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. 2012;7(5):e37407.
doi: 10.1371/journal.pone.0037407. Epub 2012 May 23.

Impact of environmental parameters on marathon running performance

Nour El Helou  1 , Muriel Tafflet, Geoffroy Berthelot, Julien Tolaini, Andy Marc, Marion Guillaume, Christophe Hausswirth, Jean-François Toussaint
Affiliations

Impact of environmental parameters on marathon running performance

Nour El Helou et al. PLoS One. 2012.

Abstract

Purpose: The objectives of this study were to describe the distribution of all runners' performances in the largest marathons worldwide and to determine which environmental parameters have the maximal impact.

Methods: We analysed the results of six European (Paris, London, Berlin) and American (Boston, Chicago, New York) marathon races from 2001 to 2010 through 1,791,972 participants' performances (all finishers per year and race). Four environmental factors were gathered for each of the 60 races: temperature (°C), humidity (%), dew point (°C), and the atmospheric pressure at sea level (hPA); as well as the concentrations of four atmospheric pollutants: NO(2)-SO(2)-O(3) and PM(10) (μg x m(-3)).

Results: All performances per year and race are normally distributed with distribution parameters (mean and standard deviation) that differ according to environmental factors. Air temperature and performance are significantly correlated through a quadratic model. The optimal temperatures for maximal mean speed of all runners vary depending on the performance level. When temperature increases above these optima, running speed decreases and withdrawal rates increase. Ozone also impacts performance but its effect might be linked to temperature. The other environmental parameters do not have any significant impact.

Conclusions: The large amount of data analyzed and the model developed in this study highlight the major influence of air temperature above all other climatic parameter on human running capacity and adaptation to race conditions.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Number of starters and finishers by marathon and year (missing data points for Boston, Chicago and Paris marathons).
Figure 2
Figure 2. Distribution of performances: example of men's performances distribution for Chicago (in 2002: T°C = 5.4°C; and in 2007: T°C = 25°C); and Paris (in 2002: T°C = 7.6°C; and in 2007: T°C = 17.4°C).
Figure 3
Figure 3. Quadratic second degree polynomial fit for Women's P1 running speeds vs. air temperature, r2 = 0.27; p<0.001; max = 9.9°C. B) Men's Q1 running speeds vs. air temperature, r2 = 0.24; p<0.001; max = 6°C.
Figure 4
Figure 4. Relationship between air temperature and the percentage of runners' withdrawals, modeled with a quadratic fit (blue curve, r2 = 0.36; p<0.0001).
The green curve represents the quadratic fit without the maxima (Chicago 2007: 30.74% withdrawals at a race temperature of 25°C).
See this image and copyright information in PMC

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