Epidemiological studies have identified several risk factors for physical training-related injuries. These include lower amounts of physical activity, cigarette smoking, slower maximal effort run times, and both high and low levels of flexibility (7,14–16,29,30). Many of these previous investigations (7,13–16) have studied these associations in the basic combat training (BCT) environment. BCT is a reliable model with which to study activity-related injuries because the physical training program and living conditions are well standardized. During BCT, activity levels are essentially identical for all individuals because they train together throughout the day and must perform and qualify on the same tasks. Environmental conditions are also similar since individuals train in the same areas, live in the same barracks, eat in the same mess halls, and are provided with equal opportunity for rest and sleep. Since 1995, BCT has been gender-integrated so that men and women perform side-by-side in the same units, allowing gender comparisons under conditions of similar activity and environment. This degree of training, environmental, and gender standardization is difficult to achieve elsewhere.
Previous studies of risk factors for training-related injuries (7,13,15,16,29,30) have used indirect, or performance-oriented, estimates of physical fitness such as maximal-effort run times and push-ups. Physiologic measures of specific components of physical fitness have not been examined and could provide additional information. For example, it has been shown that slower maximal effort long-distance run times are associated with greater likelihood of injury (7,14,16). This association with injury could be due to a number of variables associated with running performance such as aerobic capacity, pacing ability, or motivation. Examining associations between injuries and V̇O2max could help determine specifically whether aerobic capacity is an important factor. Likewise, there are conflicting data (7,14,16,29,30) on associations between injuries and body composition as estimated by body mass index (BMI) or skinfolds. Measures of body composition by dual energy x-ray absorptiometry (DEXA) may help clarify this relationship. Finally, few studies (3) have examined associations between training-related injuries and strength or power, and results of these few investigations are not clear.
The major purpose of the present investigation was to examine associations between injuries and physical fitness with special attention to physiological measures of aerobic capacity, body composition, and muscle strength. Several lifestyle characteristics (cigarette smoking and prior physical activity) were also examined in relation to injury because these have been shown to be important in past investigations (14,16).
Subjects and study design.
The initial sample consisted of 756 men and 452 women participating in BCT in two battalions (nine basic training companies). Part of the study involved detailed physiological testing and a questionnaire. Because of time, personnel, and equipment limitations, only 182 men and 168 women performed the physiological tests and 225 men and 186 women were administered questionnaires. Personnel for this testing were selected from among the volunteers by the military training cadre based primarily on who had completed initial inprocessing before BCT (clothing issue, medical checks, financial issues, etc.). In general, volunteers selected for testing were those who arrived earlier at Ft Jackson SC because these individuals were more likely to have completed inprocessing than individuals arriving later. All of the women and most of the men (N = 178) who participated in the physiological tests also completed questionnaires. For the physiological testing, potential volunteers were briefed in several large groups on the purposes and risks of the study, and they provided their informed consent to participate by signing a volunteer agreement affidavit. An institutional Human Use Review Committee that assessed the risks to the subjects and the potential benefits approved the study protocol.
The study was conducted in three phases: physiological testing, Army physical fitness testing, and injury data collection. The physiological testing was performed the week before the subjects began BCT. The Army Physical Fitness Test (APFT) was administered 1–2 d after arrival in BCT (3–7 d after the physiological testing). Injury data were collected as subjects were removed from BCT or at the conclusion of the 8-wk basic training cycle. These phases are described below.
Physiological testing was completed in a single session, and the order of tests was such that physically demanding tests were interspersed between two less physically demanding tests. Unless otherwise specified, testing was conducted with subjects in sneakers, socks, shorts, t-shirt, and underwear. Sample sizes differed for each test because of technical problems with equipment and the inability to retest because of the subjects’ military training schedule. A maximum of 32 subjects were tested each day (half in the morning and half in the afternoon).
Aerobic power was measured using a continuous uphill treadmill running protocol. An initial 5-min warm-up was performed at 0% grade and 2.68 m·s-1 (6 mph) for men and 2.24 m·s-1 (5 mph) for women. If the heart rate was less than 150 beats·min-1 by minute 5 of the warm-up, treadmill speed was increased 0.45 m·s-1 (0.5 mph) for the remainder of the test. After the warm-up, the treadmill grade was increased by 2% every 3 min until there was less than a 2-mL·kg-1·min-1 (or 0.15-L·min-1) increase with increased grade or until voluntary exhaustion. Volunteers wore a nose clip and were connected to an on-line oxygen uptake system. The on-line system consisted of an Applied Electrochemistry S-3A oxygen analyzer, a Beckman LB-2 carbon dioxide analyzer, and a K.L. Engineering flowmeter turbine, interfaced with a Hewlett-Packard model 9122 computer.
Body composition was measured with DEXA using a LUNAR (Madison, WI) system. Scanning began at the head and progressed in 1-cm slices to the feet with the machine set to the fast 10-min scanning speed. LUNAR software (version 3.6) provided estimates of percent body fat and bone mineral density.
Four measures of muscle strength were obtained. Dynamic lifting strength was measured using the incremental dynamic lifting (IDL) device and a one-repetition maximum procedure (43). Three measures of isometric strength included a seated arm and shoulder pull (24), a seated leg press (24), and a standing upright pull involving the legs and back (25). For all three isometric measurements, subjects were instructed to apply force smoothly, without jerking, to reach a maximum within 1–2 s and to hold the force for 4–5 s. The maximal force was measured by a Baldwin, Lima, Hamilton (BLH, Waltham, MA) load cell and displayed on a BLH model 450A transducer indicator.
Leg power was assessed with a vertical jump using the Vertec® apparatus. Subjects performed three countermovement jumps with at least 15-s rest between each. The vertical distance of the highest jump was recorded.
The sit-and-reach test (45) was used as a measure of hamstring flexibility (42). Subjects sat on the ground with their legs fully extended and their upper body at about a 90° angle to their legs. With fully extended arms, they bent forward as far as possible and pushed on a sliding bar. A scale on the side of the bar indicated the cm of displacement with the bottom of the foot as the reference point.
Subjects were administered a questionnaire that addressed their cigarette smoking habits and past physical activity. The smoking question asked: “Which statement best describes your smoking habits in the last year?” Subjects could respond in one of the following 5 categories: “I have never been a smoker, I smoked but quit, I smoke 10 or fewer cigarettes per day, I smoke 11 to 20 cigarettes per day, or I smoke more than 20 cigarettes per day.” One physical activity question asked: “Outside of work, how would you rate yourself as to the amount of physical activity you performed before entering the Army, compared with others of your age and sex?” Subjects could respond in one of the five following categories: “much more active, somewhat more active, about the same, somewhat less active, much less active”(44). Another physical activity question asked: “Over the last month, how often did you exercise or play sports for 15 min or more?” Subjects could respond in one of five categories: “No exercise or sports in the last month, less than once per week, 1 time per week, 2 or 3 times per week, or 4 or more times per week.”
Army Physical Fitness Test (APFT) data.
Subjects were administered the standard APFT by training personnel (drill sergeants). The test involved completing the maximal possible number of push-ups and sit-ups in separate 2-min periods and a maximal effort 3.2-km (2-mile) run for time. For the push-up, a subject was required to lower his or her body in a generally straight line to a point where his upper arm was parallel to the ground, then return to the starting point with elbows fully extended. For the sit-up, a subject’s knees were bent at a 90° angle, fingers were interlocked behind the head, and a second person held the participant’s ankles, keeping his feet firmly on the ground. The subject raised his upper body to a vertical position so that the base of the neck was anterior to the base of the spine and then returned to the starting position. The 3.2-km run was performed on a cinder track and the time to complete the distance was recorded.
Health care providers who were not part of the study diagnosed injuries and recorded the information in the subjects’ medical records. The investigators screened the medical records and specific information was obtained for each visit to a health care provider. This information included the date of visit, diagnosis, body part injured, disposition (final medical recommendation), and any days of limited duty. Limited duty involved a physical restriction that prevented the subject from full participation in training events.
An injury was defined as an event (presumably an energy exchange) that resulted in damage to the body and for which the subject visited a medical care provider. Injuries could be due to overuse (long-term energy exchanges resulting in cumulative microtrauma) or acute trauma (sudden energy exchanges resulting in sudden, overload trauma). Heat injuries, cold injuries, and animal bites were not included in the analysis (these were less than 3% of the total).
There were three injury categories (injury case definitions). The first category (all injuries) included all visits to a health care provider for any type of injury. The second category was called a time-loss injury and involved one or more days of limited duty. The third category was a lower extremity injury, which was any injury to the legs, pelvic area, or lower back.
In addition to the injury data, physical characteristics were obtained from the subjects’ physical examination (conducted on entry into the Army) contained in the medical records. These data included age, stature, and body mass. Body mass index was calculated as body mass/stature2(22).
Descriptive statistics were calculated for the physiological variables, APFT data, and physical characteristics. Comparisons between men and women were made by independent sample t-test.
To examine associations between potential injury risk factors and injuries, continuous variables were converted into categorical variables by separating them into groups with approximately equal numbers of subjects. Where sample sizes were larger (physical characteristics and APFT scores), subjects were separated into four groups (quartiles). Where sample sizes were smaller (physiological variables), subjects were separated into three groups (tertiles). The two questions on physical activity were collapsed to three categories, preserving symmetry around the central response category (because of the small number of subjects at the extremes).
Because of subject attrition during the course of the investigation, person-time injury incidence rates and survival analysis were used for most of the analysis. Person-time injury incidence rates were calculated as subjects with one or more injuries (numerator) divided by the total number of days in BCT (denominator). To obtain people injured/100 person-days, this number was multiplied by 100. Individuals who were removed from BCT before completion of the study were included: their total time in BCT was added to the denominator and if they had an injury they were include in the numerator. Log linear analysis (Poisson regression) adjusting for the time in BCT produced a chi-square test that indicated differences in incidence rates between groups. The general linear model procedure in STATA (Version 6.0, College Station, TX) was used for this analysis. For subjects completing BCT (those with equal exposure time), cumulative injury incidence was calculated as individuals with one or more injuries divided by the total number of subjects in the group. Group comparisons were made by chi-square using the Statistical Package for the Social Sciences (SPSS, Version 10.0.5, Chicago IL).
Univariate analysis of potential risk factors was performed using Cox regression (a survival analysis technique). Time to the first time-loss injury was compared between various levels of each potential risk factor. Once a trainee had a time-loss injury, his or her survival time was terminated. Those not completing BCT had their times censored at the day they left the unit. Comparisons between risk factor levels were made using the Wald statistic with the risk of the reference level set at 1.0.
A multivariate Cox regression was then used to identify independent injury risk factors and examine interrelationships among factors. Survival times and censoring were determined in the same manner as the univariate analysis. Independent variables were selected to include specific physical fitness components, lifestyle variables, and physical characteristics. These variables were peak V̇O2, push-ups, sit-ups, IDL, upper body static strength, upright pull, vertical jump, flexibility, body fat, cigarette smoking, exercise or sports frequency, age, and body mass. A backward stepwise selection procedure was used with the exit criteria set at P = 0.05. Each level of a potential risk factor was compared to a reference level (except the reference level itself) to obtain adjusted risk ratios. The Statistical Package for the Social Sciences (SPSS, Version 10.0.5, Chicago IL) was used for the Cox regressions.
Of the 756 men and 472 women who started the study, medical records were obtained on 733 men and 452 women (97% and 95% of the male and female sample, respectively). There were 102 men and 108 women who were discharged from service before the completion of basic training and there were 14 missing medical records from this subgroup. There were 37 men and 39 women who left the training units under study because they were not able to complete required training requirements on time with their peers. They were given additional time to complete requirements in another BCT unit but were lost to follow-up for this study. Nine medical records were missing from among these individuals.
Table 1 shows descriptive statistics for the physical characteristics and APFT data. Table 2 shows the physiological measures. There were significant gender differences (P < 0.01) for all the variables in Tables 1 and 2, with the exception of age (P = 0.59).
Table 3 shows the injury incidence rate in each injury category for men and women. Women had over twice the injury rate of the men for all injuries, time-loss injuries, and lower extremity overuse injuries. Similarly, women had over twice the number of limited duty days, 67 d/100 person-weeks, compared with 27 d/100 person-weeks for the men. Common injury sites for men and women were similar. The five most common sites (% of total injury) for the men were the knee (21%), ankle (16%), foot (14%), low back (11%), and shin (8%). For women the five most common sites were the ankle (20%), foot (20%), knee (19%), shin (10%), and low back (7%). Injuries involving the lower body and low back accounted for 83% of the male injuries and 87% of female injuries. Overuse injuries accounted for 75% of male injuries and 78% of female injuries. For subjects completing BCT, cumulative injury incidence for men and women were 31% and 58%, respectively (P < 0.01).
Table 4 shows the relative risks of time-loss injury for various physical characteristics and APFT measures. Fewer push-ups and slower 3.2-km run times were associated with higher injury risk in both men and women. A lower number of sit-ups was associated with higher injury risk in men. Table 5 shows relative risks of time-loss injury among physiological variables and lifestyle characteristics. Lower peak V̇O2 and cigarette smoking were associated with higher risk of injury in both men and women. For men only, high and low levels of flexibility and lower exercise or sports frequency in the last month were also associated with injury.
Table 6 shows the results of the multivariate Cox regression. The model for the men was based on 147 individuals with complete data. Lower peak V̇O2, lower exercise or sport activity in the last month, and cigarette smoking in the last year were independently associated with the risk of a time-loss injury among the men. The model for the women was based on 138 individuals with compete data. Lower peak V̇O2 and cigarette smoking in the last year were independently associated with the risk of a time-loss injury among the women.
This study examined risk factors for injuries among young men and women during a physically active training program and under the standardized conditions afforded by the BCT environment. We confirmed some past findings (7,13,16,21,29,30,38) showing that in a physically active population, slower run times, fewer push-ups, and cigarette smoking were injury risk factors for both men and women; lower levels of previous physical activity and both high and low levels of flexibility were additional injury risk factors for men. We expanded on prior findings by measuring peak V̇O2, body composition, and muscle strength and examining the association of these physical fitness measures with injury. Our study also differed from some past studies in that we included in our analysis all individuals in our initial cohort who had medical data. Past investigations (13,16) only considered subjects who completed training.
Both men and women with lower peak V̇O2 had an increased likelihood of injury. Previous studies examining injury risk factors (7,13,16,21) have used maximal effort run times as a surrogate measure of aerobic capacity because run times are highly correlated with V̇O2max(20). Individuals with lower aerobic capacity will likely experience greater physiological stress during longer-term BCT tasks (e.g., running, drill and ceremony, road marching, obstacle courses, etc.) because they will utilize a higher percentage of their maximal aerobic capacity than individuals with higher aerobic capacity. This may increase the likelihood of injury through a variety of hypothetical mechanisms. Individuals with lower aerobic capacity will perceive BCT tasks as more difficult (5), and they may fatigue more rapidly for both cardiovascular and metabolic reasons (9,10,18). Fatigue may result in changes in gait (1), resulting in unaccustomed musculoskeletal stress on specific body areas (11,31). The combined cardiovascular, metabolic, biomechanical, and perceptual stress could make injuries more likely.
In the present study, body fat measured with DEXA demonstrated only a weak association with injury. BMI has been taken as an index of adiposity because it is correlated with percent body fat (22). Previous studies that have examined association between injuries and skin-fold estimates of body fat or BMI have produced equivocal results. These studies report no association between BMI and injuries (30), that both high and low levels of BMI were associated with injury (13,32), that lower BMI was associated with injury (7), and that high BMI was associated with injury (29). The one investigation that examined injuries and a skin-fold estimate of body fat (16) showed little association with injury, in agreement with the current study. One problem in assessing the association between body fat and injury risk in BCT is that individuals at the greatest extremes of body fat are not likely to be included in the sample because they would not meet military entrance standards. Individuals with excessive body weight (adjusted for height and age) or excessive amounts of body fat (adjusted for age) cannot enter the U.S. Army by regulation. Thus, basic trainees are likely to have a greater proportion of leaner individuals than that found in the general population. This same problem probably exists in studies of runners (30,32).
Four strength measures and one measure of leg power were examined in this study. None of these measures were associated with injury. In consonance with Cowan et al. (3), no association was found between the incremental dynamic lift and injuries. On the other hand, lower levels of muscular endurance (as measured with push-ups and sit-ups) were systematically associated with higher injury risk among both men and women, although the association between sit-ups and injuries among the woman was not a strong one. Fewer push-ups have previously been related to higher injury risk in men (13,16) but not women (13), whereas this study found an association for both genders. Many tasks, including the obstacle courses, bayonet courses, tactical training (low and high crawls), and climbing high towers, performed in BCT require use of the upper body. Although upper body injuries made up only a small portion of the total number of injuries in BCT, lack of upper body muscular endurance capacity may cause greater reliance on the lower body, possibly increasing injury risk in this area. Results of the present study suggest that muscular endurance is related to injuries among both men and women.
We found a bimodal relationship between flexibility and injuries in men; those most flexible and those least flexible were at higher risk of injury compared to those of moderate flexibility. This finding supports similar results from two other investigations (16,23). It is interesting that both of these previous investigations (16,23) measured variants of hamstring flexibility, as does the sit-and-reach test used here (42). In a study (23) that collected several lower body flexibility measures, hip flexion was the only measure that demonstrated a bimodal relationship with injuries. These data suggest specifically that hamstring flexibility has the bimodal association with injuries. The hamstring muscle group is unusual because it consists of three muscles, crosses two joints, and has long fibrous tendons. It is not clear why flexibility was not associated with injury among the women in the present study.
Among the lifestyle characteristics, cigarette smoking was an independent injury risk factor for both men and women. This is in consonance with other investigations in BCT (7,16) and findings in other occupational groups (34,40). Individuals are not permitted to smoke while they are in BCT, so any mechanism proposed to account for this association must take this into consideration. Smoking has effects on the immune system that could have long-term consequences for tissue healing even after smoking cessation (8,47). Wound healing in smokers is delayed and less complete, complications are more likely to arise, and cosmetic results are less satisfying (33,37,41). Experimental fractures in nicotine-exposed rabbits produce weaker bone tissue, less callus formation, and results in delayed or inhibited bone union (36,39). Tobacco extracts have been shown to decrease fibroblast recruitment, proliferation, migration, and contraction (2,35). Human studies involving experimentally induced arm wounds show that tobacco users produce less hydroxyproline, a marker of collagen production (17). It is possible that prior smoking may result in inadequate tissue healing and increase susceptibility to future injuries during vigorous physical activity.
For the men only, low physical activity before entry into the Army was associated with injuries. This agrees with past investigations of men in BCT (6,16). In the only other study to examine prior physical activity in women, no relationship with injury was found (13). Depending on the type, intensity, frequency, and duration, physical activity can result in favorable adaptations (e.g., higher aerobic capacity, greater muscle mass, and greater bone density) that may reduce the probability of injuries in BCT (28,46). It is not clear why prior physical activity was not associated with injuries in women.
One of the most consistently demonstrated risk factors for injuries in BCT is female gender. In the present study, the injury rate of women was over twice that of men. In previous studies, the injury incidence risk ratio (women/men) has ranged from 1.6 to 2.5 (12,13,26). This gender difference is not consistent with findings from civilian sports injury studies where men and women experience similar overall injury risk (27). The reason for this discrepancy may relate to differences in the relative activity intensity experienced in BCT compared with athletics. In athletics, men and women can compete separately and can voluntarily self-select the total amount and intensity of the sport. In BCT, men and women currently perform side-by-side, so that the relative activity intensity is greater for women than for men because of women’s lower average physical capacity (Tables 1 and 2). For example, on a fast military road march walking at an average speed of 4 miles·h-1, subjects would have required an energy equivalent of 14.2 mlO2·kg-1 body weight·min-1. The average male and female subject in the present study had peak V̇O2s of 51 and 39 mLO2·kg-1·min-1, respectively. The energy cost of the forced march would require a relative energy cost of 28% of the average man’s peak V̇O2 but 36% of the average woman’s peak V̇O2. Thus, the average woman’s relative marching intensity would be greater. This would result in higher cardiovascular and metabolic stress as mentioned earlier in this discussion. Similar arguments could be made for other aerobic tasks or tasks requiring muscular endurance.
Cigarette smoking and aerobic capacity were independent injury risk factors when considered in the multivariate model, a finding similar to another investigation (38). It has been shown that younger smokers and nonsmokers have similar aerobic capacities; however, older cigarette smokers have lower aerobic capacity than older nonsmokers (4,19). In the present study, male smokers and nonsmokers had similar aerobic capacities (mean ± SD peak V̇O2 for smokers = 51.1 ± 6.1, nonsmokers = 50.2 ± 6.2, P = 0.45) as did the women (mean ± SD peak V̇O2 for smokers = 39.6 ± 4.2, nonsmokers = 39.2 ± 5.7, P = 0.72). Whether cigarette smoking and aerobic capacity would be independent injury risk factors in older individuals is not known.
The present study indicates that although women have a higher injury incidence than men, both men and women will have a higher likelihood of injury if they enter BCT with lower aerobic capacity, lower muscular endurance, or with a prior history of smoking. In addition, men will be at greater injury risk if they have either high or low levels of hamstring flexibility, or have lower levels of physical activity on entry to BCT. Although these results confirm and expand on the results of past investigations, additional studies will be necessary to clarify associations between injuries and body fat and muscular strength. An appropriate intervention based on these data would be to increase aerobic fitness prior BCT and examine the effect on injury risk.
We would like to thank the individuals who participated in and made this study possible. The following individuals provided us substantial insights into the training process: LTC Robert Redfern, CPT Gibson, CPT Cole, CPT Ronald Steig, and 1LT Hasper. Individuals who provided us substantial administrative support included CPT Christine Held, MAJ Stoneman, Ms. Shivers, SFC Upshall, and CPT Goins. Technical support was provided by Ms. Elaine Christansen, COL Michael Smutok, LTC Max Ito, SSG Roberta Worsham, SGT Rebecca Gregg, SGT Ty Smith, SPC Gregory Loomis, Mr. Robert Mello, Mr. Peter Frykman, and Mr. Clay Pandorf. Ms. Judy Cuthie provided substantial statistical support.
Address for correspondence: Dr. Joseph Knapik, Directorate of Epidemiology and Disease Surveillance, U.S. Army Center for Health Promotion and Preventive Medicine, Aberdeen Proving Ground, MD 21010; E-mail: [email protected]
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