Gait Characteristics of Dynapenia, Sarcopenia, and Presarcopenia in Community-Dwelling Japanese Older Women: A Cross-Sectional Study

Effects of Cognitive-Motor and Motor-Motor Dual Tasks on Gait Performance in Older Adults with Sarcopenia

BACKGROUND

With the advent of global aging, the health of the older population has become a critical public health challenge. The purpose of this study was to investigate the effect of dual-tasking on gait performance in patients with sarcopenia.

METHODS

Thirty participants with sarcopenia (age: 70.73 ± 4.12 yr, MMSE score: 26.90 ± 3.00), including 14 males and 16 females, were selected according to the diagnostic criteria of the Asian Working Group on Sarcopenia. All participants were instructed to perform the gait test in three modes: single task (ST), cognitive-motor dual task (CMDT), and motor-motor dual task (MMDT). Statistical analyses were performed using one-way ANOVA to evaluate the effects of different task types on gait parameters of the participants.

RESULTS

(1) Compared with ST walking, gait frequency, step length, and step speed decreased, and the gait cycle and double-support phase increased in patients with sarcopenia during dual-task walking (p < 0.05); (2) Compared with ST walking, gait variability indices such as stride frequency, stride length, and support period significantly increased in patients with sarcopenia during dual-task walking (p < 0.05).

CONCLUSIONS

The increased difficulty in postural control caused by dual-task interference may reduce the safety of motor strategies in patients with sarcopenia and increase the risk of falls. Future studies should focus on the effects of exercise interventions on multitasking patterns in people with sarcopenia to promote balance function in these populations.

Association between comorbidities associated with diabetes and higher-level functional status in older patients with type 2 diabetes mellitus: a cross sectional study

PURPOSE

To investigate the association between comorbidities associated with diabetes and higher-level functional status as well as the relationship between comorbidities associated with diabetes and higher-level functional status in older patients with type 2 diabetes mellitus who have better social networks.

METHODS

Participants were outpatients with type 2 diabetes aged ≥ 65 years, excluding individuals with severe cardiovascular or respiratory illness, hyperglycaemic crisis, type 1 diabetes, or diabetic foot. The Tokyo Metropolitan Institute of Gerontology Index of Competence (TMIG-IC) was used to evaluate the higher-level functional status. A TMIG-IC score of ≤ 9, instrumental activities of daily living (IADL) ≤ 4, intellectual activity or social role ≤ 3 were defined as decline in higher-level functional status. The comorbidities investigated included peripheral neuropathy, retinopathy, nephropathy, cognitive impairment, depression, frailty, sarcopenia, low muscle strength, stroke, heart disease, and arthritis.

RESULTS

The analysis included 198 patients (mean age 75.9 ± 5.7 years, male 60.1%). After adjusting for potential confounders, depression was associated with TMIG-IC (Prevalence ratio (PR) 2.34, 95% confidence interval (CI) 1.44-3.82), low muscle strength was associated with IADL (PR 2.85, 95% CI 1.30-6.27), and frailty was associated with intellectual activity (PR 1.38, 95% CI 1.10-1.74). In the model with social networks added as a confounder, the relationship between depression or low muscle strength and higher-level functional status was not statistically significant.

CONCLUSION

Comorbidities of depression and low muscle strength for older patients with type 2 diabetes mellitus increase the risk of malfunctioning of higher-level functional status. Increased interactions with family, friends and neighbours may reduce this event.

Characterization of gut microbiota in mouse models of aging and sarcopenia

Gut microbiota play vital roles in the maintenance of human health and in various diseases. We aimed to investigate the association of gut microbiota with aging and sarcopenia. This study contained two experimental designs using the ICR mouse model for 1) determining the association between aging and gut microbiota (by analyzing murine fecal samples) and 2) determining the association between sarcopenia and gut microbiota in mice treated with microorganisms or dexamethasone. The composition of the gut microbiota was determined by next-generation sequencing. Marginally significant differences were observed in taxon composition of the gut microbiota depending on age; particularly, the abundance of the genusAlistipes increased with increasing age. In addition, the abundance of the class Bacteroidia decreased with increasing age, whereas that of the genus Oscillibacter increased. The microbiome composition differed between young mice and aging mice with sarcopenia. Moreover, the gut microbiota in aging and sarcopenia showed altered abundances of Alistipes, Lachnospiraceae, and Bacteroides. Although the sample size was small, these results point to similarities in the gut microbiota between aging and sarcopenia and to differences between young and old individuals. The results on gut microbiota obtained in this study form a basis for studying the development of sarcopenia in geriatric animal models in the future.

Machine Learning Applications in Sarcopenia Detection and Management: A Comprehensive Survey

This extensive review examines sarcopenia, a condition characterized by a loss of muscle mass, stamina, and physical performance, with a particular emphasis on its detection and management using contemporary technologies. It highlights the lack of global agreement or standardization regarding the definition of sarcopenia and the various techniques used to measure muscle mass, stamina, and physical performance. The distinctive criteria employed by the European Working Group on Sarcopenia in Older People (EWGSOP) and the Asian Working Group for Sarcopenia (AWGSOP) for diagnosing sarcopenia are examined, emphasizing potential obstacles in comparing research results across studies. The paper delves into the use of machine learning techniques in sarcopenia detection and diagnosis, noting challenges such as data accessibility, data imbalance, and feature selection. It suggests that wearable devices, like activity trackers and smartwatches, could offer valuable insights into sarcopenia progression and aid individuals in monitoring and managing their condition. Additionally, the paper investigates the potential of blockchain technology and edge computing in healthcare data storage, discussing models and systems that leverage these technologies to secure patient data privacy and enhance personal health information management. However, it acknowledges the limitations of these models and systems, including inefficiencies in handling large volumes of medical data and the lack of dynamic selection capability. In conclusion, the paper provides a comprehensive summary of current sarcopenia research, emphasizing the potential of modern technologies in enhancing the detection and management of the condition while also highlighting the need for further research to address challenges in standardization, data management, and effective technology use.

Assessing physical abilities of sarcopenia patients using gait analysis and smart insole for development of digital biomarker

The aim of this study is to compare variable importance across multiple measurement tools, and to use smart insole and artificial intelligence (AI) gait analysis to create variables that can evaluate the physical abilities of sarcopenia patients. By analyzing and comparing sarcopenia patients with non sarcopenia patients, this study aims to develop predictive and classification models for sarcopenia and discover digital biomarkers. The researchers used smart insole equipment to collect plantar pressure data from 83 patients, and a smart phone to collect video data for pose estimation. A Mann-Whitney U was conducted to compare the sarcopenia group of 23 patients and the control group of 60 patients. Smart insole and pose estimation were used to compare the physical abilities of sarcopenia patients with a control group. Analysis of joint point variables showed significant differences in 12 out of 15 variables, but not in knee mean, ankle range, and hip range. These findings suggest that digital biomarkers can be used to differentiate sarcopenia patients from the normal population with improved accuracy. This study compared musculoskeletal disorder patients to sarcopenia patients using smart insole and pose estimation. Multiple measurement methods are important for accurate sarcopenia diagnosis and digital technology has potential for improving diagnosis and treatment.

Examining Factors Associated with Dynapenia/Sarcopenia in Patients with Schizophrenia: A Pilot Case-Control Study

Sedentary behavior in patients with schizophrenia causes muscle weakness, is associated with a higher risk of metabolic syndrome, and contributes to mortality risk. This pilot case-control study aims to examine the associated factors for dynapenia/sarcopenia in patients with schizophrenia. The participants were 30 healthy individuals (healthy group) and 30 patients with schizophrenia (patient group), who were matched for age and sex. Descriptive statistics, Welch's t-test, cross-tabulations, adjusted residuals, Fisher's exact probability test (extended), and/or odds ratios (ORs) were calculated. In this study, dynapenia was significantly more prevalent in patients with schizophrenia than in healthy individuals. Regarding body water, Pearson's chi-square value was 4.41 (p = 0.04), and significantly more patients with dynapenia were below the normal range. In particular, body water and dynapenia showed a significant association, with an OR = 3.42 and 95% confidence interval [1.06, 11.09]. Notably, compared with participants of the healthy group, patients with schizophrenia were overweight, had less body water, and were at a higher risk for dynapenia. The impedance method and the digital grip dynamometer used in this study were simple and useful tools for evaluating muscle quality. To improve health conditions for patients with schizophrenia, additional attention should be paid to muscle weakness, nutritional status, and physical rehabilitation.