Dynamic Balance Metrics Predict Physical Function in Older Adults: Linking Limits of Stability to SPPB Scores

Dynamic Balance Metrics Predict Physical Function in Older Adults: Linking Limits of Stability to SPPB Scores | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Dynamic Balance Metrics Predict Physical Function in Older Adults: Linking Limits of Stability to SPPB Scores Xiuping An, Yao Cui, Mingzhao Qin, Guohong Wang, Jian Zhou, Qian Liu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7287461/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Background Physical function is crucial for the independence of older adults. SPPB (Short Physical Performance Battery) is the main method for subjectively measuring physical function, however, the quantitative assessment methods are still lacking. This study aims to examine the value of Limits of Stability (LOS) in evaluating physical function in older adults. Methods According to SPPB results, 284 older people were split into two groups: those with poor physical function (PPF) and those with good physical function (GPF). LOS was measured using Computer Dynamic Posturography (CDP), which includes endpoint excursion (EPE) and maximal excursion (MXE). The association between LOS and SPPB scores was examined using Spearman correlation analysis and multivariate logistic regression analysis. Results Spearman correlation analysis revealed that the higher EPE and MXE, the better the physical function (P < 0.05). After controlling for age, gender, body BMI index, and age-adjusted charlson comorbidity Index scores, multivariate logistic regression analysis revealed that EPE and MXE had an independent correlation with SPPB (P < 0.05). ROC curves analysis showed that EPE (AUC = 0.73) and MXE (AUC = 0.72) were strong predictors of poor physical function. Conclusions EPE and MXE are independently associated with SPPB scores, suggesting that LOS can quantify older people's physical function, training in movement speed and distance is beneficial for improving physical function. older Limits of stability Physical function Short Physical Performance Battery Figures Figure 1 Figure 2 Figure 3 Background The global aging population is associated with diminished physical coordination, an increased risk of falls, multimorbidity, and polypharmacy. 1 – 2 Among those issues that come with the global aging population, improving physical function aroused more and more attention of society. 3 Physical function is crucial for the independence of older adults, and determines their ability to participate in social activities. 4 Maintaining physical function can reduce the costs associated with aging and is crucial for individuals, their families, communities and society as a whole. As results, it is important to maintaining physical function, which can improve one's general quality of life, mental and physical health. Physical function refers to the objectively measurable overall somatic motor function. Physical function is a multi-dimensional concept that involves not only muscle function but also nervous system function, and even cognitive and psychological aspects. 5 The physical function was evaluated by Short Physical Performance Battery (SPPB) according to the Asian Sarcopenia Working Group (AWGS 2019) 6 , which can properly evaluate the physical function. 7 However, SPPB is the main method for subjectively measuring physical function, and currently there is a lack of objective measurements to evaluating it. Therefore, objective measurements tools, which can be of help in the decision to whom preventive measures for maintaining good physical function should be recommended. It is well known that SPPB can also subjectively assess the patients’ balance ability. 8 Meanwhile, the Limits of Stability (LOS) test, measured by Computerized dynamic posturography (CDP), 9 providing researchers and clinicians a way to quantify older person's dynamic balance ability. Several recent studies have shown that balance training contributes to improving physical function. 10 – 11 However, current research remains insufficient to elucidate the potential correlation between LOS and SPPB scores, and their precise relationship has yet to be clearly established. As results, it is still unclear whether LOS in old populations can quantify older people's physical function, further studies are needed to verify the correlation between SPPB scores and LOS. The purpose of this study was to examine the value of the LOS in evaluating physical function in older adults, providing some enlightenment for the improvement of physical function strategies for the older population in the future. Methods Participants For this study, all consecutive elderly patients (≥ 60 years) admitted to the Department of Geriatrics, Beijing Tongren Hospital, between April 1, 2021, and December 30, 2024, were included. Beijing Tongren Hospital's Ethics Committee at Capital Medical University approved the use of an aggregate data set for research and quality improvement through an institutional review board (approval no. TRECKY2021042), and the Declaration of Helsinki's guidelines were adhered to. Every patient who took part signed an informed consent form. Patients were included in this study if they: a. were older than 60 years; b. were willing to take part in this study and receive related trials; c. had normal intelligence and mental state and is familiar with the test situation. Patients were excluded if they: a. can not cooperate with the test; b. complicated with underlying diseases that may affect renal function, such as acute onset of heart, lung, kidney diseases, and so on; c. complicated with severe cerebrovascular diseases; d. complicated with severe neurological or mental diseases; e. complicated with vestibular system disease; f. were taking sedatives, anti-anxiety and antidepressant drugs. Medical history collection and evaluation Medical documents pertaining to physical examinations, previous illnesses, and other ailments were gathered and examined. The usage of five or more medications is known as polypharmacy. The Age-adjusted Charlson Comorbidity Index (aCCI) was used to compute the comorbidity index for each patient. ( Supplementary table 1 ) A score of 1 was assigned for congestive heart failure, myocardial infarction, cerebrovascular disease, dementia, peripheral vascular disease, connective tissue disease, chronic obstructive pulmonary disease (COPD), mild liver disease, ulcer disease, or diabetes mellitus without end-organ damage A score of 2 for moderate-to-severe chronic kidney disease, hemiplegia, solid tumor, diabetes with end-organ damage, Iymphoma, or leukemial A score of 3 for moderate-to-severe liver disease, and a score of 6 for acquired immunodeficiency syndrome and metastatic solid tumors For patients who over 40 years old, the cumulative score was 1 point for each additional 10 years of age. Short Physical Performance Battery (SPPB) SPPB can properly evaluate the physical function, it includes standing balance, walking speed, and sitting tests. 7 ( Supplementary table 2 ) The physical function of the included participants was evaluated using SPPB according to the Asian Sarcopenia Working Group (AWGS 2019), 6 which is assessed through standing balance, 4-m gait speed, and the Five Times Sit-To-Stand Test. The completion status determines how many points are awarded, and Supplementary table 2 lists the precise scoring requirements. An SPPB score of more than 9 is regarded as normal for physical function in the Chinese and Asian populations. 6 The included patients were split into two groups based on their SPPB scores: those with poor physical function (PPF) (SPPB scores ≤ 9) and those with good physical function (GPF) (SPPB scores > 9). Computer dynamic posturography (CDP) - Limits of stability The balance ability was evaluated using the NeuroCom Company's EquiTest Dynamic Balance Bench Tester and Balance Test Board. The results of the LOS were computed and finished automatically. The patient looks at the screen while standing on the exam platform. The subject must immediately move their center of gravity toward the target area without raising their feet when a corresponding signal appears on the screen. They must then maintain stability for ten seconds before moving back to the center of the test area. Forward, backward, left, right, left-forward, right-forward, left-backward, and right-backward are the eight directions in which the subject can move. 12 The computer automatically computes: 1) Endpoint Excursion (EPE): the maximum displacement of the center of pressure (as a percentage of maximal LOS) during the initial lean toward the target; 2) Maximum excursion (MXE): The center of pressure's largest displacement recorded throughout the trial (as a percentage of the maximal LOS). Statistical analyses GraphPad Prism 6 was utilized for mapping, and SPSS software version 26.0 (IBM Corp, Armonk, NY, USA) was utilized for statistical analysis. When the distribution and variance satisfied the necessary requirements, the independent t-test or Mann-Whitney U test were used for intergroup comparisons. The continuous variables were displayed as the mean ± standard deviation (SD) or median (interquartile range). Frequency (%) was used to express categorical variables, and the chi-squared test or Fisher's exact test, if necessary, were used for analysis. To assess the relationship between LOS and SPPB scores, Spearman's correlation analysis was employed. We consider the SPPB scores ≤ 9 to be a binary categorical variable. The association between LOS and SPPB scores ≤ 9 was examined using binary logistic regression. Receiver operating characteristic (ROC) curves and the area under the curve (AUC) were computed in order to assess the prediction potential of the chosen predictors. The odds ratios (OR) were presented together with the p-value and 95% CIs. A p-value of less than 0.05 was considered statistically significant. Results Baseline characteristics A total of 284 older patients were included in the present study, 151 (53.2%) were in the GPF group and 133 (46.8%) were in the PPF group. The mean age of the included patients was 79.5 ± 0.5 years; 209 (73.6%) were male, 185 (65.1%) were the oldest old (aged ≥ 80 years), and the mean BMI was 23.9 ± 0.2 kg/m 2 . Compared with the GPF group, patients in the PPF group were older (85.0 (82.0, 88.0) vs. 77.0 (67.0, 82.0), P < 0.001) and had a higher proportion of coronary heart disease history (66 (49.6%) vs. 55 (36.4%), P = 0.025), chronic kidney disease (36 (27.1%) vs. 19 (12.6%), P = 0.002), multiple medication history (86 (64.7%) vs. 63 (41.7%), P < 0.001), and history of falls (84 (63.2%) vs. 47 (31.1%), P < 0.001). Besides, aCCI of PPF was higher (6.00 (5.0,7.0) vs. 5.00 (4.0, 6.0), P 0.05). Furthermore, there were statistically significant differences (P < 0.05) between the PPF group and the GPF group in terms of EPE and MXE. (Table 1 ) Table 1 Baseline characteristics, SPPB and LOS of the older adults. Variables GPF group(n = 151) PPF group(n = 133) p Age (years) 77.0 (67.0, 82.0) 85.0 (82.0, 88.0) < 0.001* Male (n, %) 113 (74.8) 96 (72.2) 0.613 BMI (kg/m 2 ) 23.82 ± 0.24 23.93 ± 0.29 0.783 aCCI (scores) 5.0 (4.0, 6.0) 6.0 (5.0,7.0) < 0.001* Hypertension (n, %) 99 (65.6) 100 (75.2) 0.077 Coronary heart disease (n, %) 55 (36.4) 66 (49.6) 0.025* Diabetes (n, %) 68 (45.0) 46 (34.6) 0.073 CKD (n, %) 19 (12.6) 36 (27.1) 0.002* Cerebrovascular disease (n, %) 28 (18.5) 34 (25.6) 0.153 Multiple medication history (n, %) 63 (41.7) 86 (64.7) < 0.001* Falls (n, %) 47 (31.1) 84 (63.2) < 0.001* SPPB scores 11.0 (10.0, 12.0) 7.0 (6.0, 8.0) < 0.001* Standing balance 4.0 (4.0, 4.0) 2.0 (2.0, 3.5) < 0.001* 4-m gait speed 4.0 (4.0, 4.0) 3.0 (2.0, 3.0) < 0.001* FTSST 4.0 (3.0, 4.0) 2.0 (1.0, 2.0) < 0.001* LOS EPE (%) 57.0 (51.0, 64.0) 48.5 (42.0, 56.0) < 0.001 MXE (%) 72.0 (65.0, 80.0) 64.0 (55.0, 71.0) < 0.001 aCCI, the age-adjusted Charlson Comorbidity Index; BMI, body mass index; CKD, chronic kidney disease; ΕPE, Endpoint Excursion; FTSST, Five Times Sit-To-Stand test; GPF, good physical function group; LOS, Limits of Stability Test; MXE, Maximum Excursion; PPF, poor physical function group. *A p-value < 0.05 was considered statistically significant. Correlation between LOS and SPPB scores. (Spearman correlation) The relationship between the EPE, MXE and SPPB scores was noted. The higher the EPE (R = 0.411, P < 0.001) and MXE (R = 0.429, P < 0.001), the higher the SPPB scores. Detailed results are presented in Fig. 1 . Correlation between LOS and SPPB scores ≤ 9. (Logistic analysis) To find LOS linked to good physical function (SPPB scores ≤ 9), binary regression was used. After controlling for age, sex, BMI, and aCCI scores, EPE (OR = 0.944, 95%CI: 0.914–0.976, P = 0.001) and MXE (OR = 0.953, 95%CI: 0.927–0.981, P = 0.001) showed a positive connection with SPPB. (Fig. 3 ) ROC curves analysis With SPPB ≤ 9 as a positive rate, a receiver operating characteristic (ROC) curve was created. The AUC for EPE (cut-off 50.5%), it was 0.725 (0.666, 0.783), with a sensitivity of 0.767 and a specificity of 0.577; and for MXE (cut-off 74.5%), it was 0.718 (0.658, 0.778), with a sensitivity of 0.467 and a specificity of 0.854. (Fig. 4 ) Discussion The global aging phenomenon is escalating, leading to gradual physiological decline in the elderly, compounded by the accumulation of chronic diseases. 13 – 14 Polypharmacy increases the risk of adverse drug reactions, disrupts normal physiological functions, impairs physical performance, and increasing the risk of falls. 15 Therefore, clinical attention must focus on the functional status of elderly individuals with multiple comorbidities and polypharmacy, necessitating timely interventions. Despite the absence of effective pharmacological interventions to mitigate physical function decline, exercise training remains pivotal for enhancing physical performance. 16 – 17 This study extensively explores the correlation between LOS assessed through CDP and SPPB scores, underscoring the importance of targeted training in preserving or enhancing patients' physical function. LOS is an individual's capacity to consciously shift the body's center of gravity in various directions without experiencing a loss of balance or falling. 18 LOS is intricately linked to sensory input, motor output, and the musculoskeletal system, thereby indicating the individual's proficiency in movement control. 19 Additionally, the EPE signifies the furthest distance at which the body can lean while maintaining stability, whereas the MXE denotes the farthest distance the body can reach while leaning. The Spearman correlation analysis revealed a significant positive correlation between EPE and SPPB scores (R = 0.411, p < 0.001), MXE and SPPB scores also showing a significant positive correlation (R = 0.429, p < 0.001). This means that higher SPPB score (indicating the better physical function) are associated with greater maximum displacement of the pressure center during the LOS test from the initial tilt to the target and throughout the tFest. The abnormalities in EPE and MXE not only reflect muscle strength but also involve sensory inputs such as vision, vestibular, and proprioception, as well as the integration ability of the nervous system. 19 A recent study revealled that the LOS is associated with the trunk muscle function. 20 The SPPB assesses physical functions through comprehensive evaluations of gait, balance, and muscle strength. The fundamental connection between the two is rooted in their shared dependence on the regulatory functions of the neuromuscular system. The strong correlation between LOS and SPPB (R = 0.429) in our study provides neurophysiological evidence supporting the pathological chain of "balance function decline → physical function decline." This indicates that the decline in physical function in the elderly is also linked to the coordinated regulation of the vestibulocerebellar system. Lesions affecting the visual, vestibular, proprioceptive, or neuromuscular systems can impair both balance and physical function, LOS can reflect changes in both concurrently. The LOS test serves as a quantitative assessment tool for evaluating elderly individuals’ physical function, objectively reflecting their Fphysical capabilities. It is currently believed that physical function decline in older adults often manifests as frailty and sarcopenia. This test addresses key limitations inherent in current physical function assessment methods for sarcopenia and frailty patients. In logistic regression analysis, even after adjusting for confounding variables such as age, sex, BMI, and aCCI score, EPE and MXE remained significantly positively associated with SPPB scores. This reaffirmed the intrinsic link between the LOS and physical function, demonstrating robust stability and reliability. ROC curve analysis indicated that EPE and MXE exhibited moderate accuracy in predicting poor physical function (SPPB scores ≤ 9). An EPE value of 50.5% was identified as the critical threshold (AUC = 0.725), resulting in a sensitivity of 76.7% for detecting abnormal physical function. Conversely, a MXE value of 74.5% served as the critical threshold, yielding a specificity of 85.4% in identifying abnormal physical function. These findings suggest that the combined use of EPE and MXE can effectively assess physical function and serve as a valuable screening tool in community-based elderly physical evaluations. One of the early indicators of functional decline in the elderly is imbalance. Approximately one-third of individuals aged 70 and older experience functional limitations in their home or daily activities,making them more susceptible to falls, injuries, and hospitalizations.This significantly reduces their quality of life and increases all-cause mortality. 21 Multiple factors contribute to the increased risk of imbalance in older adults, including alterations in energy expenditure, inadequate muscular compensation, and abnormal gait variations. 22 EPE and MXE have been introduced as quantitative supplementary indices of the SPPB in the elderly population for the first time. By assessing EPE and MXE, healthcare professionals can more precisely evaluate the physical function of older individuals, enabling the development of personalized intervention strategies. This quantitative correlation lays the groundwork for establishing a comprehensive assessment model combining "subjective scoring + objective biomarkers," addressing the deficiency of "limited objective physical function indicators" in the 2019 Asian Working Group for Sarcopenia (AWGS) guidelines. 6 This composite evaluation model serves as a valuable tool for early clinical screening, facilitating the timely identification of high-risk groups and the implementation of tailored rehabilitation interventions to enhance lower limb strength, such as speed and distance training. Specialized exercise training for older adults can enhance their physical coordination and balance. 23 A meta-analysis revealed that physical functional assessments and targeted exercise guidance can effectively prevent falls, even among patients with Parkinson's disease or cognitive impairment. Thus, regular screening of older adults is recommended to enable early detection of high fall risk and implementation of tailored interventions. 24 These interventions can enhance SPPB scores and mitigate the likelihood of adverse events. During the rehabilitation process, LOS can also monitor the recovery of physical functions quantitatively and guide the next rehabilitation plan accordingly. Nevertheless, this study is subject to several limitations. The participants were exclusively sourced from the Department of Geriatrics at Beijing Tongren Hospital, restricting the generalizability of the findings to other geographical locations and living conditions among the elderly population. Besides, although the two groups differed significantly in age, after adjusting for age in the logistic regression model, LOS and SPPB remained significantly correlated in this study. Furthermore, the study focused solely on two LOS indicators, EPE and MXE, potentially overlooking other relevant indicators for assessing physical function. The small sample size precluded the establishment of a cross-validation model. Future research endeavors should aim to broaden the sample pool to encompass elderly individuals from diverse centers and regions, explore additional LOS-related indicators and alternative objective evaluation metrics, and develop corresponding models to validate the efficacy of LOS in assessing physical function. This approach will facilitate the construction of a more comprehensive and precise physical function evaluation framework tailored to the elderly population. Conclusions In conclusion, this study confirmed that EPE and MXE in the LOS indicators are closely related to the physical function of the elderly, providing a new and effective means for the objective assessment of the physical function of the elderly. It facilitates the early identification of elderly individuals with poor physical function and provides a basis for formulating scientific and reasonable intervention strategies. It has positive significance for improving the quality of life of the elderly and reducing medical costs in an aging society. Abbreviations aCCI Age-adjusted Charlson Comorbidity Index AUC area under the curve BMI body mass index CDP Computer dynamic posturography ΕPE Endpoint Excursion GPF good physical function group FTSST Five Times Sit-To-Stand test LOS Limits of Stability Test MXE Maximum Excursion PPF poor physical function group OR odds ratios ROC Receiver operating characteristic SD standard deviation SPPB Short Physical Performance Battery Declarations Author Contributors AXP and CY conceptualized and designed the study, drafted the initial manuscript, and reviewed and revised the manuscript. AXP, CY, ZJ, LQ, and WGH designed the data collection instruments, collected data, carried out the initial analyses, and reviewed and revised the manuscript. CY, QMZ, WGH coordinated and supervised data collection, and critically reviewed the manuscript for important intellectual content. All authors approved the final manuscript as submitted and agreed to be accountable for all aspects of the work. Acknowledgments Not applicable. Statements This study adhere to the COPE Code of Conduct and Best Practice Guidelines. Clinical trial number Not applicable Ethics approval and consent to participate This project complies with the current laws and ethical standards of the country in which it was performed. This study was conducted by the Declaration of Helsinki. This study complied with the requirements of medical ethics and was reviewed and approved by the ethics committee of Beijing Tongren Hospital Affiliated to Capital Medical University (approval No. TRECKY2021-042). All participants were informed of the purpose of this study and signed written informed consent. Consent for publication Not applicable. Availability of data and materials The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Competing interests All authors have contributed significantly to the manuscript and declare that the work is original and has not been submitted or published elsewhere. None of the authors have any financial disclosure or conflict of interest. Funding There is no financial support for this study. References Sousa LM, Marques-Vieira CM, Caldevilla MN et al. Risk for falls among community-dwelling older people: systematic literature review. (0102–6933 (Print)):. Lusardi MM, Fritz S, Fau - Middleton A, Middleton AF, Allison L et al. Determining Risk of Falls in Community Dwelling Older Adults: A Systematic Review and Meta-analysis Using Posttest Probability. (2152 – 0895 (Electronic)):. 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The potential of assessment based on the WHO framework of intrinsic capacity in fragility fracture prevention. Aging Clin Exp Res. 2022;34(11):2635–43. Maresova P, Krejcar O, Maskuriy R, et al. Challenges and opportunity in mobility among older adults - key determinant identification. BMC Geriatr. 2023;23(1):447. Branch CMAG. Chinese expert consensus on multidisciplinary decision-making model for mobility limitation in older adults (2024 edition). Natl Med J china. 2024;104(12):893–905. Guirguis-Blake JM, Perdue LA, Coppola EL, et al. Interventions to Prevent Falls in Older Adults: Updated Evidence Report and Systematic Review for the US Preventive Services Task Force. JAMA. 2024;332(1):58–69. Additional Declarations No competing interests reported. Supplementary Files Supplementarytables.docx Supplementary table 1 The age-adjusted Charlson comorbidity index. Supplementary table 2 SPPB scores. 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Cui","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA10lEQVRIie3PsQrCMBCA4ZODuASyNih9hoNAR5+lQXATCi4FCwqKHURx9DF0c5VAu1S6dqz4BF3EwUGdlWo3h3zDTfdzHIBl/SN8DQIQiMfSD6MGiYxZn8osaXCNcu7J8xx/2EzxfAmCnksGvFBPGYh46dcmcsaU2lJfSQODQh+64GSnXW0iELwOJ9RrA0mhMwbkDOsThu3rM5noqWktAr3A74lA/rpi9MYgg58SOeMjxSlVz6fQ8bOEf/2F8nR/4fexK0ReVbcwckW8qk/e8GbrlmVZ1kcPh31AFHNyTGAAAAAASUVORK5CYII=","orcid":"","institution":"Beijing Tongren Hospital, Capital Medical University","correspondingAuthor":true,"prefix":"","firstName":"Yao","middleName":"","lastName":"Cui","suffix":""},{"id":521775634,"identity":"900e3b49-d8f6-4298-887a-cf1d3347779f","order_by":2,"name":"Mingzhao Qin","email":"","orcid":"","institution":"Beijing Tongren Hospital, Capital Medical University","correspondingAuthor":false,"prefix":"","firstName":"Mingzhao","middleName":"","lastName":"Qin","suffix":""},{"id":521775635,"identity":"74463c7b-50ed-4e79-be54-c2ce67500972","order_by":3,"name":"Guohong Wang","email":"","orcid":"","institution":"Beijing Tongren Hospital, Capital Medical University","correspondingAuthor":false,"prefix":"","firstName":"Guohong","middleName":"","lastName":"Wang","suffix":""},{"id":521775636,"identity":"f625f692-c919-42a7-b256-12185caba2c0","order_by":4,"name":"Jian Zhou","email":"","orcid":"","institution":"Beijing Tongren Hospital, Capital Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jian","middleName":"","lastName":"Zhou","suffix":""},{"id":521775637,"identity":"844eaa71-da7b-4e07-a124-2384941d5fc3","order_by":5,"name":"Qian Liu","email":"","orcid":"","institution":"Beijing Tongren Hospital, Capital Medical University","correspondingAuthor":false,"prefix":"","firstName":"Qian","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2025-08-04 06:23:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7287461/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7287461/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":92424797,"identity":"e7d0baac-a0a2-437c-b056-4f4b0f61d970","added_by":"auto","created_at":"2025-09-29 15:07:22","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":315265,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscriptrevisedversion.docx","url":"https://assets-eu.researchsquare.com/files/rs-7287461/v1/7af3f00bb3bcd7e3a2a02816.docx"},{"id":92425973,"identity":"6ed5cdce-77c5-4277-b16c-09eb67246e2f","added_by":"auto","created_at":"2025-09-29 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1","display":"","copyAsset":false,"role":"figure","size":92408,"visible":true,"origin":"","legend":"\u003cp\u003eSpearman correlation between LOS and SPPB scores.\u003c/p\u003e","description":"","filename":"image1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7287461/v1/d23b1927373e01cecb181cbc.jpeg"},{"id":92424791,"identity":"6b637c25-9eef-4e6d-a1b1-be753a5f367c","added_by":"auto","created_at":"2025-09-29 15:07:21","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":39284,"visible":true,"origin":"","legend":"\u003cp\u003eThe Logistic regression models illustrate the association between LOSand SPPB scores ≤9.\u003c/p\u003e","description":"","filename":"image2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7287461/v1/852412a01783634ef3370f65.jpeg"},{"id":92424792,"identity":"d9f4c1ee-30e0-4d49-9776-c79c1ce9da89","added_by":"auto","created_at":"2025-09-29 15:07:22","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":78743,"visible":true,"origin":"","legend":"\u003cp\u003eROC curves analysis of LOS and SPPB scores.\u003c/p\u003e","description":"","filename":"image3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7287461/v1/d000ff5e8a044695f21571ca.jpeg"},{"id":92427831,"identity":"492e5857-431f-4771-beb1-510b418f06ff","added_by":"auto","created_at":"2025-09-29 15:31:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":928233,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7287461/v1/11d3feba-e02b-46f2-b7c1-dccca08d5f55.pdf"},{"id":92424795,"identity":"6da40341-83b5-4daa-bd5a-0ffeb46cf077","added_by":"auto","created_at":"2025-09-29 15:07:22","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":17944,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary table 1 The age-adjusted Charlson comorbidity index.\u003c/p\u003e\n\u003cp\u003eSupplementary table 2 SPPB scores.\u003c/p\u003e","description":"","filename":"Supplementarytables.docx","url":"https://assets-eu.researchsquare.com/files/rs-7287461/v1/62d565c44cabe77ab410c871.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Dynamic Balance Metrics Predict Physical Function in Older Adults: Linking Limits of Stability to SPPB Scores","fulltext":[{"header":"Background","content":"\u003cp\u003eThe global aging population is associated with diminished physical coordination, an increased risk of falls, multimorbidity, and polypharmacy.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e Among those issues that come with the global aging population, improving physical function aroused more and more attention of society.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e Physical function is crucial for the independence of older adults, and determines their ability to participate in social activities.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e Maintaining physical function can reduce the costs associated with aging and is crucial for individuals, their families, communities and society as a whole. As results, it is important to maintaining physical function, which can improve one's general quality of life, mental and physical health.\u003c/p\u003e\u003cp\u003ePhysical function refers to the objectively measurable overall somatic motor function. Physical function is a multi-dimensional concept that involves not only muscle function but also nervous system function, and even cognitive and psychological aspects.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e The physical function was evaluated by Short Physical Performance Battery (SPPB) according to the Asian Sarcopenia Working Group (AWGS 2019)\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e, which can properly evaluate the physical function.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e However, SPPB is the main method for subjectively measuring physical function, and currently there is a lack of objective measurements to evaluating it. Therefore, objective measurements tools, which can be of help in the decision to whom preventive measures for maintaining good physical function should be recommended.\u003c/p\u003e\u003cp\u003eIt is well known that SPPB can also subjectively assess the patients\u0026rsquo; balance ability.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e Meanwhile, the Limits of Stability (LOS) test, measured by Computerized dynamic posturography (CDP),\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e providing researchers and clinicians a way to quantify older person's dynamic balance ability. Several recent studies have shown that balance training contributes to improving physical function.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e However, current research remains insufficient to elucidate the potential correlation between LOS and SPPB scores, and their precise relationship has yet to be clearly established. As results, it is still unclear whether LOS in old populations can quantify older people's physical function, further studies are needed to verify the correlation between SPPB scores and LOS.\u003c/p\u003e\u003cp\u003eThe purpose of this study was to examine the value of the LOS in evaluating physical function in older adults, providing some enlightenment for the improvement of physical function strategies for the older population in the future.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003eParticipants\u003c/h2\u003e\n \u003cp\u003eFor this study, all consecutive elderly patients (\u0026ge;\u0026thinsp;60 years) admitted to the Department of Geriatrics, Beijing Tongren Hospital, between April 1, 2021, and December 30, 2024, were included. Beijing Tongren Hospital\u0026apos;s Ethics Committee at Capital Medical University approved the use of an aggregate data set for research and quality improvement through an institutional review board (approval no. TRECKY2021042), and the Declaration of Helsinki\u0026apos;s guidelines were adhered to. Every patient who took part signed an informed consent form.\u003c/p\u003e\n \u003cp\u003ePatients were included in this study if they: a. were older than 60 years; b. were willing to take part in this study and receive related trials; c. had normal intelligence and mental state and is familiar with the test situation.\u003c/p\u003e\n \u003cp\u003ePatients were excluded if they: a. can not cooperate with the test; b. complicated with underlying diseases that may affect renal function, such as acute onset of heart, lung, kidney diseases, and so on; c. complicated with severe cerebrovascular diseases; d. complicated with severe neurological or mental diseases; e. complicated with vestibular system disease; f. were taking sedatives, anti-anxiety and antidepressant drugs.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eMedical history collection and evaluation\u003c/h3\u003e\n\u003cp\u003eMedical documents pertaining to physical examinations, previous illnesses, and other ailments were gathered and examined. The usage of five or more medications is known as polypharmacy. The Age-adjusted Charlson Comorbidity Index (aCCI) was used to compute the comorbidity index for each patient. (\u003cstrong\u003eSupplementary table 1\u003c/strong\u003e)\u003c/p\u003e\n\u003cp\u003eA score of 1 was assigned for congestive heart failure, myocardial infarction, cerebrovascular disease, dementia, peripheral vascular disease, connective tissue disease, chronic obstructive pulmonary disease (COPD), mild liver disease, ulcer disease, or diabetes mellitus without end-organ damage\u003c/p\u003e\n\u003cp\u003eA score of 2 for moderate-to-severe chronic kidney disease, hemiplegia, solid tumor, diabetes with end-organ damage, Iymphoma, or leukemial\u003c/p\u003e\n\u003cp\u003eA score of 3 for moderate-to-severe liver disease, and a score of 6 for acquired immunodeficiency syndrome and metastatic solid tumors\u003c/p\u003e\n\u003cp\u003eFor patients who over 40 years old, the cumulative score was 1 point for each additional 10 years of age.\u003c/p\u003e\n\u003ch3\u003eShort Physical Performance Battery (SPPB)\u003c/h3\u003e\n\u003cp\u003eSPPB can properly evaluate the physical function, it includes standing balance, walking speed, and sitting tests.\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e (\u003cstrong\u003eSupplementary table 2\u003c/strong\u003e) The physical function of the included participants was evaluated using SPPB according to the Asian Sarcopenia Working Group (AWGS 2019),\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e which is assessed through standing balance, 4-m gait speed, and the Five Times Sit-To-Stand Test. The completion status determines how many points are awarded, and Supplementary table 2 lists the precise scoring requirements. An SPPB score of more than 9 is regarded as normal for physical function in the Chinese and Asian populations.\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e The included patients were split into two groups based on their SPPB scores: those with poor physical function (PPF) (SPPB scores\u0026thinsp;\u0026le;\u0026thinsp;9) and those with good physical function (GPF) (SPPB scores\u0026thinsp;\u0026gt;\u0026thinsp;9).\u003c/p\u003e\n\u003cdiv class=\"Heading\"\u003e\u003cstrong\u003eComputer dynamic posturography (CDP) - Limits of stability\u003c/strong\u003e\u003c/div\u003e\n\u003cp\u003eThe balance ability was evaluated using the NeuroCom Company\u0026apos;s EquiTest Dynamic Balance Bench Tester and Balance Test Board. The results of the LOS were computed and finished automatically.\u003c/p\u003e\n\u003cp\u003eThe patient looks at the screen while standing on the exam platform. The subject must immediately move their center of gravity toward the target area without raising their feet when a corresponding signal appears on the screen. They must then maintain stability for ten seconds before moving back to the center of the test area. Forward, backward, left, right, left-forward, right-forward, left-backward, and right-backward are the eight directions in which the subject can move.\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e The computer automatically computes: 1) Endpoint Excursion (EPE): the maximum displacement of the center of pressure (as a percentage of maximal LOS) during the initial lean toward the target; 2) Maximum excursion (MXE): The center of pressure\u0026apos;s largest displacement recorded throughout the trial (as a percentage of the maximal LOS).\u003c/p\u003e\n\u003ch3\u003eStatistical analyses\u003c/h3\u003e\n\u003cp\u003eGraphPad Prism 6 was utilized for mapping, and SPSS software version 26.0 (IBM Corp, Armonk, NY, USA) was utilized for statistical analysis. When the distribution and variance satisfied the necessary requirements, the independent t-test or Mann-Whitney U test were used for intergroup comparisons. The continuous variables were displayed as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD) or median (interquartile range). Frequency (%) was used to express categorical variables, and the chi-squared test or Fisher\u0026apos;s exact test, if necessary, were used for analysis. To assess the relationship between LOS and SPPB scores, Spearman\u0026apos;s correlation analysis was employed. We consider the SPPB scores\u0026thinsp;\u0026le;\u0026thinsp;9 to be a binary categorical variable. The association between LOS and SPPB scores\u0026thinsp;\u0026le;\u0026thinsp;9 was examined using binary logistic regression. Receiver operating characteristic (ROC) curves and the area under the curve (AUC) were computed in order to assess the prediction potential of the chosen predictors. The odds ratios (OR) were presented together with the p-value and 95% CIs. A p-value of less than 0.05 was considered statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003eBaseline characteristics\u003c/h2\u003e\u003cp\u003eA total of 284 older patients were included in the present study, 151 (53.2%) were in the GPF group and 133 (46.8%) were in the PPF group. The mean age of the included patients was 79.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5 years; 209 (73.6%) were male, 185 (65.1%) were the oldest old (aged\u0026thinsp;\u0026ge;\u0026thinsp;80 years), and the mean BMI was 23.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 kg/m\u003csup\u003e2\u003c/sup\u003e. Compared with the GPF group, patients in the PPF group were older (85.0 (82.0, 88.0) vs. 77.0 (67.0, 82.0), P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and had a higher proportion of coronary heart disease history (66 (49.6%) vs. 55 (36.4%), P\u0026thinsp;=\u0026thinsp;0.025), chronic kidney disease (36 (27.1%) vs. 19 (12.6%), P\u0026thinsp;=\u0026thinsp;0.002), multiple medication history (86 (64.7%) vs. 63 (41.7%), P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and history of falls (84 (63.2%) vs. 47 (31.1%), P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Besides, aCCI of PPF was higher (6.00 (5.0,7.0) vs. 5.00 (4.0, 6.0), P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). However, no statistically significant differences were observed in sex, BMI, and cerebrovascular disease between the two groups (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Furthermore, there were statistically significant differences (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) between the PPF group and the GPF group in terms of EPE and MXE. (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eBaseline characteristics, SPPB and LOS of the older adults.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGPF group(n\u0026thinsp;=\u0026thinsp;151)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePPF group(n\u0026thinsp;=\u0026thinsp;133)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e77.0 (67.0, 82.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e85.0 (82.0, 88.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale (n, %)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e113 (74.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e96 (72.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.613\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e23.82\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23.93\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.783\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eaCCI (scores)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.0 (4.0, 6.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.0 (5.0,7.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHypertension (n, %)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e99 (65.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e100 (75.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.077\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCoronary heart disease (n, %)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e55 (36.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e66 (49.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.025*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiabetes (n, %)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e68 (45.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e46 (34.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.073\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCKD (n, %)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e19 (12.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e36 (27.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.002*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCerebrovascular disease (n, %)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e28 (18.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e34 (25.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.153\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMultiple medication history (n, %)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e63 (41.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e86 (64.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFalls (n, %)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e47 (31.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e84 (63.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSPPB scores\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11.0 (10.0, 12.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.0 (6.0, 8.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStanding balance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.0 (4.0, 4.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.0 (2.0, 3.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4-m gait speed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.0 (4.0, 4.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.0 (2.0, 3.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFTSST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.0 (3.0, 4.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.0 (1.0, 2.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLOS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEPE (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e57.0 (51.0, 64.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e48.5 (42.0, 56.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMXE (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e72.0 (65.0, 80.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e64.0 (55.0, 71.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eaCCI, the age-adjusted Charlson Comorbidity Index; BMI, body mass index; CKD, chronic kidney disease; ΕPE, Endpoint Excursion; FTSST, Five Times Sit-To-Stand test; GPF, good physical function group; LOS, Limits of Stability Test; MXE, Maximum Excursion; PPF, poor physical function group. *A p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eCorrelation between LOS and SPPB scores. (Spearman correlation)\u003c/h3\u003e\n\u003cp\u003eThe relationship between the EPE, MXE and SPPB scores was noted. The higher the EPE (R\u0026thinsp;=\u0026thinsp;0.411, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and MXE (R\u0026thinsp;=\u0026thinsp;0.429, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), the higher the SPPB scores. Detailed results are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eCorrelation between LOS and SPPB scores\u0026thinsp;\u0026le;\u0026thinsp;9. (Logistic analysis)\u003c/h2\u003e\u003cp\u003eTo find LOS linked to good physical function (SPPB scores\u0026thinsp;\u0026le;\u0026thinsp;9), binary regression was used. After controlling for age, sex, BMI, and aCCI scores, EPE (OR\u0026thinsp;=\u0026thinsp;0.944, 95%CI: 0.914\u0026ndash;0.976, P\u0026thinsp;=\u0026thinsp;0.001) and MXE (OR\u0026thinsp;=\u0026thinsp;0.953, 95%CI: 0.927\u0026ndash;0.981, P\u0026thinsp;=\u0026thinsp;0.001) showed a positive connection with SPPB. (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e)\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eROC curves analysis\u003c/h2\u003e\u003cp\u003eWith SPPB\u0026thinsp;\u0026le;\u0026thinsp;9 as a positive rate, a receiver operating characteristic (ROC) curve was created. The AUC for EPE (cut-off 50.5%), it was 0.725 (0.666, 0.783), with a sensitivity of 0.767 and a specificity of 0.577; and for MXE (cut-off 74.5%), it was 0.718 (0.658, 0.778), with a sensitivity of 0.467 and a specificity of 0.854. (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e)\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe global aging phenomenon is escalating, leading to gradual physiological decline in the elderly, compounded by the accumulation of chronic diseases.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e Polypharmacy increases the risk of adverse drug reactions, disrupts normal physiological functions, impairs physical performance, and increasing the risk of falls.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e Therefore, clinical attention must focus on the functional status of elderly individuals with multiple comorbidities and polypharmacy, necessitating timely interventions. Despite the absence of effective pharmacological interventions to mitigate physical function decline, exercise training remains pivotal for enhancing physical performance.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e This study extensively explores the correlation between LOS assessed through CDP and SPPB scores, underscoring the importance of targeted training in preserving or enhancing patients' physical function.\u003c/p\u003e\u003cp\u003eLOS is an individual's capacity to consciously shift the body's center of gravity in various directions without experiencing a loss of balance or falling.\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e LOS is intricately linked to sensory input, motor output, and the musculoskeletal system, thereby indicating the individual's proficiency in movement control.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e Additionally, the EPE signifies the furthest distance at which the body can lean while maintaining stability, whereas the MXE denotes the farthest distance the body can reach while leaning. The Spearman correlation analysis revealed a significant positive correlation between EPE and SPPB scores (R\u0026thinsp;=\u0026thinsp;0.411, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), MXE and SPPB scores also showing a significant positive correlation (R\u0026thinsp;=\u0026thinsp;0.429, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This means that higher SPPB score (indicating the better physical function) are associated with greater maximum displacement of the pressure center during the LOS test from the initial tilt to the target and throughout the tFest. The abnormalities in EPE and MXE not only reflect muscle strength but also involve sensory inputs such as vision, vestibular, and proprioception, as well as the integration ability of the nervous system. \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e A recent study revealled that the LOS is associated with the trunk muscle function.\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e The SPPB assesses physical functions through comprehensive evaluations of gait, balance, and muscle strength. The fundamental connection between the two is rooted in their shared dependence on the regulatory functions of the neuromuscular system. The strong correlation between LOS and SPPB (R\u0026thinsp;=\u0026thinsp;0.429) in our study provides neurophysiological evidence supporting the pathological chain of \"balance function decline \u0026rarr; physical function decline.\" This indicates that the decline in physical function in the elderly is also linked to the coordinated regulation of the vestibulocerebellar system. Lesions affecting the visual, vestibular, proprioceptive, or neuromuscular systems can impair both balance and physical function, LOS can reflect changes in both concurrently. The LOS test serves as a quantitative assessment tool for evaluating elderly individuals\u0026rsquo; physical function, objectively reflecting their Fphysical capabilities. It is currently believed that physical function decline in older adults often manifests as frailty and sarcopenia. This test addresses key limitations inherent in current physical function assessment methods for sarcopenia and frailty patients.\u003c/p\u003e\u003cp\u003eIn logistic regression analysis, even after adjusting for confounding variables such as age, sex, BMI, and aCCI score, EPE and MXE remained significantly positively associated with SPPB scores. This reaffirmed the intrinsic link between the LOS and physical function, demonstrating robust stability and reliability. ROC curve analysis indicated that EPE and MXE exhibited moderate accuracy in predicting poor physical function (SPPB scores\u0026thinsp;\u0026le;\u0026thinsp;9). An EPE value of 50.5% was identified as the critical threshold (AUC\u0026thinsp;=\u0026thinsp;0.725), resulting in a sensitivity of 76.7% for detecting abnormal physical function. Conversely, a MXE value of 74.5% served as the critical threshold, yielding a specificity of 85.4% in identifying abnormal physical function. These findings suggest that the combined use of EPE and MXE can effectively assess physical function and serve as a valuable screening tool in community-based elderly physical evaluations.\u003c/p\u003e\u003cp\u003eOne of the early indicators of functional decline in the elderly is imbalance. Approximately one-third of individuals aged 70 and older experience functional limitations in their home or daily activities,making them more susceptible to falls, injuries, and hospitalizations.This significantly reduces their quality of life and increases all-cause mortality.\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e Multiple factors contribute to the increased risk of imbalance in older adults, including alterations in energy expenditure, inadequate muscular compensation, and abnormal gait variations.\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e EPE and MXE have been introduced as quantitative supplementary indices of the SPPB in the elderly population for the first time. By assessing EPE and MXE, healthcare professionals can more precisely evaluate the physical function of older individuals, enabling the development of personalized intervention strategies. This quantitative correlation lays the groundwork for establishing a comprehensive assessment model combining \"subjective scoring\u0026thinsp;+\u0026thinsp;objective biomarkers,\" addressing the deficiency of \"limited objective physical function indicators\" in the 2019 Asian Working Group for Sarcopenia (AWGS) guidelines. \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e This composite evaluation model serves as a valuable tool for early clinical screening, facilitating the timely identification of high-risk groups and the implementation of tailored rehabilitation interventions to enhance lower limb strength, such as speed and distance training. Specialized exercise training for older adults can enhance their physical coordination and balance.\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e A meta-analysis revealed that physical functional assessments and targeted exercise guidance can effectively prevent falls, even among patients with Parkinson's disease or cognitive impairment. Thus, regular screening of older adults is recommended to enable early detection of high fall risk and implementation of tailored interventions.\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e These interventions can enhance SPPB scores and mitigate the likelihood of adverse events. During the rehabilitation process, LOS can also monitor the recovery of physical functions quantitatively and guide the next rehabilitation plan accordingly.\u003c/p\u003e\u003cp\u003eNevertheless, this study is subject to several limitations. The participants were exclusively sourced from the Department of Geriatrics at Beijing Tongren Hospital, restricting the generalizability of the findings to other geographical locations and living conditions among the elderly population. Besides, although the two groups differed significantly in age, after adjusting for age in the logistic regression model, LOS and SPPB remained significantly correlated in this study. Furthermore, the study focused solely on two LOS indicators, EPE and MXE, potentially overlooking other relevant indicators for assessing physical function. The small sample size precluded the establishment of a cross-validation model. Future research endeavors should aim to broaden the sample pool to encompass elderly individuals from diverse centers and regions, explore additional LOS-related indicators and alternative objective evaluation metrics, and develop corresponding models to validate the efficacy of LOS in assessing physical function. This approach will facilitate the construction of a more comprehensive and precise physical function evaluation framework tailored to the elderly population.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn conclusion, this study confirmed that EPE and MXE in the LOS indicators are closely related to the physical function of the elderly, providing a new and effective means for the objective assessment of the physical function of the elderly. It facilitates the early identification of elderly individuals with poor physical function and provides a basis for formulating scientific and reasonable intervention strategies. It has positive significance for improving the quality of life of the elderly and reducing medical costs in an aging society.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eaCCI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAge-adjusted Charlson Comorbidity Index\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eAUC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003earea under the curve\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eBMI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ebody mass index\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCDP\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eComputer dynamic posturography\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eΕPE\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eEndpoint Excursion\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eGPF\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003egood physical function group\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eFTSST\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eFive Times Sit-To-Stand test\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eLOS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eLimits of Stability Test\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eMXE\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eMaximum Excursion\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePPF\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003epoor physical function group\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eOR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eodds ratios\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eROC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eReceiver operating characteristic\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eSD\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003estandard deviation\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eSPPB\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eShort Physical Performance Battery\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eContributors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAXP and CY conceptualized and designed the study, drafted the initial manuscript, and reviewed and revised the manuscript. AXP, CY, ZJ, LQ, and WGH designed the data collection instruments, collected data, carried out the initial analyses, and reviewed and revised the manuscript. CY, QMZ, WGH coordinated and supervised data collection, and critically reviewed the manuscript for important intellectual content. All authors approved the final manuscript as submitted and agreed to be accountable for all aspects of the work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study adhere to the COPE Code of Conduct and Best Practice Guidelines.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis project complies with the current laws and ethical standards of the country in which it was performed. This study was conducted by the Declaration of Helsinki. This study complied with the requirements of medical ethics and was reviewed and approved by the ethics committee of Beijing Tongren Hospital Affiliated to Capital Medical University (approval No. TRECKY2021-042). All participants were informed of the purpose of this study and signed written informed consent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors have contributed significantly to the manuscript and declare that the work is original and has not been submitted or published elsewhere. None of the authors have any financial disclosure or conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere is no financial support for this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSousa LM, Marques-Vieira CM, Caldevilla MN et al. Risk for falls among community-dwelling older people: systematic literature review. (0102\u0026ndash;6933 (Print)):.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLusardi MM, Fritz S, Fau - Middleton A, Middleton AF, Allison L et al. Determining Risk of Falls in Community Dwelling Older Adults: A Systematic Review and Meta-analysis Using Posttest Probability. (2152\u0026thinsp;\u0026ndash;\u0026thinsp;0895 (Electronic)):.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBjerk MA-O, Brovold T, Skelton DA et al. Associations between health-related quality of life, physical function and fear of falling in older fallers receiving home care. (1471\u0026ndash;2318 (Electronic)):.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLowry KA, Vallejo AN, Studenski SA. Successful aging as a continuum of functional independence: lessons from physical disability models of aging. Aging disease. 2012;3(1):5\u0026ndash;15.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBeaudart C, Rolland Y, Cruz-Jentoft AJ, et al. Assessment of Muscle Function and Physical Performance in Daily Clinical Practice: A position paper endorsed by the European Society for Clinical and Economic Aspects of Osteoporosis, Osteoarthritis and Musculoskeletal Diseases (ESCEO). Calcif Tissue Int. 2019;105(1):1\u0026ndash;14.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChen LK, Woo J, Assantachai P, et al. Asian Working Group for Sarcopenia: 2019 Consensus Update on Sarcopenia Diagnosis and Treatment. J Am Med Dir Assoc. 2020;21(3):300\u0026ndash;e3072.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWelch SA, Ward RE, Beauchamp MK, et al. The Short Physical Performance Battery (SPPB): A Quick and Useful Tool for Fall Risk Stratification Among Older Primary Care Patients. J Am Med Dir Assoc. 2021;22(8):1646\u0026ndash;51.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLow DC, Walsh GS. (2022) The minimal important change for measures of balance and postural control in older adults: a systematic review. Age Ageing \u003cem\u003e51\u003c/em\u003e (12).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChieffe DJ, Zuniga SA, Marmor S, et al. Nationwide Utilization of Computerized Dynamic Posturography in an Era of Deimplementation. Otolaryngology\u0026ndash;head neck surgery: official J Am Acad Otolaryngology-Head Neck Surg. 2023;169(4):1090\u0026ndash;3.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHalvarsson A, Franz\u0026eacute;n E, St\u0026aring;hle A. Balance training with multi-task exercises improves fall-related self-efficacy, gait, balance performance and physical function in older adults with osteoporosis: a randomized controlled trial. Clin Rehabil. 2015;29(4):365\u0026ndash;75.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMonticone M, Ambrosini E, Brunati R, et al. How balance task-specific training contributes to improving physical function in older subjects undergoing rehabilitation following hip fracture: a randomized controlled trial. Clin Rehabil. 2018;32(3):340\u0026ndash;51.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFiedorov\u0026aacute; I, Mr\u0026aacute;zkov\u0026aacute; E, Z\u0026aacute;drapov\u0026aacute; M et al. (2022) Receiver Operating Characteristic Curve Analysis of the Somatosensory Organization Test, Berg Balance Scale, and Fall Efficacy Scale-International for Predicting Falls in Discharged Stroke Patients. Int J Environ Res Public Health \u003cem\u003e19\u003c/em\u003e (15).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGuo J, Huang X, Dou L, et al. Aging and aging-related diseases: from molecular mechanisms to interventions and treatments. Signal Transduct Target therapy. 2022;7(1):391.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLi Z, Zhang Z, Ren Y, et al. Aging and age-related diseases: from mechanisms to therapeutic strategies. Biogerontology. 2021;22(2):165\u0026ndash;87.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLaurence BD, Michel L. The Fall in Older Adults: Physical and Cognitive Problems. Curr Aging Sci. 2017;10(3):185\u0026ndash;200.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMendonca GV, Pezarat-Correia P, Vaz JR, et al. Impact of Exercise Training on Physiological Measures of Physical Fitness in the Elderly. Curr Aging Sci. 2016;9(4):240\u0026ndash;59.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eXu F, Soh KG, Chan YM, et al. Effects of physical exercise on physical and mental health in older adults with gait disorders: A systematic review. Geriatric Nurs (New York N Y). 2025;63:123\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRossi-Izquierdo M, Gayoso-Diz P, Santos-P\u0026eacute;rez S et al. (2018) Vestibular rehabilitation in elderly patients with postural instability: reducing the number of falls-a randomized clinical trial. \u003cem\u003eAging clinical and experimental research 30\u003c/em\u003e (11): 1353\u0026ndash;1361.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHorak FB. Postural orientation and equilibrium: what do we need to know about neural control of balance to prevent falls? Age Ageing. 2006;35(Suppl 2):ii7\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eForestieri Faccio AF, Porto JM, Freire J\u0026uacute;nior RC, et al. Trunk muscle function and anterior and posterior limits of stability in community-dwelling older adults. J Bodyw Mov Ther. 2021;28:212\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAstrone P, Perracini MR, Martin FC, et al. The potential of assessment based on the WHO framework of intrinsic capacity in fragility fracture prevention. Aging Clin Exp Res. 2022;34(11):2635\u0026ndash;43.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMaresova P, Krejcar O, Maskuriy R, et al. Challenges and opportunity in mobility among older adults - key determinant identification. BMC Geriatr. 2023;23(1):447.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBranch CMAG. Chinese expert consensus on multidisciplinary decision-making model for mobility limitation in older adults (2024 edition). Natl Med J china. 2024;104(12):893\u0026ndash;905.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGuirguis-Blake JM, Perdue LA, Coppola EL, et al. Interventions to Prevent Falls in Older Adults: Updated Evidence Report and Systematic Review for the US Preventive Services Task Force. JAMA. 2024;332(1):58\u0026ndash;69.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-geriatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bgtc","sideBox":"Learn more about [BMC Geriatrics](http://bmcgeriatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bgtc/default.aspx","title":"BMC Geriatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"older, Limits of stability, Physical function, Short Physical Performance Battery","lastPublishedDoi":"10.21203/rs.3.rs-7287461/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7287461/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003ePhysical function is crucial for the independence of older adults. SPPB (Short Physical Performance Battery) is the main method for subjectively measuring physical function, however, the quantitative assessment methods are still lacking. This study aims to examine the value of Limits of Stability (LOS) in evaluating physical function in older adults.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eAccording to SPPB results, 284 older people were split into two groups: those with poor physical function (PPF) and those with good physical function (GPF). LOS was measured using Computer Dynamic Posturography (CDP), which includes endpoint excursion (EPE) and maximal excursion (MXE). The association between LOS and SPPB scores was examined using Spearman correlation analysis and multivariate logistic regression analysis.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eSpearman correlation analysis revealed that the higher EPE and MXE, the better the physical function (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). After controlling for age, gender, body BMI index, and age-adjusted charlson comorbidity Index scores, multivariate logistic regression analysis revealed that EPE and MXE had an independent correlation with SPPB (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). ROC curves analysis showed that EPE (AUC\u0026thinsp;=\u0026thinsp;0.73) and MXE (AUC\u0026thinsp;=\u0026thinsp;0.72) were strong predictors of poor physical function.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eEPE and MXE are independently associated with SPPB scores, suggesting that LOS can quantify older people's physical function, training in movement speed and distance is beneficial for improving physical function.\u003c/p\u003e","manuscriptTitle":"Dynamic Balance Metrics Predict Physical Function in Older Adults: Linking Limits of Stability to SPPB Scores","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-29 15:07:17","doi":"10.21203/rs.3.rs-7287461/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2025-09-18T10:29:50+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-08-28T05:44:07+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-14T09:58:30+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-14T05:55:17+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Geriatrics","date":"2025-08-14T05:52:19+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-geriatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bgtc","sideBox":"Learn more about [BMC Geriatrics](http://bmcgeriatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bgtc/default.aspx","title":"BMC Geriatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"75049ddb-98e8-4a45-899d-3676185b626f","owner":[],"postedDate":"September 29th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-09-29T15:07:17+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-29 15:07:17","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7287461","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7287461","identity":"rs-7287461","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}