The effects of shoe sole thickness on running biomechanics and economy: a systematic review

The effects of shoe sole thickness on running biomechanics and economy: a systematic review | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Systematic Review The effects of shoe sole thickness on running biomechanics and economy: a systematic review Kettner, Cagla, Krapp, Felix, Stein, Thorsten This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6526264/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Advanced footwear technologies (AFT) are popular for their potential performance benefits, though concerns about injury risks persist. Among various AFT features, sole thickness is particularly debated, especially after World Athletics imposed a 40 mm limit to prevent unfair competitive advantages. However, the isolated effects of sole thickness on running biomechanics and economy are not well understood. Objective: This review examines the effects of sole thickness on spatiotemporal variables, kinematics, kinetics, and running economy. Methods: A systematic literature search was conducted following PRISMA guidelines. Eligible studies included original research on running with participants of all expertise levels, analyzing spatiotemporal variables, kinematics, kinetics, or running economy. Results: Fourteen studies met the criteria, mostly focusing on male recreational or experienced runners. Thicker soles were linked to increased stance time, while other spatiotemporal parameters remained unchanged. Significant effects were seen in ankle kinematics, with more dorsiflexion at initial contact (IC) with thicker soles, though knee and hip movements were less affected. Thicker soles increased peak eversion in the frontal plane. No consistent trends emerged for joint kinetics, stiffness, or center of mass movement. Vertical ground reaction force (GRF) peaks remained largely unchanged, but loading rates generally decreased with thicker soles. Only one study assessed running economy, with no significant effects. Conclusions: Thicker soles were largely linked to longer stance times and lower GRF loading rates. Future research should comprehensively report shoe characteristics, include more diverse populations (e.g., female runners, forefoot strikers), expand investigations to underexplored aspects such as muscle activity and movement coordination. Sports Medicine and Kinesiology Running footwear Stack height Kinematics Kinetics Running economy Spatiotemporal variables Advanced footwear technology Figures Figure 1 Key points Thicker soles increase stance time and ankle dorsiflexion at initial contact but have largely inconsistent effects on other spatiotemporal parameters as well as joint kinematics. Thicker soles reduce vertical ground reaction force loading rate, but their impact on stiffness and running economy is unclear. Methodological heterogeneity and limited participant diversity highlight the need for more inclusive and comprehensive research. 1. Background Running shoes play a vital role in enhancing performance and reducing injury risk [1]. The complexity of modern running shoes, which incorporate multiple design elements, combined with the unique needs of different runner subgroups [1], makes determining the ideal shoe design challenging. Additional factors, such as habitual foot strike patterns [2] and running surface hardness [3], further complicate this process. Another challenge is the interaction of various design features, making it difficult to isolate their individual effects [4]. For example, incorporating a carbon plate in a shoe may require a thicker sole, increasing both the height and mass of the shoe. A systematic analysis of existing research is needed to evaluate the impact of specific shoe features on biomechanics and performance. One key design feature of running shoes is sole thickness, also referred to as midsole thickness or stack height [4–7]. Since the 1970s running boom, shoe designs have substantially evolved [8]. Initially, cushioned shoes with thicker soles were developed to reduce vertical impact forces [8–10]. In the early 2000s, athletes at Stanford University trained barefoot, observing more natural landing mechanics [8]. This led to the creation of minimalist shoes designed to mimic barefoot running with a thin sole. Despite evidence that barefoot running and minimalist shoes can reduce impact forces [11] and alter spatiotemporal parameters [12,13], no studies have demonstrated a reduction in injury risk with minimalist shoes [14–16]. Some research has shown increased risk of overuse injuries when transitioning to minimalist shoes [17,18], although these injuries often seem to be linked to an abrupt transition rather than the shoes themselves. In the 2010s, alongside minimalist shoes, maximalist footwear emerged with Advanced Footwear Technology (AFT) designed to enhance performance [19,20]. The driver behind AFT development was the goal of breaking the two-hour marathon barrier, which was considered physiologically impossible by some experts and athletes [21–23]. AFT shoes feature technological advancements like carbon plates or rods to optimize shoe bending stiffness and minimize energy loss at the joints [24,25]. These carbon elements are embedded in lightweight, thick midsole foam, providing cushioning and energy return [26]. Initially, World Athletics only regulated that the shoes must not offer unfair advantages and must be available to all athletes (Technical Rule 143.2, [27]). However, in 2020, World Athletics implemented rules limiting sole thickness to 40 mm and restricting rigid structures like carbon plates to a single element in the sole [28]. In 2022, regulations prohibited the use of intelligent technology in racing shoes [29]. AFT shoes are now widely used by runners of all skill levels [19,30,31]. Several studies have shown improvements in running economy with these shoes [19,32,33], though the benefits tend to decrease with lower skill levels [33,34]. Concerns about potential injuries, particularly for non-elite runners, are growing [31]. While multiple studies have examined the biomechanical effects of AFT shoes, there is still no clear understanding of how individual shoe features influence performance and injury risk [4,7,35,36]. Most research has compared different shoe models [26,33,37] rather than isolating specific design elements. A 2020 systematic review found limited studies on sole thickness, and their findings were inconclusive [38]. A more recent scoping review published in 2023 [9] analyzed various shoe features but did not focus on sole thickness. It found that while sole thickness influences vertical ground reaction forces (GRF), it does not affect foot and knee angles at initial contact. Similarly, a narrative review on postmodern running shoes [7] included sole thickness as a sub-group of midsole geometry but did not explore the underlying biomechanical changes. Both reviews emphasized the need to understand how individual AFT features affect runners' responses and how runner-specific characteristics influence those responses. To date, no review has specifically investigated the isolated effects of shoe sole thickness on running biomechanics and economy. This systematic review aims to fill this gap by investigating how sole thickness impacts spatiotemporal variables, kinematics, kinetics, and running economy. 2. Methods This systematic review was conducted and reported in accordance with the “Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020)” [39] and “Prisma in Exercise, Rehabilitation, Sport medicine and SporTs science (PERSiST)” Guidelines [40]. 2.1. Eligibility criteria Any type of observational or experimental study was eligible for inclusion, while reviews were excluded, as in similar systematic reviews [41,42] Only full-length articles or short communications were considered, with conference proceedings excluded due to insufficient study details. Study eligibility was determined using the Population, Intervention, Comparison, and Outcome (PICO) framework [40,43] as follows: Population: Healthy adult runners (aged 18–65 years) were included. No exclusion criteria were applied regarding foot strike pattern or running expertise level (e.g., non-elite, experienced runners). Intervention: Studies assessing different running shoe conditions during running were included. Other tasks such as walking were excluded. No restrictions were applied regarding the running surface (e.g., treadmill or overground), running duration, distance, or speed. Comparison: Only studies specifically analyzing the effect of shoe sole thickness on running performance, spatiotemporal characteristics, kinematics, or kinetics were included. Comparisons of multiple design features (e.g., heel-to-toe drop, toe box width) and barefoot conditions were excluded. Outcome: Studies assessing running performance, spatiotemporal characteristics, kinematics, or kinetics were included. 2.2. Data sources and search strategy A standardized electronic literature search was conducted using the following search term combinations: (“footwear” OR “shoes”) AND (“thickness” OR “stack height”) AND (“runn*” OR “jogg*”) AND (“biomechanic*” OR “econom*” OR “kinematic*” OR “spatio*” OR “kinetic*” OR “performance”). The literature search was conducted across three databases: Scopus, Web of Science, and PubMed. Additionally, a supplementary search was performed in Footwear Science , following the approach recommended in previous reviews on running shoes [42,44]. The reference lists of relevant studies were also manually screened to identify any additional articles not captured through the database searches. Studies published up to 1 March 2025 were considered, and only articles published in English were included. 2.3. Selection and data collection process One reviewer (FK) conducted the initial electronic search and removed duplicate records. Titles, abstracts, and full-text articles were independently screened for eligibility by two reviewers (CK and FK). Any disagreements were resolved by discussion, and if necessary, a third reviewer (TS) provided input to reach a consensus. 2.4. Data extraction A data extraction form (Table 1) was developed based on previous systematic reviews in related areas and the PICO framework [38,40,41,45]. The extracted data included: research question, study design, description of the sample, details of the tested shoes, experimental and analysis protocol, and the outcomes of the study. Data were extracted independently by two reviewers (CK and FK) and compared for potential disagreements. 2.5. Study risk of bias assessment The risk of bias for each included study was independently assessed by two reviewers (CK and FK) using the Cochrane risk of bias instrument tool (RoB-2) [46], following the approach of similar running-related studies [47]. An extended version of RoB-2 for cross-over trials was applied, which included an additional domain addressing bias due to confounding factors. Within the domain bias arising from the randomization process , the randomization of shoe allocation and the presence of a power calculation were examined. Confounding factors were defined as foot strike type, additional substantial variations in shoe features (e.g., heel-to-toe drop and mass), and the expertise level of the runners. Bias in measurement of the outcome was evaluated by determining whether shoe blinding was implemented and whether validated devices were employed. The absence of a shoe familiarization session was considered a factor that could increase the bias arising from period and carryover effects . Missing effect sizes or the absence of corrections for multiple post-hoc tests were considered potential sources of bias in the selection of reported results . The risk of bias assessments were conducted independently by CK and FK. In instances where discrepancies arose between reviewers, consensus discussions were held to reach a final decision. 3. Results 3.1. Search results and study selection The initial search yielded 163 articles, which was reduced to 152 after removing duplicates (Fig. 1). Of these, 136 articles were screened, and 14 studies met the inclusion criteria (all cross-sectional). Eleven studies explicitly mentioned sole thickness in their title or research question [48–58], while one study focused on midsole geometry, including both heel-to-toe drop and sole thickness [59]. One study compared minimal versus nontraditional shoes [60] and another compared maximal versus traditional shoes [61], primarily differing in sole thickness. 3.2. Risk of bias in studies Table 2 presents the estimated risk of bias for each study, with an overall judgment ranging from low risk to some concerns, based on the RoB-2 tool. The primary sources of concern were identified as the absence of power analyses and effect sizes, potential carry-over effects due to missing shoe familiarization sessions, and the lack of shoe blinding. Confounding factors, specifically habitual foot strike patterns and unreported heel-to-toe drop and/or shoe mass, were also repeatedly detected as sources of potential bias. 3.3. Sample size and characteristics An overview of the sample size and characteristics is presented in Table 3. Four studies performed a priori power calculations [50–53]. The sample size ranged from 5 to 31 participants, with a mean of 15.4 ± 6.7 across the 14 studies, totaling 216 participants (87% male, 13% female). Mean age was 27.8 ± 6.7 years, with ranges from 20 to 35.8 years. Participant height (mean 1.76 ± 0.05 m) and mass (68.9 ± 6.8 kg) were reported in most studies. Expertise level definitions varied: six studies classified participants as "recreational runners" [51– 54,56,57], with two specifying weekly mileage thresholds, while others described participants as "physically active" [48,55], “regular” [59] or “experienced” [58] based on mileage or running history. Eight studies controlled footstrike pattern [52–55,57,59,61], with seven including only rearfoot strikers and one including non-rearfoot strikers [50]. 3.4. Running shoe characteristics An overview of the characteristics of the tested running shoes is presented in Table 4. The studies compared between two and 16 shoes, with 12 using experiment-specific shoes [49,51–53,55–62]. Sole thickness was measured at the midsole [49,54,57], heel [48,56], or both [50–53,55,58–61]. The heel-to-toe drop was reported in most studies, varying between 0 and 12 mm. Eight studies reported shoe mass [49–53,56,57], with two normalizing masses by attaching weights on shoes [56,57]. Most studies (n = 10) reported shoe material characteristics, such as hardness [48,52–55,59,60] or bending stiffness energy return, and cushioning [49,51,56]. Four studies tested carbon-infused soles [49,51,56,58]. 3.5. Study design Study designs are summarized in Table 5. All but one study consisted of a single measurement session; this one [52] had three sessions on different days. 3.5.1. Warm-up and shoe familiarization All studies included either a warm-up or a shoe familiarization session, with some using both [49,54,58]. Warm-up durations ranged from 5 to 10 minutes [49,50,54,58,59,61], with running speeds either self-selected [49,50,54,58,59] or at an easy pace [61]. Shoe familiarization durations varied (e.g., 2:40–5 minutes, or 5 trials). One study used standardized warm-up shoes [56], while seven studies stated that the participants wore their own shoes during warm-up [49,50,52–54,58,59]. 3.5.2. Running protocol Measurements were taken either on a treadmill [52–54,56,58–60] or during overground running [48– 51,55,57,61], with one overground study taking place outdoors on concrete [49]. Treadmill durations ranged from 1 to 30 minutes [52–54,56,58–60], and overground runs were typically 10–40 meters, with 5 valid trials recorded [48,50,55,57,61]. Running speeds ranged from 2.4 to 5 m/s [48,50– 53,55,57–60], although four studies did not report speed [49,54,56,61]. All studies used randomized or parallelized orders, and two used blinded designs [52,53]. Most studies allowed breaks between conditions, ranging from 2 to 10 minutes [49,50,56,58,59] or based on participant needs [53,54,57,60]. 3.6. Data recording and analysis Data recording and analysis methods are detailed in Table 6. Most studies (n = 12) used motion capturing with infrared cameras for kinematic data [48,50–58,60,61], while two also used accelerometers [52,53]. Timing gates were used to control running speed in six studies [48,50,51,55,57,61]. Force measurements were taken in eight studies using force plates [48,50,51,55,57,61] or an instrumented treadmill [54,56]. Most studies (n = 11) used a Butterworth low-pass filter (2nd or 4th order, 8-50 Hz). Step detection was based on a threshold for force data [50,51,54,56,57] or kinematics [52,53,58], while six studies did not report step detection methods [48,49,55,59–61]. The spatiotemporal, kinematic, and kinetic parameters analyzed varied across studies (see Table 7). Stance time was the most frequently analyzed parameter (n = 8, [49,50,52–56,59]), followed by step/stride frequency (n = 5, [49,54,56,58,59] and stride length (n = 3, [49,54,56]). Duty factor [58,59] and flight time [49,59] were each analyzed in two studies, and detrended fluctuation of stride time [58], ratio of braking to propulsion duration [58], time to complete the turn task [51], and running speed [49] were analyzed in one study each. For kinematics calculations, eight studies used a lower body model [51–53,55–57,60,61], while two studies used an ankle model [48,54], and another two employed a full body model [50,58]. The remaining two studies did not conduct kinematic analyses [49,59]. Only two studies [55,58] explicitly stated which kinematic model was used. Joint kinematics were the most common focus, particularly ankle and foot mechanics in the sagittal plane (n = 11, foot strike angle/index [50,52,54,55,57,59], discrete sagittal angles [52,53,55–57,61], time series [58] or stability of the angles based on maximum Lyapunov exponent (MLE) [60]). Knee and hip mechanics were analyzed in eight [50,52,53,55– 58,60] and five [50,55,56,58,60] studies, respectively. Frontal plane movements were investigated in six studies [51–53,56,58,61], with ankle frontal angle analyzed in all. Other parameters included tibialis movements [52,53,55], head acceleration [52,53], dynamic stability of body segments based on MLE [58], center of mass [49–51,58], and leg/global stiffness [49,55,58,59] or joint (ankle and knee) stiffness [55,57]. GRF was analyzed in six studies [49,51,54,55,57,61], and joint moment/work in three [48,50,55]. Running economy was assessed in one study [56]. 3.7. Statistical analysis The majority of studies [50–58,61] used repeated measures ANOVA/Friedman tests for shoe comparisons, with post-hoc tests in most cases either with [50,51,54,56–58,61] or without [52,53,55] corrections for multiple tests. Other methods included a mixed general linear model [60]; Spearman correlations [59]; principal component analysis and clustering [49]. Only five studies reported effect sizes [52,54,57,58,61]. 3.8. Outcomes In the following sections, shoes are abbreviated as “S” followed by their heel thickness in mm (e.g., S3 for shoes with a heel thickness of 3 mm). If heel thickness was not reported, midsole thickness is used instead and marked with an asterisk (e.g., S25* for shoes with a midsole thickness of 25 mm). 3.8.1. Spatiotemporal Stance time was longer for thicker soles in five studies, although not all pairwise shoe comparisons were significant [50,52–55]. Chambon et al. [55] found that S16 resulted in a longer stance than S0, while Law et al. [54] observed longer stance times for S9*, S21*, S25*, and S29* compared to S1*. TenBroek et al. found that S14 and S24 led to longer stance than S3 in a 6-min run [53], while S24 resulted in a longer stance time than both S3 and S14 in a 30-min run [52]. Conversely, Barrons et al. [56] found no significant difference between shoes. Horvais & Samozino [59] found no correlations between heel thickness and stance time. Koegel et al. [49] conducted a clustering analysis to classify runners based on their responses to different shoes and found that participants were grouped into three distinct clusters, each exhibiting unique response patterns to increasing sole thickness. Stride frequency, normalized to leg length, was higher in S50 compared to S35 at 4.2 m/s but not at 2.8 m/s [58]. Barrons et al. [56] and Law et al. [54] found no significant differences in stride frequency, and Horvais & Samozino [59] reported no significant correlations with heel thickness. Koegel et al. [49] found that step frequency had the smallest contribution to forming runner clusters and, therefore, did not analyze its variation across shoes and clusters in detail. Stride length showed no significant differences between shoes [54,56]. Koegel et al. [49] did not analyze stride length in detail due to its small contribution to cluster formation. Duty factor showed no difference between shoes in Kettner et al. [58], and there was no significant correlation with heel thickness in Horvais & Samozino [59]. Flight time also showed no significant correlations with heel thickness [59]. Other parameters, including detrended fluctuation of stride time [58], ratio of braking to propulsion duration [58], or time to complete the turn task [51] did not show any significant differences between shoes. Koegel et al. [49] found no significant differences in running speed across clusters. 3.8.2. Joint kinematics in the sagittal plane Three studies [52,53,61] reported greater ankle dorsiflexion at IC with thicker soles, though not all comparisons were significant. Hannigan & Pollard [61] found more dorsiflexion with S22 than S10. TenBroek et al. [53] observed greater dorsiflexion with S14 and S24 compared to S3, and their second study [52] found greater dorsiflexion with S24 than S3 and S14. Barrons et al. [55,56] found no significant differences. Law et al. [54] reported a higher foot strike angle, indicating a stronger rearfoot strike pattern with S25* compared to S1*, while Horvais & Samozino [59] reported a positive correlation between sole thickness and foot strike angle. Zhang et al. [57] found lower foot strike angles with S42* and S54* than S30*. Chambon et al. [55] found no differences in foot strike angle. Two studies found no differences at toe off (TO) [56,61]. For peak dorsiflexion, Barrons et al. [56] reported lower values with S50 than S35 and S40, while Miyazaki et al. [50] reported higher values with S35 than S24. Hannigan & Pollard [61] found no differences. Zhang et al. [57] found the lowest dorsiflexion velocity with S54*. Three studies [55,57,61] examined ankle range of motion (ROM) during stance, but only Hannigan & Pollard [61] reported significant differences. Kettner et al. [58] found no significant differences in the sagittal ankle angle time series. Frank et al. [60] reported no significant shoe effects on dynamic stability of the sagittal ankle angle. The sagittal knee angle at IC showed mixed results [52,53,55,56]. TenBroek et al. [53] found more knee flexion with S14 than S24, while their other study [52] reported more knee flexion with S14 and S24 than S3. Barrons et al. [56] and Chambon et al. [55] detected no significant effects. Two studies [54,56] found no differences in peak knee flexion, and Zhang et al. [57] reported no effects on knee flexion velocity. Two studies found differences in knee ROM [52,53], while two others found no effects [55,57]. Kettner et al. [58] reported no differences in the sagittal knee angle time series. Frank et al. [60] found no differences in dynamic stability of the sagittal knee angle. No differences in sagittal hip angle at IC [55,56] or TO [56] were reported. Hip ROM during stance [55] and the entire hip angle time series [58] showed no significant differences. Frank et al. [60] found no differences in dynamic stability of the sagittal hip angle. The sagittal thigh angle at IC showed mixed results. S14 and S24 led to greater thigh flexion than S3 in one study [52], while only S14 resulted in more flexion in another [53]. 3.8.3. Joint kinematics in the frontal plane Four studies [52,53,58,61] reported no significant differences in ankle angles at IC across shoe conditions. Three studies [56,58,61] found a trend toward greater eversion with thicker soles, though not all pairwise comparisons were significant. Barrons et al. [56] found greater peak eversion with S45 than S35. Hannigan & Pollard [61] reported higher peak eversion with S33 than S22. Kettner et al. [58] detected higher peak eversion with S50 than S35. TenBroek et al. [52] found lower peak eversion with S24 compared to S3 and S14. Barrons et al. [51] reported no significant differences in peak inversion or frontal angles during running turns. Foot ROM in the frontal plane showed no significant differences in two studies [53,61], while TenBroek et al. [52] found greater ROM with S14 than S24. Eversion duration was greater with thicker soles in Kettner et al. [58] (S50 > S35) and in Hannigan & Pollard [61] (S33 > S10 and S33 > S22). Kettner et al. [58] also reported greater foot inversion with S35 than S50 and found no differences in knee and hip frontal angle time series. 3.8.4. Segment kinematics TenBroek et al. [52,53] found reduced tibial internal rotation ROM with thicker soles (S14 < S3, S24 < S3). Chambon et al. [55] found no shoe effects on tibial peak acceleration, while TenBroek et al. [52,53] reported lower tibial peak accelerations with thicker soles. Thicker soles also resulted in lower peak head accelerations (S24 < S3 in two studies [52,53]: S24 < S14 in one study, S14 < S3 in the other [52]). The transfer function, which evaluated shock attenuation using head and tibial accelerations, showed no shoe effects. Finally, Kettner et al. [58] found no significant differences in the dynamic local stability of head, trunk, hip, or foot segments. 3.8.5. Center of mass movement Kettner et al. [58] found higher vertical center of mass (COM) oscillation with thicker soles (S50 > S35), while Miyazaki et al. [50] detected no significant differences. Koegel et al. [49] observed that vertical COM oscillation was the second most influential factor in forming clusters, with different response patterns to increasing sole thickness. Barrons et al. [51] found no significant shoe effects on peak COM velocities during running turns. 3.8.6. Stiffness Zhang et al. [57] reported the highest ankle and knee stiffness with the thickest sole (S54* > S40* and S54* > S30*), while Chambon et al. [55] found no significant effects. Leg stiffness was unaffected by shoe conditions in Kettner et al. [58], whereas Horvais & Samozino [59] found lower leg stiffness with greater heel thickness. Koegel et al. [49] reported that vertical stiffness was the most influential factor in their clustering analysis, with varied responses to increasing sole thickness. 3.8.7. Joint kinetics and energetics Reinschmidt & Nigg [48] found that each 10 mm increase in heel thickness increased the maximum plantarflexion moment by 6.3 Nm. In contrast, Chambon et al. [55] found no significant effects on maximum plantarflexion, knee flexion, or hip flexion moments. Miyazaki et al. [50] found that S35 led to higher peak plantar torque, positive ankle work and negative knee work compared to S24. 3.8.8. Ground reaction forces Three out of four studies found lower vertical GRF loading rates with thicker soles, though not all comparisons were significant. Hannigan & Pollard [61] and Law et al. [54] reported lower loading rates for thicker soles (Table 7). Zhang et al. [57] found higher loading rates with the thickest sole (S54* > S40* and S54* > S30*). Peak vertical GRF showed no significant differences in three studies [51,55,61], while Barrons et al. [51] found lower peak propulsive GRF with S50 during running turns. 3.8.9. Running economy and effective leg length Barrons et al. [56] reported no effects on average VO2 or energetic cost. However, they reported increased effective leg length for thicker soles in most comparisons, with significant increases in leg length at IC, mid-stance, and TO for thicker soles (e.g., S50 > S35, S50 > S40). 4. Discussion To date, no review has specifically investigated the isolated effects of shoe sole thickness on running biomechanics and economy. This systematic review aims to address this gap by examining how sole thickness impacts spatiotemporal variables, kinematics, kinetics, and running economy. This review of 14 studies revealed a consistent trend of longer stance times with thicker soles, although other spatiotemporal parameters showed no clear pattern. Thicker soles generally resulted in greater dorsiflexion at IC in the sagittal plane, with fewer effects on knee and hip kinematics. In the frontal plane, there was a weaker trend toward greater peak eversion with thicker soles. Joint kinetics, stiffness parameters, and COM movement showed no clear trends. While vertical GRF peaks remained largely unchanged, the loading rate tended to decrease with increasing sole thickness. Running economy, examined in only one study, showed no significant effects of shoe thickness. 4.1. Outcomes 4.1.1. Spatiotemporal Stance time tended to increase with thicker soles [50,52–55], typically when the thickness difference was ≥ 8 mm, though not all increases led to significant changes [50,52–56]. The increase in stance time with thicker soles may be attributed to the time required for midsole material deformation—the greater the amount of material, the longer the deformation process, leading to an extended stance phase [55]. However, this increase in stance time did not correspond to modulated leg stiffness [55,59], as one might expect [55,63]. One study found no significant difference in stance time despite a 15 mm thickness difference [56], likely due to the greater compliance (i.e., deformation under load) in AFT shoes [7]. Interestingly, longer stance times with thicker soles did not translate into changes in step frequency or stride length [54]. However, it should be noted that only two studies compared stance time alongside other spatiotemporal parameters across different shoes [54,56]. 4.1.2. Joint and segment kinematics The most notable shoe effects were observed in sagittal ankle kinematics, particularly an increase in dorsiflexion at IC with thicker soles [52,53,61]. In contrast, the effects on knee and hip kinematics were inconsistent and less pronounced across studies [52,53,55,56]. This discrepancy may be explained by the fact that shoe modifications directly influence the ankle joint, leading to compensatory adjustments being made primarily at the ankle rather than at the knee or hip. Despite the lack of significant knee and hip joint angle changes, thicker soles still led to increased vertical oscillation of the COM [58], suggesting that the motor control system responded to differences in sole thickness, as COM regulation is a key aspect of running mechanics [64]. Findings on sagittal foot strike angle varied between studies. Law et al. [54] and Horvais & Samozino [59] observed a stronger rearfoot strike pattern (i.e., a higher foot strike angle) with increasing sole thickness, while Zhang et al. [57] found that participants tended to adopt a more midfoot strike pattern. These discrepancies may stem from the different ranges of sole thickness examined. In Law et al. [54] and Horvais & Samozino [59], sole thickness varied between 1–25 mm and 0–25 mm, respectively, whereas Zhang et al. [57] tested shoes with thicknesses ranging from 30–54 mm. This suggests that the relationship between foot strike angle and sole thickness may follow a U-shaped pattern, with peak modulation occurring around 30 mm. In the frontal plane, ankle kinematics at IC showed no significant differences between shoes. However, a tendency for greater peak eversion with thicker soles was observed [56,58,61], which has been interpreted as a sign of reduced ankle stability. That said, not all pairwise shoe comparisons were significant. For example, Barrons et al. [56] reported that S45 resulted in greater eversion than S35, but S50 did not differ from S35. Similarly, Hannigan & Pollard [61] found that S33 led to greater peak eversion than S22 but did not differ from S10. Therefore, generalizing these results as evidence of reduced ankle stability or increased injury risk with thicker soles would be premature. Lastly, analyzing non-sagittal kinematics is challenging due to modeling difficulties and measurement errors [65]. Differences across platforms (e.g., OpenSim vs. Anybody) [66] and calculation methods [67] make it hard to determine the most accurate model, so results should be interpreted carefully. 4.1.3. Center of mass The effects of sole thickness on vertical oscillation of the COM showed inconsistent results. Kettner et al. [58] found that a thicker sole (S50) led to greater vertical oscillation compared to a thinner sole (S35). However, Miyazaki et al. [50] reported no significant differences in vertical oscillation between different thicknesses. Koegel et al. [49] highlighted that vertical oscillation of the COM was influential in clustering runners based on their biomechanical responses to sole thickness, but the three identified clusters displayed distinct patterns of adaptation. These discrepancies may be attributed to differences in measurement techniques. Kettner et al. [58] used a full-body kinematic model with gold-standard motion capture, while Miyazaki et al. [50] used a lower-body model, which could explain the differing results. Use of a commercial wearable sensor, which has not been validated for measuring vertical COM oscillation, in Koegel et al. [49] introduces additional uncertainty. Given the importance of COM movement in running mechanics [64], further research with standardized methods is needed to confirm whether thicker soles consistently lead to increased vertical oscillation of the COM. 4.1.4. Stiffness The relationship between sole thickness and various biomechanical stiffness values (including ankle, knee, leg, and vertical stiffness) was inconsistent across studies, suggesting a complex interaction. These contradictions can be partially explained by differences in stiffness estimation methods. Zhang et al. [57] assessed ankle and knee stiffness using purely kinematic data and found that ankle stiffness increased with thicker soles (S54*> S42* > S30*), with knee stiffness also highest in the thickest sole. Conversely, Chambon et al. [55] incorporated both force and kinematic data and found no significant effect of sole thickness on ankle or knee stiffness. Using both kinetic and kinematic data, these authors reported no significant effects on vertical stiffness. However, Koegel et al. [49] estimated vertical stiffness using only kinematic data and found that it was a key factor in clustering runners into distinct response groups. Their study suggested that individual runners exhibit different adaptations to increasing sole thickness. These findings highlight the need for a standardized approach to measuring stiffness, as variations in methodology can lead to conflicting results. 4.1.5. Joint kinetics and energetics A few studies [48,50,55] investigated joint moments, torques, or work, and their findings varied. Reinschmidt & Nigg [48] reported an increased maximum plantarflexion moment with a temporal shift in the stance phase, though their small sample size and lack of foot strike pattern data limited the reliability of their results. Additionally, the different heel-to-toe drops of the shoes tested could have confounded the sole thickness effects [45]. On the other hand, Chambon et al. [55] tested shoes with a standardized heel-to-toe drop (0 mm) and found no significant effects of sole thickness on plantarflexion, knee flexion, or hip flexion moments. This suggests that the changes observed by Reinschmidt & Nigg [48] might have been influenced by the heel-to-toe drop rather than sole thickness. Miyazaki et al. [50] found that a thicker sole (S35 vs. S24) increased peak plantar torque, positive ankle work, and negative knee work, while decreasing peak knee extension torque. However, this study also involved varying heel-to-toe drops, complicating the attribution of effects solely to sole thickness. In summary, the effects of sole thickness on joint kinetics and energetics remain unclear due to the methodological differences and limited number of studies. 4.1.6. Ground reaction forces The loading rate of vertical GRF generally decreased with increased sole thickness [49,51,61], with one study finding no significant shoe effects [55]. This finding can be explained by the increased cushioning and reduced stiffness of the shoes [49,56]. GRF parameters are often analyzed to understand shock attenuation and potential injury risk. A systematic review suggested that runners with a history of stress fractures tend to have greater loading rates than those without prior running injuries [68]. However, a more recent study [69] argued that vertical loading rate is not directly associated with running injuries, making the protective role of thicker soles uncertain. 4.1.7. Running economy and leg length Running economy was investigated in only one study [56], which is surprising given the ongoing debate on the effects of sole thickness on performance. Some studies suggest that greater sole thickness increases effective leg length, which may enhance stride length and running economy [4]. However, not all studies support this hypothesis [5]. The findings of Barrons et al. [56] also contradicted this, as they observed an increase in estimated leg length with thicker soles, but this did not translate into longer stride length or improved running economy. 4.2. Measurement and reporting protocol of shoes World Athletics uses the term "sole thickness" [29] which is measured at both the forefoot and heel. In contrast, scientific studies often use the terms “midsole thickness” [50,70,71] or “stack height” [6,49,72,73], although they typically refer to the same feature. To maintain consistency with World Athletics regulations, this review uses the term "sole thickness". According to the latest World Athletics regulations [29], sole thickness should be measured at the center of the forefoot and the center of the heel, which are specifically defined as 12% and 75% of the internal shoe length, respectively. However, only one study explicitly reported where these measurements were taken [58]. Additionally, some studies reported only midsole thickness [49,54,57] or heel thickness [48,56], making it more difficult to interpret results due to missing information (e.g., heel-to-toe drop). Shoe mass can also be a confounding factor, depending on the difference in mass between tested shoes. A mass increase of 100 g has been shown to negatively impact running economy and performance, whereas a 50 g difference had no effect [74]. In studies where mass was explicitly reported, the difference between tested shoes was generally below 50 g. However, shoe mass was not reported in all studies [48,54,55,59–61], further complicating result interpretation. The material composition of shoe foam is another important factor influencing running economy and biomechanics [75]. However, not all reviewed studies explicitly stated which materials were used in the tested shoes [48,57–61]. For better transparency, future studies should report the full midsole geometry (including forefoot and heel thickness with precise measurement locations and heel-to-toe drop), shoe mass, and material composition. 4.3. Limitations and future directions 4.3.1. Shoes The shoes used in the reviewed studies mainly differed in sole thickness, with some studies also reporting slight variations in shoe mass [49–53,57,58]. Two studies accounted for mass differences by adding small weights to the shoes [56,57], while others did not match mass between shoes, making it challenging to fully isolate the effects of sole thickness. Additionally, in some studies, the heel-to-toe drop varied between shoes [50,52,53,57,60], which could have been another confounding factor influencing the results. Four studies involved AFT shoes. Given that these regulations came after the AFT era, further research on AFT shoes is needed to better understand how sole thickness interacts with other shoe features [7]. 4.3.2. Participants The studies reviewed primarily included recreational to experienced runners, with a notable underrepresentation of elite and novice runners. Additionally, most participants were habitual rearfoot strikers, and some studies did not control for this factor. To provide a more comprehensive understanding of the impact of sole thickness, future research should involve elite and novice runners, as well as other type of strikers. Most participants were male, with a mean height range of 1.69 to 1.81 m and mean mass between 58.3 and 73.6 kg. To ensure a more representative sample, future studies should include a broader range of participants, particularly females, and those outside typical height and mass ranges. 4.3.3. Study design Only four studies performed a priori power calculations to determine sample size, which may have limited the statistical power of their findings. The majority of studies (n = 13) were conducted in laboratory settings, using either a standard laboratory floor or a motorized treadmill for running tests (Table 5). However, since ground surface material and stiffness can affect running economy and biomechanics [76–78], future research should incorporate various surfaces (e.g., track or concrete) to better simulate real-life running conditions. Another limitation was the inconsistency in biomechanical modeling, with an overreliance on lower-body models: only two studies used full-body models (Table 5). Additionally, only two studies explicitly stated their kinematical model, making cross-study comparisons challenging. Another limitation was that most studies focused on a single joint degree of freedom, overlooking coordination of multiple degrees of freedom which is crucial for understanding motor control [79]. Recent literature suggests that individualized shoe design and development could be beneficial in the future [9]. Future research could explore more personalized approaches, such as clustering participants based on their response to specific shoe features [49]. Additionally, critical aspects such as running economy [80], muscle activity [81,82], movement coordination [83] remain underexplored in the literature. To provide a more comprehensive understanding of the effects of sole thickness, further studies should address these aspects. 5. Conclusion A review of 14 studies on the effects of running shoe sole thickness revealed consistent trends, including longer stance times, increased ankle dorsiflexion at IC, and a decreased loading rate of GRF with thicker soles. However, many other parameters—such as step frequency, knee kinematics, and stiffness—did not show consistent trends across studies. Shoe mass and heel-to-toe drop emerged as potential confounding factors that may have influenced the results. The sample demographics were limited, with a focus primarily on male recreational or experienced runners. Future research should aim to report shoe features more comprehensively and transparently, include a more diverse range of participants (e.g., female runners, forefoot strikers), and broaden the analysis to include aspects like running economy, muscle activity, and movement coordination. This would provide a more thorough understanding of the effects of sole thickness on running economy and biomechanics. Abbreviations AFT: Advanced footwear technologies COM: Center of mass IC: Initial contact GRF: Ground reaction force MLE: Maximum Lyapunov exponent PERSiST: Prisma in Exercise, Rehabilitation, Sport medicine and SporTs science PICO: Population, Intervention, Comparison, Outcome, and Study Design PRISMA: Preferred Reporting Items for Systematic Reviews and Meta-Analyses RoB-2: Cochrane risk of bias instrument tool ROM: Range of motion TO: Toe-off Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. 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Hamill J, Palmer C, Van Emmerik REA. Coordinative variability and overuse injury. Sports Medicine, Arthroscopy, Rehabilitation, Therapy & Technology. 2012;4:45. Tables Tables 1 to 7 are available in the Supplementary Files section. Additional Declarations The authors declare no competing interests. Supplementary Files Tables1t07.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6526264","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Systematic Review","associatedPublications":[],"authors":[{"id":447847599,"identity":"9262f233-d995-4c64-b103-c3cbb4b6fb4c","order_by":0,"name":"Kettner, Cagla","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9ElEQVRIiWNgGAWjYHACxgMMDAlQdkUCD4iSIKQHrIWHDcQ8k8DDQ5oWxjYgg5AW/vbjFw78YEiTs5fvPfi4cl6ajD0D88HbPHi0SJzJKTjYw5BjzMPGl2x4dlsO0GFsydb4tBgw5CQc4GGoSOxh4zGTbNxWAdTCYyaNVwv/m4SDfxgq6oFazH82zgFp4f+GX4tE+oHDPECreIC2MDY2gBzGw4ZXi8SNNwyHZQzSDHuO5RhLNhxL4+E5zGZsOQePFv7+9IcP31Qky7M3nzH82FCTbM/e3vwQaA4+wGMACgQkwIxXOQiwPyCoZBSMglEwCkY4AABzekMskTV4oQAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0003-4283-281X","institution":"BioMotion Center, Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany","correspondingAuthor":true,"prefix":"","firstName":"Cagla","middleName":"","lastName":"Kettner","suffix":""},{"id":447847835,"identity":"58ed54b2-8857-49a2-bc6d-c0236a14d3ce","order_by":1,"name":"Krapp, Felix","email":"","orcid":"","institution":"BioMotion Center, Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany","correspondingAuthor":false,"prefix":"","firstName":"Felix","middleName":"","lastName":"Krapp","suffix":""},{"id":447847836,"identity":"690be052-0a2e-4006-9949-955df4e0714e","order_by":2,"name":"Stein, Thorsten","email":"","orcid":"","institution":"BioMotion Center, Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany","correspondingAuthor":false,"prefix":"","firstName":"Thorsten","middleName":"","lastName":"Stein","suffix":""}],"badges":[],"createdAt":"2025-04-25 07:19:26","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-6526264/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6526264/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":82273282,"identity":"e1173da0-afdd-485b-a55c-4c2faa62b3f9","added_by":"auto","created_at":"2025-05-08 14:28:00","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":2190962,"visible":true,"origin":"","legend":"\u003cp\u003eFlow diagram of the systematic search. Adapted from PRISMA 2020 flow diagram template for\u003c/p\u003e\n\u003cp\u003esystematic reviews [39].\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-6526264/v1/77ce6d745e5221c39da5beda.png"},{"id":82274750,"identity":"6737c4d6-9b36-49ba-b2a2-685fba0c6682","added_by":"auto","created_at":"2025-05-08 14:36:04","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3251322,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6526264/v1/12ef7213-c0b5-4d69-a5c9-7dcbbbbf954d.pdf"},{"id":82273281,"identity":"f0d00ebe-23ed-4067-bba3-c073dbae5e5f","added_by":"auto","created_at":"2025-05-08 14:28:00","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":64333,"visible":true,"origin":"","legend":"","description":"","filename":"Tables1t07.docx","url":"https://assets-eu.researchsquare.com/files/rs-6526264/v1/551c06c322698e26ab4f03de.docx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eThe effects of shoe sole thickness on running biomechanics and economy: a systematic review\u003c/p\u003e","fulltext":[{"header":"Key points","content":"\u003col\u003e\n \u003cli\u003eThicker soles increase stance time and ankle dorsiflexion at initial contact but have largely inconsistent effects on other spatiotemporal parameters as well as joint kinematics.\u003c/li\u003e\n \u003cli\u003eThicker soles reduce vertical ground reaction force loading rate, but their impact on stiffness and running economy is unclear.\u003c/li\u003e\n \u003cli\u003eMethodological heterogeneity and limited participant diversity highlight the need for more inclusive and comprehensive research.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"1. Background","content":"\u003cp\u003eRunning shoes play a vital role in enhancing performance and reducing injury risk [1]. The complexity of modern running shoes, which incorporate multiple design elements, combined with the unique needs of different runner subgroups [1], makes determining the ideal shoe design challenging. Additional factors, such as habitual foot strike patterns [2] and running surface hardness [3], further complicate this process. Another challenge is the interaction of various design features, making it difficult to isolate their individual effects [4]. For example, incorporating a carbon plate in a shoe may require a thicker sole, increasing both the height and mass of the shoe. A systematic analysis of existing research is needed to evaluate the impact of specific shoe features on biomechanics and performance.\u003c/p\u003e\n\u003cp\u003eOne key design feature of running shoes is sole thickness, also referred to as midsole thickness or stack height [4\u0026ndash;7]. Since the 1970s running boom, shoe designs have substantially evolved [8]. Initially, cushioned shoes with thicker soles were developed to reduce vertical impact forces [8\u0026ndash;10]. In the early 2000s, athletes at Stanford University trained barefoot, observing more natural landing mechanics [8]. This led to the creation of minimalist shoes designed to mimic barefoot running with a thin sole. Despite evidence that barefoot running and minimalist shoes can reduce impact forces [11] and alter spatiotemporal parameters [12,13], no studies have demonstrated a reduction in injury risk with minimalist shoes [14\u0026ndash;16]. Some research has shown increased risk of overuse injuries when transitioning to minimalist shoes [17,18], although these injuries often seem to be linked to an abrupt transition rather than the shoes themselves.\u003c/p\u003e\n\u003cp\u003eIn the 2010s, alongside minimalist shoes, maximalist footwear emerged with Advanced Footwear Technology (AFT) designed to enhance performance [19,20]. The driver behind AFT development was the goal of breaking the two-hour marathon barrier, which was considered physiologically impossible by some experts and athletes [21\u0026ndash;23]. AFT shoes feature technological advancements like carbon plates or rods to optimize shoe bending stiffness and minimize energy loss at the joints [24,25]. These carbon elements are embedded in lightweight, thick midsole foam, providing cushioning and energy return [26]. Initially, World Athletics only regulated that the shoes must not offer unfair advantages and must be available to all athletes (Technical Rule 143.2, [27]). However, in 2020, World Athletics implemented rules limiting sole thickness to 40 mm and restricting rigid structures like carbon plates to a single element in the sole [28]. In 2022, regulations prohibited the use of intelligent technology in racing shoes [29].\u003c/p\u003e\n\u003cp\u003eAFT shoes are now widely used by runners of all skill levels [19,30,31]. Several studies have shown improvements in running economy with these shoes [19,32,33], though the benefits tend to decrease with lower skill levels [33,34]. Concerns about potential injuries, particularly for non-elite runners, are growing [31]. While multiple studies have examined the biomechanical effects of AFT shoes, there is still no clear understanding of how individual shoe features influence performance and injury risk [4,7,35,36]. Most research has compared different shoe models [26,33,37] rather than isolating specific design elements. A 2020 systematic review found limited studies on sole thickness, and their findings were inconclusive [38]. A more recent scoping review published in 2023 [9] analyzed various shoe features but did not focus on sole thickness. It found that while sole thickness influences vertical ground reaction forces (GRF), it does not affect foot and knee angles at initial contact. Similarly, a narrative review on postmodern running shoes [7] included sole thickness as a sub-group of midsole geometry but did not explore the underlying biomechanical changes. Both reviews emphasized the need to understand how individual AFT features affect runners\u0026apos; responses and how runner-specific characteristics influence those responses.\u003c/p\u003e\n\u003cp\u003eTo date, no review has specifically investigated the isolated effects of shoe sole thickness on running biomechanics and economy. This systematic review aims to fill this gap by investigating how sole thickness impacts spatiotemporal variables, kinematics, kinetics, and running economy.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cp\u003eThis systematic review was conducted and reported in accordance with the \u0026ldquo;Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020)\u0026rdquo; [39] and \u0026ldquo;Prisma in Exercise, Rehabilitation, Sport medicine and SporTs science (PERSiST)\u0026rdquo; Guidelines [40].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.1. Eligibility criteria\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAny type of observational or experimental study was eligible for inclusion, while reviews were excluded, as in similar systematic reviews [41,42] Only full-length articles or short communications were considered, with conference proceedings excluded due to insufficient study details. Study eligibility was determined using the Population, Intervention, Comparison, and Outcome (PICO) framework [40,43] as follows:\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePopulation: \u003c/em\u003eHealthy adult runners (aged 18\u0026ndash;65 years) were included. No exclusion criteria were applied regarding foot strike pattern or running expertise level (e.g., non-elite, experienced runners).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eIntervention: \u003c/em\u003eStudies assessing different running shoe conditions during running were included. Other tasks such as walking were excluded. No restrictions were applied regarding the running surface (e.g., treadmill or overground), running duration, distance, or speed.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eComparison: \u003c/em\u003eOnly studies specifically analyzing the effect of shoe sole thickness on running performance, spatiotemporal characteristics, kinematics, or kinetics were included. Comparisons of multiple design features (e.g., heel-to-toe drop, toe box width) and barefoot conditions were excluded.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eOutcome: \u003c/em\u003eStudies assessing running performance, spatiotemporal characteristics, kinematics, or kinetics were included.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2. Data sources and search strategy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA standardized electronic literature search was conducted using the following search term combinations: (\u0026ldquo;footwear\u0026rdquo; OR \u0026ldquo;shoes\u0026rdquo;) AND (\u0026ldquo;thickness\u0026rdquo; OR \u0026ldquo;stack height\u0026rdquo;) AND (\u0026ldquo;runn*\u0026rdquo; OR \u0026ldquo;jogg*\u0026rdquo;) AND (\u0026ldquo;biomechanic*\u0026rdquo; OR \u0026ldquo;econom*\u0026rdquo; OR \u0026ldquo;kinematic*\u0026rdquo; OR \u0026ldquo;spatio*\u0026rdquo; OR \u0026ldquo;kinetic*\u0026rdquo; OR \u0026ldquo;performance\u0026rdquo;). The literature search was conducted across three databases: Scopus, Web of Science, and PubMed. Additionally, a supplementary search was performed in \u003cem\u003eFootwear Science\u003c/em\u003e, following the approach recommended in previous reviews on running shoes [42,44]. The reference lists of relevant studies were also manually screened to identify any additional articles not captured through the database searches. Studies published up to 1 March 2025 were considered, and only articles published in English were included.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3. Selection and data collection process\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOne reviewer (FK) conducted the initial electronic search and removed duplicate records. Titles, abstracts, and full-text articles were independently screened for eligibility by two reviewers (CK and FK). Any disagreements were resolved by discussion, and if necessary, a third reviewer (TS) provided input to reach a consensus.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003e2.4. Data extraction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA data extraction form (Table 1) was developed based on previous systematic reviews in related areas and the PICO framework [38,40,41,45]. The extracted data included: research question, study design, description of the sample, details of the tested shoes, experimental and analysis protocol, and the outcomes of the study. Data were extracted independently by two reviewers (CK and FK) and compared for potential disagreements.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.5. Study risk of bias assessment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe risk of bias for each included study was independently assessed by two reviewers (CK and FK) using the Cochrane risk of bias instrument tool (RoB-2) [46], following the approach of similar running-related studies [47]. An extended version of RoB-2 for cross-over trials was applied, which included an additional domain addressing bias due to confounding factors. Within the domain \u003cem\u003ebias arising from the randomization process\u003c/em\u003e, the randomization of shoe allocation and the presence of a power calculation were examined. Confounding factors were defined as foot strike type, additional substantial variations in shoe features (e.g., heel-to-toe drop and mass), and the expertise level of the runners. \u003cem\u003eBias in measurement of the outcome \u003c/em\u003ewas evaluated by determining whether shoe blinding was implemented and whether validated devices were employed. The absence of a shoe familiarization session was considered a factor that could increase the \u003cem\u003ebias arising from period and carryover effects\u003c/em\u003e. Missing effect sizes or the absence of corrections for multiple post-hoc tests were considered potential sources of \u003cem\u003ebias in the selection of reported results\u003c/em\u003e. The risk of bias assessments were conducted independently by CK and FK. In instances where discrepancies arose between reviewers, consensus discussions were held to reach a final decision.\u003c/p\u003e"},{"header":"3. Results","content":"\u003cp\u003e\u003cstrong\u003e3.1. Search results and study selection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe initial search yielded 163 articles, which was reduced to 152 after removing duplicates (Fig. 1). Of these, 136 articles were screened, and 14 studies met the inclusion criteria (all cross-sectional). Eleven studies explicitly mentioned sole thickness in their title or research question [48\u0026ndash;58], while one study focused on midsole geometry, including both heel-to-toe drop and sole thickness [59]. One study compared minimal versus nontraditional shoes [60] and another compared maximal versus traditional shoes [61], primarily differing in sole thickness.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2. Risk of bias in studies\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 2 presents the estimated risk of bias for each study, with an overall judgment ranging from low risk to some concerns, based on the RoB-2 tool. The primary sources of concern were identified as the absence of power analyses and effect sizes, potential carry-over effects due to missing shoe familiarization sessions, and the lack of shoe blinding. Confounding factors, specifically habitual foot strike patterns and unreported heel-to-toe drop and/or shoe mass, were also repeatedly detected as sources of potential bias.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3. Sample size and characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAn overview of the sample size and characteristics is presented in Table 3. Four studies performed \u003cem\u003ea priori\u0026nbsp;\u003c/em\u003epower calculations [50\u0026ndash;53]. The sample size ranged from 5 to 31 participants, with a mean of 15.4 \u0026plusmn; 6.7 across the 14 studies, totaling 216 participants (87% male, 13% female). Mean age was 27.8 \u0026plusmn; 6.7 years, with ranges from 20 to 35.8 years. Participant height (mean 1.76 \u0026plusmn; 0.05 m) and mass (68.9 \u0026plusmn; 6.8 kg) were reported in most studies.\u003c/p\u003e\n\u003cp\u003eExpertise level definitions varied: six studies classified participants as \u0026quot;recreational runners\u0026quot; [51\u0026ndash; 54,56,57], with two specifying weekly mileage thresholds, while others described participants as \u0026quot;physically active\u0026quot; [48,55], \u0026ldquo;regular\u0026rdquo; [59] or \u0026ldquo;experienced\u0026rdquo; [58] based on mileage or running history. Eight studies controlled footstrike pattern [52\u0026ndash;55,57,59,61], with seven including only rearfoot strikers and one including non-rearfoot strikers [50].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4. Running shoe characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAn overview of the characteristics of the tested running shoes is presented in Table 4. The studies compared between two and 16 shoes, with 12 using experiment-specific shoes [49,51\u0026ndash;53,55\u0026ndash;62]. Sole thickness was measured at the midsole [49,54,57], heel [48,56], or both [50\u0026ndash;53,55,58\u0026ndash;61]. The heel-to-toe drop was reported in most studies, varying between 0 and 12 mm. Eight studies reported shoe mass [49\u0026ndash;53,56,57], with two normalizing masses by attaching weights on shoes [56,57]. Most studies (n = 10) reported shoe material characteristics, such as hardness [48,52\u0026ndash;55,59,60] or bending stiffness energy return, and cushioning [49,51,56]. Four studies tested carbon-infused soles [49,51,56,58].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.5. Study design\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStudy designs are summarized in Table 5. All but one study consisted of a single measurement session; this one [52] had three sessions on different days.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.5.1. Warm-up and shoe familiarization\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll studies included either a warm-up or a shoe familiarization session, with some using both [49,54,58]. Warm-up durations ranged from 5 to 10 minutes [49,50,54,58,59,61], with running speeds either self-selected [49,50,54,58,59] or at an easy pace [61]. Shoe familiarization durations varied (e.g., 2:40\u0026ndash;5 minutes, or 5 trials). One study used standardized warm-up shoes [56], while seven studies stated that the participants wore their own shoes during warm-up [49,50,52\u0026ndash;54,58,59].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.5.2. Running protocol\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMeasurements were taken either on a treadmill [52\u0026ndash;54,56,58\u0026ndash;60] or during overground running [48\u0026ndash; 51,55,57,61], with one overground study taking place outdoors on concrete [49]. Treadmill durations ranged from 1 to 30 minutes [52\u0026ndash;54,56,58\u0026ndash;60], and overground runs were typically 10\u0026ndash;40 meters, with 5 valid trials recorded [48,50,55,57,61]. Running speeds ranged from 2.4 to 5 m/s [48,50\u0026ndash; 53,55,57\u0026ndash;60], although four studies did not report speed [49,54,56,61]. All studies used randomized or parallelized orders, and two used blinded designs [52,53]. Most studies allowed breaks between conditions, ranging from 2 to 10 minutes [49,50,56,58,59] or based on participant needs [53,54,57,60].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.6. Data recording and analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData recording and analysis methods are detailed in Table 6. Most studies (n = 12) used motion capturing with infrared cameras for kinematic data [48,50\u0026ndash;58,60,61], while two also used accelerometers [52,53]. Timing gates were used to control running speed in six studies [48,50,51,55,57,61]. Force measurements were taken in eight studies using force plates [48,50,51,55,57,61] or an instrumented treadmill [54,56]. Most studies (n = 11) used a Butterworth low-pass filter (2nd or 4th order, 8-50 Hz). Step detection was based on a threshold for force data [50,51,54,56,57] or kinematics [52,53,58], while six studies did not report step detection methods [48,49,55,59\u0026ndash;61].\u003c/p\u003e\n\u003cp\u003eThe spatiotemporal, kinematic, and kinetic parameters analyzed varied across studies (see Table 7). Stance time was the most frequently analyzed parameter (n = 8, [49,50,52\u0026ndash;56,59]), followed by step/stride frequency (n = 5, [49,54,56,58,59] and stride length (n = 3, [49,54,56]). Duty factor [58,59] and flight time [49,59] were each analyzed in two studies, and detrended fluctuation of stride time [58], ratio of braking to propulsion duration [58], time to complete the turn task [51], and running speed [49] were analyzed in one study each.\u003c/p\u003e\n\u003cp\u003eFor kinematics calculations, eight studies used a lower body model [51\u0026ndash;53,55\u0026ndash;57,60,61], while two studies used an ankle model [48,54], and another two employed a full body model [50,58]. The remaining two studies did not conduct kinematic analyses [49,59]. Only two studies [55,58] explicitly stated which kinematic model was used. Joint kinematics were the most common focus, particularly ankle and foot mechanics in the sagittal plane (n = 11, foot strike angle/index [50,52,54,55,57,59], discrete sagittal angles [52,53,55\u0026ndash;57,61], time series [58] or stability of the angles based on maximum Lyapunov exponent (MLE) [60]). Knee and hip mechanics were analyzed in eight [50,52,53,55\u0026ndash; 58,60] and five [50,55,56,58,60] studies, respectively. Frontal plane movements were investigated in six studies [51\u0026ndash;53,56,58,61], with ankle frontal angle analyzed in all. Other parameters included\u003c/p\u003e\n\u003cp\u003etibialis movements [52,53,55], head acceleration [52,53], dynamic stability of body segments based on MLE [58], center of mass [49\u0026ndash;51,58], and leg/global stiffness [49,55,58,59] or joint (ankle and knee) stiffness [55,57]. GRF was analyzed in six studies [49,51,54,55,57,61], and joint moment/work in three [48,50,55]. Running economy was assessed in one study [56].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.7. Statistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe majority of studies [50\u0026ndash;58,61] used repeated measures ANOVA/Friedman tests for shoe comparisons, with \u003cem\u003epost-hoc\u0026nbsp;\u003c/em\u003etests in most cases either with [50,51,54,56\u0026ndash;58,61] or without [52,53,55] corrections for multiple tests. Other methods included a mixed general linear model [60]; Spearman correlations [59]; principal component analysis and clustering [49]. Only five studies reported effect sizes [52,54,57,58,61].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.8. Outcomes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the following sections, shoes are abbreviated as \u0026ldquo;S\u0026rdquo; followed by their heel thickness in mm (e.g., S3 for shoes with a heel thickness of 3 mm). If heel thickness was not reported, midsole thickness is used instead and marked with an asterisk (e.g., S25* for shoes with a midsole thickness of 25 mm).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.8.1. Spatiotemporal\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStance time was longer for thicker soles in five studies, although not all pairwise shoe comparisons were significant [50,52\u0026ndash;55]. Chambon et al. [55] found that S16 resulted in a longer stance than S0, while Law et al. [54] observed longer stance times for S9*, S21*, S25*, and S29* compared to S1*. TenBroek et al. found that S14 and S24 led to longer stance than S3 in a 6-min run [53], while S24 resulted in a longer stance time than both S3 and S14 in a 30-min run [52]. Conversely, Barrons et al. [56] found no significant difference between shoes. Horvais \u0026amp; Samozino [59] found no correlations between heel thickness and stance time. Koegel et al. [49] conducted a clustering analysis to classify runners based on their responses to different shoes and found that participants were grouped into three distinct clusters, each exhibiting unique response patterns to increasing sole thickness.\u003c/p\u003e\n\u003cp\u003eStride frequency, normalized to leg length, was higher in S50 compared to S35 at 4.2 m/s but not at 2.8 m/s [58]. Barrons et al. [56] and Law et al. [54] found no significant differences in stride frequency, and Horvais \u0026amp; Samozino [59] reported no significant correlations with heel thickness. Koegel et al. [49] found that step frequency had the smallest contribution to forming runner clusters and, therefore, did not analyze its variation across shoes and clusters in detail.\u003c/p\u003e\n\u003cp\u003eStride length showed no significant differences between shoes [54,56]. Koegel et al. [49] did not analyze stride length in detail due to its small contribution to cluster formation.\u003c/p\u003e\n\u003cp\u003eDuty factor showed no difference between shoes in Kettner et al. [58], and there was no significant correlation with heel thickness in Horvais \u0026amp; Samozino [59]. Flight time also showed no significant correlations with heel thickness [59].\u003c/p\u003e\n\u003cp\u003eOther parameters, including detrended fluctuation of stride time [58], ratio of braking to propulsion duration [58], or time to complete the turn task [51] did not show any significant differences between shoes. Koegel et al. [49] found no significant differences in running speed across clusters.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.8.2. Joint kinematics in the sagittal plane\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThree studies [52,53,61] reported greater ankle dorsiflexion at IC with thicker soles, though not all comparisons were significant. Hannigan \u0026amp; Pollard [61] found more dorsiflexion with S22 than S10. TenBroek et al. [53] observed greater dorsiflexion with S14 and S24 compared to S3, and their second study [52] found greater dorsiflexion with S24 than S3 and S14. Barrons et al. [55,56] found no significant differences. Law et al. [54] reported a higher foot strike angle, indicating a stronger rearfoot strike pattern with S25* compared to S1*, while Horvais \u0026amp; Samozino [59] reported a positive correlation between sole thickness and foot strike angle. Zhang et al. [57] found lower foot strike angles with S42* and S54* than S30*. Chambon et al. [55] found no differences in foot strike angle. Two studies found no differences at toe off (TO) [56,61].\u003c/p\u003e\n\u003cp\u003eFor peak dorsiflexion, Barrons et al. [56] reported lower values with S50 than S35 and S40, while Miyazaki et al. [50] reported higher values with S35 than S24. Hannigan \u0026amp; Pollard [61] found no differences. Zhang et al. [57] found the lowest dorsiflexion velocity with S54*. Three studies [55,57,61] examined ankle range of motion (ROM) during stance, but only Hannigan \u0026amp; Pollard [61] reported significant differences. Kettner et al. [58] found no significant differences in the sagittal ankle angle time series. Frank et al. [60] reported no significant shoe effects on dynamic stability of the sagittal ankle angle.\u003c/p\u003e\n\u003cp\u003eThe sagittal knee angle at IC showed mixed results [52,53,55,56]. TenBroek et al. [53] found more knee flexion with S14 than S24, while their other study [52] reported more knee flexion with S14 and S24 than S3. Barrons et al. [56] and Chambon et al. [55] detected no significant effects. Two studies [54,56] found no differences in peak knee flexion, and Zhang et al. [57] reported no effects on knee flexion velocity. Two studies found differences in knee ROM [52,53], while two others found no effects [55,57]. Kettner et al. [58] reported no differences in the sagittal knee angle time series. Frank et al. [60] found no differences in dynamic stability of the sagittal knee angle.\u003c/p\u003e\n\u003cp\u003eNo differences in sagittal hip angle at IC [55,56] or TO [56] were reported. Hip ROM during stance [55] and the entire hip angle time series [58] showed no significant differences. Frank et al. [60] found no differences in dynamic stability of the sagittal hip angle.\u003c/p\u003e\n\u003cp\u003eThe sagittal thigh angle at IC showed mixed results. S14 and S24 led to greater thigh flexion than S3 in one study [52], while only S14 resulted in more flexion in another [53].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.8.3. Joint kinematics in the frontal plane\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFour studies [52,53,58,61] reported no significant differences in ankle angles at IC across shoe conditions. Three studies [56,58,61] found a trend toward greater eversion with thicker soles, though not all pairwise comparisons were significant. Barrons et al. [56] found greater peak eversion with S45 than S35. Hannigan \u0026amp; Pollard [61] reported higher peak eversion with S33 than S22. Kettner et al. [58] detected higher peak eversion with S50 than S35. TenBroek et al. [52] found lower peak eversion with S24 compared to S3 and S14. Barrons et al. [51] reported no significant differences in peak inversion or frontal angles during running turns.\u003c/p\u003e\n\u003cp\u003eFoot ROM in the frontal plane showed no significant differences in two studies [53,61], while TenBroek et al. [52] found greater ROM with S14 than S24. Eversion duration was greater with thicker soles in Kettner et al. [58] (S50 \u0026gt; S35) and in Hannigan \u0026amp; Pollard [61] (S33 \u0026gt; S10 and S33 \u0026gt; S22). Kettner et al. [58] also reported greater foot inversion with S35 than S50 and found no differences in knee and hip frontal angle time series.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.8.4. Segment kinematics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTenBroek et al. [52,53] found reduced tibial internal rotation ROM with thicker soles (S14 \u0026lt; S3, S24 \u0026lt; S3). Chambon et al. [55] found no shoe effects on tibial peak acceleration, while TenBroek et al. [52,53] reported lower tibial peak accelerations with thicker soles. Thicker soles also resulted in lower peak head accelerations (S24 \u0026lt; S3 in two studies [52,53]: S24 \u0026lt; S14 in one study, S14 \u0026lt; S3 in the other [52]). The transfer function, which evaluated shock attenuation using head and tibial accelerations, showed no shoe effects. Finally, Kettner et al. [58] found no significant differences in the dynamic local stability of head, trunk, hip, or foot segments.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.8.5. Center of mass movement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eKettner et al. [58] found higher vertical center of mass (COM) oscillation with thicker soles (S50 \u0026gt; S35), while Miyazaki et al. [50] detected no significant differences. Koegel et al. [49] observed that vertical COM oscillation was the second most influential factor in forming clusters, with different\u003c/p\u003e\n\u003cp\u003eresponse patterns to increasing sole thickness. Barrons et al. [51] found no significant shoe effects on peak COM velocities during running turns.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.8.6. Stiffness\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eZhang et al. [57] reported the highest ankle and knee stiffness with the thickest sole (S54* \u0026gt; S40* and S54* \u0026gt; S30*), while Chambon et al. [55] found no significant effects. Leg stiffness was unaffected by shoe conditions in Kettner et al. [58], whereas Horvais \u0026amp; Samozino [59] found lower leg stiffness with greater heel thickness. Koegel et al. [49] reported that vertical stiffness was the most influential factor in their clustering analysis, with varied responses to increasing sole thickness.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.8.7. Joint kinetics and energetics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eReinschmidt \u0026amp; Nigg [48] found that each 10 mm increase in heel thickness increased the maximum plantarflexion moment by 6.3 Nm. In contrast, Chambon et al. [55] found no significant effects on maximum plantarflexion, knee flexion, or hip flexion moments. Miyazaki et al. [50] found that S35 led to higher peak plantar torque, positive ankle work and negative knee work compared to S24.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.8.8. Ground reaction forces\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThree out of four studies found lower vertical GRF loading rates with thicker soles, though not all comparisons were significant. Hannigan \u0026amp; Pollard [61] and Law et al. [54] reported lower loading rates for thicker soles (Table 7). Zhang et al. [57] found higher loading rates with the thickest sole (S54* \u0026gt; S40* and S54* \u0026gt; S30*). Peak vertical GRF showed no significant differences in three studies [51,55,61], while Barrons et al. [51] found lower peak propulsive GRF with S50 during running turns.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.8.9. Running economy and effective leg length\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBarrons et al. [56] reported no effects on average VO2 or energetic cost. However, they reported increased effective leg length for thicker soles in most comparisons, with significant increases in leg length at IC, mid-stance, and TO for thicker soles (e.g., S50 \u0026gt; S35, S50 \u0026gt; S40).\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eTo date, no review has specifically investigated the isolated effects of shoe sole thickness on running biomechanics and economy. This systematic review aims to address this gap by examining how sole thickness impacts spatiotemporal variables, kinematics, kinetics, and running economy. This review of 14 studies revealed a consistent trend of longer stance times with thicker soles, although other spatiotemporal parameters showed no clear pattern. Thicker soles generally resulted in greater dorsiflexion at IC in the sagittal plane, with fewer effects on knee and hip kinematics. In the frontal plane, there was a weaker trend toward greater peak eversion with thicker soles. Joint kinetics, stiffness parameters, and COM movement showed no clear trends. While vertical GRF peaks remained largely unchanged, the loading rate tended to decrease with increasing sole thickness. Running economy, examined in only one study, showed no significant effects of shoe thickness.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.1. Outcomes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.1.1. Spatiotemporal\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStance time tended to increase with thicker soles [50,52\u0026ndash;55], typically when the thickness difference was \u0026ge; 8 mm, though not all increases led to significant changes [50,52\u0026ndash;56]. The increase in stance time with thicker soles may be attributed to the time required for midsole material deformation\u0026mdash;the greater the amount of material, the longer the deformation process, leading to an extended stance phase [55]. However, this increase in stance time did not correspond to modulated leg stiffness [55,59], as one might expect [55,63]. One study found no significant difference in stance time despite a 15 mm thickness difference [56], likely due to the greater compliance (i.e., deformation under load) in AFT shoes [7].\u003c/p\u003e\n\u003cp\u003eInterestingly, longer stance times with thicker soles did not translate into changes in step frequency or stride length [54]. However, it should be noted that only two studies compared stance time alongside other spatiotemporal parameters across different shoes [54,56].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.1.2. Joint and segment kinematics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe most notable shoe effects were observed in sagittal ankle kinematics, particularly an increase in dorsiflexion at IC with thicker soles [52,53,61]. In contrast, the effects on knee and hip kinematics were inconsistent and less pronounced across studies [52,53,55,56]. This discrepancy may be explained by the fact that shoe modifications directly influence the ankle joint, leading to compensatory adjustments being made primarily at the ankle rather than at the knee or hip. Despite the lack of significant knee and hip joint angle changes, thicker soles still led to increased vertical oscillation of the COM [58], suggesting that the motor control system responded to differences in sole thickness, as COM regulation is a key aspect of running mechanics [64].\u003c/p\u003e\n\u003cp\u003eFindings on sagittal foot strike angle varied between studies. Law et al. [54] and Horvais \u0026amp; Samozino [59] observed a stronger rearfoot strike pattern (i.e., a higher foot strike angle) with increasing sole thickness, while Zhang et al. [57] found that participants tended to adopt a more midfoot strike pattern. These discrepancies may stem from the different ranges of sole thickness examined. In Law et al. [54] and Horvais \u0026amp; Samozino [59], sole thickness varied between 1\u0026ndash;25 mm and 0\u0026ndash;25 mm, respectively, whereas Zhang et al. [57] tested shoes with thicknesses ranging from 30\u0026ndash;54 mm. This suggests that the relationship between foot strike angle and sole thickness may follow a U-shaped pattern, with peak modulation occurring around 30 mm.\u003c/p\u003e\n\u003cp\u003eIn the frontal plane, ankle kinematics at IC showed no significant differences between shoes. However, a tendency for greater peak eversion with thicker soles was observed [56,58,61], which has been interpreted as a sign of reduced ankle stability. That said, not all pairwise shoe comparisons were significant. For example, Barrons et al. [56] reported that S45 resulted in greater eversion than S35, but S50 did not differ from S35. Similarly, Hannigan \u0026amp; Pollard [61] found that S33 led to greater peak eversion than S22 but did not differ from S10. Therefore, generalizing these results as evidence of reduced ankle stability or increased injury risk with thicker soles would be premature.\u003c/p\u003e\n\u003cp\u003eLastly, analyzing non-sagittal kinematics is challenging due to modeling difficulties and measurement errors [65]. Differences across platforms (e.g., OpenSim vs. Anybody) [66] and calculation methods [67] make it hard to determine the most accurate model, so results should be interpreted carefully.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.1.3. Center of mass\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe effects of sole thickness on vertical oscillation of the COM showed inconsistent results. Kettner et al. [58] found that a thicker sole (S50) led to greater vertical oscillation compared to a thinner sole (S35). However, Miyazaki et al. [50] reported no significant differences in vertical oscillation between different thicknesses. Koegel et al. [49] highlighted that vertical oscillation of the COM was influential in clustering runners based on their biomechanical responses to sole thickness, but the three identified clusters displayed distinct patterns of adaptation. These discrepancies may be attributed to differences in measurement techniques. Kettner et al. [58] used a full-body kinematic model with gold-standard motion capture, while Miyazaki et al. [50] used a lower-body model, which could explain the differing results. Use of a commercial wearable sensor, which has not been validated for measuring vertical COM oscillation, in Koegel et al. [49] introduces additional uncertainty. Given the importance of COM movement in running mechanics [64], further research with standardized methods is needed to confirm whether thicker soles consistently lead to increased vertical oscillation of the COM.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.1.4. Stiffness\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe relationship between sole thickness and various biomechanical stiffness values (including ankle, knee, leg, and vertical stiffness) was inconsistent across studies, suggesting a complex interaction. These contradictions can be partially explained by differences in stiffness estimation methods. Zhang et al. [57] assessed ankle and knee stiffness using purely kinematic data and found that ankle stiffness increased with thicker soles (S54*\u0026gt; S42* \u0026gt; S30*), with knee stiffness also highest in the thickest sole. Conversely, Chambon et al. [55] incorporated both force and kinematic data and found no significant effect of sole thickness on ankle or knee stiffness. Using both kinetic and kinematic data, these authors reported no significant effects on vertical stiffness. However, Koegel et al. [49] estimated vertical stiffness using only kinematic data and found that it was a key factor in clustering runners into distinct response groups. Their study suggested that individual runners exhibit different adaptations to increasing sole thickness. These findings highlight the need for a standardized approach to measuring stiffness, as variations in methodology can lead to conflicting results.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.1.5. Joint kinetics and energetics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA few studies [48,50,55] investigated joint moments, torques, or work, and their findings varied. Reinschmidt \u0026amp; Nigg [48] reported an increased maximum plantarflexion moment with a temporal shift in the stance phase, though their small sample size and lack of foot strike pattern data limited the reliability of their results. Additionally, the different heel-to-toe drops of the shoes tested could have confounded the sole thickness effects [45]. On the other hand, Chambon et al. [55] tested shoes with a standardized heel-to-toe drop (0 mm) and found no significant effects of sole thickness on plantarflexion, knee flexion, or hip flexion moments. This suggests that the changes observed by Reinschmidt \u0026amp; Nigg [48] might have been influenced by the heel-to-toe drop rather than sole thickness. Miyazaki et al. [50] found that a thicker sole (S35 vs. S24) increased peak plantar torque, positive ankle work, and negative knee work, while decreasing peak knee extension torque. However, this study also involved varying heel-to-toe drops, complicating the attribution of effects solely to sole thickness. In summary, the effects of sole thickness on joint kinetics and energetics remain unclear due to the methodological differences and limited number of studies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.1.6. Ground reaction forces\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe loading rate of vertical GRF generally decreased with increased sole thickness [49,51,61], with one study finding no significant shoe effects [55]. This finding can be explained by the increased cushioning and reduced stiffness of the shoes [49,56]. GRF parameters are often analyzed to understand shock attenuation and potential injury risk. A systematic review suggested that runners with a history of stress fractures tend to have greater loading rates than those without prior running injuries [68]. However, a more recent study [69] argued that vertical loading rate is not directly associated with running injuries, making the protective role of thicker soles uncertain.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.1.7. Running economy and leg length\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRunning economy was investigated in only one study [56], which is surprising given the ongoing debate on the effects of sole thickness on performance. Some studies suggest that greater sole thickness increases effective leg length, which may enhance stride length and running economy [4]. However, not all studies support this hypothesis [5]. The findings of Barrons et al. [56] also contradicted this, as they observed an increase in estimated leg length with thicker soles, but this did not translate into longer stride length or improved running economy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.2. Measurement and reporting protocol of shoes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWorld Athletics uses the term \u0026quot;sole thickness\u0026quot; [29] which is measured at both the forefoot and heel. In contrast, scientific studies often use the terms \u0026ldquo;midsole thickness\u0026rdquo; [50,70,71] or \u0026ldquo;stack height\u0026rdquo; [6,49,72,73], although they typically refer to the same feature. To maintain consistency with World Athletics regulations, this review uses the term \u0026quot;sole thickness\u0026quot;.\u003c/p\u003e\n\u003cp\u003eAccording to the latest World Athletics regulations [29], sole thickness should be measured at the center of the forefoot and the center of the heel, which are specifically defined as 12% and 75% of the internal shoe length, respectively. However, only one study explicitly reported where these measurements were taken [58]. Additionally, some studies reported only midsole thickness [49,54,57] or heel thickness [48,56], making it more difficult to interpret results due to missing information (e.g., heel-to-toe drop).\u003c/p\u003e\n\u003cp\u003eShoe mass can also be a confounding factor, depending on the difference in mass between tested shoes. A mass increase of 100 g has been shown to negatively impact running economy and performance, whereas a 50 g difference had no effect [74]. In studies where mass was explicitly reported, the difference between tested shoes was generally below 50 g. However, shoe mass was not reported in all studies [48,54,55,59\u0026ndash;61], further complicating result interpretation.\u003c/p\u003e\n\u003cp\u003eThe material composition of shoe foam is another important factor influencing running economy and biomechanics [75]. However, not all reviewed studies explicitly stated which materials were used in the tested shoes [48,57\u0026ndash;61].\u003c/p\u003e\n\u003cp\u003eFor better transparency, future studies should report the full midsole geometry (including forefoot and heel thickness with precise measurement locations and heel-to-toe drop), shoe mass, and material composition.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.3. Limitations and future directions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.3.1. Shoes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe shoes used in the reviewed studies mainly differed in sole thickness, with some studies also reporting slight variations in shoe mass [49\u0026ndash;53,57,58]. Two studies accounted for mass differences by adding small weights to the shoes [56,57], while others did not match mass between shoes, making it challenging to fully isolate the effects of sole thickness. Additionally, in some studies, the heel-to-toe drop varied between shoes [50,52,53,57,60], which could have been another confounding factor influencing the results.\u003c/p\u003e\n\u003cp\u003eFour studies involved AFT shoes. Given that these regulations came after the AFT era, further research on AFT shoes is needed to better understand how sole thickness interacts with other shoe features [7].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.3.2. Participants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe studies reviewed primarily included recreational to experienced runners, with a notable underrepresentation of elite and novice runners. Additionally, most participants were habitual rearfoot strikers, and some studies did not control for this factor. To provide a more comprehensive understanding of the impact of sole thickness, future research should involve elite and novice runners, as well as other type of strikers.\u003c/p\u003e\n\u003cp\u003eMost participants were male, with a mean height range of 1.69 to 1.81 m and mean mass between 58.3 and 73.6 kg. To ensure a more representative sample, future studies should include a broader range of participants, particularly females, and those outside typical height and mass ranges.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.3.3. Study design\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOnly four studies performed \u003cem\u003ea priori \u003c/em\u003epower calculations to determine sample size, which may have limited the statistical power of their findings. The majority of studies (n = 13) were conducted in laboratory settings, using either a standard laboratory floor or a motorized treadmill for running tests (Table 5). However, since ground surface material and stiffness can affect running economy and biomechanics [76\u0026ndash;78], future research should incorporate various surfaces (e.g., track or concrete) to better simulate real-life running conditions.\u003c/p\u003e\n\u003cp\u003eAnother limitation was the inconsistency in biomechanical modeling, with an overreliance on lower-body models: only two studies used full-body models (Table 5). Additionally, only two studies explicitly stated their kinematical model, making cross-study comparisons challenging. Another limitation was that most studies focused on a single joint degree of freedom, overlooking coordination of multiple degrees of freedom which is crucial for understanding motor control [79].\u003c/p\u003e\n\u003cp\u003eRecent literature suggests that individualized shoe design and development could be beneficial in the future [9]. Future research could explore more personalized approaches, such as clustering participants based on their response to specific shoe features [49].\u003c/p\u003e\n\u003cp\u003eAdditionally, critical aspects such as running economy [80], muscle activity [81,82], movement coordination [83] remain underexplored in the literature. To provide a more comprehensive understanding of the effects of sole thickness, further studies should address these aspects.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eA review of 14 studies on the effects of running shoe sole thickness revealed consistent trends, including longer stance times, increased ankle dorsiflexion at IC, and a decreased loading rate of GRF with thicker soles. However, many other parameters\u0026mdash;such as step frequency, knee kinematics, and stiffness\u0026mdash;did not show consistent trends across studies. Shoe mass and heel-to-toe drop emerged as potential confounding factors that may have influenced the results. The sample demographics were limited, with a focus primarily on male recreational or experienced runners. Future research should aim to report shoe features more comprehensively and transparently, include a more diverse range of participants (e.g., female runners, forefoot strikers), and broaden the analysis to include aspects like running economy, muscle activity, and movement coordination. This would provide a more thorough understanding of the effects of sole thickness on running economy and biomechanics.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAFT: Advanced footwear technologies\u003c/p\u003e\n\u003cp\u003eCOM: Center of mass\u003c/p\u003e\n\u003cp\u003eIC: Initial contact\u003c/p\u003e\n\u003cp\u003eGRF: Ground reaction force\u003c/p\u003e\n\u003cp\u003eMLE: Maximum Lyapunov exponent\u003c/p\u003e\n\u003cp\u003ePERSiST: Prisma in Exercise, Rehabilitation, Sport medicine and SporTs science\u003c/p\u003e\n\u003cp\u003ePICO: Population, Intervention, Comparison, Outcome, and Study Design\u003c/p\u003e\n\u003cp\u003ePRISMA: Preferred Reporting Items for Systematic Reviews and Meta-Analyses\u003c/p\u003e\n\u003cp\u003eRoB-2: Cochrane risk of bias instrument tool\u003c/p\u003e\n\u003cp\u003eROM: Range of motion\u003c/p\u003e\n\u003cp\u003eTO: Toe-off\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo sources of funding were used to assist in the preparation of this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCK contributed to the writing of the original draft, as well as reviewing and editing the manuscript, and was responsible for visualization, methodology, investigation, formal analysis, and conceptualization. FK participated in reviewing and editing the manuscript, contributed to visualization and methodology, and was involved in the investigation. TS was responsible for reviewing and editing the manuscript, provided supervision, and contributed to the conceptualization of the study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eHonert EC, Mohr M, Lam WK, Nigg S. Shoe feature recommendations for different running levels: A delphi study. PLoS One. 2020;15:1\u0026ndash;17.\u003c/li\u003e\n \u003cli\u003eCheung RTH, Wong RYL, Chung TKW, Choi RT, Leung WWY, Shek DHY. Relationship between foot strike pattern, running speed, and footwear condition in recreational distance runners. Sports Biomech. 2017;16:238\u0026ndash;47.\u003c/li\u003e\n \u003cli\u003eZhou W, Yin L, Jiang J, Zhang Y, Hsiao CP, Chen Y, et al. Surface effects on kinematics, kinetics and stiffness of habitual rearfoot strikers during running. 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Sports Medicine, Arthroscopy, Rehabilitation, Therapy \u0026amp; Technology. 2012;4:45.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 7 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Karlsruhe Institute of Technology","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Running footwear, Stack height, Kinematics, Kinetics,Running economy, Spatiotemporal variables, Advanced footwear technology","lastPublishedDoi":"10.21203/rs.3.rs-6526264/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6526264/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eAdvanced footwear technologies (AFT) are popular for their potential performance benefits, though concerns about injury risks persist. Among various AFT features, sole thickness is particularly debated, especially after World Athletics imposed a 40 mm limit to prevent unfair competitive advantages. However, the isolated effects of sole thickness on running biomechanics and economy are not well understood.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjective: \u003c/strong\u003eThis review examines the effects of sole thickness on spatiotemporal variables, kinematics, kinetics, and running economy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eA systematic literature search was conducted following PRISMA guidelines. Eligible studies included original research on running with participants of all expertise levels, analyzing spatiotemporal variables, kinematics, kinetics, or running economy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eFourteen studies met the criteria, mostly focusing on male recreational or experienced runners. Thicker soles were linked to increased stance time, while other spatiotemporal parameters remained unchanged. Significant effects were seen in ankle kinematics, with more dorsiflexion at initial contact (IC) with thicker soles, though knee and hip movements were less affected. Thicker soles increased peak eversion in the frontal plane. No consistent trends emerged for joint kinetics, stiffness, or center of mass movement. Vertical ground reaction force (GRF) peaks remained largely unchanged, but loading rates generally decreased with thicker soles. Only one study assessed running economy, with no significant effects.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eThicker soles were largely linked to longer stance times and lower GRF loading rates. Future research should comprehensively report shoe characteristics, include more diverse populations (e.g., female runners, forefoot strikers), expand investigations to underexplored aspects such as muscle activity and movement coordination.\u003c/p\u003e","manuscriptTitle":"The effects of shoe sole thickness on running biomechanics and economy: a systematic review","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-08 14:27:56","doi":"10.21203/rs.3.rs-6526264/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3b2de185-ed75-47ab-aef4-877c3a8a061b","owner":[],"postedDate":"May 8th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":47667446,"name":"Sports Medicine and Kinesiology"}],"tags":[],"updatedAt":"2025-05-08T14:27:56+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-08 14:27:56","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6526264","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6526264","identity":"rs-6526264","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}