After "hitting the wall" in the New York Marathon, Benjamin Rapoport, an MD/PhD student in the Harvard-MIT Division of Health Sciences and Technology, decided to take a rigorous approach to calculating how fast any runner can reasonably hope to run a marathon, and just how much carbohydrate individual runners need to fuel their 26.2-mile races. The result is a new model, published October 21 in the open-access journal PLoS Computational Biology, which allows any runner to calculate those targets using an estimate of his or her aerobic capacity.

Of the hundreds of thousands of people who run a marathon each year, more than 40 percent hit the figurative wall. "Hitting the wall" occurs when carbohydrates, which the body relies on for energy during intense aerobic exercise, are completely depleted in the liver and leg muscles. This depletion forces the body to start burning fat, but fat metabolism uses oxygen less efficiently than carbohydrate metabolism and so runners are forced to slow down. Many runners also experience pain and fatigue with the abrupt transition to fat metabolism.

"People think hitting the wall is inevitable, but it's not," says Rapoport, a seasoned marathon runner. "In order to avoid it, you need to know what your capabilities are. You need to set a target pace that will get you to the finish without hitting the wall. Once you do that, you need to make sure you appropriately carbo-load."

To create his new model, Rapoport identified fundamental physiologic factors that vary from runner to runner and limit performance in endurance runners: aerobic capacity and the ability of the leg muscles to store carbohydrates as glycogen. Aerobic capacity, also known as VO2max, measures how rapidly the muscles can consume oxygen during aerobic exercise. Oxygen is critical to muscle performance because carbohydrates can only be broken down completely in the presence of oxygen.

Using Rapoport's model, any runner training for a marathon can figure out a pace he or she can sustain without hitting the wall. Additionally, the model allows runners to calculate how much carbohydrate they need to consume during the race if they want to run faster without hitting the wall.

Funding: This research was not funded.

Competing Interests: The author has declared that no competing interests exist.

Citation: Rapoport BI (2010) Metabolic Factors Limiting Performance in Marathon Runners. PLoS Comput Biol 6(10): e1000960. doi:10.1371/journal.pcbi.1000960

Source:
PLoS Computational Biology