Running science nerd alert.


by Thomas Solomon PhD and Matt Laye PhD
April 2020.

Each month we compile a short-list of recently-published, Pubmed-indexed, peer-reviewed journal articles that have caught our eye in the world of running science. We then break them into bite-sized chunks so you can digest them as food for thought during your training sessions... Welcome to this month's instalment of our "nerd alert". You can click the title of each article to see the review. Enjoy!
Reading time ~15-mins (3000-words)
or listen to the Podcast version here.
Share this nerd-alert:



Full article available here.
What was the hypothesis or research question? The authors aimed to examine the effect of 7 consecutive days of running on free-living energy intake, appetite hormones, and physical activity energy expenditure in men. There was no stated hypothesis
What did they do to test the hypothesis or answer the research question? Ten healthy and physically-active men (age 22; VO2peak 49 ml/kg/min) started two 7-day experimental conditions in a randomized cross-over design: daily supervised treadmill running (at 70%VO2peak until ~800 kcal had been expended) or no exercise, separated by a 7-day washout period. Energy expenditure was estimated using heart rate-accelerometry (Actiheart). Energy intake was recorded using written and photographic food diaries. At baseline (24 h before the start of each intervention), and 24 h and 70 h after each intervention, subjects consumed a breakfast (of unknown kcal or macronutrient composition after an overnight fast) followed by an ad libitum pasta meal 3-h later. Feelings of appetite were collected and venous blood was sampled to measure two appetite-regulating hormones, acylated ghrelin and total PYY.
What did they find? Total daily estimated energy expenditure from physical activity was significantly higher during exercise vs non-exercise (P < 0.0001; effect size [Cohen’s d] =1.44) due to increased time spent in vigorous activities during the supervised running bouts (P < 0.0001; d=3.49), while time spent in other intensity domains was not different between groups. There was, therefore, no change or difference in physical activity habits between groups. Daily energy intake was higher in the exercise vs. non-exercise group (P = 0.003; d=1.15), compensating for ~60% of the daily exercise-induced energy deficit when compared with the non-exercise group. Body mass was unaffected by either intervention and was not different between interventions. Appetite hormone responses to test meals were unaffected by the interventions and not different between them.
What were the strengths? The sample size was justified using power calculations, a randomised, cross-over design was used, and effect sizes were reported to assess the magnitude of the significant differences. The free-living design helps boost the ecological validity of the findings. Baseline energy intake was replicated during the day prior to the meal test on day 1 and the post-70h test meal.
What were the weaknesses? Free-living studies are tough to control since trust is required between subject and investigator. The study was also very short-term, only 1-week, and used a very small sample size (N=10 but 1 subject dropped out due to illness and only 7 met the minimum "wear time" criteria for the accelerometer). The subjects were also only a homogenous sample of the population - male, young, and healthy; so, the findings do not extrapolate to women, people of other ages, or unhealthy/overweight/inactive folks.
Are the findings useful in application to training/coaching practice? No. Although it would seem that daily running at 70% of VO2peak did not increase energy intake enough to compensate for the increase in energy expenditure and therefore might suggest an acute decrease in energy availability, body weight was unchanged. This combined with the use of heart rate-accelerometry (an estimate of energy expenditure) and diet records (a subjective assessment of energy intake), indicates that not much is going on. Furthermore, a single study of such a small and homogenous sample of people cannot inform a change in practice.

Full article available here.
What was the hypothesis or research question? The authors analyzed the test-retest repeatability of different technologies that measure running power output and validated the measures against oxygen consumption (VO2). This was not hypothesis-driven research.
What did they do to test the hypothesis or answer the research question? Twelve healthy endurance-trained (~7-years) male athletes (age 26, VO2max 61 ml/kg/min) completed 5 testing sessions (familiarization and VO2max test + 2 indoor + 2 outdoor) 48–72 hours apart, in a non-randomised order. Each indoor test day included 3 submaximal treadmill tests with VO2 measurements. The 3 tests were increasing speed (3-min on, 4-min rest, starting at 9 kph, increasing 1 kph/stage until VT2 was reached), increasing weight (3 x 3-min on at 10 kph, 4-min rest, with 0, +2.5, and +5kg weight vest), increasing grade (5 x 3-min on at 10 kph, 4-min rest, at -6%, -3%, 1%, 3%, and 6% grade). The outdoor tests repeated the increasing speed and the increasing weight tests on an outdoor running track. Subjects' habitual cadence was maintained at each test with a metronome. All tests were performed at 4 pm to account for circadian rhythm and under similar environmental conditions. VO2 was measured using breath-to-breath methods. Power was measured using 5 devices: Stryd, Runscribe, Garmin RP, and Polar Vantage V. Standard error of measurement, Bland-Altman analysis of systematic bias, and intraclass correlation coefficients were reported. Linear regression and standard error of the estimate between power and VO2 were measured.
What did they find? The Polar, Garmin, and Runscribe devices performed poorly under all conditions, while the Stryd device performed well. Stryd was the most repeatable technology under changing speed, weight and grade conditions (SEM =7.4 W, CV =2.8 %, ICC=0.980 vs.SEM ≥30, CV≥7, and ICC≤0.71 for the next best device). The relationship between power and VO2 was also greatest for the Stryd device (r=0.911, SEM=7.3% vs. for the next best device) and the relationship was maintained under all conditions ( speed, weight, and grade).
What were the strengths? Very thorough, sensible, and valid study design. Incredibly well controlled. Assessed the reliability and validity of the devices against VO2 measurement at different speeds, weights, and grade (including decline and incline). The authors had no conflict of interest and Stryd nor other manufacturers did not fund or author the study.
What were the weaknesses? Non-randomised order of trials does not account for potential fatigue induced by consecutive sessions in unusual environments. The study did not include trails, hills, muds or mountains.
Are the findings useful in application to training/coaching practice? Although the data cannot be extrapolated to trails and mountains on varied terrain, the Polar, Garmin, and Runscribe devices performed very poorly. In contrast, the Stryde device performed very well and could be recommended for athletes/coaches who want to monitor the training load using power output if they consider it an advatage to traditional methods (RPE, time, etc).

Full article available here.
What was the hypothesis or research question? The authors hypothesized that real-world cardiovascular remodelling in unsupervised, novice marathon runners would be more modest than previously described work involving supervised marathon training.
What did they do to test the hypothesis or answer the research question? Authors conducted a prospective observational study of men and women aged 18-35 who had never previously run a marathon, had a place in the upcoming London marathon and had no preexisting cardiovascular issues. All subjects had a resting echocardiogram, electrocardiography, cardiac-MRI, blood samples, and cardiopulmonary exercise testing using a semi-recumbent tilting cycle ergometer combined with echocardiography. All subjects were also encouraged to follow a "beginner's training plan" for 17-weeks, issued by the London Marathon, but were allowed to use alternative approaches. 128 people were recruited. 28 did not return for follow-up testing, of whom 12 ran the marathon (and did not die). A further 24 could not complete the training due to injury. The final cohort was 68 runners (36 men, 32 women) with repeated-measures ~186-days before and ~16-days after the London Marathon in 2016.
What did they find? There was 78% compliance with the training and the median finish time was 4:30 (range: 2:56– 6:51) and there were no changes in weight, BMI or body fat during the study. VO2max did not change and the % of VO2max at which ventilatory anaerobic threshold occurred decreased (very odd but it was a recumbent bike test and it was conducted many days after a marathon; i.e. lots of fatigue from an unfamiliar load and/or detraining). LV stroke volume and ejection fraction during exercise did not change. CMRI measures of cardiac chambers showed balanced eccentric remodelling and no change in LV or RV ejection fraction. No changes were observed in echocardiographic diastolic function, myocardial strain, peak rotation, twist, or torsion parameters. Aortic pulse wave velocity and peripheral and central BP at rest decreased. Electrocardiography showed no changes in resting heart rate, PR interval, QRS duration, corrected QT interval, or Sokolow–Lyon voltage. I.e. no evidence of myocardial injury.
What were the strengths? Inclusion of "normal" people, i.e. novel runners. They did not exclude subjects who were non-adherent to training plans. This was an intent-to-treat analysis to add greater validity to the outcomes. They included only those aged 18-35 to exclude possible occult atherosclerotic coronary artery disease since this age-group is the least likely to have underlying atherosclerosis in their coronary arteries. The authors had no conflict of interests. London Marathon did not fund or author the study.
What were the weaknesses? Detailed training information was missing from many subjects. Lack of treadmill exercise testing. No control groups, so outcomes may be confounded by lack of training and/or seasonal variation.
Are the findings useful in application to training/coaching practice? No. The absolute mortality rate (death from sudden cardiac arrest) during marathons is very low (1 per 100,000 people). These new findings confirm that we can continue not discouraging people from running marathons unless they have pre-existing and unmanaged cardiac problems.

Full article available here.
What was the hypothesis or research question? Researchers wanted to characterize muscle glycogen usage in two different muscles (Vastus Lateralis [thigh] and Gastrocnemius [calf]) in response to 3 different common running workouts (long tempo, 3 x 10 minute at "threshold", and 8 x 800 at VO2max) in males and females. No specific hypothesis was stated.
What did they do to test the hypothesis or answer the research question? They had a preliminary testing session to determine lactate threshold and VO2max for the interval sessions. They controlled for the menstrual cycle timing in women (one workout each month at the same time of the month). All runners were recreational (< 45 min 10 k for men and 50 min 10k for women). They controlled for diet and muscle glycogen levels in the 48 hours prior to the workout by having them complete a glycogen depletion workout, then consume a high carbohydrate diet. Runners then completed one of the workouts in a randomized fashion. Pre and post-workout biopsies were taken from the same leg and muscle glycogen utilization was measured.
What did they find? Resting glycogen levels were lower in women’s gastrocnemius, but not vastus lateralis, compared to men. Men had higher levels of glycogen in their gastrocnemius versus the vastus lateralis. In men, total usage was higher in the 10-mile tempo run compared to the 3 x 10 min or 8 x 800 workouts in both muscle types, with no differences between muscle types. In the 10-mile tempo run, men used more glycogen than women, but there were no differences in the other workouts. In women, more muscle glycogen was used in the gastrocnemius relative to the vastus lateralis. The rate of glycogen usage (compared to the absolute amount) was higher in the 8 x 800 workout compared to the other workouts.
What were the strengths? All workouts were outdoors in real-world conditions. Steps were taken to be sure starting glycogen was similar in each trial, including a depletion and controlled repletion of glycogen protocol before each workout.
What were the weaknesses? Carbohydrate loading was done per kg bodyweight weight so the women received less absolute carbohydrate during the standardization period. The outside exercise may have variables that would be different (temp, wind, etc) between trials. Testing between trials was sometimes weeks apart (28 days apart for women).
Are the findings useful in application to training/coaching practice? Possibly. The findings indicate that women may need more relative carbohydrate intake following workouts than men. Glycogen use was not important for females whether the workout was time-based (3 x 10 minutes) or distance based. After a glycogen depletion workout, 2 days of 6 g/kg of carbohydrate intake was sufficient to fuel up for each of these harder sessions regardless of gender, since all runners completed the workouts easily. Longer tempo runs will deplete carbohydrate to a greater degree than the harder shorter track sessions and may need more recovery in between them.

Full article available here.
What was the hypothesis or research question? It is known that plyometric training can increase running economy (and leg stiffness), but the authors wanted to see whether a SINGLE plyometric bout could improve running economy. A secondary comparison was to look at how plyometrics compared to weighted vest strides, which is a training intervention known to increase running economy.
What did they do to test the hypothesis or answer the research question? 12 runners with low VO2max (38 ml/kg/min) completed three different interventions. The control (6 x 10s strides), plyometric (2x8 square jump, 2x8 scissor jump, 2x8 double leg bounds), and resistance warm-ups (6 x 10s strides with 20% of bodyweight vest) were used in a counterbalanced crossover design with 48 hours separating them. Runners had their leg stiffness measured by a force plate while completing a vertical jump, asked how ready they felt prior to the running test, and then completed 3-minute stages at 7,8,9,10 km/h to measure their running economy, followed by a test to exhaustion.
What did they find? At every speed, VO2 (ml/min/kg) was lower and thus the running economy (VO2/km) was higher in the plyometric group compared to the resistance or control group (effect sizes [ES] = 0.3 - 0.5 for each speed) with no changes in RER or RPE. Leg stiffness was higher in the plyometric and strength groups compared to the controls (ES = 0.54 and 0.76 respectively). No difference in time to exhaustion between any conditions. Interestingly there was NO CORRELATION between leg stiffness changes and changes in submaximal VO2, suggesting that leg stiffness is not responsible for the changes in running economy in this study.
What were the strengths? A counterbalanced and cross over design.
What were the weaknesses? Studying recreational runners without the running history of someone who might be doing a bunch of other things to increase stiffness in the legs. Not clear how the change in VO2 occurred if not associated with leg stiffness. No control for diet (even though respiratory exchange ratios were the same). Warm-up times were slightly different between conditions.
Are the findings useful in application to training/coaching practice? Yes. Having athletes perform plyometrics regularly is a VERY good thing. The best time to do those might be right before your workout or even race. It's possible that the weight vest strides may work as well in populations other than the one used here but further work is required.

Full article available here.
What was the hypothesis or research question? Is a difference in exogenous carbohydrate use depending on the pattern of drinking a carbohydrate solution? Is there an optimal drink frequency and volume relationship?
What did they do to test the hypothesis or answer the research question? Two trials, each lasting 100 minutes at an intensity of 70% of VO2max were completed by well-trained runners. 1 Litre of fluid was consumed at a rate of either 50 mL every 5 minutes or 200 mL every 20 minutes. The researchers used [U13C]-glucose in the drink, a stable non-radioactive isotope that is chemically identical but physically distinct to normal glucose which allows scientist to “trace” where ingested fuel goes and how it is used in the body. The authors also collected expired breath and venous blood samples to compare endogenous and exogenous carbohydrate use. In addition, researchers examined gastrointestinal symptoms in each trial.
What did they find? The major finding was a 23% increase in exogenous carbohydrate oxidation in the 200 mL every 20-minute group relative to the 50 mL/5 min group. Total and endogenous carbohydrate oxidation were not significantly different but, according to my calculation, there was a moderate effect size of 0.64 for exogenous carbohydrate and 0.32 for endogenous carbohydrate oxidation, suggesting potential for lower carbohydrate oxidation in the 200 mL per 20 min group if more subjects had been studied.
What were the strengths? Tracers enable the examination of real-time metabolite kinetics. Well trained runners.
What were the weaknesses? Tracer kinetics calculations rely on a number of biological assumptions.
Are the findings useful in application to training/coaching practice? I would tell runners not to worry if they are unable to "sip" a carbohydrate drink and instead focus on a bolus. The findings might also be true for GELs - a bolus of GEL rather than “sipping” a fluid is fine, but the practicalities of carrying fuel during an event should be considered on a case-by-case basis.


That is all for this month's nerd alert. If you are interested in the entire list of papers we perused, you can download the text file here. 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.
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, 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 where they were both research scientists at the Centre for Inflammation and Metabolism at Rigshospitalet (Copenhagen University Hospital). After discussing lots of science during 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 2023. Thomas Solomon. All rights reserved.
Icons from Icons8. Photos by Thomas Solomon or from Unsplash.
Follow @thomaspjsolomon on . Follow @veohtu . Join the club on . Send me an email