Predictors of gait function among geriatric ındividuals living with chronic stroke

Authors

Abstract

AimGait impairment is a major cause of disability in older adults following stroke. Lower extremity spasticity and trunk muscle dysfunction are common post-stroke impairments; however, their relative contribution to gait performance in geriatric individuals with chronic stroke has not been clearly established.
MethodsThis cross-sectional observational study included geriatric individuals (≥65 years) living with chronic stroke. Lower extremity spasticity at the hip, knee, and ankle joints was assessed using the Modified Ashworth Scale. Trunk flexor and extensor muscle strength was evaluated using an isokinetic dynamometer at an angular velocity of 60°/s. Gait performance was assessed using the Tinetti Performance-Oriented Mobility Assessment. Associations between variables were analyzed using correlation analysis, and multiple linear regression was performed to identify independent predictors of gait performance.
ResultsGait performance was significantly and negatively correlated with spasticity levels at the hip, knee, and ankle joints, indicating that increased spasticity was associated with poorer gait function. Among these, ankle spasticity demonstrated the strongest independent association with gait performance. No significant associations were found between trunk flexor or extensor muscle strength and gait performance; therefore, trunk muscle strength was not retained as a predictor in the regression model.
ConclusionLower extremity spasticity, particularly at the ankle joint, is a primary determinant of gait performance in geriatric individuals with chronic stroke, whereas trunk muscle strength does not independently predict walking ability. These findings highlight the importance of targeting distal spasticity in rehabilitation strategies aimed at improving gait function in this population.

Keywords

Introduction

Walking is a fundamental motor skill that enables individuals to interact with their environment, maintain independence in daily activities, and preserve quality of life. However, age-related structural and functional changes in the musculoskeletal, nervous, and sensory systems lead to notable impairments in walking performance.¹ When a stroke is factored into this scenario, its effect on gait performance becomes even more significant. Chronic stroke observed in older adults further restricts mobility due to additional motor impairments such as muscle weakness, abnormal muscle tone (spasticity), and loss of postural control.²
Stroke survivors have identified walking recovery as a high-priority research need, and gait impairments persist in many individuals even three months after stroke.³ The combination of advanced age and post-stroke spasticity magnifies the challenge of regaining gait function, as elevated muscle tone contributes to abnormal gait.⁴ Several studies have explored the relationship between spasticity and gait function within this population. For instance, the prevalence of lower limb spasticity can impair balance and gait, leading to reduced walking speed and increased reliance on wheelchairs and caregiver support.⁵ Specific parameters of gait, such as movement smoothness during walking, are negatively affected by pronounced spasticity.⁶
The trunk plays a crucial role in maintaining stability and postural control, which are essential for efficient and coordinated gait performance. Previous studies have demonstrated that trunk strength is significantly associated with length of hospital stay, balance performance, and patients’ ability to perform transfer activities.^7,8 Although the adverse effects of spasticity on gait have been widely documented, the relative contribution of trunk strength—particularly in older adults who already exhibit age-related declines in postural control—remains underexplored.
This study aims to determine the extent to which lower extremity spasticity and trunk muscle strength predict gait performance in geriatric individuals with chronic stroke, thereby enhancing understanding of gait performance and informing strategies to improve mobility and functional independence.

Materials and Methods

ParticipantsThis study was conducted with 30 geriatric individuals diagnosed with chronic hemiplegia following a stroke. Participants were included in the study if they have a diagnosis of hemorrhagic or ischemic stroke confirmed by computed tomography (CT) or magnetic resonance imaging (MRI), have no history of a previous stroke, were diagnosed with stroke at least 6 months prior to the study following a cerebrovascular event, are 65 years of age or older, and scored 3 or above on the Functional Ambulation Classification (FAC). Participants were excluded from the study if they had an additional neurological disorder other than stroke, had undergone surgical intervention within the past 6 months, or had any visual or hearing impairment.
ProcedureParticipants were recruited from a university hospital’s neurorehabilitation outpatient clinic between December and January 2025/2026.
All assessments were performed by the same experienced physiotherapist to ensure reliability. Demographic and clinical data, including age, sex, height, weight, body mass index (BMI), affected side, and dominant side, were recorded.


Outcome measuresAssessment of spasticity: Lower extremity spasticity was evaluated using the Modified Ashworth Scale (MAS), which grades muscle tone on a six-point scale ranging from 0 (no increase in muscle tone) to 4 (rigid in flexion or extension). In the MAS, the level of resistance to passive joint range of motion in the extremity is measured. Spasticity was assessed on the affected side by passively moving the joints and evaluating resistance in the hip flexors, knee flexors, and ankle plantarflexors. The mean score from these regions was used for subsequent analysis.⁹ The MAS is widely used in individuals with stroke to assess spasticity and to aid in understanding motor impairment severity as well as rehabilitation outcomes.^10,11
Trunk muscle strength: Trunk flexor and extensor muscle strength were assessed using an isokinetic dynamometer (e.g., Biodex System 4 Pro, Biodex Medical Systems, Shirley, NY, USA). Participants were securely positioned in the dynamometer chair, with the pelvis and thighs stabilized by straps to minimize compensatory movements. The range of motion determined for the participants during trunk movements was 65°, extending from 15° of trunk extension to 50° of trunk flexion. This range represents the trunk motion typically observed during the performance of activities of daily living.¹² After a warm-up and familiarization trial, three maximal voluntary contractions were performed at an angular velocity of 60°/s, and the peak torque values (Nm) for trunk flexors and extensors were recorded. The highest peak torque obtained from the three trials was used for analysis.¹³ Isokinetic dynamometry is widely used in individuals with neurological conditions, including stroke, to quantify trunk muscle strength objectively and to evaluate functional impairment and rehabilitation outcomes.¹⁴
Gait Function: Gait function was evaluated using the Tinetti Performance-Oriented Mobility Assessment (POMA) test, consisting of two subscales: gait and balance. This test assesses various aspects of walking and balance, including step initiation, step length and height, symmetry, continuity, trunk stability, and sitting balance. Participants were allowed to use their customary walking aids (e.g., cane or walker) during the assessment when required, in accordance with the standard administration procedures of the test. Administration typically takes 5–10 minutes and access to basic equipment, including a stopwatch, a chair, a 5-pound (≈2.5 kg) object, and a 15-foot (≈5 m) walking space. Each item is rated on a 0–2 ordinal scale, where lower scores reflect greater impairment, with a total maximum score of 28.¹⁵ In the present study, the total POMA score was used in the analysis to represent overall mobility performance, including both gait and balance components.
Power AnalysisIn the absence of prior data specific to this population, a moderate effect size was assumed in accordance with Cohen’s guidelines for behavioral and clinical research.¹⁶ An a priori power analysis for correlation analysis was performed using G*Power software (version 3.1), with an assumed effect size of r = 0.50, an alpha level of 0.05, and a statistical power of 80%. Based on these parameters, the minimum required sample size was calculated as 29 participants. Accordingly, a total of 30 geriatric individuals with chronic stroke were included in the study.
Ethical ApprovalParticipation was voluntary and anonymous. All participants provided written informed consent before data collection. The Ethics Committee of İstanbul Atlas University approved this study (Date: 2025-12-22, No: 11/39).
Statistical AnalysisStatistical analyses were performed using SPSS v26. Normality was tested using the Shapiro–Wilk test. Data were presented as mean ± standard deviation (SD) or percentage (%). The relationships between spasticity, trunk muscle strength, and gait performance were analyzed using Pearson’s correlation coefficient (r). Variables that showed significant correlations with gait performance were subsequently entered into a multiple linear regression analysis to determine independent predictors of gait function. Statistical significance was set at p < 0.05.
Reporting GuidelinesThis cross-sectional observational study employed convenience sampling and was reported in accordance with the STROBE guidelines.

Results

A total of 30 individuals with chronic hemiplegia were included in the study (Supplementary Table 1). The mean age of the participants was 72.06 ± 4.76 years. Of the participants, 11 (36.7%) were women and 19 (63.3%) were men. The mean BMI was 25.52 ± 2.49 kg/m². All participants were right-hand dominant. The mean time since stroke onset was 52.5 ± 36.5 months, and among the participants, 18 had ischemic stroke while 12 had hemorrhagic stroke. The affected side was the right in 11 participants (36.7%) and the left in 19 participants (63.3%).
A correlation analysis was performed to examine the relationships among lower-extremity spasticity, trunk muscle strength, and gait performance. According to the results as shown in Supplementary Table 2, the POMA score was negatively correlated with spasticity levels of the knee (r = –0.691, p < 0.001), hip (r = –0.425, p = 0.019), and ankle (r = –0.825, p < 0.001) as measured by the Modified Ashworth Scale. In contrast, there was no significant correlation between gait score and trunk flexor (r = 0.256, p = 0.172) or extensor muscle strength (r = 0.227, p = 0.228).

Multiple linear regression analysis was conducted to identify independent predictors of gait function (Supplementary Table 3). The overall regression model was statistically significant (p = 0.001) and explained 60.5% of the variance in POMA scores (R² = 0.605). Among the variables included in the model, ankle spasticity (β = 0.585, p < 0.05) emerged as the strongest independent predictor of gait performance, followed by hip (β = 0.454) and knee spasticity (β = 0.4122).

Discussion

This study investigated the extent to which lower extremity spasticity and trunk muscle strength predict gait performance in geriatric individuals living with chronic stroke. The results demonstrated significant negative correlations between gait function and spasticity levels of the knee, hip, and ankle joints, indicating that higher muscle tone is associated with poorer gait performance. Trunk muscle strength did not show a significant correlation with gait performance and was therefore not included as a predictor.
Spasticity is a common sequela of stroke. According to a systematic review, approximately 25.3% of stroke survivors develop spasticity, and this rate increases up to 39.5% in patients with paresis following a first-ever stroke.¹⁷ Spasticity after stroke prominently impacts gait performance, thereby limiting patients’ independence and overall functional mobility. Recent evidence also suggests that chronic spasticity contributes to secondary biomechanical changes, including muscle shortening and joint stiffness, which may further exacerbate gait impairments over time.¹⁸
Although studies have demonstrated that lower limb spasticity adversely affects balance, gait performance, and fall risk in post-stroke individuals, the extent of these impairments may vary depending on the severity of the spasticity.⁵ In the participants of this study, while the knee and hip exhibited mild to moderate levels of spasticity based on the MAS, ankle spasticity was comparatively higher, approaching the upper range of moderate severity. This pattern was consistent with the regression analysis, in which ankle spasticity demonstrated the strongest independent association with gait performance, followed by hip and knee spasticity. Our findings align with those of Freire et al,¹⁹ who reported that higher MAS scores, particularly in the ankle plantar flexors, are associated with reduced walking ability and poorer functional mobility in individuals with chronic stroke. In the recent observational study examining functional performance across spasticity severity levels using balance and gait ability tests, only gait tests involving directional changes differentiated individuals with higher ankle plantar flexor spasticity from those without.²⁰ This aligns with our findings, highlighting that distal spasticity primarily affects gait-related parameters.
Trunk muscle impairment is a frequent issue following a stroke, resulting in difficulties with everyday activities, balance, and independent walking.²¹ Earlier studies have demonstrated that trunk-related measures are closely associated with balance, gait, and overall functional ability in individuals with post-stroke hemiplegia.^12,22 In addition, trunk muscle mass decreases with age; therefore, assessing and addressing trunk function within rehabilitation is considered particularly important for geriatric individuals living with stroke.
While the trunk plays a crucial role in maintaining stability and gait after stroke, most research has focused on trunk control rather than muscle strength. Evidence on the relationship between trunk strength and gait is limited in patients with stroke; however, since muscle strength is a key component of trunk control, it is often assumed that greater trunk strength contributes to better walking performance.²³ In the present study, however, no significant correlation was found between gait performance and either trunk flexor or extensor strength. This finding contrasts with earlier research suggesting that greater trunk muscle strength is associated with improved gait speed, balance, and overall functional mobility in individuals with stroke.^12,24 One possible explanation for this contradiction may lie in the advanced age and chronic stage of our sample, where long-term compensatory strategies and neuromuscular adaptations could have diminished the contribution of trunk muscles to gait control. Moreover, our participants demonstrated relatively high trunk torque values compared with those in previous studies,^13,22,25 suggesting a possible “ceiling effect,” that is, limited variability at the upper range of strength scores, which may have masked potential correlations. Another possible explanation is that, in the chronic phase of stroke, gait performance depends more strongly on distal factors such as spasticity, balance control, and sensory feedback rather than on proximal trunk strength alone. Indeed, our results showed that spasticity of the ankle, hip, and knee joints—particularly at the ankle—was a more powerful predictor of gait outcomes. Taken together, these findings suggest that while trunk function remains essential for maintaining postural stability and balance, its direct contribution to walking ability in geriatric individuals with chronic stroke may be overshadowed by the effects of distal motor impairments and long-term neuromuscular adaptations.

Limitations

This study has some limitations. The absence of a control group limited our ability to compare and interpret the isokinetic strength values in a broader clinical context. In addition, trunk function was evaluated solely through muscle strength measurements, and no specific assessment of trunk control or postural coordination was included; therefore, the complex contribution of trunk control to gait performance may not have been fully captured. Lastly, gait performance was evaluated using a clinical observational scale (POMA) rather than objective instrumented gait analysis, which may provide more detailed information about walking performance.

Conclusion

This study demonstrates that lower extremity spasticity, particularly at the ankle joint, is a significant predictor of gait performance in geriatric individuals with chronic stroke. In contrast, trunk muscle strength did not independently contribute to walking ability in this population. These findings suggest that distal motor impairments more strongly influence gait performance in the chronic and geriatric stroke population than proximal trunk strength. Targeting lower limb spasticity may therefore be a key focus in rehabilitation strategies aimed at improving gait function.

Declarations

Abbreviations

BMI, body mass index;
CT, computed tomography;
FAC, Functional Ambulation Classification;
MAS, Modified Ashworth Scale;
MRI, magnetic resonance imaging;
POMA, Performance-Oriented Mobility Assessment;
SD, standard deviation;
SPSS, Statistical Package for the Social Sciences;
STROBE, Strengthening the Reporting of Observational Studies in Epidemiology.

References

1. Busch TDA, Duarte YA, Pires Nunes D, et al. Factors associated with lower gait speed among the elderly living in a developing country: a cross-sectional population-based study. BMC Geriatr. 2015;15(1):35. doi:10.1186/s12877-015-0031-2
   Article PubMed Google Scholar
2. Banky M, Ross H, Williams G, Kahn M. The distribution and severity of lower-limb hypertonicity and spasticity differentially impacts walking speed in people with neurological injuries. Disabil Rehabil. 2024;47(16):4176-4183.
   PubMed Google Scholar
3. Rudberg AS, Berge E, Laska AC, et al. Stroke survivors’ priorities for research related to life after stroke. Top Stroke Rehabil. 2021;28(2):153-158. doi:10.1080/10749357.2020.1789829
   Article PubMed Google Scholar
4. Li S. Ankle and foot spasticity patterns in chronic stroke survivors with abnormal gait. Toxins (Basel). 2020;12(10):646. doi:10.3390/toxins12100646
   Article PubMed Google Scholar
5. Silva MRE, Jacinto J. Velocity determinants in spastic patients after stroke—a gait analysis study. Neurol Int. 2020;12(3):48-54. doi:10.3390/neurolint12030011
   Article PubMed Google Scholar
6. Garcia FDV, da Cunha MJ, Schuch CP, et al. Movement smoothness in chronic post-stroke individuals walking in an outdoor environment—a cross-sectional study using IMU sensors. PLoS One. 2021;16(4):e0250100. doi:10.1371/journal.pone.0250100
   Article PubMed Google Scholar
7. Karaca O, Sütçü G, Kılınç M. The effects of trunk and extremity functions on activities of daily living, balance, and gait in stroke. Neurol Res. 2023;45(4):312-318. doi:10.1080/01616412.2022.2142424
   Article PubMed Google Scholar
8. Karthikbabu S, Verheyden G. Relationship between trunk control, core muscle strength and balance confidence in community-dwelling patients with chronic stroke. Top Stroke Rehabil. 2021;28(2):88-95. doi:10.1080/10749357.2020.1783896
   Article PubMed Google Scholar
9. Vidmar T, Kregar NG, Puh U. Reliability of the Modified Ashworth Scale after stroke for 13 muscle groups. Arch Phys Med Rehabil. 2023;104(10):1606-1611. doi:10.1016/j.apmr.2023.04.008
   Article PubMed Google Scholar
10. Munin MC, Camões-Barbosa A, Cordero-García C, et al. Efficacy and safety of incobotulinumtoxinA in older patients with upper limb spasticity: a pooled analysis. Geriatrics. 2025;10(6):155. doi:10.3390/geriatrics10060155
    Article PubMed Google Scholar
11. Sahbaz T, Medin-Ceylan C. Stroke severity to determine musculoskeletal symptoms in family caregivers. Rev Latino-Am Enfermagem. 2023;31:e4004.
    PubMed Google Scholar
12. Quintino LF, Franco J, Gusmão AFM, et al. Trunk flexor and extensor muscle performance in chronic stroke patients: a case-control study. Braz J Phys Ther. 2018;22(3):231-237. doi:10.1016/j.bjpt.2017.12.002
    Article PubMed Google Scholar
13. Rabelo M, Fachin-Martins E. Inter-rater and test-retest reliabilities of the isokinetic measurements: assessing strength and endurance of the trunk muscles in two different protocols for able-bodied and post-stroke hemiparesis. Top Stroke Rehabil. 2018;25(6):424-431. doi:10.1080/10749357.2018.1481568
    Article PubMed Google Scholar
14. Bohannon RW. Measurement of trunk muscle strength after stroke: an integrative review. Top Stroke Rehabil. 2022;29(3):173-180. doi:10.1080/10749357.2021.1904583
    Article PubMed Google Scholar
15. Yücel SD, Şahin F, Doğu B, et al. Reliability and validity of the Turkish version of the Performance-Oriented Mobility Assessment I. Eur Rev Aging Phys Act. 2012;9(2):149-159. doi:10.1007/s11556-012-0096-2
    Article PubMed Google Scholar
16. Cohen J. Statistical power analysis for the behavioral sciences. 2nd ed. Hillsdale, NJ: Lawrence Erlbaum Associates; 1988.
    PubMed Google Scholar
17. Zeng H, Chen J, Guo Y, Tan S. Prevalence and risk factors for spasticity after stroke: a systematic review and meta-analysis. Front Neurol. 2021;11:616097. doi:10.3389/fneur.2020.616097
    Article PubMed Google Scholar
18. Persson CU, Holmegaard L, Redfors P, et al. Increased muscle tone and contracture late after ischemic stroke. Brain Behav. 2020;10(2):e01509. doi:10.1002/brb3.1509
    Article PubMed Google Scholar
19. Freire B, Bochehin do Valle M, Lanferdini FJ, et al. Cut-off score of the Modified Ashworth Scale corresponding to walking ability and functional mobility in individuals with chronic stroke. Disabil Rehabil. 2023;45(5):866-870. doi:10.1080/09638288.2022.2037753
    Article PubMed Google Scholar
20. An S, Lee D, Park D, Lee K. Differences in functional performance and minimal detectable change according to levels of ankle plantar flexor spasticity in patients with chronic stroke. J Clin Med. 2025;14(20):7358. doi:10.3390/jcm14207358
    Article PubMed Google Scholar
21. Akkurt L, Yağcıoğlu GA, Aksoy CC, Yaman F. The effect of trunk control on sitting balance and upper extremity functions in patients with subacute stroke. Neurol Sci. 2024;45(12):5807-5812. doi:10.1007/s10072-024-07817-w
    Article PubMed Google Scholar
22. Yanartaş G, Karakoyun A. Isokinetic analysis of trunk muscles in stroke patients and its association with functional parameters. J Stroke Cerebrovasc Dis. 2020;29(12):105329. doi:10.1016/j.jstrokecerebrovasdis.2020.105329
    Article PubMed Google Scholar
23. Marchesi G, Arena G, Parey A, et al. A strong core for a strong recovery: a scoping review of methods to improve trunk control and core stability of people with different neurological conditions. Appl Sci. 2024;14(11):4889. doi:10.3390/app14114889
    Article PubMed Google Scholar
24. Karatas M, Çetin N, Bayramoglu M, Dilek A. Trunk muscle strength in relation to balance and functional disability in unihemispheric stroke patients. Am J Phys Med Rehabil. 2004;83(2):81-87. doi:10.1097/01.phm.0000107486.99756.c7
    Article PubMed Google Scholar
25. Silva P, Franco J, Gusmão A, et al. Trunk strength is associated with sit-to-stand performance in both stroke and healthy subjects. Eur J Phys Rehabil Med. 2015;51(6):717-724.
    PubMed Google Scholar

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About This Article

Received:

February 23, 2026

Accepted:

April 24, 2026

Published Online:

May 1, 2026