Abstract
Introduction
According to the National Fire Protection Association [1], approximately 345,950 career firefighters are employed within the United States (U.S.) to serve over 318 million citizens across the nation. While on the job, firefighters must regularly execute a range of physically and mentally demanding tasks such as disaster assistance, fire prevention, and hazardous material response [2]. A recent report from the Federal Emergency Management Agency [3] revealed that 30 career firefighters incurred fatal injuries while on-duty in 2012 alone, 16 of which were caused by the stress and overexertion associated with on-the-job performance, and 13 of which were specifically classified as heart attacks. Sudden cardiac events have remained the leading cause of firefighter fatality in the U.S. for over 30 years [4, 5], yet reports indicate that only 30% of U.S. fire departments have preventive programs in place to maintain firefighter cardiovascular health and fitness [6]. According to Perroni et al. [7], “An adequate financial investment focused on assessment and increase of physical capabilities of firefighters could effectively reduce the health risks linked to emergencies.” In an attempt to minimize the persistent risk of sudden cardiac death among firefighters, leaders of national agencies such as FEMA continue to solicit calls for assistance to other researchers and health care professionals to improve the cardiovascular health and fitness offirefighters [3, 8].
It has been consistently reported in the literature that firefighters possessing high levels of cardiovascular fitness are at reduced risk of incurring a sudden cardiovascular event while performing vigorous activity on the job [8–10]. Despite this evidence, very little research has been conducted to examine the effects of the fitness training already implemented within the 10–26 weeks of training typically implemented/undertaken at U.S. firefighter training academies [11, 12]. Research has revealed that firefighter recruits experience an improvement in cardiovascular fitness from pre-training to post-training [13], and that firefighter recruits graduate with cardiovascular fitness levels at or slightly above the minimum standards established for performing live fire suppression tasks [14–16]. Based on the results above [13], fire departments should continue to implement mandatory exercise programs among new hires to establish minimum standards of cardiovascular fitness. Although evidence exists to support the contention that firefighter recruits’ cardiovascular fitness may improve from pre- to post- training [13], no research to date has been conducted to monitor and understand the changes or adaptations that occur across multiple time points during firefighter training academies. Since physiological training adaptations can occur in less than 16 weeks, such evidence-based knowledge could be utilized to modify the structure of training programs so as to maximize trainingefficiency (e.g., periodization) and elicit training gains beyond that which are already achieved.
Over the past few decades, several methods have been established to assess and monitor individuals’ cardiovascular fitness, results of which are typically reported in terms of maximal oxygen uptake (VO2max). Perhaps the most common methods for cardiovascular fitness assessment in both the popularand academic realms are the treadmill and cycle ergometer maximal and submaximal VO2max tests. Although the treadmill and cycle ergometer tests provide the most accurate prediction of an individual’s VO2max, these tests often require expensive equipment, can take anywhere from 20–40 minutes to administer, and require administration by a trained professional. In light of these considerations as well as the limitations in resources available to most fire departments, researchers and fire organizations have utilized assessments such as the Forestry Step Test to assess cardiovascular fitness among firefighters. The Forestry Step Test, a submaximal test initially developed by Sharkey [17, 18] to predict the VO2max of wildland firefighters, is a method of assessment that requires minimal and inexpensive equipment, takes less than 10 minutes to complete from start to finish, and can be administered without the direct supervision of a trained professional. In addition to the acquisition of VO2max data, another benefit of utilizingthe Forestry Step Test is that heart rate recovery (ΔHR) data can be easily obtained during the administration of the test.
Previous research has indicated that ΔHR, or the rate at which one’s heart rate returns to resting values following a submaximal or maximal bout of exercise, is linked to both cardiovascular fitness [19, 20] and mortality [21–23]. Although ΔHR has been assessed and discussed in the firefighting literature as an indicator of cardiovascular strain [24], ΔHR has yet to be assessed or discussed in the literature as an indicator of firefighters’ cardiovascular fitness. Furthermore, no research to date has examined changes in ΔHR among firefighter recruits that may occur duringfirefighter training academies.
Given the paucity of research conducted to understand the phasic changes in firefighter recruits’ cardiovascular fitness over the course of the firefighter training academies, as well as the lack of literature on ΔHR, there is a need to concurrently monitor firefighter recruits’ VO2max and ΔHR across multiple time points during the training academies. As such, the purposes of the current study were to: (a) describe changes observed in firefighter recruits’ estimated VO2max across the duration of the training academy program, (b) describe changes observed in firefighter recruits’ ΔHR across the duration of the training academy program, and (c) determine the relationship between firefighter recruits’ estimated VO2max and ΔHR across the duration of the training academy program. Changes observed in firefighter recruits’ body weight and body fat percentage as well as relationships between VO2max, ΔHR, body weight, and body fat percentage were examined and reported to provide context for interpretation of study results.
Methods
Participants
Prior to the onset of data collection, the current study was approved by the affiliate university’s Institutional Review Board (IRB) for the projection of human subjects. A total of 42 firefighter recruits(3 females, 39 males) employed within metropolitan areas of a state in the Midwest region of the U.S. volunteered to participate in the study. At the time of data collection, all participants were enrolled in a typical 16-week firefighter training academyprogram. Prior to data collection, all participants were screened for eligibility and all participants provided their informed consent to participate in the current study. Eligibility for participation in the current study was established using the following inclusion criteria:(a) between the ages of 18 and 50 years; (b) speak and write English fluently; (c) pass all previous physical and psychological screenings required by their respective fire departments; (d) no prescription medications taken for symptomatic illness; (e) no injuries, surgeries, or bone abnormalities to their knees, hips, or ankles within one year of data collection; (f) no existing heart conditions; and (g) no chest pain or dizziness at rest or during exercise.
Procedure
Data collection for all participants took placeduring or near (i.e.,±one week) the first (T1), eighth (T2), and sixteenth (T3) weeks of their training academy programs. To obtain values necessary for body fat percentage calculations, measures of body weight, rounded to the nearest 0.1 kg, were obtained at each time of data collection. To obtain HR data necessary for VO2max and ΔHR calculations, participants wore Polar T31i heart rate monitors (Polar Electro, Lake Success, NY) and completed the Forestry Step Test [17, 18]. To complete the Forestry Step Test, participants stepped up on to and down off of a 15 3/4 inch step to the beat of a metronome set to 90 beats per minute for five minutes. After completing the five minutes of stepping, participants immediately sat on their respective steps and post-test heart rate (HR) data were recorded at 0 seconds post-test, 15 seconds post-test and 60 seconds post-test. As described further in the sections below, collected post-test HR data were then used to calculate VO2max and ΔHR measures.
Measures
Estimated maximal oxygen uptake
Participants’ 15-second post-test HR data were used to obtain gender-specific, age-adjusted, estimated measures of maximal oxygen uptake (estimated VO2max) from a published table [17, 18]. Participants’ estimated VO2max values were reported in relative terms or milliliters of oxygen consumed per kilogram of body weight per minute (mL/kg/min).
Heart rate recovery
Participants’ HR data at 0 seconds post-test and 60 seconds post-test were used to calculate measures of ΔHR (HR0seconds –HR60seconds). Participants’ ΔHR values were reported in beats per minute (bpm).
Body weight and body fat percentage
As mentioned previously, to provide context to the measures of estimated VO2max and ΔHR across time points, concurrent assessments of participants’ body weight (kg) and body fat percentages were conducted. Following the American College of Sports Medicine (ACSM) guidelines [25], participants’ skinfolds were measured using a Lange skinfold caliper (Beta Technology, Santa Cruz, CA) and reported to the nearest millimeter (mm). Based on these skinfolds, body densities were calculated using the Jackson & Pollock Three Skinfold Site method [26] and percent body fat was calculated using Siri’s body fat percentage equation [27]. For male participants, the triceps, subscapular, and pectoral skinfold measures were used to determine body density. For female participants, the triceps, abdominal, and suprailiac skinfold measures were used to determine body density. To ensure reliability, all skinfold measures were taken at least twice by the same expert researcher across participants.
Statistical analyses
Over the course of data collection, one of the 42 participants was unable to complete all three instances of data collection. As such, that participant was excluded from the study and a final sample size of 41 was used for all statistical analyses. To describe changes observed in participants’ estimated VO2max and ΔHR, repeated measures analysis of variance (RM ANOVA) calculations were conducted. To provide relevant context to the potential changes in estimated VO2max and ΔHR, significant changes in body weight and body fat percentage across time points were also examined by conducting RM ANOVA calculations. Separate Pearson product-moment correlation calculations were conducted to investigate the potential relationships between estimated VO2max, ΔHR, body weight, and body fat percentage, at T1, T2, and T3. Consistent with the descriptive nature of the current study, all statistical analyses were determined to be statistically significant based on an alpha level of 0.05.
Results
Descriptive statistics
At the onset of data collection, participants’ (M age = 30.49, SD = 4.62) measured 179.4 cm in height (SD = 6.4 cm) and 87.81 kg (SD = 11.73 kg) in body weight. Descriptive statistics for all measured physiological variables across time points are reported in Table 1.
Changes in estimated VO2max and ΔHR across time points
Skewness and kurtosis calculations and visual inspections of normal Q-Q plots for all data revealed no consistent outliers across the dependent variables, thereby meeting the normality assumptions for both the RM ANOVA and associated post hoc pairwise comparison calculations. The RM ANOVA assumption of sphericity was also confirmed for each dependent variable via Mauchly’s test of sphericity calculations: VO2max (Mauchly’s W = 0.961, p = 0.461) and ΔHR (Mauchly’s W = 0.963, p = 0.715). The RM ANOVA calculations revealed that mean estimated VO2max values differed significantly between time points, F(2, 80) = 75.525, p < 0.001. Post-hoc pairwise comparisons further revealed significant estimated VO2max mean differences between T1 and T2 (I-J = –6.634, p < 0.001) and between T1 and T3 (I-J = –6.098, p < 0.001), but no significant difference was revealed between T2 and T3 (I-J = 0.537, p = 0.343). The RM ANOVA calculations also revealed that mean ΔHR values differed significantly between time points F(2, 80) = 4.368, p = 0.016. Post-hoc pairwise comparisons revealed significant ΔHR mean differences between T1 and T2 (I-J = –4.976, p = 0.006) and between T1 and T3 (I-J = –3.878, p = 0.027), but no significant difference was revealed between T2 and T3 (I-J = 1.098, p = 0.562). In terms of overall change observed, the firefighter recruits in the current study experienced a 16.5% gain in estimated VO2max and a 12.8% gain in ΔHR from T1 to T2, and lost 1.3% and 2.8% of those respective gains from T2 to T3.
Concurrent changes in body weight and body fat percentage across time points
To provide context to the changes in estimated VO2max and ΔHR reported above, significant changes in body weight and body fat percentage across time points were also examined by conducting RM ANOVA calculations. Skewness and kurtosis calculations and visual inspections of the normalQ-Q plots for all data revealed no consistent outliers across the dependent variables, thereby meeting the normality assumptions of an RM ANOVA and associated post hoc pairwise comparison calculations. Since the assumption of sphericity was violated for the dependent variable of body weight (Mauchly’s W = 0.500, p < 0.001), a Greenhouse-Geisser correction was applied to the associated RM ANOVA calculation. The RM ANOVA assumption of sphericity was confirmed for the dependent variable of body fat percentage (Mauchly’s W = 0.882, p = 0.086). The RM ANOVA calculations revealed that participants’ mean body weights differed significantly between time points, F(2, 53.325) = 6.470, p = 0.008. Post hoc pairwise comparisons further revealed significant body weight mean differences between T1 and T3 (I-J = 1.393, p < 0.05) and between T2 and T3 (I-J = 0.753, p < 0.05), but no significant difference was revealed between T1 and T2 (I-J = 0.639, p = 0.059). In addition, RM ANOVA calculations revealed that participants’ mean body fat percentages differed significantly between time points, F(2, 80) = 24.585, p < 0.001. Post hoc pairwise comparisons further revealed significant body fat percentage mean differences between T1 and T2 (I-J = 1.452, p < 0.001) and between T1 and T3 (I-J = 1.533, p < 0.001); however, no significant difference emerged between T2 and T3 (I-J = 0.081, p = 0.702). These findings are consistent with the changes observed in estimated VO2max and ΔHR reported above.
Correlations between estimated VO2max and ΔHR
As outlined in Tables 2 through 4, Pearson prod-uct-moment correlation calculations yielded no significant relationship between estimated VO2max and ΔHR at T1 (r = 0.116, p = 0.470), T2 (r = 0.064, p = 0.693), or T3 (r = –0.134, p = 0.405). Significant relationships were identified between body weight and ΔHR at T1 (r = –0.563, p < 0.01), as well as between body fat percentage and estimated VO2max at T1 (r = –0.601, p < 0.01), T2 (r = –0.542, p < 0.01), and T3 (r = –0.544, p < 0.01). These findings are consistent with those of previous research on firefighter cardiovascular fitness and body composition [28, 29].
Discussion
Results of the current study indicated that throughout the training academy program: (a) firefighter recruits experienced significant improvements in estimated VO2max; (b) firefighter recruits experienced significant improvements in ΔHR; and (c) estimated VO2max was not significantly correlated with ΔHR at T1, T2, or T3. Furthermore, while attendingthe firefighter training academies, firefighter recruits experienced: No significant gains in estimated VO2max or ΔHR after the first eight weeks of training, no significant loss in body weight until the last eight weeks of training, and no significant loss in body fat percentage after the first eight weeks of training. The findings of the current study, limitations of the current study, and directions for future research will be addressed throughout the next paragraphs.
It has been suggested that the minimum VO2max necessary to complete fire suppression tasks on the job ranges between 40.3 and 45.0 mL/kg/min[14, 30–32]. During their 16 weeks at the academy, firefighter recruits in the current study achieved estimated VO2max values above these suggested minimum standards, thereby demonstrating the practical effectiveness of the traditional academy program in terms of producing desirable fitness outcomes. Findings of the current study are also consistent with previous literature which suggests that short periods of resistance and/or endurance training (i.e., 12–16 weeks) can lead to significant improvements in cardiovascular fitness (i.e., VO2max) among previously unfit or physically inactive young adults [33, 34]. In their study comparing the outcomes of high-intensity and traditional exercise interventions, Nybo and colleagues determined that 12 weeks of high-intensity interval running yielded a 12–16% increase in VO2max among untrained, young adults. Other research has demonstrated that a 16-week periodized training program to improve overall fitness levels of firefighter recruits yielded a 28% improvement in VO2max (35±7 to 45±6 mL/kg/min) as measured using a submaximal cycle ergometer test [13]. The sample of firefighter recruits in the current study experienced a 16.5% gain in mean estimated VO2max during the first eight weeks of training, but lost 1.3% of that gain in the last eight weeks of training. A limitation of the current study is that a submaximal step test was used to estimate VO2max values, as VO2max testing with a treadmill or cycle ergometer was not possible in the available testing environment. Future research should be conducted to confirm the adaptations observed in the current study with those among a larger sample, utilizing a laboratory-based method to obtain VO2max values.
Until the current study, no research had been cond-ucted to monitor the observed changes in ΔHR during fire training academies. Similar to the observed improvements in estimated VO2max, the firefighter recruits in the study experienced a 12.8% improvement in mean ΔHR within the first eight weeks of training, and lost 2.8% of that gain over the next eight weeks of training. These findings are consistent with previous literature which suggests that strength and endurance trained athletes experience a more rapid ΔHR following exercise than sedentary subjects [35–39] and that post-exercise ΔHR may be accelerated after approximately eight weeks of moderate-intensity training [40, 41]. Future research should be conducted to: (a) confirm the ΔHR adaptations observed in the current study in larger samples of firefighter recruits; (b) explore the clinical relevance of ΔHR for long-term health, fitness, and performance; and (c) determine the link between or independence of ΔHR and VO2max.
Since no relationship was identified between estimated VO2max and ΔHR, it is possible that VO2max and ΔHR represent two independent factors of cardiovascular health and/or fitness. Given that the step test used to predict maximal oxygen uptake in the current study was based on a 15-second post-exercise ΔHR measure, it is also possible that different calculations of ΔHR (e.g., 15-seconds post-exercise, 30-seconds post-exercise, 60-seconds post-exercise, etc.) or different mathematical components of ΔHR (e.g., slope of heart rate decline) may each be more or less related to estimations of VO2max. Furthermore, and although the findings were not directly connected to a stated purpose of the current study, since ΔHR in the current study was only related to body weight at T1 and was not related to body fat percentage at any time points, future research could be conducted to better understand the role of muscle mass and/or muscular strength as it relates to ΔHR.
As the participants in the current study started to experience a small loss of training gains in both estimated VO2max and ΔHR during the last eight weeks of the training academy, and since only 30% of U.S. fire departments have a preventive program in place to protect the cardiovascular fitness of firefighters after graduation [6], potential detraining patterns among firefighter recruits and graduates must be considered. Research suggests that detraining periods of just 3–6 weeks can result in 6–14% reductions in VO2max [42], and post-exercise ΔHR improvements achieved during eight weeks of training can be lost in just four weeks of detraining [40]. Other researchers have suggested that overall fitness can regress by 50% duringa 4–12 week period of detraining [43], and that endurance capacity can vary substantially within a period of detraining without measurable changes in VO2max [44]. Within the tactical domain, a recent study conducted by Liguori, Krebsbach, and Schuna Jr. [45] demonstrated that young, male Army Reserve Officers’ Training Corps (ROTC) cadets experienced a 4.3 –7.1% reduction in VO2max during their3-month summer break, findings which were consistent with those observed in research on sport athletes [46]. Given the strong links between cardiovascular factors such as VO2max and ΔHR and mortality [21–23], research is warranted to monitor the fitness levels of firefighter recruit graduates across multipletime points, examine the potential consequences of detraining among active duty firefighters, and establish the efficacy of interventions to prevent the loss of training gains achieved during fire training academies.
Conclusion
The current study is the first of its kind to describe the VO2max and ΔHR adaptations observed during fire training academies across multiple time points. The collective findings of the current study suggest that while fire training academies are effective in yielding cardiovascular fitness gains over a 16-week period, there may be opportunities to modify programs targeting the last eight weeks in order to facilitate continuation, or at minimum, retention of gains. Furthermore, results of the current study indicate that VO2max and ΔHR may represent two distinct but equally important factors of cardiovascular health and fitness, warranting the consideration of differentmodalities of training to best develop each factor. Much research is still needed to understand the clinical relevance of ΔHR in the contexts of long-term health and performance among firefighters.
Conflict of interest
The authors of the current study report that there are no conflicts of interest.
Footnotes
Acknowledgments
The authors of the current study would like toacknowledge the following individuals for their contributions to the successful completion of this research project: Jason Mims (Milwaukee Fire Department Health and Safety Officer), Aaron Zamzow (Madison Fire Department Firefighter) Mark Rohlfing (Milwaukee Fire Chief), Erich Roden (Milwaukee Battalion Chief), and the Milwaukee Fire Department’s peer fitness trainers.
