Objective To quantify the associations between muscle-strengthening activities and the risk of non-communicable diseases and mortality in adults independent of aerobic activities. Design Systematic review and meta-analysis of prospective cohort studies. Data sources MEDLINE and Embase were searched from inception to June 2021 and the reference lists of all related articles were reviewed. Eligibility criteria for selecting studies Prospective cohort studies that examined the association between muscle-strengthening activities and health outcomes in adults aged ≥18 years without severe health conditions. Results Sixteen studies met the eligibility criteria. Muscle-strengthening activities were associated with a 10–17% lower risk of all-cause mortality, cardiovascular disease (CVD), total cancer, diabetes and lung cancer. No association was found between muscle-strengthening activities and the risk of some site-specific cancers (colon, kidney, bladder and pancreatic cancers). J-shaped associations with the maximum risk reduction (approximately 10–20%) at approximately 30–60 min/week of muscle-strengthening activities were found for all-cause mortality, CVD and total cancer, whereas an L-shaped association showing a large risk reduction at up to 60 min/week of muscle-strengthening activities was observed for diabetes. Combined muscle-strengthening and aerobic activities (versus none) were associated with a lower risk of all-cause, CVD and total cancer mortality. Conclusion Muscle-strengthening activities were inversely associated with the risk of all-cause mortality and major non-communicable diseases including CVD, total cancer, diabetes and lung cancer; however, the influence of a higher volume of muscle-strengthening activities on all-cause mortality, CVD and total cancer is unclear when considering the observed J-shaped associations. Systematic review registration PROSPERO CRD42020219808.

Letter from JAMA Internal Medicine — Accuracy of Wearable Devices for Estimating Total Energy Expenditure — Comparison With Metabolic Chamber and Doubly Labeled Water Method

Habitual moderate-to-vigorous–intensity physical activity attenuates arterial stiffening. However, it is unclear whether light physical activity also attenuates arterial stiffening. It is also unclear whether light physical activity has the same effects in fit and unfit individuals. This cross-sectional study was performed to determine the relationships between amount of light physical activity determined with a triaxial accelerometer and arterial stiffness. A total of 538 healthy men and women participated in this study. Subjects in each age category were divided into either high-light or low-light physical activity groups based on daily time spent in light physical activity. Arterial stiffness was measured by carotid-femoral pulse wave velocity. Two-way ANOVA indicated a significant interaction between age and time spent in light physical activity in determining carotid-femoral pulse wave velocity ( P <0.05). In the older group, carotid femoral pulse wave velocity was higher in the low-light physical activity level group than in the high-light physical activity level group (945±19 versus 882±16 cm/s; P <0.01). The difference remained significant after normalizing carotid-femoral pulse wave velocity for amounts of moderate and vigorous physical activity. The carotid-femoral pulse wave velocity ( r =−0.47; P <0.01) was correlated with daily time spent in light physical activity in older unfit subjects. No relationship was observed in older fit subjects. These results suggested that longer time spent in light physical activity is associated with attenuation of arterial stiffening, especially in unfit older people.

Background: Self-monitoring using certain types of pedometers and accelerometers has been reported to be effective for promoting and maintaining physical activity (PA). However, the validity of estimating the level of PA or PA energy expenditure (PAEE) for general consumers using wearable devices has not been sufficiently established. Objective: We examined the validity of 12 wearable devices for determining PAEE during 1 standardized day in a metabolic chamber and 15 free-living days using the doubly labeled water (DLW) method. Methods: A total of 19 healthy adults aged 21 to 50 years (9 men and 10 women) participated in this study. They followed a standardized PA protocol in a metabolic chamber for an entire day while simultaneously wearing 12 wearable devices: 5 devices on the waist, 5 on the wrist, and 2 placed in the pocket. In addition, they spent their daily lives wearing 12 wearable devices under free-living conditions while being subjected to the DLW method for 15 days. The PAEE criterion was calculated by subtracting the basal metabolic rate measured by the metabolic chamber and 0.1×total energy expenditure (TEE) from TEE. The TEE was obtained by the metabolic chamber and DLW methods. The PAEE values of wearable devices were also extracted or calculated from each mobile phone app or website. The Dunnett test and Pearson and Spearman correlation coefficients were used to examine the variables estimated by wearable devices. Results: On the standardized day, the PAEE estimated using the metabolic chamber (PAEEcha) was 528.8±149.4 kcal/day. The PAEEs of all devices except the TANITA AM-160 (513.8±135.0 kcal/day; P>.05), SUZUKEN Lifecorder EX (519.3±89.3 kcal/day; P>.05), and Panasonic Actimarker (545.9±141.7 kcal/day; P>.05) were significantly different from the PAEEcha. None of the devices was correlated with PAEEcha according to both Pearson (r=−.13 to .37) and Spearman (ρ=−.25 to .46) correlation tests. During the 15 free-living days, the PAEE estimated by DLW (PAEEdlw) was 728.0±162.7 kcal/day. PAEE values of all devices except the Omron Active style Pro (716.2±159.0 kcal/day; P>.05) and Omron CaloriScan (707.5±172.7 kcal/day; P>.05) were significantly underestimated. Only 2 devices, the Omron Active style Pro (r=.46; P=.045) and Panasonic Actimarker (r=.48; P=.04), had significant positive correlations with PAEEdlw according to Pearson tests. In addition, 3 devices, the TANITA AM-160 (ρ=.50; P=.03), Omron CaloriScan (ρ=.48; P=.04), and Omron Active style Pro (ρ=.48; P=.04), could be ranked in PAEEdlw. Conclusions: Most wearable devices do not provide comparable PAEE estimates when using gold standard methods during 1 standardized day or 15 free-living days. Continuous development and evaluations of these wearable devices are needed for better estimations of PAEE.

Aim: To re‐evaluate the suitability of calf circumference as a surrogate marker of low muscle mass measured by both bioelectrical impedance analysis (BIA) and dual‐energy X‐ray absorptiometry (DXA). We also examined the effects of obesity and age on low muscle mass screening using calf circumference.Methods: In total, 1239 adults participated in this cross‐sectional study. We measured the maximum calf circumference in a standing position and appendicular skeletal muscle mass (ASM) using BIA and DXA. We defined low muscle mass based on the Asian Working Group for Sarcopenia 2019 consensus.Results: Calf circumference was positively correlated with BIA‐measured ASM/height² (men: r = 0.81, women: r = 0.73) and DXA‐measured ASM/height² (men: r = 0.78, women: r = 0.76). In the subgroup analyses by obesity and age, calf circumference was also positively correlated with ASM/height². The optimal calf circumference cut‐offs for low muscle mass screening measured by BIA and DXA were 35 cm (sensitivity 91%, specificity 84%) and 36 cm (sensitivity 82%, specificity 80%) for men, and 33 cm (sensitivity 82%, specificity 84%) and 34 cm (sensitivity 85%, specificity 72%) for women, respectively.Conclusions: Calf circumference is positively correlated with BIA‐ and DXA‐measured muscle mass regardless of obesity and age and is a simple and accurate surrogate marker of muscle mass for diagnosing sarcopenia. Geriatr Gerontol Int 2020; 20: 943–950.