Identify Risk Factors For Injury Research Articles

Data Driven Identification of Injury Risk Factors During Expansion on Irish Dairy Farms.

This paper sought to determine risk factors of occupational injury in the Irish dairy farming sector and to estimate the roles of both dairying expansion and the discipline of agricultural extension in influencing reducing injury occurrence. Data for this study was obtained via the Irish National Farm Survey (NFS). In total, 260 farm (83.6% of NFS dairy farm sample) workplace injury survey questionnaires were completed by NFS recorders by interviewing principal farm operators for year 2017. Injury survey data was analysed for 48 variables in conjunction with NFS core farm socio-economic, physical and financial data. Additionally, core data from 2010 for 78.5% of farms surveyed in 2017 was included in the study. Data were analysed using a three-step statistical testing process which met all Binary Logistic Regression assumptions. The study found that dairy farms had a higher farm workplace occupational injury level compared to a previous study. The study data indicates occurrence of elevated injury levels on farms which expanded and which were intensively managed from a milk production perspective. Farm expansion was associated with increased labor units used and increased investment per hectare. The study also found that use of extension services and farm discussion group participation were not associated with injury occurrence. This study demonstrates how a retrospective farm workplace occupational injury survey of Irish dairy farms, analysed in combination with farm business data can be used to identify injury risk factors, including those associated with production expansion. Irish dairy farms have a heightened farm workplace occupation injury level while dairy production expansion increased injury levels. Extension engagement did not influence on injury levels. Approaches to improve farm safety on dairy farms are outlined.

Epidemiology of adult injuries: A multi-center study in greater Beirut

IntroductionInjury accounts for nearly 4 million deaths and 63 million disabilities annually. The injury burden is disproportionally large in low- and middle-income countries (LMICs), including Lebanon. This study aims to examine the characteristics and patterns of adult injuries presenting at multiple emergency departments (ED) in Lebanon and further identifies factors associated with hospital admission. Materials and methodsA retrospective cross-sectional study was conducted on adult patients (aged≥16) who presented with an injury to one of the five participating EDs from June 2017 to May 2018. Pan-Asia Trauma Outcomes Study (PATOS) variables were adopted for data collection. A descriptive analysis was performed, followed by bivariate and multivariate logistic regression to identify injury risk factors for hospital admission. ResultsA total of 3,716 patients’ records were included. Most injuries were sustained by males (62.7%), patients aged between 16 and 35 years (16–25: 28%; 26–35: 22.7%), and above 65 years (15.6%). Most injuries were unintentional (94.9%). Falls were highly prevalent across all age groups (38.8%), more proclaimed among the older adults’ population (56–65:52.8%; ≥66:73.7%), followed by struck-by object (23.6%) and transport injuries (10.1%). Upper and lower extremity injuries were common across all ages. Most patients (80.9%) were treated and discharged at the ED, 11.4% were admitted to the hospital, 4.3% were transferred to other trauma care facilities, and 2 patients died in the ED. Factors positively associated with hospital admission included: older age (≥ 56 years); private insurance; spine and lower extremity injuries; fractures, cuts/open wounds, concussion, and organ injuries (p-value≤0.05; OR>1). ConclusionInjury is a neglected public health problem in many LMICs, including Lebanon. While youth and the elderly are most affected, injuries occur across all age groups. This study lays the foundation for establishing a population-based injury surveillance system, crucial for designing tailored injury prevention programs to reduce injury-related deaths and disabilities.

Cloud-based deep learning-assisted system for diagnosis of sports injuries

At both clinical and diagnostic levels, machine learning technologies could help facilitate medical decision-making. Prediction of sports injuries, for instance, is a key component of avoiding and minimizing injury in motion. Despite significant attempts to forecast sports injuries, the present method is limited by its inability to identify predictors. When designing measures for the avoidance of work-related accidents and the reduction of associated risks, the risk of injury to athletes is a crucial consideration. Various indicators are being evaluated to identify injury risk factors in a number of different methods. Consequently, this paper proposes a Deep Learning-assisted System (DLS) for diagnosing sports injuries using the Internet of Things (IoT) and the concept of cloud computing. The IoT sensors that compose the body area network collect crucial data for the diagnosis of sports injuries, while cloud computing makes available flexible computer system resources and computing power. This research examines the brain injury monitoring framework, uses an optimal neural network to forecast brain injury, and enhances the medical rehabilitation system for sports. Using the metrics accuracy, precision, recall, and F1-score, the performance of the proposed model is assessed and compared with current models.

Possibilities of using biomechanical human motion capture systems in medical rehabilitation (review)

Biomechanical motion capture is the most accurate non-contact instrumental method of studying human locomotion and is increasingly being used in the medical rehabilitation of patients with various diseases. Human motion capture systems are promising tools for clinical use to assess and control the correct execution of movements, as well as to identify injury risk factors.
 Currently, human motion capture systems are mainly used only in scientific research. The development and implementation of biomechanical motion capture systems in clinical practice can help doctors determine the best solution when planning medical rehabilitation and, thereby, reduce the recovery time of patients.
 This review aims to present up-to-date data on motion capture techniques and features of their application in the medical rehabilitation of patients with diseases of the nervous system. The review provides a brief overview of the existing technologies for the study of locomotor functions. The principles of operation, advantages and disadvantages of optoelectronic, electromagnetic, inertial and ultrasonic measuring systems are presented. The review describes in detail the possibilities of biomechanical motion capture in conducting a personalized diagnostic process, planning and evaluating the results of medical rehabilitation in patients with stroke, Parkinson's disease, cerebral palsy, spinal cord injury and multiple sclerosis.
 The search was conducted in the databases eLibrary, PubMed, Scopus, Web of Science and Google Academy (Google Scholar). The review includes studies in which motion capture systems were used and spatial-temporal, kinematic, kinetic and electromyographic parameters were analyzed.

Concurrent Validity of Movement Screening Criteria Designed to Identify Injury Risk Factors in Adolescent Female Volleyball Players.

Anterior cruciate ligament (ACL) injuries in female adolescent athletes occur at disproportionately high levels compared to their male counterparts. However, limited prospective data exist on the validity of low-cost screening tools that can proactively identify ACL injury risk, specifically for female athletes. The purpose of this study was to assess the concurrent validity of a three-task injury risk factor assessment by comparing visually derived outcome scores from two-dimensional (2D) video data with dichotomized three-dimensional (3D) biomechanical variables collected using motion capture technology. A total of 41 female club volleyball athletes (14.7 ± 1.4 years) were tested and asked to perform three tasks: double-leg vertical jump (DLVJ), single-leg squat (SLS), and single-leg drop landing (SLDL). One rater was trained on the scoring criteria for the 2D data and independently scored one forward-facing and one side-facing video for each task. Risk factors identified included poor knee position, lateral trunk lean, and excessive trunk flexion/extension. In addition, 3D joint angles were calculated for the trunk and knee in the sagittal and frontal planes and converted to dichotomous variables based on biomechanical thresholds of injury risk. For comparison of 2D and 3D outcomes, percent agreement and Cohen's kappa were calculated for each risk factor individually. Overall, 2D scores were found to exhibit moderate to excellent percent agreement with 3D outcomes for trunk position (69.1–97.1%). Specifically, ipsilateral trunk lean during single-leg tasks exhibited the highest agreement (85.3–88.2%) with moderate reliability (κ = 0.452–0.465). In addition, moderate to substantial reliability was found for trunk flexion during double-leg tasks (κ = 0.521–0.653); however, an evaluation of single-leg tasks resulted in only fair reliability (κ = 0.354). Furthermore, 2D scores were not successful in identifying poor knee position as percent agreement fell below 50% for both the single-leg tasks and averaged 60% agreement across both the phases of the DLVJ. Kappa coefficients further emphasized these trends indicating no to slight concurrent validity (κ = −0.047–0.167) across tasks. Overall, these findings emphasize the potential for valid, low-cost screening tools that can identify high-risk movement patterns. Further study is needed to develop improved assessment guidelines that may be employed through visual assessment in sports environments.

Development of a trail running injury screening instrument: A multiple methods approach

ObjectiveTo develop a trail running injury screening instrument (TRISI) for utilisation as clinical decision aid in determining if a trail runner is at an increased risk for injury. DesignMultiple methods approach. MethodsThe study utilised five phases 1) identification of injury risk factors 2) determining the relevance of each identified risk factor in a trail running context, 3) creating the content of the Likert scale points from 0 to 4, 4) rescaling the Likert scale points to determine numerical values for the content of each Likert scale point, and 5) determining a weighted score for each injury risk factor that contributes to the overall combined composite score. ResultsOf the 77 identified injury risk factors, 26 were deemed relevant in trail running. The weighted score for each injury risk factor ranged from 2.21 to 5.53 with the highest calculated score being 5.53. The final TRISI includes risk categories of training, running equipment, demographics, previous injury, behavioural, psychological, nutrition, chronic disease, physiological, and biomechanical factors. ConclusionThe developed TRISI aims to assist the clinician during pre-race injury screening or during a training season to identify meaningful areas to target in designing injury risk management strategies and/or continuous health education.

Injury risk factors and barriers to their mitigation for women playing rugby league: a Delphi study

ABSTRACT This study aimed to 1) develop a consensus (≥70% agreement between experts) on injury risk factors specific to women playing rugby league, 2) establish the importance of the identified injury risk factors and the feasibility of mitigating these risk factors and 3) establish context specific barriers to injury risk management. Aim 1: A Delphi panel, consisting of 12 experts in rugby league and injury (e.g., physiotherapists, research scientists) were asked to identify injury risk factors specific to women playing rugby league. Aim 2: seven coaches of women’s rugby league teams were asked to rate each risk factor that achieved consensus by their importance and feasibility to manage. Aim 3: Coaches reported barriers which restrict injury risk factor mitigation. Of the 53 injury risk factors which achieved consensus, the five injury risk factors with the highest combination of importance and feasibility ratings were: “poor tackle technique”, “a lack of pre-season intensity”, “training session are too short”, “the current medical standards”, and “limited access to physiotherapists”. Following the identification of injury risk factors, their feasibility to manage and context specific barriers, this study proposes three constraint driven, integrated solutions which may reduce the barriers which limit injury risk factor management.

Game Exposure, Player Characteristics, and Neuromuscular Performance Influence Injury Risk in Professional and Youth Field Hockey Players.

Background:Identifying factors that contribute to the occurrence of injury is an important step in designing training programs to minimize the risk of injury. However, despite high injury rates, variables contributing to injury in field hockey players remain relatively unexplored.Purpose:To identify factors that may predict injury in professional and youth field hockey players.Study Design:Cohort study; Level of evidence, 2.Method:Professional and youth hockey players completed preseason neuromuscular performance testing and were monitored for injuries, training, and game exposure throughout the subsequent 12-month indoor and outdoor hockey season. Least absolute shrinkage and selection operator analysis was conducted to identify injury risk factors. Receiver operating characteristic curves were then calculated to determine the individual predictive accuracy of the identified variables.Results:A total of 83 players (mean ± SD age, 20.7 ± 4.9 years; 34.9% female) with complete performance, injury, and exposure data were included for data analysis. Almost half of players (44.6%) sustained a time-loss injury during the season, and 73% of these injuries occurred in the lower limb. Playing more games and having an older age, asymmetrical and poor dynamic postural control, and better explosive performance were identified as jointly influencing the risk of injury. When considered individually, number of games played throughout the season was the most accurate predictor of injury risk (area under the curve [AUC] = 0.74; P < .001), while asymmetrical and poor dynamic postural control (AUCs = 0.61-0.65; P = .01-.04) and better explosive athletic performance (AUCs = 0.65-0.67; P < .01) were identified as moderate individual predictors of sustaining a general or lower limb injury.Conclusion:A number of modifiable factors were individually and jointly associated with an increased injury risk in field hockey players, providing initial evidence for the design of targeted and sport-specific training programs to mitigate the risk of injury.

Differences in cervical kinesthesia between amateur athletes with and without a history of contact sport participation

ABSTRACT Objective: Identify cervical sensorimotor function differences between amateur athletes with and without a history of contact sport participation. A secondary aim of the study was to explore the association between neck reposition error and previously identified injury risk factors. Design: Cross-sectional. Participants: 27 amateur campus recreation sport athletes with a history of contact sport participation and 20 amateur campus recreation sport athletes with no history of contact sport. Main Outcome Measures: Baseline signs and symptoms (S/S) number and severity, Neck Disability Index, total neck reposition error, maximum reposition error, cervical range of motion, and cervical isometric strength were then compared between independent factor groups (contact vs. non-contact). Results: Amateur sport athletes with a history of contact sport exposure exhibited 25.2% more total neck reposition error and 24.6% more maximum neck reposition error than athletes with no history of contact sport participation. S/S number (r2 = .12, F(2,44) = 6.2, p = .017) and S/S severity (r2 = .14, F(2,44) = 5.6, p = .02) were significantly correlated with total neck reposition error. Conclusions: Athletes with a history of contact sport participation exhibited greater cervical spine reposition error. The degree to which these sensory position-sense deficits increase risk of injury and long-term quality of life is unknown, but should be explored in future studies.

Training, Injury, and Lifestyle Characteristics of Recreational Triathletes.

Triathlon is a popular sport among recreational and competitive athletes. As triathletes compete in races ranging from 16 to 140.6 miles and train in three disciplines simultaneously, it is difficult to identify injury risk factors. The aim of this study was to evaluate characteristics of a group of recreational triathletes regarding their medical history, training regimen, and injuries. Thirty-four triathletes completed this survey. We found a wide range of body types, training habits, and lifestyle characteristics. As in previous studies, we found a high rate of injuries in our surveyed triathletes. Injury rates were higher in athletes who had completed a longer race and those who reported higher training times per week. Additionally, many individuals have medical problems, use a variety of supplements, and follow specific dietary restrictions, which need to be considered in addition to training when assessing injury risk and recovery from injury.

Injury Risk Factors Associated With Weight Training.

Grier, T, Brooks, RD, Solomon, Z, and Jones, BH. Injury risk factors associated with weight training. J Strength Cond Res 36(2): e24-e30, 2022-The purpose of this evaluation was to identify injury risk factors associated with weight training (WT). Subjects were 4,785 men and 542 women in a U.S. Army Division. Personal characteristics, unit training, personal training, fitness, and 12-month injury history were obtained by an electronic survey. Risk factors for WT injuries were explored using backward stepping multivariable logistic regression. Risk ratios, odds ratios (ORs), and 95% confidence intervals (95% CIs) were calculated for each risk factor. Over a one-year period, 4.5% of men and 0.6% of women experienced a WT injury. Weight-training injury incidence was 0.31 and 0.05 per 1,000 hours of WT for men and women, respectively. Overall, men were 7.4 times more likely to experience a WT injury compared with women. For men who participated in WT, independent risk factors for a WT injury included older age (OR [23-27/≤ 22 years] = 1.99, 95% CI 1.22-3.27; OR [>28/≤ 22 years] = 2.48, 95% CI 1.52-4.03) and higher amounts of personal WT per week (OR [60-165/≥ 166 minutes] = 0.58, 95% CI 0.39-0.88; and OR [15-59/≥ 166 minutes] = 0.40, 95% CI 0.24-0.66). A linear trend was revealed indicating an increasing risk of a WT injury with greater amounts of time spent WT per week (p < 0.01). Performing moderate amounts of WT may reduce the risk of experiencing a WT injury. However, because muscle strength is an important component of fitness for Soldiers, specialized WT programs that improve strength while minimizing injury risks are needed.

Using machine learning to improve our understanding of injury risk and prediction in elite male youth football players

ObjectivesThe purpose of this study was to examine whether the use of machine learning improved the ability of a neuromuscular screen to identify injury risk factors in elite male youth football players. DesignProspective cohort study. Methods355 elite youth football players aged 10–18 years old completed a prospective pre-season neuromuscular screen that included anthropometric measures of size, as well as single leg countermovement jump (SLCMJ), single leg hop for distance (SLHD), 75% hop distance and stick (75%Hop), Y-balance anterior reach and tuck jump assessment. Injury incidence was monitored over one competitive season. Risk profiling was assessed using traditional regression analyses and compared to supervised machine learning algorithms constructed using decision trees. ResultsUsing continuous data, multivariate logistic analysis identified SLCMJ asymmetry as the sole significant predictor of injury (OR 0.94, 0.92–0.97, p<0.001), with a specificity of 97.7% and sensitivity of 15.2% giving an AUC of 0.661. The best performing decision tree model provided a specificity of 74.2% and sensitivity of 55.6% with an AUC of 0.663. All variables contributed to the final machine model, with asymmetry in the SLCMJ, 75%Hop and Y-balance, plus tuck jump knee valgus and anthropometrics being the most frequent contributors. ConclusionsAlthough both statistical methods reported similar accuracy, logistic regression provided very low sensitivity and only identified a single neuromuscular injury risk factor. The machine learning model provided much improved sensitivity to predict injury and identified interactions of asymmetry, knee valgus angle and body size as contributing factors to an injurious profile in youth football players.

Risk factors for injury among military working dogs deployed to Iraq

There is limited literature concerning the types of injuries that military working dogs (MWDs) face while in a deployed theater of operations and associated risk factors. To summarize injuries and identify injury risk factors in MWDs during their first deployments to Iraq, demographic and medical data were collected for 794 MWDs from the U.S. Army, Air Force, Navy, and Marine Corps that deployed to Iraq between March 20, 2003 and December 31, 2007. Sixty-two percent (n = 490) had a medical encounter during deployment. Injuries were categorized as traumatic or musculoskeletal. MWD demographics, characteristics, and injury types were summarized. Injury risk factors were assessed using multivariable logistic regression.A majority of the population were German Shepherds (56 %), intact males (49 %), and dogs certified in both patrol and explosives detection (73 %). During their first deployment to Iraq, 20 % (n = 156) experienced an injury. Risk factors included breed, age, and occupational certification. Belgian Malinois and Labrador Retriever dogs had greater odds of injury compared to German Shepherds (p = 0.04 and p = 0.02) and the oldest MWDs had about a 50 % higher risk of injury compared to the youngest (p = 0.01), especially for musculoskeletal injuries. MWDs with Specialized Search certification were at increased injury risk (p = 0.02). Training, equipment, and supplies for veterinary service personnel, MWD handlers, and MWDs should be tailored with consideration of the injury risks of the MWD population. Further study is needed to investigate chronic injuries in military working dogs to better understand causation and prevention.

Modeling the Risk of Team Sport Injuries: A Narrative Review of Different Statistical Approaches.

Injuries are a common occurrence in team sports and can have significant financial, physical and psychological consequences for athletes and their sporting organizations. As such, an abundance of research has attempted to identify factors associated with the risk of injury, which is important when developing injury prevention and risk mitigation strategies. There are a number of methods that can be used to identify injury risk factors. However, difficulty in understanding the nuances between different statistical approaches can lead to incorrect inferences and decisions being made from data. Accordingly, this narrative review aims to (1) outline commonly implemented methods for determining injury risk, (2) highlight the differences between association and prediction as it relates to injury and (3) describe advances in statistical modeling and the current evidence relating to predicting injuries in sport. Based on the points that are discussed throughout this narrative review, both researchers and practitioners alike need to carefully consider the different types of variables that are examined in relation to injury risk and how the analyses pertaining to these different variables are interpreted. There are a number of other important considerations when modeling the risk of injury, such as the method of data transformation, model validation and performance assessment. With these technical considerations in mind, researchers and practitioners should consider shifting their perspective of injury etiology from one of reductionism to one of complexity. Concurrently, research implementing reductionist approaches should be used to inform and implement complex approaches to identifying injury risk. However, the ability to capture large injury numbers is a current limitation of sports injury research and there has been a call to make data available to researchers, so that analyses and results can be replicated and verified. Collaborative efforts such as this will help prevent incorrect inferences being made from spurious data and will assist in developing interventions that are underpinned by sound scientific rationale. Such efforts will be a step in the right direction of improving the ability to identify injury risk, which in turn will help improve risk mitigation and ultimately the prevention of injuries.

Injury Profile and Risk Factors in a Young High Competitive Population of Judo Athletes

High competitive level judo practice from a very young age, may lead to an increasing risk of injury. The aim of this study is to identify injury risk factors in a young high-level judo population to develop future specific strategies for injury prevention. An individual questionnaire was applied by physicians to cadet and junior athletes that competed in international judo tournaments in 2014. Statistical inferential analysis was performed to identify the major injury risk factors and injury patterns in these ages.

Technique selection in young female gymnasts: Elbow and wrist joint loading during the cartwheel and round-off

Biophysical loading of the elbow and wrist is a potential reason for chronic lesions in gymnastics and present a real concern for coaches, scientist and clinicians. Previous research has identified injury risk factors during round-off (RO) skills in elite female gymnasts. The aim of this study was to investigate key elbow and wrist joint injury risk factors during different techniques of fundamental cartwheel (CW) and RO skills performed by young female artistic gymnasts. Seventeen active young female gymnasts performed 30 successful trials of both CW and RO from a hurdle step with three different hand positions (parallel (10), T-shape (10) and reverse (10)). Synchronised kinematic (240 Hz) and kinetic (1200 Hz) data were collected for each trial. One-way repeated measures ANOVA and effect size (ES) were used for statistical analysis. The results showed statistically significant differences (P < .05) and large ES (>0.8) among hand positions for peak vertical ground reaction force (VGRF), peak elbow compression force, peak wrist compression force, elbow internal adduction moment and wrist dorsiflexion angle. In conclusion, the parallel and reverse techniques increase peak VGRF, elbow and wrist compression forces, and elbow internal adduction moment. These differences indicate that the parallel and reverse techniques may increase the potential of elbow and wrist injuries in young gymnasts compared with the T-shape technique; this is of particular importance with the high frequency of the performance of these fundamental skills.

Functional Movement Screen™ and history of injury in the assessment of potential risk of injury among team handball players.

Handball is known to be one of the team sports representing the highest risk of injury. Several investigators have tried to identify injury risk factors in team sports including handball and suggested the need to develop an optimal tool to capture and quantify the potential risk of injury. The aim of the study was to evaluate potential risk of injury among handball players. This was a mixed-design study. Handball players from 1st and 2nd division were evaluated (N.=30) using the Functional Movement Screen™ (FMS™). Additionally, self-reported history of injury was collected during FMS™ evaluation and after 6 months. Competitive level, training experience, playing position, anthropometric features, symmetry of movement patterns and history of previous injury were analyzed while assessing the potential risk of injury. Significant difference between the right and left side (upper limb) was revealed for Shoulder Mobility Test (U=308.5, P=0.014). Odds Ratio analysis revealed that having previous injury in the last 12 months is the only statistically significant injury risk factor (OR=13.71, P=0.02). Based on this study we can assume that previous injury history reports are crucial in predicting injuries. FMS™ can help in identifying a typical adaptation in throwing shoulder among handball players, but should not be used alone to assess injury risk.

Body Mass Index as a Predictor of Injuries in Athletics.

The quest to identify injury risk factors in sports has been an ongoing and well-researched field in the world of sports medicine. Knowing some of these factors helps keep sports participation safe. Both intrinsic and extrinsic factors have been studied. Body mass index (BMI) is widely known to contribute to several medical conditions. Its association with some sports injuries has been established but the information is vast, with few studies that are randomized controlled trials. It is important to analyze these studies and confirm whether BMI is a predictor of lower-extremity injuries. Such knowledge allows for better effective treatment and prevention strategies. This article will summarize current evidence of association between BMI and lower-extremity injuries in athletes and whether BMI is a predictor of lower-extremity injuries.

Mechanisms, prediction, and prevention of ACL injuries: Cut risk with three sharpened and validated tools

Economic and societal pressures influence modern medical practice to develop and implement prevention strategies. Anterior cruciate ligament (ACL) injury devastates the knee joint leading to short term disability and long term sequelae. Due to the high risk of long term osteoarthritis in all treatment populations following ACL injury, prevention is the only effective intervention for this life-altering disruption in knee health. The "Sequence of Prevention" Model provides a framework to monitor progress towards the ultimate goal of preventing ACL injuries. Utilizing this model, our multidisciplinary collaborative research team has spent the last decade working to delineate injury mechanisms, identify injury risk factors, predict which athletes are at-risk for injury, and develop ACL injury prevention programs. Within this model of injury prevention, modifiable factors (biomechanical and neuromuscular) related to injury mechanisms likely provide the best opportunity for intervention strategies aimed to decrease the risk of ACL injury, particularly in female athletes. Knowledge advancements have led to the development of potential solutions that allow athletes to compete with lowered risk of ACL injury. Design and integration of personalized clinical assessment tools and targeted prevention strategies for athletes at high risk for ACL injury may transform current prevention practices and ultimately significantly reduce ACL injury incidence. This 2016 OREF Clinical Research Award focuses on the authors' work and contributions to the field. The author's acknowledge the many research groups who have contributed to the current state of knowledge in the fields of ACL injury mechanisms, injury risk screening and injury prevention strategies. © 2016 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 34:1843-1855, 2016.

Injuries in a Professional Ballet Dance Company: A 10-year Retrospective Study.

Ballet dancers are high-performance athletes who are particularly susceptible to a wide variety of musculoskeletal injuries. However, they are relatively understudied, and data on their injury rates are lacking. This retrospective study features the largest aggregate data on professional ballet dancers to date and aims to identify the most common diagnoses and areas of injury in this unique population to better direct preventative and clinical practices. The study encompassed a 10-year period from January 2000 to December 2010 of dancers from a single company. Data regarding the dancers' age, gender, location of injury, and diagnosis were collected from workers' compensation claims, company records, and medical records maintained by the treating doctors. These were analyzed to determine metrics on injury incidence, frequency, and diagnosis. Over the 10-year span, 574 injuries occurred. There were approximately 52 dancers per year for a total of 153 who danced at least one complete season during the study period. The average age was 27, and 53% were female. Given turnover with retirement and replacements, the total number of dancer-years was 520, indicating an injury incidence per annum of 1.10 (574 injuries per 520 dancer-years). The most common locations of injury were foot and ankle and the lumbar spine, with the three most common diagnoses making up greater than a third (37%) of the total. As the current largest study in professional ballet, the findings set the benchmark metrics for musculoskeletal injury to the foot, ankle, and lumbar spine sites. Future studies should aim to identify injury risk factors and modalities for prevention of these injuries.