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Article

Declines in Activities in Daily Living of Older Adults with Sarcopenia Were Associated with Gait Speed

1
Integrated Facility for Medical and Long-Term Care, Care Facility for the Elderly “Maronie-en”, 533-4 Iguchi, Nasushiobara 329-2763, Japan
2
Department of Physical Therapy, School of Health Sciences, International University of Health and Welfare, Otawara 324-8501, Japan
3
Nishinasuno General Home Care Center, Department of Day Rehabilitation, Care Facility for the Elderly “Maronie-en”, Nasushiobara 329-2763, Japan
4
Department of Geriatric Medicine, School of Medicine, International University of Health and Welfare, Chiba, Narita 286-8686, Japan
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Medicina 2026, 62(2), 263; https://doi.org/10.3390/medicina62020263
Submission received: 19 December 2025 / Revised: 15 January 2026 / Accepted: 26 January 2026 / Published: 26 January 2026
(This article belongs to the Section Epidemiology & Public Health)

Abstract

Background and Objectives: Early assessment interventions are recommended for older adults with sarcopenia. Gait speed in older adults considerably decreases activities of daily living (ADL). However, the association between ADL and gait speed in older adults with sarcopenia has not yet been fully elucidated. This study aimed to clarify the association between walking speed and ADL in older adults with sarcopenia. Materials and Methods: A total of 72 older adults with sarcopenia who required support or care under Japan’s long-term care insurance system were included. Correlation and multivariate analyses were performed to examine the association between walking speed and ADL performance. A receiver operating characteristic analysis was used to evaluate the discrimination power of gait speed for ADL independence. Results: Gait speed was significantly and positively correlated with the Barthel Index scores for the men and women. ADL were independently and significantly associated with walking speed in the multivariate analysis. The threshold for gait speed that distinguished ADL independence in older adults with sarcopenia was 0.76 m/s (area under the curve = 0.75, sensitivity 72.7%, specificity 74.0%). Conclusions: Decreased gait speed in older adults with sarcopenia was associated with decreased ADL. Gait speed had high discriminatory power in identifying ADL independence. This indicates that an assessment intervention for gait speed in older adults with sarcopenia may have high clinical utility.

1. Introduction

Sarcopenia is defined as an age-related decline in skeletal muscle mass and muscle strength [1]. Sarcopenia has been reported to be associated with decreased activities of daily living (ADL) [2] and increased risks of rehospitalization [3] and mortality [4], indicating the importance of nutritional and exercise interventions for its management [5,6]. In Japan, the overall incidence of sarcopenia among community-dwelling older adults is approximately 14.1%. However, the decline in skeletal muscle mass progresses with age, with prevalence rates of approximately 5.2% among individuals aged 65–69 years, and 40.8% among those aged ≥80 years, demonstrating a clear increasing trend [7]. Furthermore, sarcopenia is highly prevalent among older adults requiring long-term care, with a prevalence of approximately 56.3% [8] and a new-onset rate of 13.0% after 6 months, underscoring the importance of early assessment and intervention [9]. Therefore, facilities that provide medical and nursing care and assessment interventions to prevent decline in ADL are essential for the continuation of independent living for older adults with sarcopenia. Furthermore, recent studies have reported that depression is associated with care dependency among older adults with sarcopenia [10], and that obesity is associated with increased mortality risk [11]. An aging society is one of the most important public health challenges in developed Asian countries because the number of people requiring long-term care is rising, and the need to promote the extension of healthy life expectancy is growing [12,13,14].
In previous studies, factors associated with decreased ADL in older adults included low nutritional status [15], grip strength [16], skeletal muscle mass index (SMI) [17], and decreased walking speed [18]. Improvement in walking speed through rehabilitation is associated with enhanced ADL [19,20]. However, previous studies have focused on community-dwelling older adults, leaving the factors related to ADL and the characteristics of older adults with established sarcopenia unclear. Identifying the features of sarcopenia that are closely associated with ADL decline could aid in rehabilitation management and enable earlier intervention for older adults requiring long-term care.
Therefore, we hypothesized that ADL and gait speed would be reduced in older adults with sarcopenia. This study aimed to clarify whether gait speed can be used to identify impaired ADL in older adults with sarcopenia.

2. Materials and Methods

2.1. Ethical Considerations

This study is a single-center cross-sectional study involving older adults receiving day care services. This cross-sectional study was conducted between March 2023 and September 2024. The study protocol was approved by the Ethics Review Board of our facility (approval numbers: 21-Io-22-3 and 17-Io-189-7). All the participants (or their family members) provided written informed consent. This study was conducted in accordance with the principles of the Declaration of Helsinki.

2.2. Study Participants

This cross-sectional study enrolled 208 individuals assessed as requiring support or care under the Japanese long-term care insurance system and were utilizing day rehabilitation facilities for older adults [21]. Their body composition was measured.
We included 72 older adults who met the inclusion and exclusion criteria in the study analysis. The inclusion and exclusion criteria for this study were established by referencing the subject criteria used in previous studies [22], with the additional criterion of excluding non-sarcopenia cases. The exclusion criteria were individuals (1) younger than 65 years, (2) older than 100 years, (3) requiring walking assistance, (4) who did not present with sarcopenia, and (5) with missing data.

2.3. Measurements

2.3.1. Sarcopenia Diagnosis

Gait speed was measured twice at a normal walking pace between 3 and 8 m (5 m) on an 11 m walking path; the average value was used as the representative value.
Grip strength was assessed twice in the right and left hands in the sitting position using a grip strength meter (TKK5401 Grip-D; Takei Kiki, Niigata, Japan). The maximum value was considered the representative value.
Skeletal muscle mass was measured in the sitting position using a body composition analyzer (InBodyS10; InBody, Seoul, Republic of Korea). Sarcopenia diagnostic criteria were defined according to Asian Working Group for Sarcopenia (AWGS) 2019 as appropriate for Asians [23]. For men, low muscle strength was defined as grip strength < 28 kg, low physical function as walking speed < 1.0 m/s, and low skeletal muscle mass as SMI < 7.0 kg/m2. For women, low muscle strength was defined as grip strength < 18 kg, low physical function as walking speed < 1.0 m/s, and low skeletal muscle mass as SMI < 5.7 kg/m2. We classified the participants into the sarcopenia (severe sarcopenia and sarcopenia) and non-sarcopenia groups.

2.3.2. ADL Assessment

The Barthel Index (BI) was used for ADL assessment; the score ranges from 0–100 and a higher BI score indicates less dependence. The BI has been reported as a reliable ADL assessment tool [24]. The inter-rater reliability was ICC = 0.98 (95% confidence interval: 0.97–0.98), indicating that this is a highly reliable ADL assessment tool [25].

2.3.3. Other Covariates

Age, sex, and height data were obtained from the facility’s medical records. Nutritional status was determined using the Mini Nutritional Assessment Scale-Short Form (MNA-SF), which is recommended for use with older adults [26]. The MNA-SF scores were classified as 0–7 (malnutrition), 8–11 (at risk for malnutrition), and 12–14 (no malnutrition).

2.4. Statistical Analyses

Pearson’s and Spearman’s rank correlation coefficients were used to analyze the factors related to ADL. A multiple regression analysis was performed using gait speed as the independent variable to examine its relationship with the BI score, the dependent variable. This study investigated which indicators—grip strength, walking speed, and SMI—are associated with ADL. The MNA-SF was included as a control variable, along with gender, age, and BMI, as it may act as a confounding factor for both ADL and sarcopenia [9].
A receiver operating characteristic curve was created to determine the threshold for gait speed to identify ADL independence (BI = 100) and the area under the curve (AUC). Sensitivity and specificity were calculated using the Youden Index to determine the optimal threshold for AUC values: >0.9 (high precision); 0.7–0.9 (moderate precision); and <0.7 (low precision) [27].
Statistical analyses were performed using the Statistical Package for the Social Sciences, Version 25 (IBM Corp., Armonk, NY, USA). Significance was set at p < 0.05. A power analysis was performed using G*Power version 3.1.2.1.

2.5. Sample Size

The power analysis utilized a bivariate normal model with a t-test, yielding a power of 0.99 using an effect size of 0.47 for walking speed and BI, an alpha error probability of 0.05, and a sample size of 72.

3. Results

Figure 1 presents the flowchart of those enrolled and the 72 older adult study participants. Table 1 is a summary of the basic attributes, ADL, grip strength, walking speed, SMI, and nutritional status of the study participants. Since the proportion of missing values in this study is less than 10%, the listwise deletion method was adopted.
Table 2 lists the factors related to ADL. The correlation analysis revealed significant positive correlations between BI, grip strength (r = 0.26), and walking speed (r = 0.47). A significant positive correlation was observed between BI, grip strength (r = 0.31), and walking speed (r = 0.50) for both men and women. The BI score and gait speed for women were significantly positively correlated (r = 0.45).
Table 3 presents the results for the relationship between the walking speed and ADL performance. The multiple regression analysis revealed a significant association between walking speed (β = 0.45, p < 0.001, R2 = 0.29) and ADL independence.
Furthermore, 22 participants (30.6%) had a BI score of 100. The optimal threshold for walking speed to identify ADL independence (BI = 100) was 0.76 m/s (AUC = 0.75, 95% CI: 0.62–0.88, sensitivity 72.7%, specificity 74.0%) (Figure 2). Only one point at which the Youden Index reached its maximum value was identified.

4. Discussion

In this study, we identified factors associated with ADL of older adults with sarcopenia. In addition, we determined the discriminatory power of normal gait speed for identifying ADL independence. To the best of our knowledge, this was the first study to evaluate the association between gait speed and ADL in older adults with sarcopenia.
We found a significant positive correlation between gait speed and ADL for both men and women. Gait speed SMI, and grip strength are key components of sarcopenia assessment and are expected to be lower compared to other groups. This study revealed that, among sarcopenic older adults with reduced gait speed, SMI, and grip strength, gait speed in particular is closely associated with ADL. Gait speed in older adults is associated with balance function [28] and muscle mass asymmetry [29]. The group with slower gait speed had a higher fall rate than the group with higher gait speed [30]. A previous study reported a correlation between gait speed and ADL, low walking speed, and increased risk of death [31]. Furthermore, because walking speed is associated with age-related frailty [32], an indirect association may be possible. In a population of older adults with care needs, a decline in normal gait speed can indicate worsening of independent care capacity, suggesting the need for early assessment interventions for gait speed [33]. The results of this study support previous findings showing that decreased normal gait speed is associated with decreased ADL. Interestingly, this study revealed that gait speed, and not skeletal muscle mass, influenced ADL status in older adults with sarcopenia. Previous reports show an association between skeletal muscle mass and ADL [34]. This may be owing to differing ages of the participants in this study compared to those in previous studies; in addition, the participants in this study sarcopenic population with low skeletal muscle mass, indicating that gait speed, a measure of physical function, may have a profound effect on ADL. This novel study clarified the relationship between ADL and normal gait speed in older adults with sarcopenia. Nutrition and exercise have been reported to improve walking speed and SMI in older individuals with sarcopenia [35]; however, no studies have examined their effects on ADL. Therefore, future rehabilitation protocols should incorporate ADL assessment and targeted intervention.
Recent studies indicate that low physical performance, defined as a walking speed ≤ 0.8 m/s, is a strong predictor of functional impairment in individuals aged 60 years and older [36]. In populations with a high proportion of individuals with disabilities, a cutoff of 0.6 m/s may serve as a useful threshold for identifying the risk of further functional decline in older adults who already have functional impairments [37]. In this study, we postulated a new reference value for walking speed to identify ADL in older adults with sarcopenia. The results indicated that the optimal gait speed threshold to identify ADL independence was 0.76 m/s. For individuals aged 75 years and older, reduced walking speed (<0.7 m/s) is a predictor for hospitalization, need for a caregiver, and new falls [38]. Previous studies indicate an average walking speed of 0.70 ± 0.18 m/s among sarcopenic older requiring care [39]. Given that this study population consists of older sarcopenic adults, a walking speed cutoff of 0.76 m/s is considered appropriate. The results of this study showed sufficient discrimination power for identifying ADL independence, which suggest that the thresholds obtained are reasonable indicators; indicating older adults with sarcopenia-reduced skeletal muscle mass can be independent in ADL if their walking speed is maintained at 0.76 m/s.
This study has a few limitations. First, it was cross-sectional; therefore, the causal relationship between ADL and decreased gait speed remains unknown. To clarify causality, longitudinal follow-up studies of participants are desirable, along with longitudinal validation of the gait speed cutoff value. Second, regarding the reliability of the gait speed cutoff, single-center bias and preexisting conditions may affect its robustness. Frail older adults often have multiple comorbidities, making it difficult to adjust for the effects of these conditions [40]. Considering the skewed distribution of participants’ ADL independence levels, future research would benefit from strategies for gait classification under conditions of class imbalance and limited sample size [41]. Additionally, future research should utilize 3D motion analysis systems for gait speed assessment to employ more reliable measurement tools [42]. Third, this study did not include frailty indices or the Charlson Comorbidity Index [43,44]. Including these indices may improve the robustness of findings. Moreover, this approach does not adequately capture the contribution of cognitive-behavioral factors to instrumental activities of daily living and independence; using a broader battery of tests would improve functional characterization [45]. Furthermore, since DEXA/CT/MRI [46], creatinine excretion [47], and isokinetic dynamometry are also used to assess or evaluate its associations [48], it would be valuable for future research to investigate correlations with these indicators as well. Finally, walking speed is recognized as a key functional indicator in the AWGS 2025 Consensus and an outcome of muscle function decline [1]. Future research should examine this according to various sarcopenia criteria [49].

5. Conclusions

In conclusion, we found that a decreased normal gait speed in patients with sarcopenia was associated with decreased ADL. Furthermore, normal gait speed was highly discriminative of ADL independence. This indicates that a clinical assessment intervention for gait speed can be highly useful for maintaining independent ADL in older adults with sarcopenia.

Author Contributions

Conceptualization, R.S., Y.S., T.H., T.S., L.Y. and T.U.; Data Curation, R.S., Y.S., T.H., T.S., L.Y. and T.U.; Formal Analysis, R.S. and T.U.; Investigation, R.S., Y.S., T.H., T.S., L.Y., S.T. and T.U.; Methodology, R.S., Y.S. and T.U.; Project Administration, R.S., Y.S. and T.U.; Validation, R.S., Y.S., T.H., T.S., L.Y. and T.U.; Visualization, R.S., Y.S., T.H., T.S., L.Y. and T.U.; Writing—Original Draft Preparation, R.S., Y.S., T.H., T.S., L.Y., M.I. and T.U.; Funding Acquisition, Y.S. and T.U.; Supervision, Y.S. and T.U. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Japan Society for the Promotion of Science Grants-in-Aid for Scientific Research (grant numbers 23K06873 and 22K17539).

Institutional Review Board Statement

This study was conducted in accordance with the Declaration of Helsinki and was approved by the ethics committee of the International University of Health and Welfare (Approval no.: 17-Io-189-7; 30 March 2020 and Approval no.: 21-Io-22-3; 22 October 2025).

Informed Consent Statement

Informed consent was obtained from all participants involved in the study.

Data Availability Statement

The data presented in this study are available from the corresponding author only upon reasonable request, due to ethical restrictions.

Acknowledgments

We thank all the participants at the Nishinasuno General Home Care Center.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Chen, L.K.; Hsiao, F.Y.; Akishita, M.; Assantachai, P.; Lee, W.J.; Lim, W.S.; Muangpaisan, W.; Kim, M.; Merchant, R.A.; Peng, L.; et al. A focus shift from sarcopenia to muscle health in the Asian Working Group for Sarcopenia 2025 consensus update. Nat. Aging 2025, 11, 2164–2175. [Google Scholar] [CrossRef]
  2. Zhou, H.; Ding, X.; Luo, M. The association between sarcopenia and functional disability in older adults. J. Nutr. Health Aging 2024, 28, 100016. [Google Scholar] [CrossRef]
  3. Abe, T.; Yoshimura, Y.; Sato, Y.; Nagano, F.; Matsumoto, A. Sarcopenia as a robust predictor of readmission within 6 months among individuals experiencing acute stroke. Ann. Geriatr. Med. Res. 2024, 28, 307–314. [Google Scholar] [CrossRef]
  4. Xiong, L.; Liao, T.; Guo, T.; Zeng, Z.; Wang, S.; Yang, G.; Wang, X.; Wang, X.; Zhu, J.; Zhao, P.; et al. The relationship between sarcopenia and mortality in Chinese community-dwelling adults: A 7-year cohort study with propensity score matching and Mendelian randomization. Front. Endocrinol. 2023, 14, 1215512. [Google Scholar] [CrossRef] [PubMed]
  5. Shen, Y.; Shi, Q.; Nong, K.; Li, S.; Yue, J.; Huang, J.; Dong, B.; Beauchamp, M.; Hao, Q. Exercise for sarcopenia in older people: A systematic review and network meta-analysis. J. Cachexia Sarcopenia Muscle 2023, 14, 1199–1211. [Google Scholar] [CrossRef] [PubMed]
  6. Calvani, R.; Picca, A.; Coelho-Júnior, H.J.; Tosato, M.; Marzetti, E.; Landi, F. Diet for the prevention and management of sarcopenia. Metabolism 2023, 146, 155637. [Google Scholar] [CrossRef] [PubMed]
  7. Kitamura, A.; Seino, S.; Abe, T.; Nofuji, Y.; Yokoyama, Y.; Amano, H.; Nishi, M.; Taniguchi, Y.; Narita, M.; Fujiwara, Y.; et al. Sarcopenia: Prevalence, associated factors, and the risk of mortality and disability in Japanese older adults. J. Cachexia Sarcopenia Muscle 2021, 12, 30–38. [Google Scholar] [CrossRef]
  8. Sato, R.; Sawaya, Y.; Ishizaka, M.; Shiba, T.; Hirose, T.; Urano, T. Assessing nutritional status in older adults requiring long-term care: Interchangeability of bioelectrical impedance analysis and manual methods for upper arm anthropometric measurements. Geriatr. Gerontol. Int. 2022, 22, 938–942. [Google Scholar] [CrossRef]
  9. Sato, R.; Sawaya, Y.; Shiba, T.; Hirose, T.; Ishizaka, M.; Urano, T. Indicators predicting the development and improvement of sarcopenia in older adults requiring long-term care. J. Phys. Ther. Sci. 2023, 35, 242–246. [Google Scholar] [CrossRef]
  10. Shiba, T.; Sato, R.; Sawaya, Y.; Hirose, T.; Ishizaka, M.; Kubo, A.; Urano, T. Sarcopenia with depression presents a more severe disability than only sarcopenia among Japanese older adults in need of long-term care. Medicina 2023, 59, 1095. [Google Scholar] [CrossRef]
  11. Silay, K.; Selvi, O.; Oztorun, H. Sarcopenic obesity is linked to worse clinical outcomes than sarcopenia or obesity alone in hospitalized older adults. BMC Geriatr. 2025, 25, 443. [Google Scholar] [CrossRef] [PubMed]
  12. Ga, H. The Korean long-term care system: 2024 update. Ann. Geriatr. Med. Res. 2024, 28, 235–267. [Google Scholar] [CrossRef] [PubMed]
  13. Takahashi, S.; Yonekura, Y.; Takanashi, N.; Tanno, K. Risk factors of long-term care insurance certification in Japan: A scoping review. Int. J. Environ. Res. Public Health 2022, 19, 2162. [Google Scholar] [CrossRef]
  14. Tsuji, I. Epidemiologic research on healthy life expectancy and proposal for its extension: A revised English version of Japanese in the Journal of the Japan Medical Association. JMA J. 2020, 3, 149–153. [Google Scholar] [CrossRef] [PubMed]
  15. Sato, R.; Sawaya, Y.; Ishizaka, M.; Shiba, T.; Hirose, T.; Urano, T. Association between decreased neck circumference and impaired activities of daily living among older adults in long-term care. Geriatr. Gerontol. Int. 2023, 23, 906–911. [Google Scholar] [CrossRef]
  16. Dai, S.; Wang, S.; Jiang, S.; Wang, D.; Dai, C. Bidirectional association between handgrip strength and ADLs disability: A prospective cohort study. Front. Public Health 2023, 11, 1200821. [Google Scholar] [CrossRef]
  17. Iida, H.; Seki, T.; Sakai, Y.; Watanabe, T.; Wakao, N.; Matsui, H.; Imagama, S. Low muscle mass affect hip fracture treatment outcomes in older individuals: A single-institution case-control study. BMC Musculoskelet. Disord. 2021, 22, 259. [Google Scholar] [CrossRef]
  18. Perez-Sousa, M.A.; Venegas-Sanabria, L.C.; Chavarro-Carvajal, D.A.; Cano-Gutierrez, C.A.; Izquierdo, M.; Correa-Bautista, J.E.; Ramírez-Vélez, R. Gait speed as a mediator of the effect of sarcopenia on dependency in activities of daily living. J. Cachexia Sarcopenia Muscle 2019, 10, 1009–1015. [Google Scholar] [CrossRef]
  19. Pellicer, M.G.; Lusar, A.C.; Casanovas, J.M.; Ferrer, B.S. Effectiveness of a multimodal exercise rehabilitation program on walking capacity and functionality after a stroke. J. Exerc. Rehabil. 2017, 13, 666–675. [Google Scholar] [CrossRef] [PubMed]
  20. Ohmine, T.; Demizu, S.; Murakami, T.; Yoshioka, T.; Aisu, J.; Katsuda, H.; Shimada, N. Improvement in gait speed affects short-term improvement in activities of daily living in patients with moderate and severe knee osteoarthritis. Prog. Rehabil. Med. 2024, 9, 20240002. [Google Scholar] [CrossRef]
  21. Yamada, M.; Arai, H. Long-term care system in Japan. Ann. Geriatr. Med. Res. 2020, 24, 174–180. [Google Scholar] [CrossRef]
  22. Sato, R.; Sawaya, Y.; Hirose, T.; Shiba, T.; Yin, L.; Ishizaka, M.; Urano, T. Screening for sarcopenia using calf muscle circumference in older adults requiring long-term care. J. Nutr. Health Aging 2024, 28, 100006. [Google Scholar] [CrossRef]
  23. Chen, L.K.; Woo, J.; Assantachai, P.; Auyeung, T.W.; Chou, M.Y.; Iijima, K.; Jang, H.C.; Kang, L.; Kim, M.; Kim, S.; et al. Asian Working Group for sarcopenia: 2019 consensus update on sarcopenia diagnosis and treatment. J. Am. Med. Dir. Assoc. 2020, 21, 300–307.e2. [Google Scholar] [CrossRef] [PubMed]
  24. Bouwstra, H.; Smit, E.B.; Wattel, E.M.; van der Wouden, J.C.; Hertogh, C.M.P.M.; Terluin, B.; Terwee, C.B. Measurement properties of the Barthel Index in geriatric rehabilitation. J. Am. Med. Dir. Assoc. 2019, 20, 420–425.e1. [Google Scholar] [CrossRef]
  25. Dos Reis, N.F.; Figueiredo, F.C.X.S.; Biscaro, R.R.M.; Lunardelli, E.B.; Maurici, R. Psychometric properties of the Barthel Index used at intensive care unit discharge. Am. J. Crit. Care 2022, 31, 65–72. [Google Scholar] [CrossRef]
  26. Kaiser, M.J.; Bauer, J.M.; Ramsch, C.; Uter, W.; Guigoz, Y.; Cederholm, T.; Thomas, D.R.; Anthony, P.; Charlton, K.E.; Maggio, M.; et al. Validation of the mini nutritional assessment short-form (MNA-SF): A practical tool for identification of nutritional status. J. Nutr. Health Aging 2009, 13, 782–788. [Google Scholar] [CrossRef] [PubMed]
  27. Akobeng, A.K. Understanding diagnostic tests 3: Receiver operating characteristic curves. Acta Paediatr. 2007, 96, 644–647. [Google Scholar] [CrossRef]
  28. Oliva-Zapata, F.; Ururi-Cupi, K.; Salazar-Talla, L.; Alcantara-Diaz, A.L.; Cuba-Ruiz, S.; Urrunaga-Pastor, D.; Runzer-Colmenares, F.M.; Parodi, J.F. Association between gait speed and balance disorders in older adults from 12 high Andean Peruvian communities, 2013–2019. Ann. Geriatr. Med. Res. 2024, 28, 291–300. [Google Scholar] [CrossRef]
  29. Sato, R.; Sawaya, Y.; Ishizaka, M.; Shiba, T.; Hirose, T.; Urano, T. Leg skeletal muscle mass asymmetry is independently associated with gait speed in older adults requiring long-term care. Geriatr. Gerontol. Int. 2023, 23, 371–375. [Google Scholar] [CrossRef] [PubMed]
  30. Beck Jepsen, D.; Robinson, K.; Ogliari, G.; Montero-Odasso, M.; Kamkar, N.; Ryg, J.; Freiberger, E.; Masud, T. Predicting falls in older adults: An umbrella review of instruments assessing gait, balance, and functional mobility. BMC Geriatr. 2022, 22, 615. [Google Scholar] [CrossRef]
  31. Toots, A.; Rosendahl, E.; Lundin-Olsson, L.; Nordström, P.; Gustafson, Y.; Littbrand, H. Usual gait speed independently predicts mortality in very old people: A population-based study. J. Am. Med. Dir. Assoc. 2013, 14, 529.e1–529.e6. [Google Scholar] [CrossRef] [PubMed]
  32. Soto, R.; Díaz, L.A.; Rivas, V.; Fuentes-López, E.; Zalaquett, M.; Bruera, M.J.; González, C.; Mezzano, G.; Benítez, C. Frailty and reduced gait speed are independently related to mortality of cirrhotic patients in long-term follow-up. Ann. Hepatol. 2021, 25, 100327. [Google Scholar] [CrossRef]
  33. Sawaya, Y.; Hirose, T.; Shiba, T.; Sato, R.; Yin, L.; Kubo, A.; Urano, T. Decrease in the usual walking speed and body fat percentage associated with a deterioration in long-term care insurance certification levels. PeerJ 2024, 12, e17529. [Google Scholar] [CrossRef]
  34. Wang, D.X.M.; Yao, J.; Zirek, Y.; Reijnierse, E.M.; Maier, A.B. Muscle mass, strength, and physical performance predicting activities of daily living: A meta-analysis. J. Cachexia Sarcopenia Muscle 2020, 11, 3–25. [Google Scholar] [CrossRef]
  35. Ji, S.; Baek, J.Y.; Go, J.; Lee, C.K.; Yu, S.S.; Lee, E.; Jung, H.W.; Jang, I.Y. Effect of exercise and nutrition intervention for older adults with impaired physical function with preserved muscle mass (functional sarcopenia): A randomized controlled trial. Clin. Interv. Aging 2025, 20, 161–170. [Google Scholar] [CrossRef]
  36. de Souza, A.F.; de Oliveira, D.C.; Ramírez, P.C.; de Oliveira, M.R.; Luiz, M.M.; Delinocente, M.L.B.; Steptoe, A.; de Oliveira, C.; da Silva Alexandre, T. Low gait speed is better than frailty and sarcopenia at identifying the risk of disability in older adults. Age Ageing 2025, 54, afaf104. [Google Scholar] [CrossRef]
  37. Abellan van Kan, G.; Rolland, Y.; Andrieu, S.; Bauer, J.; Beauchet, O.; Bonnefoy, M.; Cesari, M.; Donini, L.M.; Gillette Guyonnet, S.; Inzitari, M.; et al. Gait speed at usual pace as a predictor of adverse outcomes in community-dwelling older people an International Academy on Nutrition and Aging (IANA) Task Force. J. Nutr. Health Aging 2009, 13, 881–889. [Google Scholar] [CrossRef]
  38. Montero-Odasso, M.; Schapira, M.; Soriano, E.R.; Varela, M.; Kaplan, R.; Camera, L.A.; Mayorga, L.M. Gait velocity as a single predictor of adverse events in healthy seniors aged 75 years and older. J. Gerontol. A Biol. Sci. Med. Sci. 2005, 60, 1304–1309. [Google Scholar] [CrossRef] [PubMed]
  39. Kitamura, M.; Izawa, K.P.; Ishihara, K.; Matsuda, H.; Okamura, S.; Fujioka, K. Physical activity and sarcopenia in community-dwelling older adults with long-term care insurance. Eur. J. Investig. Health Psychol. Educ. 2021, 11, 1610–1618. [Google Scholar] [CrossRef] [PubMed]
  40. Aoki, T.; Yamamoto, Y.; Ikenoue, T.; Onishi, Y.; Fukuhara, S. Multimorbidity patterns in relation to polypharmacy and dosage frequency: A nationwide, cross-sectional study in a Japanese population. Sci. Rep. 2018, 8, 3806. [Google Scholar] [CrossRef]
  41. Trabassi, D.; Castiglia, S.F.; Bini, F.; Marinozzi, F.; Ajoudani, A.; Lorenzini, M.; Chini, G.; Varrecchia, T.; Ranavolo, A.; De Icco, R.; et al. Optimizing rare disease gait classification through data balancing and generative AI: Insights from hereditary cerebellar ataxia. Sensors 2024, 24, 3613. [Google Scholar] [CrossRef]
  42. Scataglini, S.; Abts, E.; Van Bocxlaer, C.; Van den Bussche, M.; Meletani, S.; Truijen, S. Accuracy, validity, and reliability of markerless camera-based 3D motion capture systems versus marker-based 3D motion capture systems in gait analysis: A systematic review and meta-analysis. Sensors 2024, 24, 3686. [Google Scholar] [CrossRef]
  43. Shashikumar, S.A.; Huang, K.; Konetzka, R.T.; Joynt Maddox, K.E. Claims-based frailty indices: A systematic review. Med. Care 2020, 58, 815–825. [Google Scholar] [CrossRef]
  44. Charlson, M.E.; Carrozzino, D.; Guidi, J.; Patierno, C. Charlson Comorbidity Index: A critical review of clinimetric properties. Psychother. Psychosom. 2022, 91, 8–35. [Google Scholar] [CrossRef] [PubMed]
  45. Gutierrez-Arias, R.; Neculhueque-Zapata, X.; Valenzuela-Suazo, R.; Oliveros, M.J.; Morales, C.; Vásquez, L.; Jalil, Y.; Marzuca-Nassr, G.N.; Inostroza Quiroz, J.L.; Fuentes-Aspe, R.; et al. Assessment of activities and participation of people by rehabilitation-focused clinical registries: A systematic scoping review. Eur. J. Phys. Rehabil. Med. 2023, 59, 640–652. [Google Scholar] [CrossRef] [PubMed]
  46. Vogele, D.; Otto, S.; Sollmann, N.; Haggenmüller, B.; Wolf, D.; Beer, M.; Schmidt, S.A. Sarcopenia-definition, radiological diagnosis, clinical significance. Rofo 2023, 195, 393–405. [Google Scholar] [CrossRef]
  47. Papadopoulou, S.K.; Voulgaridou, G.; Kondyli, F.S.; Drakaki, M.; Sianidou, K.; Andrianopoulou, R.; Rodopaios, N.; Pritsa, A. Nutritional and nutrition-related biomarkers as prognostic factors of sarcopenia, and their role in disease progression. Diseases 2022, 10, 42. [Google Scholar] [CrossRef] [PubMed]
  48. Steffl, M.; Stastny, P. Isokinetic testing of muscle strength of older individuals with sarcopenia or frailty: A systematic review. Isokinet. Exerc. Sci. 2020, 28, 291–301. [Google Scholar] [CrossRef]
  49. Stuck, A.K.; Basile, G.; Freystaetter, G.; de Godoi Rezende Costa Molino, C.; Lang, W.; Bischoff-Ferrari, H.A. Predictive validity of current sarcopenia definitions (EWGSOP2, SDOC, and AWGS2) for clinical outcomes: A scoping review. J. Cachexia Sarcopenia Muscle 2023, 1, 71–83. [Google Scholar] [CrossRef]
Figure 1. Selection process flowchart for the study participants.
Figure 1. Selection process flowchart for the study participants.
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Figure 2. Receiver operating characteristic curve analysis to identify independence for activities of daily living owing to gait speed. AUC, area under the curve; CI, confidence interval.
Figure 2. Receiver operating characteristic curve analysis to identify independence for activities of daily living owing to gait speed. AUC, area under the curve; CI, confidence interval.
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Table 1. Overall participant characteristics.
Table 1. Overall participant characteristics.
Total (n = 72)
Sex (Women: %)31.0%
Age (years)82.1 ± 6.7
Height (cm)157.2 ± 8.7
Weight (kg)53.0 ± 8.2
BMI (kg/m2)21.4 ± 2.9
Barthel Index (score)90 (83.8–100)
Grip strength (kg)18.8 ± 6.0
Gait speed (m/s)0.7 ± 0.2
SMI (kg/m2)5.9 ± 0.7
Malnutrition (%)26.4%
At risk of malnutrition (%)47.2%
Non-malnutrition (%)26.4%
The data are denoted as mean ± standard deviation or median (1st–3rd quartiles). BMI, body mass index, SMI, skeletal muscle mass index. SMI = skeletal muscle mass (kg)/height2 (m2); BMI = weight (kg)/height2 (m2).
Table 2. Correlations between variables.
Table 2. Correlations between variables.
Barthel Index (Score) Age (Years)BMI (kg/m2)Grip Strength (kg)Gait Speed (m/s)SMI (kg/m2)MNA-SF
(Score)
(Total)
Barthel Index (score) −0.06 (0.633)0.01 (0.923)0.26 (0.028)0.47 (<0.001)0.13 (0.284)0.08 (0.526)
Age (years)−0.07 (0.575)−0.15 (0.210)0.00 (0.993)0.00 (0.972)0.13 (0.281)
BMI (kg/m2)0.02 (0.857)−0.11 (0.360)0.16 (0.189)0.40 (0.001)
Grip strength (kg)0.36 (0.002)0.60 (<0.001)0.21 (0.074)
Gait speed (m/s)0.21 (0.076)0.12 (0.314)
SMI (kg/m2)0.29 (0.014)
MNA-SF (score)
(Men)
Barthel Index (score) 0.10 (0.549)0.01 (0.946)0.26 (0.097)0.49 (0.001)−0.01 (0.948)0.15 (0.354)
Age (years)−0.16 (0.311)−0.20 (0.208)0.13 (0.0.433)0.17 (0.301)0.15 (0.348)
BMI (kg/m2)−0.01 (0.926)−0.11 (0.489)0.28 (0.072)0.29 (0.063)
Grip strength (kg)0.30 (0.058)0.05 (0.744)0.19 (0.244)
Gait speed (m/s)0.03 (0.832)0.13 (0.429)
SMI (kg/m2)0.21 (0.211)
MNA-SF (score)
(Women)
Barthel Index (score) −0.20 (0.282)0.02 (0.934)0.33 (0.074)0.45 (0.011)0.17 (0.348)−0.09 (0.630)
Age (years)0.03 (0.858)−0.08 (0.662)−0.15 (0.411)−0.06 (0.752)0.12 (0.526)
BMI (kg/m2)0.17 (0.354)−0.10 (0.580)0.32 (0.081)0.47 (0.008)
Grip strength (kg)0.24 (0.201)0.28 (0.132)0.18 (0.336)
Gait speed (m/s)0.02 (0.914)−0.05 (0.783)
SMI (kg/m2)0.32 (0.0076)
MNA-SF (score)
BMI, body mass index; MNA-SF, Mini Nutritional Assessment Scale-Short Form; SMI, skeletal muscle mass index. SMI = skeletal muscle mass (kg)/height2 (m2); BMI = body weight (kg)/height2 (m2); values between parentheses indicate p-values.
Table 3. Factors related to activities of daily living according to the multiple regression analysis.
Table 3. Factors related to activities of daily living according to the multiple regression analysis.
βB95% CIp-ValueVIF
Gait speed (m/s)0.4519.53(9.54–29.52)<0.0011.18
Sex (Men: 0, Women: 1)0.214.49(−4.09–13.06)0.3003.68
Age (years)−0.02−0.04(−0.38–0.31)0.8381.06
BMI (kg/m2)0.110.42(−0.44–1.27)0.33721.25
Grip strength (kg)0.270.49(−0.07–1.04)0.08412.19
SMI (kg/m2)0.040.65(−4.85–6.14)0.81483.22
MNA-SF (score)−0.04−0.16(−1.14–0.81)0.7391.28
β, standardized regression coefficient; B, unstandardized regression coefficient; CI, confidence interval; BMI, body mass index; MNA-SF, Mini Nutritional Assessment-Short Form; SMI, skeletal muscle mass index; VIF, variance inflation factor. SMI = skeletal muscle mass (kg)/height2 (m2); BMI = weight (kg)/height2 (m2).
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Sato, R.; Sawaya, Y.; Hirose, T.; Shiba, T.; Yin, L.; Tsuji, S.; Ishizaka, M.; Urano, T. Declines in Activities in Daily Living of Older Adults with Sarcopenia Were Associated with Gait Speed. Medicina 2026, 62, 263. https://doi.org/10.3390/medicina62020263

AMA Style

Sato R, Sawaya Y, Hirose T, Shiba T, Yin L, Tsuji S, Ishizaka M, Urano T. Declines in Activities in Daily Living of Older Adults with Sarcopenia Were Associated with Gait Speed. Medicina. 2026; 62(2):263. https://doi.org/10.3390/medicina62020263

Chicago/Turabian Style

Sato, Ryo, Yohei Sawaya, Tamaki Hirose, Takahiro Shiba, Lu Yin, Shuntaro Tsuji, Masahiro Ishizaka, and Tomohiko Urano. 2026. "Declines in Activities in Daily Living of Older Adults with Sarcopenia Were Associated with Gait Speed" Medicina 62, no. 2: 263. https://doi.org/10.3390/medicina62020263

APA Style

Sato, R., Sawaya, Y., Hirose, T., Shiba, T., Yin, L., Tsuji, S., Ishizaka, M., & Urano, T. (2026). Declines in Activities in Daily Living of Older Adults with Sarcopenia Were Associated with Gait Speed. Medicina, 62(2), 263. https://doi.org/10.3390/medicina62020263

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