Nutritional behavior of cyclists during a 24-hour team relay race: a field study report

Bescós, Raúl; Rodríguez, Ferrán A.; Iglesias, Xavier; Knechtle, Beat; Benítez, Adolfo; Marina, Míchel; Padullés, Josep Maria; Torrado, Priscila; Vázquez, Jairo; Rosemann, Thomas

doi:10.1186/1550-2783-9-3

Cited by 29 publications

(22 citation statements)

References 48 publications

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“…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.…”

Section: Macronutrientscontrasting

confidence: 44%

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Energy Balance, Macronutrient Intake, and Hydration Status During a 1,230 km Ultra-Endurance Bike Marathon

Geesmann

Mester

Koehler

2014

International Journal of Sport Nutrition and Exercise Metabolism

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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.

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Section: Macronutrientscontrasting

confidence: 44%

“…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).…”

Section: Macronutrientsmentioning

confidence: 97%

Energy Balance, Macronutrient Intake, and Hydration Status During a 1,230 km Ultra-Endurance Bike Marathon

Geesmann

Mester

Koehler

2014

International Journal of Sport Nutrition and Exercise Metabolism

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“…It has been reported before, that the cycling speed during the training units was significantly and negatively related to race time (Knechtle et al, 2011, 2012b). Nevertheless, differences in race performances in ultra-endurance events can also result from various other influencing factors like race tactics, weather conditions, motivation (Lahart et al, 2013), sleep deprivation (Knechtle et al, 2012a), nutrition (Stewart and Stewart, 2007; Hulton et al, 2010; Bescós et al, 2012; Lahart et al, 2013; Paulin et al, 2015) and so on, which are not taken into account in this publication.…”

Section: Discussionmentioning

confidence: 99%

Training Intensity Distribution and Changes in Performance and Physiology of a 2nd Place Finisher Team of the Race across America Over a 6 Month Preparation Period

et al. 2016

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Aim: To monitor the training intensity distribution (TID) and the development of physiological and performance parameters.Methods: During their preparation period for the RAAM, 4 athletes (plus 1 additional backup racer) performed 3 testing sessions; one before, one after 3, and one after 6 months of training. VO2max, maximal rate of lactate accumulation (dLa/dtmax), critical power, power output at lactate minimum (MLSSP), peak and mean power output during a sprint test, heart rate recovery, isometric strength, jumping height, and body composition were determined. All training sessions were recorded with a power meter. The endurance TID was analyzed based on the time in zone approach, according to a classical 3-zone model, including all power data of training sessions, and a power specific 3-zone model, where time with power output below 50% of MLSSP was not considered.Results: The TID using the classical 3-zone model reflected a pyramidal TID (zone 1: 63 ± 16, zone 2: 28 ± 13 and zone 3: 9 ± 4%). The power specific 3-zone model resulted in a threshold-based TID (zone 1: 48 ± 13, zone 2: 39 ± 10, zone 3: 13 ± 4%). VO2max increased by 7.1 ± 5.3% (P = 0.06). dLa/dtmax decreased by 16.3 ± 8.1% (P = 0.03). Power output at lactate minimum and critical power increased by 10.3 ± 4.1 and 16.8 ± 6.2% (P = 0.01), respectively. No changes were found for strength parameters and jumps.Conclusion: The present study underlines that a threshold oriented TID results in only moderate increases in physiological parameters. The amount of training below 50% of MLSSp (~28% of total training time) is remarkably high. Researchers, trainers, and athletes should pay attention to the different ways of interpreting training power data, to gain realistic insights into the TID and the corresponding improvements in performance and physiological parameters.

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“…This cross-sectional data analysis is limited since aspects such as anthropometry [40,41], physiology [42], training [17,40,41], previous experience [17,43], pacing strategy [42,44], nutrition [3,18,45], fluid intake [46,47], and support during the race [17,40,41] were not included. Another weak point is the fact that the analysis is based on publicly available data, without any explanatory variables.…”

Section: Discussionmentioning

confidence: 99%

Age and gender difference in non-drafting ultra-endurance cycling performance - the ‘Swiss Cycling Marathon’

et al. 2013

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BackgroundIn recent years, there was an increased interest in investigating the gender difference in performance and the age of peak performance in ultra-endurance performances such as ultra-triathlon, ultra-running, and ultra-swimming, but not in ultra-cycling. The aim of the present study was to analyze the gender difference in ultra-cycling performance and the age of peak ultra-cycling performance in the 720-km ‘Swiss Cycling Marathon’, the largest European qualifier for the ‘Race Across America’.MethodsChanges in the cycling speed and age of 985 finishers including 38 women and 947 men competing in the Swiss Cycling Marathon from 2001 to 2012 covering a distance of 720 km with a change of altitude of 4,993 m were analyzed using linear regression.ResultsThe gender difference in performance was 13.6% for the fastest cyclists ever, 13.9% ± 0.5% for the three fastest cyclists ever and 19.1% ± 3.7% for the ten fastest cyclists ever. The gender difference in performance for the annual top three women and men decreased from 35.0% ± 9.5% in 2001 to 20.4% ± 7.7% in 2012 (r2 = 0.72, p = 0.01). The annual top three women improved cycling speed from 20.3 ± 3.1 km h−1 in 2003 to 24.8 ± 2.4 km h−1 in 2012 (r2 = 0.79, p < 0.01). The cycling speed of the annual top three men remained unchanged at 30.2 ± 0.6 km h−1 (p > 0.05). The age of peak performance for the ten fastest finishers ever was 35.9 ± 9.6 years for men and 38.7 ± 7.8 years for women, respectively (p = 0.47).ConclusionsThe gender difference in ultra-cycling performance decreased over the 2001 to 2012 period in the 720-km Swiss Cycling Marathon for the annual top three cyclists and reached approximately 14%. Both women and men achieved peak performance at the age of approximately 36 to 39 years. Women might close the gender gap in ultra-endurance cycling in longer cycling distances. Future studies need to investigate the gender difference in performance in the Race Across America, the longest nonstop and non-drafting ultra-cycling race in the world.

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Nutritional behavior of cyclists during a 24-hour team relay race: a field study report

Cited by 29 publications

References 48 publications

Energy Balance, Macronutrient Intake, and Hydration Status During a 1,230 km Ultra-Endurance Bike Marathon

Energy Balance, Macronutrient Intake, and Hydration Status During a 1,230 km Ultra-Endurance Bike Marathon

Training Intensity Distribution and Changes in Performance and Physiology of a 2nd Place Finisher Team of the Race across America Over a 6 Month Preparation Period

Age and gender difference in non-drafting ultra-endurance cycling performance - the ‘Swiss Cycling Marathon’

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