Heat Acclimation Knowledge among Recreational Runners

at acclimation (HA) is the foremost method of preventing exertional heat illness during exercise in hot and humid environments. However, the prevalence of HA training and its associated knowledge is not currently known in recreational running populations. The purpose of this study was to determine the knowledge of recreational runners toward HA. A survey consisting of 38 questions that required approximately 10–15 min to complete was disseminated to running clubs throughout the Southeastern United States. Questions were designed to collect data on participant demographics, yearly training habits, and HA knowledge. Recreational runners (N= 125) demonstrated a lack of knowledge toward proper HA training and its associated bene ts. Participants largely received HA advice from their peers (31.2%) and reported no professional guidance in their training (79.2%). Finally, participants' beliefs toward proper HA training differed among training groups with moderate and high groups perceiving greater frequency, miles/wk, and min/wk as appropriate for HA compared to the low group (p 0.05). Due to the warmer temperatures and higher relative humidity experienced in the southeastern, southwestern, and mid-Atlantic locations of the United States and throughout certain regions of the European Union, governing bodies in sport and exercise science should develop more educational initiatives to convey the importance and advantages of HA, especially when runners are training

to the low group (p 0.05). Due to the warmer temperatures and higher relative humidity experienced in the southeastern, southwestern, and mid-Atlantic locations of the United States and throughout certain regions of the European Union, governing bodies in sport and exercise science should develop more educational initiatives to convey the importance and advantages of HA, especially when runners are training for major marathons that are typically held in the late spring and early fall seasons. Keywords:running; heat; acclimation; humidity; heat index; apparent temperature 1. Introduction Exertional heat illness, among individuals performing physical activity in thermally stressful environments, is especially prevalent in the Southeastern United States, in which average maximum ambient temperatures of >30 and relative humidities 85% are experi- enced throughout the summer season [1–3]. Exertional heat illness encompasses multiple health conditions that manifest with symptoms such as headache, nausea, and vomiting. Heat stroke and heat exhaustion are forms of exertional heat illness with core temperatures of <40 C and >40 C, respectively [4]. The National Athletic Trainers Association recommends certi ed athletic trainers provide heat acclimation (HA) programs to athletes to reduce the occurrence of exertional heat illness [5]. Heat acclimation results in physiological adaptations to hot and humid environments via repeated exposure, leading to better management of internal and external heat stress [6]. Although various methods of HA exist, the physiological adaptations are similar, namely the greater dissipation of heat caused by an increased plasma volume and sweat rate, leading to greater potential evaporative cooling [7]. Athletes often utilize HA training techniques in the weeks leading up to competitions in thermally stressful environments [8]. Professional athletes often have educated exercise science professionals assisting with performance enhancement and HA training protocols [9]. Conversely, recreationally active individuals may not have access to this same expertise. Hosokawa et al. (2019) determined Sports2023,11, 49.

Sports2023,11, 49 2 of 10 in a sample of 2091 recreational runners, only 47.4% were aware of the correct duration of a HA protocol [9]. Additionally, Shendell et al. (2010) [10] sampled 1138 recreational marathon runners in the Southeastern United States and found 47.9% did not understand the risks of dying from heat stroke. Recreational athletes were found to receive a large portion of their hydration advice from peers, and it is possible that the same trend may occur for HA [11]. Furthermore, multiple studies across recreational to elite endurance athlete populations have reported that >40% of athletes surveyed experienced symptoms of exertional heat illness [8,11–13]. With the prevalence of exertional heat illness among recreational athletes, in addition to data showing both college and even professional athletic populations often engaging in physical activity in dehydrated states, it is important that athletes are made aware of strategies to mitigate heat stress and reduce the risk of exertional heat illness during physical activity [14–20]. Additionally, it is especially important to educate the recreational athlete population as it could be speculated that these individuals are at a greater risk of injury due to lack of guidance from sports medicine professionals. If this population lacks knowledge in the realm of HA strategies, more educational material and initiatives are needed for the recreational athlete. Thus, the purpose of this study was to assess the recreational running population to determine their knowledge of proper HA protocols, its associated bene ts, and the sources from which they receive HA information. A secondary purpose was to determine if any differences in HA knowledge were present among recreational runners of various training categories. The current authors hypothesized that runners categorized into a “low” training category based on their training preferences would demonstrate signi cantly less overall training in the measured variables (frequency, volume, etc.) for each season when compared to runners categorized into a “high” training group. 2. Materials and Methods 2.1. Participants Participants were recruited via email lists for local running clubs in the Southeastern United States (U.S.) as well as by word of mouth with an electronic

preferences would demonstrate signi cantly less overall training in the measured variables (frequency, volume, etc.) for each season when compared to runners categorized into a “high” training group. 2. Materials and Methods 2.1. Participants Participants were recruited via email lists for local running clubs in the Southeastern United States (U.S.) as well as by word of mouth with an electronic announcement that included a link to the survey on a hosting website (Qualtrics, Provo, UT, USA). Inclusion criteria included males and females between the ages of 18 and 70 years, running at least 3 times per week for at least 1 year and living and training in the Southeastern U.S. For this study, the states of South Carolina, North Carolina, Tennessee, Mississippi, Alabama, Georgia, and Florida were considered to make up the Southeastern U.S., based onDiem et al. (2017) [21] . Arkansas and Louisiana were additionally included based on their status as a humid sub-tropical climate [22]. All procedures were explained in an informed consent form at the start of the electronic survey. Participation was voluntary and participants were free to withdraw from the study at any time. 2.2. Questionnaire The questionnaire included modified or adapted questions from previously used ques- tionnaires along with original questions specific to the population beingsurveyed [ The survey included 38 questions and required approximately 10–15 min to complete. The questionnaire included ve sections: demographics, yearly training habits, HA and related topic knowledge, HA practices during the summer, and experiences with exertional heat illness. This manuscript includes results from the rst three sections of the survey with a focus on participant demographics, seasonal training, and HA knowledge. Section one of the survey contained nine questions on age, sex, education level, profes- sion, geographic location, training and racing history, and participants' predicted current 10 kmtime based on their current training practices and their most recent race nishing time, if applicable. Section two included 12 questions on training practices throughout the year split into three questions per season. Speci c questions included running intensity on a 0–10 rating of perceived exertion scale [25], running duration, as well

and racing history, and participants' predicted current 10 kmtime based on their current training practices and their most recent race nishing time, if applicable. Section two included 12 questions on training practices throughout the year split into three questions per season. Speci c questions included running intensity on a 0–10 rating of perceived exertion scale [25], running duration, as well as frequency, mileage, and running minutes per week. Participants were asked to report weekly training in miles

Sports2023,11, 49 3 of 10 due to the sample being from the United States, wherein the imperial measurement system is used. The current researchers converted the data to km/wk for international reporting purposes. Section three of the survey included eight questions on participants' HA knowl- edge. Speci c questions were asked regarding where HA information was acquired, past attempts at engaging in HA protocols, perceived appropriate training frequency, exercise duration, exercise intensity, perceived appropriate training times during a summer day, the bene ts of HA, and whether participants' consistently ran during the hottest part of the day during the summer in order to become heat acclimated. 2.3. Statistical Analysis All data were collected via Qualtrics software (Qualtrics, Provo, UT, USA) and im- ported to SPSS version 27.0 (IBM Corp., Armonk, NY, USA) for analysis. Means SDs are reported for quantitative demographic variables and frequencies and percentages are reported for qualitative demographic variables. Participants were divided into low and high training groups based on a product of summer training frequency, summer miles/wk, and predicted 10 km race time to determine if there were any differences in HA knowledge based on training status. Welch'sttests were performed on the quantitative responses and chi-square tests of independence were performed on the qualitative responses to determine differences among training groups. An alpha of 0.05 was used for all analyses. 3. Results A total of 216 surveys were collected with 125 of them meeting the inclusion criteria (N= 125). Responses from individuals older than 70 years of age or from individuals who did not train and reside in the Southeastern United States were excluded from the analyses. The nal sample resulted in an approximate power of 0.80 for a medium effect size and alpha 0.05 for independentttests. The nal sample included 55 males and 70 females with an average age of 44.6 years 12.2 years. 3.1. Demographics The participants in this study were experienced recreational runners with14.1 11.5 years of training experience, 13.1 11.3 years of race experience, and reported a predicted10 km race time of 55.8 13.3 min. Training status of the participants constituted a

independentttests. The nal sample included 55 males and 70 females with an average age of 44.6 years 12.2 years. 3.1. Demographics The participants in this study were experienced recreational runners with14.1 11.5 years of training experience, 13.1 11.3 years of race experience, and reported a predicted10 km race time of 55.8 13.3 min. Training status of the participants constituted a total 64 in the low training group category and 61 in the high training group category. Tables provide details on geographic location and type of professional training guidance received, respectively. Almost half (46.4%) of the participants reported having earned a graduate degree, while 40% of the participants reported holding a bachelor's degree, and 4.8% reported holding an associate degree. The remaining participants reported other forms of education (graduate school students, some college education, and high school diploma). Table 1.Geographic distribution of participants (N= 125). State n % of Sample Alabama 52 41.6 Tennessee 35 28.0 Louisiana 19 15.2 Arkansas 12 9.6 Florida 3 2.4 Georgia 2 1.6 Mississippi 1 0.8 South Carolina 1 0.8

Sports2023,11, 49 4 of 10 Table 2.Professional training guidance and HA information sources (N= 125). * Professional n % of Sample Running coach 18 14.4 Athletic trainer 4 3.2 Strength and conditioning specialist 4 3.2 Medical doctor 1 0.8 Other professional 7 5.6 No professional supervision 99 79.2 Note. * = Some participants reported receiving guidance from more than 1 type of professional/information source. 3.2. Yearly Training Habits Table high training groups. In Table, the signi cant differences found for duration, frequency, mileage (reported in kilometer units), and minutes/week within each season are presented. The low training group ran with less duration, frequency, km/wk, and min/week than the high training group for each season. Table 3. M SD in Seasonal Training Practices for Runners of Low Training Status (n= 64) and High Training Status (n= 61).Summer Fall Low High MD Low High MD Duration (min.) 54.8 18.4 68.8 19.7 14.0 * 61.0 19.6 71.8 18.8 10.8 * Frequency (days/wk) 4.0 0.7 5.7 0.9 1.7 * 4.0 0.9 5.7 0.9 1.7 * km/wk 31.1 9.2 64.7 20.3 33.6 * 35.2 12.4 66.8 21.6 31.5 * Rate of Perceived Exertion 6.3 1.6 5.8 1.5 0.5 5.9 1.5 5.9 1.4 0.0 min/wk 197.7 67.1 381.6 139.4 183.9 * 218.6 76.1 392.6 141.0 174.0 * Winter Spring Duration (min.) 56.8 17.8 68.1 22.0 11.4 * 58.6 18.7 69.7 20.6 11.1 * Frequency (days/wk) 3.8 1.0 5.4 1.2 1.6 * 4.1 0.8 5.7 0.9 1.6 * km/wk 33.8 14.6 63.4 24.1 29.5 * 35.4 13.2 65.3 20.1 30.1 * Rate of Perceived Exertion 5.6 1.7 5.8 1.5 0.2 6.1 1.5 6.1 1.4 0.0 min/Wk 208.2 81.2 363.3 149.0 155.1 * 214.6 70.5 376.6 140.5 161.9 * Note.MD= mean difference; * denotes significant mean difference between the low and high groups based onp 0.05. 3.3. Heat Acclimation Knowledge The rst question of Section acclimation protocol? Check all that apply.” Participants were required to correctly identify HA bene ts out of seven options, with four options being true and three options being false. A total of 3.2% (n= 4) of participants identi ed three options correctly, 30.4%(n=

the low and high groups based onp 0.05. 3.3. Heat Acclimation Knowledge The rst question of Section acclimation protocol? Check all that apply.” Participants were required to correctly identify HA bene ts out of seven options, with four options being true and three options being false. A total of 3.2% (n= 4) of participants identi ed three options correctly, 30.4%(n= 38) identi ed four options correctly, 28.0% (n= 35) identi ed ve options correctly, 27.2% identi ed six options correctly, and 11.2% (n= 14) of participants identi ed all seven options correctly. The Welchttest revealed no statistical differences in the number of correct responses among the low (M= 5.1) and high (M= 5.2) training groups (M D= 0.07, 95% CI [ 0.45, 0.31]). The second question of Section a heat acclimation protocol by increasing running intensity, frequency, or duration in the summer (20 June–19 September)?” There was an approximately equal split among the participants, with 64 (51.2%) respondents answering “yes” and 61 (48.8%) answering “no.” The chi-square test of independence reported no associations between the participants belief on whether a HA protocol should be followed and training status (N= 125; 2= 2.9; p= 0.09). The third question of Section exercise in the hottest part of the day during the summer?” An overwhelming majority of respondents (90.4%) answered “no”, while the remaining (9.6%) answered “yes”. The

Sports2023,11, 49 5 of 10 chi-square test of independence indicated no association between training status and time of day to train for HA purposes (N= 125; 2 = 1.7;p= 0.19). The nal question in Section consider most appropriate to run at when attempting to heat acclimate?” The most common times for training were 9:00 a.m.–11 a.m. (28.8%;n= 36), before 8:00 a.m. (24%;n= 30), 3:00 p.m.–5:00 p.m.(23.2%;n= 29), and 6:00 p.m.–8:00 p.m. (8.8%;n= 11), respectively. The chi-square test of independence noted no association between time of day for training and training status (N= 125; 2 = 1.84;p= 0.77). 3.4. Heat Acclimation Training Beliefs Figure for the variables of duration, frequency, km/wk, and rating of perceived exertion (RPE) during the summer season.Sports 2023, 11, x FOR PEER REVIEW 5 of 10 the summer (20 June–19 September)?” There was an approximately equal split among the participants, with 64 (51.2%) respondents answering “yes” and 61 (48.8%) answering “no.” The chi-square test of independence reported no associations between the partici- pants belief on whether a HA protocol should be followed and training status (N = 125; χ 2 = 2.9; p = 0.09). The third question of Section 3 asked participants “Should runners consist- ently exercise in the hottest part of the day during the summer?” An overwhelming ma- jority of respondents (90.4%) answered “no,” while the remaining (9.6%) answered “yes.” The chi-square test of independence indicated no association between training status and time of day to train for HA purposes (N = 125; χ 2 = 1.7; p = 0.19). The final question in Section 3 asked participants “What time of day would you con- sider most appropriate to run at when attempting to heat acclimate?” The most common times for training were 9:00 a.m.–11 a.m. (28.8%; n = 36), before 8:00 a.m. (24%; n = 30), 3:00 p.m.–5:00 p.m. (23.2%; n = 29), and 6:00 p.m.–8:00 p.m. (8.8%; n = 11), respectively. The chi- square test of independence noted no association between time of day for training and training status (N = 125; χ 2 = 1.84; p = 0.77). 3.4. Heat Acclimation

a.m.–11 a.m. (28.8%; n = 36), before 8:00 a.m. (24%; n = 30), 3:00 p.m.–5:00 p.m. (23.2%; n = 29), and 6:00 p.m.–8:00 p.m. (8.8%; n = 11), respectively. The chi- square test of independence noted no association between time of day for training and training status (N = 125; χ 2 = 1.84; p = 0.77). 3.4. Heat Acclimation Training Beliefs Figure 1 presents the participants’ perceptions on appropriate HA training protocols for the variables of duration, frequency, km/wk, and rating of perceived exertion (RPE) during the summer season. Figure 1. Participants’ perception of appropriate HA training during the summer. Note. * Denotes significant differences vs. the high training group at the p < 0.05 level. Duration = min/run, Fre- quency = days/wk, RPE = rating of perceived exertion on a 0–10 scale. at the p < 0.05 level. 3.4.1. Duration Results from the Welch t test revealed no significant differences in perceived dura- tion to be appropriate for HA between the low training (M = 33.2) and high training (M = 37.3) groups (M Δ = −4.1, 95% CI[−8.9, 0.6]). * * * Figure 1. Participants' perception of appropriate HA training during the summer. Note. * Denotes signi cant differences vs. the high training group at thep< 0.05 level. Duration = min/run, Frequency = days/wk, RPE = rating of perceived exertion on a 0–10 scale. at thep< 0.05 level. 3.4.1. Duration Results from the Welchttest revealed no signi cant differences in perceived duration to be appropriate for HA between the low training (M= 33.2) and high training (M= 37.3) groups (M D= 4.1, 95% CI [ 8.9, 0.6]). 3.4.2. Frequency Results from the Welchttest revealed that runners in the low training group (M= 3.3) perceived training fewer days in a week to be appropriate for HA compared to the high training group (M= 4.0), (M D= 0.7, 95% CI [ 1.1, 0.4]). 3.4.3. Kilometers Results from the Welchttest revealed that runners in the low training group (M= 22.6) perceived fewer km/week to be appropriate for HA compared to the high training group (M= 34.4), (M D= 11.8, 95%

in a week to be appropriate for HA compared to the high training group (M= 4.0), (M D= 0.7, 95% CI [ 1.1, 0.4]). 3.4.3. Kilometers Results from the Welchttest revealed that runners in the low training group (M= 22.6) perceived fewer km/week to be appropriate for HA compared to the high training group (M= 34.4), (M D= 11.8, 95% CI [ 16.6, 7.0]). 3.4.4. Rating of Perceived Exertion (RPE) Results from the Welchttest revealed no signi cant differences in RPE between the low training (M= 4.8) and high training (M= 4.5) groups (M D= 0.3, 95% CI [ 0.3, 0.9]).

This research highlights the lack of heat acclimation knowledge among recreational runners.