Hamstring Muscle Injuries and Hamstring Specific Training in Elite Athletics (Track and Field) Athletes

describe hamstring muscle injury (HMI) history and hamstring speci c training (HST) in elite athletes. A secondary aim was to analyse the potential factors associated with in-championships HMI. Methods: We conducted a prospective cohort study to collect data before and during the 2018 European Athletics Championships. Injury and illness complaints during the month before the championship, HMI history during the entire career and the 2017–18 season, HST (strengthening, stretching, core stability, sprinting), and in-championship HMI were recorded. We calculated proportions of athletes with HMI history, we compared HST according to sex and disciplines with Chi2 tests or ANOVA, and analysed factors associated with in-championship HMI using simple model logistic regression. Results: Among the 357 included athletes, 48% reported at least one HMI during their career and 24% during the 2017–18 season. Of this latter group, 30.6% reported reduced or no participation in athletics' training or competition at the start of the championship due to the hamstring injury. For HST, higher volumes of hamstring stretching and sprinting were reported for disciplines requiring higher running velocities (i.e., sprints, hurdles, jumps, combined events and middle distances). Five in-championship HMIs were recorded. The simple model analysis showed a lower risk of sustaining an in-championships HMI for athletes who performed more core (lumbo-pelvic) stability training (OR =

due to the hamstring injury. For HST, higher volumes of hamstring stretching and sprinting were reported for disciplines requiring higher running velocities (i.e., sprints, hurdles, jumps, combined events and middle distances). Five in-championship HMIs were recorded. The simple model analysis showed a lower risk of sustaining an in-championships HMI for athletes who performed more core (lumbo-pelvic) stability training (OR = 0.49 (95% CI: 0.25 to 0.89),p= 0.021). Conclusions: Our present study reports that HMI is a characteristic of the athletics athletes' career, especially in disciplines involving sprinting. In these disciplines, athletes were performing higher volumes of hamstring stretching and sprinting than in other disciplines. Further studies should Int. J. Environ. Res. Public Health2022,19, 10992.

Int. J. Environ. Res. Public Health2022,19, 10992 2 of 14 be conducted to better understand if and how HST are protective approaches for HMI in order to improve HMI risk reduction strategies. Keywords:track and eld; injury surveillance; epidemiology; risk factors; hamstring; prevention 1. Introduction In athletics (track and eld), hamstring muscle injury (HMI) represents an important challenge for athletes, health professionals, coaches and other stakeholders. HMI is one of the most prevalent injuries, especially in disciplines requiring high running velocities, with about 20% of athletes sustaining an HMI per season [1–4]. HMIs account for 17% of all injuries during international athletics championships, ranging from 0 to 35% according to sex and athletics discipline [5,6]. HMI also represents a major burden on sport practice due to time loss from sport and injury recurrence [3–10]. However, some of these studies' results were limited by: relative small sample sizes (from 30 to 64 athletes) [1–3], not considering an entire athletics season and only international athletics championships (3 to 9 days in the season) [5,6], or no information on training exposure [5–10]. This justi es further studies to assess HMI epidemiology and potential risk factors, especially in elite athletes. Increased knowledge on athletics-speci c HMI risk factors may help to improve HMI risk reduction strategies [11]. In the context of international athletics championships, male sex, older age, and disciplines requiring faster velocity have been reported to be associated with higher HMI risk [5,6]. In other athletics contexts, male sex and older age [12] were also associated with HMI, in addition to previous hamstring injury [8], lower exibility [13] and weak or imbalanced knee exors or hip extensors strength [1–3]. In contrast with other sports such as football [14,15], knowledge on factors associated with HMI risk in athletics are thus limited [1–3,6,8,12,13], especially in the context of elite athletes during international athletics championships [5,6]. In addition, recommendations for HMI risk reduction strategies speci cally for ath- letics do not currently exist. Since the physical, mechanical, technical and psychological demands are different in athletics compared to football and other sports, it may be inappro- priate to

risk in athletics are thus limited [1–3,6,8,12,13], especially in the context of elite athletes during international athletics championships [5,6]. In addition, recommendations for HMI risk reduction strategies speci cally for ath- letics do not currently exist. Since the physical, mechanical, technical and psychological demands are different in athletics compared to football and other sports, it may be inappro- priate to extrapolate results from other sports to athletics, especially elite athletes. Given the previously reported HMI risk factors in athletics [1–3,6,13], we can hypothesise that hamstring muscle strengthening and stretching, and preparation/training to fast veloci- ties, may belong to HMI risk reduction strategies speci cally for athletics. Lumbo-pelvic (core) conditioning has been advocated for HMI prevention, rehabilitation and athletics performance [16], and could also be a relevant additional strategy. As a rst step in the development of such recommendations, improvement in the sport-speci c knowledge on current practice towards HMI risk reduction strategies during usual training (i.e., hamstring speci c training) in elite athletics athletes is of importance. Therefore, we aimed to describe HMI history and hamstring speci c training in elite athletes. A secondary aim was to analyse the potential factors associated with HMI occurrence during international athletics championships. 2. Methods 2.1. Study Design and Overall Procedure We conducted a prospective cohort study to collect data before and during the 24th European Athletics Championships in Berlin in 2018 (EOC2018, 7–12 August 2018; //www.europeanchampionships.com/2018-berlin-glasgow on injury and illness complaints during the month before the Championships, HMI history during the entire career, hamstring speci c training, and in-championship injury and illness including in-championship HMI. There was no patient and public involvement. The study protocol was reviewed and approved by the Saint-Etienne University Hospital Ethics

Int. J. Environ. Res. Public Health2022,19, 10992 3 of 14 Committee (Institutional Review Board: IORG0007394; IRBN742020/CHUSTE) and all included athletes provided their informed consent. 2.2. Population One month before the championships, European Athletics (EA,https://www.european- athletics.com tions to participate in the study. European Athletics sent an email including information about the study, an information letter for athletes and a pre-participation health question- naire (PPHQ) that should be lled in by athletes. The same information was sent to national medical teams by the EA Medical and anti-doping commission. EA and EA medical and anti-doping commission, respectively, asked national federations and national medical teams whether they accepted to participate in this study and to forward the email to their athletes selected and registered for the EOC2018. Eligible athletes were athletes registered for the EOC2018. Athletes were included in the present study if they were registered for the EOC2018, member of a national federation who accepted to participate in this study, and if they completed the PPHQ. 2.3. Data Collection Before the start of the championships, athletes registered for the EOC2018 were asked by EA through their national federation and/or national medical team to ll in a PPHQ. The PPHQ was developed by three sports medicine physicians with extensive experience in athletics medicine (PE, PB and FD). It was available in paper and electronic format in English. Athletes were asked to complete the questionnaire themselves and to return it to designated desks at their hotel or the warm-up area, or to their medical team who gave it to the main investigator (PE). The PPHQ included two parts similar to that from previous published studies: [17,18] (1) athletes' characteristics: country, sex, date of birth, discipline, height, weight and mean training time per week during the four preceding weeks; (2) pre-participation health problems (analysed on a binary basis: yes/no) during the four weeks preceding the championship; and a third part (3) on history of HMI and hamstring speci c training (Supplementary File S1). The last part included three questions about history of HMI: HMI during athlete's career (yes/no), HMI during the current 2017–18 season—from October 2017

four preceding weeks; (2) pre-participation health problems (analysed on a binary basis: yes/no) during the four weeks preceding the championship; and a third part (3) on history of HMI and hamstring speci c training (Supplementary File S1). The last part included three questions about history of HMI: HMI during athlete's career (yes/no), HMI during the current 2017–18 season—from October 2017 to August 2018 (yes/no), and, if so, if the respective athlete had any dif culties to participate in normal training and competition due to hamstring pain (yes/no); and then four questions about athletes' current practice towards HMI risk reduction strategies during their usual training (i.e., hamstring speci c training). These current training practice questions included four main domains of modi able intrinsic HMI risk factors reported in athletics [1–3,6,13] and other sports: [15,19] hamstring strengthening, hamstring stretching, core stability (lumbo-pelvic) conditioning and/or sprint running at maximal intensity/velocity. There were no more details for athletes than the four terms presented above. For each of these four questions, athletes selected one of the ve possible responses according to the frequency of that type of exercise: no (0), less than one time a month (1), more than one time a month but less than one time a week (2), more than one time a week but less than three time a week (3), more than three time a week (4) (Supplementary File S1). For the descriptive analysis and comparison according to sex and discipline we used this categorical variable (i.e., 0, 1, 2, 3 and 4) to create a hamstring speci c training (HST) score by summing up the results of the four questions. During the period of the championships, newly incurred injuries and illnesses were recorded by national medical teams (physicians and/or physiotherapists) and/or by physi- cians on the local organizing committee (LOC), using the same de nitions and procedures than during previous international athletics championships [17,18,20]. In-championship HMI was de ned as an injury reported by LOC or national medical teams located at the “posterior thigh” and with “strain/muscle rupture/tear” or “muscle cramps or spasm” as a type, based on clinical

physiotherapists) and/or by physi- cians on the local organizing committee (LOC), using the same de nitions and procedures than during previous international athletics championships [17,18,20]. In-championship HMI was de ned as an injury reported by LOC or national medical teams located at the “posterior thigh” and with “strain/muscle rupture/tear” or “muscle cramps or spasm” as a type, based on clinical examination and/or medical imaging by the national medical teams and/or by LOC physicians, such as in previous studies [5,6].

Int. J. Environ. Res. Public Health2022,19, 10992 4 of 14 2.4. Con dentiality The athletes' sex, date of birth and nationality were used to match data from the PPHQ and the in-championship registration of injury. Information about the purpose of the study and the procedure was provided to the athletes in writing and at information desks at the athlete hotels. All athletes were free to refuse the inclusion of their in-championship injury and illness data in the interpretation. All PPHQ and injury and illness reports were stored in a locked filing cabinet and were made anonymous after the championships. The confidentiality of all information was ensured so that no individual athlete or national team could be identi ed. 2.5. Data Analysis We performed a descriptive analysis of the included population, using number and percentages for categorical variables and mean with standard deviations ( SD) for contin- uous variables, calculated the number of responders for each variable, based on the data from the PPHQ and the in-championships injury and illness data collection. Analysis of the non-responders was performed by comparing the distribution of sex, age and discipline between the eligible population and the included athletes using Chi2 tests. Given the differences in injury rates and characteristics between sex and discipline [20], all analyses were performed by using “sex x discipline” categories. There were thus 18 different categories for the two sexes and the nine disciplines. No separated analysis was performed only between sexes or only between disciplines. We then analysed the potential differences according to sex discipline (i) in the distribution of number of athletes with history of HMI during their career and during the 2017–18 season using Chi2 tests, and (ii) for hamstring speci c training using Chi2 tests for hamstring strengthening, hamstring stretching, core stability conditioning and/or sprinting (i.e., categorical variables) and using an ANOVA for the HST score. The signi cance level was initially set atp< 0.05. Statistical analyses were performed using JASP (JASP Team software, Version 0.14.1, University of Amsterdam, Amsterdam, The Netherlands, https://jasp-stats.org/download/ To analyse the potential factors associated with HMI occurrence during the champi- onships,

hamstring strengthening, hamstring stretching, core stability conditioning and/or sprinting (i.e., categorical variables) and using an ANOVA for the HST score. The signi cance level was initially set atp< 0.05. Statistical analyses were performed using JASP (JASP Team software, Version 0.14.1, University of Amsterdam, Amsterdam, The Netherlands, https://jasp-stats.org/download/ To analyse the potential factors associated with HMI occurrence during the champi- onships, we performed binomial logistic regression with in-championships HMI (yes/no) as the dependent variable and sex x discipline, age, country, history of HMI during the career (yes/no), history of HMI during the 2017–18 season (yes/no), injury complaint (yes/no), ill- ness complaint (yes/no), strengthening, stretching, core stability, sprinting, HST score(0–16) as independent variables. Risk indicators were presented as Odds ratios (OR) and 95% confidence intervals (95% CI) for univariate and multivariable models. In a multivariable model, we examined the adjusted OR when including all variables as independent variables and in-championship HMI as a dependent variable. The significance level was initially set atp< 0.05. Statistical analyses were conducted using R (version 4.0.2,©Copyright 2020 The Foundation for Statistical Computing,Vienna, Austria (Comprehensive R Archive Network, http://www.R-project.org 3. Results 3.1. Population Among the 51 national federations registered at the EOC2018, 24 (47.1%) agreed to participate in the study, including a total of 794 eligible athletes (50.6% of the 1570 athletes registered at the EOC2018). Among them, 357 (45.0%) athletes (22.7% of eligible athletes) agreed to participate, returned their questionnaires, and were included in the present study. Analysis of the non-responders did not show signi cant differences between eligible and included athletes for the distribution of discipline but did so for sex (higher proportion of female athletes in the included athletes (53.8%) compared to the eligible population (45.3%), p= 0.005) and age (slightly higher proportion of athletes under 20 and older than 35 among included athletes (7.0% vs. 4.0%),p= 0.01). None of the included athletes refused to allow their data to be used for scienti c research. The characteristics of the 357 included athletes are reported in Table.

under 20 and older than 35 among included athletes (7.0% vs. 4.0%),p= 0.01). None of the included athletes refused to allow their data to be used for scienti c research. The characteristics of the 357 included athletes are reported in Table.

Int. J. Environ. Res. Public Health2022,19, 10992 5 of 14 Table 1. Characteristics of the 357 included athletes who participated at the 24th European Athletics Championships in Berlin in 2018 and who were included in the present study, as well as their history of hamstring muscle injuries (HMI), preparticipation health problems and in-championships injuries, illnesses and hamstring muscle injuries. Data are presented using mean with standard deviations ( SD) for continuous variables and using number and frequency with percentages for categorical variables. Total Sprints Hurdles Jumps Throws Combined Events Middle Distances Long Distances Marathon Race Walking F M F M F M F M F M F M F M F M F M Athletes' characteristics N (%) 357 (100.0) 57 (16.0) 46 (12.9) 15 (4.2) 16 (4.5) 32 (9.0) 18 (5.0) 23 (6.4) 23 (6.4) 8 (2.2) 5 (1.4) 14 (3.9) 14 (3.9) 12 (3.4) 14 (3.9) 15 (4.2) 12 (3.4) 16 (4.5) 17 (4.8) Age (years) (mean (SD)) 26.6 (4.9) 24.8 (3.9) 25.0 (3.6) 24.1 (4.7) 24.6 (2.9) 25.1 (4.4) 26.5 (3.8) 28.3 (4.6) 28.0 (5.6) 22.2 (4.0) 25.2 (2.6) 25.7 (2.9) 25.2 (3.2) 28.7 (4.0) 26.6 (2.6) 34.6 (5.0) 32.7 (4.4) 28.7 (4.7) 28.7 (7.0) Height (cm) (mean (SD)) 177.2 (9.2) 170.5 (5.7) 182.5 (6.1) 173.0 (5.9) 186.6 (5.8) 176.7 (6.8) 187.3 (5.3) 177.2 (6.9) 189.4 (6.8) 172.9 (5.1) 185.2 (5.7) 169.3 (3.7) 181.5 (4.8) 169.0 (7.3) 178.9 (7.8) 165.8 (4.1) 179.0 (4.8) 165.8 (8.3) 179.6 (5.7) Weight (kg) (mean (SD)) 68.2 (16.7) 59.2 (5.2) 75.8 (6.2) 61.3 (5.9) 78.0 (6.7) 61.5 (6.0) 76.9 (5.7) 83.9 (14.8) 110.1 (19.2) 61.4 (3.5) 82.6 (4.4) 53.3 (3.0) 65.5 (3.6) 50.4 (5.5) 63.7 (7.6) 50.5 (4.7) 62.1 (5.4) 50.6 (5.1) 66.3 (5.2) BMI (kg.cm 2 ) (mean (SD)) 21.5 (3.8) 20.4 (1.5) 22.7 (1.4) 20.5 (1.3) 22.4 (1.3) 19.7 (1.2) 21.9 (1.3) 26.6 (3.6) 30.7 (5.5) 20.6 (1.6) 24.1 (0.8) 18.6 (1.2) 19.9 (0.8) 17.6 (0.9) 19.8 (1.2) 18.4 (1.2) 19.4 (1.4) 18.4 (0.8) 20.6 (1.4) Mean training time per week (h) (mean (SD)) 13.4 (5.1) 11.3 (3.2) 10.7 (3.6) 10.6 (4.9) 11.8 (4.0) 11.2 (4.0) 10.5 (4.8) 16.9 (4.2)

Study on hamstring injuries and training in elite track and field athletes.