Leg muscle microvascular function is associated with dynamic but not static balance performance in older adults

Abstract

Background

Balance impairments in older adults significantly increase fall risk and are a growing public health concern. While muscle strength and mass have been extensively studied in relation to balance, the role of skeletal muscle microvascular function remains unclear. The purpose of this study was to evaluate whether skeletal muscle microvascular function is associated with static and dynamic balance in healthy older adults.

Methods

This cross-sectional study included 57 healthy community-dwelling older adults aged 60—75 years old. Static balance was assessed under four conditions (eyes open/closed, on firm/foam surface) using center of pressure metrics. Dynamic balance was evaluated using the Y Balance Test (YBT). Microvascular function of the tibialis anterior (TA) and medial gastrocnemius (MG) was assessed via near-infrared spectroscopy and post-occlusive reactive hyperemia, using TSI10 (initial reperfusion slope), TSI1/2 (recovery half-time), TSI_desaturation (total desaturation magnitude), and TSI_recovery (total recovery magnitude) as key indicators. Multiple linear regression analyses were performed to assess associations between microvascular and balance parameters, adjusting for age, sex, grip strength, body fat percentage, and estimated VO₂max.

Results

No significant associations were found between microvascular parameters and static balance outcomes. For dynamic balance, after adjusting for age, sex, grip strength, body fat percentage, and estimated VO₂max, MG TSI_recovery was significantly and positively associated with YBT performance on both dominant and non-dominant legs (both p < 0.05). In addition, MG TSI10 was significantly associated with YBT performance on the dominant leg (p < 0.05). No significant associations were found between TA microvascular parameters and dynamic balance performance (all p > 0.05).

Conclusion

This study demonstrates that leg muscle microvascular function, particularly the MG muscle, is associated with dynamic but not static balance performance in older adults.

Background

As life expectancy increases globally, age-related declines in physical function have become a major public health issue. In older adults, impairments in balance function are of particular concern, as declining postural stability greatly increases the risk of falls and associated injuries [1]. People with advanced ages usually present with many sensory and neuromuscular declines that could adversely affect the balance-relevant inputs and responses, leading to greater postural sway and instability [2, 3]. Given the severity of fall outcomes [4], it’s crucial to identify the factors contributing to poor balance, thereby developing targeted strategies to prevent falling in this population.

Previous studies that evaluated balance and fall risks in older adults have generally focused on muscle mass/size, strength, and power [5–8]. Muscle strength and power play an important role in maintaining balance and preventing falls in older adults, and the decline in muscle quality significantly contributes to postural instability, and has therefore been extensively studied [9, 10]. Many studies have reported that low muscle strength or power as significant factors influencing balance and fall risks [5, 6, 11, 12]. Additionally, it was confirmed that reduced muscle mass/size, as evaluated by multiple imaging techniques such as ultrasound, magnetic resonance imaging or dual-energy X-ray absorptiometry (DXA), is related to poor balance function in older adults [13–15]. While muscle mass, strength and power are critical, vascular function, which supports muscle performance through adequate blood flow, may also influence balance, yet its role remains underexplored.

Mechanistically, vascular function is important for maintaining adequate blood flow to the lower limbs, which are essential for standing, walking, and maintaining static and dynamic balance [16]. In healthy young adults, it was reported that arterial stiffness and augmentation index are associated with balance function [17]. Research that has directly evaluated the association between vascular function and balance performance in healthy older adults have been scarce. However, several lines of evidence suggest that poor macrovascular health, as indicated by low flow-mediated dilation or increased carotid intima media thickness, is related to diminished physical functional performance results [18–20], with one study also included a balance assessment component [20]. It’s worth noticing that these studies all focused on the macrovascular level of vascular health. On the other hand, microvascular function influences not only blood supply but also the efficiency of oxygen delivery, metabolite clearance, and maintenance of muscle fiber excitability [21], all of which support neuromuscular control during postural tasks. Age-related decline in capillary density and microvascular responses may reduce muscle oxidative capacity and increase fatiguability [22], which may contribute to the poor postural stability seen in older adults. Nevertheless, to the best of our knowledge, a direct link between microvascular function and postural control in older adults has not yet been established. This is of particular importance, given that advancing age is characterized by vascular dysfunction, especially reduced capillary density, and decreased microvascular function [22], which could significantly impair microcirculation that supplies skeletal muscle and result in poor postural stability.

To address this gap in knowledge, this cross-sectional study aims to investigate the potential association between microvascular function and balance performance in older adults, thereby contributing to a better understanding of the factors influencing postural stability in this population. To comprehensively assess balance, we employed both the standard static as well as the dynamic balance testing paradigms. Based on the results of previous studies and given the critical role of microvascular function in muscle health, we hypothesized that older individuals with better muscle microvascular function would have better balance performance. Findings of this study could provide valuable insights into the role of muscle microvascular health in fall prevention in older adults, and thereby aids the development of targeted strategies and promote healthy aging.

Methods

Participants

Fifty-seven community-dwelling healthy older adults participated in this study. The inclusion criteria were 1) between the ages of 60—75 years old, 2) generally healthy without any known cardiovascular, metabolic, or musculoskeletal diseases, 3) able to ambulate without any assistive devices, 4) no injury to the lower extremity for the past year, 5) BMI < 30 kg/m². This study was approved by the Institutional Review Board at our university, and all participants provided written consent prior to any data collection. A standard warm-up protocol was performed first, including a 3-min walking at self-selected speed, and a 2–3-min light stretches of the legs which was guided by a research assistant. Balance tests were performed in the set order as described below (static balance first, dynamic balance later), and sufficient rest time was given between consecutive tests. Among these participants, 22 were taking anti-hypertension drugs. They were asked not to take these medications on the day of testing until all testing procedures were completed. Specifically, the medication withdrawal period was set to exceed 12 h to eliminate potential residual effects of these drugs on vascular function, ensuring the accuracy of microvascular assessments. All study protocols were carried out at our university laboratories.

Static balance assessment

For all participants, balance was assessed using a Kistler force plate (9287CAQ, Kistler, Winterthur, Switzerland) under four conditions: 1) eyes open on the force plate (EO), 2) eyes closed on the force plate (EC), 3) eyes open on a foam pad (EOF), and 4) eyes closed on a foam pad (ECF). For the latter two conditions, a 49.5 cm * 39.5 cm * 5.5 cm balance foam pad (Rising Sporting Goods, Nantong, Jiangsu, China) was placed on top of the force plate. Participants were instructed to stand barefoot with feet shoulder-width apart and arms on their waist throughout the tests. For the eyes-open conditions, participants were instructed to stare at an “X” sign placed approximately 3 m directly in front of the participant. For the eyes-closed conditions, participants were asked to close their eyes after establishing a stable stance.

Each condition lasted 30 s and was repeated three times. The recording time started after the participant was able to keep his/her balance on the force plate. A 1-min rest period was given between two consecutive trials to prevent fatigue. Center of pressure (COP) data were recorded at a sampling frequency of 1000 Hz and subsequently low-pass filtered at 10 Hz using a fourth-order Butterworth filter. Force plate data were processed using a Python script modified based on the open-access code developed by Quijoux et al. [23]. The first 5 s of the 30 s testing data were removed, leaving 25 s data for analysis. The primary COP-based balance outcome variables include 1) sway area, which refers to the area of the 95% confidence ellipse enclosing the COP trajectory, and 2) mean velocity, which refers to the mean COP sway velocity. These two parameters are among the commonly used parameters in literature to indicate balance function in older adults [24, 25]. In general, increased COP sway area and velocity suggest greater sway during the test, indicating less stability and poorer balance.

All static balance assessment were carried out three times for each condition, and the results for the three trials were averaged. A few participants failed to stand still occasionally under the ECF condition, in which case sufficient rest time was given before starting the next trial. All participants completed all conditions within 5 attempts. The coefficient of variation (CV) for static balance measurements in older adults in our laboratory was 6.9%-9.1%, and the intraclass correlation (ICC) was greater than 0.9, indicating very good reliability.

Dynamic balance assessment

The Y Balance Test (YBT) was administered to assess dynamic balance and functional mobility for both legs in participants. The participant was given the chance to familiarize with the testing procedure before the actual test starts. Additionally, a comprehensive warm-up session was conducted prior to the formal assessment, including light aerobic exercise to activate relevant muscle groups and optimize movement performance. Each participant stood barefoot on a stance platform, with one leg positioned at the center of the YBT grid. Participants were instructed to reach as far as possible with the other leg in three directions-anterior, posteromedial, and posterolateral, while maintaining balance on the stance leg. The maximum reach distance in each direction was recorded in 0.5 cm over three trials per leg, with the best trial used for analysis. Standardized verbal cues and a 1-min rest period between trials ensured consistency. Each direction was administered three times, and the maximal reach distance was used for subsequent analysis. Once one side is finished with the test, sufficient rest time was given, and the procedure was repeated for the other leg. Leg length was measured for both sides from the anterior superior iliac spine to the most distal part of the medial malleolus using a tape measure.

YBT performance score was calculated for each side. The composite score for the leg was calculated as the sum of reach distance across all three directions, divide by three times the leg length and multiplied by 100% [26]. This composite score was calculated for both the dominant (supporting leg; YBT_d) and non-dominant (YBT_n) leg. Higher composite score generally means better dynamic balance performance. The coefficient of variation (CV) for YBT measures in older adults in our laboratory was 2%-3%, and the intraclass correlation (ICC) was greater than 0.9, indicating very good reliability.

Microvascular function assessment

For all participants, skeletal muscle microvascular function was assessed using near-infrared spectroscopy (NIRS) coupled with the post-occlusive reactive hyperemia technique. The tibialis anterior (TA) and medial gastrocnemius (MG) muscles of the dominant leg were tested.

Participants lay on a bed for at least 10 min before the start of the test to ensure hemodynamic stabilization. Two continuous-wave NIRS sensors (PortaLite, Artinis Medical Systems B.V., Netherlands), each equipped with multiple source-detector separations (3.0, 3.5, and 4.0 cm) that provides approximately 1.5—2 cm penetration depth, were placed on the muscle belly of the TA and MG. The location of the placement was one-third distance between the tibial plateau and the medial malleolus, closer to the tibial plateau. The NIRS probes were attached to the skin using double-sided tapes, and were gently secured using self-adhesive wraps. The NIRS sensors measure the light absorption characteristics and generate measures of oxygenated- and deoxygenated hemoglobin concentrations within the tissue. Additionally, the NIRS sensors also measure local tissue overall oxygenation information with a parameter called the tissue saturation index (TSI) using the spatially resolved spectroscopy method.

A pneumatic tourniquet was placed above the knee, which is connected to a custom-built rapid cuff inflation device that can provide pressure to a preset level within 0.5 s. At the start of the test, the NIRS sensors were turned on with the participant lying still, and a 1–2-min baseline was collected. Then, the tourniquet was rapidly inflated to 250 mm Hg to provide full vascular occlusion to the leg for 5 min. At the end of the occlusion, the pressure was rapidly turned off, and the participant continued lying still for another 3 min. The NIRS sensors collected data throughout the entire test at a sampling rate of 10 Hz.

A custom-written Matlab script (version 2020b, The Mathworks, Natick, MA, USA) was used to process NIRS data. Key parameters commonly used to measure skeletal muscle microvascular function were assessed, including 1) the first 10 s slope of TSI immediately following tourniquet release (TSI10), which is used to quantify the initial reperfusion rate, 2) TSI half-time recovery (TSI1/2), which refers to the time it takes for the recovery slope to reach half of its peak value, 3) total desaturation magnitude during occlusion, TSI_desaturation, 4) total recovery magnitude during post occlusive reactive hyperemia, TSI_recovery [27–31]. The coefficient of variation (CV) for NIRS derived microvascular function parameters in older adults in our laboratory was 7%-12%, and the intraclass correlation (ICC) was 0.63—0.75, indicating generally good reliability.

Physical fitness assessment

Aerobic fitness was evaluated using the 6-min walk test, a validated submaximal exercise test for estimating aerobic endurance. Participants were instructed to walk as far as possible within six minutes, maintaining their fastest pace, along a 30-m indoor corridor. No assistive devices were allowed, and standardized verbal encouragement was provided throughout. The total distance covered was recorded as the primary outcome, which was used to further estimate maximal oxygen consumption (VO₂max) using established equation [32].

Muscle strength was evaluated using a mechanical handgrip dynamometer (Model WL-1000, Zhenghe Co., Hengshui, China), which is a widely accepted indicator of overall muscle strength and is closely linked to important health outcomes. Participants stood with feet shoulder-width apart, holding the dynamometer at their side without the arm touching the body and the wrist in a neutral position. After one low-intensity familiarization trial, participants performed three maximal isometric contractions on each hand alternately, with 60 s of rest between trials. The highest reading, measured to the nearest 0.1 kg, was recorded as the final grip strength.

Body fat percentage (%BF) was assessed via a whole-body DXA (Hologic Inc., Marlborough, MA, USA) scan. The participant wore minimal clothing, and the scan was carried out according to manufacturer’s instructions. %BF was determined from the scan using the manufacture to software (excluding the head).

Statistics

Sample size was determined a priori using G*Power 3.1.9.7 (Heinrich-Heine-Universität Düsseldorf, Germany) [33]. For the multiple linear regression analyses with 6 predictors (the microvascular parameter of interest plus 5 covariates), we assumed a medium effect size (f² = 0.15), α = 0.05 (two-tailed), and power = 0.80, and the results yielded a required total sample size of 55 participants.

All statistical analyses were performed using SPSS 27.0 (IBM Corp., Armonk, NY, USA). One-way repeated ANOVA was used to assess balance parameters across the four different conditions (EO, EC, EOF and ECF). The condition with the highest value of instability was chosen to represent static balance in further analyses [17]. To investigate the relationship between microvascular function and balance, multiple linear regression using microvascular parameter as the independent predictor and balance parameter as the dependent variable, adjusting for age, sex, estimated VO₂max, grip strength and %BF was carried out. We included %BF as a covariate as a previous similar study has utilized this covariate [17], and studies have shown fat mass may negatively impact vascular function [34, 35]. Normality of residuals was checked via visually inspecting the histograms, homoscedasticity was checked via visually inspecting the scatterplots, and multicollinearity was diagnosed via the variance inflation factor (VIF > 10 indicates potential collinearity problem), and the results suggest that all models do not violate the assumptions for normality and homoscedasticity, and no collinearity problem was detected. Significance level was set at p < 0.05.

Results

Fifty-seven participants volunteered for the study (n = 16 for males). The physical characteristics for the participants are summarized in Table 1. For balance measures, ECF condition generally induced greater instability compared to other conditions (Table 2). Therefore, further investigation regarding static balance was done using ECF condition. Results for NIRS measured microvascular function parameters are summarized in Table 3. For static balance, neither MG nor TA microvascular parameters were significantly associated with any balance outcomes after adjusting for age, sex, estimated VO₂max, grip strength and %BF (all p > 0.05; Table 4).

Table 1.

Physical characteristics for all participants

	All (n = 57)	Men (n = 16)	Women (n = 41)	p-value	Effect size (Hedge’s g)
Age	64.9 ± 4.4	65.3 ± 4.0	64.7 ± 4.6	0.633	0.141
Height (cm)	161.4 ± 8.6	172.5 ± 6.3	157.0 ± 4.5	0.000*	3.066
Weight (kg)	60.9 ± 10.1	72.15 ± 7.2	56.6 ± 7.3	0.000*	2.128
BMI (kg/m2)	23.3 ± 2.5	24.2 ± 2.4	22.9 ± 2.5	0.070	0.545
BF%	30.3 ± 5.6	23.8 ± 3.5	32.9 ± 3.9	0.000*	2.424
Max Grip Strength (kg)	38.5 ± 8.6	48.7 ± 6.4	34.6 ± 5.5	0.000*	2.477
VO2max (mL/kg/min)	25.7 ± 5.0	28.4 ± 5.0	24.6 ± 4.6	0.010*	0.789

^*Significant between-sex differences

BF%, body fat percentage

Table 2.

Results for balance measures in all participants

		All (n = 57)	Men (n = 16)	Women (n = 41)	p-value	Effect size (Hedge’s g)
EO	Sway area (cm2)	4.0 ± 2.2	3.6 ± 2.2	4.2 ± 2.2	0.327	0.291
	Mean velocity (cm/s)	1.3 ± 0.4	1.3 ± 0.4	1.3 ± 0.4	0.804	0.073
EC	Sway area (cm2)	3.9 ± 2.2	4.1 ± 2.4	3.8 ± 2.1	0.619	0.418
	Mean velocity (cm/s)	1.5 ± 0.5	1.6 ± 0.5	1.5 ± 0.4	0.436	0.232
EOF	Sway area (cm2)	15.4 ± 8.1	14.6 ± 9.8	15.6 ± 7.4	0.660	0.131
	Mean velocity (cm/s)	2.6 ± 0.7	2.7 ± 0.9	2.5 ± 0.6	0.486	0.251
ECF	Sway area (cm2)	19.3 ± 11.3	18.2 ± 10.0	19.7 ± 11.8	0.661	0.130
	Mean velocity (cm/s)	3.5 ± 0.9	3.8 ± 1.0	3.4 ± 0.8	0.096	0.499
YBT	Dominant	97.8 ± 11.0	98.0 ± 13.9	97.8 ± 9.9	0.308	0.021
	Non-dominant	99.4 ± 10.7	97.1 ± 12.9	100.4 ± 9.7	0.944	0.303

EO, eyes open on the force plate; EC, eyes closed on the force plate; EOF, eyes open on a foam pad; ECF, eyes closed on a foam pad; YBT, Y balance test

Table 3.

Results for NIRS measured microvascular function parameters in all participants

		All (n = 57)	Men (n = 16)	Women (n = 41)	p-value	Effect size (Hedge’s g)
TA	TSIdesaturation	15.4 ± 4.5	16.7 ± 4.0	14.9 ± 4.6	0.162	0.412
	TSIrecovery	21.7 ± 7.8	23.0 ± 6.3	21.2 ± 8.4	0.438	0.227
	TSI1/2	9.8 ± 2.8	10.3 ± 2.7	9.6 ± 2.8	0.351	0.244
	TSI10	1.1 ± 0.5	1.1 ± 0.4	1.1 ± 0.5	0.974	0.009
MG	TSIdesaturation	14.9 ± 6.6	17.4 ± 6.7	14.0 ± 6.4	0.039*	0.517
	TSIrecovery	20.2 ± 6.7	24.8 ± 7.6	18.4 ± 5.5	0.001*	1.032
	TSI1/2	7.8 ± 1.9	8.7 ± 1.7	7.4 ± 1.9	0.016*	0.671
	TSI10	1.3 ± 0.5	1.5 ± 0.6	1.2 ± 0.5	0.093	0.497

^*Significant between-sex differences

TA tibialis anterior, MG medial gastrocnemius, TSI10 the first 10 s slope of TSI immediately following tourniquet release, TSI1/2 the time it takes for the recovery slope to reach half of its peak values, TSIdesaturation total desaturation magnitude during occlusion, TSI_recovery total recovery magnitude during post occlusive reactive hyperemia

Table 4.

Association between NIRS measured microvascular function parameters with static balance measures. All models adjusted for age, sex, estimated VO₂max, grip strength and % body fat

Outcome	Predictor	Unstandardized β	Standardized β	LowerCI	UpperCI	p-value	R2
ECF sway area	TA TSIdesaturation	0.069	0.028	-0.612	0.749	0.840	0.132
	TA TSIrecovery	0.287	0.199	-0.125	0.700	0.168	0.164
	TA TSI1/2	0.495	0.122	-0.592	1.583	0.365	0.145
	TA TSI10	1.479	0.065	-4.924	7.882	0.645	0.367
	MG TSIdesaturation	0.074	0.043	-0.415	0.563	0.762	0.133
	MG TSIrecovery	-0.082	-0.049	-0.604	0.441	0.755	0.133
	MG TSI1/2	-0.076	-0.013	-1.798	1.645	0.929	0.131
	MG TSI10	-1.287	-0.057	-8.097	5.523	0.706	0.134
ECF mean velocity	TA TSIdesaturation	-0.005	-0.025	-0.054	0.044	0.848	0.210
	TA TSIrecovery	-0.009	-0.078	-0.039	0.022	0.572	0.214
	TA TSI1/2	-0.005	-0.017	-0.084	0.074	0.895	0.209
	TA TSI10	-0.098	-0.057	-0.560	0.363	0.671	0.212
	MG TSIdesaturation	0.004	0.032	-0.031	0.039	0.814	0.210
	MG TSIrecovery	0.004	0.033	-0.033	0.042	0.825	0.210
	MG TSI1/2	0.041	0.091	-0.083	0.165	0.509	0.216
	MG TSI10	-0.038	-0.022	-0.529	0.454	0.878	0.209

ECF eyes closed on a foam pad condition, TA tibialis anterior, MG medial gastrocnemius, TSI10 the first 10 s slope of TSI immediately following tourniquet release, TSI1/2 the time it takes for the recovery slope to reach half of its peak values, TSIdesaturation total desaturation magnitude during occlusion, TSI_recovery total recovery magnitude during post occlusive reactive hyperemia

For dynamic balance, after controlling for age, sex, estimated VO₂max, grip strength and %BF, the results for MG showed that there was a strong and positive association between TSI_recovery with both YBT_d (standardized β = 0.494, p = 0.001) and YBT_n (standardized β = 0.418, p = 0.008). MG TSI10 was significantly associated with YBT_d (standardized β = 0.374, p = 0.014). No other significant association was found for MG (all p > 0.05, Table 5). No significant association was found for any TA microvascular parameters with YBT_d and YBT_n (all p > 0.05, Table 5).

Table 5.

Association between NIRS measured microvascular function parameters with dynamic balance measures. All models adjusted for age, sex, estimated VO₂max, grip strength and % body fat

Outcome	Predictor	Unstandardized β	Standardized β	LowerCI	UpperCI	p-value	R2
YBTd	TA TSIdesaturation	0.406	0.166	-0.275	1.086	0.237	0.093
	TA TSIrecovery	-0.399	-0.283	-0.810	0.057	0.057	0.133
	TA TSI1/2	0.096	0.024	-1.016	1.207	0.864	0.068
	TA TSI10	-2.837	-0.128	-9.294	3.620	0.382	0.081
	MG TSIdesaturation	0.030	0.018	-0.466	0.526	0.903	0.067
	MG TSIrecovery	0.808	0.494	0.330	1.286	0.001*	0.242
	MG TSI1/2	0.191	0.033	-1.554	1.937	0.827	0.068
	MG TSI10	8.239	0.374	1.731	14.747	0.014*	0.174
YBTn	TA TSIdesaturation	0.350	0.148	-0.312	1.012	0.293	0.083
	TA TSIrecovery	-0.324	-0.237	-0.727	0.079	0.113	0.109
	TA TSI1/2	0.535	0.139	-0.533	1.603	0.319	0.081
	TA TSI10	-4.439	-0.207	-10.622	1.744	0.155	0.100
	MG TSIdesaturation	0.019	0.012	-0.462	0.499	0.938	0.063
	MG TSIrecovery	0.662	0.418	0.184	1.141	0.008*	0.188
	MG TSI1/2	0.332	0.059	-1.358	2.023	0.695	0.066
	MG TSI10	5.856	0.275	-0.641	12.353	0.076	0.120

^* Significant association after adjusting for confounding variables

YBT_d Y balance test composite score on the dominant side, YBT_n Y balance test composite score on the non-dominant side, TA tibialis anterior, MG medial gastrocnemius, TSI10 the first 10 s slope of TSI immediately following tourniquet release, TSI1/2 the time it takes for the recovery slope to reach half of its peak values, TSIdesaturation total desaturation magnitude during occlusion, TSI_recovery total recovery magnitude during post occlusive reactive hyperemia

Discussion

To the best of our knowledge, this is the first study that examined the relationship between skeletal muscle microvascular function and balance in older adults. We observed that MG microvascular function was significantly and positively associated with dynamic balance performance (as indicated by YBT results) in older adults, whereas no such relationship was found with static balance measures under various conditions (EO, EC, EOF and ECF) when adjusting for physical characteristics as well as fitness measures. This suggests that older individuals with better microcirculatory function in their MG muscles tended to perform better on dynamic balance tasks, however this was not the case for static balance tasks. A plausible explanation for this discrepancy is that static balance primarily relies on the integrative function of the nervous system, including sensory integration from visual, vestibular, and proprioceptive pathways, whereas dynamic balance is more dependent on the functional state of muscles, such as their oxidative capacity and fatigue resistance, which are closely modulated by microvascular function.

Balance is an essential physical function in older adults. Better balance directly impacts seniors’ ability to move independently, perform daily activities, and reduce fall risks and associated injuries [3, 36]. Therefore, factors influencing balance performance in older adults have been studied extensively in literature. For example, a large cohort study found that older adults with greater lower limb strength tend to have better balance performance [37]. However, very few studies have explored whether vascular function is related to balance. Although the study by Cilhoroz et al. showed that augmentation index and arterial stiffness, measured by pulse wave velocity method, are significant contributors to balance in healthy young adults [17], their conclusions cannot be generalized to older adults, as this population have altered vascular function and control mechanisms, at both macro- and micro-vascular levels [38, 39].

Our study revealed that MG microvascular function was consistently associated with dynamic balance performance, showing significant positive associations with both YBT_d and YBT_n. In contrast, no significant associations were observed between TA microvascular parameters and YBT performance. The microvascular parameters and YBT results obtained for our cohort were comparable with previous studies [40–42], indicating that our sample’s microvascular reactivity is representative of the older adult’s population. The difference is likely related to the distinct physiological demands of the balance tasks, as well as the different anatomical and functional roles of the two muscles. MG is located in the posterior compartment of the leg and is a primary muscle responsible for plantarflexion and ankle stiffness regulation. During the multi-directional reaching movements of the YBT, the stance limb must maintain stability while controlling forward and lateral shifts of the center of mass, which may impose substantial and sustained demands on the plantarflexor muscles. Better MG microvascular function may therefore facilitate oxygen delivery and metabolite clearance, supporting the muscle’s capacity to maintain postural control during the task. On the other hand, TA is located in the anterior compartment of the leg and contributes to dorsiflexion control. Although TA is involved in ankle stabilization, its microvascular parameters were not significantly related to YBT outcomes in our cohort, suggesting that TA microvascular function may be less influential for overall YBT composite performance than MG in healthy older adults. However, these inferences need to be further validated by studies that directly assess muscle activation patterns during YBT using techniques such as EMG.

Another noteworthy finding is the lack of association between microvascular function with static balance under any conditions. Compared to YBT, static balance involves minimal movement, and these tasks rely heavily on sensory integration from visual, vestibular, and proprioceptive systems [2]. The lack of significant association indicates that factors other than microvascular function, such as sensory processing or neuromuscular control, may play more essential roles in static balance. In static balance tasks, the sensory input systems deliver feedback to the central nervous system, which processes the information and makes nuanced adjustment to the body through the neuromuscular system to stabilize the body [43–45]. Therefore, static balance imposes lower metabolic demand, and the requirement for oxygen and nutrients delivery is reduced, making the microvascular function much less critical under these circumstances. This likely explains why our study found no significant link between microvascular function and static balance performance in older adults.

Our findings may have important clinical implications, particularly regarding fall prevention in older adults. Dynamic balance is essential for daily activities such as walking, climbing stairs, or recovering from perturbations, all of which are common scenarios for falls. Given the important role of the plantarflexor muscle group (including MG) in supporting ankle stability and postural control during dynamic movements, as well as the significant association found between MG microvascular function and dynamic balance performance, these findings raise the possibility that improving microvascular function in muscles like the MG could enhance dynamic balance and reduce fall risk. However, because muscle activation patterns (e.g., EMG) were not measured in this study, this relationship should be interpreted with caution. Nevertheless, our study results suggest intervention such as aerobic exercise, which has been shown to be able to improve microvascular function [46, 47], could be incorporated into fall prevention programs which may potentially lead to better balance performance. Additionally, resistance exercise targeting lower-limb plantarflexors may also improve dynamic balance in older adults, a notion that needs to be further validated. However, whether these training methods could be useful for fall prevention through improved microvascular health needs to be validated by randomized controlled trials.

Limitations of this study must be addressed. First, the cross-sectional nature of this study prevents the inference of causality. Longitudinal studies are needed to clarify the temporal relationship between microvascular function and balance. Interventional studies targeting microvascular function through exercise, diet, or pharmacology could test whether improvements translate to better balance and reduced fall rates. Second, this study recruited exclusively healthy older adults. It’s possible that microvascular function plays a more important role in clinical populations, such as those with peripheral arterial diseases or diabetes, thereby influencing their static balance. Therefore, the study results should not be generalized to other populations without specifically designed studies. Third, this study assessed leg muscle microvascular function. It’s unclear the microvascular function of the thigh muscles, which also contributes significantly to daily postural stability, is related to balance performance in older adults, a topic worth further exploration. Fourth, NIRS-based assessments have inherent methodological constraints, such as sensitivity to adipose tissue thickness, motion artifacts, and the limited depth of penetration, which may influence the estimation of microvascular parameters. Additionally, the muscle oxygenation changes during balance assessment may offer more insights into the relationship between muscle microvascular function, which was not performed in the current study and should be included in future relevant studies.

Conclusion

In conclusion, the results of this study provide new evidence that skeletal muscle microvascular function is linked to dynamic balance ability in older adults. However, this relationship was not observed for static balance. Future studies should explore whether interventions targeting microvascular function could be a promising strategy to improve balance and reduce fall risk in older adults.

Abbreviations

NIRS

Near-Infrared Spectroscopy

YBT

Y Balance Test

TA

Tibialis Anterior

MG

Medial Gastrocnemius

COP

Center of Pressure

TSI10

The first 10 s slope of Tissue Saturation Index

TSI1/2

Tissue Saturation Index Half-Time Recovery

TSI_desaturation

Total desaturation magnitude during occlusion

TSI_recovery

Total recovery magnitude during post occlusive reactive hyperemia

VO₂max

Maximal Oxygen Consumption

%BF

Body Fat Percentage

DXA

Dual-Energy X-ray Absorptiometry

BMI

Body Mass Index

EMG

Electromyography

EO

Eyes Open on Force Plate

EC

Eyes Closed on Force Plate

EOF

Eyes Open on a Foam Pad

ECF

Eyes Closed on a Foam Pad

CV

Coefficient of Variation

ICC

Intraclass Correlation

YBT_d

Y Balance Test score on the Dominant side

YBT_n

Y Balance Test score on the Non-dominant side

Authors’ contributions

Research conception, funding acquisition, resources, and supervision: CZ. Data curation: BL, HH, YH, ZL and JS. Investigation: CZ, BL, HH, YH, ZL, JS and SW. Formal analysis: HH, BL, YH and ZL. Software: SW. Writing of the manuscript: CZ, ZL and BL. Reviewing and editing manuscript draft: CZ. Final approval: all authors.

Funding

This study was supported by the National Natural Science Foundation of China (NO.82301791), the Self-determined Research Funds of CCNU from the colleges’ basic research and operation of MOE (Grant CCNU24JC040), and the Central China Normal University faculty startup funding (Grant NO. 31101222041).

Data availability

The dataset used in the current study are available from the corresponding author upon reasonable request.

Declarations

Ethics approval and consent to participates

The authors state that their research was conducted ethically in accordance with the Declaration of Helsinki. This study was approved by the Institutional Review Board at Central China Normal University (approval No. CCNU-IRB-20403082A). The participants provided written informed consent to participate in the study prior to data collection.

Consent for publication

Not applicable in this section.

Competing interests

The authors declare no competing interests.