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Resistance training is used to combat skeletal muscle function decline in older adults. Few studies have been designed specific for females, resulting in very limited treatment options for skeletal muscle atrophy in aging women. Here, we analyzed the gene expression profiles of skeletal muscle samples from sedentary young women, sedentary older women, and resistance-trained older women, using microarray data from public database. A total of 45 genes that were differentially expressed during female muscle aging and reversed by resistance training were identified. Functional and pathway enrichment analysis, protein–protein interaction network analysis, and receiver operating characteristic analysis were performed to reveal the key genes and pathways involved in the effects of resistance training on female muscle aging. The collagen genes COL1A1, COL3A1, and COL4A1 were identified important regulators of female muscle aging and resistance training, by modulating multiple signaling pathways, such as PI3 kinase-Akt signaling, focal adhesions, extracellular matrix-receptor interactions, and relaxin signaling. Interestingly, the expression of CDKN1A and TP63 were increased during aging, and further upregulated by resistance training in older women, suggesting they may negatively affect resistance training outcomes. Our findings provide novel insights into the molecular mechanisms of resistance training on female muscle aging and identify potential biomarkers and targets for clinical intervention.

Community-dwelling people with Mild Cognitive Impairment self-reporting not to be meeting recommended physical activity levels participated in this study to (a) determine compliance of wearing (thigh-worn) accelerometers, (b) describe physical activity levels and sedentary behavior, and (c) determine the validity of the Physical Activity Scale for the Elderly (PASE) compared with activPAL accelerometers. A total of 79 people had valid accelerometer data (median [interquartile range]: age, 71 [54–75] years). Compliance was 86.81%. Participants were sedentary for 10.6 hr per day and engaged in a median of 9 min per day of moderate-intensity physical activity. Fair correlations were found between the PASE and total stepping time per day (r = .35, p < .01), total number of steps per day (r = .36, p < .01), and number of steps in stepping activities completed for ≤1 min (r = .42, p < .01). The PASE and Standing time (r = .04, p = .724) and PASE and Sitting time (r = .04, p = .699) had little to no relationship. The use of thigh-worn accelerometers for this population is achievable. People with Mild Cognitive Impairment have high levels of sedentary behavior and minimal engagement in moderate-intensity physical activity. The PASE has fair, positive criterion validity with activity-based outcomes measured by activPAL accelerometers but not with sedentary behavior, which is high for this population.

The aims of the current study were to analyze the association between the barriers to and changes in physical activity levels and sedentary behavior, as well as to examine whether these barriers change over time in patients with peripheral artery disease. In this longitudinal study, we assessed 72 patients (68% men; 65.7 ± 9.2 years). Physical activity was measured over a 7-day period using an accelerometer, and data were collected on time spent in sedentary activities, low-light physical activities, and moderate-to-vigorous physical activities. Personal and environmental barriers to physical activity were collected using yes or no questions. Assessments were repeated in the same patients after 27 months (95% confidence interval [26, 28] months). Most barriers remained stable in these patients; however, those who reported lack of money experienced an increase in sedentary behavior (β = 392.9 [159.7] min/week, p = .02) and a decrease in low-light physical activity (β = −372.4 [140.1] min/week, p = .02). These findings suggest that patients with symptomatic peripheral artery disease typically exhibit stable barriers over time, and individuals reporting lack of money demonstrated a decrease in low-light physical activity and an increase in sedentary behavior after 27 months.

There is a critical need for fall-prevention interventions to reach medically underserved, hard-to-reach, rural older adults. The evidence-based Tai Ji Quan: Moving for Better Balance (TJQMBB) program reduces falls in older adults. This pre-COVID-19 pandemic study assessed the feasibility and impact of a 16-week tele-TJQMBB intervention in older adults. Instructors led six tele-TJQMBB classes via Zoom for 52 older adults (mean age ± SD 68.5 ± 7.7 years) at one academic and four community sites. Nearly all (97%) planned sessions were delivered. Average attendance was 61%. There were no adverse events. Fidelity was fair to good (mean 67%). Forty-one percent of sessions experienced technical disruptions. Participants improved their gait speed, balance, lower-extremity strength, and body mass index. Tele-TJQMBB was feasible with a positive impact on outcomes. This study was the first step toward establishing an additional delivery mode that could potentially expand TJQMBB’s reach and maintenance.

Little is known about physical activity (PA) and sedentary behavior (SB) among nursing home residents although PA is known as a health promoter. This study examined PA, SB, and their predictors among nursing home residents (n = 63). Dependent variables were accelerometry-based PA and SB. Predictor variables included in a path analysis were age, sex, body mass index, Barthel Index, cognitive status (Mini-Mental State Examination), physical performance (hand grip strength and habitual walking speed), and well-being (World Health Organization-5 well-being index). PA was very low (M steps per day = 2,433) and SB was high (M percentage of sedentary time = 89.4%). PA was significantly predicted by age (β = −0.27, p = .008), body mass index (β = −0.29, p = .002), Barthel Index (β = 0.24, p = .040), and hand grip strength (β = 0.30, p = .048). SB was significantly predicted by body mass index (β = 0.27, p = .008) and Barthel Index (β = −0.30, p = .012). Results might be helpful for everyday practice to identify individuals at high risk for low PA and high SB.