prod, but it takes the brain out of it and they can get a maximal voluntary contraction.
01:01:23.693 --> 01:01:26.141
And they looked at that on a force plate.
01:01:26.141 --> 01:01:29.322
indoors fresh and then after the event.
01:01:30.402 --> 01:01:35.065
for the legs, there was no significant deficit.
01:01:35.065 --> 01:01:48.007
And there is data, thank you, Susan, for highlighting, there is data in women to show that women compared to men may have a more protective effect and more resiliency to neuromuscular fatigue and Wow.
01:01:48.007 --> 01:01:51.748
We don't have an N equals 10 male cohort going at the same time.
01:01:51.748 --> 01:01:54.208
That would have been really neat.
01:01:54.489 --> 01:01:57.251
anyways, that was quite astounding.
01:01:57.251 --> 01:02:00.411
In the arms, they did show a deficit.
01:02:01.612 --> 01:02:08.597
So that's up to Chris and Nikki to tease out.
01:02:08.597 --> 01:02:10.998
That's their research area.
01:02:10.998 --> 01:02:14.440
But yeah, that's an interesting outcome for sure.
01:02:14.440 --> 01:02:15.514
That is fascinating.
01:02:15.514 --> 01:02:15.987
Wow.
01:02:15.987 --> 01:02:20.519
guess one thing we didn't highlight was the minimal sleep that the athletes got.
01:02:20.519 --> 01:02:22.951
At least I don't think we talked about that.
01:02:23.032 --> 01:02:30.916
I mean, I think they were averaging about five hours a night, but one and a half hours a night for one of the athletes.
01:02:31.106 --> 01:02:39.800
I think that what does that, that's how many, that's nine hours over the course of the event.
01:02:39.836 --> 01:02:40.380
Dang.
01:02:40.380 --> 01:02:43.561
I think the maximum was like 41 hours over six days.
01:02:43.561 --> 01:02:49.052
So we really also saw very limited amount of recovery time.
01:02:49.052 --> 01:03:01.867
And so for them to have done what they did with energy deficit and kind of limited amount of sleep and recovery really, when you stop to think about it, it's kind of, it's mind blowing.
01:03:01.867 --> 01:03:03.706
So, yeah.
01:03:04.791 --> 01:03:09.635
You didn't happen to measure like protein synthesis or mitochondrial.
01:03:09.795 --> 01:03:10.282
Okay.
01:03:10.282 --> 01:03:20.483
did not, that would directly require a muscle biopsy, indirectly requires another quarter million dollar in protein tracers, which we didn't do.
01:03:23.550 --> 01:03:24.610
Yeah.
01:03:25.351 --> 01:03:26.311
Wow.
01:03:26.512 --> 01:03:27.472
Gosh.
01:03:27.512 --> 01:03:28.072
Yeah.
01:03:28.072 --> 01:03:29.643
ah Okay.
01:03:29.643 --> 01:03:30.673
I have one last question.
01:03:30.673 --> 01:03:40.760
Speaking of all that, if you're allowed to share this part, creatine kinase levels, you drew that, was it immediately after the six days?
01:03:43.804 --> 01:03:49.646
Yeah, so there was a significant relationship between daily distance and creatine kinase.
01:03:49.646 --> 01:03:51.958
So the more you ran, the higher your creatine kinase.
01:03:51.958 --> 01:03:55.969
You know, there's some of the highest creatine kinases I've ever seen.
01:03:55.969 --> 01:04:03.083
So one of the athletes peaked out on day two and three approaching 10,000 units in terms of creatine kinase.
01:04:03.804 --> 01:04:08.646
What was interesting is by day four and five, she was down to 7,000.
01:04:08.646 --> 01:04:12.110
4,000 and then post race down to just under 2,000.
01:04:12.110 --> 01:04:17.313
So you can see an adaptive effect of creatine kinase within the race.
01:04:17.313 --> 01:04:18.731
Almost all athletes look like that.
01:04:18.731 --> 01:04:21.806
It peaks at day one or two, and then it's coming down over the U.S.
01:04:21.806 --> 01:04:22.996
six days.
01:04:23.518 --> 01:04:28.610
Most of the other athletes were all under 2,000 units for creatine kinase.
01:04:28.610 --> 01:04:31.443
A couple were above that.
01:04:31.443 --> 01:04:40.458
I suspect creatine kinase will also be really significantly correlated to the eccentric component of a course, the downhill parts.
01:04:40.458 --> 01:04:51.021
And because our course was very flat, a lot of these creatine kinases weren't that huge except one or two of the athletes that went really well.
01:04:51.021 --> 01:04:53.211
If you measured it at Western States.
01:04:53.211 --> 01:04:59.018
So the doc there was like, these are pretty low compared to what I'm used to at Western States with all the downhill pieces.
01:04:59.018 --> 01:05:00.039
yeah.
01:05:00.119 --> 01:05:07.563
And the body is, I mean, it sounds like it's like adapting to that and clearing that out over the coming days.
01:05:07.563 --> 01:05:09.384
Like, it's pretty incredible.
01:05:09.384 --> 01:05:10.304
Wow.
01:05:11.023 --> 01:05:23.369
That is a marker that I think is fascinating where I've had clients who will come to me and they're like, PCP does their labs and like that's elevated because they took it right after like an Iron Man race or something.
01:05:23.369 --> 01:05:24.152
The doctors.
01:05:24.152 --> 01:05:26.092
a little going what's going on.
01:05:26.311 --> 01:05:26.831
Yeah.
01:05:27.452 --> 01:05:27.746
Yeah.
01:05:27.746 --> 01:05:30.326
we need to put you on a super low protein diet.
01:05:30.326 --> 01:05:32.525
Don't take your creatine.
01:05:33.085 --> 01:05:41.373
I know it's totally yeah, if you want to speak on that, I'd love for our listeners to hear your your input or thoughts on that.
01:05:41.512 --> 01:05:47.179
I would just not take that test right after doing that kind of a race.
01:05:47.179 --> 01:05:55.186
I would just do your blood work once or twice a year, your baseline, and then that's the best way to do it.
01:05:55.186 --> 01:06:02.532
I don't think we really, it's interesting information, but I think your general listener doesn't need to know what their creatine kinase levels are.
01:06:02.789 --> 01:06:03.710
Yeah.
01:06:03.711 --> 01:06:12.710
Do you have a recommendation of like rest days prior to a blood work or how long it takes for those levels to normalize after a hard effort?
01:06:14.300 --> 01:06:22.027
Well, we definitely recommend a rested blood work and usually we're looking at 24 to 48 hours if we can have that.
01:06:22.027 --> 01:06:28.833
Sometimes we don't get that, but we're then looking at having our athletes not do a hard training session.
01:06:28.833 --> 01:06:41.034
So to answer the question about how close proximity to after a hard training session, I don't know what the best answer is there, Trent, do you?
01:06:43.065 --> 01:06:47.465
I think it depends on whether or not that hard training session is routine for that athlete.
01:06:47.465 --> 01:06:48.905
That's the really big piece.
01:06:48.905 --> 01:06:58.565
So if they're used to running hard for one hour, three times a week, their creatine kinase is barely going to blip because that's what they're used to.
01:06:58.706 --> 01:07:04.246
If you take someone new and you have them do a one hour run, their creatine kinase is going to go through the roof.
01:07:05.025 --> 01:07:08.786
So it depends on their history and where they're at.
01:07:08.945 --> 01:07:12.088
Usually we try that 24 to 48 hour clear window.
01:07:12.088 --> 01:07:17.403
It helps with iron measurements as well, because there's not elevated exudin and elevated ferritins.
01:07:17.403 --> 01:07:25.340
You get a first thing in the morning, ideally with about the same hydration factor and pick the same lab.
01:07:25.340 --> 01:07:27.675
Lab to lab differences can be quite large.
01:07:27.675 --> 01:07:31.498
So no matter what you're measuring, ideally it's going to that same lab.
01:07:31.608 --> 01:07:34.358
Yeah, that makes that's lot of good suggestions there.
01:07:34.358 --> 01:07:41.541
Okay, I'm going to jump back to your two truths and a lie and we are going to find out some fun facts.
01:07:41.563 --> 01:07:45.550
Okay, so Susan says the world consumes 50 billion burgers a year.
01:07:45.550 --> 01:07:51.554
All further athletes ate burgers and classic burgers are also known as the California burger.
01:07:51.554 --> 01:07:55.166
I thought the 50 billion burgers a year was a lie.
01:07:55.166 --> 01:07:56.436
Is that correct?
01:07:56.735 --> 01:07:58.115
That's the truth.
01:07:59.635 --> 01:08:01.556
I know crazy, hey?
01:08:01.576 --> 01:08:02.416
The further.
01:08:02.416 --> 01:08:05.335
Yeah, so we actually had one vegan athlete.
01:08:06.416 --> 01:08:08.023
So yeah.
01:08:08.597 --> 01:08:09.148
Okay.
01:08:09.148 --> 01:08:12.376
No burger for the- but did everybody else eat burgers besides the vegan?
01:08:12.376 --> 01:08:13.007
Pretty much.
01:08:13.007 --> 01:08:18.939
We did some pre-testing as Trent mentioned.
01:08:19.079 --> 01:08:24.721
We had a chef set up then, but then they had to move their entire kitchen facility to another location.
01:08:25.622 --> 01:08:32.184
While they were doing that, there was a little tiny bit of a window and we went for in-and-out burgers for the athletes.
01:08:32.184 --> 01:08:39.793
And then Trent, you said during the peak of the Seattle grunge Rock area, you had dreadlocks, six tattoos and a nipple piercing.
01:08:39.793 --> 01:08:42.077
I'm thinking the six tattoos was a lie.
01:08:42.077 --> 01:08:43.930
Which one was your lie?
01:08:43.930 --> 01:08:47.212
right, I only have one small tattoo on my leg, so...
01:08:47.212 --> 01:08:47.793
Yeah.
01:08:47.793 --> 01:08:51.927
oh was a nipple piercing and dreadlocks.
01:08:51.927 --> 01:08:55.167
Yeah, yeah, and don't do this at home.
01:08:55.167 --> 01:09:06.247
I went to Woodstock 99, because I went to stay at school at Cornell, which is like quite close to, and I got that piercing like two weeks before going to that.
01:09:06.547 --> 01:09:08.847
This is dumbest idea ever.
01:09:08.927 --> 01:09:10.347
And it didn't get infected.
01:09:10.347 --> 01:09:12.347
I have no idea how that didn't happen.
01:09:12.347 --> 01:09:13.520
So there you go.
01:09:13.615 --> 01:09:14.547
is impressive.
01:09:14.547 --> 01:09:14.908
Wow.
01:09:14.908 --> 01:09:16.091
Okay.
01:09:16.091 --> 01:09:17.212
Well, this has been super fun.
01:09:17.212 --> 01:09:19.498
Where can our listeners find you, follow you?
01:09:19.498 --> 01:09:23.914
When is this doing, when do we think this paper is like officially getting published?
01:09:23.914 --> 01:09:25.086
Do we have an idea?
01:09:25.985 --> 01:09:27.297
That's a tricky estimate.
01:09:27.297 --> 01:09:31.762
I've had papers published in two weeks to eight months.
01:09:31.762 --> 01:09:33.434
It depends on the number of reviews.
01:09:33.434 --> 01:09:39.310
It depends on what the reviewers think of it, how quickly they do the reviews, how many review cycles we have.
01:09:40.792 --> 01:09:43.771
next four plus or minus two months.
01:09:43.771 --> 01:09:44.274
Yeah.
01:09:44.274 --> 01:09:44.837
Okay.
01:09:44.837 --> 01:09:45.621
Great.
01:09:45.621 --> 01:09:49.372
are either of you speaking to any conferences coming up in 2026?
01:09:51.184 --> 01:09:51.743
I'm not.
01:09:51.743 --> 01:09:53.164
have a slew of them.
01:09:53.164 --> 01:09:54.125
Yeah.
01:09:55.185 --> 01:10:01.395
Yeah, I'll speak at the American College of Sports Medicine Conference.
01:10:01.395 --> 01:10:07.439
That's in Utah and then the International Society of Sport Nutrition in Florida as well.
01:10:07.439 --> 01:10:11.319
I those are my two US ones.
01:10:11.319 --> 01:10:17.520
I have one in Germany in March, but that's a translated one or whatever.
01:10:17.520 --> 01:10:18.492
Awesome.
01:10:18.492 --> 01:10:20.064
I might see you at the ISSN one.
01:10:20.064 --> 01:10:21.654
I'm going to try and go to that.
01:10:21.756 --> 01:10:24.661
I'll have to pop in and say hi.
01:10:24.661 --> 01:10:26.654
And then Susan, where can people find you?
01:10:26.654 --> 01:10:29.046
Follow your research.
01:10:29.488 --> 01:10:31.220
Are you taking on clients?
01:10:31.827 --> 01:10:40.474
I don't take on clients because I'm 100 % subscribed to Canadian Sport Institute and I'm generally not really much on social media.
01:10:40.474 --> 01:10:50.983
So I think if you want to follow my research, you're following Trent's research because mostly everything that he's doing, I'm in the background supporting, well, not mostly, some of.
01:10:50.983 --> 01:10:52.373
So yeah.
01:10:52.895 --> 01:10:54.207
So perfect.
01:10:54.207 --> 01:10:56.881
Well, this has been super fun and fascinating.
01:10:56.881 --> 01:10:59.496
Thank you both, Susan and Trent, for joining us.
01:10:59.496 --> 01:11:00.856
This has been wonderful.
01:11:01.904 --> 01:11:03.043
Yeah, thank you very much.
01:11:03.043 --> 01:11:03.963
It was a lot of fun.
01:11:03.963 --> 01:11:05.583
Thanks for inviting us.
01:11:05.835 --> 01:11:06.317
You bet.