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2 June 2026

9 Pages

The Relationship Between Handgrip Strength and Cognitive Ability in the Elderly with Early-Stage Dementia

,
and
1
Department of Medicine, National and Kapodistrian University of Athens, Mikras Asias 75, 11527 Athens, Greece
2
Department of Physiotherapy, School of Health Sciences, University of West Attica, Agiou Spiridonos 28, 12243 Athens, Greece
3
Laboratory of Biomechanics, Department of Physiotherapy, School of Health Sciences, University of Peloponnese, Plateon 20, 23100 Sparta, Greece
*
Author to whom correspondence should be addressed.
Clin. Transl. Neurosci.2026, 10(2), 13;https://doi.org/10.3390/ctn10020013
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Abstract

(1) Background: Alzheimer’s disease is a common neurodegenerative disease which mainly affects the elderly. The aim of the study is to investigate the relationship between handgrip strength and cognitive ability in a geriatric population with early-stage dementia. There are only a few studies that associate handgrip strength with cognitive ability in a population with early-stage dementia. (2) Methods: The present study consists of a sample of 60 individuals with early-stage dementia and was conducted at the Alzheimer’s Association of Athens. Participants’ ages ranged from 65 to 93 years (M = 80 years, SD = 6.05). Specific inclusion and exclusion criteria of the sample were defined. Handgrip strength was assessed using a digital handheld dynamometer, while cognitive ability was measured using the Mini-Mental State Examination Test (MMSE). (3) Results: Descriptive statistics showed that the mean handgrip strength of the dominant upper limb was 144.45 ± 50.47 Newtons, and the mean cognitive score was M = 21.75 (SD = 1.97) (0–30 points). In a multivariable regression analysis adjusted for age, sex, and education, handgrip strength was not significantly associated with MMSE score (B = 0.056, 95% CI: −0.054 to 0.166, p = 0.314). (4) Discussion: There are few studies that correlate cognitive ability with handgrip strength in a population with early-stage dementia; thus, further studies are needed to investigate the present results, possibly with a larger sample size or using different cognitive function measurement tools. (5) Conclusions: Handgrip strength may appear not to be associated with cognitive ability when elderly patients are in early-stage dementia. More research should be conducted to confirm the present findings.

1. Introduction

With the continuous improvement of the average life expectancy of the global population and the increasingly severe aging problem, the rapid growth of the elderly population has brought unprecedented challenges to the current society and economy, especially the public health system. The diseases of the geriatric population include cardiological, respiratory, metabolic, rheumatological, orthopedic, oncological and neurodegenerative diseases. In several of these pathological conditions, individuals have sarcopenia, as is the case with elderly people with dementia. Dementia is most commonly attributed to Alzheimer’s disease (AD), which causes impairment in areas of mental functioning such as memory, reasoning, concentration, and language and thus leads to poor quality of life, reduces functional ability, and increases mortality [1,2]. People with early-stage dementia are characterized by loss of cognitive abilities (i.e., forgetting appointments, difficulty making decisions, being repetitive, misplacement of items), functional impairment in everyday life activities, and emotional symptoms (anxiety, depression, and lack of motivation). In the moderate stage of dementia, individuals cannot perform daily activities (i.e., cooking and washing). There is stiffness, loss of mobility, muscle atrophy, loss of muscle elasticity, and inability to perform skilled movements [3]. The above mobility problems ultimately lead to a loss of functional ability and self-care of the individual [4]. Also, they show a greater lack of orientation and memory problems. In the advanced stage of the disease, individuals experience both mobility problems and problems with feeding and urination, since they cannot move independently. At this stage, the physical symptoms are even more apparent. Memory problems become more and more severe, and patients find it difficult to recognize their friends and relatives as well as various objects [5,6]. Moreover, the geriatric population with dementia has sarcopenia. Sarcopenia and cognitive impairment, as pathological conditions of the geriatric population, share common risk factors, such as age, cardiac history, sedentary lifestyle and inflammatory processes [7,8], resulting in reduced functional capacity, loss of balance with frequent falls and reduced quality of life. Studies have shown a possible link between sarcopenia and cognitive impairment [9]. The available evidence [10,11,12] on the association between sarcopenia and cognitive impairment is based on cross-sectional data and needs to be verified by large-scale longitudinal studies. It has also been reported that skeletal muscle secretes neurotrophic factors, which affect brain function and motor units. Therefore, sarcopenia may be a potential risk factor for cognitive impairment. Several studies have hypothesized that premature decline in handgrip strength may be associated with further cognitive decline [13]. Studies have shown a positive association of sarcopenia with cognitive decline [9,14,15,16,17,18], while others have not found a significant association [19,20].
Handgrip strength is widely regarded as a simple, reliable, and low-cost indicator of overall muscle strength and general physical condition. Beyond its value in the assessment of physical performance, increasing evidence suggests that it may also reflect neurological and cognitive health in older adults. A study reported that higher baseline handgrip strength was associated with better cognitive performance and a lower risk of subsequent cognitive decline [21]. Similarly, another study highlighted the prognostic value of handgrip strength in older adults, showing that reduced grip strength is linked with adverse health outcomes and may serve as a useful clinical marker of vulnerability. Taken together, these findings support the use of handgrip strength as an accessible measure in studies exploring the relationship between physical function and cognitive impairment [21,22]. Handgrip strength could predict cognitive function over time. Furthermore, cognitive function and muscle strength may share the same brain regions and networks [21,23,24,25,26]. Before the onset of Alzheimer’s disease, there is a silent period that can last 10–15 years [21,22]. The main variables that are correlated with handgrip strength are sex and age. There are only a few studies that have explored the relationship between handgrip strength and cognitive ability in the elderly [27]. The aim of the study is to investigate if there is a relationship between handgrip strength and cognitive ability in a geriatric population with early-stage dementia. Examining its relationship helped us see a possible decline in handgrip strength and therefore a possible worsening of cognitive ability.

2. Materials and Methods

2.1. Study Design

This study has been registered and approved by the Ethics Committee of the School of Health Studies of the University of Peloponnese (203/6 April 2023) and the Scientific Council of the Alzheimer Athens Association (77A/6 April 2023). The study was in agreement with the Declaration of Helsinki Ethics principles.

2.2. Sample

An a priori power analysis was performed using GPower version 3.1.9.7 to determine the required sample size. Based on an assumed alpha level of 0.05, a desired statistical power of 0.80, and a medium effect size, the analysis indicated that a minimum of 52 participants was necessary to detect statistically significant effects.
Sixty older adults (37 women, 23 men) with a mean age of 80 ± 6 years were recruited from the Day Care Centre of the Alzheimer Association. All the participants were able to walk independently. The categories of drugs that the patients were taking included the following: antihypertensives, beta blockers, antiplatelet agents, anticoagulants, memantine, acetylcholinesterase inhibitors, levodopa, levothyroxine and metformin. The inclusion criteria were as follows: (a) a confirmed diagnosis of early-stage Alzheimer’s-type dementia, (b) residence in the community, (c) age between 65 and 95 years, (d) both sexes, (e) adequate verbal and written communication skills and capacity to follow instructions, (f) ability to ambulate, (g) absence of acute medical events in the preceding month (e.g., heart or respiratory failure, stroke), and (h) willingness to participate in the study.
Exclusion criteria included the following: (a) moderate or severe-stage dementia, (b) severe psychiatric disorders such as psychosis, (c) significant medical conditions (e.g., clinically important cardiac or respiratory disease), and (d) inability to walk. Participant selection was based on a neurologist’s diagnosis, informed by clinical evaluation and objective assessments. Diagnoses adhered to DSM-IV and NINCDS/ADRDA criteria [28].
The neurologist administered diagnostic tools once at baseline to determine eligibility for the program [29,30].

2.3. Materials

The outcome measures were as follows:
1.
Handgrip strength
The digital handheld dynamometer is a tool for measuring upper extremity muscle strength. The handgrip dynamometer has very good reliability in people with early-stage dementia (ICC = 0.97). The dimensions of the dynamometer (Charder Company, Taichung City, Taiwan, Model MG4800) are 100 mm × 212 mm × 55 mm; it weighs 400 g and is battery-operated [31].
2.
Cognitive ability
The Mini-Mental State Examination test is the most widely used tool for testing cognitive ability in clinical and research practice for detection of cognitive decline in a population with early-stage dementia [32,33]. The test assesses orientation in space and time, attention, memory, language skills and comprehension. The score ranges from 0 to 30. A score greater than or equal to 25 is normal, while a score lower than 25 indicates the presence of a cognitive disorder. The lower the scores on the scale, the greater the cognitive impairment. The Greek version was used, which was translated and validated [34].

2.4. Procedure

A signed consent form was completed by all participants after being informed about the procedure of the study. They were asked to complete an information sheet with the number of falls during the last year and their lifestyle and exercise habits. Demographic variables, including age, gender, occupation, and level of education, were considered. Their smoking and drinking status, medical problems, and medication were obtained from the information sheet. This study was carried out in a private clinical setting by a team of physiotherapists. We assessed participants on their cognitive ability using the Mini-Mental State Examination and handgrip strength using a handgrip dynamometer. The participants sat on a chair with their arm at their side and elbow bent at 90°. Each person pushed the dynamometer as hard as possible to reach the maximum weight; each participant had three attempts. The evaluator marks the best of the three attempts. The right hand was considered dominant, and the values were not normalized; we chose the best effort [35]. During the assessment the researchers were not blinded.

2.5. Statistical Analysis

Initially, the variables were examined for normality using the Kolmogorov–Smirnov index. The statistical analyses included descriptive statistical methods (e.g., frequency distributions, mean values, standard deviations) of the research variables. The statistics analysis included a multivariable regression analysis. The statistical package used was SPSS 26.00 for Windows with a statistical significance level of α = 0.05.

3. Results

Descriptive Statistics of the Sample

A total of 60 participants (male and female) participated in the study. A total of 23 were men (38.3%) and 37 were women (61.7%), with an age that ranged from 65 to 93 years (mean age of 80.0 ± 6.059 years). No patient dropped out during the study. Additional descriptive statistics regarding cognition mean handgrip strength and medical history are presented in Table 1 and Table 2.
Table 1. Descriptive statistics of demographical and clinical-cognitive characteristics.
Table 2. Medical history of the sample.
To examine the association between handgrip strength and cognitive performance, a multivariable regression analysis was fitted, with MMSE score (points, 0–30) as the dependent variable. The overall multivariable model with MMSE as the dependent variable was not statistically significant; F(6, 53) = 0.737, p = 0.622, R2 = 0.077, adjusted R2 = −0.027. Dominant handgrip strength was not significantly associated with MMSE score after adjustment for age, sex, and education (B = 0.056, SE = 0.055, t = 1.017, p = 0.314, 95% CI: −0.054 to 0.166). The direction of the association was positive. The p values of the variables (p = 0.327, p = 0.986, p = 0.816, p = 0.979, p = 0.330, p = 0.314) are much higher than the α = 0.05; therefore, we cannot reject the null hypothesis. Age (B = 0.043, p = 0.330), sex (p = 0.327), and education level (overall p = 0.996) were also not significantly associated with MMSE (Table 3).
Table 3. Multivariable regression for cognitive ability and handgrip strength.

4. Discussion

The results showed that no statistically reliable independent association was detected in this particular small sample, using the MMSE as the sole cognitive measure. Thus, these results may not be interpreted as evidence of absence of a relationship. Also, the analysis indicated that the included predictors explain little variance in MMSE performance. This further supports the interpretation of this study as an underpowered exploratory dataset rather than a confirmatory analysis.
Although our study only included individuals with early-stage dementia, our results are consistent with a recent meta-analysis that examined the relationship between handgrip strength and cognitive ability and also showed a nonlinear relationship between handgrip strength and the risk of cognitive decline, with significant effects at the threshold [36]. This means that beyond a certain point, further increases in handgrip strength may have a diminished protective effect on cognitive health [36,37,38]. Non-statistically significant differences can be attributed to the individual characteristics of each individual, which are different, but also to the previous cognitive profile of each individual [39]. Moreover, dementia, as a condition, shows great heterogeneity among geriatric patients [40].
Handgrip strength is a non-invasive measure of physical health used to measure handgrip strength in the geriatric population. It can represent total body muscle strength and may also be an overall indicator of central nervous system integrity [41]. Weak handgrip strength may indicate sarcopenia or damage to the central nervous system, which accelerates functional limitation. Previous studies have shown an association between handgrip strength and cognitive function in cohort studies with geriatric populations [16,25], suggesting that reduced cognitive function and functional limitation exhibit a mutually reinforcing process. Handgrip strength is an important health indicator associated with various health outcomes [42,43,44]. A study showed that handgrip strength is associated with cognitive ability in a healthy geriatric population [45].
The mechanism of the association between low muscle strength and increased cognitive decline is not understood but may have multiple explanations. Firstly, muscle activity can improve emotional health and stimulate the brain, releasing substances (endorphins) beneficial to cognitive function [46,47]. Weak muscle strength can lead to a reduction in these, affecting cognitive function. Secondly, chronic inflammation and oxidative stress are known triggers of various diseases, such as neurodegenerative diseases. These factors accelerate cognitive decline and impair muscle quality [48,49]. Thirdly, growth factors such as fibroblast growth factor (FGF) regulate muscle and bone quality during aging and have neuroprotective effects [50,51]. Neurotrophic factors such as FGF-23 can promote neuronal proliferation, maintain muscle homeostasis, and improve cognitive function [52].
The current study, which assesses the relationship between handgrip strength and cognitive ability in individuals with early-stage dementia, is one of few studies to examine this relationship in a population with early-stage dementia [27]. Although handgrip strength was not a statistically significant predictor of MMSE score, the point estimate was positive and the confidence interval remained compatible with a small association. Given the modest sample size, this study likely had limited power to detect small independent associations after adjustment for age, sex, and education.
However, some limitations should be acknowledged. The sample consisted only of individuals with early-stage dementia of both sexes. Another major limitation is the use of a single tool for measuring cognitive ability, i.e., MMSE. Also, this tool suffers from a ceiling effect, so there is a possibility that this affects the sensitivity of the specific tool; therefore, it has limited power to detect small effects. The use of more specialized cognitive assessment tools would have provided a relationship between grip strength and cognitive ability in individuals with early dementia. Furthermore, this study lacks anthropometric normalization. Handgrip strength is strongly influenced by sex, body size, muscle mass, and frailty status. We did not examine all aforementioned variables, such as body mass and frailty status, which may affect the results of the study. As a result, limited sample size, skewed distributions, and reduced variability may obscure clinically important associations between cognitive ability and handgrip strength.
Future studies may perform robust balancing and validation strategies to increase the methodology of the study. In future studies, in a population with moderate dementia, it is crucial to assess the relationship between (a) handgrip strength and cognitive ability, (b) lower limb strength and cognitive ability, and (c) genders. Furthermore, it would be beneficial to examine the relationship between handgrip strength and cognitive ability using a bigger sample and more tools for cognitive assessment, such as MoCA and ACE-R, that are valid and widely used and cover a bigger spectrum of cognitive ability [53,54].

5. Conclusions

Our study did not find a correlation between handgrip strength and cognitive ability in people with early-stage dementia possibly due to the lack of evidence. Further research is necessary to explore the results of the present study, using a larger sample size and adopting a different approach of assessing cognitive ability.

Author Contributions

Conceptualization, A.C. and P.P.; methodology, A.C., P.P. and M.L.S.; software, P.P. and M.L.S.; validation, P.P. and M.L.S.; formal analysis, P.P. and M.L.S.; investigation P.P. and M.L.S.; resources, A.C.; data curation, M.L.S.; writing—original draft preparation, A.C., P.P. and M.L.S.; writing—review and editing, A.C., P.P. and M.L.S.; visualization, A.C., P.P. and M.L.S.; supervision, A.C.; project administration, A.C. All authors have read and agreed to the published version of the manuscript.

Funding

This study received no external funding.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of the School of Health Studies of the University of Peloponnese (661/11 January 2023).

Data Availability Statement

Data available on request from the corresponding author.

Acknowledgments

We would like to thank our participants for taking part in the present study.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Scheltens, P.; De Strooper, B.; Kivipelto, M.; Holstege, H.; Chételat, G.; Teunissen, C.E.; Cummings, J.; van der Flier, W.M. Alzheimer’s disease. Lancet 2021, 397, 1577–1590. [Google Scholar] [CrossRef] [Scilit]
  2. Lane, C.A.; Hardy, J.; Schott, J.M. Alzheimer’s disease. Eur. J. Neurol. 2018, 25, 59–70. [Google Scholar] [CrossRef] [Scilit]
  3. Arvanitakis, Z.; Shah, R.C.; Bennett, D.A. Diagnosis and management of dementia: Review. JAMA 2019, 322, 1589–1599. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  4. Pomeroy, V. The effect of physiotherapy input on mobility skills of elderly people with severe dementing illness. Clin. Rehabil. 1993, 7, 163–170. [Google Scholar] [CrossRef] [Scilit]
  5. Papageorgiou, S.G.; Kontaxis, T.; Bonakis, A.; Karahalios, G.; Kalfakis, N.; Vassilopoulos, D. Rapidly progressive dementia: Causes found in a Greek tertiary referral center in Athens. Alzheimer Dis. Assoc. Disord. 2009, 23, 337–346. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  6. Sandilyan, M.B.; Dening, T. Diagnosis of dementia. Nurs. Stand. 2015, 29, 36–41. [Google Scholar] [CrossRef] [Scilit]
  7. Basile, G.; Sardella, A. From cognitive to motor impairment and from sarcopenia to cognitive impairment: A bi-directional pathway towards frailty and disability. Aging Clin. Exp. Res. 2021, 33, 469–478. [Google Scholar] [CrossRef] [Scilit]
  8. Chang, K.V.; Hsu, T.H.; Wu, W.T.; Huang, K.C.; Han, D.S. Association between sarcopenia and cognitive impairment: A systematic review and meta-analysis. J. Am. Med. Dir. Assoc. 2016, 17, 1164.e7–1164.e15. [Google Scholar] [CrossRef] [Scilit]
  9. Peng, T.C.; Chen, W.L.; Wu, L.W.; Chang, Y.W.; Kao, T.W. Sarcopenia and cognitive impairment: A systematic review and meta-analysis. Clin. Nutr. 2020, 39, 2695–2701. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  10. Chen, X.; Han, P.; Yu, X.; Zhang, Y.; Song, P.; Liu, Y.; Jiang, Z.; Tao, Z.; Shen, S.; Wu, Y.; et al. Relationships between sarcopenia, depressive symptoms, and mild cognitive impairment in Chinese community-dwelling older adults. J. Affect. Disord. 2021, 286, 71–77. [Google Scholar] [CrossRef] [Scilit]
  11. Wu, B.; Lyu, Y.B.; Cao, Z.J.; Wei, Y.; Shi, W.Y.; Gao, X.; Zhou, J.; Kraus, V.; Zhao, F.; Chen, X.; et al. Associations of sarcopenia, handgrip strength and calf circumference with cognitive impairment among Chinese older adults. Biomed. Environ. Sci. 2021, 34, 859–870. [Google Scholar] [PubMed]
  12. Bai, A.; Xu, W.; Sun, J.; Liu, J.; Deng, X.; Wu, L.; Zou, X.; Zuo, J.; Zou, L.; Liu, Y.; et al. Associations of sarcopenia and its defining components with cognitive function in community-dwelling oldest old. BMC Geriatr. 2021, 21, 292. [Google Scholar] [CrossRef] [Scilit]
  13. Pasco, J.A.; Williams, L.J.; Jacka, F.N.; Stupka, N.; Brennan-Olsen, S.L.; Holloway, K.L.; Berk, M. Sarcopenia and the common mental disorders: A potential regulatory role of skeletal muscle on brain function? Curr. Osteoporos. Rep. 2015, 13, 351–357. [Google Scholar] [CrossRef] [Scilit]
  14. Kohara, K.; Okada, Y.; Ochi, M.; Ohara, M.; Nagai, T.; Tabara, Y.; Igase, M. Muscle mass decline, arterial stiffness, white matter hyperintensity, and cognitive impairment: Japan Shimanami Health Promoting Program Study. J. Cachexia Sarcopenia Muscle 2017, 8, 557–566. [Google Scholar] [CrossRef] [Scilit]
  15. da Silva Alexandre, T.; de Oliveira Duarte, Y.A.; Ferreira Santos, J.L.; Wong, R.; Lebrão, M.L. Prevalence and associated factors of sarcopenia among elderly in Brazil: Findings from the SABE study. J. Nutr. Health Aging 2014, 18, 284–290. [Google Scholar] [CrossRef] [Scilit]
  16. Papachristou, E.; Ramsay, S.E.; Lennon, L.T.; Papacosta, O.; Iliffe, S.; Whincup, P.H.; Wannamethee, S.G. The relationships between body composition characteristics and cognitive functioning in a population-based sample of older British men. BMC Geriatr. 2015, 15, 172. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  17. Maeda, K.; Akagi, J. Cognitive impairment is independently associated with definitive and possible sarcopenia in hospitalized older adults: The prevalence and impact of comorbidities. Geriatr. Gerontol. Int. 2017, 17, 1048–1056. [Google Scholar] [CrossRef] [Scilit]
  18. Nishiguchi, S.; Yamada, M.; Shirooka, H.; Nozaki, Y.; Fukutani, N.; Tashiro, Y.; Hirata, H.; Yamaguchi, M.; Tasaka, S.; Matsushita, T.; et al. Sarcopenia as a risk factor for cognitive deterioration in community-dwelling older adults: A 1-year prospective study. J. Am. Med. Dir. Assoc. 2016, 17, 372.e5–372.e8. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  19. van Kan, G.A.; Cesari, M.; Gillette-Guyonnet, S.; Dupuy, C.; Vellas, B.; Rolland, Y. Association of a 7-year percent change in fat mass and muscle mass with subsequent cognitive dysfunction: The EPIDOS-Toulouse cohort. J. Cachexia Sarcopenia Muscle 2013, 4, 225–229. [Google Scholar] [CrossRef] [Scilit]
  20. Manrique-Espinoza, B.; Salinas-Rodríguez, A.; Rosas-Carrasco, O.; Gutiérrez-Robledo, L.M.; Avila-Funes, J.A. Sarcopenia is associated with physical and mental components of health-related quality of life in older adults. J. Am. Med. Dir. Assoc. 2017, 18, 636.e1–636.e5. [Google Scholar] [CrossRef] [Scilit]
  21. Liu, Y.; Cao, X.; Gu, N.; Yang, B.; Wang, J.; Li, C. A prospective study on the association between grip strength and cognitive function among middle-aged and elderly Chinese participants. Front. Aging Neurosci. 2019, 11, 250. [Google Scholar] [CrossRef] [Scilit]
  22. Rijk, J.M.; Roos, P.R.; Deckx, L.; van den Akker, M.; Buntinx, F. Prognostic value of handgrip strength in people aged 60 years and older: A systematic review and meta-analysis. Geriatr. Gerontol. Int. 2016, 16, 5–20. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  23. Camargo, E.C.; Weinstein, G.; Beiser, A.S.; Tan, Z.S.; DeCarli, C.; Kelly-Hayes, M.; Kase, C.; Murabito, J.M.; Seshadri, S. Association of physical function with clinical and subclinical brain disease: The Framingham Offspring Study. J. Alzheimer’s Dis. 2016, 53, 1597–1608. [Google Scholar] [CrossRef] [Scilit]
  24. Praetorius Björk, M.; Johansson, B.; Hassing, L.B. I forgot when I lost my grip: Strong associations between cognition and grip strength in level of performance and change across time in relation to impending death. Neurobiol. Aging 2016, 38, 68–72. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  25. Veronese, N.; Stubbs, B.; Trevisan, C.; Bolzetta, F.; De Rui, M.; Solmi, M.; Sartori, L.; Musacchio, E.; Zambon, S.; Perissinotto, E.; et al. What physical performance measures predict incident cognitive decline among intact older adults? A 4.4-year follow-up study. Exp. Gerontol. 2016, 81, 110–118. [Google Scholar] [CrossRef] [Scilit]
  26. Hooghiemstra, A.M.; Ramakers, I.H.G.B.; Sistermans, N.; Pijnenburg, Y.A.L.; Aalten, P.; Hamel, R.E.G.; Melis, R.J.F.; Verhey, F.R.J.; Rikkert, M.G.M.O.; Scheltens, P.; et al. Gait speed and grip strength reflect cognitive impairment and are modestly related to incident cognitive decline in memory clinic patients with subjective cognitive decline and mild cognitive impairment: Findings from the 4C study. J. Gerontol. Ser. A Biol. Sci. Med. Sci. 2017, 72, 846–854. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  27. Kobayashi-Cuya, K.E.; Sakurai, R.; Suzuki, H.; Ogawa, S.; Takebayashi, T.; Fujiwara, Y. Observational evidence of the association between handgrip strength, hand dexterity, and cognitive performance in community-dwelling older adults: A systematic review. J. Epidemiol. 2018, 28, 373–381. [Google Scholar] [CrossRef] [Scilit]
  28. Dubois, B.; Feldman, H.H.; Jacova, C.; DeKosky, S.T.; Barberger-Gateau, P.; Cummings, J.; Delacourte, A.; Galasko, D.; Gauthier, S.; Jicha, G.; et al. Research criteria for the diagnosis of Alzheimer’s disease: Revising the NINCDS-ADRDA criteria. Lancet Neurol. 2007, 6, 734–746. [Google Scholar] [CrossRef] [Scilit]
  29. Mioshi, E.; Dawson, K.; Mitchell, J.; Arnold, R.; Hodges, J.R. The Addenbrooke’s Cognitive Examination Revised (ACE-R): A brief cognitive test battery for dementia screening. Int. J. Geriatr. Psychiatry 2006, 21, 1078–1085. [Google Scholar] [CrossRef] [Scilit]
  30. Dubois, B.; Slachevsky, A.; Litvan, I.; Pillon, B. The FAB: A frontal assessment battery at bedside. Neurology 2000, 55, 1621–1626. [Google Scholar] [CrossRef] [Scilit]
  31. Alencar, M.A.; Dias, J.M.; Figueiredo, L.C.; Dias, R.C. Handgrip strength in elderly with dementia: Study of reliability. Rev. Bras. Fisioter. 2012, 16, 510–514. [Google Scholar] [CrossRef] [Scilit]
  32. Jannati, A.; Toro-Serey, C.; Gomes-Osman, J.; Banks, R.; Ciesla, M.; Showalter, J.; Bates, D.; Tobyne, S.; Pascual-Leone, A. Digital Clock and Recall is superior to the Mini-Mental State Examination for the detection of mild cognitive impairment and mild dementia. Alzheimer’s Res. Ther. 2024, 16, 2. [Google Scholar] [CrossRef] [Scilit]
  33. Arevalo-Rodriguez, I.; Smailagic, N.; Roqué-Figuls, M.; Ciapponi, A.; Sanchez-Perez, E.; Giannakou, A.; Pedraza, O.L.; Bonfill Cosp, X.; Cullum, S. Mini-Mental State Examination (MMSE) for the early detection of dementia in people with mild cognitive impairment (MCI). Cochrane Database Syst. Rev. 2021, 2021, CD010783. [Google Scholar] [CrossRef] [Scilit]
  34. Fountoulakis, K.N.; Tsolaki, M.; Chantzi, H.; Kazis, A. Mini-Mental State Examination (MMSE): A validation study in Greece. Am. J. Alzheimer’s Dis. Other Dement. 2000, 15, 342–345. [Google Scholar] [CrossRef] [Scilit]
  35. Mutalib, S.A.; Mace, M.; Seager, C.; Burdet, E.; Mathiowetz, V.; Goldsmith, N. Modernizing grip dynamometry: Inter-instrument reliability between GripAble and Jamar. BMC Musculoskelet. Disord. 2022, 23, 80. [Google Scholar] [CrossRef] [Scilit]
  36. Nie, W.; Hu, J. The relationship between grip strength and cognitive impairment: Evidence from NHANES 2011–2014. Brain Behav. 2025, 15, e70381. [Google Scholar] [CrossRef] [Scilit]
  37. Ludyga, S.; Pühse, U.; Gerber, M.; Mücke, M. Muscle strength and executive function in children and adolescents with autism spectrum disorder. Autism Res. 2021, 14, 2555–2563. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  38. Lim, G.; Lee, H.; Lim, Y. Potential effects of resistance exercise on cognitive and muscle functions mediated by myokines in sarcopenic obese mice. Biomedicines 2022, 10, 2529. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  39. Kim, J.; McKenna, C.F.; Salvador, A.F.; Scaroni, S.E.; Askow, A.T.; Cerna, J.; Cannavale, C.N.; Paluska, S.A.; De Lisio, M.; Petruzzello, S.J.; et al. Cathepsin B and muscular strength are independently associated with cognitive control. Brain Plast. 2022, 8, 19–33. [Google Scholar] [CrossRef] [Scilit]
  40. Di Fazio, C.; Scaliti, E.; Stanziano, M.; Nigri, A.; Demichelis, G.; Tamietto, M.; Palermo, S. Exploring cortical excitability modulation to promote cognitive resilience in aging: An rTMS study protocol. Front. Hum. Neurosci. 2026, 20, 1743236. [Google Scholar] [CrossRef] [Scilit]
  41. Fritz, N.E.; McCarthy, C.J.; Adamo, D.E. Handgrip strength as a means of monitoring progression of cognitive decline—A scoping review. Aging Res. Rev. 2017, 35, 112–123. [Google Scholar] [CrossRef] [Scilit]
  42. Kim, G.R.; Sun, J.; Han, M.; Nam, C.M.; Park, S. Evaluation of the directional relationship between handgrip strength and cognitive function: The Korean Longitudinal Study of Ageing. Age Ageing 2019, 48, 426–432. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  43. Filardi, M.; Barone, R.; Bramato, G.; Nigro, S.; Tafuri, B.; Frisullo, M.E.; Zecca, C.; Tortelli, R.; Logroscino, G. The relationship between muscle strength and cognitive performance across the Alzheimer’s disease clinical continuum. Front. Neurol. 2022, 13, 833087. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  44. Van Hulle, C.; Jonaitis, E.M.; Betthauser, T.J.; Batrla, R.; Wild, N.; Kollmorgen, G.; Andreasson, U.; Okonkwo, O.; Bendlin, B.B.; Asthana, S.; et al. An examination of a novel multipanel of CSF biomarkers in the Alzheimer’s disease clinical and pathological continuum. Alzheimer’s Dement. 2021, 17, 431–445. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  45. Zammit, A.R.; Piccinin, A.M.; Duggan, E.C.; Koval, A.; Clouston, S.; Robitaille, A.; Brown, C.L.; Handschuh, P.; Wu, C.; Jarry, V.; et al. A coordinated multi-study analysis of the longitudinal association between handgrip strength and cognitive function in older adults. J. Gerontol. Ser. B Psychol. Sci. Soc. Sci. 2021, 76, 229–241. [Google Scholar] [CrossRef] [Scilit]
  46. Battaglia, S.; Avenanti, A.; Vécsei, L.; Tanaka, M. Neurodegeneration in cognitive impairment and mood disorders for experimental, clinical and translational neuropsychiatry. Biomedicines 2024, 12, 574. [Google Scholar] [CrossRef] [Scilit]
  47. Tanaka, M.; Battaglia, S.; Giménez-Llort, L.; Chen, C.; Hepsomali, P.; Avenanti, A.; Vécsei, L. Innovation at the intersection: Emerging translational research in neurology and psychiatry. Cells 2024, 13, 790. [Google Scholar] [CrossRef] [Scilit]
  48. Ebner, N.C.; Kamin, H.; Diaz, V.; Cohen, R.A.; MacDonald, K. Hormones as “difference makers” in cognitive and socioemotional aging processes. Front. Psychol. 2015, 5, 1595. [Google Scholar] [CrossRef] [Scilit]
  49. Fotiadis, P.; Parkes, L.; Davis, K.A.; Satterthwaite, T.D.; Shinohara, R.T.; Bassett, D.S. Structure-function coupling in macroscale human brain networks. Nat. Rev. Neurosci. 2024, 25, 688–704. [Google Scholar] [CrossRef] [Scilit]
  50. Jiang, C.; Li, G.; Huang, P.; Liu, Z.; Zhao, B. The gut microbiota and Alzheimer’s disease. J. Alzheimer’s Dis. 2017, 58, 1–15. [Google Scholar] [CrossRef] [Scilit]
  51. Cho, S.; Lee, H.; Lee, H.Y.; Kim, S.J.; Song, W. The effect of fibroblast growth factor receptor inhibition on resistance exercise training-induced adaptation of bone and muscle quality in mice. Korean J. Physiol. Pharmacol. 2022, 26, 207–218. [Google Scholar] [CrossRef] [Scilit]
  52. Hensel, N.; Schön, A.; Konen, T.; Lübben, V.; Förthmann, B.; Baron, O.; Grothe, C.; Leifheit-Nestler, M.; Claus, P.; Haffner, D. Fibroblast growth factor 23 signaling in hippocampal cells: Impact on neuronal morphology and synaptic density. J. Neurochem. 2016, 137, 756–769. [Google Scholar] [CrossRef] [Scilit]
  53. Lord, A.R.; Amitrano, N.R.; González, D.A. Reliability and validity of the Montreal Cognitive Assessment’s auditory items (MoCA-22). Clin. Neuropsychol. 2024, 38, 783–798. [Google Scholar] [CrossRef] [Scilit]
  54. Hsieh, S.; Schubert, S.; Hoon, C.; Mioshi, E.; Hodges, J.R. Validation of the Addenbrooke’s Cognitive Examination III in frontotemporal dementia and Alzheimer’s disease. Dement. Geriatr. Cogn. Disord. 2013, 36, 242–250. [Google Scholar] [CrossRef] [Scilit]
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