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Pongmala C, Stonsaovapak C, Luker A, Griggs A, van Emde Boas M, Haus JM, Bohnen NI. Association of Specific Leg Muscle Strength and Motor Features in Parkinson's Disease. PARKINSON'S DISEASE 2024; 2024:5580870. [PMID: 38939534 PMCID: PMC11211005 DOI: 10.1155/2024/5580870] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/04/2024] [Revised: 05/05/2024] [Accepted: 06/06/2024] [Indexed: 06/29/2024]
Abstract
Background Postural instability and gait difficulties (PIGD) are a significant cause of falls, mobility loss, and lower quality of life in Parkinson's disease (PD). The connection between PD progression and diminished strength in the lower limbs has been acknowledged. However, the identification of specific muscle groups linked to PIGD and non-PIGD motor features is still unknown. Objective To explore the relationship between the strength of specific lower limb muscle groups, along with muscle mass, and their associations with PIGD, PIGD subtypes, and non-PIGD motor features in PD. Methods 95 PD participants underwent detailed motor and non-motor test batteries, including lower limb isometric strength testing and whole-body lean mass assessments. Correlation analysis and univariate and multivariate linear/logistic forward stepwise regression were performed to test associations between PIGD and non-PIGD motor features with normalized value (z-score) of lower limb muscle strength and measures of lean mass. Results Multivariate regression analysis, adjusted for age, gender, and levodopa equivalent dose, revealed that hip abductor strength was significantly associated with overall PIGD motor severity ratings (p < 0.001), impaired balance (p < 0.001), and non-PIGD Parkinsonian motor features (p < 0.001). Conversely, hip extensor strength was significantly associated with falls, slow walking, and FoG motor features (p=0.016; p=0.003; p=0.020, respectively). Conclusion We found that lower hip abductor strength was associated with PIGD and non-PIGD motor features. The association between non-PIGD motor features may suggest specific vulnerability of the hip abductors as part of a proposed brain-muscle loop hypothesis in PD. Moreover, lower hip extensor strength correlated with falls, slow walking, and FoG.
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Affiliation(s)
- Chatkaew Pongmala
- Functional Neuroimaging, Cognitive and Mobility Laboratory, University of Michigan, Ann Arbor, MI, USA
- Department of Radiology, University of Michigan, Ann Arbor, MI, USA
- Morris K. Udall Center of Excellence in Parkinson's Disease Research, University of Michigan, Ann Arbor, MI 48105, USA
| | - Chernkhuan Stonsaovapak
- Department of Rehabilitation Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | - Austin Luker
- Functional Neuroimaging, Cognitive and Mobility Laboratory, University of Michigan, Ann Arbor, MI, USA
- Department of Radiology, University of Michigan, Ann Arbor, MI, USA
| | - Alexis Griggs
- Functional Neuroimaging, Cognitive and Mobility Laboratory, University of Michigan, Ann Arbor, MI, USA
- Department of Radiology, University of Michigan, Ann Arbor, MI, USA
| | - Miriam van Emde Boas
- Functional Neuroimaging, Cognitive and Mobility Laboratory, University of Michigan, Ann Arbor, MI, USA
- Department of Radiology, University of Michigan, Ann Arbor, MI, USA
- Morris K. Udall Center of Excellence in Parkinson's Disease Research, University of Michigan, Ann Arbor, MI 48105, USA
| | - Jacob M. Haus
- School of Kinesiology, University of Michigan, Ann Arbor, MI, USA
| | - Nicolaas I. Bohnen
- Functional Neuroimaging, Cognitive and Mobility Laboratory, University of Michigan, Ann Arbor, MI, USA
- Department of Radiology, University of Michigan, Ann Arbor, MI, USA
- Morris K. Udall Center of Excellence in Parkinson's Disease Research, University of Michigan, Ann Arbor, MI 48105, USA
- Department of Neurology, University of Michigan, Ann Arbor, MI, USA
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The Identification of Elderly People with High Fall Risk Using Machine Learning Algorithms. Healthcare (Basel) 2022; 11:healthcare11010047. [PMID: 36611508 PMCID: PMC9818612 DOI: 10.3390/healthcare11010047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Revised: 12/09/2022] [Accepted: 12/20/2022] [Indexed: 12/28/2022] Open
Abstract
Falling is an important public health issue, and predicting the fall risk can reduce the incidence of injury events in the elderly. However, most of the existing studies may have additional human and financial costs for community workers and doctors. Therefore, it is socially important to identify elderly people who are at high fall risk through a reasonable and cost-effective method. We evaluated the potential of multifractal, machine learning algorithms to identify the elderly at high fall risk. We developed a 42-point calibration model of the human body and recorded the three-dimensional coordinate datasets. The stability of the motion trajectory is calculated by the multifractal algorithm and used as an input dimension to compare the performance of the six classifiers. The results showed that the instability of the faller group was significantly greater than that of the no-faller group in the male and female cohorts (p < 0.005), and the Gradient Boosting Decision Tree classifier showed the best performance. The findings could help elderly people at high fall risk to identify individualized risk factors and facilitate tailored fall interventions.
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Fyfe JJ, Hamilton DL, Daly RM. Minimal-Dose Resistance Training for Improving Muscle Mass, Strength, and Function: A Narrative Review of Current Evidence and Practical Considerations. Sports Med 2021; 52:463-479. [PMID: 34822137 DOI: 10.1007/s40279-021-01605-8] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/15/2021] [Indexed: 12/20/2022]
Abstract
Resistance training (RT) is the only non-pharmacological intervention known to consistently improve, and therefore offset age-related declines in, skeletal muscle mass, strength, and power. RT is also associated with various health benefits that are underappreciated compared with the perceived benefits of aerobic-based exercise. For example, RT participation is associated with reduced all-cause and cancer-related mortality and reduced incidence of cardiovascular disease, hypertension, and symptoms of both anxiety and depression. Despite these benefits, participation in RT remains low, likely due to numerous factors including time constraints, a high-perceived difficulty, and limited access to facilities and equipment. Identification of RT strategies that limit barriers to participation may increase engagement in RT and subsequently improve population health outcomes. Across the lifespan, declines in strength and power occur up to eight times faster than the loss of muscle mass, and are more strongly associated with functional impairments and risks of morbidity and mortality. Strategies to maximise healthspan should therefore arguably focus more on improving or maintaining muscle strength and power than on increasing muscle mass per se. Accumulating evidence suggests that minimal doses of RT, characterised by lower session volumes than in traditional RT guidelines, together with either (1) higher training intensities/loads performed at lower frequencies (i.e. low-volume, high-load RT) or (2) lower training intensities/loads performed at higher frequencies and with minimal-to-no equipment (i.e. resistance 'exercise snacking'), can improve strength and functional ability in younger and older adults. Such minimal-dose approaches to RT have the potential to minimise various barriers to participation, and may have positive implications for the feasibility and scalability of RT. In addition, brief but frequent minimal-dose RT approaches (i.e. resistance 'exercise snacking') may provide additional benefits for interrupting sedentary behaviour patterns associated with increased cardiometabolic risk. Compared to traditional approaches, minimal-dose RT may also limit negative affective responses, such as increased discomfort and lowered enjoyment, both of which are associated with higher training volumes and may negatively influence exercise adherence. A number of practical factors, including the selection of exercises that target major muscle groups and challenge both balance and the stabilising musculature, may influence the effectiveness of minimal-dose RT on outcomes such as improved independence and quality-of-life in older adults. This narrative review aims to summarise the evidence for minimal-dose RT as a strategy for preserving muscle strength and functional ability across the lifespan, and to discuss practical models and considerations for the application of minimal-dose RT approaches.
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Affiliation(s)
- Jackson J Fyfe
- Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia.
| | - D Lee Hamilton
- Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia
| | - Robin M Daly
- Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia
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Cho K, Suzuki M, Iso N, Okabe T, Goto H, Hirata K, Shimizu J. Impact of different bilateral knee extension strengths on lower extremity performance. Medicine (Baltimore) 2021; 100:e27297. [PMID: 34559141 PMCID: PMC8462631 DOI: 10.1097/md.0000000000027297] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/03/2021] [Accepted: 09/03/2021] [Indexed: 01/05/2023] Open
Abstract
Despite the impact of leg muscle strength on lower extremity motor performance-including walking and sit-to-stand transfer-it remains difficult to predict the relationship between bilateral leg muscle strength and lower extremity performance. Therefore, this study was designed to predict lower extremity function through the differential modeling of logarithmic and linear regression, based on knee extension strength.The study included 121 individuals living in the same community. The bilateral strengths of the knee extensors were measured using a handheld dynamometer, and the Timed Up & Go test (TUG) performance time and 5-m minimum walking times were assessed to predict lower extremity motor functions. Bilateral normalized knee extension muscle strengths and lower extremity motor function scores, including walking or TUG performance times, were assessed on the logarithmic and linear models. The Akaike information criterion (AIC) was used to evaluate the coefficient compatibility between the logarithmic regression model and the linear regression model.The AIC value for the linear model was lower than that for the logarithmic model regarding the walking time. For walking time estimation in the linear model, the coefficient value of knee extension strength was larger on the strong than on the weak side; however, the AIC value for the logarithmic model was lower than that for the linear model regarding TUG performance time. In the logarithmic model's TUG performance time estimation, the coefficient value of knee extension strength was larger on the weak than on the strong side.In conclusion, our study demonstrated different models reflecting the relationship between both legs' strengths and lower extremity performance, including the walking and TUG performance times.
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Reliability and validity of an adapted hip abductor strength measure as a potential new fall risk assessment for older persons: a study protocol. BMC Geriatr 2021; 21:110. [PMID: 33546611 PMCID: PMC7866761 DOI: 10.1186/s12877-021-02048-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2020] [Accepted: 01/21/2021] [Indexed: 11/16/2022] Open
Abstract
Background Persons aged ≥ 65 years are currently the world’s fastest growing age group. An important complication of age is the increasing risk of falls. Falls have multifactorial etiology and modifiable risk factors open for interventions in prevention and rehabilitation, are of high interest. In this context, strong hip abductors seem to be important to prevent falls. A newly adapted measurement device to measure hip abductor strength (HAS) in a closed chain position was developed. We aim to assess feasibility, intra- and inter-tester reliability and construct and criterion validity of the new measure. Methods In two subsequent parts a feasibility, reliability and validity study with an adapted measurement instrument for the assessment of HAS (index test) in a closed chain position in persons aged ≥ 65 years will be conducted. Part I investigates feasibility of the measure in clinical settings as well as reliability of the new HAS test (n = 26). Part II evaluates construct and criterion validity (n = 169). Construct validity will be assessed cross-sectional, criterion validity by comparison with prospectively followed up fall history for 12 months (external criterion) and other functional fall risk assessments (Short Physical Performance Battery, Timed Up and Go test, usual gait speed and hand grip strength). Discussion Results of feasibility, will give insight in its applicability in daily clinical life and clinimetric properties will show if measurements of HAS in a closed chain position should be encouraged to include in fall risk assessments in older adults.
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Van Eetvelde BLM, Lapauw B, Proot P, Vanden Wyngaert K, Celie B, Cambier D, Calders P. The impact of sensory and/or sensorimotor neuropathy on lower limb muscle endurance, explosive and maximal muscle strength in patients with type 2 diabetes mellitus. J Diabetes Complications 2020; 34:107562. [PMID: 32122790 DOI: 10.1016/j.jdiacomp.2020.107562] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/15/2019] [Revised: 01/26/2020] [Accepted: 02/20/2020] [Indexed: 12/29/2022]
Abstract
AIMS The purpose of this study was to investigate the impact of diabetic neuropathy (dNP) on lower limb endurance, explosive and maximal muscle strength in patients with Type 2 Diabetes Mellitus (T2DM). METHODS Fifty-four participants, aged between 55 and 85, were enrolled in this observational comparative study. The patients with T2DM had an average HbA1c of 7.4% (±1.03) and diabetes duration of 13 years. Participants were classified by means of electroneuromyography as T2DM without dNP (dNP-; n = 8), T2DM with sensory dNP (dNPs; n = 13), T2DM with sensorimotor dNP (dNPsm; n = 14), and healthy controls without neuropathy (C; n = 19). Maximal muscle strength and muscle endurance of the dominant knee and ankle were measured by dynamometry, while explosive muscle strength was evaluated by mechanography. RESULTS Muscle endurance "total work" in knee extension and ankle plantar flexion was higher in the healthy controls compared to dNP-, dNPs and dNPsm, in knee flexion compared to dNPs and dNPsm, and in ankle dorsiflexion compared to dNPsm only (p<0.05). Furthermore, relative explosive muscle strength "total power/body weight" and relative maximal muscle strength "peak torque/lean body mass of the dominant leg" considering knee flexion, ankle plantar flexion and dorsiflexion, were higher in healthy controls compared to the dNPsm group, and for maximal muscle strength ankle dorsiflexion even between dNP- and dNPsm (p < 0.05). CONCLUSIONS Muscle endurance is impaired in patients with T2DM, independent of the presence of dNP. Explosive and maximal muscle strength are more likely affected by the presence and severity of dNP.
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Affiliation(s)
- Birgit L M Van Eetvelde
- Department of Rehabilitation Sciences, Ghent University, Corneel Heymanslaan 10, 9000 Ghent, Belgium.
| | - Bruno Lapauw
- Department of Endocrinology, Ghent University Hospital, Corneel Heymanslaan 10, 9000 Ghent, Belgium.
| | - Pascal Proot
- Department of Neurology, Ghent University Hospital, Corneel Heymanslaan 10, 9000 Ghent, Belgium.
| | - Karsten Vanden Wyngaert
- Department of Rehabilitation Sciences, Ghent University, Corneel Heymanslaan 10, 9000 Ghent, Belgium.
| | - Bert Celie
- Department of Rehabilitation Sciences, Ghent University, Corneel Heymanslaan 10, 9000 Ghent, Belgium.
| | - Dirk Cambier
- Department of Rehabilitation Sciences, Ghent University, Corneel Heymanslaan 10, 9000 Ghent, Belgium.
| | - Patrick Calders
- Department of Rehabilitation Sciences, Ghent University, Corneel Heymanslaan 10, 9000 Ghent, Belgium.
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