Background and objectives: One of the greatest challenges facing the healthcare of the aging population is frailty. There is growing scientific evidence that gait assessment using wearable sensors could be used for prefrailty and frailty screening. The purpose of this study was to examine the ability of a wearable sensor-based assessment of gait to discriminate between frailty levels (robust, prefrail, and frail). Materials and methods: 133 participants (≥60 years) were recruited and frailty was assessed using the Fried criteria. Gait was assessed using wireless inertial sensors attached by straps on the thighs, shins, and feet. Between-group differences in frailty were assessed using analysis of variance. Associations between frailty and gait parameters were assessed using multinomial logistic models with frailty as the dependent variable. We used receiver operating characteristic (ROC) curves to calculate the area under the curve (AUC) to estimate the predictive validity of each parameter. The cut-off values were calculated based on the Youden index. Results: Frailty was identified in 37 (28%) participants, prefrailty in 66 (50%), and no Fried criteria were found in 30 (23%) participants. Gait speed, stance phase time, swing phase time, stride time, double support time, and cadence were able to discriminate frailty from robust, and prefrail from robust. Stride time (AUC = 0.915), stance phase (AUC = 0.923), and cadence (AUC = 0.930) were the most sensitive parameters to separate frail or prefrail from robust. Other gait parameters, such as double support, had poor sensitivity. We determined the value of stride time (1.19 s), stance phase time (0.68 s), and cadence (101 steps/min) to identify individuals with prefrailty or frailty with sufficient sensitivity and specificity. Conclusions: The results of our study show that gait analysis using wearable sensors could discriminate between frailty levels. We were able to identify several gait indicators apart from gait speed that distinguish frail or prefrail from robust with sufficient sensitivity and specificity. If improved and adapted for everyday use, gait assessment technologies could contribute to frailty screening and monitoring.

Background and Objectives: It is thought that muscle and bone interact only on a biomechanical level, however, some research is now emerging that links bone and muscle on a cellular level. The aim of this study was to explore associations between physical function, muscle mass and bone density in community-dwelling elderly men with sarcopenia. A secondary goal was to analyze if muscle morphology was associated with bone density and physical functioning. Materials and Methods: Body composition was measured by dual-energy X-ray absorptiometry (DXA). Bone density was evaluated according to WHO criteria. Sarcopenia was diagnosed according to European Working Group on Sarcopenia in Older People (EWGSOP) criteria: low muscle mass and low muscle strength or low physical performance. Microbiopsy of musculus vastus lateralis was performed with a disposable muscle microbiopsy system. The perimeter and cross-sectional area of muscle fibers were calculated using image analysis software in whole slide images; type of fibers and their distribution were evaluated as well. Results: A total of 151 men, 60 years or older were included in this study. Mean age of the subjects was 72.9 ± 8.02 years. Sarcopenia was diagnosed in 45 (29.8%) men. Multiple significant correlations were found between bone mineral density, lean mass, appendicular lean mass, arm and leg lean mass, gait speed, balance test and handgrip strength in sarcopenic men. Lean mass was associated with femoral neck BMD (bone mineral density; r = 0.418, p = 0.006) and handgrip strength (r = 0.553, p < 0.001). In the sarcopenia group, 25 muscle biopsies were examined. In 9 sarcopenic men with T-scores equal or below −2.5, the muscle fiber area had a significant correlation with the balance test (r = 0.73, p = 0.025). Conclusions: In men with sarcopenia, low lean muscle mass was associated with low femoral neck BMD and low muscle strength. In sarcopenic men with osteoporosis, low muscle fiber area was associated with low scores in a balance test.

Background and Objectives: Information on how psychomotor speed is associated with the risk of falling is scarce, even in older adults. Therefore, this study aimed to determine the relationship between falls and psychomotor speed in older adults with sarcopenia and frailty. Materials and Methods: A total of 204 subjects (aged 83 (77–87) years) participated in this study: 161 women (78.9%) and 43 men (21.1%). The history of falls was assessed by asking whether the subject had experienced a fall in the past 12 months. Psychomotor speed was evaluated by reaction time and frequency of movement. Sarcopenia was diagnosed based on the EWGSOP2 criteria. Frailty was confirmed if the participants met ≥3 criteria according to the Fried frailty criteria. The relationship between falls and psychomotor speed was measured using partial correlations. Binary logistic regression analysis was used to assess if psychomotor speed had an impact on falls. Results: Sarcopenia was confirmed in 93 (45.58%) and frailty in 91 (44.6%) subjects. Both sarcopenia and frailty were present in 62 (30.39%) participants. In the sarcopenia and frailty group, falls were related to simple reaction time (r = 0.444, p = 0.002), hand movement frequency in 10 s (r = −0.352, p = 0.014), and in 60 s (r = −0.312, p = 0.026). In women with sarcopenia and frailty, there were relationships between falls and simple reaction time (r = 0.68, p = 0.002), complex reaction time (r = 0.406, p = 0.004), hand movement frequency in 10 s (r = −0.614, p = 0.001), and in 60 s (r = −0.584, p = 0.001). In regression analysis, it was found that each millisecond increase in reaction time was associated with a 1.5% higher fall risk in the participants with sarcopenia (OR: 1.015 [1, 1.031], p = 0.048). Conclusions: This study demonstrates that slower psychomotor speed, particularly reaction time, is linked to a higher risk of falls in older adults with sarcopenia and frailty, especially in women.

Background: The aim of this study was to explore the association between muscle mass, morphology, bone mineral density, and physical function in community-dwelling older men with sarcopenia.Methods: A total of 151 men, 60 years or older were included in this study. Body composition was measured by dual-energy X-ray absorptiometry (DXA). Low bone mineral density was diagnosed if T-score was equal to or below -1.0 SD of mean young men reference range. Sarcopenia was diagnosed according to European Working Group on Sarcopenia in Older People (EWGSOP) criteria: low muscle mass and low muscle strength or low physical performance. Physical performance was evaluated by short physical performance battery. Microbiopsy of musculus vastus lateralis was performed with disposable muscle microbiopsy system. The perimeter and cross-section area of muscle fibers were calculated using image analysis software in whole slide images; type of fiber and their distribution were evaluated as well. Relationship between variables were examined using Spearman’s and Pearson’s correlations. The level of significance (p-value) of < 0.05 was considered as statistically significant.Results: Mean age of the subjects was 72.9 ± 8.02 years. Sarcopenia was diagnosed in 45 (29.8%) men. In the sarcopenia group, 25 muscle biopsies were examined. The average muscle fiber length was 217.47 ± 25.22 microm and average fiber cross-sectional area was 2446 ± 608.87 microm². In 9 sarcopenic men with T-scores equal or below -2.5, the muscle fiber area had a significant correlation with balance test (r = 0.73, p = 0.025). Multiple significant correlations were found between bone mineral density, lean mass, appendicular lean mass, arm and leg lean mass, gait speed, balance test and handgrip strength.Conclusions: In men with sarcopenia, low lean muscle mass was associated with low femoral neck and hip BMD, and lower muscle strength. In sarcopenic men with osteoporosis, lower muscle fiber area was associated with lower scores of balance test.Trial registration: study protocol has been approved by Lithuanian regional biomedical research ethics committee (No. 158200-03-208-75).