Sarcopenia and cognitive performance in hospitalized older adults: evidence of an association

Introduction: Population aging increases the coexistence of geriatric syndromes, including sarcopenia and cognitive impairment, which negatively affect functional prognosis and clinical outcomes. Evidence on the association between sarcopenia and cognitive performance in hospitalized elderly individuals, particularly across cognitive domains, remains limited. Therefore, the objective of this study was to investigate the association between sarcopenia and cognitive performance, both globally and across specific cognitive domains, in hospitalized elderly individuals.

Methods: This observational cross-sectional study included elderly patients hospitalized in a medium-sized hospital in São Paulo, Brazil, from 2024 to 2025, evaluated within the first 48 hours of admission. Exclusion criteria included weight-loss diets, chronic renal failure on dialysis, paresis or hemiparesis due to stroke, altered body fluid levels, pacemaker use, and chronic corticosteroid therapy. Sarcopenia screening and diagnosis followed the European Consensus criteria, and cognitive performance was assessed using the Mini-Mental State Examination (MMSE). Comparative analyses were conducted among non-sarcopenic, sarcopenia risk, and sarcopenic groups, including correlations with sociodemographic variables.

Results: Eighty-four older adults were assessed (54.76% women; mean age 68.1 ± 6.7 years). Sarcopenia risk was identified in 29.76% and confirmed sarcopenia in 19.05%. MMSE scores showed a moderate negative correlation with age (r = −0.48; p < 0.0001) and positive correlations with education (r = 0.58; p < 0.0001), physical activity (r = 0.31; p = 0.0038), and income (r = 0.23; p = 0.0326). Mean MMSE scores differed significantly among groups: non-sarcopenic (26.84 ± 3.24), sarcopenia risk (22.32 ± 5.86), and sarcopenic (18.69 ± 7.98) (p < 0.0001). Worse performance in orientation, attention/calculation, and language was observed in the sarcopenia risk and sarcopenia groups (p < 0.001).

Conclusion: Sarcopenia, even at early stages, is associated with reduced global cognitive performance and specific impairments in orientation, attention/calculation, and language in hospitalized elderly individuals. These findings underscore the importance of early screening and targeted interventions to preserve both muscle and cognitive health, reinforcing the need for integrated care strategies in hospital settings.

1 Introduction

Population aging is a global phenomenon that poses significant challenges to health systems, particularly in maintaining the functionality, autonomy, and quality of life of older adults (Corrao et al., 2025). In this context, sarcopenia, characterized by the progressive and widespread loss of muscle mass, strength, and function, has emerged as a major public health challenge (Cruz-Jentoft et al., 2019).

The prevalence of sarcopenia increases proportionally with age and is associated with a series of adverse outcomes, including functional decline, increased risk of falls and fractures, loss of independence, and increased mortality (Kirk et al., 2024). Global estimates indicate a prevalence ranging from 2 to 17%, with an average of approximately 10% (Petermann-Rocha et al., 2021). In Brazil, this rate is even higher, reaching 28.6% in certain studies, depending on the diagnostic criteria used (Diz et al., 2016), which highlights the urgency of adequate diagnostic and preventive strategies.

Aging is a significant and independent cause for the development of sarcopenia, contributing to marked functional limitations and worsening of pre-existing clinical conditions, especially in hospitalized elderly individuals (Fernandes et al., 2022; Veronese et al., 2019). Furthermore, it is associated with unfavorable clinical outcomes, including longer hospital stays, an increased risk of complications, and higher healthcare costs (Álvarez-Bustos et al., 2022; Tan et al., 2017). The severity of this condition justifies recent efforts to standardize its definition and diagnosis.

In recent decades, advances in the field have culminated in the development of international consensus guidelines that standardize the definition and diagnosis of sarcopenia. The 2019 European Consensus, for example, introduced a staged classification (probable, confirmed, and severe), facilitating clinical practice and therapeutic targeting (Cruz-Jentoft et al., 2019). The 2024 International Consensus reaffirms the need to simultaneously consider loss of muscle mass, strength, and function in the diagnosis (Kirk et al., 2024).

In addition to its physical impacts, sarcopenia has been increasingly associated with cognitive impairment, including dementia, neuropsychiatric disorders, and brain atrophy (Huang et al., 2025; Tolea and Galvin, 2015). This bidirectional relationship between muscle function and cognitive health underscores the importance of integrated assessments. To measure cognitive performance, the Mini-Mental State Examination (MMSE) stands out as a validated instrument that assesses domains such as orientation, visuospatial constructive ability, immediate memory, recall, attention, and calculation, in addition to language (Wu et al., 2024).

However, although the literature recognizes the correlation between sarcopenia and cognitive decline, the most affected domains in hospitalized elderly individuals with sarcopenia have not yet been clarified. Determining which areas of cognitive functioning are most impacted can inform personalized clinical interventions and strengthen interdisciplinary approaches in the hospital setting.

Therefore, the objective of this study was to investigate the association between sarcopenia and cognitive performance, both globally and by domains, in hospitalized elderly individuals.

2 Materials and methods

2.1 Study design

This observational, cross-sectional study was conducted in a medium-sized hospital located in the interior of the state of São Paulo, Brazil, between September 2024 and May 2025.

2.2 Participants

Patients aged 60 years or older, of both sexes, hospitalized in clinical wards and evaluated within the first 48 h of admission were included. Inclusion criteria required sufficient clinical and cognitive ability to understand and actively participate in the administration of the instruments. Participation was voluntary and subject to signing the Informed Consent Form (ICF). Patients undergoing palliative care; with severe physical limitations that prevented assessment of muscle strength or cognitive status; with pacemakers or metal valves; with generalized edema or anasarca; undergoing renal replacement therapy; on severely restricted diets; on prolonged use of corticosteroids; with paresis or plegia; inability to remain upright; neuromuscular diseases; suspected or confirmed highly transmissible infectious diseases or in isolation; and those with advanced dementia syndromes or inability to respond for themselves were excluded.

The study included 105 elderly patients admitted to a medium-sized hospital in the interior of São Paulo state, Brazil. Of these, 84 met the eligibility criteria and underwent the proposed assessments. Those hospitalized for up to 48 h were considered eligible to minimize biases related to prolonged hospitalization.

2.3 Data collection procedures

The sample selection was based on screening of electronic hospital records. After identifying eligible patients, the researchers employed a face-to-face bedside approach to present the research objectives. Those who understood the proposal and consented to participate signed the informed consent form.

Data collection involved structured interviews to obtain sociodemographic information (age, sex, education, origin), clinical information (comorbidities, continuous use of medications, history of hospitalizations and falls), and behavioral information (smoking, alcohol consumption and physical activity).

2.3.1 Assessment of sarcopenia

Sarcopenia was investigated according to the guidelines of the European Working Group on Sarcopenia in Older People 2 (Cruz-Jentoft et al., 2019), through a three-stage protocol: Stage 1 consisted of screening using the SARC-F questionnaire (Strength, Assistance with walking, Rise from a chair, Climb stairs, and Falls), consisting of five items on strength, assistance with locomotion, ability to get up from a chair, climb stairs, and occurrence of falls in the last 12 months. The score ranges from 0 to 10, with a score of ≥ 4 indicating a risk of sarcopenia. Stage 2 involved assessing muscle strength/dynamometry, with handgrip strength measured using a hand dynamometer (Jamar) according to a standardized protocol. Three alternating measurements were taken on each hand, with a minimum interval of 1 min to avoid fatigue. Values were expressed in kilogram-force (kgf) and calculated as the average of three measurements of the dominant hand.

The adopted cutoff points were <27 kgf for men and <16 kgf for women. In the third stage, to confirm sarcopenia by detecting low muscle quantity/quality, a tetrapolar bioelectrical impedance device (Biodynamics®, model 450) was used. Individuals with muscle mass <20 kg (men) and <15 kg (women) were considered sarcopenic, according to the equation by Janssen et al. (2000).

2.3.2 Assessment of cognition

Cognitive function was assessed using the Mini-Mental State Examination (MMSE), which comprises tests of orientation (temporal and spatial), immediate and delayed memory, attention, calculation, language, comprehension, and motor skills. The maximum score is 30 points, and the following categories were adopted to classify cognitive performance: ≥ 25 points (preserved cognition), 21–24 (mild impairment), 10–20 (moderate impairment), and < 9 points (severe impairment).

In the moment of MMSE application, the data about muscle mass, strength and sarcopenia status were not available yet to the test performers. The results were appreciated only once the MMSE was concluded.

2.4 Data processing and statistical analysis

After collection, the data were anonymized and tabulated in a spreadsheet (Microsoft Excel®). Statistical analysis was conducted using BioEstat® software, version 5.3. Comparison tests between groups and correlation analysis were applied according to data distribution, with a significance level set at p < 0.05. The following statistical tests were used: Spearman’s correlation test and Mann–Whitney test.

2.5 Ethical aspects

The study was approved by the Research Ethics Committee of the University of Marília, São Paulo, Brazil, under opinion number 5.467.081 em 13/06/2022.

3 Results

The paragraph was included in the Methods section, 2.2 Participants.

Initial screening for sarcopenia was performed using the SARC-F questionnaire, with a mean score of 2.46 ± 2.68. Twenty-five individuals (29.76%) obtained a score ≥ 4 and were classified as at risk for sarcopenia. Handgrip strength allowed for stratification of the sample into two groups: those with and those without dynapenia. Forty-two elderly individuals (50%) were identified with reduced muscle strength, including 24 women (57.14%) and 18 men (42.86%). Body composition analysis, obtained by bioelectrical impedance analysis, identified 16 participants (19.05%) with reduced appendicular skeletal muscle mass. Based on handgrip strength and muscle mass parameters, the sample was classified into three groups: healthy (n = 37), at risk of sarcopenia (n = 31), and sarcopenic (n = 16).

Table 1 presents the sociodemographic characteristics of the sample. There was a predominance of females (54.76%), an age range from 60 to 69 years (51.19%), and self-reported white skin color (67.86%). Regarding education, more than half had completed elementary school at most, and 21.43% were illiterate. Most participants reported a monthly income of less than two minimum wages (79.77%) and a lack of regular physical activity (60.71%).

Table 1

Table 1. Sociodemographic characterization of hospitalized elderly individuals participating in the study (n = 84).

The Mini-Mental State Examination (MMSE) was administered to the three groups defined by muscle status. Table 2 presents the correlation coefficients between cognitive scores and sociodemographic variables. A moderate negative correlation was observed between age and cognitive performance (r = −0.4799, p < 0.0001), indicating a progressive decline in cognitive performance associated with aging. Education demonstrated a significant positive correlation (r = 0.5842; p < 0.0001), suggesting a protective effect of education on cognitive domains. Positive correlations, although of lesser magnitude, were also observed with physical activity (r = 0.3124; p = 0.0038), alcohol consumption (r = 0.3235; p = 0.0027) and monthly income (r = 0.2333; p = 0.0326). No significant correlations were observed for the variables sex (r = 0.0496; p = 0.6542) and smoking (r = −0.0154; p = 0.8896).

Table 2

Table 2. Correlation between the score obtained in the mini-mental assessment test and the sociodemographic variables evaluated.

The analysis of the MMSE means between sociodemographic groups, presented in Table 3, revealed statistically significant differences according to age, education, income, physical activity, and alcohol consumption. Individuals aged 60 to 69 years had a higher mean score (25.74 ± 4.47) than those aged ≥ 70 years (21.39 ± 6.98; p = 0.0010). Cognitive performance increased progressively with education level, with participants with elementary school II standing out (27.05 ± 2.98), while illiterate individuals had the lowest scores (20.35 ± 6.70; p < 0.0001). Elderly individuals with an income higher than two minimum wages demonstrated higher cognitive performance (27.44 ± 2.42) compared to those with lower incomes (22.72 ± 6.48; p = 0.0034). Regular physical activity was associated with higher scores (26.15 ± 3.77) compared to inactive individuals (21.98 ± 6.90; p = 0.0047).

Table 3

Table 3. Comparison of the mean score on the mini-mental state examination according to sociodemographic variables (n = 84).

The mean score on the Mini-Mental State Examination (MMSE) varied significantly between the groups defined by the risk or presence of sarcopenia, as shown in Table 4. Non-sarcopenic individuals had a higher mean score (26.84 ± 3.24), followed by those at risk (22.32 ± 5.86) and sarcopenic individuals (18.69 ± 7.98). There was a statistically significant difference between non-sarcopenic and at-risk individuals (p = 0.0003), as well as between non-sarcopenic and sarcopenic individuals (p < 0.0001). No significant difference was observed between the at-risk and sarcopenic groups (p = 0.1269). When considered together, at-risk or sarcopenic individuals obtained a significantly lower score (21.09 ± 6.80) compared to non-sarcopenic individuals (26.84 ± 3.24; p < 0.0001).

Table 4

Table 4. Comparison of mini-mental state examination scores in non-sarcopenic elderly individuals at risk of sarcopenia and sarcopenic individuals (n = 84).

Figure 1 illustrates the distribution of MMSE scores across groups. A trend toward progressive decline in cognitive performance was observed as muscle condition worsened. The healthy group had the highest median (26.8 points), followed by the at-risk group (22.3 points), while the sarcopenic group had the lowest (18.6 points). Furthermore, the interquartile range was wider in the at-risk and sarcopenic groups, reflecting greater cognitive variability.

Figure 1

Figure 1. Distribution of Mini-Mental State Examination (MMSE) scores according to sarcopenic classification in hospitalized elderly individuals. Boxplot representing the distribution of MMSE scores in non-sarcopenic at-risk and sarcopenic elderly individuals. The center line of each box indicates the median. The upper and lower limits represent the 1st and 3rd quartiles, and the ends of the bars indicate the minimum and maximum values within 1.5 times the interquartile range. Points outside the bars represent outliers. A trend toward progressive reduction in cognitive scores is observed as the sarcopenic state worsens, with the lowest values identified in the sarcopenic group.

In the analysis of the MMSE domains, patients without signs of sarcopenia were compared to those classified as at risk or sarcopenic. The domains evaluated were: temporal–spatial orientation, registration, attention and calculation, remote memory, and language. Significant differences were observed for orientation, attention, calculation, and language (p = 0.0003, p = 0.0015, and p < 0.0001, respectively). The registration (p = 0.4778) and remote memory (p = 0.0752) domains did not present statistically significant differences (Table 5).

Table 5

Table 5. Comparison of the score obtained in each domain assessed in the mini-mental test between non-sarcopenic elderly people and those at risk or with sarcopenia.

4 Discussion

This study revealed a high prevalence of sarcopenia and dynapenia in elderly hospitalized patients, demonstrating a significant association between muscle status and cognitive decline, particularly in the domains of attention/calculation, orientation, and language. Our findings suggest that sarcopenia is not only associated with loss of muscle mass and function but may also negatively impact specific cognitive functions, reinforcing the importance of assessing sarcopenia in hospital settings.

Considering the accelerated aging of the population and the consequent increase in the prevalence of chronic conditions, it is urgent to understand how the loss of muscle mass and function can negatively impact cognition in clinical settings. Growing evidence indicates that sarcopenia is not limited to physical consequences but is also related to neurocognitive changes, suggesting a multifactorial interaction that compromises autonomy and quality of life in aging (Hsu et al., 2024; Kannan and Arunachalam, 2025; Kim et al., 2024).

Half of the individuals with sarcopenia had moderate cognitive impairment, and 12.5% had severe impairment, while only 31.25% maintained preserved cognition. In contrast, in the group without sarcopenia, 83.78% had preserved cognitive function, and no cases of severe impairment were identified. These results reinforce the hypothesis that the severity of sarcopenia is proportionally associated with the magnitude of cognitive decline.

In the sarcopenia risk group, cognitive changes were also significant, with only 45.16% of individuals showing preserved cognition, and a significant distribution between mild (22.58%), moderate (20.32%), and severe (22.58%) levels of impairment. These data reinforce the hypothesis that even the risk of sarcopenia is already associated with cognitive impairments, possibly related to standard pathophysiological mechanisms, such as low-grade chronic inflammation, oxidative stress, metabolic dysfunction, and reduced physical activity (Arosio et al., 2023; Yang et al., 2022; Shlisky et al., 2017).

Similar results were observed by Li et al. (2022), who identified a significant association between sarcopenia and cognitive decline, particularly in the domains of attention and calculation, in hospitalized elderly Chinese individuals. Similarly, Dong et al. (2024) demonstrated that individuals with sarcopenia had lower scores in executive functions, verbal fluency, calculation, and delayed recall memory, reinforcing the hypothesis that muscle loss influences multiple cognitive domains.

Physical activity showed a moderate correlation with Mini-Mental State Examination scores (r = 0.3124), suggesting a positive association between higher activity levels and better cognitive performance. It is noteworthy that a sedentary lifestyle was prevalent in more than half of the sample (60.71%), reinforcing the vulnerability of this population to neurocognitive impairment. The literature has consistently highlighted the importance of regular physical exercise, especially when combined with a balanced diet, as a key protective factor for brain function in older adults. This beneficial effect is partially mediated by the release of neuroactive myokines, such as irisin, cathepsin B, BDNF (Brain-Derived Neurotrophic Factor), IL-6, and LIF, produced by skeletal muscle during muscle contraction. These substances promote the neuroplasticity of synaptic function and cognitive integrity throughout the aging process. Conversely, the reduction in muscle mass often observed in physically inactive individuals compromises the release of these myokines and may contribute to the acceleration of cognitive decline (Arosio et al., 2023; Scisciola et al., 2021; Sui et al., 2020; Lim et al., 2022).

Recent evidence indicates that higher educational attainment is positively associated with gray matter volume in several cortical regions, which appears to mediate the prevention of sarcopenia in older adults indirectly. This relationship suggests a bidirectional communication between brain and muscle, in which the central nervous system regulates muscle function through neuromuscular junctions, while muscle tissue influences brain function through the release of cytokines such as myokines (Arosio et al., 2023; Zhang et al., 2024; Lu et al., 2024). In the present study, it was observed that more than 50% of the participants had 4 years of schooling or less, which was strongly associated with the presence of sarcopenia. These data corroborate the findings of Gabriela et al. (2023), that who in an observational study conducted with elderly Brazilians, identified that 61.7% of individuals with sarcopenia had between one and 4 years of schooling. Thus, education, as a marker of cognitive capital and a socioeconomic indicator, should be considered a critical variable in the formulation of preventive strategies and public policies aimed at reducing sarcopenia in the elderly population.

Furthermore, higher health literacy is associated with better awareness and understanding of clinical conditions such as sarcopenia. Individuals with higher educational levels tend to adopt healthier lifestyles characterized by a balanced diet and regular physical activity—key factors in preventing and managing this condition (Rao et al., 2025; Wang et al., 2024).

A comparative analysis between the groups revealed statistically significant differences in Mini-Mental State Examination (MMSE) scores, with lower scores observed in individuals at risk for or with a confirmed diagnosis of sarcopenia compared to those without the condition (Table 4 and Figure 1). These results corroborate previous findings in the literature, which indicate a dose-dependent association between sarcopenia severity and cognitive impairment (Peng et al., 2019). Furthermore, data from studies suggest that individuals with sarcopenia have a two-fold increased risk of impaired cognitive function, with this risk significantly increased in cases of severe sarcopenia (Ohta et al., 2023).

In a longitudinal study conducted with a Chinese population (Zhang et al., 2023), demonstrated a bidirectional relationship between sarcopenia and cognitive function. Primary sarcopenia was associated with lower subsequent cognitive performance, while lower initial cognitive scores also predicted a higher risk of future sarcopenia, suggesting a feedback dynamic between both conditions. Furthermore, Yigit et al. (2022) observed that elderly individuals with cognitive impairment had a significantly higher prevalence of sarcopenia (15.4%) compared to those with preserved cognition (3.7%), reinforcing the existence of a clinically relevant association (Zhang et al., 2023; Yigit et al., 2022).

Analysis of the cognitive domains assessed by MMSE revealed statistically significant differences between the study groups. Individuals classified as “at risk for sarcopenia” and “sarcopenic” presented lower performance in the domains of orientation (p = 0.0003), attention/calculation (p = 0.0015), and language (p < 0.0001) compared to non-sarcopenic individuals. These results suggest an association between the presence of sarcopenia and cognitive impairment, reinforcing the hypothesis that muscle mass loss may be related to deficits in specific cognitive functions. This finding highlights the importance of cognitive assessments in elderly individuals with sarcopenia, although confounding factors and longitudinal studies are needed to confirm this association.

In the language domain, the difference observed in our study was statistically significant, confirming the results of the English Longitudinal Study of Ageing (ELSA), which demonstrated an association between sarcopenia and impairments in multiple cognitive domains, particularly verbal fluency. In this study, individuals with sarcopenia were more likely to perform poorly on verbal fluency tests, reinforcing the hypothesis that reduced muscle mass and strength can directly impact language skills, consequently affecting the autonomy of older adults (Maniscalco et al., 2024).

Our study has some limitations. First, it is a cross-sectional study that only observed patients up to 48 h after hospitalization, making it impossible to draw causal conclusions. Second, it was conducted with a sample from a single center. Finally, it uses only one screening instrument to assess the degree of global cognition (MMSE), which may limit the ability to detect specific interferences in the cognitive domains addressed. Overall, these limitations suggest the need for caution in interpreting the results and for further research in this area.

It is important to acknowledge the limitations in this present study. First, it must be clear about the limitation showed by the small sample selected for the statistical tests, specifically the small number of participants included in the sarcopenic subgroup. A further limitation concerns the exclusive use of the MMSE in a sample with widely varying educational levels. Because the MMSE does not incorporate education-adjusted cutoffs in its scoring, cognitive status may have been underestimated among participants with lower schooling, thereby limiting the interpretability of the results. Additionally, the domain-specific analyses should be interpreted with caution, as MMSE subdomains have limited psychometric validity for fine-grained cognitive profiling. Future studies should employ neurocognitive instruments that provide more robust adjustment for education and allow a more precise assessment of specific cognitive domains.

Another important limitation of this study is the absence of multivariable adjustments, which prevents conclusions about independent relationships between sarcopenia and cognitive performance. Although meaningful associations were identified, these findings may be partially influenced by unmeasured or uncontrolled confounders. Future studies with larger samples and sufficient statistical power are needed to apply multivariate models capable of clarifying the relative contributions of demographic, clinical, and functional factors to the associations observed.

It is important to acknowledge that bioelectrical impedance analysis (BIA) is sensitive to variations in hydration status, which may compromise the accuracy of body composition estimates in hospitalized individuals. Although the study adopted exclusion criteria related to evident hydration disturbances, subclinical fluctuations may still occur during hospitalization and influence parameters such as fat-free mass and total body water. This methodological limitation should be considered when interpreting the results. Future investigations may incorporate reference techniques (e.g., DEXA or computed tomography) to enhance measurement precision and reduce potential biases.

Overall, these findings underscore that sarcopenia, even in its early stages, is significantly associated with global cognitive impairment in hospitalized elderly individuals, with notable deficits in attention/calculation and language domains. This highlights the importance of early screening for sarcopenia in clinical settings, enabling timely interventions that may simultaneously preserve muscle function and cognitive health. Future studies employing longitudinal designs and comprehensive cognitive assessments are warranted to further elucidate these associations.

It is important to distinguish statistical significance from clinical relevance when interpreting the findings of this study. Although some differences between groups reached statistical significance, the magnitude of these effects must be evaluated in the context of their actual clinical impact on the population assessed. In hospitalized older adults, small variations in muscle or cognitive parameters may achieve statistical significance due to the sensitivity of the tests employed, yet may not represent changes substantial enough to modify clinical decision-making or prognosis. Therefore, the results should be understood as indicative of meaningful trends, while their clinical applicability must be interpreted with caution and complemented by future investigations capable of more robustly quantifying the clinical weight of these associations.

Data availability statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.

Ethics statement

The studies involving humans were approved by Research Ethics Committee of the University of Marília (UNIMAR). It was recognized by CONEP under registration n° 25000.00764/2007–47, on January 18, 2007. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.

Author contributions

OS: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Visualization, Writing – original draft, Writing – review & editing. LG: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Validation, Visualization, Writing – original draft, Writing – review & editing, Project administration. CS: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Validation, Visualization, Writing – original draft, Writing – review & editing. SB: Conceptualization, Data curation, Formal analysis, Methodology, Validation, Visualization, Writing – original draft, Writing – review & editing, Resources, Software, Supervision. MB: Conceptualization, Formal analysis, Methodology, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing, Project administration. CL: Formal analysis, Methodology, Validation, Visualization, Writing – original draft, Writing – review & editing, Data curation, Investigation, Software. CD: Data curation, Formal analysis, Software, Validation, Visualization, Writing – original draft, Writing – review & editing, Conceptualization, Project administration, Supervision. KQ: Conceptualization, Data curation, Formal analysis, Project administration, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing, Funding acquisition, Investigation, Methodology, Resources.

Funding

The author(s) declared that financial support was not received for this work and/or its publication.

Conflict of interest

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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The author(s) declared that Generative AI was not used in the creation of this manuscript.

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References

Álvarez-Bustos, A., Rodríguez-Sánchez, B., Carnicero-Carreño, J. A., Sepúlveda-Loyola, W., Garcia-Garcia, F. J., and Rodríguez-Mañas, L. (2022). Healthcare cost expenditures associated to frailty and sarcopenia. BMC Geriatr. 22:747. doi: 10.1186/s12877-022-03439-z,

PubMed Abstract | Crossref Full Text | Google Scholar

Arosio, B., Calvani, R., Ferri, E., Coelho-Junior, H. J., Carandina, A., Campanelli, F., et al. (2023). Sarcopenia and cognitive decline in older adults: targeting the muscle–brain axis. Nutrients 15:1853. doi: 10.3390/nu15081853,

PubMed Abstract | Crossref Full Text | Google Scholar

Corrao, S., Cerasola, D., Lucini, D., and Argano, C. (2025). Ageing, clinical complexity, and exercise therapy: a multidimensional approach. Front. Sports Act. Living 6:1422222. doi: 10.3389/fspor.2024.1422222,

PubMed Abstract | Crossref Full Text | Google Scholar

Cruz-Jentoft, A. J., Bahat, G., Bauer, J., Boirie, Y., Bruyère, O., Cederholm, T., et al. (2019). Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing 48, 16–31. doi: 10.1093/ageing/afy169

Crossref Full Text | Google Scholar

Diz, J. B. M., Leopoldino, A. A. O., Moreira, B. d. S., Henschke, N., Dias, R. C., Pereira, L. S. M., et al. (2016). Prevalence of sarcopenia in older Brazilians: a systematic review and meta-analysis. Geriatr Gerontol Int 17, 5–16. doi: 10.1111/ggi.12720,

PubMed Abstract | Crossref Full Text | Google Scholar

Dong, X., Yu, Y., Li, J., Chai, X., Shan, W., Yan, H., et al. (2024). A study of the correlation between sarcopenia and cognitive impairment in older individuals over 60 years: cross-sectional and longitudinal validation. Front. Aging Neurosci. 16:1489185. doi: 10.3389/fnagi.2024.1489185,

PubMed Abstract | Crossref Full Text | Google Scholar

Fernandes, L. V., Paiva, A. E. G., Silva, A. C. B., de Castro, I. C., Santiago, A. F., de Oliveira, E. P., et al. (2022). Prevalence of sarcopenia according to EWGSOP1 and EWGSOP2 in older adults and their associations with unfavorable health outcomes: a systematic review. Aging Clin. Exp. Res. 34, 505–514. doi: 10.1007/s40520-021-01951-7,

PubMed Abstract | Crossref Full Text | Google Scholar

Gabriela, C. C., de Daniela, A., Arbex, S., Aprahamian, I., Falcão, S., Meire Cachioni,, et al. (2023). Cognitive impairment predicts sarcopenia 9 years later among older adults. J. Am. Med. Dir. Assoc. 24, 1207–1212. doi: 10.1016/j.jamda.2023.05.008

Crossref Full Text | Google Scholar

Hsu, P. S., Lee, W. J., Peng, L. N., Lu, W. H., Meng, L. C., Hsiao, F. Y., et al. (2024). Safeguarding vitality and cognition: The role of sarcopenia in intrinsic capacity decline among octogenarians from multiple cohorts. J. Nutr. Health Aging, 28:100268. doi: 10.1016/j.jnha.2024.100268

Crossref Full Text | Google Scholar

Huang, J., Li, M., Luo, Q., and Li, J. (2025). The association of sarcopenia, possible sarcopenia and cognitive impairment: a systematic review and meta-analysis. PLoS One 20, e0324258–e0324258. doi: 10.1371/journal.pone.0324258,

PubMed Abstract | Crossref Full Text | Google Scholar

Janssen, I., Heymsfield, S. B., Baumgartner, R. N., and Ross, R. (2000). Estimation of skeletal muscle mass by bioelectrical impedance analysis. J. Appl. Physiol. 89, 465–471. doi: 10.1152/jappl.2000.89.2.465,

PubMed Abstract | Crossref Full Text | Google Scholar

Kannan, N., and Arunachalam, D. (2025). “Global Population Aging 1950–2050.” in Handbook of aging, health and public policy: Perspectives from Asia (Singapore: Springer Nature Singapore), 99–390 116. doi: 10.1007/978-981-16-1914-4_154-1

Crossref Full Text | Google Scholar

Kim, S., Wang, S., Kang, D. W., Um, Y. H., Yoon, H. M., Lee, S., et al. (2024). Development of a prediction model for cognitive impairment of sarcopenia using multimodal neuroimaging in non-demented older adults. Alzheimers Dement. 20, 4868–4878. doi: 10.1002/alz.14054,

PubMed Abstract | Crossref Full Text | Google Scholar

Kirk, B., Cawthon, P. M., Arai, H., Ávila-Funes, J. A., Barazzoni, R., Bhasin, S., et al. (2024). The conceptual definition of sarcopenia: Delphi consensus from the global leadership initiative in sarcopenia (GLIS). Age Ageing 53, 1–10. doi: 10.1093/ageing/afae052,

PubMed Abstract | Crossref Full Text | Google Scholar

Kirk, B., Cawthon, P. M., and Cruz-Jentoft, A. J. (2024). Global consensus for sarcopenia. Aging [Internet] 16, 9306–9308. doi: 10.18632/aging.205919,

PubMed Abstract | Crossref Full Text | Google Scholar

Li, F., Bian, D., Bai, T., Jin, H., Sun, X., Lu, J., et al. (2022). Cognitive impairment is associated with sarcopenia mainly related to attention and calculation in hospitalized Chinese elderly men. Asia. Pac. J. Clin. Nutr. 31, 534–542. doi: 10.6133/apjcn.202209_31(3).0021

Crossref Full Text | Google Scholar

Lim, G., Lee, H., and Lim, Y. (2022). Potential effects of resistant exercise on cognitive and muscle functions mediated by myokines in sarcopenic obese mice. Biomedicine 10:2529. doi: 10.3390/biomedicines10102529,

PubMed Abstract | Crossref Full Text | Google Scholar

Lu, C., Liu, W., Cang, X., Sun, X., Wang, X., Wang, C., et al. (2024). The bidirectional associations between sarcopenia-related traits and cognitive performance. Sci. Rep. 14:7591. doi: 10.1038/s41598-024-58416-w,

PubMed Abstract | Crossref Full Text | Google Scholar

Maniscalco, L, Veronese, N, Francesco Saverio Ragusa,, Vernuccio, L, Domínguez, LJ, Smıth, L, et al. Sarcopenia using muscle mass prediction model and cognitive impairment: a longitudinal analysis from the English longitudinal study on ageing. Arch. Gerontol. Geriatr.. 2024. 117:105160–105160. doi: 10.1016/j.archger.2023.105160, 37672877.

Crossref Full Text | Google Scholar

Ohta, T., Hiroyuki Sasai,, Yosuke Osuka,, Kojima, N., Abe, T., Yamashita, M., et al. (2023). Age- and sex-specific associations between sarcopenia severity and poor cognitive function among community-dwelling older adults in Japan: the IRIDE cohort study. Front. Public Health 11:1148404. doi: 10.3389/fpubh.2023.1148404

Crossref Full Text | Google Scholar

Peng, T. C., Chen, W. L., Wu, L. W., Chang, Y. W., and Kao, T. W. (2019). Sarcopenia and cognitive impairment: a systematic review and meta-analysis. Clin. Nutr. 39, 2695–2701. doi: 10.1016/j.clnu.2019.12.014,

PubMed Abstract | Crossref Full Text | Google Scholar

Petermann-Rocha, F., Balntzi, V., Gray, S. R., Lara, J., Ho, F. K., Pell, J. P., et al. (2021). Global prevalence of sarcopenia and severe sarcopenia: a systematic review and meta-analysis. J. Cachexia. Sarcopenia Muscle 13, 86–99. doi: 10.1002/jcsm.12783,

PubMed Abstract | Crossref Full Text | Google Scholar

Rao, A. R., Bhagwasia, M., Singh, V., Bajpai, S., Singhal, S., Chatterjee, P., et al. (2025). Prevalence and determinants of sarcopenia among older adults in India: insights from the longitudinal aging study in India. J. Am. Geriatr. Soc. 73, 1429–1440. doi: 10.1111/jgs.19373,

PubMed Abstract | Crossref Full Text | Google Scholar

Scisciola, L., Fontanella, R. A., Surina,, Cataldo, V., Paolisso, G., and Barbieri, M. (2021). Sarcopenia and cognitive function: role of myokines in muscle brain cross-talk. Life. 11:173. doi: 10.3390/life11020173

Crossref Full Text | Google Scholar

Shlisky, J., Bloom, D. E., Beaudreault, A. R., Tucker, K. L., Keller, H. H., Freund-Levi, Y., et al. (2017). Nutritional considerations for healthy aging and reduction in age-related chronic disease. Adv. Nutr. 8, 17.2–17.26. doi: 10.3945/an.116.013474

Crossref Full Text | Google Scholar

Sui, S. X., Williams, L. J., Holloway-Kew, K. L., Hyde, N. K., and Pasco, J. A. (2020). Skeletal muscle health and cognitive function: a narrative review. Int. J. Mol. Sci. 22:255. doi: 10.3390/ijms22010255,

PubMed Abstract | Crossref Full Text | Google Scholar

Tan, L. F., Lim, Z. Y., Choe, R., Seetharaman, S., and Merchant, R. (2017). Screening for frailty and sarcopenia among older persons in medical outpatient clinics and its associations with healthcare burden. J. Am. Med. Dir. Assoc. 18, 583–587. doi: 10.1016/j.jamda.2017.01.004,

PubMed Abstract | Crossref Full Text | Google Scholar

Tolea, M., and Galvin, J. (2015). Sarcopenia and impairment in cognitive and physical performance. Clin. Interv. Aging 10, 663–671. doi: 10.2147/CIA.S76275,

PubMed Abstract | Crossref Full Text | Google Scholar

Veronese, N., Demurtas, J., Soysal, P., Smith, L., Torbahn, G., Schoene, D., et al. (2019). Sarcopenia and health-related outcomes: an umbrella review of observational studies. Eur. Geriatr. Med. 10, 853–862. doi: 10.1007/s41999-019-00233-w,

PubMed Abstract | Crossref Full Text | Google Scholar

Wang, D., Zeng, H., Wu, P., Zhou, Y., Chen, H., Zhao, F., et al. (2024). Path analysis of the awareness status and influencing factors of sarcopenia in older adults in the community: based on structural equation modeling. Front. Public Health 12:1391383. doi: 10.3389/fpubh.2024.1391383,

PubMed Abstract | Crossref Full Text | Google Scholar

Wu, Y., Wang, Z., and Fang, Y. (2024). Association of performance on multiple cognitive domains with sarcopenia among middle-aged and older adults. Dement. Geriatr. Cogn. Disord. 53, 162–167. doi: 10.1159/000538751,

PubMed Abstract | Crossref Full Text | Google Scholar

Yang, Y., Xiao, M., Leng, L., Jiang, S., Feng, L., Pan, G., et al. (2022). A systematic review and meta-analysis of the prevalence and correlation of mild cognitive impairment in sarcopenia. J. Cachexia. Sarcopenia Muscle 14, 45–56. doi: 10.1002/jcsm.13143,

PubMed Abstract | Crossref Full Text | Google Scholar

Yigit, B., Oner, C., Cetin, H., and Simsek, E. E. (2022). Association between sarcopenia and cognitive functions in older individuals: a cross-sectional study. Ann. Geriatr. Med. Res. 26, 134–139. doi: 10.4235/agmr.22.0027,

PubMed Abstract | Crossref Full Text | Google Scholar

Zhang, J., Jia, X., Li, Y., Li, H., and Yang, Q. (2023). The longitudinal bidirectional association between sarcopenia and cognitive function in community-dwelling older adults: findings from the China health and retirement longitudinal study. J. Glob. Health 13:4182. doi: 10.7189/jogh.13.04182,

PubMed Abstract | Crossref Full Text | Google Scholar

Zhang, Y., Wang, R., Chen, Z., Zhou, F., and Su, S. (2024). Educational attainment, brain cortical structure, and sarcopenia: a mendelian randomization study. Front. Public Health 12:1415343. doi: 10.3389/fpubh.2024.1415343,

PubMed Abstract | Crossref Full Text | Google Scholar