Introduction

The practice of physical exercise has evolved from being a spontaneous activity associated with survival or informal recreation to becoming a key tool for public health promotion and optimizing sports performance. Since the late 20th century, epidemiological evidence has linked physical inactivity with non-communicable chronic diseases, which led to the creation of formal physical activity guidelines and their incorporation into health policies (1). For instance, the World Health Organization published global recommendations on exercise and sedentary behavior in 2020, which guide national policies within its Global Action Plan 2018-2030 (2). At the same time, modern sports adopted methods of systematic scientific training. Today, exercise is understood both as a strategy for preventing chronic diseases and as a structured element of high-performance sports programs (1,2).

Physical inactivity in youth is a global problem with implications for their physical development and future health. Data from the World Health Organization indicates that more than 80% of adolescents do not meet the minimum recommendation of 60 minutes of moderate to vigorous physical activity daily (3). In Latin America and the Caribbean, this situation is especially concerning; regional analyses have reported low compliance rates with recommendations among adolescents and high levels of sedentary behavior (4). This context reinforces the need to assess and promote physical fitness in youth using valid and sensitive functional indicators that can detect changes (5).

Regular exercise during youth is a critical determinant of health and highly relevant in promotion and prevention programs, as it optimizes neuromuscular maturation, cardiorespiratory fitness, and body composition, while reducing cardiometabolic and psychosocial risk factors. Evidence synthesized with accelerometry indicates that higher volumes of vigorous activity are associated with better adiposity profiles, aerobic capacity, and cardiometabolic markers, with relevant dose-response effects in children and adolescents (6). On a global scale, multicenter analyses show that more minutes of moderate-vigorous activity and less sedentary time are associated with lower body mass index and more favorable risk trajectories, with consistent patterns by sex and site, highlighting the need for school and community policies that increase daily activity during this life stage (7).

Vertical jump tests, particularly the countermovement jump (CMJ) and squat jump (SJ), as well as the Abalakov jump, are standardized and widely used procedures to estimate lower limb explosive power, a component associated with both sports performance and cardiometabolic risk profiles (8).

Anthropometry, defined as the quantitative study of body dimensions relevant to movement, is a key determinant of motor performance, as it integrates morphological traits, segmental lengths, circumferences, and composition with the mechanical demands of a task (9). In youth and young adults, recent evidence suggests that characteristics such as thigh and lower leg muscle volume/morphology, as well as foot and distal leg traits, are related to jump performance, although with directions and magnitudes depending on the type of jump and the individual’s profile (10). For example, positive associations have been described between anthropometric estimates of lower limb muscle mass/volume and CMJ height; while structural traits of the foot may show negative correlations with the height reached (11).

The effect of lower limb length on jump height, however, is non-linear and gesture-dependent. In schoolchildren and pre-adolescents, positive relationships have been observed between longer leg length and jump performance (9). Arm drive significantly modifies jump mechanics by providing additional work and allowing for a distinct coordination strategy, as it significantly increases the height reached compared to jumps without arm swing (12). Therefore, analyzing separately the modalities with (Abalakov) and without arm drive (CMJ and SJ) is methodologically relevant to isolate the morphological effect.

Considering the high physical inactivity burden in the region (4) and the scarcity of studies specifically exploring the influence of lower limb segmental lengths on jump performance in Latin American youth, the present study addresses the question: What is the effect of lower limb anthropometry on maximum jump height in vertical jumps with and without arm drive in youth in Colombia? Answering this provides applied criteria for individualized training, performance tracking, and the interpretation of functional tests in university and sports contexts in the region, as well as aligning functional assessment with public health priorities to improve youth physical fitness (8).

Method

Study Design

An observational, cross-sectional, and analytical study with repeated measures per participant was conducted. Each subject provided three observations corresponding to the best height achieved in SJ, CMJ, and Abalakov, which allowed for modeling the effect of jump type within-subject.

Participants and Context

Young adults from Manizales (Colombia) participated, evaluated in a controlled environment. The unit of analysis was the best height (centimeters) per jump type, generating three records per individual (Abalakov, CMJ, and SJ). Data integrity was verified (n = 216 valid observations), with no missing or outlier values (criterion ± 3 SD) prior to analysis.

Functional Assessment Procedures

Participants were instructed in the standardized execution of the three vertical jumps: SJ, CMJ, and Abalakov. For each modality, trials were conducted, and the best height from three attempts was retained as the representative measure of performance. The order of modalities and technical instructions were kept constant for all participants:

SJ: Start from ~90° knee flexion, without arm swing..

CMJ: Countermovement from standing position to ~90° knee flexion, without arm swing.

Abalakov: Countermovement with free arm swing.

Any trial that did not comply with the protocol (e.g., use of arms in SJ/CMJ, hands off hips, or loss of balance) was invalidated and repeated. To reduce variability, technical instructions, order, and criteria for repetition due to protocol non-compliance were kept constant. Jump height was measured using an Axon Jump contact mat.

Instrument and Measurement Quality

Jump height was recorded using an Axon Jump contact mat, which estimates height based on flight time. The choice of this instrument is supported by studies reporting high consistency/reproducibility of the measurement in vertical jump tests (e.g., SJ and CMJ) and high agreement when compared to reference devices/platforms used in jump assessment (13).

Lower Limb Anthropometry

The primary exposure was the trochanter → toe length (cm), recorded as the linear measurement of the distal lower limb. Additionally, height (m), age (years), and physical activity level were recorded in three categories (low, moderate, and high).

Variables and Operational Definitions

The dependent variable was the maximum jump height (cm) per modality, defined as height_best_cm in the analytical database. Jump type was treated as a categorical factor with Abalakov as the reference (comparisons against CMJ and SJ). The trochanter → toe length was modeled as a continuous covariate and interaction with jump type to estimate specific slopes per modality. Height, age, and physical activity level (low, moderate, and high) were included as covariates.

Statistical Methods

Given that there are 3 observations per subject, a mixed linear model (GAMLj in jamovi) with random intercept by ID was fitted: Height ~ Length + Jump_type + Length × Jump_type + Height + Activity_level + Age + (1|ID). Continuous covariates were centered. Restricted maximum likelihood estimation, Satterthwaite degrees of freedom, 95% confidence interval (CI95%), assumption verification (QQ-plot and residuals vs. predicted), estimated marginal means (EMM) by jump type, and comparison of nested models were used to assess the contribution of the interaction.

After confirming the integrity of the 216 records with no missing or outlier values (± 3 SD), descriptive statistics for sex, age, height, trochanter-to-toe length, and activity level were obtained. Jump height (cm) was modeled using a mixed linear model that included trochanter-to-toe length (continuous), jump type (Abalakov reference; CMJ and SJ), and their interaction as fixed effects, along with covariates age, height, and activity level. To capture the dependency of the three attempts per participant, a random intercept by subject was added. The significance of the parameters was evaluated with F-tests, using Satterthwaite degrees of freedom. The model fit was described with the marginal R² (50.7%) and conditional R² (92.8%) coefficients. Nested models were contrasted using a likelihood ratio test (χ²), reporting the increase in R². Assumptions of homoscedasticity and normality of residuals were verified, with no significant violations. For interpretation, adjusted marginal means and simple slopes of the length-height relationship within each modality were calculated and visualized with lines and 95% confidence intervals.

Ethical Considerations

The protocol was approved by the institutional ethics committees (Faculty of Health Sciences, University of Caldas: CBCS-089/acta 020-2019; University of Manizales: acta CBE-02-2021). All participants signed written informed consent, in accordance with the Declaration of Helsinki, before any procedures were performed.

Results

A total of 216 subjects participated in the study (58.8% men and 41.2% women), with a mean age of 24.77 ± 4.87 years and an average height of 1.67 ± 0.09 m.

The mixed linear model explained 50.7% of the marginal variance and 92.8% of the conditional variance of jump height. The trochanter → toe length showed a significant effect (F (1, 210) = 6.99; p = 0.009), and an interaction with jump type was observed (F (2, 428) = 20.24; p < 0.001), indicating that the slope of the length-height relationship differed between Abalakov, CMJ, and SJ (Table 1). Among the covariates, height (F (1, 210) = 43.18; p < 0.001) and high physical activity level (F (2, 210) = 5.81; p = 0.003) were positively associated with performance, while age was not significant (p = 0.757). The comparison of nested models showed that adding the interaction and covariates significantly improved the fit (ΔR² = 0.007; LRT χ² = 95.14; p < 0.001).

The estimated marginal means showed that the Abalakov jump reached the highest adjusted height (34.5 cm; 95% CI = 33.6-35.5) compared to CMJ (30.0 cm; 95% CI = 29.0-30.9) and SJ (23.1 cm; 95% CI = 22.2-24.1), with all differences being statistically significant (Table 2).

In the analysis of simple slopes (Figure 1), the negative relationship between length and height was most pronounced in SJ (β ≈ −0.74 cm per centimeter of length), followed by CMJ (β ≈ −0.58 cm/cm) and Abalakov (β ≈ −0.46 cm/cm). A difference equivalent to one standard deviation (~5.43 cm) in length was associated with approximate reductions of 4.03 cm (SJ), 3.16 cm (CMJ), and 2.49 cm (Abalakov) in jump height.

The relationship between trochanter → toe length and jump height was observed according to the jump type (Abalakov, CMJ, and SJ). In Figure 1, the lines represent the slopes estimated by the mixed linear model, adjusted for height, physical activity level, and age. The shaded bands indicate the 95% confidence intervals. It is observed that the negative slope is most pronounced in SJ, followed by CMJ, and lowest in Abalakov.

Analysis

For each +1 cm increase in trochanter → toe length, the estimated jump height decreases by −0.46 cm for Abalakov, −0.58 cm for CMJ, and −0.74 cm for SJ, adjusted for covariates. Considering that the standard deviation (SD) of length in the sample was approximately 5.43 cm, a difference of about 5.4 cm between two subjects was associated with approximate reductions in jump height of −2.49 cm (Abalakov), −3.16 cm (CMJ), and −4.03 cm (SJ). Height showed a positive association, with the coefficient indicating that for each 1 cm increase in height, jump height increases by approximately 0.72 cm, holding other variables constant. The simple slope analysis confirmed that the negative slope of length was most pronounced in SJ, followed by CMJ, and lowest in Abalakov.

Discussion

In this sample (n = 216; 58.8% men; 24.8 ± 4.9 years; 1.67 ± 0.09 m), the mixed linear model explained a substantial proportion of the jump height variance and revealed a significant interaction between trochanter-to-toe length and jump type (F (2, 428) = 20.24; p < 0.001). The marginal means showed the expected pattern: Abalakov > CMJ > SJ (34.5, 30.0, and 23.1 cm, respectively), with significant differences between modalities. This gradient aligns with the mechanics of the stretch-shortening cycle and the contribution of arm swing, which increases CMJ height compared to SJ and adds ~15-17% more when arm swing is allowed, particularly in younger populations, but also applicable to young adults engaged in recreational activities (14).

The key finding was that a greater length of the distal lower limb (trochanter → toe) was associated with lower jump height, and this negative slope was most pronounced in SJ, intermediate in CMJ, and lowest in Abalakov (simple slopes for +1 SD ≈ 5.43 cm: −4.03 cm in SJ; −3.16 cm in CMJ; −2.49 cm in Abalakov). This pattern is biomechanically plausible: as distal length increases, the moment of inertia also increases, requiring more time to accelerate the system and penalizing gestures with less elastic contribution and arm swing (SJ > CMJ > Abalakov). Recent evidence suggests that the tibia/femur ratio and leg length modulate performance in explosive actions, with sport- and sex-specific associations (15,16). Additionally, segmental anthropometry studies in untrained individuals indicate that foot and lower leg lengths are relevant predictors of vertical jump, while the thigh contributes less information, consistent with our findings (16).

Beyond global length, foot morphology may act as a distal modulator of force production and foot-ground coupling. In young adults, foot measurements have been related to jump performance in a sex-dependent manner (17), and in university males, height and foot metrics show correlations with strength and power during CMJ/SJ (19). In a meta-analysis of individuals with flat feet, no differences in jump height were observed, suggesting that the morphological effect is not linear and depends on multiple covariates (20). These data complement the negative slope observed here for trochanter-to-toe length, highlighting the greater weight of the distal lever over simple height.

In the covariate analysis, height showed a strong positive association with jump height, while high physical activity level was associated with greater jump heights (B ≈ +2.74 cm compared to “low”). These associations align with the literature: anthropometric and body composition profiles are related to neuromuscular performance (21), and greater exposure to plyometric/neuromuscular training translates into improved jump height (22)..

The differential effects by modality reinforce the idea that the mechanical context of the gesture modulates the impact of anthropometry. In the model performed, the penalty of length was greater in SJ, a "muscular" jump with minimal elastic contribution, and lower in Abalakov, where arm swing and greater intersegmental coordination allow for angular momentum transfer, reducing the disadvantage of long levers (14). Additionally, recent studies connect muscle structure (lower limb muscle volume) with power and jump performance, with effects dependent on sex/age (23,24), suggesting that at the muscle-functional level, distal anthropometric disadvantages can be partially compensated.

From an applied perspective, individualized training based on mechanical profiles has gained traction; however, some reviews indicate small to moderate improvements in jump height and effects comparable to non-optimized programs when a profile is already close to optimal (25,26). In populations engaged in recreational or mixed activities, such as the present one, this evidence prioritizes strength and speed capabilities in an integrated manner, rather than assuming that “more length” or “more arm swing” alone determine performance (26).

These findings suggest that in sports medicine, vertical jump interpretation should not be based solely on absolute height, as lower limb anthropometry may influence performance depending on the modality. In clinical practice, an individualized approach is recommended, prioritizing intra-subject comparisons (tracking the same athlete) and selecting the test according to the objective (SJ, CMJ, or Abalakov). This can support training decisions, rehabilitation, and return-to-sport strategies, interpreting performance changes and comparisons between athletes (14).

Limitations

Although a mixed model was used with adjustment for sex, height, age, and physical activity level, the design is cross-sectional, which does not allow for inferring causality. The trochanter-to-toe length captures the effective distal lever but does not discriminate the contributions of the tibia, foot, or tendon stiffness (17,18). Muscle volume and architecture, variables that have been independently linked to power and jump performance (23,24), were not quantified. Additionally, the differences between jump modalities may be influenced by technical criteria (e.g., coupling time, depth, arm swing synchronization), and different measurement technologies present biases (25). Furthermore, the physical activity level was categorical and does not quantify the dose-response of training (type, volume, and intensity), which restricts the interpretation of its effect.

Conclusiones

Of the three movements evaluated, the Abalakov jump (which allows the use of the arms and torso for propulsion) was clearly the one that took participants the highest. The CMJ jump ranked second, and the SJ (which starts from a squat without arm propulsion) was the lowest. In other words, when the entire body is used for propulsion, more height is achieved. Although it may seem counterintuitive, people with a greater distance from the hip to the tip of the foot tended to jump slightly less. This disadvantage was small in the Abalakov, moderate in the CMJ, and most evident in the SJ. In jumps where arm swing is not as involved, longer legs may require more strength to lift off.

Greater overall height (head to feet) was associated with greater jump height, regardless of the jump type or leg length. Additionally, those who reported a high level of daily physical activity outperformed those with medium or low levels; however, age did not make a difference in this young group. When considering jump type, height, leg length, and physical activity level together, most of the variations observed in jump height can be understood and even predicted. This suggests that these elements are key for designing training programs or performance tests.

References

Notes

Funding The authors did not receive any funding for writing this article.

Conflict of Interest The authors declare that they have no conflicts of interest.

Author notes

^a Correspondence author: eduardomarulandalopez@gmail.com

Additional information

How to cite: Alba Ospina D, López Ríos MA, Marulanda López JE. Influence of Lower Limb Length on Vertical Jump Performance in Young Adults. Univ Med. 2026;(67). https://doi.org/10.11144/Javeriana.umed67.illl

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