Context

To our knowledge, no researchers have investigated thermoregulatory responses and exertional heat illness (EHI) risk factors in marching band (MB) artists performing physical activity in high environmental temperatures.

Objective

To examine core temperature (Tc) and EHI risk factors in MB artists.

Design

Descriptive epidemiology study.

Setting

Three rehearsals and 2 football games for 2 National Collegiate Athletic Association Division I institution's MBs.

Patients or Other Participants

Nineteen volunteers (females = 13, males = 6; age = 20.5 ± 0.9 years, height = 165.1 ± 7.1 cm, mass = 75.0 ± 19.1 kg) completed the study.

Main Outcome Measure(s)

We measured Tc, wet bulb globe temperature, and relative humidity preactivity, during activity, and postactivity. Other variables were activity time and intensity, body surface area, hydration characteristics (fluid volume, sweat rate, urine specific gravity, percentage of body mass loss), and medical history (eg, previous EHI, medications). The statistical analysis consisted of descriptive information (mean ± standard deviation), comparative analyses that determined differences within days, and correlations that identified variables significantly associated with Tc.

Results

The mean time for rehearsals was 102.8 ± 19.8 minutes and for games was 260.5 ± 47.7 minutes. Mean maximum Tc was 39.1 ± 1.1°C for games and 38.4 ± 0.7°C for rehearsals; the highest Tc (41.2°C) occurred during a game. Fluid consumption did not match sweat rates (P < .001). Participants reported to games in a hypohydrated state 63.6% of the time. The maximum Tc correlated with the maximum wet bulb globe temperature (r = 0.618, P < .001) and was higher in individuals using mental health medications (rpb = −0.254, P = .022) and females (rpb = 0.330, P = .002). Body surface area (r = −0.449, P < .001) and instrument mass (r = −0.479, P < .001) were negatively correlated with Tc.

Conclusions

Marching band artists experienced high Tc during activity and should have access to athletic trainers who can implement EHI-prevention and -management strategies.

Key Points
• During football season rehearsals and game days, marching band artists demonstrated high core temperatures and exhibited several risk factors for exertional heat illness.

• Athletic trainers and band administrators should work with student health, athletics, and other institutional partners to develop prevention and management strategies for exertional heat illness to ensure that marching band artists receive appropriate medical care.

Marching band (MB) is a popular activity among high school and collegiate students. Some MBs may have only 10 members, whereas larger institutions and elite performing groups (ie, Drum Corps International) can range from 100 to more than 300 members. Marching band artists face many of the same physical activity demands, risks, and injuries as traditional student-athletes.1  However, unlike collegiate student-athletes who have access to multiple sports medicine providers (athletic trainers [ATs], physicians, strength and conditioning specialists, nutritionists, etc), collegiate MB artists are often considered part of the general student body. It is common for band directors or other nonmedical personnel to be responsible for recognizing and referring MB artists with a medical concern to student health, a stadium first-aid station during games, or other community health care facilities. Musculoskeletal injuries are prevalent in MB artists and attributed to the physical movements during a show (eg, running or high-step marching) and carrying instruments,2,3  but musculoskeletal injuries are not the only health care concern common to student-athletes and MB artists.

Similar to fall-sport student-athletes (eg, football, soccer), MB artists complete preseason activity at the beginning of August, which includes rehearsing for football performances (pregame and half time) outdoors for several hours a day in high heat and humidity.1  Preseason is the most dangerous time for fall-sport student-athletes to experience exertional heat illness (EHI), especially exertional heat stroke. In an epidemiologic study4  of 25 National Collegiate Athletic Association sports, student-athletes experienced 232 EHI events over 5 years. Most EHIs occurred during preseason (64.7%) and practices (72.8%) and were associated with football (75%).4  To our knowledge, no researchers have documented core body temperature (Tc) among MB artists, and little scholarly evidence exists on EHI occurrence among MB artists. Most studies1,5  of MB members that examined injuries or illnesses were retrospective, used self-reported data at the end of a season, or combined heat illnesses with other nonmusculoskeletal illnesses. Heat distress accounted for 6% to 8% of health clinic visits during a high school band camp in August.2  In unpublished data from our research group, 50.6% (611/1207) of collegiate MB artists indicated previously experiencing EHI associated with MB activities. News stories611  have demonstrated that hundreds of MB artists were hospitalized due to EHI, including exertional heat stroke. Despite the lack of scientific evidence, MB artists not only have similar physical and environmental demands as student-athletes, but they also have other risk factors that predispose them to EHIs.

Based on known risk factors in other populations1214  and anecdotal experience, MB artists' EHI risks may include a lack of knowledge about proper hydration and nutrition; not gradually increasing exercise duration and intensity; a lack of heat acclimatization; poor physical conditioning; alcohol and medication use; preexisting medical conditions; and sleep deprivation, immune disturbances, or both perpetuated by the stress associated with managing academics, practice times, and travel. Similar to football players who wear heavy protective equipment, traditional MB performance uniforms are often heavy, cover the arms and legs, and include plastic hats without ventilation.5  Football players who wore full uniforms experienced less time to exhaustion and significantly higher Tc than those not wearing uniforms,15  so we can presume that MB uniforms and equipment (eg, drums, sousaphones) trap sweat against the skin and inhibit evaporative cooling, causing heat to be retained and Tc to increase.

The author16  of a study on musculoskeletal injury and sudden illness rates suggested that MBs would benefit from the care of ATs. This was further supported by a National Athletic Trainers' Association (NATA) guideline encouraging collaboration between band personnel and ATs to reduce the incidence of injuries or illnesses.17  We sought to provide additional support for MB artists to have access to ATs, due to the AT's ability to prevent, recognize, and manage patients with emergent conditions such as exertional heat stroke. Evidence on physiological responses and EHI risk factors will also support MB-specific heat policies and procedures. Our primary purpose was to assess Tc among MB artists during rehearsals and football game performances. Secondly, we sought to identify specific EHI risk factors among MB artists and determine how these may influence Tc.

## METHODS

We used a cross-sectional study design. The primary dependent variable was Tc assessed before, during, and after the rehearsal or game. Other physiological outcome variables were heart rate (HR), percentage change in body mass (%BM), urine specific gravity (Usg), fluid volume (Fvol), sweat rate, and perceived thirst. Based on the NATA position statement on EHIs,12  we selected several intrinsic and extrinsic risk factors to examine in our population, including previous EHI, environment, physical activity time and intensity, ground surface, previous night's sleep, medication use, and current general illness.

### Participants

Participants were recruited from 2 National Collegiate Athletic Association Division I institutions' MBs (MB1 and MB2). A total of 19 MB artists completed the study (10 from MB1, 9 from MB2; age = 20.5 ± 0.9 years): 13 females (height = 161.8 ± 5.5 cm, mass = 72.5 ± 16.7 kg) and 6 males (height = 172.5 ± 3.6 cm, mass = 80.4 ± 24.4 kg). To be included, recruits had to be at least 18 years old and active in the university's MB during the fall 2018 season. Individuals were excluded if they had a swallowing, gastrointestinal, or other medical disorder that prevented them from ingesting the Tc sensor. The study was approved by the primary investigators' institutional review boards, and all participants read and signed an informed consent form.

### Measurements and Instrumentation

#### Anthropometrics

Height, mass, body fat percentage, and body surface area (BSA) were obtained. Height was measured using a stadiometer height board (ShorrBoards; Shorr Productions LLC, Olney, MD). Mass and body fat percentage were measured using a body composition scale (model SC 331S; Tanita Corp of America, Inc, Arlington Heights, IL). We calculated BSA using the equation of Du Bois and Du Bois.18  On 1 day, participants were weighed with their instruments to determine instrument mass.

#### Core Temperature

To assess thermoregulatory strain, Tc (°C) was monitored continuously and recorded every 15 minutes throughout exercise using ingestible thermistors (CorTemp; HQ, Inc, Palmetto, FL). Participants ingested the pill approximately 6 hours before data collection to ensure that the sensor reached the large intestine at the appropriate time.

#### Hydration

Hydration status was characterized by %BM and Usg. Body mass was measured preactivity and postactivity. Participants voided urine before being weighed with minimal clothing (eg, shorts and T-shirt, no shoes), and mass was adjusted by 0.5 kg for clothing. During the postactivity weighing, participants toweled off sweat before stepping on the scale. Urine was obtained preactivity and postactivity. Participants urinated into a specimen cup, and Usg was measured using a refractometer (MB1: model PEN-PRO; Atago Co, Ltd, Tokyo, Japan; MB2: model REF 312; Atago Co Ltd).

To maintain the participants' normal hydration behaviors, we did not provide them with individual bottles or fluids. For rehearsals, participants brought their own containers with their preferred amount and type of fluid. For football games, the institution's MB provided fluids. We weighed each person's container to determine Fvol (g) consumption. If a participant needed to urinate after the preactivity weighing and before activity ended, he or she did so in a designated urine volume container, and we measured total urine volume using a graduated cylinder (mL). We calculated sweat rate (L/h) using
$$\def\upalpha{\unicode[Times]{x3B1}}$$$$\def\upbeta{\unicode[Times]{x3B2}}$$$$\def\upgamma{\unicode[Times]{x3B3}}$$$$\def\updelta{\unicode[Times]{x3B4}}$$$$\def\upvarepsilon{\unicode[Times]{x3B5}}$$$$\def\upzeta{\unicode[Times]{x3B6}}$$$$\def\upeta{\unicode[Times]{x3B7}}$$$$\def\uptheta{\unicode[Times]{x3B8}}$$$$\def\upiota{\unicode[Times]{x3B9}}$$$$\def\upkappa{\unicode[Times]{x3BA}}$$$$\def\uplambda{\unicode[Times]{x3BB}}$$$$\def\upmu{\unicode[Times]{x3BC}}$$$$\def\upnu{\unicode[Times]{x3BD}}$$$$\def\upxi{\unicode[Times]{x3BE}}$$$$\def\upomicron{\unicode[Times]{x3BF}}$$$$\def\uppi{\unicode[Times]{x3C0}}$$$$\def\uprho{\unicode[Times]{x3C1}}$$$$\def\upsigma{\unicode[Times]{x3C3}}$$$$\def\uptau{\unicode[Times]{x3C4}}$$$$\def\upupsilon{\unicode[Times]{x3C5}}$$$$\def\upphi{\unicode[Times]{x3C6}}$$$$\def\upchi{\unicode[Times]{x3C7}}$$$$\def\uppsy{\unicode[Times]{x3C8}}$$$$\def\upomega{\unicode[Times]{x3C9}}$$$$\def\bialpha{\boldsymbol{\alpha}}$$$$\def\bibeta{\boldsymbol{\beta}}$$$$\def\bigamma{\boldsymbol{\gamma}}$$$$\def\bidelta{\boldsymbol{\delta}}$$$$\def\bivarepsilon{\boldsymbol{\varepsilon}}$$$$\def\bizeta{\boldsymbol{\zeta}}$$$$\def\bieta{\boldsymbol{\eta}}$$$$\def\bitheta{\boldsymbol{\theta}}$$$$\def\biiota{\boldsymbol{\iota}}$$$$\def\bikappa{\boldsymbol{\kappa}}$$$$\def\bilambda{\boldsymbol{\lambda}}$$$$\def\bimu{\boldsymbol{\mu}}$$$$\def\binu{\boldsymbol{\nu}}$$$$\def\bixi{\boldsymbol{\xi}}$$$$\def\biomicron{\boldsymbol{\micron}}$$$$\def\bipi{\boldsymbol{\pi}}$$$$\def\birho{\boldsymbol{\rho}}$$$$\def\bisigma{\boldsymbol{\sigma}}$$$$\def\bitau{\boldsymbol{\tau}}$$$$\def\biupsilon{\boldsymbol{\upsilon}}$$$$\def\biphi{\boldsymbol{\phi}}$$$$\def\bichi{\boldsymbol{\chi}}$$$$\def\bipsy{\boldsymbol{\psy}}$$$$\def\biomega{\boldsymbol{\omega}}$$$$\def\bupalpha{\bf{\alpha}}$$$$\def\bupbeta{\bf{\beta}}$$$$\def\bupgamma{\bf{\gamma}}$$$$\def\bupdelta{\bf{\delta}}$$$$\def\bupvarepsilon{\bf{\varepsilon}}$$$$\def\bupzeta{\bf{\zeta}}$$$$\def\bupeta{\bf{\eta}}$$$$\def\buptheta{\bf{\theta}}$$$$\def\bupiota{\bf{\iota}}$$$$\def\bupkappa{\bf{\kappa}}$$$$\def\buplambda{\bf{\lambda}}$$$$\def\bupmu{\bf{\mu}}$$$$\def\bupnu{\bf{\nu}}$$$$\def\bupxi{\bf{\xi}}$$$$\def\bupomicron{\bf{\micron}}$$$$\def\buppi{\bf{\pi}}$$$$\def\buprho{\bf{\rho}}$$$$\def\bupsigma{\bf{\sigma}}$$$$\def\buptau{\bf{\tau}}$$$$\def\bupupsilon{\bf{\upsilon}}$$$$\def\bupphi{\bf{\phi}}$$$$\def\bupchi{\bf{\chi}}$$$$\def\buppsy{\bf{\psy}}$$$$\def\bupomega{\bf{\omega}}$$$$\def\bGamma{\bf{\Gamma}}$$$$\def\bDelta{\bf{\Delta}}$$$$\def\bTheta{\bf{\Theta}}$$$$\def\bLambda{\bf{\Lambda}}$$$$\def\bXi{\bf{\Xi}}$$$$\def\bPi{\bf{\Pi}}$$$$\def\bSigma{\bf{\Sigma}}$$$$\def\bPhi{\bf{\Phi}}$$$$\def\bPsi{\bf{\Psi}}$$$$\def\bOmega{\bf{\Omega}}$$$${{{\rm{Preactivity\ Body\ Mass\ }}\left( {{\rm{kg}}} \right){\rm{\ }} - {\rm{Postactivity\ Body\ Mass\ }}\left( {{\rm{kg}}} \right)\atop + {\rm{Fluid\ Volume\ }}\left( {\rm{L}} \right) - {\rm{Urine\ Volume\ }}\left( {\rm{L}} \right)} \over {{\rm{Activity\ Time\ }}\left( {\rm{h}} \right)}}.$$

Perceived thirst was measured using a 9-point thirst scale. Verbal anchors ranged from 1 (not thirsty at all) to 5 (moderately thirsty) to 9 (very, very thirsty).14  Participants rated thirst preactivity and postactivity.

#### Environment

Wet bulb globe temperature (WBGT, °C) and percentage of relative humidity (RH) were continuously measured and recorded every 15 minutes using a thermal environmental monitor (model 3000HS; Kestrel Instruments, Boothwyn, PA). We recorded the ground surface (ie, turf, pavement, natural grass) each day.

#### Pre-Activity Questionnaire

To enable us to identify potential EHI risk factors before each rehearsal or performance, participants completed a 24-hour recall of medication and supplement use; sleep quantity; and any signs or symptoms of illness.

### Activity and HR

Activity watches (model M200; Polar Electro, Inc, Lake Success, NY) continuously monitored HR. We programmed each watch with the participant's dominant hand, height, mass, date of birth, and sex according to the manufacturer's instructions. On data-collection days, participants wore the watches during the rehearsal or performance. At the end of data collection, we synchronized watches to the Polar Flow Web service and downloaded the data to determine the maximum HR during the rehearsal or performance and estimated maximum oxygen consumption (V̇O2max).

We recorded physical activity and duration in minutes. Activities were categorized as one of the following: (1) stretching or general warmup, (2) standing without instrument, (3) standing with instrument, (4) marching without instrument, (5) marching with instrument, (6) high-step marching without instrument, (7) high-step marching with instrument, and (8) rest or water break. Each coded activity intensity was based on the compendium of physical activities.19  We then calculated average metabolic equivalents (METs) for each rehearsal and game.

### Procedures

During an information session, recruits reviewed the study components and were informed of the risks and benefits. Those who consented to participate completed the health history questionnaire so that we could identify previous medical illness or injury (eg, gastrointestinal or metabolic disorders, EHI history), current medications and supplements, menstrual regularity, age, education level, sex, ethnicity, heat-acclimatization status, years of MB experience, and MB primary instrument. We measured participants' height and mass and familiarized them with the thirst scale and preactivity questionnaire. The day before rehearsal or game data collection, we gave participants specific oral and written instructions on how and when to ingest the Tc sensor. Participants received their activity watches with instructions on when and how to wear them.

Data were collected at each institution on 5 days: 3 outdoor rehearsals during the school year and 2 home game football days. Rehearsal data collection took place during August and September. All football game data collection occurred in September. For each football game, the bands rehearsed in the morning; we only measured environment, activity, and hydration during morning rehearsals. Participants reported 30 minutes early for preactivity measures and surveys. During activity, they maintained their typical hydration and activity habits. We recorded Tc, HR, and environment every 15 minutes. During the rehearsal or game, an investigator continuously tracked activity; all urine was collected in the participant's designated container, and we tracked Fvol consumed. Postactivity measures and surveys were recorded after the rehearsal or performance.

### Statistical Analysis

We used SPSS (version 26; IBM Corp, Armonk, NY) for all analyses. The significance level was set at P < .05. We calculated descriptive statistics (mean, SD, and maximum) for all variables. The primary dependent variable was Tc. Because of varying rehearsal and game times, we could not compare Tc and HR at multiple timepoints (ie, every 15 minutes). We determined mean Tc and HR at preactivity and postactivity and identified each person's maximum Tc and HR during activity to determine a mean maximum Tc and HR for each rehearsal and game day. Boxplots were used to identify extreme outliers, and subsequently, we removed 1 participant's Tc rehearsal data for day 3. Pearson correlations were computed to assess the relationship between maximum Tc and each of the following variables: maximum WBGT, maximum HR, V̇O2max, mass, BSA, Usg, %BM, METs, physical activity time, and instrument mass. We used Pearson partial correlations to determine the relationship between maximum Tc and select variables (eg, WBGT, HR) while controlling for sex, V̇O2max, BSA, activity time, and instrument mass. Point biserial correlations were generated to examine associations between Tc and sex, medication use, and current illness. We described the correlation strength (weak, moderate, or strong) based on the Cohen guidelines.20  We used paired-samples t tests to identify differences from before rehearsal or game to after rehearsal or game for Tc, HR, and Usg and between Fvol and sweat rate. To control for BM, Fvol was corrected to milliliters per kilogram. Chi-square analysis was performed to evaluate associations for sleep, medication use, and current illness between rehearsals and games. Finally, we conducted 1-way analyses of variance to characterize differences between MB1 and MB2 for anthropometrics, environments, physical activity time, and METs.

## RESULTS

A total of 22 participants began the study; we withdrew 2 because they could not swallow the Tc sensor, leaving 20. We excluded 1 participant's data from analysis because the individual had an indoor rehearsal day due to weather and scheduling. Therefore, the data of 19 participants were analyzed. Demographics are presented in Table 1. No differences were found in age, height, or body fat percentage between the groups. However, mass and BSA were greater for MB1. Participants were predominately upperclassmen, whose experience and instruments varied. Estimated V̇O2max was not different between the MBs. We examined sex to classify participants' aerobic fitness.21  Males had a higher V̇O2max (49.8 ± 12.1 mL·kg−1·min−1), indicating good aerobic fitness,21  than females (37.1 ± 6.9 ml·kg−1·min−1; F1,15 = 7.8; P = .014), who had fair aerobic fitness.21

Table 1

Participants' Demographics

### Physiological Measures

Mean preactivity, postactivity, and maximum Tc and HR for rehearsals and games are shown in Table 2. We observed no Tc difference from pregame to postgame, but Tc increased from prerehearsal to postrehearsal. Five individuals in MB2 experienced Tc > 40°C (without central nervous system dysfunction) for >60 minutes during games. The highest maximum Tc during a game was 41.2°C and during a rehearsal was 40.6°C. Mean changes in Tc throughout each rehearsal and game by MB1 and MB2 are provided in the Figure. Heart rate increased from preactivity to postactivity for both rehearsals and games (Table 2).

Table 2

Core Temperature and Heart Rate (Mean ± SD) During Rehearsals and Games

Figure 1

Mean core temperature throughout A) Rehearsals and B) Games for each marching band. Baseline on game-day is 2 hours before kickoff before all pep-rallies and other activities. Abbreviations: R, rehearsal; Gm, game.

Figure 1

Mean core temperature throughout A) Rehearsals and B) Games for each marching band. Baseline on game-day is 2 hours before kickoff before all pep-rallies and other activities. Abbreviations: R, rehearsal; Gm, game.

Hydration status, sweat rate, Fvol, and thirst measures are reported in Table 3. Prerehearsal Usg was lower than the postrehearsal value. No difference was apparent in Usg from preactivity to postactivity for games or morning game-day rehearsals. Defining hypohydrated as Usg ≥ 1.025,22  we classified individuals as either hypohydrated or euhydrated. Participants arrived hypohydrated at morning game-day rehearsals 40.5% of the time and at pregames 63.6% of the time. More often (76.4% of the time), they presented to rehearsals euhydrated. Fluid consumption was less than the sweat rate during rehearsals (t40 = 7.0), games (t33 = 8.1), and morning rehearsals (t33 = 5.2; P < .001). Thirst increased from prerehearsal to postrehearsal (t52 = −5.1, P < .001) but was not different from preactivity to postactivity for morning game-day rehearsals or games.

Table 3

Hydration Characteristics for Rehearsals and Game Days (Mean ± SD)

### Risk Factors for EHI

Three participants reported they did not believe they were heat acclimatized. However, these individuals completed 8 to 14 days of band camp and 2 weeks of regular rehearsals before data collection, suggesting that they were indeed acclimatized. Twelve participants regularly exercised outside of MB activities. Mean BSA was higher in MB1 participants (Table 1); among these, 3 had BSAs > 2.0 m2. Two of these (1 male, 1 female) stated they exercised regularly; both played sousaphone (the second heaviest instrument at approximately 13.4 kg) and had the highest body fat percentage (>45%) and lowest estimated V̇O2max (<30 mL·kg−1·min−1). Three participants described experiencing a previous EHI; all 3 cases were exertional heat exhaustion and occurred 1 to 4 years before fall 2018. Two of the people with a previous EHI (both female) were in MB2, played woodwind instruments (piccolo and clarinet), and regularly experienced Tc >39.5°C during rehearsals and >40°C during games, including the highest Tc (41.2°C).

Each band's rehearsal and game WBGT range, activity time, mean METs, and number of breaks during activity are provided in Table 4. For comparison, we used regional guidelines23  to indicate the recommended activity based on WBGT measures. Both bands were in category 3.23  Environmental measures were not different between institutions. Mean WBGT for rehearsals was 28.8°C ± 5.2°C, for morning game-day rehearsals was 25.6°C ± 10.1°C, and for games was 32.7°C ± 9.9°C. Mean RH during rehearsals was 61.2% ± 21.8%, during morning game rehearsals was 77.4% ± 16.7% and during games was 55.8% ± 12.1%. Mean rehearsal time was 102.8 ± 19.8 minutes and was longer for MB2 than MB1 (116.3 ± 15.3 minutes versus 87.5 ± 11.4 minutes; F1,47 = 54.5, P < .001). Mean game time was 260.5 ± 47.7 minutes and was longer for MB1 (282.6 ± 46.2 minutes) than MB2 (234.2 ± 35.3 minutes; F1,33 = 11.8, P = .002). For morning game-day rehearsals, mean METs (3.3 ± 0.4) were higher than for rehearsals (3.0 ± 0.3; P < .001) and games (3.0 ± 0.5; P = .004). Mean METs differed between bands: MB1 was greater than MB2 during rehearsals (3.2 ± 0.3 versus 2.7 ± 0.3; F1,52 = 51.9, P < .001). However, MB2 averaged greater METs during morning game-day rehearsals (3.5 ± 0.6 versus 3.2 ± 0.2; F1,37 = 7.7, P = .009).

Table 4

Environmental Conditions, Ground Surface, Activity Time, Metabolic Equivalents, and Work-Rest Amounts for All Activity Days

Correlation and point biserial correlation results are listed in Table 5. Maximum Tc did not significantly correlate with V̇O2max, postactivity Usg, %BM, METs, or HR. We identified a strong correlation between Tc and WBGT that persisted when adjusted for METs (rpartial = 0.617, P < .001) and decreased slightly when activity time (rpartial = 0.577, P < .001) and instrument mass (rpartial = 0.552, P < .001) were controlled. The weak association between Tc and activity minutes decreased and was no longer significant when we adjusted for WBGT (rpartial = 0.112, P = .324). We found moderate negative correlations for Tc with BSA and mass. When WBGT was adjusted, Tc and BSA remained significantly correlated but decreased (rpartial = −0.292, P = .008). Maximum Tc was negatively correlated with preactivity Usg; this relationship increased when activity time was controlled (rpartial = −0.427, P < .001) and decreased when WBGT was adjusted (rpartial = −0.286, P = .012). Sex significantly correlated with Tc, with females being higher than males (38.9 ± 1.0°C versus 38.2 ± 0.7°C). The moderate negative correlation between Tc and instrument mass decreased slightly when WBGT was controlled (rpartial = −0.367, P = .001).

Table 5

Pearson and Point Biserial Correlations for Maximum Core Temperature

Based on the NATA position statement on EHIs,12  we examined associations for individuals taking specific medications known to alter thermoregulation. Three participants took mental health medications daily. Other common medications taken occasionally included antibiotics, nonsteroidal anti-inflammatories, and cold and asthma medications. Maximum Tc correlated with the use of any medication and specifically mental health medication (Table 5). Maximum Tc was higher among individuals who were taking regular medications (39.1 ± 1.0°C) than among those who were not (38.4 ± 0.8°C). Similarly, individuals who were taking mental health medications experienced higher Tc (39.3 ± 1.1°C) than those who were not (38.6 ± 0.9°C).

To examine any associations between rehearsals and games for medication and current illness, we violated the assumption for expected cell frequency counts using the χ2 analysis. Hours of sleep were significantly associated with rehearsals or games (χ2 = 16.3, P < .001). When participants reported <5 hours of sleep the night before, this occurred more often for games than for rehearsals (73.1% of the time versus 26.9%). In the same way, more individuals reported receiving below-average sleep hours for games compared with rehearsals (61.8% versus 38.2%, χ2 = 12.8, P = .002).

## DISCUSSION

We sought to assess Tc in MB artists and determine the presence of EHI risk factors. During rehearsals and performances, MB artists experienced high Tc similar to temperatures observed among collegiate and professional football players (range = 37.2–40.7°C)14,2427  and collegiate cross-country runners (38.5–39.5°C).24  We also identified that MB artists had multiple EHI risk factors and that those who were less physically fit (with larger BSA or mass) or carrying heavier instruments could not be assumed to be at the highest risk. Several other intrinsic variables appeared to affect Tc in this population. Being female and using mental health medications resulted in higher Tc. Generally, females have lower V̇O2max than males, and we observed this in our population. Less aerobic fitness may explain the higher Tc during activity,28  but V̇O2max did not correlate with Tc in our participants. The 2 individuals with previous EHI who experienced the highest Tc were female. We cannot determine which risk factor had the greatest effect on Tc, but our results suggested that females exhibited several risk factors that likely contributed to high Tc.

The MB2 participants averaged higher estimated V̇O2max, lower BSA, and less weight and carried lighter instruments, yet their Tc was generally higher during rehearsals and games compared with MB1 individuals. This was likely due to the environment. Although not a statistically significant finding, MB2 members experienced higher WBGT, which was strongly correlated with Tc even when we adjusted for other factors, such as activity time and METs. We did not expect to find a lower Tc among MB artists with a higher BSA, considering that higher BSA and mass have been associated with greater heat storage.29,30  This difference may be partially explained by activity intensity (ie, METs). Different sections and even individuals within a section may not move as much as others during a performance. For example, the sousaphone players may have less distance to cover and, therefore, experience less activity intensity and metabolic heat production. In contrast, some piccolo players may be required to perform at high intensity if the drill requires them to cover more yards than others in their section. Subsequently, a great deal of variability in the physical strain may be present within the band and within the section that the person may not be conditioned to perform.

As in any setting, certain EHI risk factors can be modified and others cannot. Colleges, particularly members of the Power 5 conferences, cannot alter football game times, as these are often dictated by television. Also, marching bands have no control over game field surfaces and may lack control over practice field settings. In general, our participants' Tc values were highest at the beginning of the game and throughout the pregame show, which is likely due to the long game-day schedule before kickoff. As an example, morning rehearsal for an 11:00 am game may run from 6:00 to 9:00 am, followed by a short 30-minute break before 1 hour of pep rallies and other performances for fans. By the time pregame begins, some MB artists have been in full uniform, playing outdoors for several hours, without access to water or shade.

Many MB artists arrived at rehearsals and games hypohydrated, a finding that was similar to results in traditional athletic settings31,32  and a recent investigation among Japanese collegiate MB artists.33  The limited water breaks or rest time during rehearsals and, for MB2, bringing their own fluids likely explains why MB members did not match their sweat rates during rehearsals. Even though they had ready access to water during games (the band supplies water bottles and coolers), they did not consume enough fluids to match their sweat loss. This fluid deficit is reflected in the greater game-day %BM loss. Although MB artists averaged <2% loss, several members lost 2% to 3%, and 2 MB1 members (both in the drumline with lean builds and similar sweat rates) experienced >4% loss during games. It is important to educate MB individuals about hydrating throughout the day so as to arrive at activity euhydrated and, particularly for those who lose more than 2% during an activity, how to replenish fluid losses afterward.

When we compared activity and rest time with recommended guidelines based on WBGT (Table 4), 2 rehearsals and 3 games occurred during black conditions (≥33.4°C). The MB2's game field was turf, which corresponded to the highest recorded WBGT on all data-collection days (game 2 maximum = 51°C). The rehearsal surface was pavement, which also corresponded to WBGT measures exceeding 43°C. On only 1 occasion, MB1's morning game 1 rehearsal, did rest time meet the recommendation. For 5 out of 10 rehearsals, only 1 break was allowed for the entire rehearsal time. Water breaks are important not only for rehydrating but also to permit the artists' Tc values to decrease. The inadequate rest time based on the environmental conditions may have led to higher Tc throughout rehearsals, particularly for MB2. Guidelines for modifying activity due to extreme weather are predominately based on football data, and some aspects could be easily incorporated to reduce risks. For instance, when WBGT exceeds 27.8°C, multiple rest breaks could be incorporated, in the shade if possible, to allow individuals time to cool down. Another consideration is the time of day when rehearsal takes place. The MB1 rehearsal began at 5:00 pm, whereas MB2 started at 3:45 pm, when it was presumably hotter. For MB2, rehearsals 1 and 2 both started in black conditions but cooled during the session. Moving rehearsal time to later in the day could decrease the heat exposure and minimize the EHI risk. Other activity modifications may not be as easily applied to MB, particularly when the individuals responsible for implementing preventive measures are band directors. Specific MB guidelines could address the maximum intensity of a rehearsal—eg, standing or learning drills with no instruments or not playing versus full-speed drill runs while playing. Although football players would never play a game without their full equipment, some MBs have alternative uniforms for extreme environmental conditions, whereas others wear full uniforms to maintain their show appearance. Overall, specific MB activity-modification guidelines, including preseason heat-acclimatization recommendations, could help align expectations across the country and the occurrence of EHIs in MB artists.

Uniforms may have played a role in participants' Tc. However, our limited game-day data did not allow us to determine the extent to which uniforms may have affected Tc. Both bands in our study wore traditional game-day uniforms made of wool-blend bibs and jackets, plastic hats, and cotton-blend gloves. Some bands have a summer uniform option: members may wear shorts and either a T-shirt or polo shirt at certain environmental temperatures. The MB2 had a summer uniform that was worn during game 1. Even in this alternate uniform, MB artists experienced extremely high Tc, suggesting that it was being driven by other factors. The institution's policy at the time dictated that summer uniforms were only allowed for 1 game. As it turned out, the second game was hotter, and MB2 members were required to wear full uniforms. Though MB2's 6:00 am rehearsal for game 2 took place under cool conditions, it averaged the highest METs of all days, and many participants presented hypohydrated with less than average sleep the previous night. The combination of sleep loss, fatigue, hypohydration, full uniforms, turf, and high WBGT during the entire game resulted in not only study participants experiencing high Tc but many nonstudy participant band members seeking shade and treatment for exertional heat exhaustion at the first-aid station.

### Limitations and Future Research

Our investigation was limited in that we only assessed 2 Division I MBs. Style and movement vary greatly within a performance depending on the institution and traditions. Our results are applicable to bands with a corps marching style and traditional uniforms that are located in hot, humid geographic areas. Our findings may not be applicable to bands with different styles, who wear auxiliary (color guard or dance) uniforms, or who are located in cooler parts of the country. One game for MB1 was delayed due to extreme weather that required members to seek shelter under the stadium. The delay may have altered the results, as participants were able to rest, which would have lowered Tc and allowed more time for hydration. The MB1 rehearsals were shorter and occurred later in the day than for MB2, which may explain the generally lower Tc in MB1. Our sample size and study design prevented us from determining associations between Tc and certain risk factors (eg, previous EHI, ground surface, sleep, sex). Finally, MB1 had an AT providing medical coverage, while MB2 did not. The preventive EHI strategies implemented by ATs and adopted by MB1 may have led to artists being more cognizant about proper hydration, nutrition, and sleep or being more aware of early EHI signs and more willing to seek care earlier, or both.

Future researchers should examine skin temperature along with Tc to determine the effects of wearing different types of band uniforms on sweating and thermoregulation. The physiological responses and risks for various instrument sections may differ. Some sections of the band may move more than others during a drill, carry different loads, and require different playing techniques that may demand various levels of energy. Certain band sections, particularly the drumline, may rehearse outside for longer periods than others, potentially increasing their exposure and risk. More investigation at different levels (high school, small colleges, elite, and military MBs) and on different marching styles (traditional, high step) is needed. Continuing to examine physiological responses, EHI prevalence rates, and different environmental temperatures will allow for the development of more specific MB activity-modification guidelines. Finally, more research is needed on patient outcomes and best practices among MBs who have access to ATs.

## CONCLUSIONS

Our MB artists experienced high Tc during football rehearsals and games and exhibited several EHI risk factors. Performing physical activity in a hot, humid environment for several hours a day on ground surfaces that radiate heat, using medications that alter thermoregulation, and inadequate sleep can all increase Tc and ultimately the EHI risk. Implementing heat policies while taking into consideration the unique aspects of game-day performances may be challenging. In the absence of ATs, EHI prevention, recognition, and treatment are at the discretion of band directors, student leaders, or other nonmedical personnel. We suggest that ATs and band administrators work together along with student health and athletic personnel and other institutional partners to develop specific EHI-prevention and -management strategies that use best practices and ensure that MB artists receive appropriate medical care. Recommendations include requiring preparticipation examinations to identify at-risk individuals, creating guidelines to modify rehearsal time and intensity in extreme environments, providing ample shade and rest breaks, considering alternate game-day uniforms during extreme conditions, and establishing a management protocol in the event of an MB member with exertional heat stroke.

## REFERENCES

REFERENCES
1.
Hatheway
M,
Chesky
K.
Epidemiology of health concerns among collegiate student musicians participating in marching band
.
Med Probl Perform Art
.
2013
;
28
(4)
:
242
251
.
2.
Kilanowski
JF.
Marching athletes: injuries and illnesses at band camp
.
MCN Am J Matern Child Nurs
.
2008
;
33
(6)
:
338
345
.
3.
Beckett
S,
Seidelman
L,
Hanney
WJ,
Liu
X,
Rothschild
CE.
Prevalence of musculoskeletal injury among collegiate marching band and color guard members
.
Med Probl Perform Art
.
2015
;
30
(2)
:
106
110
.
4.
Yeargin
SW,
Dompier
TP,
Casa
DJ,
Hirschhorn
RM,
Zerr
ZY.
Epidemiology of exertional heat illnesses in National Collegiate Athletic Association athletes during the 2009–2010 through 2014–2015 academic years
.
J Athl Train
.
2019
;
54
(1)
:
55
63
.
5.
Harman
SE.
Medical problems of marching musicians
.
Med Probl Perform Art
.
1993
;
8
(4)
:
132
135
.
6.
The show must go on: band in 2 July 4 parades deals with extreme heat
.
CBS Boston Web site.
7.
Jenkins
J.
37 Marshall County school band members treated for heat exhaustion
.
MetroNews Web site.
8.
Dear
H.
Carolina Band suffers in September heat
.
The Daily Gamecock Web site
.
9.
Dits
J.
Heat sickens band members at competition at Penn High School
.
South Bend Tribune Web site
.
10.
Smith
C.
Oklahoma high school band members suffer heat stroke, dehydration during steamy practice
.
USA Today Web site.
11.
Revuelta
M.
Record heat takes toll on local high school band; 3 taken to hospital
.
KWTX-TV News 10 Web site.
12.
Casa
DJ,
DeMartini
JK,
Bergeron
MF,
et al
National Athletic Trainers' Association position statement: exertional heat illnesses
.
J Athl Train
.
2015
;
50
(9)
:
986
1000
.
13.
Gardner
JW,
Kark
JA,
Karnei
K,
et al
Risk factors predicting exertional heat illness in male Marine Corps recruits
.
Med Sci Sports Exerc
.
1996
;
28
(8)
:
939
944
.
14.
Yeargin
SW,
Casa
DJ,
Armstrong
LE,
et al
Heat acclimatization and hydration status of American football players during initial summer workouts
.
J Strength Cond Res
.
2006
;
20
(3)
:
463
470
.
15.
Armstrong
LE,
Johnson
EC,
Casa
DJ,
et al
The American football uniform: uncompensable heat stress and hyperthermic exhaustion
.
J Athl Train
.
2010
;
45
(2)
:
117
127
.
16.
Rhode
AC.
Injury and illness in marching band and color guard members and the need for athletic trainers: a critically appraised topic
.
J Sports Med Allied Health Sci
.
2017
;
3
(2)
:
1
7
.
17.
NATA offers timely recommendations to keep marching band members healthy and well prepared for activity
.
National Athletic Trainers' Association Web site
.
https://www.nata.org/NR08182017-1. Published 2017. Accessed December 28, 2020.
18.
Du Bois
D,
Du Bois
EF.
Clinical calorimetry: tenth paper a formula to estimate the approximate surface area if height and weight be known
.
Arch Intern Med (Chic)
.
1916
;
17
(6_2)
:
863
871
.
19.
Ainsworth
BE,
WL,
Whitt
MC,
et al
Compendium of physical activities: an update of activity codes and MET intensities
.
Med Sci Sports Exerc
.
2000
;
32
(9 Suppl)
:
S498
S504
.
20.
Cohen
J.
Statistical Power Analysis for the Behavioral Sciences. 2nd ed
.
Hillsdale, NJ
:
Erlbaum Associates;
1988
.
21.
Health-related physical fitness testing and interpretation
.
In:
Pescatello
LS,
Arena
R,
Riebe
D,
Thompson
PD,
eds.
ACSM's Guidelines for Exercise Testing and Prescription. 9th ed
.
Baltimore, MD
:
Lippincott Williams & Wilkins;
2014
:
72
94
.
22.
Armstrong
LE,
Pumerantz
AC,
Fiala
KA,
et al
Human hydration indices: acute and longitudinal reference values
.
Int J Sport Nutr Exerc Metab
.
2010
;
20
(2)
:
145
153
.
23.
Grundstein
A,
Williams
C,
Phan
M,
Cooper
E.
Regional heat safety thresholds for athletics in the contiguous United States
.
Applied Geography
.
2015
;
56
:
55
60
.
24.
Godek
SF,
Godek
JJ,
Bartolozzi
AR.
Thermal responses in football and cross-country athletes during their respective practices in a hot environment
.
J Athl Train
.
2004
;
39
(3)
:
235
240
.
25.
McClelland
JM,
Godek
SF,
PS,
Feairheller
DL,
Morrison
KE.
Effects of cardiovascular fitness and body composition on maximal core temperature in collegiate football players during preseason
.
J Strength Cond Res
.
2018
;
32
(6)
:
1662
1670
.
26.
Godek
SF,
Bartolozzi
AR,
Burkholder
R,
Sugarman
E,
Dorshimer
G.
Core temperature and percentage of dehydration in professional football linemen and backs during preseason practices
.
J Athl Train
.
2006
;
41
(1)
:
8
17
.
27.
Duffield
R,
McCall
A,
Coutts
AJ,
Peiffer
JJ.
Hydration, sweat and thermoregulatory responses to professional football training in the heat
.
J Sport Sci
.
2012
;
30
(10)
:
957
965
.
28.
Kazman
JB,
Purvis
DL,
Heled
Y,
et al
Women and exertional heat illness: identification of gender specific risk factors
.
US Army Med Dep J
.
2015
;
58
66
.
29.
Epstein
Y,
Shapiro
Y,
Brill
S.
Role of surface area-to-mass ratio and work efficiency in heat intolerance
.
J Appl Physiol Respir Environ Exerc Physiol
.
1983
;
54
(3)
:
831
836
.
30.
Marino
FE,
Mbambo
Z,
Kortekaas
E,
et al
Advantages of smaller body mass during distance running in warm, humid environments
.
Pflugers Arch
.
2000
;
441
(2–3)
:
359
367
.
31.
Osterberg
KL,
Horswill
CA,
Baker
LB.
Pregame urine specific gravity and fluid intake by National Basketball Association players during competition
.
J Athl Train
.
2009
;
44
(1)
:
53
57
.
32.
Stover
EA,
Zachwieja
J,
Stofan
J,
Murray
R,
Horswill
CA.
Consistently high urine specific gravity in adolescent American football players and the impact of an acute drinking strategy
.
Int J Sports Med
.
2006
;
27
(4)
:
330
335
.
33.
Yasuda
N,
Ito
S.
Effects of playing position on hydration status in collegiate marching band musicians
.
Med Probl Perform Art
.
2018
;
33
(3)
:
175
182
.