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A Simple Method to Analyze Overall Individual Physical Fitness in Firefighters

Calavalle, Anna R.; Sisti, Davide; Mennelli, Giacomina; Andolina, Giuseppe; Del Sal, Marta; Rocchi, Marco B.L.; Benelli, Piero; Stocchi, Vilberto

Journal of Strength and Conditioning Research: March 2013 - Volume 27 - Issue 3 - p 769–775
doi: 10.1519/JSC.0b013e3182600554
Original Research
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Calavalle, AR, Sisti, D, Mennelli, G, Andolina, G, Del Sal, M, Rocchi, MBL, Benelli, P, and Stocchi, V. A simple method to analyze overall individual physical fitness in firefighters. J Strength Cond Res 27(3): 769–775, 2013—The aim of this study was to identify the main components that determine firefighters' level of physical fitness using a stair-climbing test. The age, weight, height, body fat, and V[Combining Dot Above]O2max of the firefighters were recorded before the trial, and percentage of heart rate reserve (%HRR) was recorded during the stair climbing. Nonlinear modeling of HRR time series and Principal Component Analysis (PCA) was applied to the data to isolate a small number of variables that quantify overall individual physical fitness. The HRR was represented as a function of time using the sum of linear and trigonometric functions. Four main factors that influence performance, obtained from PCA analysis, emerged (78.2% of total explained variance): the capacity to carry the extra load (22.8% of total variance); the effect of body fat (19.6% of total variance); the influence of age in the task (19.3% of total variance); and the overall fitness level (16.4% of total variance). This approach allowed us to make a rapid assessment of each subject's fitness level. Such an assessment could be used in planning individualized functional training programs to improve each firefighter's job performance and reduce injuries and hence save time, energy, and financial resources.

Department of Bio Molecular Sciences, Sport Sciences Section, “Carlo Bo” University, Urbino, Italy

Address correspondence to Anna R. Calavalle, anna.calavalle@uniurb.it

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Introduction

It is crucial for firefighters to be physically fit, and the lack of an appropriate regular exercise program for these professionals is associated with job-related injuries (29). Moreover, in a study conducted between 1994 and 2004, Kales et al. showed that heart disease caused 45% of on-duty deaths among the U.S. firefighters (14,21,34). Data regarding Italian firefighters collected by the Ministry of the Interior (2008) showed that a high percentage of the total injuries between 2003 and 2007 occurred during interventions. In particular, in 2007, 1,078 of 2,181 injuries occurred during interventions (nearly 50%, confirming the trend for the entire period). In the same year (2007), a total of 76,878 workdays were lost (26). The lack of an appropriate regular exercise program for these professionals may contribute to high on-duty injury rates and deaths caused by heart disease (31). A firefighter's job is characterized by long periods of low-intensity work and occasional bursts of activity that range from moderate to very high intensity (5), accompanied by mental and emotional stress (6,27). The energy expenditure required for these occasional bursts of activity is very high (8). Such episodes can go on for extended periods in extreme temperatures, and the protective equipment that firefighters must wear adds to the strain (13).

With a wide range of tasks to perform, experience plays a key role in firefighting, but age is inversely proportional to levels of physical efficiency (20). The relationship between fitness/age and cardiac risk is well established. Cady et al. (7) showed that firefighters who possess a below-average capacity for physical work are 2.6 times more likely to suffer a myocardium heart attack than their fitter colleagues. In addition, demographic changes, such as the increase in average life expectancy, the need to continue working to a more advanced age, together with the need to limit new hiring, will lead to the further aging of workers in all fields (28,30,36). It is clear that firefighters should follow a well-organized regular physical fitness program (4); nevertheless, in Italy, they are not required to do so, and moreover housing Italian Fire Departments have no gym or special room for fitness activity. Such fitness programs should be designed to meet firefighters' specific needs and be calibrated according to the most common and demanding kinds of tasks that they are called on to perform. Furthermore, it is crucial to quantify the overall job-related fitness level of firefighters, a first step in prevention to reduce the total number of injuries. Several authors have used the stair-climbing test (4,20) to quantify specific physiological demands, but, to the best of our knowledge, they did not process the data to quantify different independent characteristics that determine an individual's physical fitness.

In this investigation, we suggest processing the stair-climbing data to simultaneously quantify several independent characteristics that determine specific physical demands. The data collected for each firefighter should then allow us to develop simple individualized training programs that can be implemented anywhere.

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Methods

Experimental Approach to the Problem

The aim of the investigation was to identify the main components that determine firefighters' level of physical fitness through a stair-climbing test and to then use the resulting data to develop an easy-to-implement individualized fitness program for each firefighter. To make a rapid economic assessment, of which components influence the performance of each of the subjects in our sample group in carrying out the most demanding task that firefighters are called on to perform, we gathered our data in 2 stages. The first stage of the investigation was developed so that it could be performed in any setting equipped with a treadmill and the necessary equipment to record anthropometric and physiological variables commonly used in formulating a functional training program. In this stage, we measured subjects' height, weight, and waist and neck circumference to calculate body mass index (BMI) and body fat percent (BF%). Then using the treadmill test, we evaluated the V[Combining Dot Above]O2 submaximal and in turn calculated the V[Combining Dot Above]O2 maximal (modified Balke protocol). The second stage of the experiment, carried out in the fire training tower in the Fire Department courtyard, consisted of the collection of physiological data during the stair-climbing test. Several studies have shown that body fat and V[Combining Dot Above]O2max are the two parameters that have the greatest influence on our overall physical well-being and firefighters' ability to perform specific tasks (4,14,35). Other studies have shown the importance of the role of the stair-climbing test in determining the suitability of an individual to perform the duties of a firefighter (13,17,23). In our investigation, nonlinear modeling of percentage of heart rate reserve (%HRR) time series showed the distinctive characteristics of the stair-climbing test performance, and the Principal Component Analysis (PCA) method was chosen to highlight which factors are indicative of the overall fitness of firefighters.

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Subjects

The experiments were carried out on 35 healthy male firefighters (age 44.9 ± 4.79 years) of the “Comando Provinciale di Pesaro e Urbino” (Italy). Before beginning, participants attended a presentation outlining the study's purpose and the procedures that would be used. All participants were informed of the experimental risks, signed an informed consent form, and completed a questionnaire indicating their age, sex, years of service, and physical activity background. The subjects ranged from sedentary to fairly active. Their principal anthropometrical and physiological characteristics are reported in Table 1. The study was approved by an institutional review board of human subjects.

Table 1

Table 1

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Procedures

Anthropometric Data

Each subject's height, weight, BMI, and BF% were measured. Standing body height was measured without shoes to the nearest 0.5 cm. Body mass index was calculated as weight in kilograms divided by height in square meters (kg·m−2). Body fat percent was determined from an individual's weight and girth measurements (neck, waist, and height) according to Hodgdon and Beckett (11).

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Maximum Aerobic Capacity

Estimated V[Combining Dot Above]O2 maximum was obtained using a submaximal treadmill test (Figure 1), modified Balke protocol (2). This method was adopted because it provides very reliable data at a low cost, with reduced risks and limited demands placed on subjects (1). Estimated V[Combining Dot Above]O2max was obtained by having subjects maintain a constant speed with 2.5% increases in the gradient every 2 minutes, starting from a gradient of 0%. Heart rates (HR) of all the subjects were recorded for the duration of the test. Tests were terminated when subjects reached 85% of their age predicted maximal HR (220 − age) or when they elected to stop. For further elucidation, see Balke and Ware (2).

Figure 1

Figure 1

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Stair-Climbing Test

The test consisted of climbing up and down a flight of stairs (there were 69 steps in the flight and each step was 15 cm high) as fast as possible for the 5-minute testing time (8,23). Subjects had to maintain a steady pace without running or holding on to the handrail and could only take one step at a time. Testing time (in seconds) was recorded by a sports instructor who climbed along with the participants throughout the test, starting at the moment the firefighter started to climb the first step and finishing at the moment he touched the last step with both feet. The tests were performed in the late morning over a 1-week period in March in a training tower located near the firehouse. The temperature in the training tower ranged from 10 to 15° C. During the test, subjects wore their own standard protective firefighting turnout gear, gloves, Nomex flash hood, helmet, and self-contained breathing apparatus (SCBA). In all cases, the gear met European Fire Protection Standards (EN 531 A, B1, C1, EN 469/97, EN 469/95). Tissue cotton station pants and a fire T-shirt were worn beneath the turnout gear, along with underwear, shorts, socks, and running shoes. Such gear is routinely used in real-life emergencies. The total weight of the gear with an air bottle and a hose was approximately 20 kg. To simulate the most common sort of operation performed by firefighters, rescuing a victim from a building, the subjects carried one 30 kg high-rise extra load on their shoulders (Figures 2 and 3). Moreover, to simulate normal job conditions, the firefighters' habits (food and beverage consumption, hours of sleep per night) were not altered in any way. There was a period of acclimation before the test to reduce variability (acclimation phase). During this phase, the subjects, completely dressed in their protective gear, had to stand still for 5 minutes, the required time for all variables to reach steady-state values after adding the equipment. It was decided not to give the subjects time to warm up to better simulate the real conditions of a sudden intervention.

Figure 2

Figure 2

Figure 3

Figure 3

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Heart Rate Measurements

Heart rate was monitored using a Polar S720i transmitter (Body Media, Pittsburgh, PA, USA) attached with an elasticized belt fitted around the chest and taped in place (Figures 3 and 4). Heart rate was recorded every 10 seconds during the rest phase, and stair-climbing test HR data were expressed as a %HRR. This index of cardiovascular strain is recommended by the American College of Sports Medicine (1,3), and it takes into account individually measured resting and maximal HRs. All tests were overseen by experienced investigators who had been trained in the proper technique, format, and procedures for each of the tests. The tests were explained and demonstrated to all the participants to ensure uniform procedures.

Figure 4

Figure 4

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Statistical Analyses

Nonlinear Fitting

The results of the stair-climbing test were quantified using an appropriate function, deriving frequency, and phase from the sum of a straight line, with slope and intercept and a sinusoidal function, defined by amplitude, frequency, and phase. The value of %HRR measured during the test (%HRRt) was considered as a time-dependent variable; the value of %HRRt had a specific basal value (%HRR0) for each subject during the course of the test, and this value had a linear tendency to increase (Δ%HRR/t) because there was a progressive exertion. In addition, the value underwent some fluctuations (A%HRR) as a function of the moment in which each subject was going up or down the flight of stairs. Subjects also carried out a fixed number of fluctuations (ω) at the set time of 5 minutes. Hence, the following function, with the above-mentioned parameters, was used:

Nonlinear regression was performed determining unweighted least squares estimates of parameters using the Levenberg-Marquardt method. The goodness of fit of the obtained values of the stair-climbing test was quantified by the determination adjusted coefficient (R2).

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Principal Component Analysis

To simultaneously obtain factors that influence the overall individual fitness of our subjects, analysis of the main components (PCA) was performed. This method aims to reduce the complexity of the data by decreasing the number of variables that need to be considered. Principal Component Analysis was performed on the estimators obtained from the nonlinear regression (%HRR0, Δ%HRR/t, A%HRR, ω), age, weight, height, body fat, V[Combining Dot Above]O2max. Principal Component Analysis is an approach to factor analysis that considers the total variance in the data, unlike common factor analysis. Principal Component Analysis generates a matrix that contains the factor loadings of all the variables on all the extracted factors. The factor loadings in PCA are the simple correlation between the factors and the variables. A varimax solution yields results that make it as easy as possible to identify each variable with a single factor. The number of factors was evaluated using the Kaiser criterion (eigenvalues >1) and scree plot. To determine if the variables were correlated highly enough to provide a reasonable basis for PCA, the Bartlett test was also performed. Factor loading under 0.35 is considered low and was not considered. Statistical analyses were performed using SPSS for Windows (version 13.0, Chicago, IL, USA).

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Results

In the stair-climbing test, 422 ± 69 steps were climbed, at a rate of 84.4 ± 13.9 steps per minute. The %HRR value of the sample under study was 82.5 ± 9.9. This value is close to the maximum %HRR values, which correspond to a “vigorous-maximum” physical activity level (25). The %HRR as a function of time is represented using function 1; it was proposed as the union of two equations:

  • 1) A linear component, that is,
  • , represents the linear growth rate as a function of time, starting from %HRR0. Clearly, the higher the value of the intercept (%HRR0), the smaller the range in which the cardiac frequency can fluctuate during the stair-climbing test. In the sample, the intercept has a value of 71.83 ± 11.27. On the contrary, the slope of the line (Δ%HRR/t) quantifies the variation rate over time, that is, how much the slope increases every 5 seconds. The value recorded in the sample was 7.58 ± 4.36% (Figure 4);
  • 2) A trigonometric component, that is,
  • , represents the fluctuation of the %HRR as a function of time. The A%HRR value shows an average value of 6.48 ± 2.78, whereas ω shows an average value of 0.058 ± 0.019, corresponding to 2.83 complete cycles ± 0.92 cycles, that is, the complete number (climbing up and down a training tower). The proposed function shows a discrete fit with all the experimental data. The multiple adjusted determination coefficient (R2) shows an average value of 0.84 ± 0.14. All scatter plots between variables used for PCA showed a reasonable linear dependence when variables were correlated.

Principal Component Analysis generates a matrix that contains the loading factors of all the variables on all the factors extracted. The loading factors in PCA are the simple correlation between the factors and the variables. A varimax solution yields results that make it as easy as possible to identify each variable with a single factor. The Bartlett test yielded significant results (p < 0.001). This means that the variables are correlated highly enough to provide a reasonable basis for PCA analysis. Both the scree plot and eigenvalues (with value >1) support the conclusion that the initial correlation matrix can be reduced to 4 principal components (PCs), which together explain 78.2% of the data variance. The first component (PC1) accounted for 22.8% of the total variance in the data sets; A%HRR, weight, and height are highly correlated with PC1. The second component (PC2), which accounted for 19.6% of the total variance, included body fat, V[Combining Dot Above]O2max, and weight. The third component (PC3), representing 19.3% of the total variance, is correlated to %HRR0, age, and V[Combining Dot Above]O2max. The fourth component (PC4), accounting for 16.4% of the total variance, comprises Δ%HRR/t, ω, and V[Combining Dot Above]O2max, which are highly correlated with this component. Principal Component Analysis results are reported in Table 2. These results allowed us to highlight the individual characteristics of our sample.

Table 2

Table 2

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Discussion

The aim of this study was to identify the main components that determine firefighters' level of physical fitness using a test involving stair climbing, one of the most demanding specific psychophysical tasks executed by firefighters. The data from this test may then be used as a basis to design functional individualized training programs to improve the subjects' performance, reduce the risk of injury, and hence save time, energy, and financial resources. Existing literature has thoroughly dealt with the energetic and psychological costs of the tasks firefighters are frequently required to carry out (6,12). This investigation focuses on the influence of the following variables on the subjects' fitness levels: weight, height, body fat, age, V[Combining Dot Above]O2max, and 4 parameters obtained from nonlinear regression of %HRR time series, followed by PCA. The PCs that influenced the specific performance of each subject were isolated, and the characteristics of the these 4 components are illustrated below.

Principal Component 1 describes the relative workload, which may explain the inverse association of the amplitude of the sinusoidal fluctuation of the %HRR with weight and height. The relative workload is lower for subjects with a larger body mass because the same type of task with the same absolute load has a greater impact on smaller subjects. Wearing protective clothing and carrying SCBA added to the subjects' physical load, which increases cardiovascular strain in 2 ways: by impeding movement and by increasing the total mass of the individual (6). Moreover, during the trial, the subjects carried another additional load of 30 kg; hence, the relative increase in carried weight and the physical exertion are higher for smaller subjects (12). Subjects with a greater weight had fewer sudden jumps in %HRR because they felt the additional weight less during the stair climbing. Nevertheless, their average HR was similar to that of the other subjects because a taller person has a greater body mass and requires more energy to move (12).

During the test, cardiovascular strain, indicated by HR response, was maximal or near maximal, as has been reported in several other studies involving simulated firefighting or related physical activities (30). Such tasks should therefore be performed by persons with a larger body mass because the physiological strain that they experience is less than that of smaller persons carrying the same load (12).

Principal Component 2 describes the effect of body composition. Our results show that V[Combining Dot Above]O2max is inversely associated with body fat and weight. These results are in agreement with other studies (33) in which V[Combining Dot Above]O2max was inversely correlated to the sum of four skinfolds. Nokes (22) reported that body mass index and waist circumference were inversely associated with cardiorespiratory fitness. Excess body fat is also a risk factor for cardiovascular morbidities (4), and there is a strong consensus that firefighting is a physically demanding occupation requiring good cardiovascular fitness (15). Our results showed that the expression of V[Combining Dot Above]O2 peak relative to total mass was significantly reduced for the high-fat groups compared with their matched counterparts, which is consistent with the findings of Louhevaara et al. (18). Other studies (6,19) have shown that individuals with more fat tend to have more difficulty performing certain tasks, especially those requiring weight-bearing activity and cardiorespiratory endurance. Finally, Williford et al. (35) report a strong correlation between the percentage of body fat and stair-climbing ability: Subjects with the highest percentages of body fat performed the worst.

Principal Component 3 describes the role of physiological age. It showed how age is associated negatively with V[Combining Dot Above]O2max. This result is consistent with data in literature for the general population, which show a decline in maximal aerobic power at a rate of around 5 ml·kg−1·min−1 per decade after the age of 30 years in both endurance-trained and untrained individuals (10). Specific studies on firefighters show the same results (30,38). The decline in V[Combining Dot Above]O2max that worsens with age could be mitigated with exercise training (24,25).

Principal Component 4 describes the state of fitness. This last component showed that high V[Combining Dot Above]O2max values are associated with a smaller increase in HRR during the physical exertion and a better performance with a greater number of steps climbed. Indeed, several studies report the importance of V[Combining Dot Above]O2max as a measure of cardiorespiratory endurance (32). V[Combining Dot Above]O2max is a valid index measuring the limits of the cardiorespiratory system's ability to transport oxygen from the air to the tissues at a given level of physical conditioning and oxygen availability (10). In a person with a high maximal aerobic capacity, a given sub maximal workload is likely to cause less cardiovascular strain and a lower HR than it does in a person with lower maximal aerobic capacity (12). The studies analyzed by Barr et al. (4) in a recent review showed that firefighters had a mean aerobic power ranging from 39.6 to 61 ml·kg−1·min−1. If we compare this value with the mean V[Combining Dot Above]O2max of our sample, which was 39.56 ± 6.11 ml·kg−1·min−1, we can observe that our values were equal to the minimum values in the studies reviewed by Barr et al. (5). This is probably because of the high average age of our sample group (44.9 ± 4.7 years). Numerous studies (9,16,34) have sought to determine an adequate level of V[Combining Dot Above]O2max for firefighters because it is an important factor influencing their ability to perform their aerobically demanding jobs safely and effectively. Indeed, the International Association of Firefighters (2000) has recommended that firefighters be able to reach a maximal oxygen uptake of at least 42 ml·kg−1·min−1.

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Practical Applications

Though it is a simulation, the stair-climbing test comes very close to creating the conditions firefighters face in real situations. In this investigation, we applied nonlinear modeling to HRR time series and PCA to a specific task, which simulates the task that firefighters are called on to perform the most frequently. Hence, the test could be implemented within the context of the normal drills that are routinely performed in firehouses, alternating the crews on the basis of their shifts. Specific individualized training programs could then be designed for firefighters on the basis of the results of the stair-climbing test and the subsequent nonlinear modeling and PCA analysis. Ideally, every firehouse should have an area suitable to house the simple equipment necessary for these individually tailored programs to be implemented as rapidly as possible. The benefits of an ongoing program aiming to improve and maintain the physical efficiency of firefighters could be very useful in terms of reducing sick days, injuries, and cardiovascular risk. Such data could also be used in the selection of new recruits and to reduce risks associated with the increasing average age of firefighters.

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Acknowledgments

The authors are grateful to all the volunteers in the Pesaro-Urbino Fire Department whose training program was interrupted by the tragic earthquake in the Abruzzo Region on April 6, 2009. These firefighters assisted in rescue efforts immediately after the quake hit and continued their work until just a few months ago.

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Keywords:

stair-climbing test; heart rate modeling; public safety; heart rate

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