Monday, October 28, 2013

High energy deficit in an ultraendurance athlete in a 24-hour ultracycling race

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High energy deficit in an ultraendurance athlete in a 24-hour ultracycling race
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High energy deficit in an ultraendurance athlete in a 24-hour ultracycling race
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Access the profile card for user: Christopher Williams Christopher Williams
Posted Date:
October 26, 2013 3:48 PM
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Published
 Chris Williams
 Research Review 3
   KINE 5306 – (Advanced Nutrition)

High energy deficit in an ultraendurance athlete in a 24-hour ultracycling race

Reference

Bescós, R., Rodríguez, F. A., Iglesias, X., Benítez, A., Marina, M., Padullés, J. M., . . . Knechtle, a. B. (2012). High energy deficit in an ultraendurance athlete in a 24-hour ultracycling race. Baylor University Medical Center Proceedings. 25, pp. 124–128. Waco: Baylor University Medical Center.

Purpose of Study
The purpose of the case study was to examine the nutritional behavior and energy balance of a finisher of a 24-hour ultracycling race. 
Methods and Materials
The single subject was an athlete 39 years of age and cycled 557.3 km with 8760 miles of altitude at an average speed of 25.1 km/h for 22 hours and 22 minutes.  The food and fluids consumed by the cyclist was monitored and recorded during the race, as well as heart rate (HR), to assess the effects of the energy level of the athlete.  The average air temperature during the race was 27.5ºC with a relative humidity of 53.9%, and the mean velocity of wind at 1.7 m/s.  The initial VO2 test was taken a week before the competition on a braked cycle ergometer. 
Four trained investigators examined and measured all food and fluid intake during the race and the nutritional data was analyzed for nutrient composition using nutritional software.  A heart rate monitor was used to measure the cyclist’s HR throughout the entirety of the event.  The relationship between HR and VO2 gathered during laboratory testing was used to estimate the amount of energy and oxygen used.
Summary of Results and Conclusion
The average HR for the cyclist during the event was 131 beats/min, with a ratio of HRmean/HRmax of 0.69.  The subject made a total of seven stops that totaled 1 h 38 min and expended 15,533 kcal of energy averaging 647 kcal/hour.  During the event 73% (4058 kcal) of total energy came from solid foods while the other 27% (1513 kcal) came from fluids such as sports drink.  Carbohydrates were the main source of macronutrients the cyclist ingested (1102 g; 13.1 g/kg).  The subject consumed 20.7 L (862 mL/h) of fluids and 16,182 mg (34.0 mmol/L) of sodium.  7-19 hours into the event the subject increased his caffeine intake to 231 mg (2.7 mg/kg), a small amounts of branched chain amino acids in the form of a pill, and took an ibuprofen at 9h and two aspirin at 18 hrs.
The athlete lost 2.6 kg of total body mass (prerace, 84.2 kg; postrace, 81.6 kg) and had a total deficiency of 9915 kcal after the race.  It was found that the higher proportion (64%) of energy came from the cyclist own fuel stores, not added nutrients.
Critique of the Study
The study was unique in its attempt to track a single subject and monitor their energy levels.  The results illustrated that there may be more influence on energy by what the ultra-endurance athlete consumed prior to the event verses during the event.  A few limitations caught my attention while reading this study.  One is that the racer finished third and may be very well trained which may have led to the case study finding that his energy was not significantly influenced by his diet during the event.  Others is that the environmental conditions changed during the race and the cyclist took stops, and aspirin, which may have altered some variables.
Practical Application of the Study
This study may only be applicable to other ultra-endurance athletes since it was a case study focused on only one cyclist.  What athletes like the one studied should take from this research is that their diets months and or days before competition will play the biggest role in their energy levels when competing.
Questions
What would this case study look like if it was done on an ultra-marathon runner?

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