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Open Access

Peer-reviewed

Research Article

Gender differences in the impact of fatigue on lower limb landing biomechanics and their association with anterior cruciate ligament (ACL) injuries: A systematic review and meta-analysis

  • Chengxun Liu ,

    Contributed equally to this work with: Chengxun Liu, Wuwen Peng, Wenhao Qu

    Roles Conceptualization, Data curation, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

    Affiliation Graduate School, Guangzhou Sport University, Guangzhou, Guangdong, China

    ⨯
  • Wuwen Peng ,

    Contributed equally to this work with: Chengxun Liu, Wuwen Peng, Wenhao Qu

    Roles Data curation, Investigation, Methodology

    Affiliation Graduate School, Guangzhou Sport University, Guangzhou, Guangdong, China

    ⨯
  • Wenhao Qu ,

    Contributed equally to this work with: Chengxun Liu, Wuwen Peng, Wenhao Qu

    Roles Data curation, Formal analysis, Software, Visualization

    Affiliation Graduate School, Guangzhou Sport University, Guangzhou, Guangdong, China

    ⨯
  • Zhiyong Zhang,

    Roles Data curation, Investigation, Methodology, Software, Visualization

    Affiliation School of Athletic Training, Guangzhou Sport University, Guangzhou, China

    ⨯
  • Jian Sun,

    Roles Project administration, Funding acquisition

    Affiliations School of Athletic Training, Guangzhou Sport University, Guangzhou, China,

    ⨯
  • Jiaxin He ,

    Roles Conceptualization, Project administration, Resources, Supervision, Validation

    574401513@qq.com (JH); bobo791017@163.com (BC); liduany@gzsport.edu.cn (DL)

    Affiliation School of Athletic Training, Guangzhou Sport University, Guangzhou, China

    ⨯
  • Bojin Cheng ,

    Roles Conceptualization, Investigation, Methodology, Project administration, Software, Supervision, Validation, Visualization, Writing – review & editing

    574401513@qq.com (JH); bobo791017@163.com (BC); liduany@gzsport.edu.cn (DL)

    Affiliation School of Physical Education, Guangzhou Sport University, Guangzhou, China

    ⨯
  • Duanying Li

    Roles Formal analysis, Investigation, Methodology, Project administration, Resources, Visualization, Data curation

    574401513@qq.com (JH); bobo791017@163.com (BC); liduany@gzsport.edu.cn (DL)

    Affiliations School of Athletic Training, Guangzhou Sport University, Guangzhou, China,

    ⨯

Abstract

Background

This meta-analysis examines the impact of neuromuscular fatigue on gender differences in lower limb landing biomechanics and its correlation with ACL injury risk.

Methods

A comprehensive search was conducted in PubMed, Scopus, Web of Science, Embase, and the Cochrane Library up to March 2024.

Results

Fourteen studies were included, averaging a quality score of 6.79; nine were high quality. Key findings: males showed a significant increase in knee flexion angle at initial contact (effect size -1.23), but females did not (-0.25). Both genders had significant changes in hip external rotation (males: 1.35, females: 1.20). Ankle peak dorsiflexion angle increased (-1.69) with no gender differences. Peak Knee extension moment increased in males (0.76) and females (0.48) with an overall effect size of 0.64, but no change in peak abduction moment. Peak Hip extension moment was significant in males (0.58) and overall (0.51), with no changes in internal rotation or adduction moments. Peak vertical ground reaction force showed no significant changes for either gender.

Conclusions

Fatigue alters knee biomechanics in males, raising ACL injury risk, and both genders show increased hip and ankle loads post-fatigue. These results suggest the need for gender-specific fatigue management strategies to mitigate ACL injury risk and call for further research into prevention mechanisms.

Citation: Liu C, Peng W, Qu W, Zhang Z, Sun J, He J, et al. (2025) Gender differences in the impact of fatigue on lower limb landing biomechanics and their association with anterior cruciate ligament (ACL) injuries: A systematic review and meta-analysis. PLoS One 20(5): e0321925. https://doi.org/10.1371/journal.pone.0321925

Editor: Alessandro Mengarelli, Universita Politecnica delle Marche Facolta di Ingegneria, ITALY

Received: September 5, 2024; Accepted: March 13, 2025; Published: May 7, 2025

Copyright: © 2025 . This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and its Supporting information files.

Funding: This study was funded by the Guangdong Provincial Philosophy and Social Sciences Regularization Project 2022 (GD22CTY09): Research on the Coordinated Development Path of International Competitiveness in Sports in the Guangdong-Hong Kong-Macao Greater Bay Area (to JS).

Competing interests: The authors have declared that no competing interests exist.

Introduction

Anterior Cruciate Ligament (ACL) tears are among the most common non-contact injuries in many sports [1,2], especially those involving rapid direction changes, deceleration, jumping, and landing [3–5]. ACL injuries typically occur at the knee joint due to improper landing techniques and movement patterns, which can place excessive shear forces and stress on the ACL [6]. Changes in these biomechanical characteristics are closely linked to ACL injuries, particularly increases in knee abduction angles, knee abduction moments, and hip internal rotation moments during landing, which are key factors in non-contact ACL injuries [7].

Multiple factors cause biomechanical changes in the lower limbs during landing [8–10], with fatigue being a critical one. Fatigue alters the biomechanical characteristics of the lower limbs during landing, increasing the risk of ACL injuries [11–13]. Fatigue, as a complex physiological mechanism, occurs at both central and peripheral levels, significantly affecting neuromuscular pathways [14]. Under fatigue, reduced neural feedback efficiency, prolonged muscle reaction time, and proprioceptive dysfunction slow down muscle strength generation and contraction speed [15,16]. These physiological changes not only affect kinematic performance [17,18] but also weaken joint stability [19,20], significantly impairing dynamic balance control [21]. Research further supports this, showing that vertical ground reaction forces (VGRF) significantly increase under fatigue, leading to higher knee joint loads and thus a greater risk of ACL injuries [22]. Moreover, fatigue reduces knee flexion angles, increases knee abduction angles, and heightens hip internal rotation angles, significantly raising stress on the knee joint and ACL [23,24]. Additionally, fatigue-induced reduction in knee flexion may relax the medial collateral ligament (MCL) and lateral collateral ligament (LCL), leading to rotational knee instability and further increasing the risk of ACL injury [25]. Epidemiological studies also show that most sports injuries occur in the latter stages of activities or competitions, further underscoring the importance of fatigue in sports injuries [26]. In summary, fatigue increases the risk of ACL injuries by altering lower limb biomechanics through changes in muscle and nervous system functions.

Studies have qualitatively shown gender differences in lower limb landing mechanics [27,28]. For instance, Hewett et al. found that females have smaller knee flexion angles and larger knee valgus angles during landing, leading to a significantly higher ACL injury rate than males [4]. Additionally, insufficient hip flexion and increased internal rotation can indirectly increase knee joint load [29]. Ford et al. found that female athletes have larger hip internal rotation angles during jumping and landing, making them more prone to ACL injuries [30]. However, findings on gender differences in lower limb landing mechanics under fatigue conditions are inconsistent. Fagenbaum et al. [31] employed an isokinetic machine to test six male and eight female basketball players under fatigue. Results showed that fatigued females had greater knee flexion acceleration during landing than males, who also exhibited changes in muscle coordination, unlike females. This lack of adaptation may increase the risk of ACL injuries in female athletes during jump landings. In contrast, Susan L. Rozzi et al. found that although fatigue decreased joint proprioception (especially in extension) and altered muscle activation patterns, including delayed contraction times and increased specific muscle contraction areas, there were no significant gender differences [32]. These discrepancies indicate the need for more systematic research to explore the impact of fatigue on gender differences in lower limb landing biomechanics.

Therefore, this study aims to systematically review and synthesize existing research through a meta-analysis to explore the specific impact of fatigue on gender differences in lower limb landing biomechanics. This will provide a deeper understanding and scientific basis for preventing ACL injuries, helping to identify high-risk populations and offering references for developing more personalized prevention and rehabilitation programs, thereby effectively reducing the incidence of ACL injuries.

Methods

This article is prepared according to the PRISMA project guidelines and the recommendations by Moher et al. for systematic reviews and meta-analyses [33]. The protocol has been registered on PROSPERO (ID: CRD42024545104).

Search strategy

As of March 2024, a comprehensive search was conducted in the electronic databases of PubMed, Scopus, Web of Science, Embase, and Cochrane Library. Boolean operators “AND” and “OR” were used with the following keywords (using Pubmed as an example) (Table 1).

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Table 1. PubMed literature selection strategy.

https://doi.org/10.1371/journal.pone.0321925.t001

The systematic search was conducted by two independent researchers (C.L., W.Q.). Initially, articles were screened based on titles and abstracts. If the information was unclear or ambiguous, the full texts were retrieved for further assessment. Following this, the researchers compared their findings and resolved any discrepancies through consensus discussions. In cases of unresolved disagreement, a third independent reviewer (W.P.) was consulted to provide a final decision.

To ensure agreement among the investigators, a rigorous process was followed:

  1. Predefined Eligibility Criteria: All researchers applied a set of clearly defined inclusion and exclusion criteria, which were established prior to the screening. These criteria covered study design, population characteristics, interventions, and outcomes.
  2. Independent Screening: Each researcher independently screened the articles at both the title/abstract and full-text stages based on the predefined criteria.
  3. Consensus Process: After the initial screening, any disagreements regarding study eligibility were addressed through consensus discussions. Studies that could not be agreed upon were jointly reassessed by all researchers to reach a final decision.
  4. Third-party Review: When discrepancies persisted or were particularly complex, a third independent reviewer (W.P.), with expertise in the subject area, was consulted to resolve the issue.
  5. Quality Assessment Using STROBE Guidelines: The quality of the included studies was evaluated using a modified version of the STROBE guidelines, which assessed key methodological aspects such as study design, data collection, and potential biases.

Inclusion and exclusion criteria

The literature screening criteria for this meta-analysis were established according to the PICOS [34] format (Participants, Interventions, Comparisons, Outcomes, and Study Design) used in evidence-based medicine. The inclusion criteria are: (1) studies involving both male and female participants; (2) studies utilizing a pre-post self-controlled experimental design; (3) studies implementing at least one protocol designed to induce fatigue; and (4) studies with outcomes that include kinematic, kinetic, or electromyographic analyses relevant to sports biomechanics. The exclusion criteria are: (1) studies not employing a self-controlled experimental design; (2) studies with inaccessible data; (3) studies not utilizing three-dimensional motion analysis systems or force platforms for kinematic and kinetic measurements; (4) conference papers, review articles, and opinion pieces; and (5) studies where the full text is not available.

Data extraction

All references were managed using EndNote X9 software, and duplicates were removed. Two authors (C.L and W.Q) independently extracted descriptive information from all included studies, including publication details (author, year), participant demographics (age, gender), sample size, participant characteristics, fatigue intervention protocols, implementation methods, and biomechanical outcomes (kinematics, kinetics) (Table 2). Biomechanical data necessary for calculating effect sizes (mean and standard deviation) were extracted, and corresponding authors were contacted for additional data if needed. Any discrepancies in the data extracted by C.L and W.Q were confirmed by a third researcher, W.P.

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Table 3. Quality scores of studies included in the review.

https://doi.org/10.1371/journal.pone.0321925.t003

Risk of bias assessment

The quality of the studies was assessed using a modified version of the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines for evaluating observational studies [35]. Each included study was scored based on 10 specific criteria derived from items 5, 6, 7, 8, 9, 12, 13, 14, and 15 of the original checklist (Table 3). The overall quality score was the sum of these criteria, with a maximum score of 10 points. Studies scoring 7 points or higher were considered high quality. This scoring threshold was determined by author consensus and based on previously published modifications of the STROBE guidelines [27].

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Table 2. Checklist of 10 criteria based on an adapted version of the STROBE guidelines for assessing the quality of observational studies used in this analysis.

https://doi.org/10.1371/journal.pone.0321925.t002

Data analysis

To ensure objectivity and robustness, Review Manager 5.3 software (The Nordic Cochrane Centre, Copenhagen, Denmark) was utilized for meta-analyses and subgroup analyses of data from at least two studies reporting on the same variable for both males and females. When measurement units were consistent (e.g., angles), the weighted mean difference (WMD) with a 95% confidence interval was used to assess the overall effect size. If the measurement units differed, the standardized mean difference (SMD) was applied [47]. Heterogeneity among studies was evaluated using the I² statistic, categorized as low (25–50%), moderate (50–75%), and high (greater than 75%) [48]. A fixed-effects model was used when heterogeneity was less than 25%, and a random-effects model was applied when it exceeded 25% [49]. A significance level of 0.05 was employed for all statistical tests.

Meta-analyses were conducted on 18 variables related to lower limb landing mechanics to assess changes before and after fatigue intervention. These variables included:

  1. Peak flexion angles of the knee, hip, and ankle joints.
  2. Initial contact flexion angles of the hip and knee joints.
  3. Peak abduction angles of the knee and hip joints and their angles at initial contact.
  4. Hip external rotation angle at initial contact and peak internal rotation angle.
  5. Peak internal adduction, internal rotation, extension, and flexion moments of the hip.
  6. Peak extension and abduction moments of the knee joint.
  7. Peak vertical ground reaction force (PVGRF).

To enhance the study’s comparability and reliability, data included both males and females, and subgroup analyses were manually classified by gender. Each subgroup required a sufficient number of studies; subgroups with fewer than two studies were excluded from the final analysis.

Results

Through electronic database searches, 11,057 records were identified. After the initial screening, 2,245 duplicate records were removed. Titles and abstracts of the remaining 8,812 records were screened, resulting in the exclusion of 8,657 records. A detailed evaluation of the 155 remaining full-text articles led to the exclusion of 136 based on study content and quality: 22 did not involve fatigue, 98 did not include both genders, 2 were non-English articles, 3 used 2D analysis methods, and 13 did not meet study requirements. After rigorous screening, 17 studies were included in the qualitative synthesis, and 14 were used in the quantitative synthesis. See S1 Fig in supplementary materials.

Risk of bias in included articles

Table 2 details the quality scores of the included studies. Each column corresponds to a specific quality assessment criterion (N1 to N10), with each criterion scored out of 1 point, totaling a maximum of 10 points per study. The table lists the author names, their scores for each criterion, and the total score. Most studies scored between 5 and 8 out of 10, with an average score of 6.79. Nine out of the 14 studies were identified as “high quality,” scoring 7 or higher.

Characteristics of included studies

This meta-analysis included 14 studies involving different populations: six studies with healthy individuals, three with amateur athletes, two with collegiate athletes, and three with registered athletes, team athletes, and young individuals with a history of recurrent low back pain but currently asymptomatic. These studies encompassed a total of 496 participants, with 259 males and 237 females. Six studies used single-leg landing, while eight used double-leg landing. All fatigue induction protocols involved peripheral fatigue. The included studies provided extensive kinematic and kinetic results, covering peak flexion angles of the knee, hip, and ankle joints; initial contact flexion angles of the hip and knee joints; peak abduction angles of the knee and hip joints and their angles at initial contact; hip external rotation angle at initial contact and peak internal rotation angle; as well as peak internal adduction and internal rotation moments of the hip; peak extension and abduction moments of the knee joint; and peak vertical ground reaction force (PVGRF) (Table 4).

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Table 4. Demographic information from included studies.

https://doi.org/10.1371/journal.pone.0321925.t004

Kinematic data of landing biomechanics

This meta-analysis included a total of 14 studies that examined the kinematic data of the knee, hip, and ankle joints, investigating the effects of fatigue and gender on these parameters. The kinematic data for each joint were represented by three-dimensional joint angles (in degrees). The specific parameters analyzed are detailed in Table 5.

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Table 5. Summary of a meta-analysis evaluating the effects of fatigue before and after (including gender subgroups) and on major biomechanical variables of lower limb landing mechanics.

https://doi.org/10.1371/journal.pone.0321925.t005

Knee kinematics

The meta-analysis focused on changes in knee flexion and abduction at initial contact, as well as peak flexion and abduction, before and after fatigue. See S2 Fig in supplementary materials. Key findings include:

  1. Knee flexion angle at initial contact: Ten studies with 378 participants showed a total effect size of -0.72 (95% CI: -1.28, -0.17). Males exhibited a significant increase in angle (effect size: -1.23, 95% CI: -1.85, -0.61), while females showed an increasing trend that was not statistically significant (effect size: -0.25, 95% CI: -1.22, 0.72).
  2. Peak knee flexion angle: Fatigue did not significantly affect peak flexion angle for both males and females (total effect size: -0.96, 95% CI: -2.93, 1.00; males: -1.42, 95% CI: -5.19, 2.34; females: -0.75, 95% CI: -3.13, 1.63).
  3. Knee abduction angle at initial contact: The total effect size was -0.26 (95% CI: -0.55, 0.04), with both genders showing a non-significant increasing trend post-fatigue (males: -0.13, 95% CI: -0.57, 0.31; females: -0.36, 95% CI: -0.76, 0.04).
  4. Peak knee abduction angle: Changes in peak abduction angle were not statistically significant for both genders (total effect size: 0.23, 95% CI: -0.13, 0.60; males: 0.41, 95% CI: -0.12, 0.95; females: 0.07, 95% CI: -0.44, 0.58).

Hip kinematics

The meta-analysis of hip biomechanics before and after fatigue covered six outcome measures: hip flexion and abduction at initial contact, peak flexion and abduction, and external and internal rotation movements. See S3 Fig in supplementary materials. Key findings include:

  1. Hip flexion angle at initial contact: Males (5 studies, N = 68) had an effect size of 0.48 (95% CI: -1.98, 2.93), and females (5 studies, N = 65) had an effect size of -0.06 (95% CI: -2.20, 2.09), showing no significant changes.
  2. Peak hip flexion angle: Males (5 studies, N = 68) had an effect size of 0.63 (95% CI: -2.83, 4.09), and females (5 studies, N = 65) had an effect size of -2.21 (95% CI: -6.39, 1.97), showing no significant changes, though females trended towards increased angles post-fatigue.
  3. Hip abduction angle at initial contact: Males (5 studies, N = 74) had an effect size of -0.13 (95% CI: -1.70, 1.44), and females (5 studies, N = 71) had an effect size of -0.22 (95% CI: -1.43, 0.99), showing no significant changes.
  4. Peak hip abduction angle: Males (4 studies, N = 53) had an effect size of -0.19 (95% CI: -2.09, 1.72), and females (4 studies, N = 50) had an effect size of 0.29 (95% CI: -2.36, 2.94), showing no significant changes.
  5. Hip external rotation angle at initial contact: Both genders showed significant positive changes, with males (3 studies, N = 45) having an effect size of 1.35 (95% CI: 0.51, 2.18) and females (3 studies, N = 45) having an effect size of 1.20 (95% CI: 0.40, 2.01), indicating a trend of angle reduction post-fatigue.
  6. Peak hip internal rotation angle: Males (4 studies, N = 58) had an effect size of -1.26 (95% CI: -3.77, 1.25), and females (3 studies, N = 37) had an effect size of -0.05 (95% CI: -2.79, 2.70), showing no significant changes, although males trended towards increased angles.

Overall, while some changes were observed, most results regarding hip flexion and abduction were not statistically significant, with only hip external rotation at initial contact showing significant changes in both genders.

Ankle kinematics

In this meta -analysis, changes in peak ankle dorsiflexion angle before and after fatigue were evaluated across genders. The overall effect size was -1.69 (95% CI: -3.64, 0.26). For males (3 studies, N = 35), the effect size was -1.61 (95% CI: -4.64, 1.41), and for females (3 studies, N = 33), it was -1.75 (95% CI: -4.29, 0.79), both showing no significant changes, and heterogeneity (I²) was 0% for both. These results suggest that fatigue may lead to an increase in ankle dorsiflexion angle and indicate no significant difference in changes between males and females under fatigue, with the changes not significantly influenced by sample heterogeneity. See S4 Fig in supplementary materials.

Kinetics data of landing biomechanics

The dynamic data for the hip and knee joints, as well as peak vertical ground reaction force (PVGRF), were evaluated.

Knee kinetics

This meta-analysis examined the effects of fatigue on knee extension and abduction torques, considering gender differences. For Peak knee extension moment, males (N = 55) exhibited an effect size of 0.76 (95% CI: 0.29, 1.23, P = 0.002), indicating a significant change, while females (N = 36) had an effect size of 0.48 (95% CI: 0.01, 0.95, P = 0.05), which was nearly significant. The overall effect size was 0.64 (95% CI: 0.33, 0.95, P < 0.001), demonstrating a significant change. Heterogeneity was 29% for males, 0% for females, and 4% overall, indicating a significant reduction in knee extension torque due to fatigue.

For Peak Knee abduction moment, males (N = 59) showed an effect size of -0.07 (95% CI: -0.60, 0.46, P = 0.79), and females (N = 56) had an effect size of -0.34 (95% CI: -1.39, 0.70, P = 0.52). The overall effect size was -0.19 (95% CI: -0.72, 0.34, P = 0.48), with none showing significant changes. Heterogeneity was 51% for males, 85% for females, and 73% overall. These results suggest a statistically significant effect of fatigue on knee extension moment in males, but not on abduction torque for either gender, with high heterogeneity observed. See S5 Fig in supplementary materials.

Hip kinetics

This meta-analysis assessed changes in hip internal rotation, flexion, extension, and adduction torques before and after fatigue across genders. For peak hip internal rotation moment, males (3 studies, N = 43) had an effect size of -0.35 (95% CI: -1.05, 0.35, P = 0.33), and females (3 studies, N = 42) had -0.45 (95% CI: -1.06, 0.15, P = 0.14). The overall effect size was -0.41 (95% CI: -0.83, 0.00, P = 0.05), with no significant changes. For peak hip flexion moment, males (2 studies, N = 23) had an effect size of 0.29 (95% CI: -0.40, 0.98, P = 0.41), and females (2 studies, N = 22) had 0.40 (95% CI: -0.26, 1.07, P = 0.24). The overall effect size was 0.34 (95% CI: -0.08, 0.76, P = 0.12), with no significant changes. For peak hip extension moment, males (2 studies, N = 25) had an effect size of 0.58 (95% CI: 0.01, 1.15, P = 0.04), and females (2 studies, N = 23) had 0.43 (95% CI: -0.16, 1.01, P = 0.15). The overall effect size was 0.51 (95% CI: 0.10, 0.92, P = 0.01), showing significant changes in males and the overall analysis, indicating a decrease. For peak hip adduction moment, males (3 studies, N = 43) had an effect size of 0.30 (95% CI: -0.44, 1.05, P = 0.43), and females (3 studies, N = 43) had 0.35 (95% CI: -0.21, 0.91, P = 0.22). The overall effect size was 0.34 (95% CI: -0.08, 0.75, P = 0.11), with no significant changes. These findings highlight the potential impact of fatigue on different hip joint moment, with significant changes particularly in male hip extension moment. See S6 Fig in supplementary materials.

Peak VGRF

The meta-analysis of peak vertical ground reaction force (PVGRF) examined gender differences in biomechanical responses to fatigue. The effect size for males (7 studies, N = 158) was 0.02 (95% CI: -0.39, 0.42, P = 0.93), and for females (7 studies, N = 136), it was 0.10 (95% CI: -0.26, 0.45, P = 0.59), neither indicating significant changes. The overall effect size was 0.06 (95% CI: -0.20, 0.31, P = 0.67), also showing no significant changes. Heterogeneity was 63% for males, 49% for females, and 54% overall. These results indicate no significant differences in peak vertical ground reaction force between genders before and after fatigue, with moderate heterogeneity. The findings suggest that fatigue does not significantly impact peak vertical ground reaction force across genders, and variability among study samples may affect result consistency. See S7 Fig in supplementary materials.

Discussion

This meta-analysis systematically reviewed existing literature to understand how fatigue influences gender differences in landing biomechanics and the associated risk of ACL injuries. The results indicate that fatigue significantly affects the kinematics and kinetics of the knee, hip, and ankle joints. However, most gender differences in these effects were not statistically significant, with only a few variables showing notable changes. This discussion will delve into our key findings, focusing on the landing biomechanics of the knee, hip, and ankle, while offering a deeper analysis of the potential mechanisms behind observed gender differences.

In the sagittal plane biomechanics, our study found that males had a greater knee flexion angle at initial contact compared to females, both before and after fatigue. Under fatigue, both genders showed an increase in knee flexion angle, but the increase was more significant in males.This may be attributed to the greater strength and control over the knee joint in males, which allows for more noticeable alterations in landing biomechanics under fatigue, as they depend on neuromuscular adjustments to stabilize the knee during landing. In contrast, females may rely more on passive structures, such as ligaments and joint flexibility, leading to less pronounced changes under fatigue [50,51]. For peak knee flexion angles, both genders showed an increasing trend post-fatigue, which is considered a compensatory mechanism after fatigue and also a strategy to reduce ACL loading [52]. Decker et al.‘s study supports this perspective but additionally observed that, in a non-fatigued state, females exhibit greater knee flexion angles during landing compared to males [8]. This gender difference may be attributed to females’ higher flexibility during physical activity [53] and distinct muscle strength distributions [54], both of which influence their landing mechanics and potential injury risks. Our study found that males typically exhibit smaller peak knee flexion angles before fatigue compared to females, which may be attributed to their greater muscle strength and mass, both of which enhance knee stability and facilitate earlier stabilization. The greater musculature in males enables more effective control of knee movement, thereby reducing excessive knee flexion at initial contact [55,56]. However, under fatigue, this greater muscle strength facilitates a more pronounced compensatory increase in knee flexion, as males rely more on muscular control to stabilize the knee during landing.

The importance of sagittal plane knee movements lies in their relationship with anterior-posterior knee shear forces. There is considerable debate on whether abnormal sagittal plane dynamics can cause anterior cruciate ligament (ACL) injuries. Chappell et al. [22] noted that increased anterior tibial shear forces during stop-jumping were associated with increased knee flexion angles. Our study found that the reduction in knee extension torque post-fatigue was more significant in males, with an effect size of 0.76, compared to 0.48 in females. This may be due to the downward momentum reduction caused by knee flexion during landing, along with eccentric contraction of the surrounding knee muscles [8]. The human body’s inherent ability to adapt and regulate enables it to modify lower limb kinematics, thereby reducing the risk of ACL injuries [57]. This can be considered a natural protective mechanism against landing impacts. However, while knee flexion can help mitigate impact forces to some extent, improper flexion may compromise the stability of the medial collateral ligament (MCL) and lateral collateral ligament (LCL), resulting in rotational instability of the knee and an increased risk of ACL injuries [25]. This observation further elucidates why ACL injuries frequently occur during the landing phase of basketball [58]. However, a study by Schmitz et al. [59] on 90-minute intermittent exercise found that as exercise duration increased, subjects landed in a more upright posture post-fatigue, with less hip and knee flexion. Reduced joint flexion was accompanied by decreased hip work and increased knee shear forces [60]. Some studies noted that compared to males, females showed increased quadriceps activation before landing in the same tasks [61]. Krosshaug et al. [62] found that female basketball players exhibited significantly greater knee flexion angles at initial ground contact and within the first 50 milliseconds after contact compared to males, suggesting that females might use different biomechanical strategies during landing to better absorb impact forces. Increased quadriceps activation during landing preparation might increase ACL loading [63]. However, this activation also plays a critical role in reducing rotational stress on the knee joint. In fact, the protective effect of quadriceps activation against rotational instability can, to some extent, offset its contribution to increased ACL tension [64,65]. Regarding hip extension (2 studies) and flexion (2 studies) torques, as well as peak ankle dorsiflexion angles (3 studies), despite being low risk, the limited number of studies reporting these indicators prevents drawing definitive conclusions on potential biomechanical differences in landing mechanics between genders under fatigue.

Frontal plane biomechanics are also related to ACL injuries. Our study found no significant differences in knee and hip abduction angles at initial contact and peak values. However, under fatigue, females showed a greater trend of increased knee abduction angles compared to males. Evidence suggests that excessive dynamic knee valgus may increase ACL tear risk [7,66]. Hewett et al. [4] conducted a prospective study on female athletes in high-risk sports (such as soccer, basketball, and volleyball) during jumping and landing tasks. Using three-dimensional motion capture, they measured joint angles to assess neuromuscular control and kinetic methods to measure joint loads (joint torques). Among the participants, 9 athletes sustained ACL injuries. The ACL injury group had a knee abduction angle of 8° during landing, significantly higher than the non-injured group. Additionally, their knee abduction torque was 2.5 times greater, and the ground reaction force was 20% higher. The injured athletes also showed a faster increase in angular velocity, ground reaction force, and joint torque compared to non-injured athletes. Chappell and Yu et al. [67] further showed that during jumping and landing tasks, female athletes exhibited greater valgus torques compared to males. It is worth noting that compared to males, females generally have a larger Q angle, which refers to the relationship of the femoral axis relative to the tibial axis in the frontal plane of the knee joint and is often associated with increased knee valgus [68,69]. However, no significant relationship has been found between the Q angle and ACL injury rates in female athletes [70,71].

Horizontal plane biomechanics primarily focus on the movement mechanisms of the hip and knee joints. However, this study only included some hip joint mechanical indicators. We found that under fatigue, the hip external rotation angle at initial contact significantly decreased in both male and female athletes. This change could increase the load on the knee and ankle joints, thereby raising the risk of ACL injuries. Koga et al.‘s study [72] using a 3D MBIM system found significant differences in hip joint positions between ACL injury cases during actual competitions and non-injury conditions, as well as during side-cutting and landing movements. In injury cases, the hip joint typically showed a smooth flexion transition after ground contact, whereas ACL injuries were characterized by significant hip internal rotation, causing internal rotation of the knee and ankle joints. This internal rotation increased the load on the knee joint, raising the risk of ACL injuries.

Additionally, Koga et al.‘s research [72] indicated that during side-cutting and landing movements, hip internal rotation affects not only the hip joint itself but also negatively impacts the entire lower limb kinetic chain, increasing stress and injury risks to other joints. This suggests that future research on ACL injury mechanisms should focus more on the dynamic performance of the hip joint and its coordination with other lower limb joints.

Conclusion

This study employed a systematic review and meta-analysis to investigate the effects of fatigue and gender differences on lower limb landing biomechanics and their relationship with ACL injury risk. While most results did not show significant changes, some important trends and significant findings were identified.

First, fatigue significantly increased the knee flexion angle at initial contact in males, which helps reduce ACL loading. Second, males showed a significant reduction in knee extension torque after fatigue, potentially affecting knee stability and increasing injury risk. Additionally, fatigue significantly decreased the hip external rotation angle at initial contact in both males and females, which may increase the load on the knee and ankle joints, raising the risk of injury. However, other hip torques (internal rotation, flexion, and adduction) did not show significant changes under fatigue. Finally, the ankle dorsiflexion angle and peak vertical ground reaction force (VGRF) did not show significant changes before and after fatigue, indicating limited effects of fatigue on these parameters.

Overall, fatigue significantly affects certain knee and hip joint parameters, especially in males. These findings underscore the importance of considering gender differences in fatigue management and sports strategies to reduce ACL injury risk. Future research should further explore the mechanisms behind these changes and assess gender-specific interventions to mitigate ACL injury risk.

Limitations

The study has several limitations that should be considered. First, although 14 studies were included, only a few reported ankle biomechanical variables, which limited the scope of the analysis. This restriction hinders the investigation of the impact of ankle biomechanics on lower limb kinematics and ACL injury risk during landing. Second, the review focused solely on lower limb biomechanical indicators, without considering the positioning and control of the trunk and the entire kinetic chain, which could significantly influence knee biomechanics [73]. Neglecting potential interactions across the kinetic chain, including trunk and hip control, may lead to an incomplete understanding of knee biomechanics. This limitation may underestimate the interdependencies between body segments and their effect on ACL injury mechanisms. Third, while the study emphasized gender, it did not perform a subgroup analysis of the effects of different landing styles and fatigue protocols on lower limb biomechanics. Variations in landing styles and fatigue protocols could alter the biomechanics of lower limb joints during landing. Finally, although the 14 studies included in this review reported data on both sexes before and after fatigue, studies focusing on a single sex were excluded. This omission may affect the comprehensive understanding of gender differences. Future research should address these limitations by incorporating a broader range of biomechanical variables, conducting subgroup analyses, and including sex-specific studies to provide a more comprehensive understanding of ACL injury mechanisms and prevention strategies.

Supporting information

S1 Fig. PRISMA flow chart for inclusion and exclusion of studies.

https://doi.org/10.1371/journal.pone.0321925.s001

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S2 Fig. The forest plot of the effects of fatigue on knee joint kinematics and gender differences.

https://doi.org/10.1371/journal.pone.0321925.s002

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S3 Fig. The forest plot of the effects of fatigue on hip joint kinematics and gender differences.

https://doi.org/10.1371/journal.pone.0321925.s003

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S4 Fig. The forest plot of the effects of fatigue on ankle joint kinematics and gender differences.

https://doi.org/10.1371/journal.pone.0321925.s004

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S5 Fig. The forest plot of the effects of fatigue on knee joint kinetics and gender differences.

https://doi.org/10.1371/journal.pone.0321925.s005

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S6 Fig. The forest plot of the effects of fatigue on hip joint kinetics and gender differences.

https://doi.org/10.1371/journal.pone.0321925.s006

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S7 Fig. The forest plot of the effects of fatigue on vertical ground reaction force and gender differences.

https://doi.org/10.1371/journal.pone.0321925.s007

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S1 File. PRISMA_2020_checklist.

https://doi.org/10.1371/journal.pone.0321925.s008

(DOCX)

S2 File. Data availability.

https://doi.org/10.1371/journal.pone.0321925.s009

(DOCX)

Acknowledgments

Thank you to all the researchers who have contributed to this study.

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