Introduction
The work performed by military firefighters is very complex and subdivided into different tasks that require substantial physical performance such as muscle strength, power, endurance, aerobic power, and cardiovascular endurance as well as an established psychological equilibrium. Indeed, these workers are called upon to engage in emergency intervention and drills in regard to both old and new threats (27). Physical stress, caused also by strenuous training, can involve many risks for the cardiovascular and respiratory systems, as well as for skeletal muscles, and may provoke a reduction in immunologic responses (10,22,26). Firefighting activities may also cause great psychological stress, inducing hormonal changes as demonstrated by increased levels of cortisol in the plasma (31).
Moreover, current firefighting protective gear is heavy, thick, multilayered, and bulky, and it exacerbates the challenge of thermoregulation because of limited water vapor permeability, increased metabolic load, and insulative properties (21,24,29). Considering the intense nature of their work and the fact that higher levels of training are correlated to a decreased risk of injury (5,26), the important question that arises from these assumptions is, Do firefighters possess high enough levels of aerobic capacity, physical fitness, and emotional stability to perform in a safe and efficient manner?
The high number of job-related injuries per year has led organizations, such as the American Fire Protection Agency, the International Association of Firefighters, and the International Association of Fire Chiefs, to consider and suggest physical training recommendations for firefighters. The Italian military firefighters carry out a lot of drills to reach adequate technical competency; however, no training is undertaken to improve their aerobic capacity and physical fitness. In fact, the Italian Air Force recommends only 2 hours per week of cardiovascular training without any specific program of intervention. The “Standardization of Physical Fitness Maintenance Program for Fire-Fighters” (Stanag 7162), a specific training program, will be applied only from June 2009.
Because there is limited information regarding the psycho-physical conditions of Italian military firefighters who perform routine firefighting duties and tasks and, because this occupational hazard is unavoidable, the study of the psycho-physical parameters affected by firefighting activity is a key step in understanding the importance of the physiologic imbalances induced. The aim of this research was to determine the physiologic and psychological responses to typical activities performed by firefighters who took part in a supervised live-fire work performance test and to examine the trend in these responses over the following 24 hours. These data may contribute to reducing the gap present in the literature on the physical exertion and psychological strain during typical activities of Italian military firefighters. These results will be also helpful in developing appropriate training intervention programs for firefighters.
Methods
Experimental Approach to the Problem
To evaluate the physiologic conditions in which military Italian firefighters operate during routine duties and to consider the psychological stress to which they are exposed, a supervised live-fire work performance test was set up. The cardiovascular condition, overall physical fitness, and emotional response of the firefighters were evaluated during the fire drill and over the 24-hour period after this work at the “G. Vassura” Airport in Rimini, Italy. Cardiovascular and psycho-physical responses of recruit firefighters were investigated by measuring heart rate (HR), energy expenditure as metabolic equivalent units (METs), skin temperature (T.Sk.) and galvanic skin response (GSR).
In this study, multivariate linear step-wise regression between dependent variables (HR, METs, T.Sk., and GSR) and predictor variables (body mass index [BMI], height, weight, age) was chosen to allow us to analyze the physiologic responses of firefighter recruits during a supervised live-fire work performance test, also taking into consideration the characteristics of the protective equipment used, and to evaluate their influence on task performance. This approach shows the cross-sectional nature of this work.
Subjects
This study was carried out at the “G. Vassura” Rimini Airport in September 2007 with the protocol being approved by the Military Institutional Review Board. Thirteen healthy military firefighters were recruited to perform a battery of fitness and job-related performance tests. Table 1 reports the descriptive data (mean, SDs) regarding sex, age, body weight, weight of subjects wearing full firefighting protective clothing and self-contained breathing apparatus, height, BMI, percentage body fat (%BF), smoking, and years of military firefighting service.
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Table 1: Descriptive data.
Before the study, participants attended a presentation outlining the purpose and procedure involved. All firefighters had passed their annual physical examination required by the Armed Forces and were on active duty during the procedure test. Their physical activity background ranged from sedentary to fairly active. Some had been doing some weight-based training, and some had been engaged in aerobic training. The research project and methods used were also approved by the Ethics Committee of Urbino University (Italy), and the all participants were informed about the project and the risks of the research and provided written informed consent before participation.
Environmental Conditions
The meteorologic conditions recorded during the performance test by the military weather station at the airport were clear skies; wind: variable direction/speed 0 to 8 knots; humidity 85%; air temperature 23.15°C.
Procedures
All tests were overseen by experienced investigators who had been trained in the proper technique, format, and procedures for all tests, which were explained and demonstrated to all participants to ensure uniform procedures. The firefighters completed a questionnaire providing descriptive information, including age, sex, and years of military fire service.
Dressing and Weighing
During work, subjects wore their own military standard protective firefighting turnout gear, gloves, Nomex flash hood, helmet, and self-contained breathing apparatus (SCBA). In all cases, the gear met the European Fire Protection Standards (EN523, EN367, EN366, UNIEN1486, EN340). Tissue cotton station pants and a fire t-shirt were worn beneath the turnout gear, along with underwear, shorts, socks, and running shoes. During dressing, an HR monitor (Polar S720i) and a metabolic holter device, SenseWear PRO2 Armband (SP2) developed by Body Media (Pittsburgh, PA, USA) were applied. The SP2 monitor is a wireless body monitor that is worn over the triceps of the right arm. The SP2 uses a series of noninvasive biometric sensors to continuously measure different physical parameters (heat flux, GSR, T.Sk., near-body temperature, and motion, determined from a 2-axis accelerometer). Several studies have demonstrated the usefulness and accuracy of the Sensewear Pro Armband in measuring estimated energy expenditure and physical activity under free-living conditions (8,14,15,35,38). Subjects were weighed while wearing protective fire Nomex underclothes and with firefighter protective clothing.
Work Performance Tests
The work was performed in 2 sessions. The first session corresponded to acclimation (acclimation phase), during which subjects, completely dressed in their protective clothing, had to stand still for 5 minutes, the required time for all variables to reach the steady-state values after adding the equipment. The second session was a fire-extinguishing drill (work phase). An iron tank of kerosene (20 L) was set on fire, and water was used to extinguish the fire to increase the difficulty of the drill. In detail, 5 tasks were performed: a) carrying a hose for approximately 20 m; b) pushing a water pump trailer for approximately 10 m; c) pulling the hose toward the fire; d) fire extinguishing; e) return to the initial conditions (Figure 1). Environmental temperatures, humidity, and wind conditions were recorded at the beginning of the first session.
Figure 1: Flow chart of experimental design.
Measurements
Heart Rate Measurements
Heart rate was monitored using a Polar S720i transmitter attached with an elasticized belt fitted around the chest and taped in place. Its infrared technology allowed us to download data directly to a PC without a separate interface. Heart rate was recorded every 5 seconds during the acclimation and work sessions.
Energy Expenditure, Skin Temperature Measurements, and Galvanic Skin Response
Energy expenditure as METs, T.Sk., and GSR were recorded using the multisensor body monitor SenseWear Pro Armband (20) on the upper right arm over the triceps muscle of each subject before dressing and for the following 24 hours. Physiologic body signals from the 4 sensors (T.Sk., heat flux, GSR, and 2-axis accelerometers) were combined with “context recognition” patterns. These algorithms are the result of controlled experiments in which physiologic data from the armband and metabolic carts were compared and validated. Validations of resting and active energy expenditure were performed against doubly labelled water (35) and metabolic carts (14,20) showing a high degree of correlation. The SenseWear data were then processed using the Inner View Research 5.0 software.
Anthropometric Data
Height and weight BMI and %BF were measured for every individual. Standing body height was measured without shoes to the nearest 0.5 cm. Subjects were weighed without shoes and wearing only underclothes. Body mass index was calculated as weight in kilograms divided by the height in square meters (kg/m2); %BF was estimated from an individual's weight and girth measurements (neck, waist, and height) by applying the following formula: (%BF = 495/(1.0324 - .19077 (log(abdomen - neck)) + 0.15456 (log(height))) - 450) (11), also taking age into account (9).
Statistical Analyses
All values are expressed as mean ± SDs and/or standard error. The correlation between dependent variables and predictor variables (BMI, height, weight, age) was evaluated using multiple linear regression analysis, with stepwise selection of predictor variables. All parameters were observed in the acclimation phase and the work phase with respect to the relative baseline. The level of confidence was at p < 0.05. Test-retest reliability for the dependent variables was determined by use of an intraclass correlation coefficient. Statistical analyses were performed using STATISTICA 6 software (Statsoft, Tulsa, OK, USA).
Results
As a group, the subjects were of average height; however, the BMI and the estimation of the %BF, used to determine whether subjects are under- or overweight, were found to be 25 kg/m2 or greater and with a mean of 23.61% (min 19.8 - max 29.4%), respectively, denoting that the group was clinically overweight (9,11).
The performance evaluated was composed of several tasks that are typical of real work situations (simulated action of fighting fire, dragging, lifting, and controlling active fire hoses, lifting and carrying heavy material, etc.). The mean time the firefighters needed for the entire exercise (acclimation and work phases) was 18.77 minutes, but this varied according to individual performances from 18 to 20 minutes. In this study, during the simulated job, the firefighters' average HR was 90.00 ± 9.81, and their peak HR reached 179.43 ± 12.36 beats·min−1 (96.89 ± 7.35% of age-predicted maximum heart rate [HR max]). The average and peak HR are considered “hard (vigorous)” and “very hard,” respectively, by the American College of Sports Medicine (2). During this work day, firefighters spent a mean of 1.8 METs ± 0.2.
Figure 2 shows the HR data collected during the work phase and highlights the 44.29% increase during the 5-minute acclimation phase (mean baseline - acclimation: 65.82 - 119.56 b*min−1), a subsequent exponential increase during the first 3 minutes of work followed by a slow increase, up to 60.41%, during the remaining work phase (mean baseline - work phase: 65.82 - 167.43 b*min−1). Figure 3 graphically displays MET (A) T.Sk. (B), and GSR (C) values during the work phase and the following 24 hours. As expected, a significant increase in all parameters was observed in the acclimation phase with respect to the relative baseline: METs 58.86% (mean baseline - acclimation: 0.85 - 2.36 kcal/kg/h), T.Sk. 7.48% (mean baseline - acclimation: 30.06 - 32.53 °C); and GSR 84.96% (mean baseline - acclimation: 0.110 - 0.979 uSiemens). A subsequent exponential increase in all values followed by a linear increase was noted during the work phase: METs 87.51% (mean baseline - work phase: 0.85 - 7.524 kcal/kg/h); T.Sk. 10.62% (mean baseline - work phase: 30.06 - 33.67 °C); GSR 94.60% (mean baseline - work phase: 0.110 - 1.94 uSiemens).
Figure 2: Heart rate (HR) response during work phase. Values are mean percent (±SD) calculated as [(Acclimation - Baseline)/Acclimation]*100; [(Work - Baseline)/Work]*100.
Figure 3: A) Skin temperature (T.Sk.), B) galvanic skin response (GSR), and C) metabolic equivalent units (METs) responses during work performance test and the following 24 hours. Values are means (±SD).
Metabolic equivalent units and T.Sk. values returned to normal levels within a few hours after the performance test (Figure 3, A and B). In contrast, the GSR showed a different recovery rate, taking between 6 to 12 hours to return to normal initial levels (Figure 3C).
The multiple linear regression analysis was set up with the item showing the correlation with basal metabolism by correlation analysis between dependent variable (acclimation, work, and recovery minimum, maximum, and average) and predictor variables (BMI, age, weight, height) (Table 2). The main finding in this analysis was that the mean and minimal HR values were strongly correlated with the BMI during the acclimation phase (beta 0.59, p < 0.001; beta 1.09, p = 0.003 respectively) (Figure 4A) as were the mean and HR max values during the work phase (beta 1.08, p = 0.05; beta 1.17, p = 0.04, respectively) (Figure 4B). Moreover, HR showed a significant correlation with weight during the acclimation phase (beta 0.46, p = 0.03 ) (Table 2).
Table 2: Multivariate linear step-wise regression analysis.
Figure 4: Relationship between body mass index (BMI) versus heart rate (HR) during A) acclimation phase (mean and minimum value) and B) work phase (mean and max value).
Mean and minimal METs values were significantly correlated with the age of subjects during the acclimation phase (beta 0.46, p = 0.01; beta 0.49, p = 0.008, respectively) (Figure 5A). Maximal METs values were also correlated with the weight of the subjects during the work performance test (beta 0.51, p = 0.03), (Figure 5B).
Figure 5: Relationship between age versus metabolic equivalent units (METs) during A) acclimation phase (mean and minimum value) and weight versus METs during B) work phase (maximum values).
With regard to the recovery phase, no significantly correlated data were found except for the mean values of T.Sk., which were higher in the lighter-weight subjects (beta -0.61, p = 0.03), (Figure 6), indicating a faster return to the basal temperature level in the lighter subjects. No correlations between predictor and dependent variables were found for GSR.
Figure 6: Relationship between weight versus skin temperature (T.Sk.) during recovery phase (mean value).
The test-retest method for the dependent variables showed the following ICC values: HR (R2 = 0.95 p < 0.05), METs (R2 = 0.85 p < 0.05), T.Sk. (R2 = 0.83 p < 0.05), GSR (R2 = 0.80 p < 0.05). Validity and repeatability of the SenseWear Armband as an energy expenditure detection device has been recently acquired (17).
Discussion
The data obtained demonstrate that the physical fitness and anthropometric characteristics of firefighters influence their performance of firefighting tasks. Among the different parameters considered, BMI is the most important variable responsible for the physiologic responses of firefighters during live-fire work. Multivariate linear regression analysis demonstrated that BMI has a greater effect than other parameters in increasing HR during the different phases of the drill (acclimation and work phases).
In particular, in the acclimation phase, the HR of the recruited subjects was found to increase considerably, even while simply standing still wearing the protective clothing and equipment, the weight of which, approximately 28 kg, represents an additional load for the firefighters. This is in agreement with the results reported by Holewijn (13), showing that the physiologic strain in terms of HR increased considerably while standing still with a load of 10.4 kg as compared with a situation without any additional weight. Louhevaara et al. (19) also demonstrated that a set of gear weighing 24 kg reduces the performance of the wearer by 25%, and the size of the clothing and the number of textile layers also increase the energy consumption of the wearer and thus the heat loss required (18,37). Moreover, the levels of HR of the firefighters in the present study were highly correlated with the BMI not only in the acclimation phase but also in the work phase; considering that most of the recruits were overweight, we may assert that a high BMI added stress on the cardiovascular system in these workers.
In multivariate linear step-wise regression analysis, the variables that resulted independently and significantly associated with the METs achieved were age and weight. The MET is the weight-relative unit that represents a multiple of the resting rate of oxygen consumption (1). The METs values are useful when considering exercise intensity and calculating the energy cost of exercises. It is generally accepted that people unexceptionally use 3.5 mL·kg−1·min−1 as the resting rate of O2 to calculate energy consumption (2).
In the present study, the subjects recruited had a mean age of 35 (range 24-46) years, with a mean work experience of 16 years of firefighting. The minimum and mean METs were found to be significantly correlated with the age and weight of the subjects, indicating that these factors directly influence performance, increasing energy expenditure in older and overweight subjects. Our results for the acclimation phase clearly indicate that older subjects have higher METs values than do younger firefighters. This indicates that, in older subjects, the added weight of the protective clothing alone leads to a greater energy expenditure than in younger subjects. It has been demonstrated that physiologic and muscular decline is positively correlated with age if adequate physical exercise is not taken (6,25,30). Lemon and Hermiston (16) reported that professional firefighters aged 20 to 29 years had an average O2max of 44 mL·kg−1·min−1. When these professional firefighters were evaluated at age 40 to 49 years, this value had decreased to 34 mL·kg−1·min−1. Saupe et al. (28) observed a 45% decline in O2max (47.7 to 26.0 mL·kg−1·min−1) from age 20 to 60 years in professional firefighters. Sothman et al. (34) found that professional firefighters with a O2max of less than 33.5 mL·kg−1·min−1 were more susceptible to fatigue and thus to failing to complete a standardized firefighting protocol. Therefore, the percent decline in physical performance for firefighters is comparable with that of a sedentary population, indicating that the firefighters studied did only modest exercise/physical training outside of their work. This statement is in agreement with the findings of Sothman and coworkers (18,19,37). These low levels of physical activity outside the workplace are consistent with the low average O2 maximum of 31.5 mL·kg−1·min−1 measured in firefighters (36).
During the work phase, a statistically significant correlation was found between METs and the weight of the subjects, indicating that heavier subjects must make a greater effort than lighter-weight colleagues. Although no correlation was found between age and MET during the work phase, this could be because the older subjects carried out the task more slowly and “economically” in terms of time and energy cost because no time limit was given. Indeed, Sothman et al. (32-34) indicate that older firefighters probably do the job differently and more efficiently than younger firefighters.
As regards the variable of T.Sk., it is important to highlight that this was measured using the metabolic holter with the T.Sk. sensor placed on the right arm of the firefighters, and therefore the firefighters' clothing and workgear covered them. The site of the metabolic holter was chosen because the device was calibrated by the manufacturer for use as an arm band, and the external heat exposure could have been interfered with the data collection. Although in the literature rectal temperature has been reported as a parameter to measure body temperature, T.Sk. has been demonstrated to be useful in terms of ease of measurement and of signal trend revealed during the drill and the period of recovery postexercise. As soon as the firefighters entered the work phase, all variables increased rapidly as expected, and the T.Sk. of all firefighters in this phase increased by approximately 3°C with respect to the baseline. The external temperature measured by the armband was constant during all phases of the performance test. Thus, this trend was mostly caused by the heat produced by the body and not because of heat exposure. The simulated tasks were in fact performed in an environment with much lower temperature than firefighters would normally experience while at a fire scene. In a real situation with a live fire, firefighters could be exposed to worse environmental conditions, and the heat could be much higher. The added temperature in those situations will greatly increase the demand on the cardiovascular system because heat dissipation is vital (26).
The mean values for the T.Sk. during the recovery phase were higher in the lighter-weight subjects. In these subjects, the T.Sk. returned faster to the baseline values than it did in the heavier ones. Therefore, it appears that the body mass of the subjects influences the T.Sk. during the recovery phase.
Galvanic skin response gives a measurement of electrical conductance in the skin and provides information on the activity of the sweat glands, which reflects variations in the psychological, emotional, and attention states of the subject (3). This is affected by nervous system responses, and it is not just a reaction of increased conductivity caused by augmented sweat emission because of the exercise stress. Situations that provoke anxiety or involve strenuous exercise lead to a significant increase in both the cortisol levels in the plasma and GSR. However, although cortisol is directly correlated with physical exertion, GSR levels are highly variable in that they reflect the subject's perception of anxiety (7,12,23). In the present study, the high GSR levels recorded during the work phase underline the high degree of emotional stress to which the firefighters were subjected. If, on the one hand, the increase in this variable, along with the others, was expected, on the other hand, the values for the recovery phase were unexpected in that they returned to normal levels only 12 hours after completion of the work phase. This result indicates that high levels of psychological stress remain, even after physical recovery. This finding could have implications for work-rest cycles in firefighters.
Our data are in agreement with those of previous studies that showed that the physical load involved when carrying protective gear represented a great physiologic demand on firefighters (4). In addition, repeated exposure to high anxiety occurring during the real, live emergencies are also responsible for significant cardiovascular stress. Firefighters should be strongly encouraged to participate in programs aimed at minimizing age- and inactivity-related decrease in physical performance by regular physical training, with exercises that are relevant for real firefighting actions to allow them to perform fire suppression tasks safely and efficiently.
Practical Applications
Valid information regarding the activity of military firefighting is fundamental for understanding the physical demands of this work and for planning specific and adequate fitness training. Fatigue arises from a number of sources with considerable interplay between firefighters' behavior, physical condition, and the fireground environment. The strain experienced by firefighters can include physiologic responses such as elevated HR and sweating and subjective responses such as increases in perceived exertion and thermal discomfort.
Although this study is based on a simulated job, the firefighters' physical activity (as represented by average %HR and peak %HR) is considered “hard” and “very hard,” respectively, by the American College of Sports Medicine (2). The individual responses of the subjects to the live firefighting task was found to be positively correlated with age, BMI, and weight, demonstrating that their physical fitness and anthropometric characteristics had a significant influence on work performances.
Moreover, the protective equipment worn by these workers added stress on their cardiovascular system; in particular, the older subjects showed higher METs than the younger ones, even when simply wearing protective equipment while standing still.
The data obtained may be of use in setting up specific training programmes that meet the real needs of firefighters in terms of physical fitness. In particular, new Italian Air Force regulations requiring physical fitness training alongside technical training will be introduced for firefighters by 2010. Accordingly, it will be important to identify the fundamental physical fitness tests for these workers to establish suitable protocols. This may require testing aerobic capacity more frequently, measuring body composition, and maintaining a BMI less than 25. Fire agencies can advise their personnel on the physical activities they can undertake to prepare physically for the fire season, increasing their resistance to fireground fatigue.
This study also contributes to filling the gap in the literature regarding this category of workers, providing useful information on the physiologic variations that are produced during firefighting activities and on the psychological and physical stress to which military firefighters are exposed during their normal daily work routine. These features are important for the safety, productivity, and well-being of firefighters.
Acknowledgments
This study would not have been possible without the participation of the volunteers and support of the commanding officers of the Italian Airforce at the Airport “G. Vassura” of Rimini, Italy. The authors are grateful for the technical assistance of the personal of Airport “G. Vassura” during the live-fire work performance test and Dr. Elisabeth Ferguson at the Faculty “Lingue e Letterature Straniere” of the University of Urbino “Carlo Bo,” Italy, for help with manuscript preparation. The authors have no conflicts of interest.
References
1. ACSM.
Guidelines for Exercise Testing and Prescription (3rd ed). Philadelphia: Lea & Febiger, 1986.
2. ACSM.
Guidelines for Exercise Testing and Prescription (7th ed). Baltimore: Lippincott Williams & Wilkins, 2006.
3. Boucsein, W.
Electrodermal Activity. New York: Plenum Press, 1992.
4. Bugajska, J, Zuzewicz, K, Szmauz-Dybko, M, and Konarska, M. Cardiovascular stress, energy expenditure and subjective perceived ratings of fire fighters during typical fire suppression and rescue tasks.
Int J Occup Saf Ergon 13: 323-331, 2007.
5. Cady, LD, Bischoff, DP, O'Connell, ER, Thomas, PC, and Allan, JH. Strength and fitness and subsequent back injuries in firefighters.
J Occup Med 21: 269-272, 1979.
6. Findley, BW, Brown, LE, Whitehurst, MG, Russell, A, and Susanna, A. Age-group performance and physical fitness in male firefighters.
J Strength Cond Res 9: 259-260, 1995.
7. Fredrikson, M, Sundin, O, and Frankenhaeuser, M. Cortisol excretion during the defense reaction in humans.
Psychosom Med 47: 313-319, 1985.
8. Fruin, ML and Rankin, JW. Validity of a multi-sensor armband in estimating rest and exercise energy expenditure.
Med Sci Sports Exerc 36: 1063-1069, 2004.
9. Gallagher, D, Heymsfield, SB, Heo, M, Jebb, SA, Murgatroyd, PR, and Sakamoto, Y. Healthy percentage body fat ranges: an approach for developing guidelines based on
body mass index.
Am J Clin Nutr 72: 694-701, 2000.
10. Garver, JN, Jankovitz, KZ, Danks, JM, Fittz, AA, Smith, HS, and Davis, SC. Physical fitness of an industrial fire department vs. a municipal fire department.
J Strength Cond Res 19: 310-317, 2005.
11. Hodgdon, J and Beckett, M. Prediction of percent body fat for U.S. navy men and women from body circumferences and height. Reports no. 84-29 and 84-11. San Diego, CA: Naval Health Research Center, 1984.
12. Hoehn, T, Braune, S, Scheibe, G, and Albus, M. Physiological, biochemical and subjective parameters in anxiety patients with panic disorder during stress exposure as compared with healthy controls.
Eur Arch Psychiatry Clin Neurosci 247: 264-274, 1997.
13. Holewijn, M. Physiological strain due to load carrying.
Eur J Appl Physiol Occup Physiol 61: 237-245, 1990.
14. Jakicic, JM, Marcus, M, Gallagher, KI, Randall, C, Thomas, E, Goss, FL, and Robertson, RJ. Evaluation of the SenseWear Pro Armband to assess energy expenditure during exercise.
Med Sci Sports Exerc 36: 897-904, 2004.
15. King, GA, Torres, N, Potter, C, Brooks, TJ, and Coleman, KJ. Comparison of activity monitors to estimate energy cost of treadmill exercise.
Med Sci Sports Exerc 36: 1244-1251, 2004.
16. Lemon, PW and Hermiston, RT. Physiological profile of professional fire fighters.
J Occup Med 19: 337-340, 1977.
17. Linden, CB. Accuracy and reliability of the SenseWear Armband as an energy expenditure assessment device.
BodyMedia White Papers, 2002.
18. Lotens, WA. Clothing design for work in the cold.
Arctic Med Res 46: 3-12, 1987.
19. Louhevaara, V, Ilmarinen, R, Griefahn, B, Kunemund, C, and Makinen, H. Maximal physical work performance with European standard based fire-protective clothing system and equipment in relation to individual characteristics.
Eur J Appl Physiol Occup Physiol 71: 223-229, 1995.
20. Malavolti, M, Pietrobelli, A, Dugoni, M, Poli, M, Romagnoli, E, De Cristofaro, P, and Battistini, NC. A new device for measuring resting energy expenditure (REE) in healthy subjects.
Nutr Metab Cardiovasc Dis 17: 338-343, 2007.
21. McLellan, TM, Jacobs, I, and Bain, JB. Influence of temperature and metabolic rate on work performance with Canadian Forces NBC clothing.
Aviat Space Environ Med 64: 587-594, 1993.
22. Melius, J. Occupational health for firefighters.
Occup Med 16: 101-108, 2001.
23. Moya-Albiol, L, Salvador, A, Costa, R, Martinez-Sanchis, S, Gonzalez-Bono, E, Ricarte, J, and Arnedo, M. Psychophysiological responses to the Stroop Task after a maximal cycle ergometry in elite sportsmen and physically active subjects.
Int J Psychophysiol 40: 47-59, 2001.
24. Nunneley, SA. Heat stress in protective clothing. Interactions among physical and physiological factors.
Scand J Work Environ Health 15(Suppl 1): 52-57, 1989.
25. Pollock, ML, Foster, C, Knapp, D, Rod, JL, and Schmidt, DH. Effect of age and training on aerobic capacity and body composition of master athletes.
J Appl Physiol 62: 725-731, 1987.
26. Rhea, MR, Alvar, BA, and Gray, R. Physical fitness and job performance of firefighters.
J Strength Cond Res 18: 348-352, 2004.
27. Roberts, MA, O'Dea, J, Boyce, A, and Mannix, ET. Fitness levels of firefighter recruits before and after a supervised exercise training program.
J Strength Cond Res 16: 271-277, 2002.
28. Saupe, K, Sothmann, M, and Jasenof, D. Aging and the fitness of fire fighters: the complex issues involved in abolishing mandatory retirement ages.
Am J Public Health 81: 1192-1194, 1991.
29. Selkirk, GA, McLellan, TM, and Wong, J. Active versus passive cooling during work in warm environments while wearing firefighting protective clothing.
J Occup Environ Hyg 1: 521-531, 2004.
30. Short, KR, Bigelow, ML, Kahl, J, Singh, R, Coenen-Schimke, J, Raghavakaimal, S, and Nair, KS. Decline in skeletal muscle mitochondrial function with aging in humans.
PNAS 102: 5618-5623, 2005.
31. Smith, DL, Petruzzello, SJ, Chludzinski, MA, Reed, JJ, and Woods, JJ. Selected hormonal and immunological responses to strenuous live-fire firefighting drills.
Ergonomics 48: 55-65, 2005.
32. Sothmann, MS, Landy, F, and Saupe, K. Age as a bona fide occupational qualification for firefighting. A review on the importance of measuring aerobic power.
J Occup Med 34: 26-33, 1992.
33. Sothmann, MS, Saupe, K, Jasenof, D, and Blaney, J. Heart rate response of firefighters to actual emergencies. Implications for cardiorespiratory fitness.
J Occup Med 34: 797-800, 1992.
34. Sothmann, MS, Saupe, K, Jasenof, D, and Blaney, J, Fuhrman, SD, Woulfe, T, Raven, PB, Pawelczyk, JP, Dotson, CO, Landy, FJ, Smith, JJ, and Davis, PO. Advancing age and the cardiorespiratory stress of fire suppression: determining a minimum standard for aerobic fitness.
Hum Perform 3: 217-236, 1990.
35. St-Onge, M, Mignault, D, Allison, DB, and Rabasa-Lhoret, R. Evaluation of a portable device to measure daily energy expenditure in free-living adults.
Am J Clin Nutr 85: 742-749, 2007.
36. Swank, AM, Adams, KJ, Barnard, KL, Berning, JM, and Stamford, BA. Age-related aerobic power in volunteer firefighters, a comparative analysis.
J Strength Cond Res 14: 170-174, 2000.
37. Teitlebaum, A and Goldman, RF. Increased energy cost with multiple clothing layers.
J Appl Physiol 32: 743-744, 1972.
38. Welk, GJ, McClain, JJ, Eisenmann, JC, and Wickel, EE. Field validation of the MTI Actigraph and BodyMedia armband monitor using the IDEEA monitor.
Obesity (Silver Spring) 15: 918-928, 2007.
