Abstract
[Purpose] Individuals with chronic stroke often exhibit low physical activity and prolonged sedentary behavior, possibly due to muscle weakness and impaired postural control. This study investigated associations between trunk and lower limb muscle thickness and physical activity, including sedentary behavior, in ambulatory individuals with chronic post-stroke hemiplegia. [Participants and Methods] Twenty-six ambulatory individuals with chronic post-stroke hemiplegia were included. Physical activity was assessed for 7 consecutive days using a triaxial accelerometer and categorized as sedentary behavior, light physical activity, and moderate to vigorous physical activity. Bilateral muscle thickness of the diaphragm, internal oblique, gluteus medius, quadriceps, soleus, and tibialis anterior was measured using ultrasonography. Pearson’s correlation and multiple regression analyses adjusted for age and Fugl–Meyer Assessment for the Lower Extremity (FMA-LE) scores were performed. [Results] Sedentary behavior was negatively correlated with the muscle thickness of the unaffected-side diaphragm, affected-side internal oblique, and unaffected-side internal oblique. Post-hoc power analysis demonstrated 0.54 statistical power. However, these associations were not independently significant after adjustment for age and FMA-LE scores. [Conclusions] Greater trunk muscle thickness was associated with less sedentary behavior in univariate analysis but not after adjustment. The independent clinical significance of trunk muscle morphology requires confirmation in larger longitudinal studies.
Key words: Hemiplegia, Physical activity, Sedentary behavior
INTRODUCTION
Physical activity is an important determinant of health and functional independence. Individuals with chronic stroke are less active and spend more time sedentary than healthy adults, which may adversely affect long-term health and function1, 2). Because recovery often plateaus in the chronic phase, identifying factors related to habitual physical activity is important for rehabilitation2).
Trunk control, balance, and lower limb function are important determinants of physical activity after stroke1, 3). In particular, trunk muscles such as the diaphragm and abdominal muscle contribute to postural control and gait performance, whereas lower limb muscles support stability and walking function. These muscle characteristics may therefore be related to daily activity behavior4, 5).
Moderate-to-vigorous physical activities in individuals with chronic stroke are frequently extremely restricted owing to neurological deficits. Consequently, identifying factors contributing to extended sedentary behavior which is an independent risk factor for secondary cardiovascular events and disuse-related muscle atrophy, represents a more realistic and crucial target for community-based rehabilitation6).
Strokes can also lead to muscle weakness and asymmetry, which may affect balance control and movement efficiency7,8,9). Although muscle thickness has been associated with physical function and mobility, its relationship with objectively measured daily physical activity, especially sedentary behavior, remains unclear in individuals with chronic post-stroke hemiplegia.
This study investigated the association between trunk and lower limb muscle thickness and objectively measured daily physical activity in ambulatory individuals with chronic post-stroke hemiplegia. We hypothesized that reduced trunk muscle thickness would be associated with increased sedentary behavior, while lower limb muscle thickness would correlate with light or moderate-to-vigorous physical activity.
PARTICIPANTS AND METHODS
The participants were 26 ambulatory individuals with chronic post-stroke hemiplegia (19 males and 7 females) (Table 1). They had a mean age of 61.3 ± 11.0 years, height of 167.0 ± 10.3 cm, and weight of 63.9 ± 11.7 kg.
Table 1. Participant characteristics.
| Category / Variable | Values (n=26) | |
| Demographic characteristics | ||
| Age (years) | 61.3 ± 11.0 | |
| Gender (female/male) | 7/19 | |
| Height (cm) | 167.0 ± 10.3 | |
| Weight (kg) | 63.9 ± 11.7 | |
| BMI (kg/m2) | 22.9 ± 2.9 | |
| Stroke and clinical status | ||
| Disease type (bleeding/infarction) | 8/18 | |
| Paralysis side (right/left) | 17/9 | |
| Duration from onset (months) | 103.8 ± 73.0 | |
| Walking aids usage (None/T-cane) | 18/8 | |
| Ankle-foot orthosis (Yes/No) | 19/7 | |
| Functional assessments | ||
| FIM (score) | 115.2 ± 10.7 | |
| FAC (score) | 5 ± 0 | |
| FMA-LE (score) | 20.3 ± 5.9 | |
| BBS (score) | 41.8 ± 7.4 | |
| Physical activity metrics | ||
| Valid wear time (min/day) | 854.8 ± 173.2 | |
| Valid wear days (days) | 7 ± 0 | |
| Absolute sedentary time (min/day) | 639.2 ± 155.7 | |
| Sedentary behavior (%) | 74.3 ± 8.2 | |
| LPA (%) | 22.8 ± 7.4 | |
| MVPA (%) | 0.4 ± 0.6 | |
| Step counts (steps/day) | 1,884 (481–2,544) | |
Data are presented as mean ± standard deviation for all variables except Step counts, which are presented as median (interquartile range). BMI: body mass index; FIM: functional independence measure; FAC: functional ambulation categories; FMA-LE: Fugl–Meyer Assessment for the Lower Extremity; BBS: Berg Balance Scale; LPA: light physical activity; MVPA: moderate-to-vigorous physical activity.
Regarding walking status, 18, 8, and 19 participants walked independently without aids, used a T-cane and used ankle-foot orthoses, respectively.
Participants were eligible if they were between 20 and 80 years of age, were at least 6 months after stroke onset, had a unilateral supratentorial lesion, and had a Functional Ambulation Categories (FAC) score of 4 or higher. Individuals with conditions that could affect physical function or physical activity measurement were excluded.
This study was approved by the Ethics Committee of Nittaduka Medical and Welfare Center (approval no. Nittaduka 2023-13). Written informed consent was obtained from all participants before participation. All procedures were conducted in accordance with the Declaration of Helsinki.
Functional independence was assessed using the Functional Independence Measure, FAC, Fugl–Meyer Assesment for the Lower Extremity (FMA-LE), and Berg Balance Scale (BBS). Physical activity levels and step counts were recorded beginning the following day.
Bilateral muscle thickness of the diaphragm, internal oblique, gluteus medius, quadriceps femoris, tibialis anterior, and soleus was measured by B-mode ultrasonography (Vivid 6, GE Healthcare) using previously reported methods10, 11). Each muscle was measured three times, and the mean value was used for analysis. A single physical therapist with 3 years of experience in musculoskeletal ultrasonography, who had previously evaluated a preliminary sample of healthy adults to establish intra-rater reliability before assessing the cohort with stroke, performed all measurements. Furthermore, previous studies have already established that the ultrasonographic measurement of the trunk and lower limb muscle thickness using identical anatomical landmarks is highly reliable and reproducible even in patients with stroke10). Although target muscle morphology may vary in clinical populations, this preliminary evaluation was performed to confirm the technical competency and reproducibility of the ultrasonographic geometric landmarks before assessing the cohort with stroke.. Intra-rater reliability was excellent for all muscles (Supplementary Table 1).
Physical activity was measured using a triaxial accelerometer (Active Style Pro HJA750-C, Omron Healthcare, Kyoto, Japan) worn at the waist during waking hours for 7 consecutive days12, 13) Days with at least 10 h of wear time were considered valid. Activity intensity was classified as sedentary behavior (≤1.5 METs), light physical activity (1.6–2.9 METs), and moderate-to-vigorous physical activity (≥3.0 METs), and the percentage of time spent in each category relative to total active time was calculated, and the mean daily step count across 7 days was recorded. Although gait asymmetry and slow walking speed could impact step count accuracy, the validity on the Active Style Pro HJA750-C and its predictive algorithms for identifying locomotive and household intensity under free-living conditions was previously established12, 13), and its concurrent validity for METs estimation during walking and performing daily tasks in patients with stroke had also been recently demonstrated, regardless of the hemiplegic side in which the device was worn14). Furthermore, to facilitate clinical interpretation, the absolute sedentary time (min/day), mean daily wear time, and number of valid days were calculated.
Activity data were analyzed using a 60-s epoch according to previous studies12,13,14,15).
Statistical analyses were performed using EZR (Saitama Medical Center, Jichi Medical University, Saitama, Japan). Normality was assessed using the Shapiro–Wilk. Descriptive data are presented as mean ± standard deviations.
Pearson’s correlation coefficients (r) were calculated between height-normalized muscle thicknesses and physical activity metrics. Post-hoc power analysis was performed based on the sample size (n=26) and the observed clinical effect size.
Multiple linear regression analysis (forced entry method) was conducted to identify independent predictors of sedentary behavior after adjustment for age and FMA-LE. Multicollinearity was assessed using the variance inflation factor (VIF).
Statistical significance was set at p<0.05.
RESULTS
Participant characteristics and descriptive statistical data are summarized in Table 1. The participants’ mean daily step count was 1,920.1 ± 1,870.5 steps.
The mean valid accelerometer wear time was 854.8 ± 173.2 min/day, spanning 7 ± 0 valid days. The absolute sedentary duration was 639.2 ± 155.7 min/day. Participants spent 74.3 ± 8.2% of waking time engaged in sedentary behavior, 22.8 ± 7.4% in light physical activity, and 0.4 ± 0.6% in moderate-to-vigorous physical activity. For the univariate correlation analysis, post-hoc power analysis revealed that with the sample size of n=26 and a moderate effect size (r=0.40), the achieved statistical power (1 − β) was 0.54. Sedentary behavior was negatively correlated with diaphragm thickness on the unaffected side and with internal oblique thickness on both sides (Table 2). Thus, greater trunk muscle thickness was associated with less sedentary behavior in the univariate analysis.
Table 2. Correlations between sedentary time and height-normalized trunk muscle thickness.
| Muscle | r | 95% CI |
| Affected-side diaphragm | −0.182 | −0.533 to 0.220 |
| Unaffected-side diaphragm | −0.419 | −0.697 to −0.038 |
| Affected-side internal oblique | −0.417 | −0.696 to −0.035 |
| Unaffected-side internal oblique | −0.400 | −0.685 to −0.015 |
Data are expressed as Pearson’s correlation coefficients (r), with exact p-values and 95% confidence intervals (95% CIs) calculated for a sample size of n=26. CI: confidence interval.
No significant associations were observed between muscle thickness and light or moderate-to-vigorous physical activity. The comprehensive correlation matrix, including the exact Pearson correlation coefficients (r), p-values, and 95% confidence intervals for all bilateral trunk and lower limb muscles with light and moderate to vigorous physical activities, is presented in Supplementary Table 2.
In multiple regression analysis adjusting for age and FMA-LE, trunk muscle thickness was not independently associated with sedentary behavior (Table 3).
Table 3. Multiple regression models for sedentary time.
| Model / Independent variables | Unstandardized B | standard error (SE) | Standardized β | 95% CI | VIF | |
| Model 1: Unaffected side diaphragm | ||||||
| Unaffected-side diaphragm | −31.836 | 19.727 | −0.31 | −72.75 to 9.07 | 1.15 | |
| Age | 0.128 | 0.153 | 0.16 | −0.19 to 0.45 | 1.12 | |
| FMA-LE | −0.219 | 0.364 | −0.12 | −0.97 to 0.54 | 1.14 | |
| Model 2: Affected side internal oblique | ||||||
| Affected side internal oblique | −5.587 | 3.166 | −0.34 | −12.15 to 0.98 | 1.28 | |
| Age | −0.001 | 0.145 | −0.01 | −0.30 to 0.30 | 1.22 | |
| FMA-LE | −0.441 | 0.301 | −0.29 | −1.07 to 0.18 | 1.34 | |
| Model 3: Unaffected side internal oblique | ||||||
| Unaffected side internal oblique | −4.830 | 2.513 | −0.37 | −10.04 to 0.38 | 1.35 | |
| Age | 0.038 | 0.141 | 0.05 | −0.26 to 0.33 | 1.25 | |
| FMA-LE | −0.487 | 0.293 | −0.32 | −1.09 to 0.12 | 1.45 | |
Data are presented as unstandardized coefficients (B), standard errors (SE), standardized coefficients (β), 95% confidence intervals (CI), and variance inflation factors (VIFs). The dependent variable was sedentary behavior percentage (%).CI: confidence interval; FMA-LE: Fugl–Meyer Assessment for the Lower Extremity; VIF: variance inflation factor.
Although the multivariable models were not significant, the direction of the regression coefficients was consistent with the univariate findings (Table 3). Residual diagnostics revealed no multicollinearity, with VIF values of 1.12–1.45 across all models.
DISCUSSION
This study examined the associations between muscle thickness and objectively measured daily physical activity in ambulatory individuals with chronic post-stroke hemiplegia. In univariate analysis, greater thickness of the diaphragm and internal oblique muscles was associated with less sedentary behavior. However, these associations were no longer significant after adjustment for age and FMA-LE. These findings suggest that the observed associations may be confounded by age and motor impairment rather than representing independent effects. Therefore, the current findings require cautious interpretation.
The observed association between trunk muscle thickness and sedentary behavior may be clinically relevant because the diaphragm and internal oblique muscles contribute to trunk stabilization and postural control16,17,18,19). Reduced thickness of these muscles may therefore be associated with lower daily movement. However, because of the cross-sectional design, the direction of this relationship remains unclear.
No significant associations were found for light physical activity or moderate-to-vigorous physical activity. These activity levels are likely influenced by multiple factors beyond muscle thickness20, 21), and the very low amount of moderate-to-vigorous physical activity in this sample may also have limited the ability to detect such relationships. In addition, muscle thickness alone may not fully reflect muscle function after stroke. Therefore, the present findings should be interpreted as preliminary.
This study has several limitations. First, the sample size was relatively small (n=26), potentially increasing the risk of type II errors. Indeed, our post-hoc power analysis yielded a 0.54 statistical power for univariate correlations under the current sample size. Therefore, the lack of significant correlations between physical activity metrics and lower limb muscle thickness should be carefully interpreted as these nonsignificant findings may reflect insufficient statistical power rather than a true absence of biological association. To confirm these associations, future larger-scale studies are warranted. Second, although the intra-rater reliability of muscle thickness measurements was validated in healthy adults to confirm technical proficiency before this study, post-stroke muscle alterations, including spasticity and tissue architectural changes, may impact measurement reproducibility. Future studies should directly confirm the reliability of these ultrasonographic metrics within the population with stroke. Third, we did not evaluate trunk and lower limb muscle strength or quality, including intramuscular fat infiltration, which could also affect physical activity. Finally, the cross-sectional design of this study precluded the identification of causal relationships between muscle thickness and sedentary behavior.
Larger longitudinal or interventional studies are needed to clarify whether trunk muscle characteristics are independently associated with sedentary behavior and whether they are modifiable rehabilitation targets.
In ambulatory individuals with chronic post-stroke hemiplegia, greater diaphragm and internal oblique muscle thickness was associated with less sedentary behavior in univariate analysis, but not after adjustment for age and motor impairment. Trunk muscle morphology may be related to sedentary behavior, although its independent clinical significance requires further investigation
Funding
No funding was received.
Conflict of interest
The authors declare that there are no conflicts of interests.
Supplementary
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