Background
Foot and ankle injuries are highly prevalent in adolescents [
1‐
3]. This is especially true for footballers, who have an increased risk of fractures and epiphyseal injuries [
1‐
3]. These injuries can lead to long periods of physical inactivity, which can have a detrimental effect on a patient’s quality of life [
4]. One factor that can alter loading of the ankle–foot complex, and potentially lead to pain and injury, is foot morphology.
The morphology of the foot has been well researched in order to establish its link to increased pain and injury in the foot and ankle [
5]. The foot arch has received the most focus because a flat arch (pes planus) or a high arch (pes cavus) presentation can lead to altered loading of the foot during athletic tasks, and decreased static and dynamic postural stability performance [
6‐
9]. Altered loading from foot morphology is a particular concern in adolescents, where it could further overload and lead to significant foot fractures and overuse injuries [
10‐
12]. Thus, foot morphology assessment is warranted as a routine part of football screening.
Foot morphology assessment is usually carried out in a clinical setting because medical imaging is costly, time-consuming, and any potential radiation risk would be unsuitable for a young, asymptomatic population, as per ALARA principles [
13]. While various assessments exist, few have been validated in the adolescent population [
14]. Clarke’s Angle has been recently confirmed as reliable and valid in adolescents of all ages [
14‐
16], while Resting Calcaneal Stance Position is strongly correlated with imaging methods, and it has been used to define cut-offs in adolescents previously [
17,
18]. However, a limitation of these analyses is that they are two-dimensional (2D) approaches to the three-dimensional (3D) foot, missing the global picture from forefoot to hindfoot [
19]. While whole foot approaches like the Foot Posture Index 6 (FPI-6) exist, they can lack reliability due to their subjective assessment [
16,
20]. While readily accessible, these limitations to current 2D and/or subjective clinical assessments make objective 3D approaches attractive for accurate diagnosis and treatment for those in large health centres or in sporting environments, where more funding for equipment is available and large populations are tested more frequently. Moreover, the costs are constantly decreasing with models available from approximately $200USD on the market [
21].
The most common 3D approach to foot assessment is laser scanning. Laser scanning has no risk of radiation, and offers a fast, reliable, and accurate assessment [
22]. However, a limitation is the interpretation of the foot scans in regards to the population being compared against. This normative population description can be defined using Statistical Shape Models (SSMs). Using 3D foot scanning technology, three studies have attempted to define normative data values for adult populations [
23‐
25]. Mei et al. analysed the difference between habitually barefoot and habitually shod males, and they found a variance in principal component generation, though specific differences between groups were not determined [
24]. Conrad et al. had a large sample size of over 1700 females and 2400 males, and they discovered that females had a higher arch and instep, as well as a narrower foot compared to males. However, the paper lacked elaboration and the foot shape did not specify toe morphology [
23]. Stanković et al. (2018) described in-detail normative data for a healthy adult population with a specific foot shape that showcased the intricacies of each principal component that related to arch height, forefoot type, heel variation, hallux angulation, and midfoot width, amongst others. They found significant results in relation to gender, age, and shoe size, and showed individual foot comparisons to the population [
26]. This study group additionally validated the same techniques in analysing abnormal foot arches and hallux variation, and could completely characterise these abnormalities in 3D for the first time [
25]. However, such SSM analysis has not been conducted in an adolescent, football-playing population, despite the repetitive loading of the foot and ankle complex and potential injury risk associated with foot morphology.
Thus, the first aim of this research was to describe 3D foot morphology differences between age groups of elite male adolescent footballers. Furthermore, it would be beneficial to understand how much usual clinical measures can relate to and explain the 3D foot presentation. Thus, the second aim was to compare clinical assessments to the specific foot morphology related to arch height in this population by correlation and linear regression analyses. Since this is a football-playing population, to discover the relationship between foot morphology and a performance-related measure would be beneficial for sport practitioners. Therefore, the last aim of this research was to assess the relationship between foot morphology and postural stability measures.
Discussion
The 3D foot SSM of male adolescent footballers detailed nine modes of foot morphology, which explained 77.22% of the foot shape variance. This is in contrast to Stanković et al. (2018), where they accounted for the variation of foot length before creating their model [
26]. Thus, their first reported mode describes the foot arch, which is the second mode in this current study. Due to this difference in approach, the models should not be conflated. Previous research has shown that foot length increases over time in adolescents, and the model in this paper indicated that this plateaued at 16 years of age as shown in Mode 1 (Fig.
1) [
35]. This suggests that those before and up to the age of 16 should continually monitor the length and size of their foot for correct footwear during sport to prevent discomfort from ill-fitting boots.
Mode 2 is similar to findings in Stanković et al. (2018); that the entire 3D foot arch can be captured from forefoot to hindfoot [
26]. In contrast to the literature, which has found decreased flatfoot prevalence in older adolescents [
14,
36], the results here show that it varied from U15 onwards, as both the U17 and U19 age groups presented with more pronated feet compared to U16 and U18. These are important findings for the literature and clinical practice, as it cannot be assumed that there is a linear pattern to foot arch presentation in adolescents. This makes foot assessment crucial for all ages to discover if they lie outside of the normal ranges for their age group, as foot type variability is considered [
14]. 3D foot scans allow interpretation of these results as a global picture as opposed to usual clinical assessments, as shown by the results of our second objective.
Only low-to-moderate correlations and regression models were found when comparing the usual clinical assessments of CA and RCSP to the mode that specifies arch height (Mode 2). This indicates that these 2D measures do not capture the complete multifaceted nature of 3D foot morphology in flat or high arched feet. This is consistent with the literature, which shows that 2D measures are not as valid and reliable compared to 3D techniques [
14,
37]. Interestingly, the results displayed different peaks and troughs of foot arch presentation. In both the clinical assessments, the U13 age group had the flattest foot presentation. This is in comparison to our model, which showed that the U14 age group had the ‘flattest’ 3D foot arch morphology. The differently identified ‘flattest arched’ groups and the regression analysis indicates that there is more to 3D foot arch presentation than 2D rearfoot and plantar sole analysis can determine alone.
Mode 5 showed the effect of tibial rotation on the foot, despite standardised protocols to eliminate rotational factors on scanning and in the SSM analysis. As per Schultz et al., adolescents tend to move from a pronated foot and internally rotated tibia to a supinated and externally rotated tibia [
38]. Our results showed similar findings overall, especially in the U16-U19 age groups. The U16 and U18 age groups presented with a more supinated foot, as well as a more externally rotated tibia. In contrast, the U17 and U19 age groups presented with a more pronated foot, as well as a more internally rotated tibia. However, an interesting finding is that children started off in the U12 age groups with a more supinated foot too. Older age groups then had a more internally rotated tibia before the foot pronated. Following this foot pronation, the tibia presented with more external rotation. This potential coupling of the tibial torsion and foot gait mechanics, such as the Foot Progression Angle, has been well documented in the literature [
39], and increased external rotation of the lower limb has been observed in those with flatfoot [
40]. This may explain why a more externally rotated tibia was found in older age groups to counteract a more pronated foot presentation. Alongside further dynamic gait analysis, these findings could suggest recommendations for different age groups to prevent overload [
41]. As U12 players move from a supinated to a pronated foot, potentially more external rotation strength could benefit the lower limb. Older age groups varied considerably, so their results should be interpreted individually as to whether they require more internal or external alignment interventions of the lower limb and foot.
Modes 3, 4, 6–9 were not significant in this study. Mode 3, which corresponds to foot width, surprisingly showed no significant differences between age groups, even though the literature reports a significant increase in foot width at 13–14 years of age in boys [
42]. This may have been due to the wide variance of foot width in our population. Larger sample numbers, as are used in population studies, may discover a significance [
42]. The other modes became more specific, and may be more related to individual abnormalities rather than age group specificities. For instance, Mode 9, corresponding to hallux abduction or adduction, was not significant between age groups, perhaps due to the fact that abnormal presentations of hallux valgus have a low prevalence of 7.8% in adolescents, and they are more common in females than males [
43,
44]. However, the importance of these modes should be noted. They are the first time 3D foot morphology has been reported for adolescents, and are novel findings for the literature. They can guide better understanding of the variance of the adolescent foot, and what areas should be of focus in clinical assessment, with potential caution if significant differences are found compared to the mean shape for those non-significant modes, such as great toe length or hallux angle.
Footballers have been shown to have the second best postural stability when compared to other sports and controls in bilateral, open eyes position [
45]. In our results, postural stability measures showed a trend of stabilising in the U16 group as, while they continued to decrease, they became non-significant between age groups thereafter. These results are similar to the literature, which found differences between younger and older footballers [
46], though presented here are results for each age group. These can be used as reference values for researchers and coaches who are using the same protocol and technology. Our correlation analysis found only a few low correlating factors to postural stability, and only foot length in unilateral postural stability was a factor related to foot morphology. This may be due to factors associated with postural stability beyond the scope of this research paper, such as maturation status [
47] and strength of the trunk and lower limb [
48]. The negligible correlations indicate that foot specific exercises should only be part of a multifaceted program to improve postural stability in footballers, as shown by multimodal interventions that lead to increased performance and decreased injury with better postural stability results [
48,
49].
There are limitations to this research. These measures were taken with the participant in a static posture, and were not an analysis of dynamic measurements, which are usual practice in foot assessment [
50]. An issue with 3D shapes and dynamic measurements is capturing the varying 3D shape over time, i.e., analysing a four-dimensional (4D) foot shape. Recent research has been promising in this area, and it is hoped that it continues to develop so foot morphology during gait can be compared to a general population for abnormalities, with footwear and treatment considerations from a functional perspective [
51,
52]. The use of 4D foot morphology assessment would also be beneficial for longitudinal analysis to assess if the foot develops as described here. Future research could compare 3D foot shape with injury and/or pain development in participants to discover if any foot morphological features are associated with risk of injury or pain. This could inform cut-offs and abnormal ranges for 3D foot morphology for clinicians, and work similar to Stanković et al. for detecting abnormalities may streamline and standardise clinical assessment and treatment [
51,
25].
This research only assessed male footballers and should be repeated in females, as there is less literature available on postural stability and foot morphology in this population [
53,
54]. Further comparison to non-sport playing controls would be beneficial to determine the role of sport-playing on foot morphology and postural stability [
45,
55]. Ethnicity was not gathered and should be a part of future research studies as there can be significant changes between different ethnical groups [
56]. The clinical assessments used in this study were adapted for the 3D scans. They should be compared and validated compared to their 2D clinical equivalents. FPI-6 and Navicular Height measures were not used for this retrospective study due to their requirement of palpation for best practice [
16,
57].
However, despite these limitations, there are clear practical applications from the results. Laser scanning enhances its value to clinicians when combined with SSM techniques, as the principal component analysis reduces the 3D foot into different shape features for analysis. This would normally require multiple assessments in the clinic, which would be time-consuming for each foot in comparison to a single scan. They are also not as reliable in replicating the 3D nature of the foot morphology as this study found. This becomes particularly important in assessment of adolescents.
Tracking of progression of 3D foot morphology in adolescence could identify those with abnormal morphology for potential treatment before pain and further deformity occur, which is preferable over a wait and see approach [
19]. This identification can be personalised as the participant’s 3D foot can be compared to the population of the same age group with similar characteristics, i.e., male and football playing. The breakdown into the shape features can then identify where their foot significantly differs compared to the usual population, i.e., a significantly wider foot, flatter foot, etc., which can then lead to specific recommendations to the player, i.e., further dynamic and/or medical assessment, boot modification, exercise consideration. The larger datasets gathered, the reduced variability in the spread of the population across a shape feature, and the more accurate the clinician can be in determining what lies outside the normal variance for a given population for a given shape feature, i.e., determining an ‘abnormality’. This makes for precise, personalised care for the participant when examining the 3D foot shape.
As previously mentioned, foot assessment is warranted in youth footballers as there is repetitive loading on the foot-and-ankle complex, which could lead to overload from altered foot morphology [
6,
9,
12]. We found significant differences in tibial rotation relative to the foot and foot arch morphology, which may led to significant changes in loading of the foot–ankle complex, which could predispose to pain and injury. As part of preseason assessment, the 3D foot scan could be analysed for these foot morphologies, with recommendations made for those in abnormal ranges for the upcoming season. Those in abnormal ranges could then be scanned more regularly to ascertain treatment or intervention benefit, with comparison to the population and their previous scans for an objective, personalised assessment. With the addition of comparison to postural stability measures, if an abnormality was found that was significantly related to poorer postural stability performance, it could be recommended to add postural stability exercises for that abnormal foot morphology. Future research and practice can expand on this by comparing 3D foot morphology to gait analysis, usual and sport-specific, for more movement-specific recommendations if altered loading is connected to a particular 3D foot morphology. Further, examining whether ‘abnormal’ ranges are then linked prospectively to injury and/or pain would further refine and personalise recommendations from 3D foot assessment.
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