October 2021

Are Static and Dynamic Postural Balance Assessments Two Sides of the Same Coin? A Cross-Sectional Study in the Older Adults

By Alex Rizzato, Antonio Paoli, Marta Andretta, Francesca Vidorin, and Giuseppe Marcolin

These authors investigate the impact of static and dynamic postural balance assessments and the effects of a cognitive-interference task on balance control performance in older adults.

Postural balance control has been defined as the ability of a subject to maintain the center of pressure (CoP) within the base of support to prevent falling. Traditionally, literature differentiates between static and dynamic balance conditions. The static condition is referred to balance under unperturbed environments such as quiet standing, while the dynamic condition is connected to the ability of the subject to react efficiently to the base of support displacements or to external mechanical stimuli. The CoP displacement, derived from force platforms, is considered the most reliable output for postural balance control assessment under static conditions. Nevertheless, both static and dynamic postural control are crucial for the activities of daily living and are implicated in multiple scenarios of everyday life. Hence, the evaluation of the dynamic postural balance control is necessary besides the static one. Since the interaction of the postural control systems is complex, the assessment of postural balance control in a concise and holistic approach is demanding as well. On this point, Ringhof and Stein extended the traditional perspective considering balance as a general ability and reinforced the idea that dynamic balance tests are necessary and not interchangeable.

Consequently, the efficiency of the systems involved in postural balance control (ie, visual, vestibular, and proprioceptive systems) is crucial for people of different ages. Since the mid-seventies, an increased postural sway in the older adults has been recognized, in association with a higher risk of falling. Indeed, more than one-third of persons over 65 falls each year, and in half of such cases, falls are recurrent. Hageman et al found a larger area of sway in healthy older adults than in a younger group for all the studied conditions: eyes open, eyes closed, and with visual feedback. Similarly, Fernie et al demonstrated a greater sway path velocity in older adults who had fallen once or several times in a year with respect to non-fallers. However, a review by Rubenstein reported that the fall-risk is more tightly associated with dynamic than static conditions. Moreover, Blake et al identified tripping as the most recurrent fall-related event after a community survey on 1,042 individuals age 65 and over. This age-dependent decrease in postural balance control has been interpreted as deterioration of sensory, motor, or cognitive systems. Moreover, the reduced rate of force development in older adults has been associated with a lower capacity for neuromuscular response to control body balance. Older fallers demonstrated a reduced contractile rate of force development than non-fallers. Similarly, Paillard hypothesized a relationship between lower extremity strength and postural performance (ie, the stronger the muscles the better the postural performance), confirming the role of strength on postural balance control. A final aspect to consider is that many falls in older adults occurred when a secondary cognitive or motor task (ie, dual-tasking) was performed. Thus, the use of dual-task (DT) paradigms to predict falls among older adults is encouraged for its superiority over the employment of single-tasks (STs). The secondary task can be manual, discrimination and decision-making, mental tracking, verbal fluency, and working memory. Indeed, during dual-tasking, the 2 tasks reciprocally interfere with the performer’s attention overloading the cognitive sources. Therefore, the introduction of a secondary cognitive task over the motor one (ie, postural balance control) may help to understand the cognitive contribution involved in postural regulation both in static and dynamic conditions.

On the relevance of these previous investigations and considering that dynamic postural control has been recognized as important as the static postural control, the first aim of the present cross-sectional study was to investigate whether there was a relationship between static and dynamic postural balance performance in a group of healthy older adults. Moreover, considering the greater exposure to fall-risk of the older adults under dual-tasking condition, our second aim was to study if the addition of a cognitive-demanding task could equally affect static and dynamic postural balance control.

Materials and Methods

We outlined a cross-sectional design in which two balance conditions, bipedal static (BS) and bipedal dynamic (BD) were tested both in ST and DT modality. Fifty-seven healthy older adults (age = 73.2 ± 5.0 years, height = 1.66 ± 0.08 m, body mass = 72.8 ± 13.8 kg, fall-risk questionnaire score = 1.37 ± 1.59 [score >4 indicates fall risk]) completed the study. Static and dynamic balance were assessed both in single-task and dual-task conditions through a force plate and an oscillating platform. The dominant handgrip strength was also measured with a dynamometer. Details on the experimental design, data analysis, and statistical analysis can be found in the original publication available at the website noted on page 45.

Results

Table 1 reports the results of all parameters obtained from both static and dynamic postural balance tests. The results of the correlational analysis are presented in Table 2. In detail, Pearson’s correlation revealed non-statistically significant correlations between Total Stability Index and all the static postural parameters (namely, ellipse area, sway path, and maximal AP oscillations). Moreover, Pearson’s correlation did not show any significant correlation between the static postural parameters and handgrip strength. On the contrary, a weak though significant negative correlation was found between TSI scores and handgrip strength test both in the ST (P < 0.05; r = −0.264) and in the DT (P < 0.05; r = −0.302) condition.

Paired t-tests showed an overall significant worsening of balance performance in the DT condition than in the ST condition, for all the parameters investigated (ellipse area: P < 0.001, Cohen’s d = 0.40; sway path: P < 0.001, Cohen’s d = 0.53; maximal AP oscillations: P < 0.001, Cohen’s d = 0.42; TSI: P < 0.001, Cohen’s d = 0.58) as shown in Table 1. The one-way ANOVA showed statistically significant differences in the DT cost (P < 0.001; ηp 2: 0.099) and the post-hoc multiple comparisons (Bonferroni test) showed a significantly higher (P < 0.001) DT cost for TSI (147.80 ± 24.55%) than ellipse area (72.93 ± 19.46%), sway path (43.45 ± 6.37%), and maximal AP oscillations (25.10 ± 24.55%), respectively (Figure 1). Additionally, the number of correct answers given by each participant was significantly lower (P < 0.001) in the BD-DT (4.03 ± 2.16) condition compared to the BS-DT (5.56 ± 0.42) condition.

Discussion

The main purpose of this study was to compare the static and dynamic postural balance control in a group of older adults to understand whether these two conditions were interdependent from each other. Indeed, understanding whether a relationship between static and dynamic postural balance exists may lead to important practical applications in the assessment of postural balance control among older adults. Our results showed a non-significant correlation between static and dynamic postural balance control in any of the indexes investigated, both in ST and DT conditions. Although static and dynamic postural balance control is ruled by the same structures (ie, cerebral cortex, basal ganglia, cerebellum, brainstem, and spinal cord), their different contribution in the 2 balance conditions could account for the non-significant correlations detected. Our findings are in line with previous research where bipedal quiet stance showed no correlation with proactive (Timed Up & Go test and Functional Reach Test) and reactive (perturbed standing) balance.

Figure 1. Dual-task cost for static and dynamic postural balance parameters. Black histogram represents the dynamic parameter (TSI, total stability index) while white histograms represent static parameters. DT, dual-task condition; ST, single-task condition. Data are presented as mean + standard error of the mean (SEM). ***Significantly different (p < 0.001).

Indeed, the human bipedal quiet stance has been modeled as a single inverted pendulum whose pivot is located at the ankle. In this model, the projection of the center of mass falls in front of the ankle, creating a dorsiflexor moment around the ankle, which is continuously counteracted by the stabilizing effect of tonic muscles. This oscillation could be considered as a mostly automatic process of postural control since the subject is largely unaware of the adjustments of postural muscles. Therefore, postural regulation mainly occurs at brainstem-spinal levels with neural circuits tuned by local loops of assistance or self-organized mechanisms due to the unperturbed and extremely predictable context. Conversely, when dynamic tasks are performed, continuous changes in the surrounding environment, acting forces, and sensory inputs happen, leading to a higher involvement of the cognitive process of postural control to achieve goal-directed movements. Thus, a prevalence of the supra-spinal postural strategy is required due to the ongoing regulation of the movement for the adaptation to the new environment.

Our results on the addition of a cognitive-demanding task showed an overall decrease in postural balance performance under DT compared to ST condition, both in the static and dynamic assessment. This is not surprising since postural regulation could never be considered as totally automatic. Moreover, older adults exhibit less automatic processing of posture while standing, leading to greater involvement of cognitive resources. Although the presence of a DT helped the subjects to address their attention to an external focus with a theoretical improvement of the balance performance (Masters and Maxwell, 2008), DT condition simultaneously resulted in increasing the complexity of the physiological and behavioral system. Consequently, an increase in information processing occurred, leading to cognitive-motor interference.

The theoretical approaches for explaining this DT interference are 2-fold: the capacity sharing model and the bottleneck model. In the first, it is assumed that people share a finite mental processing capacity among tasks. Thus, for each task that is performed, a section of this capacity is covered. When more than one task is performed, a decline of the performance on both tasks is registered if the total capacity is overcome. In the second model, it is postulated that when two tasks are performed, they compete for the same processing operation; consequently, a bottleneck occurs, and one or both tasks will be impaired.

Since the two theoretical approaches are not mutually exclusive, they could together account for the greater worsening of postural balance (+147.8%) and cognitive (+38%) performance (ie, less correct answers given) detected under dynamic than static condition (Figure 2). During the dynamic test (Figure 2C), the voluntary control of postural balance required a greater processing capacity than in the static test (Figure 2A). Being the cognitive task of the same difficulty in both the balance conditions (Figures 2B,D), the older adults should have invested a higher mental processing capacity in the dynamic postural task without worsening the cognitive task. However, the performance of the cognitive task decreased as well: supposedly, the processing capacity required to cope with the dynamic test in the DT condition exceeded the overall available capacity. Finally, since the cognitive and the postural task required the same central mechanism simultaneously, the resulting bottleneck contributed, together with the processing capacity saturation, to the highest worsening of both tasks in the dynamic condition (Figure 2D). Conversely, the bottleneck model could explain alone the worsening of the static postural performance (+25.10%, +43.45%, and +72.93% for ellipse area, sway path, and maximal AP oscillations, respectively). Indeed, the static postural task was less demanding (ie, less capacity required; Figure 2A) and allowed to cover each task without exceeding the total amount of the processing capacity (Figure 2B).

Figure 2. Capacity sharing and bottleneck model approaches to explain dual-task interference. (A) Inputs from the postural task (blue balls) cover a small part of the whole processing capacity (few balls in the glass) due to the mostly automatic control involved in quiet standing. No bottleneck occurs in this condition. (B) Under the static dual-task condition, a bottleneck results since postural (blue balls) and cognitive (yollow balls) tasks require the same mechanism at the same time. Moreover, the presence of both tasks covers a considerable part of the whole processing capacity (higher number of balls in the glass). (C) The dynamic postural task requires more processing capacity than static postural task (I.e., more blue balls in the glass). No bottleneck occurs in this condition. (D) Under the dynamic dual-task condition, a bottleneck occurs as for (B) and the processing capacity required, exceeds its total amount (the balls overflow the glass).

A difference between static and dynamic postural balance control has been detected looking at the handgrip test results. An intriguing significant weak correlation was found between handgrip strength and dynamic postural balance control. This correlation seems to demonstrate that the greater the strength of the older adults, the better the dynamic postural balance performance (ie, lower TSI). Although this relationship certainly deserves further investigation, our data are in line with the results published in 2014 by Forte et al, who pointed out the interaction between strength and dynamic postural balance. However, although the level of strength has often been related to fall-risk, its relationship with balance performance is still a debated issue in the scientific literature since some authors found no relationship between postural sway and strength or power.

It is relevant to mention some limitations of the present work. Postural balance control is a multifactorial construct in older adults. Although we enrolled a homogeneous group of healthy non-faller older adults thanks to the physiatric screening, we could not control all the variables that might have affected balance performance, and thus, few of them could have been neglected, confounding some of our findings. Then, although we followed the recommendations of the international society of posturography for the static test standardization, the employment of the same feet position could have been challenging depending on the anthropometric characteristics of each subject. Last, the interpretation of the DT interference on brain structures and thus on balance performance followed a theoretical approach. Further studies measuring brain involvement while performing different balance tasks are warranted to support the interpretation presented in this study.

In conclusion, although the same structures govern static and dynamic postural balance control, the relative contribution of each structure is different in the two balance conditions. The absence of significant correlations supports this consideration, corroborating the assumption that postural balance assessments should include both static and dynamic conditions in older adults. Moreover, concurrently cognitive-interference tasks exacerbated the degradation of postural control performance, especially under dynamic conditions. Therefore, static and dynamic postural control assessments with cognitive tasks are encouraged to give clinicians more accurate indications on postural control for the development of tailored training programs.

Alex Rizzato is a student in the Human Inspired Technology Research Centre in the Department of Biomedical Sciences at the University of Padova in Italy.

Antonio Paoli, MD, BSc, FECSS, FACSM, is Professor and Chair of Sport and Exercise Sciences, Director of the Nutrition & Exercise Physiology Laboratory in the Department of Biomedical Sciences, University of Padova, Italy, and I am also professor and Chair of Strength Training and sport Nutrition at the Catholic University of Murcia (UCAM) in Spain.

Marta Andretta is in the School of Human Movement Sciences at the University of Padova in Italy.

Francesca Vidorin is in the School of Human Movement Sciences at the University of Padova in Italy.

Giuseppe Marcolin, PhD, is Assistant Professor in the Department of Biomedical Sciences, University of Padova, Italy.

This article has been excerpted from “Are Static and Dynamic Postural Balance Assessments Two Sides of the Same Coin? A Cross-Sectional Study in the Older Adults” by the same authors, which was published online June 29, 2021 in the journal Frontiers in Physiology: Exercise Physiology. doi.org/10.3389/fphys.2021.681370. Editing has occurred, including the renumbering of figures, and references have been removed for brevity. Use is per the Creative Commons Attribution License (CC BY). Readers are encouraged to read the full article at https://www.frontiersin.org/articles/10.3389/fphys.2021.681370/full

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