International Journal of Sport Nutrition and Exercise Metabolism, 2014, 24, 497 -506 http://dx.doi.org/10.1123/ijsnem.2013-0169 © 2014 Human Kinetics, Inc
www.IJSNEM-Journal.com ORIGINAL RESEARCH
Energy Balance, Macronutrient Intake, and Hydration Status During a 1,230 km Ultra-Endurance Bike Marathon Bjoern Geesmann, Joachim Mester, and Karsten Koehler German Sport University Athletes competing in ultra-endurance events are advised to meet energy requirements, to supply appropriate amounts of carbohydrates (CHO), and to be adequately hydrated before and during exercise. In practice, these recommendations may not be followed because of satiety, gastrointestinal discomfort, and fatigue. The purpose of the study was to assess energy balance, macronutrient intake and hydration status before and during a 1,230-km bike marathon. A group of 14 well-trained participants (VO2max: 63.2 ± 3.3 ml/kg/min) completed the marathon after 42:47 hr. Ad libitum food and fluid intake were monitored throughout the event. Energy expenditure (EE) was derived from power output and urine and blood markers were collected before the start, after 310, 618, and 921 km, after the finish, and 12 hr after the finish. Energy intake (EI; 19,749 ± 4,502 kcal) was lower than EE (25,303 ± 2,436 kcal) in 12 of 14 athletes. EI and CHO intake (average: 57.1 ± 17.7 g/hr) decreased significantly after km 618 (p < .05). Participants ingested on average 392 ± 85 ml/hr of fluid, but fluid intake decreased after km 618 (p < .05). Hydration appeared suboptimal before the start (urine specific gravity: 1.022 ± 0.010 g/ml) but did not change significantly throughout the event. The results show that participants failed to maintain in energy balance and that CHO and fluid intake dropped below recommended values during the second half of the bike marathon. Individual strategies to overcome satiety and fatigue may be necessary to improve eating and drinking behavior during prolonged ultra-endurance exercise. Keywords: energy expenditure, energy intake, dehydration, carbohydrates, urine specific gravity Ultra-endurance cycling events are considered to be among the largest physiological challenges (Hulton et al., 2010). In recent years, races such as the Race Across America, Trondheim-Oslo and Paris-Brest-Paris (PBP) have become increasingly popular. PBP, which is the world’s largest bicycle marathon in terms of participation, covers a distance of 1,230 km and accumulates about 10,000 m in elevation gain. The successful participation in such extreme events greatly depends on adequate nutrition and hydration strategies (Black et al., 2012; Jeukendrup, 2011). It is considered essential that athletes ingest sufficient energy from food and fluid to compensate the high energy expenditure (EE) of ultra-endurance exercise (Jeukendrup, 2011; Rehrer, 2001). Consequently athletes are advised to maintain energy balance so as not to compromise their endurance performance (American Dietetic Association; Dietitians of Canada et al., 2009). Not only energy intake (EI), but also macronutrient composition plays an important role, with carbohydrates
Geesmann and Koehler are with the Institute of Biochemistry, and Mester the Institute of Training Science and Sport Informatics, German Sport University, Cologne, Germany. Address author correspondence to Karsten Koehler at k.koehler@psu. edu.
(CHO) being the most important component of EI. During prolonged exercise, fatigue is often associated with a depletion of muscle glycogen stores and reduced blood glucose levels and it has been shown that providing exogenous CHO may help to stabilize blood glucose levels and positively affect endurance performance (Jeukendrup, 2011). Controlled laboratory experiments have established that the oxidation rate of exogenous CHO increases linearly with increasing exercise intensity until approximately 50 to 60% of VO2max (Jeukendrup & Jentjens, 2000). At higher exercise intensities, intestinal CHO absorption seems to be limited, and consequently the oxidation rate of exogenous CHO plateaus at approximately 90 g/hr (Burke et al., 2011; Jeukendrup et al., 2006). Hence, a CHO intake of 60 to 90 g/hr in the form of multiple transportable CHO is recommended for endurance events lasting longer than 2.5 hr to maximize exogenous CHO oxidation and to prevent glycogen depletion (Jeukendrup, 2011; American Dietetic Association; Dietitians of Canada et al., 2009). Dehydration may also impair athletic performance during prolonged exercise (Jeukendrup, 2011; Sawka & Noakes, 2007; American College of Sports Medicine et al., 2007). General hydration recommendations include 1) to start exercise in a euhydrated state and 2) to drink adequately to avoid dehydration by more than 2 to 3% of the initial body weight (Jeukendrup, 2011; American College of Sports Medicine et al., 2007; Rehrer, 2001). 497
498 Geesman et al.
The American College of Sports Medicine recommends a fluid intake of 400 to 800 ml/hr during exercise, but states that drinking strategies should be adjusted individually to sweat rates and exercise duration (American College of Sports Medicine et al., 2007; Jeukendrup, 2011; Sawka & Noakes, 2007). During ultra-endurance exercise, these generalized recommendations may not be applicable and may even compromise each other. First, a CHO intake of 60 to 90 g/hr limits EI to about 250 to 380 g/hr, so that other macronutrients are required to maintain energy balance. Second, the provision of sufficient energy and fluid as recommended could lead to satiety and gastro-intestinal discomfort. Even though fluid can be used to provide energy in form of CHO, it should be considered that gastric emptying and fluid uptake may be impaired when the CHO content exceeds 6% (Pfeiffer et al., 2012). Consequently, CHO intake may be limited to 24 to 48 g/ hr when fluid intake is as recommended. Most scientific reports on nutrition and hydration practices during ultra-endurance events are single case studies (Knechtle et al., 2005; Bircher et al., 2006) or studies with a limited sample size (Hulton et al., 2010), which makes it difficult to summarize reported data on energy balance and hydration status, especially when considering that the magnitude of interindividual differences is unknown. The purpose of the current study was to assess components of energy balance (EI, EE), macronutrient intake, and hydration status (urine specific gravity (USG), hematocrit, hemoglobin, changes in plasma volume) during the bike marathon PBP to evaluate changes over the course of the marathon and to compare food and fluid intake to available recommendations. A secondary goal was to assess interindividual differences in these components in a group of equally trained cyclists. We hypothesized that 1) food and fluid intake would decrease over the course of the event, that 2) the athletes would not be able to remain in energy balance and in a euhydrated state, and that 3) the athletes would fail to meet recommendations for CHO and fluid intake.
Methods The Bike Marathon The study was performed around the 2011 edition of the bicycle marathon Paris-Brest-Paris, which was started on August 22nd at 4:00 PM. PBP is organized as a socalled brevet, which implies that riders can ride alone or in groups but are required to finish within defined time limits. For the 2011 edition of PBP, the riders were allowed a maximum of 86 hr to complete the 1,230-km course. During the event, participants passed a total of 14 control stations, where time was recorded and food and drinks were available ad libitum. Supporting crews were not allowed on the official route, so that riders had to carry all food and fluid for the sections between control stations in their jersey pockets or in bottles at the bike.
The participants did not plan to sleep during the marathon. Temperature varied between 18.5 and 41.0°C and relative humidity was between 55 and 80%.
Participants Eighteen well-trained male amateur athletes volunteered to participate in this study. Volunteers were recruited from a training group which participated in a commercial training program for ultra-endurance events. All participants provided written informed consent and the investigation was approved by the ethical review board of the German Sports University. All participants were without medical illness and did not take any medication at the time of the screening visit or the bike marathon.
Screening Visit Within 6 weeks before the marathon, participants completed a screening visit to the laboratory, which included: 1) informed consent, 2) anthropometrical measurements, and 3) a preliminary performance test. The performance test was conducted on a stationary bicycle ergometer (SRM, Jülich, Germany) and served to determine maximal oxygen uptake (VO2max) and to assess the individual relationship between power output (in W) and EE (in kcal/ min). After resting in a sitting position on the ergometer for 3 min, the test was initiated at 100 W and power output was increased stepwise by 50 W every 4 min. After completion of the 250 W step, power output was increased by 25 W every 30 seconds until a plateau in oxygen uptake was observed despite a further increase in workload. During the test, EE was assessed by indirect calorimetry (ZAN 600, nSpire Health, Inc., Colorado, USA) using the Weir equation (Weir, 1949).
Measurements During the Event Body weight and body fat was measured the morning before the start of the marathon following an overnight fast and again immediately after the finish. A Tanita BC-545 (Tanita, Hoofddorp, Netherlands) was used to assess body weight to the nearest 0.01 kg. Percentages of body fat were assessed by calipermetry (Baty International, West Sussex, UK) using the 10-point-method (Allen et al., 1956). Urine and capillary blood samples were collected the morning before the start, at control stations after 310, 618, and 921 km, immediately after the finish and following a recovery period of approximately 12 hr. Urine samples collected before the start and after the 12-hr recovery period presented first morning void urine samples, while all other samples presented spot urine samples. Urine samples were frozen immediately for convenience and USG was subsequently analyzed with a DMA 38 density meter (Anton Paar, Graz, Austria). Based on USG, participants were categorized as adequately hydrated ( 1.030 g/ml; Armstrong, 2005; Shirreffs, 2003; Kavouras, 2002).
Energy and Hydration Status During Ultra-Endurance Exercise 499
Capillary blood samples were centrifuged and directly analyzed for hematocrit and hemoglobin concentrations (QBC Diagnostics, Inc., Port Matilda, PA, USA). Changes in plasma volume (ΔPV) were calculated according to Dill & Costill (1974). Unfortunately, because of a centrifuge malfunction, no values could be obtained for the samples collected after the finish. All riders were equipped with an SRM system (SRM, Jülich, Germany) to assess power output continuously throughout the bike marathon. Power output was averaged over 1-minute intervals and subsequently converted to EE, using the individual relationship determined during the screening visit. For intervals with an average power of 0 W and for all resting periods, EE was defined as resting EE measured during the 3-minute rest period at the start of the performance test during the screening visit. Dietary intake was recorded continuously for each individual athlete by trained staff. The macronutrient content of food was obtained from the manufacturer’s information or from the Federal German Nutrient Database (Bundeslebensmittelschluessel, Version II.4).
Results Participants Four athletes were forced to terminate the bike marathon before reaching the finish because of issues unrelated to the present investigation (orthopedic complications (n = 2), exhaustion (n = 1), and heatstroke acquired before the start (n = 1) and were excluded from the subsequent analysis. The 14 successful participants were 43.6 ± 7.8 years of age, 180.1 ± 6.2 cm tall, weighted 74.1 ± 6.8 kg and had a maximal oxygen uptake (VO2max) of 63.2 ± 3.3 ml/min/kg.
Bike Marathon The participants rode together as a closed group over the whole course and finished the bike marathon after 54 hr, with a net cycling time of 42 hr and 47 min. Average velocity and power output declined significantly between the first and second and between the second and third section (P = .001; Table 1).
Statistics
Energy Balance
For data analysis, the bike marathon was divided into four sections based on stops at control stations after 310 km (end of section 1), 618 km (section 2), and 921 km (section 3), and the finish (section 4). Statistical analyses were performed with SPSS (version 21, IBM, New York, USA). If not reported otherwise, data are presented as mean ± standard deviation and ranges (min, max). Data were tested for normality using the Kolmogorov-Smirnov test. For comparisons between time points, analysis of variance with repeated measures was applied and a t test served as post hoc test. The level of significance was set at p < .05. For pairwise multiple comparisons, the level of significance was adjusted by Bonferroni’s correction. Spearman’s correlation coefficient was determined for correlation analyses.
Mean EI throughout the event was 19,749 ± 4,502 kcal and individual values ranged from 13,657 kcal to 28,395 kcal (Figure 1). When expressed as kcal per 24h, the average EI was 8,777 ± 2,001 kcal/24h. EI increased significantly from the first section (4,733 ± 1,136 kcal) to the second section (6,093 ± 1,838 kcal; P = .042), but decreased significantly between the third section (5,601 ± 1,081 kcal) and the last section (3,322 ± 1,564 kcal; P = .001). The cyclists derived 15,634 ± 4,310 kcal (range: 10,676 kcal—26,005 kcal) from solid foods sources (79 ± 9%) and 4,115 ± 1,851 kcal (range: 2,234 kcal—8,147 kcal) from liquids (21 ± 9%). In average, EE throughout the event was 25,303 ± 2,436 kcal and ranged from 21,801 kcal to 30,567 kcal
Table 1 Race Data Separated in the Four Sections (km 0–310, 311–618, 619–921, 922–1,230) and Overall Section 1 Distance [km]
Section 2
Section 3
Section 4
Overall
310
308
303
309
1,230
Cycling time [hr:min]
10:11
10:32
11:17
10:47
42:47
Rest [hr:min]
00:43
02:02
05:34
02:54
11:13
Total time [hr:min] Average power output [W] Average Intensity [% VO2max] Velocity [km/h]
10:54
12:34
16:51
13:41
54:00
149.5 ± 11.7
138.3 ± 11.2**
127.4 ± 13.9††**
126.1 ± 20.7**
135.4 ± 13.0
45.4 ± 5.5
42.0 ± 4.8
41.0 ± 3.8
40.5 ± 5.4
43.6 ± 4.4
30.4
29.2**
26.8††**
28.7##**
28.7
**Significantly different from section 1 (p < .001). ††Significantly different from section 2 (p < .001). ##Significantly different from section 3 (p < .05).
500 Geesman et al.
(Figure 1). When expressed as kcal per 24h mean EE was 11,246 ± 1,083 kcal/24 hr (range: 9,689 to 13,585 kcal/24h). Average energy balance was -5,554 ± 4,567 kcal, but individual energy balance ranged from -11,859 kcal to 3,593 kcal (Figure 1). When expressed as kcal per 24 hr, energy balance was -2,468 ± 2,030 kcal/24 hr (range: -5,271 to 1,597 kcal/24/hr). EI was the main significant predictor of energy balance (r = .93, p < .001). Energy balance was also highly correlated with EI from solid foods (r = .86; p < .001; Figure 2) Body weight did not change significantly over the course of the event. Average weight loss was 0.1 ± 1.4 kg and individual weight changes ranged from –1.9 kg to 2.4 kg. Fat mass decreased significantly (p = .001) by 0.9 ± 0.5 kg (range: 0.3 kg to 1.9 kg). Fat-free mass increased
significantly (p = .039) by 0.8 ± 1.3 kg (range: –1.4 to 3.0 kg). Changes in body weight (r=-0.45, p = .47) and fat mass (r = .42, P = .50) were not significantly correlated with energy balance.
Macronutrient Intake The largest proportion of energy was provided from CHO (57.5 ± 5.8%), when compared with fat (29.3 ± 4.0%) and protein (13.2 ± 2.0%). In total, the cyclists consumed 3,011 ± 525 g of CHO, which accounted for a total of 40.7 ± 8.5 g/kg BW. When expressed as g/hr mean CHO intake was 57.1 ± 17.7 g/hr. Total protein intake was 705 ± 213 g (9.6 ± 3.2 g/kg BW) and fat intake was 691 ± 179 g (9.4 ± 2.7 g/kg BW). CHO intake (Figure 3) increased significantly from section 1 (10.2 ± 2.4 g/kg BW) to section 2 (12.5 ± 3.2
Figure 1 — Individual data for energy intake, energy expenditure and resulting energy balance in the 14 bicyclists
Figure 2 — Association between energy intake from solid foods (left) and the energy intake from liquid foods (right) with energy balance
Energy and Hydration Status During Ultra-Endurance Exercise 501
Figure 3 — Macronutrient composition in g/kg BW (top) and in % of energy intake (bottom) over the course of the race. *Significantly different from section 1 (p < .05); †,††,†††: significantly different from section 3 (p < .05, p < .01, p < .001).
g/kg BW; p = .022) and decreased from section 3 (11.5 ± 2.7 g/kg BW) to section 4 (6.5 ± 2.4 g/kg BW; p < .001). Likewise, protein and fat intake increased from section 1 (protein: 2.2 ± 0.8 g/kg BW; fat: 2.1 ± 0.7 g/kg BW) to section 2 (protein: 3.0 ± 1.3 g/kg BW, p = .042; fat: 2.8 ± 1.1 g/kg BW, p = .038) and decreased from section 3 (protein: 2.6 ± 0.7 g/kg BW; fat: 2.6 ± 0.8 g/kg BW) to section 4 (protein: 1.7 ± 1.0 g/kg BW, p = .007; fat: 1.9 ± 0.9 g/kg BW, p = .014).
Fluid Intake and Hydration Status The participants ingested a total of 21,186 ± 4,586 ml fluid (range: 13,422 ml—28,065 ml) during the event, which corresponds to 392 ± 85 ml/hr (range: 249 ml/ hr—520 ml/hr). Fluid intake was not significantly associated with EI from liquid sources (r = .11, p = .70). Following an insignificant increase from the first section (473 ± 108 ml/hr) to the second section (506 ± 165 ml/ hr), mean fluid intake decreased significantly in the third section (333 ± 95 ml/hr; p = .017). The further reduction in the fourth section (297 ± 91 ml/hr) was not significant. On the morning before the start, participants exhibited a mean hematocrit of 49.6 ± 3.1% and a mean hemo-
globin of 16.6 ± 0.9 mg/dl (Figure 4). Between sections 2 and 3, there was a significant reduction in hematocrit (51.5 ± 4.2% to 48.5 ± 3.4%; P = .023) and hemoglobin (17.0 ± 1.2 g/dl to ; 16.1 ± 1.4 g/dl; P = .045). Following the 12-hr recovery period, hematocrit and hemoglobin were further reduced when compared with the end of the third section (hematocrit: 45.5 ± 2.3%; p = .006; hemoglobin: 15.2 ± 0.9 g/dl; p = .018). Average changes in plasma volume ranged from –0.5 ± 4.0 to 1.3 ± 4.7% and there was no clear trend in plasma volume over the course of the bike marathon. Despite small average changes in plasma volume, interindividual changes varied between -5.3 and 11.6%. USG on the morning before the start was 1.022 ± 0.010 g/ml (range: 1.004 g/ml to 1.035 g/ml). Over the course of the bike marathon, USG declined continuously but not significantly to 1.018 ± 0.007 g/ml (range: 1.004 g/ml to 1.028 g/ml) after the end of the third section. Immediately after the finish, the riders exhibited a mean USG of 1.021 ± 0.008 g/ml (range from 1.004 g/ml to 1.036 g/ml). After the 12-hr recovery period, USG was in the range of the values before the event (1.022 ± 0.005 g/ ml; range from 1.014 g/ml to 1.028 g/ml). There were no significant differences in USG between any time points. Based on the aforementioned criteria for USG, six cyclists were considered mildly dehydrated and three cyclists were considered severely dehydrated on the morning before the start. The lowest number of dehydrated riders was noted after the third section (seven riders mildly dehydrated, no rider severely dehydrated). After the finish, seven riders were classified as mildly dehydrated and one rider as severely dehydrated. Following the 12-hr regeneration period, nine riders were classified as mildly dehydrated based on their USG. Changes in USG were not significantly correlated with fluid intake (r = .09, p = .77) and EI from liquid sources (r = .18, p = .55).
Discussion The current study underlines the extreme physiological burden to the human body while participating in ultraendurance cycling events. Our results show a considerable decline in ad libitum food and fluid intake during the second half of the marathon. Consequently, participants were not able to remain in energy balance and failed to meet recommendations for CHO (60 to 90 g/hr) and fluid intake (400 to 800 ml/hr) during the second half of the bike marathon. Hydration status was suboptimal in a considerable number of participants already at the morning of the start, but did not appear to worsen during the event.
Energy Intake and Energy Balance On average, energy balance was –5,554 ± 4,567 kcal. The standard deviation of 4,567 kcal (CV = 82%) indicates that energy balance varied considerably between individual participants. Twelve riders were not able to
502 Geesman et al.
Figure 4 — Hematocrit (top left), hemoglobin (top right), changes in plasma volume (bottom left) and urinary specific gravity (bottom right) over the course of the race. *Significantly different from section 3 (p < .05); †,††: significantly different from section 4 (p < .05, p < .01).
match their EE, whereas two riders were in a positive energy balance. Differences in energy balance were primarily caused by interindividual differences in EI, as the riders with a positive energy balance also had the highest reported EI (26,981 kcal; 28,395 kcal). EI declined significantly after the first half of the marathon, so that the energy deficit was primarily attained during the second half. For the first section, an average energy deficit of 1,523 ± 1,012 kcal was determined, but it has to be considered that food and drinks before the start were not accounted for our calculations. In the second section, the participants were able to meet their EE (energy balance: -137 ± 1716 kcal). Potential reasons for the reduction in EI during later sections of the event will be discussed below, because they are likely identical to reasons for the reduction in CHO and fluid intake. The overall negative energy balance is in agreement with the loss of fat mass of 0.9 ± 0.5 kg accounting for approximately 6,900 kcal. However, several methodological limitations have to be considered when evaluating changes in body weight and composition during the current study. First, it has to be taken into account that body weight and body composition before the start were assessed following an overnight fast, while measure-
ments after the marathon were taken immediately after the finish, so that recently ingested food or drinks might have increased weight. Second, fluid shifts associated with an increase in total body water, which have been reported following ultra-endurance events in other studies (Knechtle et al., 2011; Noakes et al., 2005), might have led to an overestimation of fat-free mass. It has been argued that the increase in body water is caused by increased extracellular sodium and elevated aldosterone levels and that it acts to maintain the body’s circulating blood volume to perfuse all organs (Knechtle et al., 2011). In the current study, fat-free mass increased by 0.8 ± 1.3. kg over the course of the marathon. When comparing energy balance during the current study with data from similar events, it has to be considered that energy requirements largely depend on the length of the event. For the RAAM (approximately 4, 800 km), Hulton et al. (2010) assessed the EE in four athletes who competed for 12 hr/day. Daily EI (4,918 ± 810 kcal) and EE (6,420 ± 470 kcal) were approximately half of the values reported in the current study (EI: 8,777 ± 2,001 kcal/24 hr; EE: 11,246 ± 1,083 kcal/24 hr). Knechtle et al. (2005) assessed an EI of 9,612 ± 1,500 kcal/d and an EE of 17,965 ± 2,165 kcal/d in a single case
Energy and Hydration Status During Ultra-Endurance Exercise 503
study, which was substantially higher than our values and also more than twice the values reported by Hulton et al. (2010). It should be considered that Knechtle et al. (2005) used continuous heart rate monitoring to assess EE which is associated with errors up to 30% (Ainslie et al., 2003), whereas Hulton et al. (2010) measured EE with the gold-standard method of doubly labeled water (Ainslie et al., 2003).
Macronutrients The largest proportion of energy was provided from CHO (57.5 ± 5.8%), but CHO intake decreased in the last section of the event in terms of absolute (in g/kg) and relative intake (in % of EI). The ratio between CHO and protein remained fairly stable, whereas the reduction in relative CHO intake in the last section was associated with an increase in fat intake. During the bike marathon, mean CHO supply was 57.1 ± 17.7 g/hr, which is only slightly below the recommendation of 60 to 90 g/h for events lasting longer than 2.5 hr (Jeukendrup, 2011; American Dietetic Association; Dietitians of Canada et al., 2009). The participants were able to meet the recommendations during the first half of the event (section 1: 69.0 ± 12.8 g/h, section 2: 73.6 ± 17.9 g/hr), but CHO intake dropped significantly in the second half and fell below 60 g/hr (section 3: 50.5 ± 10.6 g/hr, section 4: 35.2 ± 12.1 g/hr). Providing exogenous CHO may help to maintain and stabilize blood glucose concentrations, delay muscle glycogen depletion and fatigue, and improve endurance performance (Burke et al., 2011; Jeukendrup, 2011). However, it has been shown that the oxidation of exogenous CHO during exercise is limited to approximately 90 g/h, even when multiple transportable CHO are used to maximize intestinal absorption (Burke et al., 2011; Pfeiffer et al., 2010; Jeukendrup et al., 2006). Because an increase in CHO intake above 90 g/hr has been associated with an increased likelihood of gastrointestinal distress (Pfeifer et al., 2012; Jeukendrup, 2011), a CHO intake of 60 to 90 g/h is typically recommended for endurance exercise lasting longer than 2.5 hr (Burke et al., 2011; Jeukendrup, 2011). In the current study, participants were able to maintain their CHO in the range of the recommendations for the first half of the marathon, which they completed in 20 hr 43 min, without reporting gastrointestinal symptoms. The reduction in CHO intake, which was associated with a reduction in food intake, was not related to gastrointestinal discomfort. This shows that it is possible to tolerate 60 to 90 g of CHO per hr for prolonged periods of exercise and that gastrointestinal distress does not seem to be a factor that limits CHO intake during ultra-endurance exercise when CHO intake is kept within the range of the recommendation. However, it remains questionable whether CHO recommendations are appropriate for prolonged ultraendurance exercise as reported in the current study. Studies in which the maximal oxidation rates of 60 to
90 g/hr were established were conducted at exercise intensities between 51 and 64% of VO2max at exercise durations between 2 and 5 hr (Jeukendrup et al., 2006; Jeukendrup & Jentjens, 2000). During the current study, exercise intensity was slightly lower (43.6% of VO2max), but exercise duration was much longer (54 hr). van Loon et al. (1999) reported an oxidation rate of only 43 g/hr for exogenous CHO at an exercise intensity of 40 to 45% of VO2max in trained cyclists, but it should be considered that the study was not designed to maximize exogenous CHO oxidation (van Loon et al., 1999). Endogenous CHO was contributed at a rate of 52 g/hr to a total CHO oxidation rate of 95 g/hr at 40 to 45% of VO2max in trained cyclists (van Loon et al., 1999). Considering that CHO oxidation remains stable during prolonged ultra-endurance exercise (Jeukendrup et al., 2006), a CHO intake closer to total CHO oxidation might help to prevent premature depletion of muscle and liver glycogen stores. However, future studies investigating CHO oxidation rates at exercise durations greater than 5 hr are necessary to refine CHO recommendations for ultra-endurance exercise. When CHO are used as the sole source of energy as recommended (60 to 90 g/h), EI is limited to 250–380 kcal/h. Without an adequate intake of fat and protein, this will result in an accumulated energy deficit, which could compromise performance during ongoing exercise. In the current study, CHO intake accounted for 57% of total EI, which is in the range of values reported for the team-event of RAAM (56 to 64%, Hulton et al., 2010). Higher relative CHO intakes (70 to 75% of EI) have been reported in single-case studies during the RAAM and the Race Across the Alps (Knechtle et al, 2005; Bircher et al, 2006 and in bike races of shorter duration (Black et al., 2012; Bescós et al., 2012). Consequently, fat intake in the current study (29.3 ± 4.0%) was considerably greater than fat intake reported in other ultra-endurance events. In most studies, fat intake was in the range between 14 and 17% of total EI (Bescós et al., 2012; Hulton et al., 2010; Bircher et al, 2006; Knechtle et al., 2005). To our knowledge, only limited literature data are available to which extent the ingestion of other macronutrients impacts the absorption and oxidation of exogenous CHO. Fat supplementation during exercise was not found to attenuate CHO oxidation (Jeukendrup et al., 1996, 1998), but it has been argued that increased fat or protein ingestion during exercise may be associated with gastrointestinal discomfort (Jeukendrup, 2011; Jeukendrup et al., 1998; Jeukendrup et al., 1996). However, exercise intensity during the present event (43.6% VO2max) was lower than exercise intensities in studies that have reported gastrointestinal discomfort (60% VO2max, Jeukendrup et al., 1998; 57% VO2max, Jeukendrup et al., 1996). Interestingly, one of the participants who was able to maintain in energy balance during the event increased his fat intake to 20.7 g/hr during the last section of the marathon without reporting gastrointestinal discomfort. Further research is needed to assess how CHO oxidation and gastrointestinal discomfort are impacted by the ingestion of other macronutrients to establish recom-
504 Geesman et al.
mendations for fat and protein intake during prolonged ultra-endurance exercise.
Fluid Intake and Hydration Status In average, the participants consumed 392 ± 85 ml/hr of fluid throughout the event. Fluid intake varied to a much lesser degree between individuals than EI (coefficient of variation: 22%). Whereas the participants were able to meet the recommendation of 400 to 800 ml/hr in the first half of the marathon, fluid intake decreased significantly in the second half and fell below the recommendations. Despite the considerably low fluid intake especially in the second half of the marathon, we observed no increase in dehydration as indicated by changes in plasma volume, hematocrit, hemoglobin, and USG. In addition, we did not find a correlation between fluid intake and changes in hydration status during the event. Consequently, it can be assumed that our participants had established individual drinking regimens that allowed them to maintain in fluid balance without excessive over- or under-drinking. To our surprise, USG indicated that the majority of the riders were not adequately hydrated before the start. Because hydration status did not worsen further during the event, it may be possible that dehydration was not a performance-limiting factor during the present event. However, it has to be taken into account that the USG before the start was determined from morning first void urine, approximately 8 hr before the start. Even though morning first void urine USG is considered a valid indicator of hydration status (Armstrong, 2005; Shirreffs, 2003), it is possible that athletes improved their hydration status in the hours before the start. For a better description of the hydration status, the assessment of individual sweat rates and fluid losses would have provided additional information. However, the assessment of sweat losses using changes in body weight would have interfered with changes in body mass due to excessive substrate use during prolonged exercise (Armstrong, 2005). Other studies have reported slightly higher fluid intake (530 to 670 ml/hr), but also no increased incidence of dehydration based on plasma volume changes and USG during other ultra-endurance events (Neumayr et al., 2003, 2005; Rüst et al., 2012). Unfortunately, we did not assess the underlying causes for the reduction in food and fluid intake during the second half of the event systematically. Based on anecdotic reports, three major reasons were identified: 1) the participants felt saturated because of the large amounts of food and drinks ingested during the previous hours of exercise, 2) the participants reported feelings of sensory-specific satiety due to high amounts of sweet, CHO-containing bars, gels and drinks, 3) a loss of continuous eating and drinking patterns because of mental fatigue. Other studies have also reported similar problems with sport foods and drinks, which were associated with an exacerbated energy deficit during ultra-endurance events lasting longer than 12 hr (Black et al, 2012, Moran
et al., 2011). Future studies may help to understand and prevent the reduction in food and fluid intake to optimize ultra-endurance exercise tolerance.
Limitations Our results are difficult to compare with other events because of differences in duration, intensity and race conditions (e.g., team vs. single starter). Nevertheless, because of the relatively large sample size, our results should give a better insight into changes over the course of time than single-case studies. In the current study, energy balance, macronutrient intake, and hydration status were assessed utilizing practical field assessment methods, so that several organizational and methodological limitations have to be considered. First of all, the athletes participated in an official event under competitive conditions, so that invasive and time-consuming procedures were not applicable. Further, we made every attempt to reduce the participants’ burden to minimize noncompliance before and during the event. Based on power output, which was continuously recorded during the marathon, we were able to determine EE, using an individual regression equation between power output and EE assessed with indirect calorimetry during the preliminary visit. Several studies indicate that the use of power output and indirect calorimetry provides acceptably valid EE results, when compared with doubly labeled water (Cuddy et al., 2010; Hulton et al., 2010). During the event, diet was continuously recorded by trained staff, but it cannot be ruled out that participants shared food and drinks with other teammates. Further, it is also possible that not all fluid was consumed as recorded, as some riders might have emptied their bottles over their head in an attempt to provide additional cooling, especially during the hot periods of the day, when temperatures above 35°C were recorded.
Practical Relevance of the Study The current study presents only a descriptive assessment and did not involve an intervention. Consequently, we cannot relate our measures of food and fluid intake to performance. However, our results may be of relevance to researchers and practitioners working with ultraendurance athletes: 1. During the second half of the ultra-endurance event, energy intake, CHO intake, and fluid intake decreased significantly and dropped below recommendations. Based on anecdotal evidence, the decrease in food and fluid intake was related to increased levels of satiety and fatigue. Individual food compatibility and changes in taste preferences especially after longer hours of exercising should be tested and evaluated during training and preparatory competitions. 2. Because the largest proportion of energy was derived from CHO, participants in ultra-endurance events
Energy and Hydration Status During Ultra-Endurance Exercise 505
should develop strategies to prevent the reduction in CHO during later stages of the event. Participants should have several CHO food sources available (normal food as well as CHO-rich sport products) and the tolerance of CHO-rich sport products should be tested in training to avoid or minimize sensoryspecific satiety. Gastrointestinal discomfort, which has been reported for high CHO during prolonged exercise (Pfeiffer et al., 2012), did not seem to play a role in the reduction in CHO intake. 3. Energy balance was strongly related to EI from solid foods. Consequently, it may be important to emphasize that sufficient food from solid sources is consumed. For lower intensity exercise as observed during the current study (43.6% VO2max), a fat intake of 30 to 40% could help to increase EI, provided that this strategy does not compromise CHO and that these amounts can be tolerated without gastrointestinal discomfort. 4. The large number of dehydrated participants during the event was most likely related to dehydration before the start, which occurred even though the participants were highly experienced in ultra-endurance events. It should be further emphasized athletes start their exercise in a euhydrated state, and practical recommendations should be given to athletes that can help them monitor their hydration status (e.g., urine color; Armstrong, 2005). 5. A fluid intake in the range of 300 to 500 ml/h may be adequate to remain hydrated during ultra-endurance exercise under common circumstances, which is supported by results from other studies.
References Ainslie, P., Reilly, T., & Westerterp, K. (2003). Estimating human energy expenditure: a review of techniques with particular reference to doubly labelled water. Sports Medicine (Auckland, N.Z.), 33(9), 683–698. PubMed doi:10.2165/00007256-200333090-00004 Allen, T.H., Peng, M.T., Chen, K.P., Huang, T.F., Chang, C., & Fang, H.S. (1956). Similarity of vital capacity in terms of body weight less adiposity in both sexes; appendix on the graphic estimation of adiposity and essential body mass from height and weight. Metabolism: Clinical and Experimental, 5(3), 353–358. PubMed American College of Sports Medicine, Sawka, M.N., Burke, L.M., Eichner, E.R., Maughan, R.J., Montain, S.J., & Stachenfeld, N.S. (2007). American College of Sports Medicine position stand. Exercise and fluid replacement. Medicine and Science in Sports and Exercise, 39(2), 377–390. PubMed doi:10.1249/mss.0b013e31802ca597 American Dietetic Association; Dietitians of Canada, American College of Sports Medicine, Rodriguez, N.R., Di Marco, N.M., & Langley, S. (2009). American College of Sports Medicine position stand. Nutrition and athletic performance. Medicine and Science in Sports
and Exercise, 41(3), 709–731. PubMed doi:10.1249/ MSS.0b013e31890eb86 Armstrong, L.E. (2007). Assessing hydration status: The elusive gold standard. Journal of the American College of Nutrition, 26(5, Suppl) 575S–584S. PubMed Bescós, R., Rodríguez, F.A., Iglesias, X., Knechtle, B., Benítez, A., Marina, M., . . . Rosemann, T. (2012). Nutritional behavior of cyclists during a 24-hour team relay race: A field study report. Journal of the International Society of Sports Nutrition, 9(1), 3. PubMed doi:10.1186/15502783-9-3 Bircher, S., Enggist, A., Jehle, T., & Knechtle, B. (2006). Effects of an extreme endurance race on energy balance and body composition - a case study. Journal of Sports Science and Medicine, 5, 154–162. PubMed Black, K.E., Skidmore, P.M.L., & Brown, R.C. (2012). Energy intakes of ultraendurance cyclists during competition, an observational study. International Journal of Sport Nutrition and Exercise Metabolism, 22(1), 19–23. PubMed Burke, L.M., Hawley, J.A., Wong, S.H.S., & Jeukendrup, A.E. (2011). Carbohydrates for training and competition. Journal of Sports Sciences, 29, S17–S27. PubMed doi:1 0.1080/02640414.2011.585473 Cuddy, J.S., Slivka, D.R., Hailes, W.S., Dumke, C.L., & Ruby, B.C. (2010). Metabolic profile of the Ironman World Championships: a case study. International Journal of Sports Physiology and Performance, 5(4), 570–576. PubMed Dill, D.B., & Costill, D.L. (1974). Calculation of percentage changes in volumes of blood, plasma, and red cells in dehydration. Journal of Applied Physiology, 37(2), 247–248. PubMed Hulton, A.T., Lahart, I., Williams, K.L., Godfrey, R., Charlesworth, S., Wilson, M., . . . Whyte, G. (2010). Energy expenditure in the Race Across America (RAAM). International Journal of Sports Medicine, 31(7), 463–467. PubMed doi:10.1055/s-0030-1251992 Jeukendrup, A. E. (2011). Nutrition for endurance sports: Marathon, triathlon, and road cycling. Journal of Sports Sciences, 29(sup1), S91. Jeukendrup, A.E., Moseley, L., Mainwaring, G.I., Samuels, S., Perry, S., & Mann, C.H. (2006). Exogenous carbohydrate oxidation during ultraendurance exercise. Journal of Applied Physiology, 100(4), 1134–1141. PubMed doi:10.1152/japplphysiol.00981.2004 Jeukendrup, A.E., & Jentjens, R. (2000). Oxidation of carbohydrate feedings during prolonged exercise: current thoughts, guidelines and directions for future research. Sports Medicine (Auckland, N.Z.), 29(6), 407–424. PubMed doi:10.2165/00007256-200029060-00004 Jeukendrup, A.E., Thielen, J.J., Wagenmakers, A.J., Brouns, F., & Saris, W.H. (1998). Effect of medium-chain triacylglycerol and carbohydrate ingestion during exercise on substrate utilization and subsequent cycling performance. The American Journal of Clinical Nutrition, 67(3), 397–404. PubMed Jeukendrup, A.E., Saris, W.H., Brouns, F., Halliday, D., & Wagenmakers, J.M. (1996). Effects of carbohydrate (CHO) and fat supplementation on CHO metabolism
506 Geesman et al.
during prolonged exercise. Metabolism: Clinical and Experimental, 45(7), 915–921. PubMed doi:10.1016/ S0026-0495(96)90169-9 Kavouras, S.A. (2002). Assessing hydration status. Current Opinion in Clinical Nutrition and Metabolic Care, 5(5), 519–524. PubMed doi:10.1097/00075197-20020900000010 Knechtle, B., Enggist, A., & Jehle, T. (2005). Energy Turnover at the Race Across AMerica (RAAM) - a Case Report. International Journal of Sports Medicine, 26(6), 499–503. PubMed doi:10.1055/s-2004-821136 Knechtle, B., Knechtle, P., & Kohler, G. (2011). The effect of 1,000 km nonstop cycling on fat mass and skeletal muscle mass. Research in Sports Medicine, 19(3), 170–185. PubMed Max Rubner-Institut. (2007). Bundeslebensmittelschlüssel.
http://www.mri.bund.de/de/service/datenbanken/ bundeslebensmittelschluessel.html Moran, S.T., Dziedzic, C.E., & Cox, G.R. (2011). Feeding strategies of a female athlete during an ultraendurance running event. International Journal of Sport Nutrition and Exercise Metabolism, 21(4), 347–351. PubMed Neumayr, G., Pfister, R., Hoertnagl, H., Mitterbauer, G., Getzner, W., Ulmer, H., . . . Joannidis, M. (2003). The effect of marathon cycling on renal function. International Journal of Sports Medicine, 24(2), 131–137. PubMed doi:10.1055/s-2003-38205 Neumayr, G., Pfister, R., Hoertnagl, H., Mitterbauer, G., Prokop, W., & Joannidis, M. (2005). Renal Function and Plasma Volume Following Ultramarathon Cycling. International Journal of Sports Medicine, 26(01/02), 2–8. Noakes, T.D., Sharwood, K., Speedy, D., Hew, T., Reid, S., Dugas, J., . . . Weschler, L. (2005). Three independent biological mechanisms cause exercise-associated hyponatremia: evidence from 2,135 weighed competitive athletic performances. Proceedings of the National Academy
of Sciences of the United States of America, 102(51), 18550–18555. PubMed doi:10.1073/pnas.0509096102 Pfeiffer, B., Stellingwerff, T., Hodgson, A.B., Randell, R., Poettgen, K., Res, P., & Jeukendrup, A.E. (2012). Nutritional Intake and Gastrointestinal Problems during Competitive Endurance Events. Medicine and Science in Sports and Exercise, 44(2), 344–351. PubMed doi:10.1249/ MSS.0b013e31822dc809 Pfeiffer, B., Stellingwerff, T., Zaltas, E., & Jeukendrup, A.E. (2010). Oxidation of Solid versus Liquid CHO Sources during Exercise. Medicine and Science in Sports and Exercise, 42(11), 2030–2037. PubMed doi:10.1249/ MSS.0b013e3181e0efc9 Rehrer, N.J. (2001). Fluid and electrolyte balance in ultraendurance sport. Sports Medicine (Auckland, N.Z.), 31(10), 701–715. PubMed doi:10.2165/00007256-20013110000001 Rüst, C.A., Knechtle, B., Knechtle, P., & Rosemann, T. (2012). No case of exercise-associated hyponatraemia in top male ultra-endurance cyclists: the ‘Swiss Cycling Marathon’. European Journal of Applied Physiology, 112(2), 689–697. PubMed doi:10.1007/s00421-011-2024-y Sawka, M.N., & Noakes, T.D. (2007). Does Dehydration Impair Exercise Performance? Medicine and Science in Sports and Exercise, 39(8), 1209–1217. PubMed doi:10.1249/ mss.0b013e318124a664 Shirreffs, S.M. (2003). Markers of hydration status. European Journal of Clinical Nutrition, 57, S6–S9. PubMed doi:10.1038/sj.ejcn.1601895 van Loon, L.J., Jeukendrup, A.E., Saris, W.H., & Wagenmakers, A.J. (1999). Effect of training status on fuel selection during submaximal exercise with glucose ingestion. Journal of Applied Physiology, 87(4), 1413–1420. PubMed Weir, J.B. (1949). New methods for calculating metabolic rate with special reference to protein metabolism. The Journal of Physiology, 109(1-2), 1–9. PubMed
Copyright of International Journal of Sport Nutrition & Exercise Metabolism is the property of Human Kinetics Publishers, Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use.
www.IJSNEM-Journal.com ORIGINAL RESEARCH
Energy Balance, Macronutrient Intake, and Hydration Status During a 1,230 km Ultra-Endurance Bike Marathon Bjoern Geesmann, Joachim Mester, and Karsten Koehler German Sport University Athletes competing in ultra-endurance events are advised to meet energy requirements, to supply appropriate amounts of carbohydrates (CHO), and to be adequately hydrated before and during exercise. In practice, these recommendations may not be followed because of satiety, gastrointestinal discomfort, and fatigue. The purpose of the study was to assess energy balance, macronutrient intake and hydration status before and during a 1,230-km bike marathon. A group of 14 well-trained participants (VO2max: 63.2 ± 3.3 ml/kg/min) completed the marathon after 42:47 hr. Ad libitum food and fluid intake were monitored throughout the event. Energy expenditure (EE) was derived from power output and urine and blood markers were collected before the start, after 310, 618, and 921 km, after the finish, and 12 hr after the finish. Energy intake (EI; 19,749 ± 4,502 kcal) was lower than EE (25,303 ± 2,436 kcal) in 12 of 14 athletes. EI and CHO intake (average: 57.1 ± 17.7 g/hr) decreased significantly after km 618 (p < .05). Participants ingested on average 392 ± 85 ml/hr of fluid, but fluid intake decreased after km 618 (p < .05). Hydration appeared suboptimal before the start (urine specific gravity: 1.022 ± 0.010 g/ml) but did not change significantly throughout the event. The results show that participants failed to maintain in energy balance and that CHO and fluid intake dropped below recommended values during the second half of the bike marathon. Individual strategies to overcome satiety and fatigue may be necessary to improve eating and drinking behavior during prolonged ultra-endurance exercise. Keywords: energy expenditure, energy intake, dehydration, carbohydrates, urine specific gravity Ultra-endurance cycling events are considered to be among the largest physiological challenges (Hulton et al., 2010). In recent years, races such as the Race Across America, Trondheim-Oslo and Paris-Brest-Paris (PBP) have become increasingly popular. PBP, which is the world’s largest bicycle marathon in terms of participation, covers a distance of 1,230 km and accumulates about 10,000 m in elevation gain. The successful participation in such extreme events greatly depends on adequate nutrition and hydration strategies (Black et al., 2012; Jeukendrup, 2011). It is considered essential that athletes ingest sufficient energy from food and fluid to compensate the high energy expenditure (EE) of ultra-endurance exercise (Jeukendrup, 2011; Rehrer, 2001). Consequently athletes are advised to maintain energy balance so as not to compromise their endurance performance (American Dietetic Association; Dietitians of Canada et al., 2009). Not only energy intake (EI), but also macronutrient composition plays an important role, with carbohydrates
Geesmann and Koehler are with the Institute of Biochemistry, and Mester the Institute of Training Science and Sport Informatics, German Sport University, Cologne, Germany. Address author correspondence to Karsten Koehler at k.koehler@psu. edu.
(CHO) being the most important component of EI. During prolonged exercise, fatigue is often associated with a depletion of muscle glycogen stores and reduced blood glucose levels and it has been shown that providing exogenous CHO may help to stabilize blood glucose levels and positively affect endurance performance (Jeukendrup, 2011). Controlled laboratory experiments have established that the oxidation rate of exogenous CHO increases linearly with increasing exercise intensity until approximately 50 to 60% of VO2max (Jeukendrup & Jentjens, 2000). At higher exercise intensities, intestinal CHO absorption seems to be limited, and consequently the oxidation rate of exogenous CHO plateaus at approximately 90 g/hr (Burke et al., 2011; Jeukendrup et al., 2006). Hence, a CHO intake of 60 to 90 g/hr in the form of multiple transportable CHO is recommended for endurance events lasting longer than 2.5 hr to maximize exogenous CHO oxidation and to prevent glycogen depletion (Jeukendrup, 2011; American Dietetic Association; Dietitians of Canada et al., 2009). Dehydration may also impair athletic performance during prolonged exercise (Jeukendrup, 2011; Sawka & Noakes, 2007; American College of Sports Medicine et al., 2007). General hydration recommendations include 1) to start exercise in a euhydrated state and 2) to drink adequately to avoid dehydration by more than 2 to 3% of the initial body weight (Jeukendrup, 2011; American College of Sports Medicine et al., 2007; Rehrer, 2001). 497
498 Geesman et al.
The American College of Sports Medicine recommends a fluid intake of 400 to 800 ml/hr during exercise, but states that drinking strategies should be adjusted individually to sweat rates and exercise duration (American College of Sports Medicine et al., 2007; Jeukendrup, 2011; Sawka & Noakes, 2007). During ultra-endurance exercise, these generalized recommendations may not be applicable and may even compromise each other. First, a CHO intake of 60 to 90 g/hr limits EI to about 250 to 380 g/hr, so that other macronutrients are required to maintain energy balance. Second, the provision of sufficient energy and fluid as recommended could lead to satiety and gastro-intestinal discomfort. Even though fluid can be used to provide energy in form of CHO, it should be considered that gastric emptying and fluid uptake may be impaired when the CHO content exceeds 6% (Pfeiffer et al., 2012). Consequently, CHO intake may be limited to 24 to 48 g/ hr when fluid intake is as recommended. Most scientific reports on nutrition and hydration practices during ultra-endurance events are single case studies (Knechtle et al., 2005; Bircher et al., 2006) or studies with a limited sample size (Hulton et al., 2010), which makes it difficult to summarize reported data on energy balance and hydration status, especially when considering that the magnitude of interindividual differences is unknown. The purpose of the current study was to assess components of energy balance (EI, EE), macronutrient intake, and hydration status (urine specific gravity (USG), hematocrit, hemoglobin, changes in plasma volume) during the bike marathon PBP to evaluate changes over the course of the marathon and to compare food and fluid intake to available recommendations. A secondary goal was to assess interindividual differences in these components in a group of equally trained cyclists. We hypothesized that 1) food and fluid intake would decrease over the course of the event, that 2) the athletes would not be able to remain in energy balance and in a euhydrated state, and that 3) the athletes would fail to meet recommendations for CHO and fluid intake.
Methods The Bike Marathon The study was performed around the 2011 edition of the bicycle marathon Paris-Brest-Paris, which was started on August 22nd at 4:00 PM. PBP is organized as a socalled brevet, which implies that riders can ride alone or in groups but are required to finish within defined time limits. For the 2011 edition of PBP, the riders were allowed a maximum of 86 hr to complete the 1,230-km course. During the event, participants passed a total of 14 control stations, where time was recorded and food and drinks were available ad libitum. Supporting crews were not allowed on the official route, so that riders had to carry all food and fluid for the sections between control stations in their jersey pockets or in bottles at the bike.
The participants did not plan to sleep during the marathon. Temperature varied between 18.5 and 41.0°C and relative humidity was between 55 and 80%.
Participants Eighteen well-trained male amateur athletes volunteered to participate in this study. Volunteers were recruited from a training group which participated in a commercial training program for ultra-endurance events. All participants provided written informed consent and the investigation was approved by the ethical review board of the German Sports University. All participants were without medical illness and did not take any medication at the time of the screening visit or the bike marathon.
Screening Visit Within 6 weeks before the marathon, participants completed a screening visit to the laboratory, which included: 1) informed consent, 2) anthropometrical measurements, and 3) a preliminary performance test. The performance test was conducted on a stationary bicycle ergometer (SRM, Jülich, Germany) and served to determine maximal oxygen uptake (VO2max) and to assess the individual relationship between power output (in W) and EE (in kcal/ min). After resting in a sitting position on the ergometer for 3 min, the test was initiated at 100 W and power output was increased stepwise by 50 W every 4 min. After completion of the 250 W step, power output was increased by 25 W every 30 seconds until a plateau in oxygen uptake was observed despite a further increase in workload. During the test, EE was assessed by indirect calorimetry (ZAN 600, nSpire Health, Inc., Colorado, USA) using the Weir equation (Weir, 1949).
Measurements During the Event Body weight and body fat was measured the morning before the start of the marathon following an overnight fast and again immediately after the finish. A Tanita BC-545 (Tanita, Hoofddorp, Netherlands) was used to assess body weight to the nearest 0.01 kg. Percentages of body fat were assessed by calipermetry (Baty International, West Sussex, UK) using the 10-point-method (Allen et al., 1956). Urine and capillary blood samples were collected the morning before the start, at control stations after 310, 618, and 921 km, immediately after the finish and following a recovery period of approximately 12 hr. Urine samples collected before the start and after the 12-hr recovery period presented first morning void urine samples, while all other samples presented spot urine samples. Urine samples were frozen immediately for convenience and USG was subsequently analyzed with a DMA 38 density meter (Anton Paar, Graz, Austria). Based on USG, participants were categorized as adequately hydrated ( 1.030 g/ml; Armstrong, 2005; Shirreffs, 2003; Kavouras, 2002).
Energy and Hydration Status During Ultra-Endurance Exercise 499
Capillary blood samples were centrifuged and directly analyzed for hematocrit and hemoglobin concentrations (QBC Diagnostics, Inc., Port Matilda, PA, USA). Changes in plasma volume (ΔPV) were calculated according to Dill & Costill (1974). Unfortunately, because of a centrifuge malfunction, no values could be obtained for the samples collected after the finish. All riders were equipped with an SRM system (SRM, Jülich, Germany) to assess power output continuously throughout the bike marathon. Power output was averaged over 1-minute intervals and subsequently converted to EE, using the individual relationship determined during the screening visit. For intervals with an average power of 0 W and for all resting periods, EE was defined as resting EE measured during the 3-minute rest period at the start of the performance test during the screening visit. Dietary intake was recorded continuously for each individual athlete by trained staff. The macronutrient content of food was obtained from the manufacturer’s information or from the Federal German Nutrient Database (Bundeslebensmittelschluessel, Version II.4).
Results Participants Four athletes were forced to terminate the bike marathon before reaching the finish because of issues unrelated to the present investigation (orthopedic complications (n = 2), exhaustion (n = 1), and heatstroke acquired before the start (n = 1) and were excluded from the subsequent analysis. The 14 successful participants were 43.6 ± 7.8 years of age, 180.1 ± 6.2 cm tall, weighted 74.1 ± 6.8 kg and had a maximal oxygen uptake (VO2max) of 63.2 ± 3.3 ml/min/kg.
Bike Marathon The participants rode together as a closed group over the whole course and finished the bike marathon after 54 hr, with a net cycling time of 42 hr and 47 min. Average velocity and power output declined significantly between the first and second and between the second and third section (P = .001; Table 1).
Statistics
Energy Balance
For data analysis, the bike marathon was divided into four sections based on stops at control stations after 310 km (end of section 1), 618 km (section 2), and 921 km (section 3), and the finish (section 4). Statistical analyses were performed with SPSS (version 21, IBM, New York, USA). If not reported otherwise, data are presented as mean ± standard deviation and ranges (min, max). Data were tested for normality using the Kolmogorov-Smirnov test. For comparisons between time points, analysis of variance with repeated measures was applied and a t test served as post hoc test. The level of significance was set at p < .05. For pairwise multiple comparisons, the level of significance was adjusted by Bonferroni’s correction. Spearman’s correlation coefficient was determined for correlation analyses.
Mean EI throughout the event was 19,749 ± 4,502 kcal and individual values ranged from 13,657 kcal to 28,395 kcal (Figure 1). When expressed as kcal per 24h, the average EI was 8,777 ± 2,001 kcal/24h. EI increased significantly from the first section (4,733 ± 1,136 kcal) to the second section (6,093 ± 1,838 kcal; P = .042), but decreased significantly between the third section (5,601 ± 1,081 kcal) and the last section (3,322 ± 1,564 kcal; P = .001). The cyclists derived 15,634 ± 4,310 kcal (range: 10,676 kcal—26,005 kcal) from solid foods sources (79 ± 9%) and 4,115 ± 1,851 kcal (range: 2,234 kcal—8,147 kcal) from liquids (21 ± 9%). In average, EE throughout the event was 25,303 ± 2,436 kcal and ranged from 21,801 kcal to 30,567 kcal
Table 1 Race Data Separated in the Four Sections (km 0–310, 311–618, 619–921, 922–1,230) and Overall Section 1 Distance [km]
Section 2
Section 3
Section 4
Overall
310
308
303
309
1,230
Cycling time [hr:min]
10:11
10:32
11:17
10:47
42:47
Rest [hr:min]
00:43
02:02
05:34
02:54
11:13
Total time [hr:min] Average power output [W] Average Intensity [% VO2max] Velocity [km/h]
10:54
12:34
16:51
13:41
54:00
149.5 ± 11.7
138.3 ± 11.2**
127.4 ± 13.9††**
126.1 ± 20.7**
135.4 ± 13.0
45.4 ± 5.5
42.0 ± 4.8
41.0 ± 3.8
40.5 ± 5.4
43.6 ± 4.4
30.4
29.2**
26.8††**
28.7##**
28.7
**Significantly different from section 1 (p < .001). ††Significantly different from section 2 (p < .001). ##Significantly different from section 3 (p < .05).
500 Geesman et al.
(Figure 1). When expressed as kcal per 24h mean EE was 11,246 ± 1,083 kcal/24 hr (range: 9,689 to 13,585 kcal/24h). Average energy balance was -5,554 ± 4,567 kcal, but individual energy balance ranged from -11,859 kcal to 3,593 kcal (Figure 1). When expressed as kcal per 24 hr, energy balance was -2,468 ± 2,030 kcal/24 hr (range: -5,271 to 1,597 kcal/24/hr). EI was the main significant predictor of energy balance (r = .93, p < .001). Energy balance was also highly correlated with EI from solid foods (r = .86; p < .001; Figure 2) Body weight did not change significantly over the course of the event. Average weight loss was 0.1 ± 1.4 kg and individual weight changes ranged from –1.9 kg to 2.4 kg. Fat mass decreased significantly (p = .001) by 0.9 ± 0.5 kg (range: 0.3 kg to 1.9 kg). Fat-free mass increased
significantly (p = .039) by 0.8 ± 1.3 kg (range: –1.4 to 3.0 kg). Changes in body weight (r=-0.45, p = .47) and fat mass (r = .42, P = .50) were not significantly correlated with energy balance.
Macronutrient Intake The largest proportion of energy was provided from CHO (57.5 ± 5.8%), when compared with fat (29.3 ± 4.0%) and protein (13.2 ± 2.0%). In total, the cyclists consumed 3,011 ± 525 g of CHO, which accounted for a total of 40.7 ± 8.5 g/kg BW. When expressed as g/hr mean CHO intake was 57.1 ± 17.7 g/hr. Total protein intake was 705 ± 213 g (9.6 ± 3.2 g/kg BW) and fat intake was 691 ± 179 g (9.4 ± 2.7 g/kg BW). CHO intake (Figure 3) increased significantly from section 1 (10.2 ± 2.4 g/kg BW) to section 2 (12.5 ± 3.2
Figure 1 — Individual data for energy intake, energy expenditure and resulting energy balance in the 14 bicyclists
Figure 2 — Association between energy intake from solid foods (left) and the energy intake from liquid foods (right) with energy balance
Energy and Hydration Status During Ultra-Endurance Exercise 501
Figure 3 — Macronutrient composition in g/kg BW (top) and in % of energy intake (bottom) over the course of the race. *Significantly different from section 1 (p < .05); †,††,†††: significantly different from section 3 (p < .05, p < .01, p < .001).
g/kg BW; p = .022) and decreased from section 3 (11.5 ± 2.7 g/kg BW) to section 4 (6.5 ± 2.4 g/kg BW; p < .001). Likewise, protein and fat intake increased from section 1 (protein: 2.2 ± 0.8 g/kg BW; fat: 2.1 ± 0.7 g/kg BW) to section 2 (protein: 3.0 ± 1.3 g/kg BW, p = .042; fat: 2.8 ± 1.1 g/kg BW, p = .038) and decreased from section 3 (protein: 2.6 ± 0.7 g/kg BW; fat: 2.6 ± 0.8 g/kg BW) to section 4 (protein: 1.7 ± 1.0 g/kg BW, p = .007; fat: 1.9 ± 0.9 g/kg BW, p = .014).
Fluid Intake and Hydration Status The participants ingested a total of 21,186 ± 4,586 ml fluid (range: 13,422 ml—28,065 ml) during the event, which corresponds to 392 ± 85 ml/hr (range: 249 ml/ hr—520 ml/hr). Fluid intake was not significantly associated with EI from liquid sources (r = .11, p = .70). Following an insignificant increase from the first section (473 ± 108 ml/hr) to the second section (506 ± 165 ml/ hr), mean fluid intake decreased significantly in the third section (333 ± 95 ml/hr; p = .017). The further reduction in the fourth section (297 ± 91 ml/hr) was not significant. On the morning before the start, participants exhibited a mean hematocrit of 49.6 ± 3.1% and a mean hemo-
globin of 16.6 ± 0.9 mg/dl (Figure 4). Between sections 2 and 3, there was a significant reduction in hematocrit (51.5 ± 4.2% to 48.5 ± 3.4%; P = .023) and hemoglobin (17.0 ± 1.2 g/dl to ; 16.1 ± 1.4 g/dl; P = .045). Following the 12-hr recovery period, hematocrit and hemoglobin were further reduced when compared with the end of the third section (hematocrit: 45.5 ± 2.3%; p = .006; hemoglobin: 15.2 ± 0.9 g/dl; p = .018). Average changes in plasma volume ranged from –0.5 ± 4.0 to 1.3 ± 4.7% and there was no clear trend in plasma volume over the course of the bike marathon. Despite small average changes in plasma volume, interindividual changes varied between -5.3 and 11.6%. USG on the morning before the start was 1.022 ± 0.010 g/ml (range: 1.004 g/ml to 1.035 g/ml). Over the course of the bike marathon, USG declined continuously but not significantly to 1.018 ± 0.007 g/ml (range: 1.004 g/ml to 1.028 g/ml) after the end of the third section. Immediately after the finish, the riders exhibited a mean USG of 1.021 ± 0.008 g/ml (range from 1.004 g/ml to 1.036 g/ml). After the 12-hr recovery period, USG was in the range of the values before the event (1.022 ± 0.005 g/ ml; range from 1.014 g/ml to 1.028 g/ml). There were no significant differences in USG between any time points. Based on the aforementioned criteria for USG, six cyclists were considered mildly dehydrated and three cyclists were considered severely dehydrated on the morning before the start. The lowest number of dehydrated riders was noted after the third section (seven riders mildly dehydrated, no rider severely dehydrated). After the finish, seven riders were classified as mildly dehydrated and one rider as severely dehydrated. Following the 12-hr regeneration period, nine riders were classified as mildly dehydrated based on their USG. Changes in USG were not significantly correlated with fluid intake (r = .09, p = .77) and EI from liquid sources (r = .18, p = .55).
Discussion The current study underlines the extreme physiological burden to the human body while participating in ultraendurance cycling events. Our results show a considerable decline in ad libitum food and fluid intake during the second half of the marathon. Consequently, participants were not able to remain in energy balance and failed to meet recommendations for CHO (60 to 90 g/hr) and fluid intake (400 to 800 ml/hr) during the second half of the bike marathon. Hydration status was suboptimal in a considerable number of participants already at the morning of the start, but did not appear to worsen during the event.
Energy Intake and Energy Balance On average, energy balance was –5,554 ± 4,567 kcal. The standard deviation of 4,567 kcal (CV = 82%) indicates that energy balance varied considerably between individual participants. Twelve riders were not able to
502 Geesman et al.
Figure 4 — Hematocrit (top left), hemoglobin (top right), changes in plasma volume (bottom left) and urinary specific gravity (bottom right) over the course of the race. *Significantly different from section 3 (p < .05); †,††: significantly different from section 4 (p < .05, p < .01).
match their EE, whereas two riders were in a positive energy balance. Differences in energy balance were primarily caused by interindividual differences in EI, as the riders with a positive energy balance also had the highest reported EI (26,981 kcal; 28,395 kcal). EI declined significantly after the first half of the marathon, so that the energy deficit was primarily attained during the second half. For the first section, an average energy deficit of 1,523 ± 1,012 kcal was determined, but it has to be considered that food and drinks before the start were not accounted for our calculations. In the second section, the participants were able to meet their EE (energy balance: -137 ± 1716 kcal). Potential reasons for the reduction in EI during later sections of the event will be discussed below, because they are likely identical to reasons for the reduction in CHO and fluid intake. The overall negative energy balance is in agreement with the loss of fat mass of 0.9 ± 0.5 kg accounting for approximately 6,900 kcal. However, several methodological limitations have to be considered when evaluating changes in body weight and composition during the current study. First, it has to be taken into account that body weight and body composition before the start were assessed following an overnight fast, while measure-
ments after the marathon were taken immediately after the finish, so that recently ingested food or drinks might have increased weight. Second, fluid shifts associated with an increase in total body water, which have been reported following ultra-endurance events in other studies (Knechtle et al., 2011; Noakes et al., 2005), might have led to an overestimation of fat-free mass. It has been argued that the increase in body water is caused by increased extracellular sodium and elevated aldosterone levels and that it acts to maintain the body’s circulating blood volume to perfuse all organs (Knechtle et al., 2011). In the current study, fat-free mass increased by 0.8 ± 1.3. kg over the course of the marathon. When comparing energy balance during the current study with data from similar events, it has to be considered that energy requirements largely depend on the length of the event. For the RAAM (approximately 4, 800 km), Hulton et al. (2010) assessed the EE in four athletes who competed for 12 hr/day. Daily EI (4,918 ± 810 kcal) and EE (6,420 ± 470 kcal) were approximately half of the values reported in the current study (EI: 8,777 ± 2,001 kcal/24 hr; EE: 11,246 ± 1,083 kcal/24 hr). Knechtle et al. (2005) assessed an EI of 9,612 ± 1,500 kcal/d and an EE of 17,965 ± 2,165 kcal/d in a single case
Energy and Hydration Status During Ultra-Endurance Exercise 503
study, which was substantially higher than our values and also more than twice the values reported by Hulton et al. (2010). It should be considered that Knechtle et al. (2005) used continuous heart rate monitoring to assess EE which is associated with errors up to 30% (Ainslie et al., 2003), whereas Hulton et al. (2010) measured EE with the gold-standard method of doubly labeled water (Ainslie et al., 2003).
Macronutrients The largest proportion of energy was provided from CHO (57.5 ± 5.8%), but CHO intake decreased in the last section of the event in terms of absolute (in g/kg) and relative intake (in % of EI). The ratio between CHO and protein remained fairly stable, whereas the reduction in relative CHO intake in the last section was associated with an increase in fat intake. During the bike marathon, mean CHO supply was 57.1 ± 17.7 g/hr, which is only slightly below the recommendation of 60 to 90 g/h for events lasting longer than 2.5 hr (Jeukendrup, 2011; American Dietetic Association; Dietitians of Canada et al., 2009). The participants were able to meet the recommendations during the first half of the event (section 1: 69.0 ± 12.8 g/h, section 2: 73.6 ± 17.9 g/hr), but CHO intake dropped significantly in the second half and fell below 60 g/hr (section 3: 50.5 ± 10.6 g/hr, section 4: 35.2 ± 12.1 g/hr). Providing exogenous CHO may help to maintain and stabilize blood glucose concentrations, delay muscle glycogen depletion and fatigue, and improve endurance performance (Burke et al., 2011; Jeukendrup, 2011). However, it has been shown that the oxidation of exogenous CHO during exercise is limited to approximately 90 g/h, even when multiple transportable CHO are used to maximize intestinal absorption (Burke et al., 2011; Pfeiffer et al., 2010; Jeukendrup et al., 2006). Because an increase in CHO intake above 90 g/hr has been associated with an increased likelihood of gastrointestinal distress (Pfeifer et al., 2012; Jeukendrup, 2011), a CHO intake of 60 to 90 g/h is typically recommended for endurance exercise lasting longer than 2.5 hr (Burke et al., 2011; Jeukendrup, 2011). In the current study, participants were able to maintain their CHO in the range of the recommendations for the first half of the marathon, which they completed in 20 hr 43 min, without reporting gastrointestinal symptoms. The reduction in CHO intake, which was associated with a reduction in food intake, was not related to gastrointestinal discomfort. This shows that it is possible to tolerate 60 to 90 g of CHO per hr for prolonged periods of exercise and that gastrointestinal distress does not seem to be a factor that limits CHO intake during ultra-endurance exercise when CHO intake is kept within the range of the recommendation. However, it remains questionable whether CHO recommendations are appropriate for prolonged ultraendurance exercise as reported in the current study. Studies in which the maximal oxidation rates of 60 to
90 g/hr were established were conducted at exercise intensities between 51 and 64% of VO2max at exercise durations between 2 and 5 hr (Jeukendrup et al., 2006; Jeukendrup & Jentjens, 2000). During the current study, exercise intensity was slightly lower (43.6% of VO2max), but exercise duration was much longer (54 hr). van Loon et al. (1999) reported an oxidation rate of only 43 g/hr for exogenous CHO at an exercise intensity of 40 to 45% of VO2max in trained cyclists, but it should be considered that the study was not designed to maximize exogenous CHO oxidation (van Loon et al., 1999). Endogenous CHO was contributed at a rate of 52 g/hr to a total CHO oxidation rate of 95 g/hr at 40 to 45% of VO2max in trained cyclists (van Loon et al., 1999). Considering that CHO oxidation remains stable during prolonged ultra-endurance exercise (Jeukendrup et al., 2006), a CHO intake closer to total CHO oxidation might help to prevent premature depletion of muscle and liver glycogen stores. However, future studies investigating CHO oxidation rates at exercise durations greater than 5 hr are necessary to refine CHO recommendations for ultra-endurance exercise. When CHO are used as the sole source of energy as recommended (60 to 90 g/h), EI is limited to 250–380 kcal/h. Without an adequate intake of fat and protein, this will result in an accumulated energy deficit, which could compromise performance during ongoing exercise. In the current study, CHO intake accounted for 57% of total EI, which is in the range of values reported for the team-event of RAAM (56 to 64%, Hulton et al., 2010). Higher relative CHO intakes (70 to 75% of EI) have been reported in single-case studies during the RAAM and the Race Across the Alps (Knechtle et al, 2005; Bircher et al, 2006 and in bike races of shorter duration (Black et al., 2012; Bescós et al., 2012). Consequently, fat intake in the current study (29.3 ± 4.0%) was considerably greater than fat intake reported in other ultra-endurance events. In most studies, fat intake was in the range between 14 and 17% of total EI (Bescós et al., 2012; Hulton et al., 2010; Bircher et al, 2006; Knechtle et al., 2005). To our knowledge, only limited literature data are available to which extent the ingestion of other macronutrients impacts the absorption and oxidation of exogenous CHO. Fat supplementation during exercise was not found to attenuate CHO oxidation (Jeukendrup et al., 1996, 1998), but it has been argued that increased fat or protein ingestion during exercise may be associated with gastrointestinal discomfort (Jeukendrup, 2011; Jeukendrup et al., 1998; Jeukendrup et al., 1996). However, exercise intensity during the present event (43.6% VO2max) was lower than exercise intensities in studies that have reported gastrointestinal discomfort (60% VO2max, Jeukendrup et al., 1998; 57% VO2max, Jeukendrup et al., 1996). Interestingly, one of the participants who was able to maintain in energy balance during the event increased his fat intake to 20.7 g/hr during the last section of the marathon without reporting gastrointestinal discomfort. Further research is needed to assess how CHO oxidation and gastrointestinal discomfort are impacted by the ingestion of other macronutrients to establish recom-
504 Geesman et al.
mendations for fat and protein intake during prolonged ultra-endurance exercise.
Fluid Intake and Hydration Status In average, the participants consumed 392 ± 85 ml/hr of fluid throughout the event. Fluid intake varied to a much lesser degree between individuals than EI (coefficient of variation: 22%). Whereas the participants were able to meet the recommendation of 400 to 800 ml/hr in the first half of the marathon, fluid intake decreased significantly in the second half and fell below the recommendations. Despite the considerably low fluid intake especially in the second half of the marathon, we observed no increase in dehydration as indicated by changes in plasma volume, hematocrit, hemoglobin, and USG. In addition, we did not find a correlation between fluid intake and changes in hydration status during the event. Consequently, it can be assumed that our participants had established individual drinking regimens that allowed them to maintain in fluid balance without excessive over- or under-drinking. To our surprise, USG indicated that the majority of the riders were not adequately hydrated before the start. Because hydration status did not worsen further during the event, it may be possible that dehydration was not a performance-limiting factor during the present event. However, it has to be taken into account that the USG before the start was determined from morning first void urine, approximately 8 hr before the start. Even though morning first void urine USG is considered a valid indicator of hydration status (Armstrong, 2005; Shirreffs, 2003), it is possible that athletes improved their hydration status in the hours before the start. For a better description of the hydration status, the assessment of individual sweat rates and fluid losses would have provided additional information. However, the assessment of sweat losses using changes in body weight would have interfered with changes in body mass due to excessive substrate use during prolonged exercise (Armstrong, 2005). Other studies have reported slightly higher fluid intake (530 to 670 ml/hr), but also no increased incidence of dehydration based on plasma volume changes and USG during other ultra-endurance events (Neumayr et al., 2003, 2005; Rüst et al., 2012). Unfortunately, we did not assess the underlying causes for the reduction in food and fluid intake during the second half of the event systematically. Based on anecdotic reports, three major reasons were identified: 1) the participants felt saturated because of the large amounts of food and drinks ingested during the previous hours of exercise, 2) the participants reported feelings of sensory-specific satiety due to high amounts of sweet, CHO-containing bars, gels and drinks, 3) a loss of continuous eating and drinking patterns because of mental fatigue. Other studies have also reported similar problems with sport foods and drinks, which were associated with an exacerbated energy deficit during ultra-endurance events lasting longer than 12 hr (Black et al, 2012, Moran
et al., 2011). Future studies may help to understand and prevent the reduction in food and fluid intake to optimize ultra-endurance exercise tolerance.
Limitations Our results are difficult to compare with other events because of differences in duration, intensity and race conditions (e.g., team vs. single starter). Nevertheless, because of the relatively large sample size, our results should give a better insight into changes over the course of time than single-case studies. In the current study, energy balance, macronutrient intake, and hydration status were assessed utilizing practical field assessment methods, so that several organizational and methodological limitations have to be considered. First of all, the athletes participated in an official event under competitive conditions, so that invasive and time-consuming procedures were not applicable. Further, we made every attempt to reduce the participants’ burden to minimize noncompliance before and during the event. Based on power output, which was continuously recorded during the marathon, we were able to determine EE, using an individual regression equation between power output and EE assessed with indirect calorimetry during the preliminary visit. Several studies indicate that the use of power output and indirect calorimetry provides acceptably valid EE results, when compared with doubly labeled water (Cuddy et al., 2010; Hulton et al., 2010). During the event, diet was continuously recorded by trained staff, but it cannot be ruled out that participants shared food and drinks with other teammates. Further, it is also possible that not all fluid was consumed as recorded, as some riders might have emptied their bottles over their head in an attempt to provide additional cooling, especially during the hot periods of the day, when temperatures above 35°C were recorded.
Practical Relevance of the Study The current study presents only a descriptive assessment and did not involve an intervention. Consequently, we cannot relate our measures of food and fluid intake to performance. However, our results may be of relevance to researchers and practitioners working with ultraendurance athletes: 1. During the second half of the ultra-endurance event, energy intake, CHO intake, and fluid intake decreased significantly and dropped below recommendations. Based on anecdotal evidence, the decrease in food and fluid intake was related to increased levels of satiety and fatigue. Individual food compatibility and changes in taste preferences especially after longer hours of exercising should be tested and evaluated during training and preparatory competitions. 2. Because the largest proportion of energy was derived from CHO, participants in ultra-endurance events
Energy and Hydration Status During Ultra-Endurance Exercise 505
should develop strategies to prevent the reduction in CHO during later stages of the event. Participants should have several CHO food sources available (normal food as well as CHO-rich sport products) and the tolerance of CHO-rich sport products should be tested in training to avoid or minimize sensoryspecific satiety. Gastrointestinal discomfort, which has been reported for high CHO during prolonged exercise (Pfeiffer et al., 2012), did not seem to play a role in the reduction in CHO intake. 3. Energy balance was strongly related to EI from solid foods. Consequently, it may be important to emphasize that sufficient food from solid sources is consumed. For lower intensity exercise as observed during the current study (43.6% VO2max), a fat intake of 30 to 40% could help to increase EI, provided that this strategy does not compromise CHO and that these amounts can be tolerated without gastrointestinal discomfort. 4. The large number of dehydrated participants during the event was most likely related to dehydration before the start, which occurred even though the participants were highly experienced in ultra-endurance events. It should be further emphasized athletes start their exercise in a euhydrated state, and practical recommendations should be given to athletes that can help them monitor their hydration status (e.g., urine color; Armstrong, 2005). 5. A fluid intake in the range of 300 to 500 ml/h may be adequate to remain hydrated during ultra-endurance exercise under common circumstances, which is supported by results from other studies.
References Ainslie, P., Reilly, T., & Westerterp, K. (2003). Estimating human energy expenditure: a review of techniques with particular reference to doubly labelled water. Sports Medicine (Auckland, N.Z.), 33(9), 683–698. PubMed doi:10.2165/00007256-200333090-00004 Allen, T.H., Peng, M.T., Chen, K.P., Huang, T.F., Chang, C., & Fang, H.S. (1956). Similarity of vital capacity in terms of body weight less adiposity in both sexes; appendix on the graphic estimation of adiposity and essential body mass from height and weight. Metabolism: Clinical and Experimental, 5(3), 353–358. PubMed American College of Sports Medicine, Sawka, M.N., Burke, L.M., Eichner, E.R., Maughan, R.J., Montain, S.J., & Stachenfeld, N.S. (2007). American College of Sports Medicine position stand. Exercise and fluid replacement. Medicine and Science in Sports and Exercise, 39(2), 377–390. PubMed doi:10.1249/mss.0b013e31802ca597 American Dietetic Association; Dietitians of Canada, American College of Sports Medicine, Rodriguez, N.R., Di Marco, N.M., & Langley, S. (2009). American College of Sports Medicine position stand. Nutrition and athletic performance. Medicine and Science in Sports
and Exercise, 41(3), 709–731. PubMed doi:10.1249/ MSS.0b013e31890eb86 Armstrong, L.E. (2007). Assessing hydration status: The elusive gold standard. Journal of the American College of Nutrition, 26(5, Suppl) 575S–584S. PubMed Bescós, R., Rodríguez, F.A., Iglesias, X., Knechtle, B., Benítez, A., Marina, M., . . . Rosemann, T. (2012). Nutritional behavior of cyclists during a 24-hour team relay race: A field study report. Journal of the International Society of Sports Nutrition, 9(1), 3. PubMed doi:10.1186/15502783-9-3 Bircher, S., Enggist, A., Jehle, T., & Knechtle, B. (2006). Effects of an extreme endurance race on energy balance and body composition - a case study. Journal of Sports Science and Medicine, 5, 154–162. PubMed Black, K.E., Skidmore, P.M.L., & Brown, R.C. (2012). Energy intakes of ultraendurance cyclists during competition, an observational study. International Journal of Sport Nutrition and Exercise Metabolism, 22(1), 19–23. PubMed Burke, L.M., Hawley, J.A., Wong, S.H.S., & Jeukendrup, A.E. (2011). Carbohydrates for training and competition. Journal of Sports Sciences, 29, S17–S27. PubMed doi:1 0.1080/02640414.2011.585473 Cuddy, J.S., Slivka, D.R., Hailes, W.S., Dumke, C.L., & Ruby, B.C. (2010). Metabolic profile of the Ironman World Championships: a case study. International Journal of Sports Physiology and Performance, 5(4), 570–576. PubMed Dill, D.B., & Costill, D.L. (1974). Calculation of percentage changes in volumes of blood, plasma, and red cells in dehydration. Journal of Applied Physiology, 37(2), 247–248. PubMed Hulton, A.T., Lahart, I., Williams, K.L., Godfrey, R., Charlesworth, S., Wilson, M., . . . Whyte, G. (2010). Energy expenditure in the Race Across America (RAAM). International Journal of Sports Medicine, 31(7), 463–467. PubMed doi:10.1055/s-0030-1251992 Jeukendrup, A. E. (2011). Nutrition for endurance sports: Marathon, triathlon, and road cycling. Journal of Sports Sciences, 29(sup1), S91. Jeukendrup, A.E., Moseley, L., Mainwaring, G.I., Samuels, S., Perry, S., & Mann, C.H. (2006). Exogenous carbohydrate oxidation during ultraendurance exercise. Journal of Applied Physiology, 100(4), 1134–1141. PubMed doi:10.1152/japplphysiol.00981.2004 Jeukendrup, A.E., & Jentjens, R. (2000). Oxidation of carbohydrate feedings during prolonged exercise: current thoughts, guidelines and directions for future research. Sports Medicine (Auckland, N.Z.), 29(6), 407–424. PubMed doi:10.2165/00007256-200029060-00004 Jeukendrup, A.E., Thielen, J.J., Wagenmakers, A.J., Brouns, F., & Saris, W.H. (1998). Effect of medium-chain triacylglycerol and carbohydrate ingestion during exercise on substrate utilization and subsequent cycling performance. The American Journal of Clinical Nutrition, 67(3), 397–404. PubMed Jeukendrup, A.E., Saris, W.H., Brouns, F., Halliday, D., & Wagenmakers, J.M. (1996). Effects of carbohydrate (CHO) and fat supplementation on CHO metabolism
506 Geesman et al.
during prolonged exercise. Metabolism: Clinical and Experimental, 45(7), 915–921. PubMed doi:10.1016/ S0026-0495(96)90169-9 Kavouras, S.A. (2002). Assessing hydration status. Current Opinion in Clinical Nutrition and Metabolic Care, 5(5), 519–524. PubMed doi:10.1097/00075197-20020900000010 Knechtle, B., Enggist, A., & Jehle, T. (2005). Energy Turnover at the Race Across AMerica (RAAM) - a Case Report. International Journal of Sports Medicine, 26(6), 499–503. PubMed doi:10.1055/s-2004-821136 Knechtle, B., Knechtle, P., & Kohler, G. (2011). The effect of 1,000 km nonstop cycling on fat mass and skeletal muscle mass. Research in Sports Medicine, 19(3), 170–185. PubMed Max Rubner-Institut. (2007). Bundeslebensmittelschlüssel.
http://www.mri.bund.de/de/service/datenbanken/ bundeslebensmittelschluessel.html Moran, S.T., Dziedzic, C.E., & Cox, G.R. (2011). Feeding strategies of a female athlete during an ultraendurance running event. International Journal of Sport Nutrition and Exercise Metabolism, 21(4), 347–351. PubMed Neumayr, G., Pfister, R., Hoertnagl, H., Mitterbauer, G., Getzner, W., Ulmer, H., . . . Joannidis, M. (2003). The effect of marathon cycling on renal function. International Journal of Sports Medicine, 24(2), 131–137. PubMed doi:10.1055/s-2003-38205 Neumayr, G., Pfister, R., Hoertnagl, H., Mitterbauer, G., Prokop, W., & Joannidis, M. (2005). Renal Function and Plasma Volume Following Ultramarathon Cycling. International Journal of Sports Medicine, 26(01/02), 2–8. Noakes, T.D., Sharwood, K., Speedy, D., Hew, T., Reid, S., Dugas, J., . . . Weschler, L. (2005). Three independent biological mechanisms cause exercise-associated hyponatremia: evidence from 2,135 weighed competitive athletic performances. Proceedings of the National Academy
of Sciences of the United States of America, 102(51), 18550–18555. PubMed doi:10.1073/pnas.0509096102 Pfeiffer, B., Stellingwerff, T., Hodgson, A.B., Randell, R., Poettgen, K., Res, P., & Jeukendrup, A.E. (2012). Nutritional Intake and Gastrointestinal Problems during Competitive Endurance Events. Medicine and Science in Sports and Exercise, 44(2), 344–351. PubMed doi:10.1249/ MSS.0b013e31822dc809 Pfeiffer, B., Stellingwerff, T., Zaltas, E., & Jeukendrup, A.E. (2010). Oxidation of Solid versus Liquid CHO Sources during Exercise. Medicine and Science in Sports and Exercise, 42(11), 2030–2037. PubMed doi:10.1249/ MSS.0b013e3181e0efc9 Rehrer, N.J. (2001). Fluid and electrolyte balance in ultraendurance sport. Sports Medicine (Auckland, N.Z.), 31(10), 701–715. PubMed doi:10.2165/00007256-20013110000001 Rüst, C.A., Knechtle, B., Knechtle, P., & Rosemann, T. (2012). No case of exercise-associated hyponatraemia in top male ultra-endurance cyclists: the ‘Swiss Cycling Marathon’. European Journal of Applied Physiology, 112(2), 689–697. PubMed doi:10.1007/s00421-011-2024-y Sawka, M.N., & Noakes, T.D. (2007). Does Dehydration Impair Exercise Performance? Medicine and Science in Sports and Exercise, 39(8), 1209–1217. PubMed doi:10.1249/ mss.0b013e318124a664 Shirreffs, S.M. (2003). Markers of hydration status. European Journal of Clinical Nutrition, 57, S6–S9. PubMed doi:10.1038/sj.ejcn.1601895 van Loon, L.J., Jeukendrup, A.E., Saris, W.H., & Wagenmakers, A.J. (1999). Effect of training status on fuel selection during submaximal exercise with glucose ingestion. Journal of Applied Physiology, 87(4), 1413–1420. PubMed Weir, J.B. (1949). New methods for calculating metabolic rate with special reference to protein metabolism. The Journal of Physiology, 109(1-2), 1–9. PubMed
Copyright of International Journal of Sport Nutrition & Exercise Metabolism is the property of Human Kinetics Publishers, Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use.
