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Objective: This study aimed to characterize the muscle strength and skeletal muscle mass of patients with heart failure by investigating hand-grip strength, five times sit-to-stand (5STS) results, and skeletal muscle mass index (SMI).Materials and Methods: Muscle strength was assessed based on hand-grip strength and 5STS, while skeletal muscle mass was assessed using a bioelectrical impedance analyzer. Hierarchical logistic regression analysis was performed to explore the association between patients with heart failure and healthy elderly individuals.Results: Hierarchical logistic regression analysis was performed to examine the muscle strength and skeletal muscle mass characteristics in patients with heart failure. Hand-grip strength and 5STS responses but not SMI outcomes differed significantly between the two groups. The results of the hierarchical logistic regression analysis revealed that the hand-grip strength and 5STS were significant predictors of heart failure. The odds ratios for hand-grip strength and 5STS were 1.44 and 0.53, respectively.Conclusion: Our results suggested that upper and lower limb muscle strengths (handgrip strength and 5STS) in elderly patients with heart failure worsened significantly without a decrease in skeletal muscle mass.
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Objective@#To assess the relationships between phase angle and muscle mass, strength, and physical function in patients with heart failure. @*Methods@#This study used a cross-sectional design. The analysis included 51 patients with heart failure. The Short Physical Performance Battery, one-leg standing time, handgrip strength, phase angle, and skeletal muscle index were measured. To identify explanatory variables of phase angle, hierarchical multiple regression analysis was performed. @*Results@#Handgrip strength was found to be an explanatory variable of phase angle independent of age, sex, and body mass index. This model was able to explain 30.4% of the model variance for phase angle. @*Conclusion@#In patients with heart failure, improving muscle strength rather than muscle mass or physical function might be more important for improving phase angle. Handgrip strength is an important outcome for improving prognosis in patients with heart failure.
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Objectives: This study examined the effects of the interaction between exercise and sleep on frailty severity in community-dwelling older adults.Materials and Methods: This was a cross-sectional study. Data were collected in July 2019. In total, 2021 adults participated who responded to a questionnaire. Among them, 672 participants (317 men and 355 women) with valid responses were included in the analysis. Ordinal logistic regression analysis was performed to examine the association between frailty severity and the interaction between exercise and sleep. The dependent variable represents three different levels of frailty. The independent variables included basic information and interaction between exercise and sleep.Results: The results of ordinal logistic regression analysis (odds ratio [OR]) showed that the period from the start of exercise (OR=0.96), age (OR=1.00 for participants in their 60 s, OR=1.65 for those in their 70s, and OR=3.13 for those aged >80 years), poor subjective health perception (OR=2.12), poor quality of sleep (OR=1.88), stress (OR=1.62), and exercise–sleep interaction (OR=1.00 based on good-exercise–good-sleep interaction, OR=3.09 poor-exercise–good-sleep interaction, and OR=3.50 poor-exercise–poor-sleep interaction) significantly contributed to the model. The Nagelkerke coefficient of determination adjusted for degrees-of-freedom (R2), which represents the contribution rate of the regression equation, was 0.334.Conclusions: Our results suggest that a combination of good exercise and good sleep is needed to prevent frailty progression in community-dwelling older adults.
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Methods@#This prospective cohort study analyzed patients with osteoporotic vertebral fractures admitted to the hospital between March 2018 and October 2019. Logistic regression analysis was performed to explore the predictors of vertebral collapse at >4 weeks after admission. Model 1 used basic medical information and physical functions at admission; model 2 used basic medical information and physical function and activity at >4 weeks after admission. @*Results@#In the model 1 results of logistic regression analysis, cardiovascular disease (odds ratio [OR], 12.27; 95% confidence interval [CI], 1.28–117.91) was extracted as a factor affecting vertebral collapse at ≥4 weeks after admission. In the model 2 results of logistic regression analysis, cardiovascular disease (OR, 34.57; 95% CI, 2.53–471.74), movement control during one leg standing at 4 weeks (OR, 7.25; 95% CI, 1.36–38.71), and Pain Catastrophizing Scale score at 4 weeks (OR, 1.11; 95% CI, 1.01–1.21) were extracted as factors affecting vertebral collapse at ≥4 weeks after admission. @*Conclusions@#Our results indicate that physical functions and comorbidity affect collapse at ≥4 weeks after admission in patients with osteoporotic vertebral fractures.
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Objectives@#Physical activity to maintain bone mass and strength is important for hip fracture prevention. We aim to investigate the relationship between physical performance/activity status and bone mineral density (BMD)/hip structural analysis (HSA) parameters among postmenopausal women in Japan. @*Methods@#Sixty-two postmenopausal women diagnosed with osteoporosis (mean age: 72.61 ± 7.43 years) were enrolled in this cross-sectional observational study. They were evaluated for BMD and HSA in the proximal femur by dual-energy X-ray absorptiometry and underwent several physical performance tests, the Geriatric Locomotive Function Scale of 25 questions (GLFS-25). Principal component analysis (PCA) was used to summarize data on the BMD/HSA parameters. Partial correlation analysis, multiple regression analysis, and structural equation modeling (SEM) were performed to investigate the relationship between physical performance/activity status and BMD/HSA parameters of the proximal femur. @*Results@#In a partial correlation analysis adjusted for age and body mass index (BMI), GLFS-25 scores were correlated with HSA parameter (|r| = 0.260–0.396, P < 0.05). Principal component 1 (PC1) calculated by PCA was interpreted as more reflective of bone strength based on the value of BMD/HSA parameters. The SEM results showed that the model created by the 3 questions (Q13, brisk walking; Q15, keep walking without rest; Q20, load-bearing tasks and housework) of the GLFS-25 had the best fit and was associated with the PC1 score (β = −0.444, P = 0.001). @*Conclusions@#The GLFS-25 score was associated with the BMD/HSA parameter, which may reflect the bone strength of the proximal femur as calculated by PCA.
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This study aimed to clarify the factors influencing changes in activities of daily living (ADL) in patients receiving home rehabilitation. The study involved patients receiving home rehabilitation for 6 months between December 2017 and June 2018. There were no exclusion criteria for disease. For 35 patients (21 women; mean age, 77.4 ± 10.4 years), we investigated basic information and measured grip strength, Bedside Mobility Scale (BMS) score, and Functional Independence Measure (FIM) score at baseline and 6 months later. Changes in grip strength, BMS, and FIM between baseline and 6 months were calculated. Multiple regression analysis was used to identify factors influencing the change in FIM score. Multiple regression analysis extracted the factors of period from onset of main disease, amount of change in grip strength, and amount of change in BMS. The standardized partial regression coefficients were －0.331, 0.353, and 0.320, respectively. The adjusted coefficient of determination was 0.392. Thus, early intervention after onset of main disease, improvement of grip strength, and improvement of BMS score appear to be important to improving ADL after 6 months of home rehabilitation.