Falls represent a leading cause of injuries in older, middle-aged, and also in young men and women (26). According to the Baltimore Longitudinal Study of Aging, the frequency of falls in young adults (age range: 20–45 years) over the 2 years amounts to 18.5% (i.e., 54 fallers of 292 young participants) (26). The reported injuries because of falls result in sprains or strains (46.2%), bruises/hematomas (28.2%), and cuts/lacerations (15.4%). The main extrinsic/environmental and intrinsic/subject-related risk factors compromised uneven surfaces (20.9%) and balance/gait impairment (38.9%), respectively.
In young adults, impaired postural control is an important risk factor for falls and sports-related injuries adults (7,27). In fact, Wang et al. (27) showed that high variations in postural sway were significantly (odds ratio = 1.2) associated with the occurrence of ankle injuries in high school basketball players. In addition, deficits in lower extremity muscle strength were reported to be a significant (odds ratio = 3.9) intrinsic risk factor for noncontact quadriceps and hamstrings strains in young soccer players (7).
From a therapist's or a practitioner's point of view, knowledge about the relationship between postural control and lower extremity muscle strength may be important for both the identification of persons with an increased fall/injury risk and the development of fall-/injury-preventive training programs. More specifically, given the association between deficits in balance and leg muscle strength/power and the occurrence of falls and sports-related injuries in young adults (7,27), findings on potential correlations between variables of balance and lower extremity muscle strength/power could provide scientific rationales for injury risk assessment and for the development of specifically tailored injury prevention and rehabilitation programs in young adults. Associations between static and dynamic balance measures and between isometric strength and power have already been studied in young healthy adults. In fact, strong relationships were found between various variables of isometric strength and power (1,20). In terms of static and dynamic balance, study results are less consistent. For example, Hsiao-Wecksler et al. (21) were able to predict the behavior during a dynamic (perturbed) balance condition from performance during a static (unperturbed) balance condition in young adults (mean age: 25 ± 3 years). However, Shimada et al. (25) did not detect significant correlations between static (i.e., performance in the sensory organization test) and dynamic (i.e., decelerating perturbation impulse while walking on a treadmill) postural control in young adults (age range: 20–32 years). Furthermore, in a recent study, Granacher et al. (9) were not able to find significant associations between measures of postural sway during standing and several gait parameters during steady-state walking in young adults (mean age: 22 ± 3 years).
There is paucity in the literature regarding the relationship between balance and isometric strength or power in young healthy adults. In fact, only 2 studies investigated this issue, and both did not find significant correlations between balance and strength/power parameters (14,23). In other words, it is unresolved whether the reported findings hold true when static and dynamic balance, isometric strength, and power measures will be compared. Therefore, the objectives of this study were to determine the relationship between variables of static and dynamic balance, isometric strength, and power in young adults. We predict that a significant relationship between measures of isometric strength and power of the lower extremities but not between static and dynamic balance and between balance and strength/power measures exists.
Experimental Approach to the Problem
Given the association between deficits in balance and leg muscle strength with the occurrence of falls and sports-related injuries in young adults (7,27), we calculated correlations between measures of static/dynamic balance, isometric strength, and power in a controlled cross-sectional study. As a measure of static and dynamic postural control, displacements of the center of pressure (CoP) in anterior-posterior and mediolateral directions were computed under unperturbed and perturbed conditions. Because of the fact that different muscle groups are required to maintain static (predominately muscles encompassing the ankle joint) and dynamic (predominately leg extensor muscles) balance (28), we selected maximal isometric torque (MIT) and rate of torque development (RTD) of the plantar flexors and countermovement jump height (CMJH) and power (CMJP) as outcome measures, respectively. Potential associations were calculated using Pearson's correlation coefficient.
Twenty-seven young healthy adults participated in the study after experimental procedures were explained. An a priori power analysis (6) with an assumed type I error of 0.05, a type II error rate of 0.10 (90% statistical power), and an effect size of 0.50 was conducted for the association between measures of balance and lower extremity muscle strength (14). The analysis revealed that 27 participants would be sufficient for finding statistically significant correlations. Participants' characteristics are presented in Table 1. No one had any history of musculoskeletal, neurological, or orthopedic disorder that might have affected their ability to perform strength and balance tests. This information was obtained by self-report using a standardized assessment protocol of the University Hospital Basel. The participants were asked to fill in the validated “Freiburg questionnaire of physical activity” (8) (Table 1). The test-retest reliability of the questionnaire is medium to large with r = 0.35–0.91, depending on the type of physical activity considered. In addition, an acceptable validity (r = 0.42) in adults aged 18–78 years has shown activity (8). The mean physical activity level for people aged 20.0–29.9 years amounts to 11.2 hours per week (8). The questionnaire revealed a physical activity level of 16.2 ± 8.6 hours per week for the participants of this study. This could be because of the fact that our participants were undergraduate students studying exercise and health sciences. Therefore, they can be classified as physically active because they attended sports-related courses like swimming, gymnastics, and track and field events during the study on a weekly basis. However, they were not specifically trained with respect to strength, power, and balance. Appropriate informed consent has been gained from the participants. Local ethical permission was given by the Ethikkommission beider Basel (EKBB), and all experiments were conducted according to the latest version of the Declaration of Helsinki (29).
Before testing, all subjects underwent a 5-minute warm-up consisting of bi- and monopedal balance exercises and 5 submaximal plyometrics. Tests included (a) measurements of static and dynamic postural control on a balance platform, (b) the analysis of CMJH and CMJP on a force platform (i.e., power), and (c) the assessment of MIT and RTD of the plantar flexors on an isokinetic device (i.e., isometric strength). This testing sequence was applied to keep the effects of neuromuscular fatigue minimal. In addition, a 5-minute rest was applied between tests and a 1-minute rest between trials.
Static and Dynamic Balance
Test circumstances (room illumination, temperature, and noise) were in accordance with recommendations for posturographic testing (22). Static and dynamic postural control was assessed by means of a balance platform (GKS 1000; IMM, Mittweida, Germany). The balance platform consists of 4 uniaxial sensors measuring displacements of the CoP in the mediolateral and anterior-posterior directions. Under static (unperturbed) conditions, the balance platform was firmly fixed on the floor. For experimental testing, participants were asked to stand on their dominant leg on the platform with their supported leg in 30° flexion, hands placed on hips, and gaze fixated on a cross on the nearby wall. The dominant leg was determined according to the lateral preference inventory (4). Subjects were instructed to remain as stable as possible and to refrain from any voluntary movements during the trials. Before testing, students performed 2 practice trials on the balance platform. Thereafter, 3 test trials were conducted. The best trial (least CoP displacements) was used for further analysis. Data were acquired for 30 seconds at a sampling rate of 40 Hz (22). Time series signals were filtered using a second-order Butterworth low-pass filter with a cutoff frequency of 10 Hz. Afterward, 2 parameters were computed from the time series of the CoP displacements: first, the displacements of the CoP in anterior-posterior direction (CoPap_s in mm) under static conditions; second, the displacements of the CoP in mediolateral direction (CoPml_s in mm) under static conditions.
Under dynamic (perturbed) conditions, the platform was placed into a cage, which is mounted to 4 springs and is free to move in the transversal, mediolateral, and anterior-posterior directions. Mediolateral perturbation impulses were applied to investigate dynamic postural control of the participants. Therefore, the platform was moved 2.5 cm from the neutral position in the mediolateral direction, where it was magnetically fixed. Participants' test position was identical with that during the assessment of static postural control. Several trials (i.e., 3–5) helped participants to get accustomed to the measuring device. After investigators visually controlled the position of the subjects, the mediolateral perturbation impulse was unexpectedly applied by detaching the magnet. The platform suddenly accelerated in the medial direction. The participants' task was to damp the oscillating platform by balancing unilaterally on the platform. Data were acquired for 10 seconds at a sampling rate of 40 Hz. If participants did not accomplish the whole sampling duration (i.e., the hands were no longer placed on hips or the unsupported leg touched the ground), they were allowed to repeat the task. Three trials were performed. The best trial (least CoP displacements) was used for further analysis. Again, time series signals were filtered as mentioned above, and displacements of the CoP in anterior-posterior (CoPap_d in mm) and mediolateral (CoPml_d in mm) directions were computed under dynamic conditions and used as outcome measures. Intraclass correlation coefficients (ICCs) were calculated for total displacements of the CoP under static (CoPap_s: ICC = 0.87; CoPml_s: ICC = 0.89) and dynamic conditions (CoPap_d: ICC = 0.83; CoPml_d: ICC = 0.87). This protocol has recently been described in detail elsewhere (12,15).
Maximal isometric torque of the plantar flexors was measured on an isokinetic system (Isomed 2000; D & R Ferstl GmbH, Hemau, Germany). The maximum error of the torque sensor was less than 0.2%. Participants lay supine on the seat of the isokinetic device, with hip and knee angles in neutral position (180°) and the ankle angle at 100°. Straps attached to the isokinetic system firmly fixed the shoulders, the waist, the thigh, the shank, and the foot. In addition, participants were asked to cross their arms in front of their chest. Thus, evasive movements of the upper and lower body were not possible. Testing was performed with the dominant leg. Before the testing started, participants warmed up by doing 3–5 submaximal isometric actions in the isokinetic system to get accustomed to the testing procedure. Thereafter, each subject performed 3 plantar flexor exercises with maximal voluntary effort. For each trial, subjects were thoroughly instructed to act as forcefully and as fast as possible and to avoid forced respiration. The torque signal was sampled at 200 Hz. A digital fourth-order recursive Butterworth low-pass filter, with a cutoff frequency of 50 Hz, filtered the torque signal. During offline analysis, the best trial in terms of maximal torque was selected and used for further data analyses. Maximal isometric torque was defined as the maximal voluntary torque value of the torque-time curve, determined under isometric condition. Rate of torque development was defined as the mean slope of the torque-time curve between 20 and 80% of the individual maximal torque. The ICC coefficient was calculated for MIT (ICC = 0.97) and RTD (ICC = 0.93) of the plantar flexors. This protocol has recently been described in detail elsewhere (17).
Participants performed maximal vertical CMJs while standing on a one-dimensional force platform (Kistler Type 9290AD; Kistler, Winterthur, Switzerland). The vertical ground reaction force was sampled at 500 Hz. During the CMJ, subjects stood in an upright position on the force platform and were instructed to begin the jump with a downward movement, which was immediately followed by a concentric upward movement, resulting in a maximal vertical jump. Before testing, students performed 2 practice trials. Thereafter, subjects performed 3 CMJs. The best trial in terms of maximal jump height was taken for further data analyses. Countermovement jump height was calculated using double integration of the vertical force signal. Countermovement jump height was defined as maximum vertical displacement of the center of mass. Countermovement jump power was calculated as the product of the vertical force signal by vertical velocity. The ICC was calculated for CMJH (ICC = 0.98) and CMJP (ICC = 0.98). This protocol has recently been described in detail elsewhere (16).
Data are presented as group mean values ± SD (Table 1). Associations of static/dynamic balance variables with isometric strength and power variables were assessed using Pearson product-moment correlation coefficient. Associations are reported by their correlation coefficient r, level of significance, and the amount of variance explained (r2). Values of r = 0.10 indicate small, r = 0.30 medium, and r = 0.50 large size of correlation (3). In addition, simple linear regression models were calculated to determine the most robust predictors of the respective outcome variables. Total variance is reported by the coefficient of determination (R2) and the respective level of significance (p value). Furthermore, parameter estimate (B), SE, standardized estimates (β coefficients), and t values are also provided. The significance level was set at α = 5%. All analyses were performed using Statistical Package for Social Sciences (SPSS, IBM Company, Armonk, NY, USA) version 19.0.
Static and Dynamic Balance
No statistically significant correlations were detected between variables of static (unperturbed condition) and dynamic (perturbed condition) balance (Table 2). Respective r values ranged from −0.090 to +0.329 (Figure 1A). Based on r2, only a small proportion of variance could be explained (1–11%).
Isometric Strength and Power
Significant positive correlations were detected between variables of isometric strength and power with RTD of the plantar flexors showing higher correlations with variables of CMJ performance than MIT of the plantar flexors (Table 2). Respective r values ranged from +0.458 to +0.689 (p < 0.05) (Figure 1B). Values for r2 indicated a large amount of variance explained (21–47%).
Balance, Strength, and Power
No significant correlations were observed between variables of balance, strength, and power (Table 2). Respective r values ranged from −0.076 to +0.387 (Figure 1C). Based on r2, only a small proportion of variance was explained (1–15%).
Because statistically significant correlations were found only between isometric strength and power, and not between static/dynamic balance and between variables of balance, isometric strength, and power, we calculated linear regression models for measures of isometric strength and power only. Results of the simple regression analysis for the variables of isometric strength and power are shown in Table 3. The R2 values ranged between 0.210 and 0.783 (p < 0.05), explaining 21–78% of total variance of the respective isometric strength and power parameters. The covariates sex, body mass, body height, and body mass index did not influence our result (data not shown). Furthermore, the regression formulas obtained for the association of CMJH with MIT (y = 2.993x + 10.626) and RTD (y = 16.888x − 197.470) revealed that, for example, a 10% increase in mean CMJH (relates to 4.1 cm) was related to 22.9 N·m and 128.4 N·m·s−1 better MIT and RTD values, respectively.
The main findings of this study can be summarized as follows: (a) no statistically significant correlations were detected between parameters of static (unperturbed) and dynamic (perturbed) balance, (b) statistically significant correlations were observed between variables of isometric strength and power, and (c) no statistically significant associations were found between measures of balance, strength, and power.
In contrast to our results, Hsiao-Wecksler et al. (21) were able to predict the behavior during a dynamic (perturbed) balance condition from performance during a static (unperturbed) balance condition in young (mean age: 25 ± 3 years) and old healthy adults (mean age: 69 ± 2 years). Based on their findings, the authors suggested that the postural control system may use the same control mechanisms during quiet stance and mild perturbation conditions. The reason for the discrepancy between our results and the findings of Hsiao-Wecksler et al. (21) may be a result of variations in the methods used for the assessment of balance and strength performance. Whereas we investigated associations between quiet stance and severe stance perturbations, Hsiao-Wecksler et al. (21) examined the relationship between quiet stance and mild stance perturbation. The mild perturbations in the study of Hsiao-Wecksler et al. (21) were initiated by activating a mechanical trigger. The authors reported that the tug necessitated only a mild postural sway response. The severe perturbations in this study were applied by detaching a magnet. Thus, it can be speculated that in fact different neuromuscular mechanisms might be responsible for the regulation of mild and severe stance perturbation impulses. In other words, the compensation of mild stance perturbations might afford only minor magnitudes of reflex controlled muscle activations, whereas severe stance perturbations demand large reflex activations of lower extremity muscles to successfully stabilize the center of gravity over the base of support. In fact, it was recently shown that reflex-controlled muscle contractions are necessary to compensate for this type of severe perturbation impulse (13).
Our results may have functional implications for future directions in balance assessment and in planning and developing adequate balance training programs to counteract intrinsic fall and injury risk factors in young adults. Based on our findings, it can be hypothesized that different neuromuscular mechanisms are responsible for the regulation of static and dynamic postural control. Because falls and sports-related injuries primarily occur during ambulation in young adults and thus during dynamic conditions (26), fall/injury risk assessment should particularly be carried out under dynamic conditions to identify potential balance problems. From an injury preventive point of view, our results indicate that static and dynamic postural control are independent of each other and may have to be trained complementarily. In fact, this is reinforced by studies that showed the effectiveness of balance training in reducing sports-related injuries among healthy young adults (5,24).
The present results are in accordance with the literature regarding the association between isometric strength and power variables of the lower extremities (1,20). Baker et al. (1) compared isometric strength and power measures in young healthy adults (mean age: 20 ± 3 years). For this purpose, participants performed unilateral isometric leg extensions, 1 repetition maximum (1RM) squats, and CMJs. Isometric leg test performance showed statistically significant correlations with 1RM squats (r = 0.58) and with CMJ (r = 0.52). Haff et al. (20) confirmed these results when comparing maximum isometric and dynamic pulls at 80, 90, and 100% of their current 1RM power clean from a standardized position on a force plate in young men (mean age: 27 ± 3 years). Isometric peak force showed large correlations with dynamic peak force during 80% (r = 0.66), 90% (r = 0.77), and 100% (r = 0.80) of the current 1RM power clean. In addition, isometric rate of force development showed also large correlations with dynamic peak force (r values ranged between 0.65 and 0.75) and with dynamic rate of force development (r values ranged between 0.84 and 0.88) during 80, 90, and 100% of the current 1RM power clean.
From a functional perspective, this indicates that training-induced strength adaptations are not necessarily task specific. In other words, gains in isometric muscle strength can be transferred at least to a certain extent to power conditions and vice versa. In fact, a study by Bruhn et al. (2) indicated that strength training significantly increased maximal isometric force and CMJH in young healthy adults (mean age: 22 ± 2 years). This finding could be beneficial for therapists, educators, and coaches in terms of the development and application of effective resistance and plyometric training programs during rehabilitation of lower extremity injuries, during physical education, and during preseason and in-season conditioning.
To date, there are only 2 studies available that investigated the association between static/dynamic balance and isometric strength or power in healthy young adults (14,23). In the first study, McCurdy and Langford (23) scrutinized the relationship between static balance (i.e., single-limb stork stand), dynamic balance (i.e., single-limb stand on a wobble board), and dynamic muscle strength (maximum unilateral squat strength) in young healthy men (mean age: 22 ± 2 years) and women (mean age: 22 ± 1 years). The authors reported no significant correlations between static/dynamic balance and dynamic strength performance for both men (r values ranged between −0.06 and +0.20) and women (r values ranged between −0.05 and +0.34). More recently, Granacher et al. (14) confirmed these findings when investigating the relationship between dynamic balance (i.e., ability to compensate for gait perturbations during walking on a treadmill) and isometric muscle strength (i.e., capacity to produce maximal leg extension force) in young (mean age: 27 ± 3 years) and old men (mean age: 67 ± 4 years). As a result, correlation coefficients (r) ranged from −0.43 to +0.53. Furthermore, in 2 recent studies from our laboratory, we obtained similar results when using the same experimental approach as in this study but investigating prepubertal children (11) and adolescents (10). Based on these results, it seems plausible to argue that balance, isometric strength, and power are independent neuromuscular capacities in children, adolescents, and in young adults who may have to be trained complementarily. This is reinforced by recent efforts to investigate the nature of adaptive mechanisms after balance vs. resistance training programs in young healthy adults (18,19). For example, Gruber et al. (19) scrutinized neural adaptations in response to 4 weeks of balance or resistance training by means of electromyography, H-reflex, and stretch reflex recordings. The authors observed significant differences in reflex excitability between the 2 training regimens, with reductions in peak-to-peak amplitudes of stretch reflexes and in the ratio of the maximum H-reflex to the maximum efferent motor response (Hmax:Mmax) after balance but not after strength training.
We acknowledge that this study has some limitations that warrant discussion. First, the sample size applied in this study is relatively small. However, the a priori power analysis revealed that 27 participants would be sufficient for finding statistically significant correlations. Second, the participants included in this study were healthy young adults with a high physical activity level per week. However, they were not specifically trained with respect to strength, power, and balance. Therefore, care is needed when generalizing the present findings to other populations (e.g., resistance-trained subjects). Third, the number of familiarization trials (i.e., 2–5 depending on the measured variable) applied in this study is relatively small, which may affect performance in subsequent test trials. Fourth, the results are specific to the measures used to assess static and dynamic balance, isometric strength, and power in this study. These measures may not represent all components of balance, strength, and power. Therefore, care is needed when generalizing the present findings to other kinds of testing situations.
Based on the results of this study, static and dynamic balance appear to be independent of each other in young healthy adults. Given that falls/injuries primarily occur during ambulation and thus during dynamic conditions in young adults (26), fall/injury risk assessment should particularly be carried out under dynamic conditions to identify potential balance deficits. Furthermore, the strong associations between isometric strength and power of lower extremity muscles imply that gains made in strength (e.g., MIT of the plantar flexors) after training may be associated with a change in performance in power (e.g., CMJH). The absence of a significant correlation between measures of static/dynamic balance, isometric strength, and power seems to be a relatively robust phenomenon, particularly because we were able to replicate these results in prepubertal children and adolescents (10,11). Furthermore, the lack of an association between static/dynamic balance, isometric strength, and power indicates that these neuromuscular capacities may be unrelated and should therefore be trained complementarily for fall-/injury-preventive purposes.
No funding was received for this research. There is no conflict of interest.
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Keywords:© 2013 National Strength and Conditioning Association
static/dynamic postural control; maximal isometric torque; rate of torque development; jump height/power