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Rhabdomyolysis in the US Active Duty Army, 2004–2006


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Medicine & Science in Sports & Exercise: March 2012 - Volume 44 - Issue 3 - p 442-449
doi: 10.1249/MSS.0b013e3182312745
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Rhabdomyolysis (RM) is a syndrome characterized by skeletal muscle degeneration and muscle enzyme leakage (22). The causes of RM are classified as either physical (i.e., gunshot wounds, traumatic crushing, obstruction of blood supply to muscles, or excessive muscle strain) or nonphysical (i.e., autoimmune muscle damage, electrolyte and metabolic disturbances, disorders of muscle energy supply, or infection).

Most cases of RM develop as a result of a physical event (muscle injury). However, the cause of RM is not always obvious. Huerta-Alardín et al. (19) reported that up to 85% of patients with major traumatic injuries will experience some degree of RM. Although rates among studies vary, approximately 15% of patients with RM will go on to experience acute renal failure (ARF) as a complication (19). On the other hand, RM may be part of the causal pathway in as much as 25% of ARF cases (19). Nonoccupational risk factors for RM include sickle cell trait (SCT), renal insufficiency, myopathy, certain medications (e.g., aspirin and lipid-lowering agents), heroin use, alcohol use, dehydration, inadequate fluid intake, exertional heat illnesses, malignant hyperthermia trait, and the ACE genotype (11,26,40).

Exertional RM (ERM) is a potential sequela of vigorous physical activity. Extended long-distance runs, long-distance hiking/marching, untrained participants, and elevated ambient temperature have been documented as factors promoting ERM (8,30,36), all of which are conditions that are commonly present in the military. Patients often not only present complaining of darkened urine and severe muscle pain but also may complain of weakness, stiffness, and reduced range of motion in affected muscles (34). ERM involves the substantial release of myoglobin and other intracellular biomaterials from skeletal muscle. This cascade of events may cause metabolic disorders (hypernatremia, hyperkalemia, hyperphosphatemia, hypocalcemia, etc.), ARF, and other serious sequelae (including death) (38).

RM is a relatively rare condition in the general US population, but considering the etiology of ERM, it follows that RM is a potentially common disorder encountered in the military setting (29). The rate of RM in the general population is difficult to establish with certainty but was estimated by one US study to be about two cases per 10,000 person-years (28). ERM specifically has been studied among military personnel, long-distance runners, and other competitive athletes (8,14,17,21). In a report of 19 soldiers who “marched intermittently over 4 weeks, carrying about 45 kg of kit, with a limited intake of food and water,” Aizawa et al. (1) found that “subclinical RM was not rare among the soldiers.”

The military and civilian communities have introduced extensive clinical mitigation measures to manage RM and reduce the risk of serious ERM. These clinical measures include better ERM diagnostic and treatment guidelines and identifying high-risk individuals (29). Despite these measures, ERM continues to result in a preventable clinical scenario seen by military and civilian health care providers. Research reports of RM in military personnel are limited to case studies or case series (1,33,39). Therefore, population-level RM rates for military populations remain elusive, and large-scale studies of risk factors for RM in this population remain challenging.

The Total Army Injury and Health Outcomes Database (TAIHOD) is a repository of administrative data on the US Active Duty Army (ADA) (2). It contains data from personnel and health records that can be used for a population-level analysis of clinically presenting RM. RM is diagnosed clinically by observing serum creatine kinase levels, but an official cut point signaling RM remains controversial (27). In a prospective study of high school students, RM was defined as creatine kinase > 1000 (24). However, in practice, most cases presenting clinically are prompted by symptomatology (such as weakness and severe muscle pain). Therefore, clinically presenting RM is most likely to be severe. Using the TAIHOD to capture RM cases (International Classification of Diseases, Ninth Revision (ICD-9) code 728.88), we will present absolute numbers and rates of clinically presenting RM, which will provide estimates on rates of severe RM in a military population.

The purpose of this study was to systemically describe the epidemiology of clinical RM within the ADA. To our knowledge, there are no recent descriptive studies presenting rates of RM in a large military population.


Study data

This study was completed using existing data obtained from the TAIHOD (2). The Defense Manpower Data Center (DMDC) compiles monthly master personnel files containing soldier-level demographic and occupational data; these were used to identify soldiers who were in the ADA in each year from 2004 to 2006. The DMDC also compiles the Contingency Tracking System data set, which contains dates of deployment to Operation Iraqi Freedom/Operation Enduring Freedom. The Patient Administration Systems and Biostatistics Activity agency provided clinical encounter data for the ADA for 2004–2006; these data sets include all inpatient and outpatient clinical encounters in both military and civilian health care facilities. Each data set contains at least four diagnostic codes in the ICD-9, Clinical Modification (ICD-9-CM) format associated with each encounter. The study population was limited to all US Army soldiers who were on active duty in any month from 2004 to 2006.

RM classification

A singular ICD-9 code for RM, 728.88, was used to identify all RM clinical encounters for the identified population. No attempt was made to separate ERM from nonexertional RM because we were not able to develop an algorithm that seemed reliable. The RM ICD-9 code came into use in the military beginning in 2003, so to account for transition, the study is limited to the years 2004–2006. An encounter was classified as a case of RM if 728.88 appeared in any of the first four diagnostic positions of the encounter. A soldier was considered as having an incident RM case on the date of the first clinical encounter reporting the RM ICD-9-CM code in the calendar year in which the incident case occurred. A soldier was considered as having a prevalent case on dates of clinical encounters reporting this code after the first encounter date within the calendar year. Although it is recognized that, in reality, an episode of RM may extend past one calendar year into the next, we were required to operationalize definitions of incident and prevalent cases to use administrative data for this analysis.

ARF classification

ARF can be considered a marker of severity when presenting with RM. The following ICD-9 codes have been found to be sensitive and specific for identifying ARF using administrative data: 584.5, 584.6, 584.7, 584.8, and 584.9 (37). A clinical encounter was classified as an ARF if any of these codes appeared in the first four diagnostic positions of the encounter. Appropriate cut points for time to ARF after incident RM were identified on the basis of clinical guidelines as follows: <30, 30–90, and 90–365 d.

Risk factor classification

The following risk factors for RM were considered: sex, age, race, ethnicity, marital status, education, length of service (LOS) in the military, Armed Forces Qualification Test (AFQT) category, grade, deployment history, and prior heat injury. Age was evaluated continuously, as well as classified into the following categories: <20, 20–25, 26–30, and >30 yr. Race was classified as white, black, Asian, American Indian, and other; ethnicity was classified as Hispanic and non-Hispanic. Although it is acknowledged that the term “black” is less favored than the term “African American,” because the native data from DMDC were collected using the term “black,” the results will be reported using this term. Education level was stratified as less than high school graduate, high school graduate (including test-based equivalency, as well as those who went on to college but had not yet obtained a college degree), college graduate (including those with a bachelor’s degree only), and advanced degree (beyond bachelor’s degree). Marital status was grouped into single, married, and divorced/widowed/separated. LOS was classified into the following categories: <90, 90–180, 181–269, and 270–364 d and ≥1 yr. All new recruits who gain access into the Army must take the AFQT at the time of entry; their score is placed on a percentile and then grouped into one of five AFQT categories. Individuals who gain access as officers are not required to take the AFQT; therefore, these findings only apply to enlisted soldiers and those officers who entered the Army originally as enlisted soldiers. Soldiers testing in higher categories (I and II) are placed on a more academically rigorous career track (e.g., legal, medicine), whereas those testing in lower categories (III and IV) are placed on less academic career tracks (e.g., combat arms). Those testing in category V are not eligible to enter the Army. For grade, enlisted soldiers were grouped as E1–E4, E5–E6, and E7–E9, with officers (including warrant officers) representing a separate group.

Soldiers were classified as having a history of deployment if the soldier was deployed in any prior year relative to the year the soldier was in the study population. For instance, an individual in the ADA in 2004 has a history of deployment if, on or before December 31, 2003, he/she was deployed during the study period. Mean deployment time in months at the beginning of each year was also reported for years prior.

To determine a yearly history of heat injury, the first four diagnostic code positions of all clinical encounters for each soldier in the preceding years were searched for the following codes: ICD-9-CM 992.2 and 992.6 (heat cramps); ICD-9-CM 992.1, 992.3, 992.4, 992.5, 992.7, 994.4, and 994.5 (heat exhaustion); ICD-9-CM 992.0 (heat stroke); and ICD-9-CM 992.8, 992.9, 276.0, and 276.1 (other heat injury) (13,15).

Analytic methods

First, all soldiers who were active for at least 1 month in the ADA from 2004 to 2006 were identified. From these individuals, soldiers with any incident RM during the same period were then identified. Because individuals may have more than one occasion when they experience RM, one soldier may have an incident case in multiple years. Absolute numbers and yearly unadjusted rates of RM per 10,000 soldiers were developed using incident cases that year as the numerator and all active soldiers that year as the denominator. It was found that all ADA soldiers have a minimum of at least one clinical encounter per year for routine preventive care (due to Army policy); therefore, using all ADA soldiers at risk for RM as the denominator was determined to be appropriate. Because a single soldier may have an incident case in multiple years, a single soldier’s case may be present in multiple yearly numerators.

Next, yearly rates of ADA soldiers with RM were then stratified by the following hypothesized risk factors: sex, age, race, ethnicity, marital status, education level, LOS, AFQT category, grade, deployment history, and prior heat injury. For each rate, the denominator consisted of the number of ADA soldiers who were active at any time during the given year in the given stratum, and the stratum-specific numerator was calculated as described above for yearly unadjusted rates. Lastly, the occurrence of an ARF after the first incident of RM was identified (using the ARF codes described above), and time from RM to ARF was calculated and presented as a percentage of all cases during the study period.

All analyses were conducted in SAS version 9.1 (SAS Institute, Cary, NC) and Microsoft Excel version 2007 (Microsoft Corporation, Redmond, WA). Investigators have adhered to the policies for protection of human subjects as prescribed in Army Regulation 70-25, and the research was conducted in adherence with the provisions of Title 45, Part 46 of the Code of Federal Regulations. This study maintains approval via expedited review by the Human Use in Research Committee at the US Army Research Institute of Environmental Medicine (Federalwide Assurance FWA00000953). The Human Use in Research Committee granted a waiver of informed consent for the study; more than 500,000 soldier records were used in the study, and it would not have been practicable to carry out the research if informed consent was required to be obtained.


During the 2004–2006 period, a total of 574,688 soldiers were in the ADA, and of these, 1203 (0.2%) met the criteria for clinically diagnosed RM at any time during this period. Table 1 presents the yearly profile of the ADA during this period, and Table 2 describes RM patients at the time they first became a patient with an incident case in this study. Compared with the background population (shown in Table 1), RM patients were more likely to be male (91% vs 85%), age 25 yr and younger (50% vs 43%–45%), and black (36% vs 21%–23%) and to have an LOS of <90 d (29% vs 12%–14%), a prior heat injury (3% vs <1%), and no history of deployment (72% vs 50%–66%).

Demographic profile of the US ADA, 2004–2006.
Demographic profile of patients with RM in the US ADA, 2004–2006.

Of the 1203 RM patients, 8% (n = 91) experienced ARF within 30 d of the initial RM diagnosis, and almost 92% (n = 1106) did not experience ARF for a year after the initial diagnosis. Of the 58 RM patients who had a previous heat injury (5% of patients), 31% had experienced a previous heat stroke, 53% had experienced previous heat exhaustion, 3% had experienced previous heat cramps, and 17% had another previous heat injury.

Figure 1 shows the unadjusted yearly rates of RM as well as RM rates stratified by sex. Unadjusted rates remained stable at 7–8 per 10,000 during the study period. Rates in men were one- to twofold higher than rates in women.

Rates of RM in the US ADA unadjusted and stratified by sex, 2004–2006.

For age, RM yearly rates were slightly higher than unadjusted among those age <20 yr (8–10 per 10,000 per year) and those age 20–25 yr (6–9 per 10,000 per year). Figure 2 shows yearly rates of RM stratified by race. The yearly RM rates in blacks are at least twice the rates in whites and reached as high as 14 per 10,000 soldiers in 2006. Yearly rates of RM in Hispanics versus non-Hispanics were comparable during the study period (5–6 vs 7–8 per 10,000).

Rates of RM in the US ADA stratified by race, 2004–2006.

For education level, a dose–response gradient was observed in that rates of RM are higher in those with lower education (less than high school = 8–10 per 10,000, high school = 7–8 per 10,000, college degree = 6–8 per 10,000, and advanced degree = 2–5 per 10,000). Concerning marital status, single soldiers had the highest rate each year (7–9 per 10,000), but this was not appreciably higher than that for married and divorced/widowed/separated (6–7 per 10,000).

Figure 3 shows yearly rates of RM stratified by LOS. Those with an LOS of <90 d had the highest rate of RM each year (14–19 per 10,000).

Rates of RM in the US ADA stratified by LOS, 2004–2006.

AFQT category IV had the highest rates of RM each year (7–10 per 10,000), which were one to two times higher than rates in category I (3–7 per 10,000). Rates of RM ranged between 6 and 10 per 10,000 for all enlisted categories; officers had the lowest rate each year (4–5 per 10,000). Concerning deployment history, rates were consistently lower for those who had a history of deployment (5 per 10,000) compared with those without a deployment history (8–11 per 10,000).

Figure 4 shows yearly rates of RM stratified by prior heat injury. Rates in the no-prior-injury category were 6–8 per 10,000 each year, which is comparable to the unadjusted rate. However, rates in those with a record of a prior heat injury were 7 to 11 times higher; rates were 52, 86, and 84 per 10,000 in 2004, 2005, and 2006, respectively.

Rates of RM in the US ADA stratified by prior heat injury, 2004–2006.


We observed that during the entire study period (2004–2006), the absolute numbers of annual clinically diagnosed ADA RM ranged between 382 and 419, maintaining a relative stable state throughout. ADA RM stratified rates were highest among those soldiers with a prior heat injury because ADA soldiers with a prior heat injury demonstrated a 7- to 11-fold increased relative risk when compared with ADA soldiers without a prior heat injury. In addition, soldiers with less than 90 d in service and black soldiers (Fig. 2) had much higher rates of RM compared with the overall rate of 7 to 8 per 10,000 in ADA soldiers.

The overall unadjusted observed yearly rate of RM in the ADA was 7 to 8 per 10,000. Comparing that to the US civilian reference population’s expected rate of 2 per 10,000 (28), the SMR found in the ADA was 3–4, indicating there are approximately 300%–400% more cases of RM in the ADA than in the reference population. In addition, we believe that ADA RM is likely underrepresented, given that our study focused only on RM that presented clinically. Actual rates of RM in the Army can be assumed to be higher, given many factors, most notably the unique, austere environment soldiers often occupy (through deployment and training). Moreover, given that the diagnostic code for RM only came into use in the military in 2003, it would be expected that a portion of RM encounters in military facilities may be miscoded as another condition. On the other hand, an RM diagnostic code may be present in a clinical encounter record at the point where the patient is suspected of having RM, but it is not confirmed. In these cases, RM may be overcounted, but for the reasons stated earlier, the potential for undercoding of RM in this population is much higher than the alternative of overcoding. Among clinically presenting patients, 8% developed concomitant ARF, which is lower than the estimate of approximately 15% of civilian RM patients who go on to experience ARF (19). This decreased ARF percentage may reflect the advanced medical training achieved by Army combat medics and health care providers.

Sex is not an established risk factor for RM, yet in all years evaluated, men had rates of RM that exceeded those of women by one- to twofold. Combat arms and other physically arduous Army occupations (Special Forces, Rangers, etc.) are limited to men (3). So, the lower prevalence of exposure of female soldiers to extreme environments that may induce RM (especially ERM) may account for the observed difference seen in our study. This gender difference may affect sex-specific RM rates in certain civilian occupations as well (e.g., firefighter, construction worker, security guard) because they have unique occupational exposures that are analogous to a soldier and are predominately filled by males (25).

The African-American race itself is not considered a risk factor for RM, but SCT is (26). SCT has traditionally been considered benign, but its role in the etiology of severe RM is reported (10). The prevalence of SCT in African Americans has been estimated to be 7%–8%, whereas in whites, it is only 0.16% (4,35). The higher prevalence of SCT in African Americans may account for the observed twofold higher rates in African-American ADA soldiers when compared with white ADA soldiers. The prevalence of this risk factor for RM should be considered in physically demanding occupations with a high level of participation by the African-American community. In August of 2010, the US Centers for Disease Control and Prevention reported rates of heat illnesses in high school athletes as high as 4.5 per 100,000 athletic exposures for boys’ football, a sport with a high participation among African-American youth (18). RM rates should also be considered in basketball, wherein the US African Americans make up approximately 74% of participants, and the sport is a physically demanding activity (20).

Higher education levels have not been established to be protective against RM. However, our findings that higher rates of RM are associated with lower levels of education in a dose–response gradient are consistent with findings for studies of cognitive ability, all-cause injury, and injury mortality in both civilian and military populations (5,31). We also found that RM rates were higher in the nondeployed, but this may be due to a type of “healthy-warrior effect,” in that soldiers sent to Operation Iraqi Freedom/Operation Enduring Freedom deployment are healthier by design than those who are ineligible for deployment (16,23).

RM rates in those with less than a high school education were 8–10 per 10,000, and RM rates in those who had less than 1 yr of service ranged from 14 to 19 per 10,000. As described earlier, a combination of dehydration, inadequate slow conditioning, and inadequate fluid intake would represent an environment conducive to the development of ERM. Not only do young soldiers new to the Army lack military experience, but also, many have not been exposed to arduous physical activity to the extent found in basic combat training (BCT) and, therefore, do not have the physical resiliency or know how (e.g., proper hydration during exercise, recognition of signs and symptoms) to prevent RM. Because RM can become epidemic secondary to physical fitness testing (12,24), it is not surprising that those undergoing BCT have an increased risk of suffering RM secondary to taking the Army Physical Fitness Test (6,33), which is administered several times during BCT. The aforementioned factors may account for the especially high RM rates seen in those with less than 180 d of service. Certainly, given the tight structure of the curriculum, BCT offers an ideal setting to administer preventive measures against RM, such as minimizing exercise in extreme heat and providing water for regular hydration. In the civilian population, young individuals in high school or college who lack exposure to intensive physical activities or sports would be at a similar elevated risk, and the RM preventive measures described above would be appropriate for this group as well (9). Although trainees who have enlisted but have not yet started BCT are required to attend the weekly 90-min Future Soldier training program administered by the US Army Recruiting Command, currently, this program does not emphasize training on the prevention of heat injury while exercising. However, the FSTP does allow tailoring so recruiters can work individually with trainees to coach them on physical activity and strategically increasing this activity as they prepare for BCT. For logistical reasons, new recruits spend differing amounts of time in the FSTP, so developing a formalized curriculum is prohibitive. Instead, a checklist (Future Soldier Pre-execution Checklist, as proscribed by US Army Recruiting Command Regulation 601-95 [32]) must be completed, and this includes addressing many administrative as well as physical activity efforts. An opportunity may exist for adding heat injury prevention training to this checklist. In addition, it would be prudent to consider expanding heat illness prevention campaigns to include college Reserve Officers’ Training Corps and high school JROTC programs as a method to reach individuals who are targeted in Army recruitment efforts such that they may be better prepared for the FSTP and subsequent BCT.

As recognized by O’Connor et al. (29), prior heat injury is a strong risk factor for subsequent heat injury (analogous to RM), and this finding was consistent in our data because those soldiers with a prior heat injury had rates of RM 7–11 times higher than those without a prior heat injury. The absolute numbers of RM patients with a prior heat injury increased from 14 in 2004 to 26 in 2006. This same phenomenon apparently holds true for civilian sports activities because a history of a previous heat illness has been identified as a risk factor for more serious heat-related events, especially in traditional late-summer sports (e.g., football, soccer, and cross-country running) (7,9). The increase in the number of yearly cases in the Army may be a result of increasing operational tempo, multiple deployments to Iraq and Afghanistan, increased training requirements/activities in extreme environmental conditions, or enhanced clinical attention to heat-related events. Our study demonstrated that 31% of these patients had a history of heat stroke, suggesting that the threat of significant heat injury sequelae (e.g., RM) is not simply associated with the most extreme heat condition. Of patients, 53% had a history of heat exhaustion, and 3% had a history of heat cramps, both of which many consider relatively benign conditions. Army leadership should be cognizant of this fact and should initiate aggressive intervention measures for all soldiers with a history of heat injury, regardless of severity. Moreover, the actual rate of those with previous heat injury may in reality be higher because we could only assess prior heat injury that took place after entry into the Army. Those individuals entering the Army with a history of heat injury could not be identified in our study. As per Table 1, each year, less than 1% of the ADA experienced a clinically diagnosed heat injury in previous years. RM intervention efforts could start by restricting extremely physically demanding activities (such as deployment and intense training activities) only to ADA soldiers who have never experienced a clinically diagnosed heat injury. From a strategic-level approach, restricting the activities of 2000–4000 soldiers per year would not severely affect Army missions yet would protect this vulnerable group from RM that could be severe and even fatal. However, operationally and tactically speaking, if these 2000–4000 soldiers were in a low-density mission-essential military occupational specialty, activity limitation would be more difficult to achieve. And lastly, certain heat injuries are believed to be underreported because heat cramps and heat exhaustion injuries are often treated by medics on the field. Therefore, many of these injuries are not captured within the Army medical database system. Thus, actual identification of soldiers vulnerable to RM due to a prior heat injury may be difficult to discern.

Our study exhibited several strengths. By using administrative data in the TAIHOD, we were able to describe Army RM from an epidemiologic approach and yield population-based estimates for our entire population of interest, the ADA. The majority of prior RM studies represent case series and case studies that are more clinically oriented and relied on small sample sizes. To our knowledge, no other study in the literature has systematically examined the epidemiology of RM in the US Army. This study significantly contributes to the literature by revealing trends in population-based rates of RM for the entire ADA during a 3-yr period, stratified by soldier subpopulations to investigate hypothesized risk factors. Moreover, the TAIHOD enabled us to capture all clinical encounters (e.g., inpatient and ambulatory) to allow for an unbiased representation of the spectrum of ADA RM clinical diagnoses. Soldier medical care is a closed single-payer system and is provided free of charge to the soldier; thus, lack of event capture is highly unlikely.

Although the use of the TAIHOD affords us an informed perspective on the epidemiology of RM in the ADA and provides a significant contribution to our understanding of the epidemiology of RM, our study is not without limitations. As noted before, clinical encounter data may not accurately identify RM in some cases. Further, because of coding practices in the military and the availability of data, our study is restricted to 2004–2006 and cannot include information about exposures before the soldier’s entry (such as heat injury before entering the Army). Lastly, our study evaluated the ADA only, and because so few research reports exist on the epidemiology of RM, it is difficult to directly compare our results with other published literature pertaining to civilian populations.

For more than a decade, the US Army has been engaging in combat operations in austere environments, with soldiers often exerting significant physical efforts with often limited opportunity for rest and recovery. Given these facts and that RM has the potential of significant morbidity and death, enhanced RM prevention efforts should be considered. Future research needs to include analytic studies (to identify the adjusted independent contributions of known and suspected risk factors) and evaluation of a soldier’s SCT status to allow us to more accurately quantify the contribution of SCT to the risk of RM. Lastly, Army occupational specialties should be evaluated to determine which are associated with higher RM rates. This will help discern if combat occupational exposures are resulting in the higher rates of RM seen in male ADA soldiers.

In conclusion, during our study period (2004–2006), the absolute numbers of clinically diagnosed ADA RM cases ranged between 382–419 per year, maintaining a relatively stable rate of 7–8 cases per 10,000 throughout the 3 yr. The observed SMR of RM in the ADA indicates that RM occurs at rates 300%–400% higher than the US civilian population. Approximately 8% of cases are severe, resulting in ARF, and this estimate is lower than for the civilian population. Rates are significantly higher in soldiers with a prior heat injury (7- to 11-fold increased risk) and are elevated in soldiers who are male, younger, African American, less educated, and with a shorter LOS.

This study was internally funded through the Military Operational Medicine Research Program.

This research was supported in part by an appointment to the Postgraduate Research Participation Program at the US Army Research Institute of Environmental Medicine administered by the Oak Ridge Institute for Science and Education through an interagency agreement between the US Department of Energy and USAMRMC.

The opinions or assertions contained herein are the private views of the authors and are not to be construed as official or reflecting the views of the Army or the Department of Defense. Any citations of commercial organizations and trade names in this report do not constitute an official Department of the Army endorsement of approval of the products or services of these organizations.

All authors have no conflicts of interest to disclose.

The results of the present study do not constitute endorsement by the American College of Sports Medicine.


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