International Journal of Environmental Research and Public Health

Article Performance and Thermal Perceptions of Runners Competing in the : Impact of Environmental Conditions

Tim Vernon * , Alan Ruddock and Maxine Gregory

Sport and Physical Activity Research Centre, Department of Sport and Physical Activity, Sheffield Hallam University, Sheffield S10 2BP, UK; [email protected] (A.R.); [email protected] (M.G.) * Correspondence: [email protected]; Tel.: +44-(0)-114-225-5761

Abstract: The 2018 Virgin Money (2018 VMLM) was the hottest in the race’s 37-year history. The aims of this research were to (1) survey novice mass participation marathoners to examine the perceptual thermal demands of this extreme weather event and (2) investigate the effect of the air temperature on finish times. A mixed-methods design involving the collection of survey data (n = 364; male = 63, female = 294) and secondary analysis of environmental and marathon performance (676,456 finishers) between 2001 and 2019 was used. The 2018 VMLM mean finishing time was slower than the mean of all other London ; there were positive correlations between maximum race day temperature and finish time for mass-start participants, and the difference in maximum race day temperature and mean maximum daily temperature for the 60 days before the London Marathon (p < 0.05). Of the surveyed participants, 23% classified their thermal sensation as ‘warm’, ‘hot’ or ‘very hot’ and 68% ‘thermally comfortable’ during training,   compared with a peak of 95% feeling ‘warm’, ‘hot’ or ‘very hot’ and 77% ‘uncomfortable’ or ‘very uncomfortable’ during the 2018VMLM. Organisers should use temperature forecasting and plan Citation: Vernon, T.; Ruddock, A.; countermeasures such as adjusting the start time of the event to avoid high temperatures, help runners Gregory, M. Performance and predict finish time and adjust pacing strategies accordingly and provide safety recommendations for Thermal Perceptions of Runners participants at high-risk time points as well as cooling strategies. Competing in the London Marathon: Impact of Environmental Conditions. Keywords: running; endurance; heat; thermoregulation; weather; cooling Int. J. Environ. Res. Public Health 2021, 18, 8424. https://doi.org/10.3390/ ijerph18168424

Academic Editor: Paul B. Tchounwou 1. Introduction Over one million runners participate in marathons annually [1], with the Virgin Received: 14 June 2021 Money London Marathon (VMLM) attracting around 40,000 participants. The demands of Accepted: 7 August 2021 marathon running are considerable irrespective of performance standard; the energy expen- Published: 10 August 2021 diture of female and male runners finishing between 2 and 4 h is within the region of 2000 to 2800 kcal, placing extensive strain on metabolic, cardiorespiratory, thermophysiological, Publisher’s Note: MDPI stays neutral mechanical and perceptual regulatory systems [2,3]. Such demands are intensified in hot with regard to jurisdictional claims in and humid conditions where finishing times are impaired [4–6], and in-race withdrawals published maps and institutional affil- increase, particularly when air temperature exceeds 20 ◦C[6]. iations. Substantial evidence supports the increased likelihood of extreme global weather events in the forthcoming decades, including periods of unseasonably cold and hot weather. In February and March 2018, the UK experienced two severe winter weather events with unseasonably low temperatures and significant snowfall [7]. For runners preparing for Copyright: © 2021 by the authors. the VMLM, these low temperatures posed logistical training demands (icy roads) and Licensee MDPI, Basel, . altered perceptual and physiological responses, potentially impairing preparation for a This article is an open access article spring marathon. These weather events were followed by unseasonably high temperatures distributed under the terms and between the 18th and 22nd of April, including the UK’s warmest April day since 1949 at conditions of the Creative Commons 29.1 ◦C. This coincided with the hottest London Marathon on record of 24.1 ◦C that took Attribution (CC BY) license (https:// place on Sunday 22nd April 2018 (10 am start), with many mass participation runners still creativecommons.org/licenses/by/ on course when this temperature was recorded. These data, however, do not capture the 4.0/).

Int. J. Environ. Res. Public Health 2021, 18, 8424. https://doi.org/10.3390/ijerph18168424 https://www.mdpi.com/journal/ijerph Int. J. Environ. Res. Public Health 2021, 18, 8424 2 of 9

potential environmental demands within the microclimate on course, whereby runners grouped nearby can experience increases in mean radiant temperature of 2 ◦C and humidity, coupled with decreases in radiative and convective heat transfer, increasing autonomic thermoregulatory challenges [8]. It is unclear how thermal sensation and comfort, which are integral to behavioural thermoregulation and dominant factors that dictate perceived exertion in hot conditions [9], are influenced in these specific environments. Furthermore, in the final weeks and days of marathon preparation, runners were faced with two conflicting extreme weather events. In the future, extreme weather events are likely to increase in either frequency and/or severity, posing risks to the short- and long-term health and wellbeing of marathon runners. As such, the aims of this research were to (1) identify historical temperature data for all London Marathons to place the extreme weather events of 2018 in context and (2) survey a sample of novice mass participation marathoners who started the 2018 VMLM to examine the thermal demands of the extreme weather event on race day. This investigation is the first in the context of the London marathon and warranted on the basis of (1) the addition to our knowledge and understanding of perceptual demands of mass participation runners in the Virgin Money London Marathon and (2) identification of potential areas whereby participants and race organisers might seek to change their practice in preparation for, or on the day of, the event when high temperatures are forecast.

2. Materials and Methods 2.1. Research Design A mixed-methods design involving the collection of survey data and the analysis of environmental and marathon performance data was used to examine the experiences of and the effects of air temperature on participants running a marathon in the heat. The local ethics committee approved the study (ER6896994). All participants provided digital informed consent, and the investigation was conducted in accordance with the Declaration of Helsinki (7th revision).

2.2. Participants The finish times of 676,456 finishers (male, 450,071; female, 226,385) of the London Marathon from 2001 to 2019 were extracted from the official website of the VMLM [10] and the marathon archives website [11]. This included the 40,179 participants who completed the 2018 VMLM (male, 23,701; female, 16,478). A random sample of participants (n = 364; male = 63, female = 294; age = 41.4 ± 8.3 years; mass = 72.2 ± 19.9 kg; stature = 168.6 ± 9.5 cm) from the 2018 VMLM (subsequently referred to as survey participants) completed an online survey relating to their expectations and experiences of the event, including expected and actual finish time, perception of temperature and thermal comfort during the marathon and during training over the winter months. The survey was distributed 7 days post-event via social media platforms and hosted on the Key Survey platform (www.keysurvey.co.uk—accessed 1 April 2018). The group was mostly inexperienced, with the 2018 VMLM being the first marathon for 63% of runners; 33% of runners had participated in between two and five marathons and only 4% had run more than six marathons. Participants were not invited to comment on the study design; however, they were consulted during the writing of a plain language summary for dissemination to their peers and distribution to participant groups.

2.3. Data Analysis Hourly temperature data (◦C) were acquired from the UK’s National Meteorological Service (the Met Office) for the date of the London Marathon and the preceding 60 days for the years 1981 to 2019. These data were recorded as per the Met Office standards at a meteorological station located in St James’s Park London, chosen for its central location on the London Marathon route. Data were processed, plotted and analysed alongside Int. J. Environ. Res. Public Health 2021, 18, x 3 of 9

meteorological station located in St James’s Park London, chosen for its central location Int. J. Environ. Res. Public Health 2021on, 18 the, 8424 London Marathon route. Data were processed, plotted and analysed alongside3 of 9 marathon performance data using customised Microsoft Excel Software (Microsoft Corp, 2013) and SPSS (Version 24.0. Armonk, NY: IBM Corp) and assumptions for parametric statistical analyses were performed. Pearson product-moment correlation was used to in- vestigatemarathon relationships performance between data using maximum customised race Microsoft day air Exceltemperature Software and (Microsoft the differential Corp, 2013) and SPSS (Version 24.0. IBM Corp, Armonk, NY, USA) and assumptions for paramet- temperature between race day temperature and average maximum temperature for the ric statistical analyses were performed. Pearson product-moment correlation was used to previous 60 days (race day temp–average max temp over previous 60 days) on the average investigate relationships between maximum race day air temperature and the differential Londontemperature Marathon between finish race time day between temperature 2001 and and average 2019. Thresholds maximum temperatureof 0.1, 0.3 and for 0.5 the for small,previous moderate 60 days and (race large day temp–averagecorrelations [12] max and temp 0.7 over and previous 0.9 for very 60 days) large on and the averageextremely largeLondon correlations Marathon [13] finish were time used between to interp 2001ret and relationships 2019. Thresholds between of variables. 0.1, 0.3 and Independ- 0.5 for entsmall, t-tests moderate were performed and large correlationsto assess the [ 12differ] andence 0.7 andin London 0.9 for veryMarathon large andfinish extremely times, air temperaturelarge correlations and expected [13] were versus used toactual interpret finish relationships time from survey between respondents. variables. Indepen- Statistical significancedent t-tests was were set performed at p < 0.05. to assess Thermal the differencesensation in[14] London and comfort Marathon data finish [15] times, were air ana- lysedtemperature using a Friedman and expected test versusand Dunn-Bonferroni actual finish time post from hoc survey test, and respondents. statistical Statisticalsignificance wassignificance set at p < was0.05. set at p < 0.05. Thermal sensation [14] and comfort data [15] were analysed using a Friedman test and Dunn-Bonferroni post hoc test, and statistical significance was 3.set Results at p < 0.05. 3.1.3. ResultsEnvironmental Data 3.1.The Environmental maximum Data air temperature recorded by the Met Office on the day of the 2018 VMLMThe was maximum 24.1 °C, hotter air temperature than the mean recorded maximum by the race Met day Office temperature on the day for of every the 2018 other yearVMLM (15.2 was ± 3.3 24.1 °C).◦C, The hotter maximum than the daily mean temperature maximum race in day the temperature60 days before for everythe 2018 other race dayyear was (15.2 also± 3.3lower◦C). than The previous maximum years daily (11.3 temperature ± 6.3 °C in vs. the 12.1 60 days± 1.6 before°C), demonstrated the 2018 race in Figureday was 1, which also lower also thanshows previous the three years extr (11.3eme± weather6.3 ◦C vs. events 12.1 ±of1.6 2018◦C), (a, demonstrated b and c). in Figure1, which also shows the three extreme weather events of 2018 (a, b and c).

◦ FigureFigure 1. Maximum 1. Maximum daily daily air airtemperature temperature (°C) ( inC) the in the60 days 60 days lead leadinging up upto London to London Marathon Marathon race race day day for for2018 2018 and and mean ± SDmean across± SD all acrossother allyears other 1981–2017 years 1981–2017 and 2019. and 2019.

3.2.3.2. Finish Finish Time Time TheThe total total field field ( (nn == 40,179) 40,179) mean completioncompletion timetime for for the the VMLM VMLM 2018 2018 was was 20 20 min min slower than the mean of all other years between 2001 and 2019 (290 ± 55.5 min vs. slower than the mean of all other years between 2001 and 2019 (290 ± 55.5 min vs. 270 ± 270 ± 64.1 min). There was a very large positive correlation (r = 0.89, p < 0.05) between 64.1 min). There was a very large positive correlation (r = 0.89, p < 0.05) between maximum maximum race day temperature and mean completion time for mass participation runners race day temperature and mean completion time for mass participation runners (n = (n = 676,456) (Figure2a), and a very large positive correlation (r = 0.85, p < 0.05) between 676,456)the differential (Figure between2a), and racea very day large temperature positive and correlation mean maximum (r = 0.85, daily p < temperature0.05) between for the differentialthe 60 days between before the race London day temperature Marathon and and mean mean completion maximum time daily for masstemperature participation for the 60runners days before (Figure the2b). London Marathon and mean completion time for mass participation runners (Figure 2b).

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Figure 2. (a) Relationship between maximum race day temperature and mean finish time in the London Marathon 2001 to FigureFigure 2. (a) Relationship2. (a) Relationship between between maximum maximum race race day day temperature temperature an andd mean mean finish finish time in thethe London London Marathon Marathon 2001 2001 to to 2019. (b) Relationship between the difference in maximum race day temperature and maximum daily temperature during 2019. (b2019.) Relationship (b) Relationship between between the differencethe difference in maximum in maximum race race day day temperature temperature andand maximum daily daily temperature temperature during during the 60 days prior to race day on mass participation and mean finish time in the London Marathon 2001 to 2019; stderror, the 60 thedays 60 priordays priorto race to dayrace onday mass on mass participation participation and and me meanan finish finish time time in in the the LondonLondon Marathon 2001 2001 to to 2019; 2019; stderror, stderror, standard error of the estimate; COV, coefficient of variation. standardstandard error oferror the of estimate; the estimate; COV, COV, coefficient coefficient of variation.of variation. The mean finish time of survey participants for the 2018 VMLM (Figure3) was The mean finish time of survey participants for the 2018 VMLM (Figure 3) was 337 ± 337The± 51mean min, finish slower time than of the survey overall participants mean finish time for the for the2018 2018 VMLM VMLM (Figure of 290 ±3) 64was min 337 ± 51 min, slower than the overall mean finish time for the 2018 VMLM of 290 ± 64 min and 51 min,and 47slower± 30 than min orthe 14% overall slower mean than finish the survey time for participants the 2018 VMLM reported of estimated 290 ± 64 min time and 47 ± 30 min or 14% slower than the survey participants reported estimated time (p < 0.05). 47 ±(p 30< 0.05).min or 14% slower than the survey participants reported estimated time (p < 0.05).

FigureFigure 3. 3.Estimated Estimated versus versus actual actual finish finish times times in in the the 2018 2018 VMLM VMLM for for survey survey participants. participants.

ForFor thosethose whowho hadhad runrun marathonsmarathons previously,previously, the the mean mean finish finish time time for for the the 2018 2018 FigureVMLMVMLM 3. Estimated was was 40 40± versus± 27 min actual slower finish than than times their their in previous previousthe 2018 VMLMbest best marathon marathon for survey time time participants. (317 (317 ± ±7171 min min vs. vs.278278 ± 60± min;60 min p <; 0.05).p < 0.05). Out Outof 101 of runners 101 runners who had who previously had previously run a runmarathon, a marathon, one runner one runnerranFor faster those ran in faster who2018 in VMLMhad 2018 run VMLM by marathonsapproximately by approximately previously, 1 min. 1 min. the mean finish time for the 2018 VMLM was 40 ± 27 min slower than their previous best marathon time (317 ± 71 min vs. 278 ± 60 min; p < 0.05). Out of 101 runners who had previously run a marathon, one runner ran faster in 2018 VMLM by approximately 1 min.

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3.3. Perception of Heat 3.3. PerceptionTo assess thermal of Heat sensation, an eight-point scale (very cold (1) to very hot (8), ‘very hot’ addedTo assess to the thermal original sensation, ASHRAE an 2017 eight-point scale) was scale used (very to ask cold participants, (1) to very ‘How hot (8), hot ‘very did youhot’ feel added during to the the original marathon, ASHRAE and how 2017 does scale) this was compare used towith ask your participants, training?’ ‘How They hotre- porteddid you feeling feel during hotter the(p < marathon, 0.01) during and the how 2018 does VMLM this compare(mean = 6.8 with ± 1.1, your median training?’ = 7) com- They paredreported with feeling a typical hotter training (p < 0.01) run during(mean = the 4.2 2018 ± 1.7, VMLM median (mean = 4) =(Figure 6.8 ± 1.1,4). Runners median =felt 7) hottercompared as the with race a progressed typical training (0 to run10 km (mean compared = 4.2 ± with1.7, all median sections, = 4) p (Figure < 0.01)4 (0). Runnersto 10 km meanfelt hotter = 6.2 ± as 1.2, the median race progressed = 6; 11 to 20 (0 km to 10 mean km compared= 6.9 ± 1.0, withmedian all = sections, 7; 21 to 30p < km 0.01) mean (0 to= 7.210 km± 0.9, mean median = 6.2 =± 7;1.2, 31 to median 42 km = mean 6; 11 to= 7.0 20 km± 1, meanmedian = 6.9= 7),± with1.0, median 76% feeling = 7; 21 ‘warm’ to 30 km to ‘verymean hot’ = 7.2 in± the0.9, first median 10 km, =7; increasing 31 to 42 km to mean91% of = participants 7.0 ± 1, median after = the 7), withfirst 10 76% km. feeling The percentage‘warm’ to ‘very of participants hot’ in the firstwho 10 felt km, ‘warm’ increasing to ‘very to 91%hot’ ofduring participants a typical after training the first run 10 was km. 23%.The percentage of participants who felt ‘warm’ to ‘very hot’ during a typical training run was 23%.

FigureFigure 4. ThermalThermal sensation sensation during during the the VMLM 2018 and a typical trainingtraining session during winter/springwinter/spring in in the the UK UK in in preparationpreparation for the 2018 VMLM.

RunnersRunners felt felt more more comfortable comfortable with with their theirbody temperature body temperature during training during (mean training = 3.5(mean ± 0.9, = median 3.5 ± 0.9, = 4) median compared = 4) with compared all sections with of all the sections 2018 VMLM of the (0 2018 to 10 VMLM km mean (0 to= ± ± 2.810 km± 1.0, mean median = 2.8 = 3;1.0, 11 medianto 20 km = mean 3; 11 to = 202.3 km ± 0.9, mean median = 2.3 = 2;0.9, 21 median to 30 km = 2;mean21 to = 30 1.9 km ± ± ± 0.9,mean median = 1.9 = 2;0.9, 31 medianto 42 km = mean 2; 31 = to 2.0 42 ± km 0.9; mean median =2.0 = 2). Runners0.9; median felt increasingly = 2). Runners more felt uncomfortableincreasingly more as the uncomfortable race progressed as the (0 to race 10 progressedkm compared (0 to with 10 kmall comparedother sections, with p all < other sections, p < 0.05); however, there was no significant change in thermal comfort from 0.05); however, there was no significant change in thermal comfort from 21 to 42 km). The 21 to 42 km). The percentage of runners feeling ‘uncomfortable’ or ‘very uncomfortable’ percentage of runners feeling ‘uncomfortable’ or ‘very uncomfortable’ increased from 37% increased from 37% during the first 10 km to 77% between kilometres 21 and 30 (Figure5 ). during the first 10 km to 77% between kilometres 21 and 30 (Figure 5). The majority of The majority of participants felt ‘comfortable’ during a typical training run; 11% of respon- participants felt ‘comfortable’ during a typical training run; 11% of respondents felt ‘un- dents felt ‘uncomfortable’ or ‘very uncomfortable’ with the temperature during a typical comfortable’ or ‘very uncomfortable’ with the temperature during a typical training run. training run.

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FigureFigure 5. Thermal 5. Thermal comfort comfort during during 2018 2018 VMLM VMLM and aa typical typical training training session session during during winter/spring winter/sprin in theg UKin the in preparation UK in prepara- tion forfor this this event.

4. Discussion4. Discussion ToTo our our knowledge, knowledge, this this investigation is is the the first first to to analyse analyse historical historical weather weather data ofdata of the London Marathon in the context of previous weather data, assess thermoperceptual the London Marathon in the context of previous weather data, assess thermoperceptual demands and determine the effect of ambient temperature on the finish time of runners. demandsThe findings and fromdetermine this investigation the effect areof ambient that: (1) The temperature 2018 VMLM on was the hotter finish than time the of mean runners. Theof findings all other Londonfrom this Marathons. investigation (2) The are 2018 that: VMLM (1) meanThe 2018 finishing VMLM time was slowerhotter than than the meanthe of mean all other of all otherLondon London Marathons. Marathons. (2) (3)The In 2018 accordance VMLM with mean the finishing aforementioned time was major slower thanfindings, the mean we foundof all other a positive London correlation Marathons. between (3) maximumIn accordance race daywith temperature the aforementioned and majorfinish findings, time for we mass found participants, a positive whereby correlation a hotter between temperature maximum was related race day to a temperature slower andfinish finish time. time (4) Wefor alsomass found participants, a positive correlationwhereby a between hotter thetemperature difference inwas maximum related to a slowerrace dayfinish temperature time. (4) We and also the found mean maximuma positive dailycorrelation temperature between for the the difference 60 days prior in max- to the London Marathon, whereby a hotter race day temperature compared with mean imum race day temperature and the mean maximum daily temperature for the 60 days training temperature resulted in a slower marathon finish time. (5) Only 23% of surveyed priorparticipants to the London classified Marathon, their thermal whereby sensation a ho astter ‘warm’, race ‘hot’day ortemperature ‘very hot’ during compared their with meantraining training period temperature compared with resulted a peak in of 95%a slower of participants marathon feeling finish ‘warm’, time. ‘hot’(5) Only or ‘very 23% of surveyedhot’ during participants the 2018VMLM. classified (6) their A total thermal of 68% ofsensation surveyed as participants ‘warm’, ‘hot’ felt or ‘comfortable’ ‘very hot’ dur- ingwith their their training body period temperature compared during with training, a peak whereas of 95% a of peak participants of 77% felt feeling ‘uncomfortable’ ‘warm’, ‘hot’ or ‘veryor ‘very hot’ uncomfortable’ during the 2018 during VMLM. the 2018 (6) VMLM. A total of 68% of surveyed participants felt ‘com- fortable’Our with findings their thatbody the temperature 2018 VMLM during was hotter training, and the whereas finish time a peak slower of than 77% previous felt ‘uncom- fortable’London or Marathons ‘very uncomforta are in accordanceble’ during with previousthe 2018 researchVMLM. indicating that finish times are slower in hot conditions compared with cooler conditions [4–6]. Predictions of performance Our findings that the 2018 VMLM was hotter and the finish time slower than previ- impairment based on ambient temperature suggest a decrease in finish time between 1.5 ousand London 2% for Marathons every 5 ◦C are increase in accordance in ambient with temperature previous above research 10–12 indicating◦C[16,17]. that Our finish timesdata, are which slower relate in specificallyhot conditions to our compared sample from wi theth cooler London conditions Marathon with[4–6]. mean Predictions finish of performancetimes between impairment 260 and 290 based min, on suggest ambient there temp is approximatelyerature suggest a 2.8% a decrease decrease in finishfinish time betweentime for 1.5 every and 52%◦C for increase every in5 °C ambient increase temperature in ambient above temperature 12 ◦C. An ab approximateove 10–12 °C 2.6% [16,17]. Ourdecrease data, which in finish relate time specifically for every 5 ◦ toC increaseour sample in temperature from the London differential Marathon is also evident with mean finishwhen times considering between the 260 difference and 290 between min, suggest maximum there race is dayapproximately temperature a and 2.8% the decrease mean in finishtemperature time for 60every days 5 before °C increase the London in ambient Marathon. temperature This knowledge above is 12 important °C. An approximate because it could be used before any London marathon to adjust pacing strategies by taking into 2.6% decrease in finish time for every 5 °C increase in temperature differential is also evi- account the St James Park weather forecast. For example, a runner with an expected dentfinish when time considering of 3 h 59 min the derived difference from between training datamaximum before therace London day temperature Marathon at and a the meanmean temperature temperature 60 of 12days◦C wouldbefore need the toLondon adjust their Marathon. performance This time knowledge by approximately is important because it could be used before any London marathon to adjust pacing strategies by taking into account the St James Park weather forecast. For example, a runner with an expected finish time of 3 h 59 min derived from training data before the London Marathon at a mean temperature of 12 °C would need to adjust their performance time by approximately 5.6%, from a mean pace of 5:40 min/km to 5:59 min/km if the expected maximum daily temperature at St James Park was forecast to be 22 °C.

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5.6%, from a mean pace of 5:40 min/km to 5:59 min/km if the expected maximum daily temperature at St James Park was forecast to be 22 ◦C. Based on the 2018 VMLM temperature data, the expected performance decrement was approximately 6.6%; however, our sample of runners experienced a 14% decrement in finish time compared with their estimated finish time. Although we are not able to confirm the reasons for this difference, one explanation for this discrepancy might be accounted for by the pacing strategies employed by respondents who attempted to start the race at their expected race pace rather than adjust their pace to offset the impact of higher- than-expected temperatures on thermophysiological, energetic and perceptual demands. This discrepancy may be further accounted for by increases in microclimate temperature, in particular an increase in relative humidity caused by evaporative heat loss through sweating and respiration in our sample of runners, who were likely running together in tight groups with limited airflow. Indeed, 101 runners in the present sample ran slower than their previous marathon best, indicating that the environmental conditions in the lead- up to the marathon and on the day of the event influenced performance to a large extent. However, it is also likely that the expected finish time of runners would be faster than their actual completion time even in typical temperatures, given that most runners in this sample were novices and runners, in general, are optimistic about their performances before a race. The complex interactions between environmental conditions, pacing strategies and runners’ previous experience likely account for this 14% discrepancy. This discrepancy highlights the importance of monitoring training data in the weeks before a marathon to accurately predict finish time before taking into account the impact of weather on health, wellbeing and performance. Only 23% of surveyed participants classified their thermal sensation as ‘warm’, ‘hot’ or ‘very hot’, respectively, during their training period compared with a peak of 95% of participants feeling ‘warm’, ‘hot’ or ‘very hot’ during the 2018 VMLM. Moreover, 68% of surveyed participants felt their thermal comfort during training was ‘comfortable’, whereas a peak of 77% felt ‘uncomfortable’ and ‘very uncomfortable’ during the 2018 VMLM. During exercise in hot environments, the two key inputs directly related to the rating of perceived exertion (RPE) are the rate of increase in and/or magnitudes of thermal sensation, thermal comfort and cardiovascular strain [9]. Initial predictions regarding the intensity of exercise are primarily made based upon skin temperature, which has a large influence on ratings of thermal comfort and thermal sensation, followed by cardiovascular strain and ventilatory rate (breathlessness). It is possible that at the start of the marathon, when ratings of thermal sensation and comfort were more similar to training, RPE and, thus, pacing were also the same. Ratings of thermal sensation and comfort are important from both thermoregulatory and homeostatic perspectives as increases in both likely reflect an increase in whole-body thermophysiological demand, in particular body temperature and significant cardiovascular challenges to maintain homeostasis. Approximately 70% of respondents felt ‘hot’ from 11–20 km, peaking at 80% between 21–30 km, compared with 40% in the first 10 km. We do not have medical records accompanying these data; however, previous research conducted on the , which was also relatively hot (air temperature = 19.1 ◦C) compared with previous years (air temperature = 11.6 ◦C), reported a mean finish time 17 min slower than previous years. In the 2007 London Marathon, there were 5032 runners treated by St John’s Ambulance, 73 hospitalisations, 6 cases of severe electrolyte imbalance and 1 death (hyponatraemia) compared with the (air temperature = 9.9 ◦C) in which the number of runners treated was 4000. It is not possible to isolate heat-related issues within these figures [18]; however, there is an association between the percentage of withdrawals from races and increasing air temperature over 15 ◦C[6]. Given the several risk factors associated with exercise in hot environments [19], global recommendations for event cancellation based on Wet Bulb Globe Temperature (WBGT) should be considered as a guide [20]. The American College of Sports Medicine [21] and Roberts [18] suggest that non-elite runners should be closely monitored, and event organisers should also consider the cancellation of the event if the Int. J. Environ. Res. Public Health 2021, 18, 8424 8 of 9

WBGT is within the range of 18.4 ◦C and 22.2 ◦C. These recommendations, however, do not take into account the acclimation state of runners and given the unseasonably low temperatures preceding the 2018 VMLM, it is reasonable to assume that the majority of mass participation runners, who trained in the UK, would not have had the opportunity to prepare in environmental conditions similar to race day. Indeed, our analysis suggests a strong relationship between the difference in maximum race day temperature and the mean maximum daily temperature for the 60 days before the London Marathon (Figure2b).

4.1. General Practical Recommendations Organisers of marathons, especially those in the and Northern Europe, should follow existing guidance on exercise in hot environments, particularly regarding fluid balance and provision of practical cooling strategies [20,22]. Specifically, organisers should (1) keep detailed logs of environmental temperature in the preparatory phases leading up to the event, use temperature forecasting and plan countermeasures such as adjusting the start time of the event to avoid high temperatures; (2) help runners predict finish time and adjust pacing strategies accordingly using temperature-based data analysis; and (3) use data regarding thermal perception to provide recommendations for participants regarding high-risk time points of events to help alleviate discomfort.

4.2. Limitations The demographics of the survey respondents are not a fully representative sample of those participating in the marathon, as our sample were predominantly female, of middle age and slower than the average runner. The survey was released 7 days after the marathon, increasing the reliance on respondents to accurately recall events from race day. The weather data measured at St James’s Park, London, was chosen for its central location but may not be representative of the weather along the entire course. Similarly, while it is appreciated that not all marathon participants would have prepared for the marathon in or around London, the use of this meteorological site to quantify the extreme cold events in Spring 2018 allowed direct comparison with race day temperatures on the marathon course. The extreme weather events experienced in London and captured in the data from the St James’s Park London station in the lead-up to the 2018 VMLM are used as a reflection of the conditions that were experienced across the rest of the UK and large parts of Europe. While we are able to conclude that a runner’s pace slows with increased race day temperature, we are unable to identify whether this is a conscious decision or a subconscious response to the increased physiological demand placed on them by the high temperature. Future research should aim to capture the responses of a more representative sample of runners, initiate and capture data earlier and collect primary data during the marathon using wearable sensors and multiple environmental condition sensors along the course.

5. Conclusions The 2018 VMLM was hotter than previous marathons; this subsequently slowed runners finishing time and made runners feel ‘very hot’ and ‘uncomfortable’ for the majority of the race. Our findings have several practical implications, most notably the utilisation of a specific analysis on predicted race day temperature and expected finish time, as well as the identification of time points of the race that coincide with increased thermal demand. Integrating a range of strategies highlighted as a result of this research could help make the race safer and more enjoyable for mass participation runners.

Author Contributions: Conceptualization, T.V., M.G. and A.R.; methodology, T.V., M.G. and A.R.; software, M.G.; validation, T.V., M.G. and A.R.; formal analysis, T.V., M.G. and A.R.; data curation, T.V., M.G. and A.R.; writing—original draft preparation, T.V., M.G. and A.R.; writing—review and editing, T.V., M.G. and A.R.; visualization, T.V.; supervision, A.R.; project administration, T.V. All authors have read and agreed to the published version of the manuscript. Funding: This research received no external funding. Int. J. Environ. Res. Public Health 2021, 18, 8424 9 of 9

Institutional Review Board Statement: The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Ethics Committee of Sheffield Hallam University (Converis number ER6896994, 22 May 2018). Informed Consent Statement: Informed consent was obtained from all subjects involved in the study. Data Availability Statement: All meteorological and race data are available online at the websites of the Met Office and the VMLM. Aggregated and anonymised survey data are available on request. Conflicts of Interest: The authors declare no conflict of interest.

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