Performance and Thermal Perceptions of Runners Competing in the London Marathon: Impact of environmental conditions (original) (raw)
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The Tokyo 2020 Olympic Games will be held in July and August. As these are the hottest months in Tokyo, the risk of heat stress to athletes and spectators in outdoor sporting events is a serious concern. This study focuses on the marathon races, which are held outside for a prolonged time, and evaluates the potential heat stress of marathon runners using the COMFA (COMfort FormulA) Human Heat Balance (HBB) Model. The study applies a four-step procedure: (a) measure the thermal environment along the marathon course; (b) estimate heat stress on runners by applying COMFA; (c) identify locations where runners may be exposed to extreme heat stress; and (d) discuss measures to mitigate the heat stress on runners. On clear sunny days, the entire course is rated as 'dangerous' or 'extremely dangerous', and within the latter half of the course, there is a 10-km portion where values continuously exceed the extremely dangerous level. Findings illustrate which stretches have the highest need for mitigation measures, such as starting the race one hour earlier, allowing runners to run in the shade of buildings or making use of urban greenery including expanding the tree canopy.
Increased risk of heat stress conditions during the 2022 Comrades Marathon
South African Journal of Science
The Comrades Marathon is South Africa’s – and the world’s – most recognised and largest ultra-marathon event, with over 15 000 participants from across the globe competing in the 89-km road running event each year. Historically, the event has been held before the start of austral winter (20 May – 17 June). However, in 2022, organisers of the race moved the event to 28 August, when austral spring commences. We explore the climate, in particular the Universal Thermal Comfort Index (UTCI), of past Comrades events (1980-2019) and compare these data to UTCI data of the new proposed date (28 August) for the same period. The climatology for May, June, July and August was determined to identify periods with the lowest risk for ‘strong’ to ‘very strong’ heat stress. Results show that participants’ risk of exposure to ‘strong’ heat stress and ‘very strong’ heat stress periods will be more likely if the event is held in August as compared to the original event dates. Therefore, it is concluded...
Impact of Environmental Parameters on Marathon Running Performance
PLoS ONE, 2012
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 (uC), humidity (%), dew point (uC), 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 (mg.m 23). 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.
Effects of weather on the performance of marathon runners
International Journal of Biometeorology, 2010
The effects of air temperature, relative and specific humidity, wind speed, solar shortwave radiation, thermal longwave radiation, and rain on the performance of participants in the annual Stockholm Marathon from 1980 to 2008 were analysed statistically. The objective was to validate and extend previous studies by including data on finishing times of slower male and female runners and on the percentage of non-finishers. Due to decadal trends in the finishing time not related to weather, the finishing time anomaly (FTA) was calculated as the deviation of the annual finishing time from the linear trend of the finishing time. In all categories of runners, the single weather parameter with highest correlation with the FTA was the air temperature (correlation coefficient r=0.66-0.73, with the highest values for slowest runners). Also, the solar shortwave radiation (r=0.41-0.71), air relative humidity (r=−0.57 to −0.44) and, for male runners, the occurrence of rain (r=−0.51 to −0.42) reached a statistically significant correlation with the FTA, but the effects of the relative humidity and rain only arose from their negative correlation with the air temperature. The percentage of non-finishers (PNF) was significantly affected by the air temperature and specific humidity (r=0.72 for multiple regression), which is a new result. Compared to faster runners, the results of slower runners were more affected by unfavourable weather conditions; this was previously known for runners with finishing times of 2.1-3 h, and now extended to finishing times of 4.7 h. Effects of warm weather were less evident for female than male runners, which was probably partly due to female runners' larger ratio of surface area to body mass and slower running speed.
Defining the determinants of endurance running performance in the heat
Temperature
In cool conditions, physiologic markers accurately predict endurance performance, but it is unclear whether thermal strain and perceived thermal strain modify the strength of these relationships. This study examined the relationships between traditional determinants of endurance performance and time to complete a 5-km time trial in the heat. Seventeen club runners completed graded exercise tests (GXT) in hot (GXTHOT; 32 C, 60% RH, 27.2 C WBGT) and cool conditions (GXTCOOL; 13 C, 50% RH, 9.3 C WBGT) to determine maximal oxygen uptake (V̇O 2max), running economy (RE), velocity at V̇O 2max (vV̇O 2max), and running speeds corresponding to the lactate threshold (LT, 2 mmol.l ¡1) and lactate turnpoint (LTP, 4 mmol.l ¡1). Simultaneous multiple linear regression was used to predict 5 km time, using these determinants, indicating neither GXTHOT (R 2 D 0.72) nor GXTCOOL (R 2 D 0.86) predicted performance in the heat as strongly has previously been reported in cool conditions. vV̇O 2max was the strongest individual predictor of performance, both when assessed in GXT HOT (r D ¡0.83) and GXT COOL (r D ¡0.90). The GXTs revealed the following correlations for individual predictors in GXT HOT ; V̇O 2max
British Journal of Sports Medicine, 2022
PurposeTo determine associations between thermal responses, medical events, performance, heat acclimation and health status during a World Athletics Championships in hot-humid conditions.MethodsFrom 305 marathon and race-walk starters, 83 completed a preparticipation questionnaire on health and acclimation. Core (Tcore; ingestible pill) and skin (Tskin; thermal camera) temperatures were measured in-competition in 56 and 107 athletes, respectively. 70 in-race medical events were analysed retrospectively. Performance (% personal best) and did not finish (DNF) were extracted from official results.ResultsPeak Tcore during competition reached 39.6°C±0.6°C (maximum 41.1°C). Tskin decreased from 32.2°C±1.3°C to 31.0°C±1.4°C during the races (p<0.001). Tcore was not related to DNF (25% of starters) or medical events (p≥0.150), whereas Tskin, Tskin rate of decrease and Tcore-to-Tskin gradient were (p≤0.029). A third of the athletes reported symptoms in the 10 days preceding the event, mai...
Influence of temperature and performance level on pacing a 161 km trail ultramarathon
International journal of sports physiology and performance, 2011
Even pacing has been recommended for optimal performances in running distances up to 100 km. Trail ultramarathons traverse varied terrain, which does not allow for even pacing. This study examined differences in how runners of various abilities paced their efforts in the Western States Endurance Run (WSER), a 161 km trail ultramarathon in North America, under hot vs cooler temperatures. Temperatures in 2006 (hot) and 2007 (cooler) ranged from 7-38°C and 2-30°C, respectively. Arrival times at 13 checkpoints were recorded for 50 runners who finished the race in both years. After stratification into three groups based on finish time in 2007 (<22, 22-24, 24-30 h), paired t tests were used to compare the difference in pace across checkpoints between the years within each group. The χ2 test was used to compare differences between the groups on the number of segments run slower in the hot vs cooler years. For all groups, mean pace across the entire 161 km race was slower in 2006 than in...
Deviation from goal pace, body temperature and body mass loss as predictors of road race performance
Journal of science and medicine in sport, 2017
The purpose of this study was to examine the relationship between pacing, gastrointestinal temperature (TGI), and percent body mass loss (%BML) on relative race performance during a warm weather 11.3km road race. Observational study of a sample of active runners competing in the 2014 Falmouth Road Race. Participants ingested a TGI pill and donned a GPS enabled watch with heart rate monitoring capabilities prior to the start of the race. Percent off predicted pace (%OFF) was calculated for seven segments of the race. Separate linear regression analyses were used to assess the relationship between pace, TGI, and %BML on relative race performance. One-way ANOVA was used to analyse post race TGI (≥40°C vs <40°C) on pace and %OFF. Larger %BML was associated with faster finish times (R(2)=0.19, p=0.018), faster average pace (R(2)=0.29, p=0.012), and a greater %OFF (R(2)=0.15, p=0.033). %OFF during the first mile (1.61km) significantly predicted overall finish time (R(2)=0.64, p<0.0...