Analysis of food and fluid intake in elite ultra-endurance runners during a 24-h world championship | Journal of the International Society of Sports Nutrition

The athletic gut microbiota | Journal of the International Society of Sports Nutrition
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Nature of the event

This study was conducted during the 24-h ultramarathon World Championship held in Albi (France) from October 26–27, 2019. The race consisted of running the greatest distance possible over 24 h (start of the race at 10:00 am the first day). Participants ran on a short loop (1.491 km) combining asphalt (~ 75%) and tartan track (~ 25%) (Fig. 1). The race took place in a mild-to-hot environment, with sunny weather (Fig. 1). The mean dry temperature was 17.4 °C [min-max: 12.2–24.3], wet-bulb temperature 14.2 °C [11.5–17.2], and globe temperature 19.8 °C [11.0–35.1]. The WBGT temperature was 16.0 °C [11.3–23.1]. Relative humidity was 74.0% [47.2–92.7] and the wind speed 0.7 m.s− 1 [0.0–2.7]. All weather measurements were made using a weather station (Kestrel Meter 5400 Heat Stress Meter, Birmingham, MI, USA) near the track at a height of 1.2 m and exposed directly to the sun.

Fig. 1
figure1

Aerial view of the accommodations of the race loop (a) and meteorological conditions (b). Open tents were reserved for open athletes (not selected by national teams). The aerial view was extracted from®Google Maps

Subjects

Twelve French elite athletes (6 men and 6 women) agreed to participate in this study (see Table 1 for characteristics). The study was conducted in accordance with the Declaration of Helsinki and was approved by the regional ethics committee (CPP Ile-de-France 8, France, registration number: 2019-A02445–52, Etude LemuR). The participants’ written informed consent was obtained after they were informed of the purpose and procedures of the study.

Table 1 Participant characteristics

Design

Participants were free to bring their personal food and drink. Energy and the macro- and micronutrient composition of all items were registered in the days before the event. Four participants using self-manufactured foods (less than 10 items in total) were asked to provide their recipes to establish the food composition.

Food and/or drinks were handed out as the participants passed in front of the France team tent (in red in Fig. 1) according to an individual nutritional program provided to the team crew prior to the race. Even if no intake was programmed, food and drinks from their selection were still available on a tray to allow the participant to pick one of them if necessary. Participants were then free to modify their program and ask for unplanned or common foods. Indeed, a selection of food and drinks was available in large amounts for all participants. All consumed food and drinks were registered, along with the amount consumed (in g or ml). To do so, team members used an individual chart displaying programmed items and quantities consumed during the run. When an item was consumed according to the program (i.e. consumed at the intended loop), it was circled. If the quantity differed, it was corrected using a blank column. Finally, when unplanned items were consumed, it was recorded, along with its quantity, in the same blank columns. The same two members of the team were assigned to four participants during the entire race.

The refreshments tent (in blue in the Fig. 1) provided a complementary source of food and drinks, providing mostly water, cake, fruit, and mashed potatoes. Participants were asked to indicate the amounts consumed after the race.

Urine and blood samples were obtained one-day before and immediately after the race for biological analysis (urine and plasma osmolality and sodium concentrations).

Methodology

Food intake

The total food and fluid intake were calculated using spreadsheets (Excel for Office 365, Microsoft, Redmond, WA, USA), a composition table of each food and drink consumed, and the timing of their intake. Foods were separated into soft (all food that did not require chewing) and solid items. Fluids were separated into water and caloric fluids (with energy content). Energy and macronutrient intake were also determined. Relative intake was then calculated. Thus, total energy intake was first split into the nature of the foods (soft and solid foods and caloric drinks) and then into macronutrient intake (carbohydrate, fat, and protein). Finally, sodium and caffeine intake were also calculated.

Energy, carbohydrate, protein, and fluid intake were compared to the latest benchmark recommendations [10]: 150–400 kcal.h− 1 (0.67–1.67 MJ.h− 1), 30–50 g.h− 1, 5–10 g.h− 1, and 450–750 mL.h− 1, respectively.

All food and drinks given to the participants were compatibilized in the calculation. When a bottle was returned unfinished, the unconsumed volume was withdrawn. We did not witness whether the participants consumed all that was handed out. They indicated to us that they ate all that was picked up at the tent. However, it is possible that a small amount was not consumed for multiple reasons (part of the food thrown away with the wrapper, water used to spray themselves, etc.) and this overestimation was hard to assess. Another source of inaccuracy was the accounting of items selected from the refreshments tent. Even if the recollection occurred just after the race, it is possible that the reported amounts diverged slightly from reality. Nevertheless, the amounts of items originating from the refreshments tent were marginal and the degree of imprecision theoretically insignificant.

Energy expenditure

Given the extreme competitive context of the race, participants refused to wear accelerometers, as in the study of Costa et al. [23], or heart rate monitors. An alternative solution was the use of an algorithm based on weight, resting heart rate, and running speed [31] to estimate energy expenditure. The running speed for each participant was retrieved from the organization (https://www.breizhchrono.com/detail-de-la-course/crs_id/13092/ for men and https://www.breizhchrono.com/detail-de-la-course/crs_id/13094/ for women). We acknowledge a certain margin of error, since, in addition to the internal degree of inaccuracy of the algorithm, the impact of accumulated fatigue and weather was not considered by the model. However, it has been shown that running speed is as accurate as heart rate for the assessment of energy expenditure [31].

Symptomology

Each hour, participants were asked by the team physician whether they experienced GIS or other symptoms (e.g. articular or muscular pain). They were informed before the race of the list of GIS (difficulty swallowing, belching, acid reflux, heartburn, nausea, vomiting, abdominal pain, bloating, flatulence, urge to defecate, diarrhea, and constipation) to facilitate the identification of these symptoms during the race. Their occurrence was therefore noted in real-time. A few hours after the race, these observations were cross-checked with the athletes.

Biological measurements

Blood was drawn from the antecubital vein 26 h before the race (between 7:00 and 9:00 am), and within 30-min of finishing. Blood was collected into two separated tubes (Becton Dickinson, Franklin Lakes, USA), one EDTA (5 mL) and one Lithium Heparin (5 mL). Tubes were conserved at 4 °C and plasma was separated within 1 h by centrifugation (2000 x g, 10 min). Participants also provided urine samples at each time point in sterile polypropylene tubes (30 mL).

The presence of urine ketone bodies was detected immediately after collection using a urinary dipstick (Multistix 10 SG Urinalysis, Reagent Strips, Siemens Healthineers, Erlangen, Germany) and a Clinitek Status+ analyzer (Siemens Healthineers, Erlangen, Germany). Four concentrations could be obtained: 0, 5, 15, or 40 mg.dL− 1. Plasma and urinary sodium, potassium, urea, and glycaemia were measured using a Roche Cobas c501 (Roche Diagnostics, Meylan, France). Plasma and urinary osmolality were calculated as follows [32, 33]:

$$ mathrm{Plasma} mathrm{osmolality} left(mathrm{mOsmol}.{mathrm{kg}}^{-1}right)=1.9 mathrm{x} Big(left[{mathrm{Na}}^{+}right]+left[{mathrm{K}}^{+}right]+left[mathrm{glucose}right]+0.5 mathrm{x} left[mathrm{urea}right]+5 $$

$$ mathrm{Urinary} mathrm{osmolality} left(mathrm{mOsmol}.{mathrm{kg}}^{-1}right)=left(2 mathrm{x} left(left[{mathrm{Na}}^{+}right]+left[{mathrm{K}}^{+}right]right)+0.9 mathrm{x} left[mathrm{glucose}right]+0.5 mathrm{x} left[mathrm{urea}right]right) mathrm{x} 0.985 $$

The hematocrit and hemoglobin concentrations were measured (XN-2000, Sysmex, Villepinte, France) and used to estimate alterations of plasma volume [34]. This technique has already been used in a previous 24-h ultramarathon [23].

Statistical analysis

All data are presented as the means ± standard deviation throughout the manuscript. In the text, the range (minimum value – maximum values) is sometimes presented inside brackets and individual data are also displayed in the Figures. Statistical analyses were performed to assess the biological changes between before and after the race. As the data were not normally distributed, according to Shapiro-Wilk tests, we performed Wilcoxon tests for paired data. The level of association between temperature and intake was assessed using Spearman’s rank correlation coefficient (ρ). Significance was defined as p < 0.05. Analyses were performed using STATISTICA software (v10, Statsoft, Tulsa, OK, USA).



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