Hrev_master Healthcare in Low-resource Settings 2023; volume 11(s1):11182 Relationship between postural stability and fall risk in young adult after lower limb muscle fatigue Mohd Khairuddin Mohd Safee,1,2 Noor Azuan Abu Osman1 1Department of Biomedical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur, Malaysia; 2Department of Science Rehabilitation, Faculty of Health Sciences, University Sultan Zainal Abidin, Kuala Nerus, Terengganu, Malaysia Abstract Introduction: Muscle fatigue can reduce body balance and activity of daily living tasks. Therefore, this study aims to identify the correlation between postural stability and fall risk due to mus- cle fatigue. The components in postural stability include Overall Stability Index (OSI), Anterior-Posterior Stability Index (APSI), and Mediolateral Stability Index (MLSI). Design and Methods: A total of seven healthy adults aged 31.1±7.4 years were recruited in this study. The sit-to-stand (STS) protocol was used to induce lower limb muscle fatigue, while pos- tural stability and fall risk were assessed using the Biodex Balance System (BBS) before and after muscle fatigue. Result: The result showed a significant increase in postural stability index after fatigue only for OSI with p<0.05, while no significant difference was found on APSI and MLSI with p=0.157 and p=0.109 respectively. However, the mean score for the postu- ral stability index showed an increase in percentage with 47.8% in OSI, 26.3% in APSI and 46.8% in MLSI. Furthermore, fall risk showed no significant differences with p=0.149, but the mean score data increased by 16.7% after fatigue. The correlation between fall risk and OSI was significant with p<0.05, while MLSI had a significant negative correlation with APSI (p<0.05). Conclusions: Based on the results, the young adults had reduced overall postural stability but were less affected by fall risk after muscle fatigue. The positive correlation between OSI and fall risk indicated that their overall postural stability can induce the fall risk after muscle fatigue. Therefore, young adults need to be aware of their fatigue symptoms during prolonged exercise that can increase fall risk potential. Introduction Fatigue can be defined as lack of energy, exhaustion, an over- whelming sense of tiredness, and difficulties in performing a vol- untary activity.1 Enoka and Duchateau2 define fatigue as “a dis- abling symptom in which physical and cognitive function is limit- ed by interactions between performance and perceived fatigabili- ty”. Muscle fatigue can affect balance, proprioception, coordina- tion, and reduce contractile muscle ability.3 There are several pos- sibilities for people experiencing muscle fatigue, such as pro- longed maintenance of the muscle force,4 incline walking,5 pro- longed isometric tasks, and repetitive movements.6 Standing up and sitting down is an everyday activity often per- formed spontaneously by healthy subjects.7 However, repetitive STS activity will produce fatigue and decrease postural stability.8 Prolonged voluntary contractions of lower limb muscles during the STS also affect motor control and body balance.9 Although fatigue reduces postural stability, a therapist provides rehabilita- tion programs for the patients to increase their ability to maintain good postural stability in daily living activities and complex tasks.10 In rehabilitation, physical actions such as exercises and repet- itive movement also increase patients’ ability to perform activities of daily living and recover their physical performance.11 However, fatigue due to prolonged physical activity negatively affects bal- ance control and increases the risk of falling even after the cessa- tion of exercise.12 Previous studies showed that elevation in the risk of falls and increasing postural instability are caused by insuf- ficient attention, memory, and executive functions.13 Arjunan et al.,4 mentioned that localized muscle fatigue might be a risk factor in causing slip-induced falls. Other studies also reported that fatigue can negatively affect muscle force-generating capacity,14 balance,15 and increase the asymmetry between the lower limbs during standing.16 In recent years, a few studies have investigated the relation- ship between postural stability during standing and muscle fatigue.3,7 However, none examined the relationship between pos- tural stability and fall risk due to muscle fatigue. Therefore, this preliminary study was conducted to identify the relationship between postural stability and fall risk among healthy young adults before and after lower limb muscle fatigue. The results will be beneficial to the young adult in performing an exercise, and therapists in identifying the effect of fatigue due to prolonged muscle activity on the patients. In addition, the results are expect- ed to help young adults plan their prolonged activities and thera- pists in planning better treatments to increase postural stability and reduce fall risk. Article Significance for public health Understanding the relationship between postural stability and fall risk enables therapists to handle and rehabilitate patients who have a deficit in one of these areas with greater care. This is because postural stability and fall risk showed a significant association in this study, which suggests that a deficiency in one of these aspects might be related to the other. The data in this study can be utilized to educate young adults about the importance of maintaining postural stability to avoid falling. It is recommended that young adults monitor their muscle exhaustion levels throughout a repetitive activity and take a break when fatigue sets in. [Healthcare in Low-resource Settings 2023; 11(s1):11182] [page 83] No n- co mm er cia l u se on ly Design and Methods This was a preliminary study conducted to identify the corre- lation between postural stability and fall risk due to muscle fatigue. The data were collected from 2019 and stopped in 2020 due to the COVID-19 pandemic and the targeted population was healthy adults between the ages of 20 and 40 years. A total of seven partic- ipants aged 31.1±7.4 years participated in this study. Participants were excluded when they have any medical history regarding mus- cular or neurological disorders, lower limb injury, or balance dis- orders. Before the experiment commenced, the subjects read and signed a consent form after explaining the experimental protocols verbally. Institutional Review Board from University Medical Committee approved the test procedure (MEC 895.7). In addition, this study was registered in a WHO-compliant trial registry (Thai Clinical Trials Registry: TCTR20210805001). All subjects performed fatigue protocol with repeated STS, the standard chair used in this protocol was a bench without armrests, 44 cm in-depth, 440 cm in width, 46cm in height. STS was per- formed with patients standing straight, knees completely extended, feet at the same distance apart as the hips, and upper limbs crossed in the anterior region. Subjects’ feet were barefoot and shoulder- width apart, the heels and toes were marked on the floor at the same level to guarantee that the feet remained stationary through- out the procedure. The subjects were asked to stand and then sit repeatedly to the metronome’s beat until they are unable to com- plete the procedure. The fatigue protocol was terminated when one of the following conditions were met: i) voluntary exhaustion occurred, ii) repeated STS movement remained below 35 beats/min, or iii) a 30-minute cut-off time was reached.3 The subjects’ postural stability and fall risk were assessed using Biodex Balance System SD Inc., Shirley, NY (BBS), a com- puterized screening test. The BBS is a round platform that can move freely and is used to assess an individual’s ability to maintain either static or dynamic postural stability as well as the anteropos- terior and mediolateral axes. Patients were asked to look at a screen in the front to ensure the markers were in the midpoint of the targeted position. The vertical projection was kept with their center of gravity on the platform, then the Anterior-Posterior Stability Index (APSI), Medial-Lateral Stability Index (MLSI), and Overall Stability Index (OSI) were used to calculate the BBS postural stability score. For the fall risk measurement, the test began with an initial platform setting of 6 and ends with a setting of 2. The BSS was used to measure the degree of tilt in each axis, providing an average sway score and calculated in the BBS’s soft- ware to identify the fall risk index. All the balance tests required that the subjects stand on the BBS without footwear. The BBS was used to assess the body displacement of sagittal and frontal plane motion, the x-direction represents the horizontal displacements along Medial-Lateral (ML) axes, while the y-direction represents vertical along Anterior-Posterior (AP) axes. Furthermore, the bipedal stance test to measure the postural stability score under the static level, and the fall risk under the dynamic level was accom- plished using BBS. The subjects were asked to maintain a static standing position for 20s during the postural stability test which was performed five times with 10s between each, and all the data were averaged. The subjects were told to maintain their foot’s placement on the platform throughout the balance test. All data were entered into a database and were verified before the analysis. Subsequently, the data were summarized in means as well as stan- dard deviations or percentages forms. The normality of the vari- ables’ distribution was tested using Shapiro–Wilk test due to the small number of subjects, while the Wilcoxon signed-rank test was used in identifying the significant difference before and after fatigue on postural stability and fall risk. Furthermore, Spearman’s rho correlation coefficient was used to examine the relationship between the study variables as all variables were not normally dis- tributed. All statistical analysis was performed using the statistical software SPSS26.0 (Version26, IBMCorp., Armonk, NY). Results and Discussions All the participants were recruited before the Covid-19 pan- demic started, the age ranged between 20 and 40 years with a mean of 31.1±7.4 years. On average, the mean scores of body mass index ranges (BMI) were normal namely 23.1±1.8. All subjects were instructed to perform experimental protocols and the results were recorded as shown in Table 1. Article Table 1. Subject’s demographic data (mean ± SD). Subjects (n=7) Age (Years) 31.1±7.4 Height (cm) 168.6±2.7 Weight (kg) 65.9±5.3 BMI (kg/cm2) 23.1±1.8 Figure 1. Mean of the postural stability before and after muscle fatigue. Figure 2. Mean of the fall risk before and after muscle fatigue. [page 84] [Healthcare in Low-resource Settings 2023; 11(s1):11182] No n- co mm er cia l u se on ly The results showed an increase in postural stability index scores after fatigue with OSI 47.8 %, APSI 26.3%, and MLSI 46.8 %. Figure 1 shows the histogram of the three postural stability indexes scores before and after muscle fatigue. Based on the result, significant differences before and after fatigue were found only on the OSI (p<0.05) but not on APSI (p=0.157) and MLSI (p=0.109). The statistical analyses for this result are summarized in Table 2. The fall risk analysis results presented in Figure 2 showed that the mean score increased after fatigue, but the increase was not sig- nificant as demonstrated by p=0.149. Furthermore, the scoring per- centage (%) was determined by normalizing the data to the pre- fatigue score and calculating the increasing value in each subject. The histogram showed a 16.7% increase in fall risk after fatigue indicating that fatigue has the potential to increase fall risk. Table 3 presents the statistical analysis for the fall risk test, while Figure 3 shows the Biodex score for postural stability and fall risk. Spearman’s rho correlation coefficient was used to assess the rela- tionship between postural stability and fall risk. The results showed that there was a significant correlation between fall risk and OSI with r= .81, p = 0.028, N=7) but not with APSL p=0.843 and MLSI p=0.640. However, the APSI and MLSI showed a sig- nificant negative correlation with each other as indicated by r= - .81, p=0.028, N=7. This shows that the score in APSI and MLSI correlated, Table 4 presents the statistical analysis for the correla- tions. One of the objectives of this study was to investigate the effect of muscle fatigue on postural stability pre and post fatigue. The results showed that the subjects demonstrated an increase in postu- ral stability but only OSI showed a significant increase after fatigue compared to APSL and MLSI. However, all mean postural stability indexes showed an increase after fatigue. The OSI indicat- ed that fatigue has a significant effect on increasing postural stabil- ity. This result aligns with previous studies that showed a relation- ship between fatigue and postural sway,8,17 specifically with the anterior-posterior and medio-lateral center pressure.8 This is pre- sumably due to the effect of the sensorimotor process that can also affect the proprioceptive system and force-generating capacity.18 Based on the results, the young adult subjects were considered to have good proprioception given that their APSI and MLSI showed no significant increase in postural stability. The subjects in this study have an excellent vestibular system that includes the propri- oception, inner ear, and vision which send the sensory information used for balance.19 Other factors that contribute to postural stability were mini- mized by filtering the subjects, hence, individuals on medication, have musculoskeletal conditions, or neurological deficits were not recruited to avoid potential confounding factors affecting balance and falls.13,20 Horak21 mentioned that a few components might affect postural stability, such as control of dynamics, biomechani- cal constraints, cognitive processing, sensory and movement Article Table 3. Fall risk score pre and post fatigue. Median Interquartile Range SD p Fall Risk Pre Fatigue 1.80 1.20 0.81 0.149 Post Fatigue 2.50 1.10 0.94 *p<0.05. Table 4. Correlations between fall risk and postural stability index (OSI, APSI, MLSI). Fall Risk OSI APSI MLSI Spearman's rho Fall Risk Correlation Coefficient 1.000 .809* .093 .217 p . .028 .843 .640 N 7 7 7 7 OSI Correlation Coefficient .809* 1.000 .000 .490 p .028 . 1.000 .264 N 7 7 7 7 APSI Correlation Coefficient .093 .000 1.000 -.808* p .843 1.000 . .028 N 7 7 7 7 MLSI Correlation Coefficient .217 .490 -.808* 1.000 p .640 .264 .028 . N 7 7 7 7 *p<0.05 Table 2. Postural stability index result pre and post fatigue. Median Interquartile Range SD p OSI Pre fatigue 0.30 0.20 0.11 0.026 Post Fatigue 0.50 0.01 0.09 APSI Pre fatigue 0.20 0.20 0.13 0.157 Post Fatigue 0.30 0.30 0.13 MLSI Pre fatigue 0.20 0.10 0.08 0.109 Post Fatigue 0.20 0.30 0.17 p<0.05. [Healthcare in Low-resource Settings 2023; 11(s1):11182] [page 85] No n- co mm er cia l u se on ly strategies, as well as orientation in space. Humans can maintain posture by restoring balance, but this requires a great ability to control the Center Of Mass (COM) above an area of equilibrium,22 maintain the Center Of Pressures (COP) to the base of support,23 and control balance strategy during perturbation.24 Furthermore, the sensory strategy for balance control also demonstrated the important role of integrated visual, vestibular, and proprioception aspects in quiet standing.19 The fall risk assessment for the young adult subjects indicated that the mean score percentage increased after fatigue but was not significant. This indicates that young adults have the potential to maintain their fall risk without other factors. However, the result showed a significant correlation between overall postural stability and fall risk after fatigue. In general, postural sway can induce an increase in fall risk after muscle fatigue for young adults. Previous studies that showed increased fall risk and decreased postural con- trol in young adults mentioned the contribution of both physical and cognitive fatigue.17,25 In contrast, this study only provided 30 minutes cut-off time for the fatigue protocol which did not signif- icantly increase fall risk among young adults. The limited-time in this study might not be sufficient to show the severity of fatigue. This aligns with Kamitani et al.26 which reported a positive associ- ation between fatigue severity and fall frequency. The positive relationship between fall risk and overall stability indicates that increasing postural sway can indirectly increase the fall risk. However, further studies with a more extended period of fatigue protocol are needed. These results are consistent with previous studies which also reported that fatigue can increase the fall risk.8,15,20,27–29 A few fac- tors related to fatigue were mentioned including lower limb amputee, pain, diseases, and repetitive movements. In other stud- ies, most of the risk factors associated with falls were primarily elderly patient cohorts and not young adults.5,30–33 Furthermore, a higher rate of falls was detected in older adults with more severe fatigue than in those who reported milder fatigue,26 but the cohort population in this study is younger compared to that of previous studies, with an age range of 20 to 40 years old. The results did not show a significant increase in fall risk in younger subjects, but the mean scores indicated a rise in fall risk by 16.7%. Nevertheless, this minimum risk needs to be considered as a potential of increas- ing falling. This implies that the age factor can be one of the com- ponents in identifying the fall risk. Considering that this is a preliminary study, it has several lim- itations, first, only seven participants were recruited due to the COVID-10 pandemic and only focused on healthy young adults. Therefore, it is suggested that further studies be conducted on a larger amount of subjects with different age populations. Second, this assessment needs to be carried out for different levels of body mass index, as well as gender and condition of patients. It can also be a pilot study to identify the correlation between muscle fatigue and fall risk in different conditions and situations. This study pro- tocol can be used for lower-limb amputees to analyze their adapta- tion during muscle fatigue and develop a rehabilitation program. Conclusions Fatigue of the lower limb muscles can impair overall postural stability of the body. Therefore, understanding the relationship between postural stability and fall risk enables therapists to handle and rehabilitate patients who have a deficit in one of these areas with greater care. This is because postural stability and fall risk showed a significant association in this study, which suggests that a deficiency in one of these aspects might be related to the other. By using a therapy method to improve one of these aspects, the other characteristics can also be improved concurrently. Therefore, the results have significant implications for monitoring fall risk and postural stability due to acute muscular exhaustion caused by recurrent multi-joint exercises and repetitive activities, mainly in the lower limb muscles. Additionally, the data can be utilized to educate young adults about the importance of maintaining postural stability to avoid falling. It is recommended that young adults monitor their muscle exhaustion levels throughout a repetitive activity and take a break when fatigue sets in. References 1. Gruet M, Temesi J, Rupp T, et al. Stimulation of the motor cor- tex and corticospinal tract to assess human muscle fatigue. Neuroscience 2019;231:384–99. Article [page 86] [Healthcare in Low-resource Settings 2023; 11(s1):11182] Correspondence: Mohd Khairuddin Mohd Safee, Science Rehabilitation Department, Faculty of Health Sciences, University Sultan Zainal Abidin, 21300 Kuala Nerus, Terengganu, Malaysia. E-mail: mohdkhairuddin@unisza.edu.my Key words: Posture stability; muscle fatigue; fall risk; young adult. Acknowledgment: The author thanks to Faculty of Engineering, University of Malaya, Kuala Lumpur, Malaysia for their support and encouragemnets during this study. Contributions: All authors contributed to this study and were fully com- mitted to the process of data collection, editing, and writing manu- scripts. All authors have read and approved the final manuscript. Conflict of interests: The author declares no conflict of interest. Funding: This study received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Clinical trials: This study has registered in a WHO-compliant trial reg- istry (Thai Clinical Trials Registry: TCTR20210805001). Availability of data and materials: All data generated or analyzed during this study are included in this published article. Informed consent: Written informed consent was obtained from a legal- ly authorized representative(s) for anonymized patient information to be published in this article. Conference presentation: Part of this paper was presented at the 2nd International Nursing and Health Sciences Symposium that took place at the Faculty of Medicine, Universitas Brawijaya, Malang, Indonesia. Received for publication: 12 December 2021. Accepted for publication: 20 May 2022. This work is licensed under a Creative Commons Attribution 4.0 License (by-nc 4.0). ©Copyright: the Author(s), 2023 Licensee PAGEPress, Italy Healthcare in Low-resource Settings 2023; 11(s1):11182 doi:10.4081/hls.2023.11182 Publisher's note: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organi- zations, or those of the publisher, the editors and the reviewers. Any prod- uct that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher. No n- co mm er cia l u se on ly 2. Enoka RM, Duchateau J. Translating fatigue to human perfor- mance. Med Sci Sports Exercise 2021;48:2228–38. 3. Barbieri FA, dos Santos PCR, Vitório R, et al. Effect of muscle fatigue and physical activity level in motor control of the gait of young adults. Gait Posture 2019;38:702–7. 4. Arjunan SP, Kumar DK, Naik G. Computation and evaluation of features of surface electromyogram to identify the force of muscle contraction and muscle fatigue. BioMed Research International 2021;2014. 5. Morrison S, Colberg SR, Parson HK, et al. Walking-Induced Fatigue Leads to Increased Falls Risk in Older Adults. J Am Med Directors Assoc 2016;17:402–9. 6. Soto-Leon V, Alonso-Bonilla C, Peinado-Palomino D, et al. Effects of fatigue induced by repetitive movements and iso- metric tasks on reaction time. Human Movement Sci 73:102679. 7. Bohannon RW. Daily sit-to-stands performed by adults: a sys- tematic review. J Physical Ther Sci 2021;27:939. 8. Bryanton MA, Bilodeau M. Postural stability with exhaustive repetitive sit-to-stand exercise in young adults. Human Movement Sci 2021;49:47–53. 9. Paillard T. Effects of general and local fatigue on postural con- trol: A review [Internet]. Vol. 36, Neurosci Biobehav Rev 2012;36:162-76. 10. Haddad JM, Rietdyk S, Claxton LJ, et al. Task-Dependent Postural Control Throughout The Lifespan. Exercise Sport Sci Rev 2021;41:123. 11. Crowther F, Sealey R, Crowe M, et al. Influence of recovery strategies upon performance and perceptions following fatigu- ing exercise: a randomized controlled trial. BMC Sports Sci Med Rehab 2017;9:25. 12. Chaubet V, Paillard T. Effects of unilateral knee extensor mus- cle fatigue induced by stimulated and voluntary contractions on postural control during bipedal stance. Neurophysiol Clinique/Clinical Neurophysiol 2012;42:377-83. 13. Nascimento M de M. Fall in older adults: considerations on balance regulation, postural strategies, and physical exercise. Geriatrics Gerontol Aging 2021;13:103–10. 14. Oksa J, Rintamäki H, Takatalo K, et al. Firefighters muscular recovery after a heavy work bout in the heat. Appl Physiol Nutrition Metabol 2017;38:292–9. 15. Abutaleb EE, Mohamed AH. Effect of induced fatigue on dynamic postural balance in healthy young adults. Bulletin Faculty Physical Ther 2015;20:161–7. 16. Penedo T, Polastri PF, Rodrigues ST, et al. Motor strategy dur- ing postural control is not muscle fatigue joint-dependent, but muscle fatigue increases postural asymmetry. PLoS One 2021;16:e0247395. 17. Beurskens R, Haeger M, Kliegl R, et al. Postural control in dual-task situations: Does whole-body fatigue matter? PLoS ONE 2021;11:e0147392. 18. Mezaour M, Yiou E, Le Bozec S. Effect of lower limb muscle fatigue on anticipatory postural adjustments associated with bilateral-forward reach in the unipedal dominant and non-dom- inant stance. Eur J Appl Physiol 2021;110:1187–97. 19. Wiesmeier IK, Dalin D, Wehrle A, et al. Balance Training Enhances Vestibular Function and Reduces Overactive Proprioceptive Feedback in Elderly. Front Aging Neurosci 2017;9:273 20. Verma SK, Willetts JL, Corns HL, et al. Falls and fall-related injuries among community-dwelling adults in the United States. PLoS One 2021;11:e0150939. 21. Horak FB. Postural orientation and equilibrium: What do we need to know about neural control of balance to prevent falls? Age and Ageing 2006, p. ii7–11. 22. WS E. Center of mass of the human body helps in analysis of balance and movement. MOJ App Bio Biomech 2018;2:144– 148 23. Ruhe A, Fejer R, Walker B. The test-retest reliability of centre of pressure measures in bipedal static task conditions - A sys- tematic review of the literature. Gait Posture 2010;32:436-45. 24. Blenkinsop GM, Pain MTG, Hiley MJ. Balance control strate- gies during perturbed and unperturbed balance in standing and handstand. Royal Society Open Sci 2021;4:161018. 25. El-Khoury F, Cassou B, Latouche A, et al. Effectiveness of two year balance training programme on prevention of fall induced injuries in at risk women aged 75-85 living in community: Ossébo randomised controlled trial. BMJ 2015;351:h3830. 26. Kamitani T, Yamamoto Y, Kurita N, et al. Longitudinal Association Between Subjective Fatigue and Future Falls in Community-Dwelling Older Adults: The Locomotive Syndrome and Health Outcomes in the Aizu Cohort Study (LOHAS). J Aging Health 2021;31:67–84. 27. Granacher U, Wolf I, Wehrle A, et al. Effects of muscle fatigue on gait characteristics under single and dual-task conditions in young and older adults. J Neuroeng Rehabil 2010;7:56. 28. Parijat P, Lockhart TE. Effects of quadriceps fatigue on the biomechanics of gait and slip propensity. Gait Posture 2008;28:568-73. 29. Wong CK evi., Chen CC, Blackwell WM, et al. Balance ability measured with the Berg balance scale: a determinant of fall history in community-dwelling adults with leg amputation. J Rehabil Med 2015;47:80-86. 30. Halvarsson A, Roaldsen KS, Nilsen P, et al. StayBalanced: implementation of evidence-based fall prevention balance training for older adults—cluster randomized controlled and hybrid type 3 trial. Trials 2021;22:1–9. 31. Renner SW, Group OF in M (MrOS) S, Cauley JA, et al. Higher Fatigue Prospectively Increases the Risk of Falls in Older Men. Innovation in Aging 2021;5:1–8. 32. Stanmore EK, Mavroeidi A, Jong LD de, et al. The effective- ness and cost-effectiveness of strength and balance Exergames to reduce falls risk for people aged 55 years and older in UK assisted living facilities: a multi-centre, cluster randomised controlled trial. BMC Medicine 2021;17:1–14. 33. Morrison S, Colberg SR, Parson HK, et al. Walking-Induced Fatigue Leads to Increased Falls Risk in Older Adults. J Am Med Directors Assoc 2021;17:402–9. Article [Healthcare in Low-resource Settings 2023; 11(s1):11182] [page 87] No n- co mm er cia l u se on ly