Intrinsic modifiable risk factors for

lower extremity injuries in female

soccer players: a prospective study during one season.

Vansant Elise

Wauters Evi

Supervisors: Prof. Dr. Roosen Philip, Dr. De Ridder Roel, Dr. Verrelst Ruth

A dissertation submitted to Ghent University in partial fulfilment of the requirements for the degree of

Master of Rehabilitation Sciences and Physiotherapy

Academic year: 2016 – 2017

Intrinsic modifiable risk factors for

lower extremity injuries in female

soccer players: a prospective study during one season.

Vansant Elise

Wauters Evi

Supervisor(s): Prof. Dr. Roosen Philip, Dr. De Ridder Roel, Dr. Verrelst Ruth

A dissertation submitted to Ghent University in partial fulfilment of the requirements for the degree of

Master of Rehabilitation Sciences and Physiotherapy

Academic year: 2016 – 2017

Gratitude

We would like to say thank you to those who helped us in the process of writing this study. First of

all, thanks to the University of Ghent to give us the opportunity to make this study. Secondly, a

big thank you to our (co)promotors for their support during this work; De Ridder Roel, Verrelst

Ruth and Philip Roosen.

Also thanks to the Spartanova team and the Royal Belgian Football Academy (RBFA) for the

good cooperation. And surely many thanks to all the participants, and their parents, for their effort

during the screening and follow up, without them the study was not even possible. Also the use of

accommodation in Tubize (Belgium) was an asset to our study, so thanks again to the RBFA.

Further, we cannot forget our fellow students. Everybody did his share in this great work and

provided an ease for each other. We are also grateful to the biostatistics unit of the University of

Ghent for their support with our statistical analyses.

Last but not least, we would like to thank our friends and family for their support during the

process.

INDEX

ABSTRACT (English version) ......................................................................................................................... 8 ABSTRACT (Dutch version) ............................................................................................................................ 9 Introduction .................................................................................................................................................... 10 Method ........................................................................................................................................................... 14 Study and participants ................................................................................................................ 14

Experimental procedure .............................................................................................................. 15

Injury registration ........................................................................................................................ 20

Statistics ..................................................................................................................................... 21 Results ........................................................................................................................................................... 21 Player and injury characteristics ................................................................................................. 21

Risk factors lower extremity ........................................................................................................ 24 Discussion ..................................................................................................................................................... 28 Demographic variables and injury risk: ....................................................................................... 28

Functional factors and injury risk ................................................................................................. 29

Methodological considerations .................................................................................................... 30

Conclusion .................................................................................................................................. 32

References ................................................................................................................................. 33

Addendum .................................................................................................................................. 42

LIST OF TABLES AND FIGURES

Figure 1: Flowchart participants

Figure 2: Lateral step down

Figure 3: Y-Balance Test Lower Quarter

Figure 4: Y-Balance Test Upper Quarter

Figure 5: Tuck Jump Test

Figure 6: Illinois Agility Test

Figure 7: Age distribution of the injured and non-injured group

Figure 8: BMI distribution of the injured and non-injured group

Figure 9: Total sport distribution of the injured and non-injured group

Table 1: Demographic data for non-injured and injured group

Table 2: Descriptives of the tests

Table 3: Single logistic regression

Table 4: Multiple logistic regression

LIST OF ABBREVIATIONS

ACL= Anterior Cruciate Ligament

App= Application

ASIS= Anterior Superior Iliac Spine

BMI= Body Mass Index

CI= Confidence Interval

D= Dominant

I= injured

IAT= Illinois Agility Test

LSD= Lateral Step Down

LQ= Lower Quarter

ND= Non-Dominant

NI= Non-Injured

RBFA = Royal Belgian Football Academy

ROM= Range Of Motion

THD= Triple Hop for Distance

TJ= Tuck Jump

UEFA= Union of European Football Associations

UQ= Upper Quarter

YBT= Y-Balance Test

8

ABSTRACT (English version)

Background: High injury incidences are seen in female soccer players. However little is known

about the risk factors and the use of functional tests as a screening tool.

Objectives: To investigate intrinsic modifiable risk factors for lower extremity injuries in female

soccer players.

Study design: Prospective cohort study; level of evidence 3.

Methods: Players of the RBFA (Royal Belgian Football Academy) (n=7 teams) were invited for a

preseason screening before the 2016-2017 competitive season. This screening started with a

baseline questionnaire for demographic information followed by some functional test like the YBT

(Y-balance test), TJ (tuck jump), THD (triple hop for distance), LSD (lateral step down) and the

IAT (Illinois agility test). After the screening, injury registration was performed on a weekly basis

using a mobile app (application) up until March 2017. Data about injury circumstances were

collected by contacting the injured players. Single and multiple logistic regression analyses were

used to calculate the odds and 95% confidence intervals for injuries.

Results: A total of 101 players were included for analysis, of which 49 players sustained a non-

contact injury. No significant difference was seen in age, BMI (body mass index) and total hours

of sport between the injured and non-injured group. The single logistic regression showed that

“asymmetric foot placement” as a subscore of TJ (P-value= 0,014; 95%CI= 1,222-5,929, Odds=

2,692) and “lumbopelvic control” as a subscore of LSD (P-value= 0,053; 95%CI= 0,990-5,377,

Odds= 2,307) are associated with non-contact lower extremity injuries.

Conclusion: Asymmetric landings after a jump and a poor lumbopelvic control were associated

with non-contact lower extremity injuries in female soccer players. The predictive value of these

risk factors needs to be confirmed in larger samples.

Key words: female; soccer; injury; risk factor; functional screening; lower extremity

9

ABSTRACT (Dutch version)

Achtergrond: Bij vrouwenvoetbal is er een hoge letsel incidentie. Er is echter weinig gekend

over de risicofactoren en het gebruik van functionele testen als screeningsinstrument.

Doelstellingen: Het onderzoeken van intrinsieke modificeerbare risicofactoren voor letsels aan

het onderste lidmaat bij vrouwelijke voetbalspeelsters.

Onderzoeksdesign: Prospectieve cohort study; level of evidence 3.

Methode: Zeven teams van de KBVB (Koninklijke Belgische VoetbalBond) zijn uitgenodigd voor

een screening voorafgaand het competitieseizoen van 2016-2017. Deze screening begon met

een basisvragenlijst over demografische gegevens gevolgd door enkele functionele testen zoals

de YBT (Y-balance test), TJ (tuck jump), THD (triple hop for distance), LSD (lateral step down) en

de IAT (Illinois agility test). Het registreren van letsels werd uitgevoerd op wekelijkse basis via

een mobiele app (applicatie) vanaf de screening tot en met maart 2017. Data over de

omstandigheden waarin het letsel is opgetreden werden verzameld door de gekwetste speelster

te contacteren. Enkelvoudige en meervoudige logistische regressie-analyses werden gebruikt om

de odds en het 95% betrouwbaarheidsinterval te berekenen.

Resultaten: In totaal zijn er 101 speelsters geïncludeerd voor de uiteindelijke analyse. Hiervan

liepen er 49 een non-contact letsel op. Er werd geen significant verschil gevonden voor leeftijd,

BMI (Body Mass Index) en aantal uren sport tussen de gekwetste en niet gekwetste groep. Met

de enkelvoudige logistische regressie kon gesteld worden dat het asymmetrisch landen tijdens

de tuck jump (P-waarde= 0,014; 95%BI= 1,222-5,929, Odds= 2,692) en lumbopelvische controle

als onderdeel van de LSD (P-value= 0,053; 95%CI= 0,990-5,377, Odds= 2,307) geassocieerd

zijn met non-contact letsels in de onderste ledematen.

Conclusie: Asymmetrisch landen na een sprong en slechte lumbopelvische controle zijn

geassocieerd met non-contact letsels in de onderste ledematen bij vrouwelijke voetbalspeelsters.

De voorspellende waarde van deze risicofactoren moet bevestigd worden in grotere

steekproeven.

Key words: vrouwen; voetbal; letsel; risicofactoren; functionele screening; onderste lidmaat

10

Introduction

Soccer is one of the most popular team sports worldwide and its popularity is still growing. Not

only in male but especially in female soccer, new players are attracted every year. UEFA (Union

of European Football Associations) reported that the number of registered female players has

multiplied with factor five since 1985, to a total amount of 1.199.584 in 2015-2016 [1]. Since there

is no doubt that sports participation is related to good health, this expansion can only be

encouraged. Adolescent athletes present a better mental, emotional and physical wellbeing.

Benefits to the cardiopulmonary, musculoskeletal and endocrine systems are some examples of

the physical profits. It is also described that impact sports, such as soccer, show significant

favorable effects in bone density and bone geometry in contrary to non-impact sports, such as

cycling and swimming [2-7]. Despite these benefits of playing sports, we must take into account

that soccer is associated with a great injury risk [8-12]. These injuries have a negative effect on

team performance and may cause a decreased participation level, change of sport and high

direct and indirect medical costs [13,14]. The individual athlete can even suffer long-term physical

consequences, such as interrupted soccer career and dramatic increase in the risk of early

developing knee osteoarthritis [15,16]. Besides physical stress, injuries can also lead to

psychological, social or emotional problems [17,18]. Therefore, to perpetuate the growth of

female soccer, the related injury risk should be addressed.

In order to control injury incidence, five major steps are required. First, the size of the injury

problem in this population needs to be uncovered. Then, the aetiology and mechanism of injuries

needs to be established. The following step includes the search for possible preventive measures

for the findings of the second step. When these measures are established, the interventions can

be implemented. Eventually the effectiveness of these interventions needs to be observed.

Compared to other sports, soccer has quite a high injury incidence [12]. The reported injury

incidence for female players during practice is approximately 1,17-3,8 injuries per 1000 playing

hours and 12,63-23,2 injuries per 1000h during games [8-11]. These varying numbers in injury

incidence can mainly be attributed to playing level, surface type, geography and injury definition.

The high incidence is not surprising as it is a high intensity contact sport characterized by quick

accelerations, decelerations, change of directions and high eccentric load. Those high loads on

11

the lower extremity makes a player susceptible for injury. The high incidence of injuries is a

growing concern and should be addressed. A clear understanding of underlying risk factors for

lower extremity injuries is crucial to tackle this incidence number.

Up until now there is a large hiatus in literature on risk factors for lower extremity injuries in

female soccer players. Most research discussing risk factors for musculoskeletal injuries is mainly

based on studies with male soccer players. These identified risk factors, however, cannot simply

be transferred to their female counterparts for several reasons. First, there is a difference in

incidence of injuries [8,19-24]. Male soccer players are at higher risk for injuries than female

players (match: 21,7-29,8 vs 12,5-22,5/1000 player hours and training: 3,0-4,7 vs 2,6-3,8/1000

player hours) [8,20-22,24]. Larruskain et al. found that the injury total incidence, in training and

match, was 30-40% higher in men, but the total number of absence days was 21% larger in

women [24]. Second, a difference is seen in type of injury. Hip and groin injuries are more

common in male players, whereas female players endure more knee injuries [8]. For example,

female athletes are eight to nine times more likely to sustain an ACL (anterior cruciate ligament)

injury [25]. Another reason prohibiting extrapolation is that risk factors for sustaining the same

injury can differ between sexes. As an increased talar tilt is reported by Beynnon et al. as a risk

factor for sustaining ankle sprains for men, an increased tibial varum and increased calcaneal

eversion were the described risk factors for women [19]. Above all, specific female related

factors, such as menstrual cycle and the use of oral contraceptives, may have an influence on

injury mechanisms [26-30]. Therefore, more research with female soccer players is necessary.

Prevention and intervention have become focal points for clinical research. This can only be

attained if the aetiology of the injuries is clearly understood. In many of these studies, two types

of risk factors are described, the extrinsic (outside the body) and intrinsic (within the body)

factors. The focus of further studies in the female soccer population should be on identifying

intrinsic modifiable risk factors for lower extremity injuries. Especially, to investigate risk factors

for the most frequently endured injuries in female soccer. Male soccer players are more

predisposed to hamstring strains and hip/groin injuries, and women to quadriceps strains, severe

knee and ankle ligament injuries. In both sexes, the overall most commonly injured region were

the hamstrings [8,24]. These intrinsic factors are, from a therapeutic/preventive point of view,

12

potentially modifiable through physical training or behavioral approaches, such as strength,

flexibility, functional performance, and psychological variables that have been associated with an

increased risk for sustaining lower extremity injuries.

In November 2015, we performed a systematic review on risk factors for lower extremity injuries

in female soccer players. We searched through Pubmed (http://www.ncbi.nlm.nih.gov/pubmed)

and Web Of Science (http://apps.webofknowledge.com) for articles that report possible risk

factors (I; intervention) for lower extremity injuries (O; outcome) in female adult soccer players (P;

population). A comparison (C) was not defined in order to obtain all available studies concerning

the possible risk factors.

The results of this review were classified in three categories. As external factors, protection

gear, playing position, competition level and load have an impact on injury occurrence

[23,26,27,31-34]. In addition, the impact of the playing surface (turf versus grass fields) showed

no major differences in incidence, severity, nature or cause of injuries in female soccer players

[19-22]. For intrinsic factors, two subdivisions were made. Previous injury, age, hormonal

condition, anatomical varieties and laxity were found as non-modifiable intrinsic factors [26-

31,33-37]. From a therapeutic point of view the most important findings are the modifiable

intrinsic factors, which are: (A) mental influences; trait anxiety, negative-life-event stress and

daily hassle were significant predictors of injury among professional soccer players [35], (B)

endurance; aerobic capacity has no influence on injuries, but more severe injuries were seen in

the later part of the game or practice, which could possibly be explained by a lack of

concentration or by muscular fatigue [34], (C) weight/BMI (body mass index); recent studies

found that a high BMI may augment the risk of sustaining a non-contact injury, however more

previous studies found no effect of body dimensions on injury risk [31,34,38], (D)

musculoskeletal; more ankle ligament injuries were seen when a higher tibial varum and

calcaneal eversion ROM (range of motion) were measured [19]. There was no consensus found

about the effect of isokinetic strength on soccer injury occurrence, but in 5/5 athletes with an ACL

(anterior cruciate ligament) tear a low concentric hamstring/quadriceps ratio was measured

[32,34]. Also, pre-activity of semitendinosus - vastus lateralis and gastrocnemius - tibialis anterior

has an impact on ACL and ankle ligament injuries respectively [34,39].

13

Prevention programs typically aim at improving strength, muscle length, postural control,

neuromuscular control, agility, stress response and performance. Nevertheless, at this moment

specific evidence is lacking in female football players as a starting point for injury prevention

protocols.

Current literature (November ‘16) described that knee valgus is a risk factor for knee injuries [40-

42]. Furthermore, Brooks et al. determined that concussed athletes were at higher risk (2,48x) of

sustaining an acute lower extremity musculoskeletal injury during the 90-day period after return to

play than controls [43]. Considering the scarce information, lack of consensus and limited

evidence, the necessity of further appropriate research is heightened.

It can be said that muscle strength imbalances are associated with higher injury risk [32,44].

Isokinetic strength testing is currently the most popular way to screen these imbalances,

nevertheless this approach is impractical and not cost effective. Above this, you can debate

whether these tests can be translated to the field. A more comparable way to reproduce the field

performance is the use of functional tests. Functional performance tests consist of dynamic

measures which evaluate general lower body function. These tests are helpful because they

combine multiple components, such as muscular strength, neuromuscular coordination, mobility

and stability. Besides, in comparison to the isokinetic tests, they are costs effective, can be

performed on the field, few materials are needed, it can be supervised by anyone and it is more

enjoyable for the athlete. Most preventive tools are based on functional movements [41,42].

Soccer is a multifactorial sport in which the maintaining of unilateral balance and control of the

lower extremity is essential for proper performance. There is also emerging evidence that a

deficiency in controlling dynamic balance and poor functional movements are linked to a higher

injury risk [40-42,45,46].

The purpose of this prospective study is to identify intrinsic modifiable risk factors for lower

extremity injuries in female soccer players. Because of the scarce information about functional

performances as risk factors for soccer injuries, the primary focus of this part of the study is to

investigate this specific topic for the most frequently endured injuries in female soccer players:

hamstring injury, ankle inversion sprain, groin pain, and quadriceps strain [8,24]. The postulated

14

hypothesis is that female soccer players scoring low on one, or a combination, of the screened

parameters (agility and functional analyses) are more susceptible to lower extremity injuries.

Method

Study and participants

The current study is part of a prospective cohort study aimed at investigating risk factors for lower

extremity injuries in female soccer players. Seven national Belgian teams were invited to

participate in this study during the season 2016-2017. Data were collected during a pre-season

screening, injury follow-up and a retrospective survey (figure 1). The Ethical Committee of the

Ghent University Hospital approved the study (see addendum) and all participants signed the

informed consent and, in case of adolescents, their parents as well.

15

Experimental procedure

In the generic study different topics were investigated. The screening was based on the

Spartanova screening tool for soccer players (www.spartanova.com). First, the athletes had to fill

in several questionnaires about administrative information, baseline sports and previous injuries.

Date of birth was obtained from administrative unit records, and age was calculated on the day of

the start of training. They were also asked for the date of their first menstruation. Secondly some

anthropometric parameters such as: body height, body weight, arm- and leg length were

measured. Leg length was defined with the athlete in standing position, heels in contact with the

wall and feet shoulder width apart. Tape measure was held between the ASIS (anterior superior

iliac spine) and the most prominent part of the medial malleolus. Arm length was defined in

standing position with both arms abducted in 90 degrees, elbows extended, hands open and

thumbs pointing to the ceiling. Tape measure was held between the spinous process of the

seventh cervical vertebra and the most distal point of the distal phalange of the third finger.

After these measures, the athletes were needed to warm-up by themselves. Then, several

screening tests were performed: (A) flexibility; hip internal and external rotation, maximal dorsal

flexion of the ankle, adductor, hamstring and quadriceps flexibility were measured (B) strength;

maximal isometric strength of the hamstring, quadriceps, hip extensors, hip abductors and

adductors and hip internal and external rotators were tested and a hamstring break test was

performed (C) endurance; yo-yo intermittent recovery test (D) functional performance; LSD

(Lateral Step Down), THD (Triple Hop for Distance), TJ (Tuck Jump), YBT (Y-Balance Test) and

IAT (Illinois Agility Test). Only field tests were implemented to increase general applicability.

College seniors in the physiotherapy and their supervisors, from the department of rehabilitation

sciences and physiotherapy at Ghent University, presented themselves as examiners. As

preparation they underwent a practicum session supervised by a Spartanova expert and used the

given manual.

In this specific part of the study five functional tests were implemented. A block randomization of

two was used to define whether to start testing on the right or left side.

16

The lateral step down is commonly used in the clinical

setting to assess quality of movement. The test has a

moderate to good reliability [47]. Our athletes performed the

test standing barefoot on a 30cm high box. If the athlete was

shorter than 1,70m a small step of 5cm was installed next to

the box, so the test was performed over a height of 25cm.

The contralateral foot was placed on the edge of the box, with

the foot pointing forward (Figure 2). The test consisted of a

slow unipodal squat, while looking forward, until the heel

touches the floor, no weight transfer was allowed. During the

test an upright position of the trunk had to be maintained,

arms were crossed over the shoulders, the iliac crests had to

be kept horizontal and the hip of the free leg needed to be

slightly flexed. Clear instructions were given. Two test trials

were allowed and after verbal feedback the actual test began,

consisting of five repetitions [48]. The 2D kinematics were

recorded with a camera, which was installed in line with the

testing leg, and allowed the testers to score the quality by observing the video. The scoring

criteria were set on balance, hip, knee and ankle movement, and was based on the main jump of

the five repetitions [score form 1].

To evaluate postural control, unilateral balance, range of motion and strength for the lower and

upper extremities the Y-balance test was implemented. The YBT is one of the most dynamic

balance tests used in sport science and is characterized by a good reliability [49-51]. The YBT kit

consists of a stance platform with three pipes attached with reach indicators. The pipes target in

the anterior, posteromedial and posterolateral direction for the lower quarter, or medial,

inferolateral and superolateral direction for the upper quarter. The posterior/lateral pipes are

positioned in 90° and in 135° from the anterior/medial pipe. Before testing the examiner

demonstrated the test with standardized instructions. To set up a consistent testing protocol, a

standard testing order was used. The procedure for the lower extremity was as follows: the

athlete was asked to stand barefoot on one leg on the stance platform with the most distal aspect

Fig. 2 Lateral Step Down

30 cm

17

of the foot behind the marked red line and the heel in line with the anterior pipe. While

maintaining a single leg stance, the athlete was asked to reach with the free limb, in the anterior,

posterolateral and posteromedial direction, pushing the reach indicator as far as possible [Figure

3]. First five trials for each leg were provided, then three attempts were registered. The testing

order was three trials standing on the right foot reaching in the anterior direction, followed by

three trials on the left foot. This procedure was repeated for the posteromedial and the

posterolateral reach directions. The maximal reach distance of each attempt was measured and

noted. An attempt was invalid if the athlete (A) failed to maintain unilateral stance (heel in contact

with the floor), (B) failed to maintain contact with the reach indicator while it was in motion (for

example kicking the target forward), (C) used the reach indicator for stance support (the reaching

foot was only allowed to touch the side of the reach indicator) or (D) failed to return the reach foot

to the starting position under control [50-56].

Fig. 3 Y-Balance Test Lower Quarter

For testing the upper quarter, the athlete

was asked to stand in a push-up position,

with feet shoulder width apart, the testing

hand on the stance platform and the

thumb adducted while being aligned

behind the red starting line and the

reach-hand on top of the reach indicator

in the medial direction. While maintaining

this position, the athlete was asked to Fig. 4 Y-Balance Test Upper Quarter

18

Fig. 5 Tuck Jump Test

reach with her free arm in the three directions, pushing the reach indicator as far as possible

[Figure 4]. Here two test trials were permitted because performing the test with the upper

extremities was harder compared to the performance with the lower extremities. Afterwards, three

attempts were registered. First three attempts with the right hand in each direction were

performed followed by three attempts with the left hand. An attempt was invalid if the athlete (A)

failed to maintain unilateral stance (touched down to the floor with the reach hand or fell), (B)

failed to maintain contact within the reach hand and indicator while it was in motion, (C) used the

reach indicator for stance support, (D) failed to return the reach hand to the starting position

under control, or (E) lifted either foot of the floor [49]. The maximum score of all three attempts

was used for analysis.

All trials were scored to the closest 0,5 cm increment. The maximum score was divided by the

subject’s homolateral leg- and arm length to normalize each reach distance [50,51,56,57].

The Tuck jump test is a plyometric test, to analyze the

jump and landing technique (58). For example, the TJ can

be used in a clinician-friendly setting to identify high-risk

landing mechanics and may provide direction for an

intervention of several injuries (e.g. ACL) (59). It has a

good to excellent intra-tester and inter-tester reliability and

is a way to detect abnormal landing mechanics and high

risk movements (60,61). The test took place on top of a

‘+’ shape tape on the floor and was performed with

running shoes. It consisted of ten jumps straight up, with a

quick rebound in between and pulling the knees as high as

possible. During the test the athlete had to look forward and

try to land on the same footprint. The test was performed

in a frontal and sagittal point of view [58-60]. A test trial was allowed before the actual test. The

quality of movement was scored using video-recording, with the same camera setting as

mentioned above. A camera was used since it is described in literature to give the best intra and

inter-tester reliability [60] [Score form 2].

19

The Triple Hop For Distance is described as a reliable measure of lower limb strength and

power. [62,63]. This test was also performed with running shoes. The athlete was asked to stand

in an unipodal position with the hands behind her back and her toes behind the line taped on the

floor. The test consisted of three one-legged hops, on the same limb, covering as much distance

as possible and with a stable landing at the end. When no stable landing was achieved a second

test had to be done. The total distance was measured from the starting line to the heel in

centimeters (no decimals). A standard procedure was used whereby one practice trial was

allowed to decrease the influence of learning effect, but avoiding the effect of fatigue. Afterwards,

three attempts were registered. The maximum score of all three attempts on each leg was used

for analysis.

The Illinois Agility Test is a valid and reliable measure to assess the athlete’s agility and the

ability to speed and change direction [64,65]. The test was set up using a standardized version

from previous literature [64]. An area was set up with four corner cones (length 10m) and 2,5m

distance from four centre cones (3,3m apart). The figure below shows the specific setting and the

running direction. Two time gates were placed at the start- and endpoint. Before starting the test,

the athlete was allowed to explore the course once, walking or jogging, after the examiner

demonstrated the test while giving clear instructions. The athlete began the test in prone position

on the floor behind the starting line with both arms on the back and her chin on the line. The

tester gave the start sign and moved her hand past the first time gate to make sure the start of

the test was registered. The athlete was encouraged to keep running as fast as she could to

insure she reached maximum speed during the test. Time stopped when the athlete passed the

second time gate and was recorded in seconds with two decimals. Disqualification was

ascertained when (A) cones were knocked over, (B) the participant failed to finish the test or (C)

did not run the course as instructed. Two trials were performed and the mean was used for

analysis. This test was also performed a third time after a Yo-Yo test was completed. In this trial,

fatigue was taken into account (Illinois fatigue test).

20

Injury registration

An accurate registration is very important in recording injuries, so a multilevel registration method

was used. A weekly based app registration was used as a primary method. The participants were

asked to complete some questions on a specifically designed app from Spartanova. Questions

about difficulties in soccer participation, reduction in training volume, affected performance and

symptoms/complaints due to injury, illness or health problems. The injury follow up started after

the preseason screening and continued until the last injury survey on 12 March 2017. If an injury

was registered, a student contacted the athlete by mail or phone to complete an UEFA injury card

about the circumstances of the injury (see addendum). As a secondary registration method, the

players were retrospectively questioned, face to face in their training complex in Tubize

(Belgium), about their sustained injuries that season (February 2017).

Based on a consensus statement, injury was defined as any tissue damage and/or physical

complaints caused by a non-contact event in a soccer match or training, irrespective of the need

for medical attention or time loss in football participation [66].

21

Statistics

SPSS was used for presenting descriptive data and statistical analysis. Only the first registered

injury was recorded for statistical analyses, unless this injury met the exclusion criteria. In this

situation the next suitable injury was used. Exclusion criteria were: (A) contact injury, (B) collision,

(C) injury incurred from a non-soccer activity, (D) type: cuts, lacerations, skin abrasions,

contusions and hematoma (E) body part: dental, head and upper limb.

First the Kolmogorov-Smirnov test was executed to investigate the normality. Frequencies and

descriptives were executed with a significance level set at P<0,05. Demographic data was

compared between the injured and non-injured groups using the Mann-Withney U-test and

unpaired Student’s t-Test (if the variable was normally divided). The preferred kicking leg was

regarded as the dominant leg. Only the scores of the injured leg in the YBT were used for

analysis.

For further analysis, a non-contact lower extremity injury was used as the main outcome variable

in the logistic regression. No separate analyses per injured body part or type of injury were

performed because of a small number of participants per subgroup. A single binary logistic

regression was performed to identify potential intrinsic modifiable risk factors for injuries (see

table 3). All variables with a p-value <0,2 in the ‘Wald Chi Square tests’ were seen as significant

and were investigated further in a multiple model. A Spearman’s correlation matrix was made to

search for correlations between the different tests. The data of the IAT and BMI were centered to

the median and mean respectively. Different logistic regression models were made (ENTER-

method) with different uncorrelated significant variables of the single logistic regression. For the

final analyses, the significance level was set at P<0,2. The 95% confidence interval, ‘Nagelkerke

R²’ and ‘Hosmer and Lemeshow Goodness-of-fit’ test were calculated to evaluate the quality of

the model.

Results

Player and injury characteristics

A total of 101 players were included for analysis. Nine players were excluded after screening,

because no injury registration or no confirmation not being injured was present (figure 1). A total

of 49 players (48,5%) sustained an injury of which 25 injured their dominant leg and 24 their non-

22

dominant leg. The non-injured (NI) players and those with an excluded injury were used as a

control group and were matched by randomization trough number lottery (D (Dominant) n=26, ND

(Non-Dominant) n=26). The injured (I) group contained more strikers (I: 24,5% vs NI: 17,3%) and

less keepers (I: 4,1% vs NI: 19,2%). Most affected body parts were thigh, knee and hip/groin

(resp. 13,9%, 9,9% and 8,9%). Next to that, injuries in the lower leg, ankle, foot and toe occurred.

Overuse and muscle rupture / strain (both 13,9%) were the two most common injuries. Also

dislocations, subluxations, sprains, lesions

of meniscus and cartilage, tendon

ruptures and tendinosis were present.

11,9% of the injuries were classified as

‘other injuries’. No significant difference

was found between the groups in age,

BMI or mean hours of sport, so we did not

include these variables in further statistics.

Demographic data of the participants are

listed in table 1 and viewed in histograms

(figure 7,8,9).

23

TABLE 1

Demographic data for non-injured and injured group.

Demographic data Non-injured n=52

Injured n= 49

P-value

Age (yr) 0,215

Pc 25 14 14,5

Median 16 16

Pc 75 18 22

Minimum 13 12

Maximum 30 33

Mean sport per week (h)² 0,639

Pc 25 8,75 9

Median 12 14,50

Pc 75 20 18,5

Minimum 5 6

Maximum 44 40

BMI (kg.m^2) 0,181¹

Mean 21,30 20,60

SD 2,21 2,54

Differences between groups were measured with the Mann-Withney U-test or ¹unpaired Student’s t-Test Significant p<0.05 ²Sport per week includes soccer, sport at school, strength training and others Yr=year; h=hours; Pc=percentile; SD= standard deviation

24

Risk factors lower extremity

Descriptives of the tests are listed in table 2.

According to the single logistic regression with the significance level set al p <0,2, following tests

are found as possible associated, positively and negatively, with sustaining an injury: IAT,

lumbopelvic control in the LSD, YBT UQ (Upper Quarter) dominant arm superolateral, TJ and

some subscores “thighs not horizontal”, “thighs asymmetric”, “foot placement not shoulder width”

TABLE 2

Descriptives of the tests.

Missings Median Minimum Maximum

Illinois mean (sec.) 26 17,66 15,92 20,56

Illinois fatigue (sec.) 55 18,17 15,48 22,83

Tuck jump 27 11 4 18

YBT UQ D MED 0 1,04 0,66 1,30

YBT UQ ND MED 1 1,04 0,60 1,30

YBT UQ D IL 0 0,98 0,70 1,30

YBT UQ ND IL 1 0,98 0,67 1,35

YBT UQ D SL 0 0,76 0,52 1,07

YBT UQ ND SL 1 0,79 0,58 1,09

YBT LQ AR 0 0,72 0,58 1,01

YBT LQ PM 0 1,21 0,88 1,42

YBT LQ PL 0 1,21 0,86 1,43

LSD 24 6

3 10

THD (cm) 30 426 297 524

YBT= Y-balance test; UQ= Upper Quarter; D= Dominant; ND= Non-Dominant MED= Medial; IL= InferoLateral; SL=

SuperoLateral; LQ= Lower Quarter; PM= PosteroMedial; PL= PosteroLateral; LSD= Lateral Step Down; THD= Triple Hop

For Distance

25

and “foot placement asymmetric”. Also age and BMI were found significant. Per year the player

gets older, the odds for injury increase with 1,106 (p=0,05). For an increase in BMI the odds for

being injured decreases with 11% (p=0,181) (see table 3).

TABLE 3 Single logistic regression

p-value Exp

(B)

95% CI

R² p-value

95% CI Exp (B) R²

IAT 0,019** 0,407 0,193 – 0,862

0,117 YBT – LQ AR

0,970 0,902 0,005 – 179,150

0,000

IAT fatigue 0,707 0,534 – 1,530

0,004 YBT – LQ PM

0,394 7,890 0,068 – 911,975

0,010

LSD 0,406 1,120 0,857 – 1,464

0,012 YBT – LQ PL

0,271 17,07 0,109 – 2671,536

0,016

LSD – dynamic balance

0,710 1,107 0,647 – 1,895

0,002 YBT – UQ D MED

0,236 12,208 0,195 – 763,157

0,019

LSD – knee valgus

0,703 0,905 0,541 – 1,514

0,003 YB – UQ ND MED

0,442 4,188 0,109 – 161,425

0,008

LSD – lumbopelvic control

0,053* 2,307 0,990 – 5,377

0,069 YBT – UQ D IL

0,251 5,180 0,313 – 85,849

0,018

LSD – ankle pronation

0,213 1,948 0,682 – 5,566

0,027 YBT – UQ ND IL

0,861 1,282 0,079 – 20,755

0,000

TJ 0,095* 0,861 0,722 – 1,027

0,052 YBT – UQ D SL

0,080* 17,175 0,710 – 415,612

0,041

TJ – knee valgus

0,288 0,756 0,451 – 1,267

0,020 YBT – UQ ND SL

0,205 9,060 0,301 – 272,870

0,022

TJ – thighs not horizontal

0,048** 0,646 0,419 – 0,995

0,072 THD 0,518 0,997 0,986 – 1,007

0,008

TJ – thighs asymmetric

0,074* 0,520 0,254 – 1,066

0,059 BMI (kg*m²)

0,181* 0,892 0,754 -1,055

0,024

TJ – foot not placed shoulder width

0,199* 0,715 0,428 – 1,193

0,031 Total Sport

0,819 1,006 0,957-1,058

0,001

TJ – foot placement asymmetric

0,014** 2,692 1,222 – 5,929

0,118 Age 0,05* 1,106 1,000 -1,224

0,055

26

TJ – fast rebound

0,929 0,968 0,472 – 1,986

0,000

TJ – no toe to midfoot landing

0,525 0,786 0,373 – 1,653

0,007

TJ – different footprints

0,772 0,963 0,598 – 1,464

0,002

Values based on single logistic regression * Significant p<0,2; **Strong significant p<0,05 R²=Nagelkerke R²; IAT=Illinois Agility Test; LSD=Lateral Step Down; TJ=Tuck Jump; YBT=Y-Balance Test; LQ=Lower Quarter; PM=Posteromedial; PL=Posteromedial; UQ=Upper Quarter; D=Dominant; MED=Medial; ND=Non-Dominant; IL=Inferolateral; SL=Superolateral; THD=Triple Hop for Distance; BMI=Body Mass Index

If the time to perform the IAT increases with one unit, the odds for being injured decreases with

59% (p=0,019). For the subscore ‘lumbopelvic control’ of the LSD, an increase by one is equal

with an increase in odds for injury of 2,307 (p=0,053). If the score in the TJ performance was

worse (higher scores), the odds for injury will decrease with 14% per unit (p=0,095). And the

same for the subscores with a decrease of 35% for “thighs not horizontal” (p=0,048), 48% for

“thigh asymmetric” (p=0,074) and 29% for “foot placement not shoulder width” (p=0,199). In

opposite, the odds for being injured increases with 2,7 fold per unit worse performance in

asymmetric foot placement (this is an increase in score) (p=0,014). Finally, an increase with one

unit in the YBT UQ for the dominant arm in superolateral direction will give an increase in odds for

an injury with 17,175 (p=0,08). Here the 95% CI is also very wide (0,710-415,612). The

Nagelkerke R² shows that only 12% of the variance in the outcome variable could be explained

by the considered logistic model per variable as a maximum, this is the case for the IAT and foot

placement asymmetric in the TJ. The percentage for all other variables were even lower.

The final statistical analyzes consisted of a multiple logistic model were the non-correlated

significant results of the single logistic regression are adjusted with each other. Significant models

are listed in table 4. Adjusted for IAT, asymmetric thighs in the TJ and BMI, the odds for

sustaining an injury increases with a 4-fold per increase in the unit of the asymmetric foot

placement (p=0,007; R²=0,32) and with a 3,3-fold when adjusted for thighs not horizontal, thighs

asymmetric and lumbopelvic control (p=0,018)(R²=0,27). In the same model, the adjusted odds

value increases with 1,943 per increase in score of the lumbopelvic control (p=0,169). The odds

for an increase in unit lumbopelvic control also increases with 1,927 adjusted for TJ (p=0,147;

R²=0,10) and with 2,263 adjusted for YBT UQ dominant arm superolateral (p=0,06; R²=0,10).

27

TABLE 4

Multiple logistic regression

Sign 95% CI Exp (B)

1 Illinois 0,090* 0,197-1,126 0,471

TJ - thighs asymmetric 0,045** 0,130-0,978 0,357

TJ – foot placement asymmetric 0,007** 1,464-11,717 4,142

BMI 0,117*

0,623-1,054 0,810

Constant 0,694 0,648

2 TJ - thighs not horizontal 0,106* 0,406-1,090 0,665

TJ - thighs asymmetric 0,067* 0,185-1,058 0,442

TJ - foot placement asymmetric 0,018** 1,232-9,107 3,350

LSD - lumbopelvic control 0,169*

0,754-5,011

1,943

Constant 0,484 0,393

3 TJ 0,131* 0,717-1,044 0,865

LSD - lumbopelvic control 0,147*

0,794-4,675 1,927

Constant 0,936 1,119

4 TJ 0,097* 0,716-1,028 0,858

BMI 0,136* 0,691-1,052 0,852

Constant 0,159 4,074

5 YB UQ dominant arm superolateral 0,148* 0,381-612,110 15,268

LSD - lumbopelvic control 0,060*

0,966-5,305

2,263

Constant 0,023 0,023

6 YB UQ dominant arm superolateral 0,200 0,318-238,793 8,709

Age 0,111* 0,981-1,209 1,089

Constant 0,026 0,041

7 LSD - lumbopelvic control 0,098*

0,874-4,896

2,068

Age 0,094* 0,980-1,288 1,124

Constant 0,011 0,031

Values based on significant non correlated values of the single logistic regression

*significant p<0,02; **strong significant p<0,5

TJ= Tuck jump; LSD= Lateral step down; YBT UQ= Y-balance upper quarter

28

Discussion

To our knowledge this is the first study using several functional tests in a pre-season screening

followed by an injury registration through a mobile app, calling, e-mail and/or text or WhatsApp to

assess potential risk factors for lower extremity injuries in elite female soccer players. The main

finding was that a more asymmetric landing in jumps is found as a predictor for non-contact lower

extremity injuries. Also worse lumbopelvic control and an increase in age were found as

predictors for these injuries.

Demographic variables and injury risk:

As found in a similar study, the dominant and non-dominant leg were equally injured [38].

Contradictory, Faude O. et al described more injuries on the dominant leg, but no comparison

could be made because most of them were contact injuries [31]. Looking at the player position,

Nilstadt et al and Mohamed et al described more lower leg and knee injuries in forward players

and less injuries in goalkeepers, similar to our findings [33,38]. This variable was not recorded in

the analysis of functional risk factors in this study. Body dimensions have previously been

investigated in various risk factors studies in soccer players and a lot of discrepancy is described.

Some studies did not find any effect [28,31,32,34,67,68]. Present study shows, in contrast with

two latest studies on elite female soccer players, that a higher BMI negatively associated with the

occurrence of an injury [31,38]. This is also in contrast with the fact that an increased BMI is

assumed to increase the stress on ligamentous and muscular structures during sports and

thereby increasing the injury risk. The significance in the Wald Chi Square test was not strong

(p=0,181) and the statement that BMI has no influence on injury occurrence could not be

rejected. Furthermore, only 2,4% of the variance of BMI could be explained by this model, so it

could be a case of coincidence. Age is often assumed as a risk factor for injuries. Supportive

findings were found in this study and were described several times in literature [27,34,35,38]. The

fact that higher hassle scores were seen in the older population in the study of Ivarsson et al.,

and a link was found with a higher injury risk need to be kept in mind [35]. Two other studies did

not find any effect of age on sustaining injuries [31,32]. In present study, BMI, age or total sport

were not included in the single regressions of the tests, because no significant difference was

found between the injured and the control group (table 1).

29

Functional factors and injury risk

According to our results, an increase in the score of the TJ, so a worse performance, more

specifically also for thighs not horizontal, thighs asymmetric and foot not placed shoulder width

were associated with a decrease in odds for injuries. No possible explanation for these results

could be found. Besides this, an asymmetry in foot placement in jumps was found as the

strongest predictor for sustaining an injury, but a knee valgus did not have any significant

influence. Myer et al. also found that poor landing techniques during the TJ are associated with

ACL injuries and in contrast to our findings, they showed that knee valgus was the main risk

factor, even so that the movement of the hip was associated with the degree of knee valgus and

indirect with an injury [59]. But only ACL injuries were included in the study, other than including

all non-contact lower extremity injuries like in present study. Tuck jump was used as a test

because it is described as a better screening test than the drop jump test. Due to the plyometric

aspect, more stress is executed on the structures, so this test is more sensitive [60]. In case of

the IAT, running the course slower, so having poor speed, accelerations and agility performance,

was found as a negatively associated with sustaining an injury. No possible explanation could be

found. Currently no study describes the association between the IAT and injury prevention, so

also no comparison could be made. More research about this specific topic is suggested,

especially because it is commonly used in case of return to sport investigations [64]. Gonnel et al.

found poor balance, tested by the YBT of the lower quarter, as a predictor for injury. No such

findings were seen in our results [51]. Like the IAT, no associations between upper quarter YBT

and injuries are earlier described in current literature. A poor lumbopelvic control in the LSD is,

besides the asymmetric landings, also found as a predictor for injuries. Only associations

between ROM in the joints of the lower extremity and the performance on the LSD were found in

current literature, so no comparison could be made [47,48]. This parameter needs to be further

investigated with greater samples to confirm the values of this variable as a predictor for injuries.

No association was found between injuries and the score on the triple hop test, so no correlation

was found between sustaining an injury and lower limb functional strength and power.

Several full significant models were found adjusting the variables. Teyhen et al found a

correlation between the LSD and YBT, but again specific for the LQ and nothing about the UQ

[53]. No other correlations, as found in present study, are earlier described. Multiple models are

preferred for describing risk factors in injuries, because non-contact injuries mostly results from a

30

complex interaction of multiple factors and events. In these models the association between the

different variables could be seen, though functional performance test already combine multiple

components.

According to our findings, core stability could possibly be seen as a basic component. Two other

studies discussed earlier the association between core strength and performance. Prieske et al.

found that core training, both on stable and unstable surfaces, improves the sprint, trunk muscle

strength and kicking performance, but no significant difference in the counter movement jump and

the T-agility test [69]. Thomas et al. described only a moderate relationship between the core

stability, and strength and functional performance as outcome variables[70]. Besides this, poor

balance, altered motor control, or lack of neuromuscular control were also found as predictors of

injury risk in the lower limbs of athletes [51].

Methodological considerations

As aforementioned, the popularity of women’s football is at an all-time high and little research has

been done on the incidence and risk factors for injuries sustained by female football players. This

study provides more insight in the possible risk factors of injuries in female elite football. That is a

first step in the prevention of sport injuries which must be seen as an essential aspect to include

in future management of women’s football. The prospective design with a longitudinally follow up

is another strength of this study, because recall bias is minimized.

While interpreting the findings of this study, several limitations need to be kept in mind. First of all,

the small sample size has to be taken into account. Several missings were described in some

variables, so the sample size was even smaller for this model. This because less participants

performed the test in the preseason due to musculoskeletal complaints, hot environment

temperature or limited by the RBFA (a risk for injuries for the red flames preseason). However,

according to Bahr and Holme (2003), moderate to strong associations could be made with this

amount of injured participants [71]. Yet, in present study no high percentages were described in

the explanation of the variance in the outcome variable with the considered model (Nagelkerke

R²). Confidence intervals were several times very wide and not frequently the hypotheses that the

variable has no influence of being injured could be rejected, this could only be stated for the

asymmetric foot placement after jumping. Also no good fit is described, because none of the

models has significant values in the Hosmer and Lemeshow Goodness-of-fit test. However, this

31

test is very sensitive for sample size. This low quality of the models needs to be kept in mind

while interpreting the findings. The predictive value of our risk model warrants validation and

replication in larger samples to ascertain the findings. Besides this, a major limitation of this study

is not excluding participants who were injured six months before the pre-season screening. This

exclusion criteria was not implemented because of the major dropout and so analyzing an even

smaller sample size. In elite male soccer players, high re-injury rates are well known [16,72,73].

This is also described for their female counterparts [27, 67,68, 74]. Other studies founded no

effect [31,32,38]. Discrepancy could be explained by differences in population (age, playing level

and the level of medical treatment and rehabilitation). For example, an increased risk for injuries

was seen in youth soccer players [67,68] but no association was found by senior players [31,32].

Also differences in definition and length of time before injuries were screened could affect the

interpretation. Besides this, we relied on interviews with the players for injury registration and

classification. This subjective recording could lead to problematic interpretation of injuries, this

was also a problem in recording the hours of sports per week. In other studies, injuries were more

objectively recorded by medical staff and coaches. According to Nilstadt et al., text messaging

appeared to be an effective method for recording injuries individually in team sports [77]. The

compliance with the app was also not as expected, so other communication media were also

used (calling, texting, WhatsApp, e-mail,..) and still injuries could have been missed. The

retrospective interview was executed to minimize these missings, but recall bias needs to be

considered. The participants were playing in different teams and at different levels, so a similar

trainings program was not possible during the follow up. The possibility of training on weaknesses

in some participants could not be covered. Another fact to keep in mind are the differences

between the procedures of the tests. In two other studies, the tuck jump test was performed as;

as many jump as possible in ten second, instead of performing ten jumps [58,60]. Other ways of

testing and scoring were described for the LSD and they also used a 20cm step height instead of

30cm [47,48]. In the study of Hamilton et al., arm swing was allowed when performing the THD

test which was not the case while performing the test for this study [63]. Without a doubt, other

important predictable factors for injuries must be considered like anatomical, hormonal and

psychological factors. Previous injuries and external factors (weather conditions, equipment,

variable surfaces, load, years of experience eo.), which are also described as important risk

factors, were not considered in present study [71]. As non-contact injuries likely result from an

32

interaction of multiple factors, present study cannot give a full description of risk factors for

injuries in female soccer players [68,71,75].

Conclusion

According to our findings, an asymmetric landing and poor lumbopelvic control are associated

with non-contact injuries in the lower extremity in female soccer players. More studies with larger

sample sizes are suggested to confirm the importance of these factors. Hereby, future studies

investigating risk factors for injuries, that also consider previous injuries and other important

factors such as anatomic, external, psychological and hormonal factors would be great to improve

preventive measures, so good interventions could be applied to tackle the high injury rate in

female soccer.

33

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39

ABSTRACT (layman version)

Background: A lot of injuries occur in female soccer players. However little is known about

possible risk factors and the use of functional tests as a screening tool.

Objectives: To investigate player-related risk factor, which can be trained, for lower extremity

injuries in female soccer players.

Study design: A study in which a specific part of a population is monitored for a certain period of

time and where the investigated outcome took place after the start of the study. Level of Evidence

3; An observational study with a control group.

Methods: Players of the RBFA (Royal Belgian Football Academy) (n=7 teams) were invited for a

preseason screening before the 2016-2017 competitive season. This screening started with a

baseline questionnaire about players-related data followed by some functional test like the YBT

(Y-balance test), TJ (tuck jump), THD (triple hop for distance), LSD (lateral step down) and the

IAT (Illinois agility test). After the screening, injury registration was performed on a weekly basis

using a mobile app (application) up until March 2017. Data about injury circumstances were

collected by contacting the injured players. Statistical analyses were executed to search for an

association between injuries and one or more predictors. In a model was looked for significant

influences of scores on the test on the occurrence of injuries. Besides this, the ratio of likelihood

that the player was injured relative to the likelihood of being uninjured was calculated per change

in the score of the analyzed test (odds), as well as a 95% confidence interval (CI) of the outcome

in the model.

Results: A total of 101 players were included for analysis, of which 49 players sustained a non-

contact injury. No significant difference was seen in age, BMI (body mass index) and total hours

of sport between the injured and non-injured group. The single logistic regression showed that

“asymmetric foot placement” as a subscore of TJ (P-value= 0,014; 95%CI= 1,222-5,929, Odds=

2,692) and “lumbopelvic control” as a subscore of LSD (P-value= 0,053; 95%CI= 0,990-5,377,

Odds= 2,307) are associated with non-contact lower extremity injuries.

Conclusion: Asymmetric landings after a jump and a poor lumbopelvic control were associated

with non-contact lower extremity injuries in female soccer players. The predictive value of these

risk factors needs to be confirmed in larger samples.

40

ABSTRACT (lekentaal)

Achtergrond: In vrouwenvoetbal komen er veel letsels voor. Er is echter weinig gekend over

mogelijke risicofactoren voor blessures in deze populatie en het gebruik van functionele testen

als screeningsinstrument.

Doelstellingen: Het onderzoeken naar risicofactoren, die speelsters-gerelateerd zijn en waaraan

gewerkt kan worden, voor letsels aan het onderste lidmaat bij vrouwelijke voetbalspeelsters.

Onderzoeksdesign: Een studie waarbij een deel van een populatie gedurende een bepaalde tijd

opgevolgd wordt en waarbij de feiten die bestudeerd worden pas plaatsvinden nadat de studie

begonnen is. Level van evidentie 3; een observerende studie met een controlegroep.

Methode: Zeven teams van de KBVB (Koninklijke Belgische VoetbalBond) werden uitgenodigd

voor een screening voorafgaand het competitieseizoen van 2016-2017. Deze screening begon

met een basisvragenlijst over speelsters-gerelateerde gegevens (oa. leeftijd, team, voet- en

handdominantie, ..) gevolgd door enkele functionele testen zoals de YBT (Y-balance test), TJ

(tuck jump), THD (triple hop for distance), LSD (lateral step down) en de IAT (Illinois agility test).

Het registreren van letsels werd uitgevoerd op wekelijkse basis via een mobiele applicatie vanaf

de screening tot in maart 2017. Data over de omstandigheden waarin het letsel is opgetreden

werden verzameld door de gekwetste speelster te contacteren. Statistische analyses werden

uitgevoerd om blessures te linken aan een of meerdere voorspellers. In een model werd er

gekeken of de scores op de testen significant een invloed hebben op de mate van het voorkomen

van een blessure. Hiernaast werd de verhouding van de waarschijnlijkheid dat de speelster

gekwetst was t.o.v. dat ze niet gekwetst was berekend per verandering van de score op de

geanalyseerde test (odds), alsook een 95% betrouwbaarheidsinterval (BI) van de uitkomst bij het

model.

Resultaten: In totaal zijn er 101 speelsters geïncludeerd voor de uiteindelijke analyse. Hiervan

liepen er 49 een non-contact letsel op. Er werd geen significant verschil gevonden voor leeftijd,

BMI (Body Mass Index) en aantal uren sport tussen de gekwetste en niet gekwetste groep. Met

de enkelvoudige logistische regressie kon gesteld worden dat asymmetrisch landen tijdens de

tuck jump (significantie= 0,014; 95%BI= 1,222-5,929, Odds= 2,692) en controle van de bekken

tijdens de LSD geassocieerd (significantie= 0,053; 95%CI= 0,990-5,377, Odds= 2,307) zijn met

het oplopen van een letsel.

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Conclusie: Asymmetrisch landen na een sprong en slechte controle van de bekken zijn

geassocieerd met non-contact letsels in de onderste ledematen bij vrouwelijke voetbalspeelsters.

De voorspellende waarde van deze risicofactoren moet bevestigd worden in grotere

steekproeven.

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Addendum 1)

SCORE FORM 1 Lateral Step Down

0= excellent

1= good

2= moderate 3 = poor

Dynamic balance Scoring based on: Hands on shoulders; Looking forward; Smooth performance

No oscillations

little oscillations

normal compensations

Bad on every criteria

Knee valgus / internal rotation Scoring based on: In deepest point of the movement: perpendicular from center patella which metatarsal?

2e metatarsal without oscillations

2e metatarsal with oscillations

1ste metatarsal with or without oscillations

medial from 1ste metatarsal or lateral shift hip

Lumbopelvic control Scoring based on: Angle between horizontal line and line between two ASIS in the deepest point of the movement

0° 0° - 10° 10° - 20° >20°

Ankle pronation

No dynamic hyper-pronation

dynamic hyper-pronation

/ /

43

2)

SCORE FORM 2 Tuck Jump

0= no single jump

1= in one to five

jumps

2= in five to nine jumps

3= in all ten jumps

Knee valgus

Thighs not horizontal

Thighs asymmetric

Foot not placed shoulder width

Foot placement asymmetric

No plyometric (rebound)

Toe-to-midfoot landing

Different footprints (not jumping on the same spot)

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3) UEFA injury card

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4) Form during the screening

Naam/Nom:_____________________________________________

Antropometrics

Links Rechts

Lichaamslengte cm

Lichaamsgewicht kg

Beenlengte cm cm

Armlengte cm cm

Heupomtrek cm

Buikomtrek cm

Borstomtrek cm

Menstruatie (datum)

Flexibility

1ste meting: L / R Links Rechts

Heup ER ROM ° °

Heup IR ROM ° °

Adductor flexibility ° °

Straigth Leg Raise ° °

Ely’s test ° °

Weigth-bearing Lunge: gebogen ° °

Weigth-bearing Lunge: gestrekt ° °

Strength

1ste meting: L / R Links Rechts

Trial 1 Trial 2 Trial 1 Trial 2

Hamstrings make N N N N

Quadriceps N N N N

Hamstrings break N N N N

Heupextensie N N N N

Heupabductie N N N N

Heupadductie N N N N

Heupexorotatie N N N N

Heupendorotatie N N N N

Endurance and agility

Illinois sec sec

Yoyo test IR Level 1

Illinois fatigue sec sec

46

Functional analyses

1ste meting: L / R Links Rechts

Lateral step down

Tuck Jump

Tripple hop For distance cm cm cm cm cm cm

Postural control

Y-balance Lower

extremity

Rechts Links

Anterior reach cm cm cm cm cm cm

Posteromedial cm cm cm cm cm cm

Posterolateral cm cm cm cm cm cm

Y-balance Lower

extremity

Mediaal cm cm cm cm cm cm

Inferolateraal cm cm cm cm cm cm

Superolateraal cm cm cm cm cm cm

Bodystat

H2O Vetpercentage Impedantie

Bodystat

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48

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