Rates of Ankle and Foot Injuries in Active-Duty U.S. Army Soldiers,

MILITARY MEDICINE, 176, 3:283, 2011 Rates of Ankle and Foot Injuries in Active-Duty U.S. Army Soldiers, 2000 2006 Robert F. Wallace, ScD, MPH * ; Monika M. Wahi, MPH, CPH * ; MAJ Owen T. Hill, SP USA * ; Ashley B. Kay, MSPH ABSTRACT Ankle and foot injuries (AFI) are a major cause of Active-Duty Army (ADA) soldiers time lost from training and combat operations. We used the Total Army Injury and Health Outcomes Database to compute the rates of AFI to identify high-risk ADA groups for the years 2000 2006. During this time, 16% of soldiers were clinically seen at least once for an AFI. Yearly, 60% to 70% of ADA soldiers with AFI had an ankle sprain/strain, and ankle sprain/strain had the highest 7-year rate of all AFIs (103 per 1,000). From 2000 to 2006, all AFI rates declined; however, enlisted male soldiers 30 years of age without an advanced degree were at highest risk. A history of an AFI in the previous 2 years increased AFI rates by 93% to 160%. Our findings provide preliminary evidence for identifying specific ADA groups at high risk of AFI; these groups should be targeted for preventive interventions. *Injury Epidemiology Section, Military Performance Division, U.S. Army Research Institute of Environmental Medicine, 42 Kansas Street, Natick, MA 01760-5007. Social Sectors Development Strategies, 1411 Washington Street, Suite 6, Boston, MA 02118. The opinions or assertions contained herein are the private views of the author(s) 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. INTRODUCTION Ankle and foot injuries (AFIs) are reported to be prominent in U.S. Active-Duty Army (ADA) soldiers. In most cases, AFIs are attributed to challenging exercise training programs and other physical activities of military training and operations. AFIs make up one of the largest proportions of lower leg injuries.1 4 However, a search of peer-reviewed literature failed to identify any studies that reported the descriptive epidemiology of AFI in ADA personnel. In addition, minimal attention has been devoted to quantifying the impact AFIs have on the mission capability of the ADA, with the exception of the parachute ankle-brace studies 5,6 and a small number of studies that examined recruit training and orthopedic injuries. 4,5,7 10 Hauret and coworkers recently looked at injury-related musculoskeletal ICD-9-CM codes that included the ankle and foot for all Active-Duty U.S. military. They reported that musculoskeletal injuries overall have been underestimated since overuse injuries caused by microtraumas have not been included in estimates of musculoskeletal injuries. Also, most of the previous studies on AFIs relied on small sample sizes that lacked the power of larger epidemiologic studies. Large studies are now possible by leveraging research database repositories currently available on ADA soldiers, such as the Total Army Injury and Health Outcomes Database (TAIHOD). The TAIHOD contains administrative data on all ADA soldiers and is utilized to facilitate epidemiologic analyses. As a result, this repository allows for researchers to investigate risk factors for AFI within subpopulations of the ADA, maintain statistical power due to large samples, and make population-based estimates. The course of an ADA soldier s career can be affected by an AFI, especially when the injury prevents a soldier from performing activities within his or her military occupational specialty or participating in physical fitness training. By way of these limitations, an AFI, especially if experienced soon after entering the service, could ultimately hamper a soldier s career advancement. Moreover, if an AFI (e.g., ankle sprain) develops into a chronic condition (e.g., chronic ankle laxity), the possibility of a medical discharge becomes more likely and could end a soldier s military career. 11,12 Finally, soldiers may be unable to perform their duties because of AFI, and this can negatively impact mission accomplishment. Thus, taking preventive measures against AFI is conducive to both the overall health of the military and the fiscal efficiency of the military as prevention is cost-effective in alleviating larger costs associated with medical treatment and discharge. It is sensible, then, to identify high-risk soldiers and to develop new or improved screening techniques for preventing AFI. Even with the common knowledge that injuries, such as stress fractures, dislocations, sprains, and strains, occur quite often during military training, there is little information about risk factors for these injuries. The small number of risk factors that have been recognized to influence AFI and other musculoskeletal injuries in the military include age group, previous injury, early return to activities, gender, and physical activity 13 16 ( Table II ). To examine how these risk factors were associated with AFI, we developed crude and stratified rates of AFI in the ADA. Our objective was to quantify acute AFI rates over time in the ADA and to identify and evaluate high-risk categories of AFI by applying stratified methods. Using the TAIHOD, we calculated unadjusted rates of AFI and stratum-specific AFI rates for categories of soldiers hypothesized to be at higher risk for AFI (categories listed in Table II ). The goal of this MILITARY MEDICINE, Vol. 176, March 2011 283

analysis was to improve the understanding of current trends in AFI rates in the U.S. Army. Long-term goals of this study are two-fold (1) to offer recommendations for how to improve Army prevention programs designed to lower AFI rates and (2) to identify high-risk soldier groups to target for prevention programs. MATERIAL AND METHODS Study Data This study was completed using existing data obtained from the TAIHOD. 17 The Defense Manpower Data Center compiles monthly master personnel files containing soldier-level demographic and occupational data; these data were used to identify soldiers who were in ADA in each year from 2000 to 2006. The Patient Administration Systems and Biostatistic Activity agency provided clinical encounter data for the ADA for 2000 2006; these datasets include all inpatient and outpatient clinical encounters in both military and civilian health care facilities. Each dataset contains at least 4 diagnostic codes in the ICD-9 format associated with each encounter. AFI and Risk Factor Classification Classifications of AFI were made using guidance from the Barell Injury Diagnosis Matrix. 18 These classifications include fracture, stress fracture, dislocation, sprains/strains, contusion/ superficial, and crush (Table I ). For ankle injuries, all Barell Matrix codes from the lower leg and ankle category were used except 823: Fracture of the tibia and fibula. For foot injuries, all Barell Matrix codes from the foot and toes category were used. Code 733.94: Stress fracture of the metatarsals was included for foot injuries as stress fractures have a high prevalence among the military. Potential risk factors were classified according to Table II. Analytic Methods First, 7-year rates (years 2000 2006) per 1,000 ADA soldiers were calculated for each AFI outcome. The denominator consisted of the number of soldiers who were on Active Duty at any time during each year. It was found that all ADA soldiers have a minimum of at least 1 clinical encounter per year for routine preventive care (by policy); therefore, using the number of all ADA soldiers at risk for AFI as the denominator was determined to be appropriate. For each outcome of interest, the numerator consisted of the number of ADA soldiers in the denominator who met the following criteria: over 2000 2006, the soldier had at least 1 clinical encounter with at least 1 of the ICD-9-codes of inclusion for the outcome of interest in at least 1 of the first 4 diagnostic positions. Also, a single ADA soldier may be present in multiple numerators if multiple records exist for that soldier. Next, yearly rates were calculated for years 2000 2006. For each year, the denominator consisted of the number of soldiers who had been on Active Duty at any given time during the year. Numerators for yearly rates were calculated similarly to those calculated for the 7-year rate discussed earlier, but only used the current year window. Again, this allows a single ADA soldier to be present in multiple numerators. To examine the presence of trends in AFI over time, the twosided Cochran Armitage χ 2 test for trend was used. p Values <0.05 were considered statistically significant. Lastly, yearly rates of any AFI were stratified by the following independent variables: sex, age, military rank classification, educational attainment, marital status, length of Active-Duty service, the existence of at least 1 AFI encounter in the previous 2 years, racial group, Hispanic ethnicity, and accession Armed Forces Qualification Test (AFQT) classification. For the following variables, the soldier s status in the earliest month in the year they were active was used: military rank classification, educational attainment, marital status, and length of Active-Duty service. 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 similarly as had been done in the nonstratified rates. All analyses were conducted in SAS version 9.1 19 and Microsoft Excel version 2007. 20 Investigators have adhered to TABLE II. Independent Variables Sex Age Rank Education Marital Status Length of Service AFI in Previous 2 years Race Hispanic Ethnicity Armed Forces Qualification Test (AFQT) Independent Variables Stratified for Risk Factor Determination Classification Categories Male, Female <20 years, 20 30 years, >30 years E1 E4, E5 E6, E7 E9, Officers (Including Warrant Officers) <High School, High School Diploma, College, Advanced Degree Single, Married, Divorced <1 year, 1 to <2 years, 2 to <3 years, 3 to <4 years, 4 to <5 years, 5 to <10 years, 10 years Yes, No White, Black, Asian, Native American, Other Yes, No I, II, III, IV (I = Highest Category, IV = Lowest Category) TABLE I. ICD-9 Codes Used to Classify AFI Barell Anatomy Classification Fracture Stress Fracture Dislocation Sprains/Strains Contusion/Superficial Crush Ankle 824 NA 837 845.0 924.10, 924.21 928.10, 928.21 Foot and Toes 825-826 733.94 838 845.1 917, 924.3, 924.20 928.3, 928.20 284 MILITARY MEDICINE, Vol. 176, March 2011

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 45 CFR 46. RESULTS Overall Results During the period 2000 2006, 1,447,285 soldiers were on Active-Duty status for at least 1 month in the U.S. Army, and 221,393 soldiers (15%) were seen in a clinical setting for at least 1 AFI during this time: 157,096 soldiers (71%) for ankle injuries and 92,581 soldiers (42%) for foot injuries. A breakdown of the 7-year rates for each type of injury is provided in Figure 1. Rates of injury by anatomy and type decreased significantly over the study period (Cochran Armitage χ 2 test for trend, p < 0.0001) for all outcomes except ankle contusion ( p = 0.0035), and foot stress fracture (p < 0.001), where there was a significant increase in rate of injury ( Figs. 2a and 2b ). Yearly rates of ankle injury were driven by ankle sprains and strains (AS), and rates of foot injury reflected rates of foot contusion. Observed rates of ankle injury were 1 to 5 times higher than rates of foot injury. Results for Hypothesized Risk Factors For stratified AFI rates, the outcome used was any AFI, since most AFI types decreased similarly over time. In addition, Cochran Armitage χ 2 tests for trend were not reported for stratum-specific trends. The observed trend in any AFI was so strong that stratum-specific trends were not meaningfully different. Sex Over the study period, annual male AFI rate ranged from 54 to 80 per 1,000 soldiers, whereas annual female AFI rates ranged from 74 to 107 per 1,000 soldiers ( Table III ). In each year, rates of AFI were at least 35% higher in females, and these rates were observed to peak in 2003, where female AFI rates were 50% higher. Age Rates of AFI ranged from 43 to 61 per 1,000 soldiers for ADA soldiers >30 years of age and from 61 to 108 per 1,000 soldiers for ADA soldiers 30 years of age ( Table III ). Rates in the younger group ( 30 years) exceeded those in the older group (>30 years) by a maximum of 56% in 2002, whereas the minimum difference between these two age groups occurred in 2006. Military Rank Classifi cation Rates of AFI among enlisted pay grade soldiers (E0 [unknown], E1 E4, E5 E6, and E7 E9) were similar across years ( Table III ), and as a result, pay grades were collapsed and were comparable to all officers. Enlisted rates exceeded officer rates each year, peaking at 136% in 2003. AFI rates of enlisted soldiers were at their lowest in 2005, with 54 per 1,000 soldiers, and at their highest in 2002, with 99 per 1,000 soldiers. AFI rates of officers ranged from 28 per 1,000 soldiers in 2004 to 39 per 1,000 soldiers in 2000, 2002, and 2005. Educational Attainment For all years, AFI rates were highest for ADA soldiers with less than a high school education, which ranged from 63 to 104 per 1,000 soldiers, and lowest for ADA soldiers with advanced degrees, which ranged from 30 to 42 per 1,000 soldiers ( Table III ). AFI rates in soldiers with less than a high school education exceeded rates in soldiers with advanced degrees by 84% to 159% for all years. AFI rates for high school graduates and those who had attended college were similar. Marital Status Single ADA had the highest rates of AFI in each year, ranging from 63 to 95 per 1,000 soldiers ( Table III ), but rates were not remarkably higher than those for the married group, which FIGURE 1. Seven-year (2000 2006) rates per 1,000 soldiers of ankle and foot injuries in the Active-Duty U.S. Army. MILITARY MEDICINE, Vol. 176, March 2011 285

FIGURE 2. Rates of ankle injury (A) and foot injury (B) per 1,000 soldiers in the ADA for the years 2000 2006, by injury type. ranged from 49 to 73 per 1,000 soldiers. All rates declined similarly over the study period. Length of Active-Duty Service A longer length of Active-Duty service was associated with lower rates of AFI across time ( Table III ). Those with less than 1 year of service had higher AFI rates each year, ranging from 92 per 1,000 soldiers in 2006 to 120 per 1,000 soldiers in 2002. Those with 10 or more years of service had the lowest AFI rates per year, ranging from 34 per 1,000 soldiers in 2004 to 53 per 1,000 soldiers in 2002. All AFI rates declined similarly over the study period. Injury in the Previous 2 Years Having an AFI in the preceding 2 years was strongly associated with an AFI in the current year. Rates of AFI in ADA soldiers with a prior AFI ranged from 124 per 1,000 soldiers in 2003 and 2006 to 147 per 1,000 soldiers in 2002, whereas rates in ADA soldiers without a prior AFI ranged from 51 per 1,000 soldiers in 2005 and 2006 to 76 per 1,000 soldiers in 2002 ( Fig. 3 ). The rate of AFI in ADA soldiers with a prior injury exceeded the rate of AFI in ADA soldiers without a prior injury by at least 93% each year. Race AFI rates were similar across races, which were between 53 and 98 per 1,000 soldiers over the study period ( Table III ). All rates declined similarly during the study period. Hispanic Ethnicity No differences were observed in rates of AFI in ADA soldiers who were Hispanic vs. non-hispanic over the study period; rates ranged from 57 to 87 per 1,000 soldiers ( Table III ). All rates declined similarly during the study period. Accession AFQT Score AFQT scores were not available for officers; therefore, AFQT category rates only apply to enlisted soldiers. Among enlisted soldiers, rates of AFI for AFQT categories I to III remained similar over the study period ( Table III ). When collapsed, soldiers in AFQT categories I to III had AFI rates ranging from 58 to 89 per 1,000. Meanwhile, AFI rates for soldiers in 286 MILITARY MEDICINE, Vol. 176, March 2011

TABLE III. Rates of AFI per 1,000 Soldiers by Soldier Demographic and Occupational Characteristics for the years 2000 2006. Year Risk Factor 2000 2001 2002 2003 2004 2005 2006 Crude 75 76 84 72 58 57 57 Sex Male 70 72 80 67 55 54 54 Female 97 100 107 100 79 75 74 Age Category (in years) <20 93 94 108 96 86 80 78 20 30 81 84 93 78 67 62 61 >30 56 56 61 53 46 43 45 Military Rank E1 E4 77 84 90 82 65 66 67 E5 E6 78 80 88 75 57 55 56 E7 E9 90 86 99 80 70 66 36 E0* 70 68 76 62 53 54 54 Officer 39 37 39 32 28 39 36 Education <High School 100 95 104 82 68 63 66 High School 74 78 86 73 58 57 55 College 62 73 84 68 60 58 58 Advanced Degree 39 39 42 34 30 34 32 Marital Status Single 84 86 95 82 67 65 63 Married 65 66 73 62 49 50 51 Divorced/Separated/ Widow 71 71 79 68 61 60 60 Length of Service (in years) <1 103 104 120 109 99 96 92 1 to <2 85 90 94 74 73 74 64 2 to <3 77 78 85 70 67 63 65 3 to <4 75 73 78 66 52 53 57 4 to <5 70 76 81 65 35 36 35 5 to <10 66 49 74 63 48 47 47 10 50 67 53 45 34 36 37 Race White 77 78 87 75 60 59 59 Black 70 72 78 67 57 55 54 Asian 77 78 88 77 57 60 57 Native American 98 93 92 73 54 53 49 Hispanic Ethnicity Yes 77 80 87 74 61 61 61 No 74 76 84 71 61 58 57 AFQT Score I 75 72 85 73 58 74 73 II 80 80 89 71 58 71 71 III 79 80 86 68 58 67 67 IV 61 62 60 55 46 56 66 category IV were remarkably lower, ranging from 46 to 66 per 1,000. Each year, the AFI rate for soldiers in AFQT categories I to III exceeded the rate for soldiers in AFQT category IV by 4% to 44%. Associations Between Risk Categories We found overlap among AFI rates for high-risk categories in ADA soldiers ( Table III ). For example, most soldiers with an advanced degree are also officers, older, and married/divorced. Given this finding, we demonstrated how a high proportion of soldiers fall simultaneously into multiple risk groups. Figure 4 shows the distribution by gender for certain high-risk categories (those shown in Table III ). Prior injury categories ( Fig. 3 ) were not included as new recruits do not have prior injury data available. Last row of Figure 4 shows that 53% of the ADA soldiers in our study was male, <30 years of age, enlisted, and without an advanced degree. DISCUSSION In this study, we observed the AFI rates of ADA soldiers to decrease significantly over the study period (2000 2006) for any ankle injury and foot injury, decreasing from 56 to 39 per 1,000 soldiers and from 23 to 21 per 1,000, respectively. Overall, annual rates of AFI gradually increased to a peak in 2002, and then decreased significantly in 2005 and 2006. Throughout the study period, ankle injuries were 1 to 5 times more prevalent than foot injuries, with the highest rates observed for AS in each year. When we examined AFI rates by soldier characteristics, soldiers > 30 years of age were found to have AFI rates 42% to 56% higher than soldiers 30 years of age. AFI rates of enlisted soldiers exceeded those of officers by as much as 136%, and soldiers with less than a high school degree had rates 84% to 159% higher than soldiers with an advanced degree. Female soldiers were found to have rates at least 35% higher than male soldiers; however, we identified an important large male subpopulation with a high AFI rate. This subpopulation consisted of enlisted male soldiers who were 30 years of age without an advanced educational degree. The strongest risk factor for AFI, identified in this study, was a record of an AFI within the previous 2 years. This finding is particularly alarming, as data on previous injuries in new recruits was not available, suggesting that these high rates may be underestimated. Earlier injuries most likely account for an AFI occurring before or during basic combat training (BCT ). Recruits diagnosed with an initial AFI during BCT may not have adequate recovery time before returning to training. Recruits may also not have followed the prescribed treatment regimen. These events can increase risk for subsequent AFI later in a soldier s military career. Knapik et al previously identified injuries during BCT and implemented programs such as the Physical Readiness Training (PRT) and the Fitness Assessment Program. 21,22 These programs have had some success in reducing similar injuries during BCT where the overall adjusted rate of injury was found to be 1.5 to 1.8 times lower in groups of soldiers using PRT when compared with groups performing traditional military physical training. 11,21,23 Our study observation of overall decreasing AFI rates may be in part due to the result of the new PRT program, which was the first program implemented on a number of training platoons by the U.S. Army Center for Health Promotion and Preventive Medicine during 2002 BCT. 21,22 Knapik et al 24 reported that implementing PRT programs consistently resulted in fewer injuries and improved fitness. A second possible cause for decreasing AFI rates may be the initiation of a 2003 MILITARY MEDICINE, Vol. 176, March 2011 287

FIGURE 3. Rates of AFI per 1,000 soldiers in ADA for the years 2000 2006, stratified by prior injury (previous 2 years). FIGURE 4. Distribution of selected characteristics associated with high AFI risk in the ADA for the years 2000 2006. partnership between the U.S. Army and the U.S. Department of Labor Occupational Safety and Health Administration. 25 One of the stated goals of this partnership is to reduce total case rates and severity rates related to musculoskeletal disorders. Our current analysis indicated that female soldiers have higher AFI rates. However, given that 84% of Active-Duty personnel are male, the greater number of AFI are represented in male soldiers. The higher rates of AFI are represented in male soldiers, consequently the impact to combat 288 MILITARY MEDICINE, Vol. 176, March 2011

mission accomplishment is significant. As shown in Table III, females with a prior AFI have consistently higher rates of current AFI than males with a similar history. Mechanisms for a sex-specific difference have been proposed. 5,26 28 The high rate of AFI in soldiers with a prior injury may result from premature return to duty, where the soldier has not adequately recovered from the initial injury. ASs are a significant lower extremity morbidity for ADA soldiers, as the sequelae of an ankle injury can often persist for extended time periods (e.g., years), adversely affecting many aspects of a soldier s career. Depending upon severity, AFI prevents soldiers from performing many tasks, including physical fitness training, occupational proficiency training, and combat training. Physical therapy rehabilitation is a frequent mainstay of AFI recovery, and access to such care is often limited due to a restricted environment (e.g., during deployment, while in training, etc.). If an AS is insufficiently rehabilitated, the risk of subsequent reinjury could possibly increase (as seen in Fig. 3 ). Cadets at West Point were shown to have 40% impairment for as long as 6 months when they returned to activities before their AS was entirely healed. 7 Additional ankle injuries increase the probability of developing chronic ankle laxity, which inhibits a soldier from performing his/her daily routine tasks, often resulting in frequent sprains and strains that otherwise would not occur. 7 The highest rates of AFI observed in this study were those for AS. These injuries may require more attention and better evaluation. The Army may benefit from introducing more physical therapy clinicians at the unit level and increasing the duration of activity limitation after injury (e.g., before returning to unlimited activity status). Given the relatively high rates of AFI seen in soldiers with a prior injury, coupled with the potential for long-term negative consequences, Army leadership should exercise caution when tasking soldiers for physical activities conducive to AFI. The results of this study can be somewhat be compared to annual rates previously reported from the Defense Medical Epidemiology Database (DMED) system of the Armed Forces Health Surveillance Center. 29 Since the DMED system is intended for surveillance, DMED rates are reported as yearly rates of inpatient and ambulatory clinical encounters, which are appropriate for visually identifying trends. However, DMED data only allow for the calculation of a limited number of stratified rates and do not provide statistical comparisons, which are necessary when assessing the impact of AFI on the U.S. ADA. Also, although Hauret s injury-related musculoskeletal matrix captures AFI microtraumas, their relative contribution to the number of overall AFI is quite low 29 and would not affect our population-based results and injury trends. However, we will incorporate microtrauma codes into all future study-related analyses. Our study provides a foundation for future cohort or case control studies, in which multivariate statistical approaches can be used to account for the significant overlap among risk factors found in this study. Results from future analytic studies investigating AFI will directly impact the implementation of Army preventive strategies and programs. In conclusion, yearly rates of AFI appear to be declining in ADA soldiers, with relatively high rates observed among enlisted males 30 years of age without advanced degrees, a group that comprises over half of the ADA soldiers. This cohort represents a high-risk soldier group, which would serve as an appropriate target for interventions. Given recent elevated and prolonged military deployment, preventing injuries in this population is of paramount importance. First-year soldiers could additionally benefit from interventions that prevent them from joining a high-risk AFI group, i.e., those with prior injuries. Moreover, secondary preventative measures implemented after an initial soldier AFI would help to ensure proper rehabilitation, thus reducing AFI rates in those with a prior injury. Finally, cohort and case control studies are necessary to identify the independent contributions of various risk factors for AFI in the ADA. From these study results, interventions can be designed and implemented to mitigate AFI in the U.S. Army. ACKNOWLEDGMENTS This project was internally funded by the U.S. Army Research Institute of Environmental Medicine. REFERENCES 1. 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