Running research nerd alert.
July 2020.
by Thomas Solomon PhD and Matt Laye PhD.

Each month we compile a short-list of our favourite recently-published papers (list available here) from the world of running science and break them into bite-sized chunks so you can digest them as food for thought during your training sessions. Welcome to this month's installment of our "nerd alert". We hope you enjoy it.
Reading time ~17-mins (3500-words)
Share this nerd alert:


Clicking the title of each article will "drop-down" our summary.

Full paper access https://pubmed.ncbi.nlm.nih.gov/32679728/
What was the hypothesis or research question?
For long-duration races lasting more than 2.5 hours, current sports nutrition guidelines advise a carbohydrate ingestion rate of 90 grams/hour during exercise. But, recent data suggest 120 g/h may help when muscle damage is more prevalent, such as in mountain races. The authors hypothesized that a carbohydrate ingestion rate of 120 g/h during exercise would reduce neuromuscular fatigue and improve recovery compared to 90 g/h.
What did they do to test the hypothesis or answer the research question?
Authors used a parallel-group, repeated-measures design to compare 3 carbohydrate dosing strategies. Thirty athletes were screened and included if they had >5 years’ ultra race experience and had undertaken “gut training” to enhance carbohydrate absorption. Twenty-six elite male athletes (including two world champions) were included and took part in a mountain race in Spain (42 km, 2000 m elevation gain), during which 6 withdrew due to injury or gastrointestinal distress. Athletes were randomised to a low (60 g/h), medium (90 g/h), and high (120 g/h) carbohydrate feeding regimen. Carbohydrate was provided as gels (formulated and packaged in the lab) providing 30 g of maltodextrin (glucose) and fructose in a 2:1 ratio, and GPS alarms were used to alert runners to consume every 15, 20 and 30 min during the race. Water was allowed ad libitum but no other food was ingested. Heart rate was measured during the race. Internal load was assessed using individualized training impulse (TRIMP). Performance tests (vertical jump height, 1RM squat, velocity during 3 x 70% 1-RM squat, and run to failure at 20 kph at 1% with lactate and HR measurement) were completed 7-days before and 24-hours after the race to determine the effects of feeding strategies on neuromuscular function (vertical jump and squats) and aerobic power (time-to-exhaustion at 20 kph).
Study design. Running science nerd alert Thomas Solomon and Matt Laye.
What did they find?
— Race day conditions were good (10 °C, 60% humidity and 10 km/h wind speed).
— Race finish times were not different between groups (P=0.06). Individual athlete data were not presented, but the authors vaguely noted “a tendency for runners who ingested 120 g/h of CHO during the marathon race to be faster than those who took 60 g/h and 90 g/h.”
— Internal load (TRIMP) was lower in the high-carb group compared to the low- and moderate-carb groups, indicating lower fatigue during the race.
— Time-to-exhaustion at 20 kph was unchanged compared to pre-race in the high-carb group (1.28 ± 8.55%) but decreased in the low-carb (−14.09 ± 14.98%) and moderate-carb (−14.87 ± 11.86%) groups, wile RPE and heart were unaffected by the race nor different between groups.
— Jump height (high: 1.19 ± 8.05%, low: −11.33 ± 8.00%, moderate: −9.66 ± 8.19%), jump time-in-air (high: 0.53 ± 5.12%, low: −5.90 ± 4.18%, moderate: −5.02 ± 4.22%), and squat 1-RM (high: −2.35 ± 7.23%, low: 15.30 ± 7.54%, moderate: −13.84 ± 9.74%) were decreased after the race in low- and moderate-carb groups but not affected in the high-carb group.
— The authors concluded that 120 g/h carbohydrate intake during a mountain marathon might limit neuromuscular fatigue and improve recovery of high-intensity running capacity 24 h after the race, compared to 90 g/h and 60 g/h.
What were the strengths?
— High external validity since the observations were made during a real race scenario in highly-experienced athletes.
— Participants’ ages and anthropometric values (BMI, body fat %) were well-matched between groups.
— Participants were advised to drop out of the race if they experienced feelings of muscle damage, injury, or gastrointestinal distress to prevent such things from influencing the data.
— Dietary intake was controlled and provided for 48-hours prior to and 24-hours following the race, to ensure sufficient energy availability.
— Repeated-measures analysis enabled fair comparison within groups.
What were the weaknesses?
— Cross-sectional comparison between separate groups of participants reduces the external validity of the between-groups comparison. A cross-over study would improve such validity but in the context of the intervention (a demanding 42 k mountain marathon), a cross-over design is not possible.
— Non-parametric stats (Kruskal–Wallis test, Mann Whitney u tests, and Wilcoxon signed rank tests) were used because the authors deemed the sample size to be “small” - this is an arbitrary way to determine choice of stats.
— Sample size was not justified using power calculations.
— No effect sizes are reported so we cannot know the magnitude of effects between groups.
— Although race finish-times were not significantly different between groups (P=0.06), presenting individual values or a regression of finish time against carbohydrate dose would enable insight into the effects of high vs. med vs. low-dose regimens.
Are the findings useful in application to training/coaching practice?
Yes. While the study does not examine the effects of the during-race feeding regimens on race performance, the finding that the high carbohydrate intake (120 g/h) prevented loss of neuromuscular fatigue and maintained run performance on the day after the race indicates improved recovery. But the urgency to recover from a 42 km mountain race within 24-hours is uncommon for athletes competing in single day events. The findings are possibly more applicable to multi-days races (e.g. Tour de Tirol, 10km, 42km, 21km format), multi-day FKT through-hikes, or race seasons like the Golden Trail series (which has several 42 km races spaced only 2-3 weeks apart).

Full paper access https://jissn.biomedcentral.com/articles/10.1186/s12970-020-00364-7
What was the hypothesis or research question?
It is very challenging to consume adequate energy and fluid during ultra races due to increased risk of adverse effects, including gastrointestinal symptoms and exercise-associated hyponatremia. The authors hypothesized that elite athletes comply to International Society of Sports Nutrition recommendations during an ultra-distance competition without exhibiting detrimental adverse symptoms
What did they do to test the hypothesis or answer the research question?
The authors conducted an observational study of 12 elite athletes (6 males and 6 females; age: 46 ± 7 years, full data here) to compare their food and fluid intake during the 2019 24-h World Championships in France to the 2019 nutritional recommendations from the International Society of Sports Nutrition. To do so, they recorded food and fluid intake during the race, and gastrointestinal symptoms (hourly), markers of dehydration (body mass, plasma and urine osmolality, and plasma volume), and exercise-associated hyponatremia (plasma and urine sodium levels) before and immediately after the race. Changes in hematocrit and hemoglobin concentrations in whole blood were measured to estimate alterations of plasma volume. Athletes were not instructed to consume certain diets and were free to choose what they wanted at the feeding zone, which was located at the end of each 1.5 km lap. One athlete dropped out of the race.
What did they find?
— Race day conditions were mild-to-hot and sunny (17.4 °C, humidity 74.0%, wind speed 0.7 m/s (2.5 kph).
— Eight participants experienced at least one gastrointestinal symptom, muscular pain was observed in 5 participants, and 2 suffered from lower back pain.
— Total distance run in 24-hours ranged 193–272 km.
— There were large variations within the groups for total energy intake and specific nutrients (full data here).
— Observations include 685 ml/h fluid (range 385-1250), 159 g/h total food (range 79-491), 1463 KJ energy/h (range 305-2284), 62.2 g/h (or 25.5 g/kg/h) carbohydrate (range 14-105 g/h), and 2054 mg/h sodium (range 271-6189). Fat and protein intake were low (~8 g/h each). Note that the nutritional recommendations for are 450–750 mL/h fluid, 670–1670 kJ/h energy, 30–50 g/h carbohydrate, and 5–10 g/h protein.
— The most notable finding was that running performance (total distance ran in 24 h) was positively associated with total energy (MJ) ingested and inversely associated with total water drunk.
— Plasma volume increased, urine (but not plasma) osmolality increased, and urinary and plasma sodium concentrations decreased following the race. Two participants had asymptomatic exercise-associated hyponatremia (plasma sodium <135 mmol/L)
Energy intake positively associated with distance ran, water intake negatively associated with distance ran. Running science nerd alert Thomas Solomon and Matt Laye.

What were the strengths?
— High external validity since the observations were made during a real race scenario in highly-experienced athletes.
— Due to non-normally-distributed data, nonparametric statistics were used (Shapiro-Wilk, Wilcoxon tests, and Spearman’s rank correlation coefficients.
What were the weaknesses?
— Sample size was not justified using power calculations.
— Small sample of athletes competing in an obscure event with few competitors (a 24-hour championship on a flat 1.5 km road loop).
— Energy expenditure, which could be measured with doubly-labelled water, was not estimated using HR monitors or accelerometers as athletes refused to wear them. Instead, it was estimated from an algorithm based on weight, resting heart rate, and speed.
— Data presentation in the figures is hard to navigate. Some extra clarity in the legends, markings, and footnotes would help more quickly understand what all the different shadings and colours mean.
Are the findings useful in application to training/coaching practice?
Yes. While the findings demonstrate that most athletes from a small sample achieve ultra-running nutrient guidelines and that some of these athletes experience evidence of dehydration and possible hyponatremia, these observations are not new. It is also not surprising that intake matched recommendations when the ISSN guidelines were based on multiple observations of athlete consumption during ultra races. A bit of a chicken and egg scenario. Since the sample of athletes was small and since they were competing in an unpopular and obscure event (24-hour championship on a flat 1.5 km road loop), it is also tricky to extrapolate the findings to all ultra events, many of which are off-road and trail/mountainous terrain with less frequent access to feeding zones. Future work is needed. However, the data do provide a clear picture that the greater the energy intake the better the ultra performance - knowledge often neglected by athletes.
https://jissn.biomedcentral.com/articles/10.1186/s12970-020-00364-7/figures/4

Full paper access https://www.sciencedirect.com/science/article/pii/S2095254620300776 or watch a video presentation here.
What was the hypothesis or research question?
The authors review the evidence that compares theoretically-optimal pacing strategies and actual pacing caused by tactical decisions during championship racing (where winning outweighs chasing fast times).
What did they do to test the hypothesis or answer the research question?
The authors conducted a “narrative review” of published literature (which means they did not use formal systematic approach or a meta-analysis of prior findings). They combine their observations of prior work with publicly-available data from World Athletics (from championship events since 2008) to construct pacing “norms” in world-class runners in 100m though to marathon distances.
What did they find?
— Elite 100m and 200m runners use an all-out pacing strategy. Max speed is reached about ½-way in a 100m and sooner in the 200m with a fade toward the line.
— 400m racers use a positive pacing strategy - start fast and fade.
— 800m athletes also use a positive pacing strategy that results in a seahorse-shaped pacing. Success is related to the runner's ability to get close to the race leaders from the beginning and produce a fast second lap. 800 m runners should also avoid running wide on the bends throughout the whole race.
— 1500m (and 1-mile) races show parabolic U-shaped pacing strategy, often with parabolic J-shaped profile during major championships. 1500 m runners should be physiologically prepared to cover the last lap of a major championship event much faster than the mean speed needed to qualify.
— 5000 m and 10,000 m races also show parabolic U-shaped pacing, on average, but many variations are found in championship races. Such runners should be prepared to run at a relatively high speed whilst repeatedly varying their pace. 5000m/10,000m and 1500m runners should stay with the lead during the last lap since they might benefit from drafting. Running wide in 1500 m, 5000 m, and 10,000 m races is only advantageous during decisive stages of the race.
— In championship ½-marathon races, typically a parabolic U-shaped pacing is used.
— In championship marathons (and cross-country), positive pacing strategies are common.
Pacing profiles and tactical behaviors of elite runners. Running science nerd alert Thomas Solomon and Matt Laye.
What were the strengths?
— Clear overview of pacing tactics used by elite athletes at championship events running from 100m through to marathons.
What were the weaknesses?
— A long-winded narrative that is very clearly and briefly described with their graphical abstract (see Figure above).
— An insight into how pacing strategies have changed over time would be useful, but this was not an a priori aim of the paper.
Are the findings useful in application to training/coaching practice?
Possibly. For athletes without a realistic chance of winning medals or finishing in a top position within close proximity to the winners, conservative pacing strategies are advised in long-distance races. Elite athletes who are in contention for championship medals or top spots should be aware of typical pacing strategies adopted in their events - and be aware that championship pacing strategies are very different from record attempts with pacemakers (or time-trials). Coaches and athletes who are students of their sport will already know these sentiments and will not learn anything new from this paper; otherwise, the paper (or at least its graphical abstract) is a very useful learning resource.

Full paper access https://bjsm.bmj.com/content/54/15/898
What was the hypothesis or research question?
To see whether running in general and the amount of running specifically was associated with lower risks of all-cause and cardiovascular and cancer specific causes of death.
What did they do to test the hypothesis or answer the research question?
The authors used a systematic review approach to select prospective cohort studies which examined whether running was associated with lower levels of mortality. The researchers used 14 studies originating from 6 different prospective studies totalling 232,149 subjects.
What did they find?
They found that within the 232,149 subjects over the 5.5-35 year follow up of the different studies there were 25,951 deaths in that period of time. This data was sufficient to perform a meta-analysis which showed a consistent reduction of all-cause, cardiovascular, and cancer death of 27%, 30%, and 23% respectively when running was compared to no running. They also looked at whether weekly frequency, weekly duration, pace, and total running volume were important for reduction and saw no significant effect of any of those variables.
What were the strengths?
— They followed proper procedure of a systematic review and registered their methods and approach prior to carrying out the study to reduce bias.
— Their research question was broad enough to be generally applicable, but specific to runners.
— Their search for studies yielded in a large number of subjects and deaths over the follow up period.
— Unlike other similar studies the end-point of this study was mortality, which is a pretty important one.
What were the weaknesses?
— The studies used are not of randomized controlled trials and only a small number of studies were selected preventing an analysis of publication bias.
— All running data that was collected was self-reported.
— Insufficient data to look at cardiovascular and cancer mortality in relation to specific attributes of running.
— Whether people continued to run was not really addressed in many of the studies they used.
— Distance was not collected in the studies they looked at.
Are the findings useful in application to training/coaching practice?
While not specifically relevant to coaching, it is a good reminder that exercise is good for us and that it actually seems to take very little exercise to have significant effects on our health. It’s not just the increase in VO2max or reduction in resting HR that changes, but also the ultimate end-point mortality. Other papers have suggested that there might be a thing as too much running, this paper does not support that argument but also notes that they needed more subjects in the high volume running group.

Full paper access https://www.jsams.org/article/S1440-2440(20)30664-2/fulltext
What was the hypothesis or research question?
Previous studies have examined the role of uphill and downhill running in trail running success, but studies have not looked at what physiological traits predict uphill and downhill running success.
What did they do to test the hypothesis or answer the research question?
They had highly trained endurance athletes complete 5km time trials downhill and also uphill in field conditions rather than in a lab. The route had 400m of gain or loss (~8%) and the experimenter followed along on an e-bike. In addition they measured flat running VO2max, lower limb extensor maximal strength, local muscle endurance, leg musculotendinous stiffness, vertical jump, explosive/agility and sprint velocity to determine whether they were associated with performance in either of the time trial conditions. The tests were done over 5 visits spread out between 3-5 days and randomized in terms of what tests they performed on a given day.
What did they find?
In the time trials VO2 on the uphill time trial was slightly higher than on the downhill time trial, while both had similar heart rate responses and lactate responses. Using all of the metrics they created a model that explained 94% of the variation in uphill running and a second model that explained 84% of the variation in downhill running. For uphill running velocity achieved at VO2max, BMI, and lower limb maximal strength (1RM squat) contributed 68.3%, 14.1%, and 2.8% in explaining 94% uphill running performance. In downhill running lower limb maximal strength (1RM squat), the velocity at VO2max, and leg musculotendinous stiffness explained 50.7%, 48%, and 10.2% of the regression analysis (which itself explained 84% of the variation).
What were the strengths?
— Strengths are that both uphill and downhill running performance were analyzed separately rather than predicting overall ultra performance.
— The unique predictor, BMI for uphill running and leg stiffness for downhill running make physiological sense.
— They also did field tests which is unique.
What were the weaknesses?
— Field tests may be influenced by environmental conditions and trail conditions.
— There were a relatively small number of subjects who were very homogenous (male, well trained).
— The time trial distance of 5km is not directly applicable to long ultras and thus some of the predictive indicators may be less important for longer races..
Are the findings useful in application to training/coaching practice?
Yes. First, you can get a good VO2max workout on downhill efforts as these athletes could maintain 90% of VO2max for the duration of the downhill time trial. We already knew that VO2max is not a great predictor of performance, but the velocity at VO2max seems particularly important and worth working on. Lower limb maximal strength and muscle stiffness can both be worked on specifically by athletes and designed into training programs.

Full paper access https://www.jsams.org/article/S1440-2440(20)30662-9/fulltext
What was the hypothesis or research question?
To see whether the diversity and overall amount of specific bacterial species is associated with the physiological responses typically seen when runners experience gastrointestinal distress in hot conditions. They hypothesized that more alpha-diversity of bacteria would be associated with lower physiological strain, thermoregulatory strain, and markers of epithelial injury, systemic inflammation, and gastrointestinal symptoms
What did they do to test the hypothesis or answer the research question?
They had relatively well trained runners (VO2max = 57.5 ml/min/kg) runners (n = 22, 13 males, age 35)) complete a 2 hour bout of exercise at 60% of VO2max in hot conditions (35oC) in the laboratory while measuring heart rate, core temperature, a scale of intestinal stress, and overall thermal comfort rating. Pre and post the run they took blood samples to measure proteins that are markers of gastrointestinal stress. They also took fecal samples pre-exercise to measure the microbiota of the gut.
What did they find?
Overall a greater abundance of both communsal (aka “good” bacteria) and pathogenic (“bad” bacteria) was associated with more intestinal epithelial injury as measured by a blood marker. Opposite of their hypothesis, a lower alpha-diversity, more overall abundance, and a higher Firmicutes:Bacteroidetes ratio were associated with a greater overall stress response to exercise in the heat. In general there were large differences in the bacterial compositions of the individuals despite being a fairly homogeneous group. No single phyla, family, or genus of bacteria was strongly associated with gastrointestinal symptoms, good or bad.
What were the strengths?
— Study design did lead to gastrointestinal issues by the subjects.
— Researchers controlled for the diet for 24 hours prior to the testing with a low FODMAP diet to reduce gastrointestinal symptoms.
— Well controlled laboratory conditions for exercise testing.
— Comprehensive markers of gastrointestinal stress, heat stress, and inflammation.
What were the weaknesses?
— The entire study was based on correlations rather than figuring out whether changes in gut bacteria are causing changes in gastrointestinal markers of stress.
— They also used markers of damage rather than assessing gastrointestinal damage directly (which is hard to do).
— Did not detect some of the taxa of bacteria found to be important in other studies of athletes gut bacteria.
— Small sample size given the diversity of gut bacteria found.
Are the findings useful in application to training/coaching practice?
Yes, there is not sufficient evidence to support the use of pro or prebiotics for performance and potentially increasing the diversity of bacteria may increase the inflammatory and heat stress while exercising in hot conditions. So don’t do anything rash.


That is all for this month's nerd alert. We hope to have succeeded in helping you learn a little more about the developments in the world of running science. Until next month, keep active, stay nerdy, and train smart.

If you are enjoying this free content, please subscribe to our nerd alerts and like and follow @veohtu, @mjlaye and @thomaspjsolomon. Please also share these nerd alerts on your social media pages, and if you would like to keep this free content alive please “buy us a beer”.
Any interpretations and recommendations we make are, and always will be, based on our own views and opinions shaped by the evidence available to us. Before making any changes to your training based on any information we provide, always ensure it is safe for you to do so and consult your doctor if you are unsure.

If you find value in these nerd alerts and want to help keep them alive, please buy us a beer:
Buy me a beer.Buy me a beer.


Dr Thomas Solomon and Dr Matt Laye. Running science nerd alert.
About the authors:
Matt and Thomas are both passionate about making science accessible and helping folks meet their fitness and performance goals. They both have PhDs in exercise science, are widely published, have had their own athletic careers, and are both performance coaches alongside their day jobs. Originally from different sides of the Atlantic, their paths first crossed in Copenhagen in 2010 as research scientists at the Centre for Inflammation and Metabolism at Rigshospitalet (Copenhagen University Hospital). After discussing lots of science, spending many a mile pounding the trails, and frequent micro brew pub drinking sessions, they became firm friends. Thomas even got a "buy one get one free" deal out of the friendship, marrying one of Matt's best friends from home after a chance encounter during a training weekend for the CCC in Schwartzwald. Although they are once again separated by the Atlantic, Matt and Thomas meet up about once a year and have weekly video chats about science, running, and beer. This "nerd alert" was created as an outlet for some of the hundreds of scientific papers they read each month.

To read more about the authors, click the buttons:



Copyright © Thomas Solomon and Matt Laye. All rights reserved.

© Copyright. Thomas Solomon (Veohtu). All rights reserved.
Icons from Icons8. Photos by Thomas Solomon or from Unsplash.
Follow @veohtu on . Join the club on . Send me an email