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The present study was performed to develop regression-based prediction equations for skeletal muscle (SM) mass by ultrasound and to investigate the validity of these equations in Japanese adults. Seventy-two Japanese men (n=38) and women (n=34) aged 18-61 years participated in this study and were randomly separated into two groups: the model development group (n=48) and the validation group (n=24). The total and regional SM mass were measured using magnetic resonance imaging (MRI) 1.5 T-scanners with spin-echo sequence. Contiguous transverse images (about 150 slices) with a slice thickness of 1 cm were obtained from the first cervical vertebra to the ankle joints. The volume of SM was calculated from the summation of digitized cross-sectional area. The SM volume was converted into mass units (kg) by an assumed SM density of 1.04 kg l(-1). The muscle thickness (MTH) was measured by B-mode ultrasound (5 MHz scanning head) at nine sites on the anatomical SM belly. Strong correlations were observed between the site-matched SM mass (total, arm, trunk body, thigh, and lower leg) by MRI measurement and the MTH x height (in m) in the model development group (r=0.83-0.96 in men, r=0.53-0.91 in women, P<0.05). When the SM mass prediction equations were applied to the validation group, significant correlations were also observed between the MRI-measured and predicted SM mass (P<0.05). The predicted total SM mass for the validation group was 19.6 (6.5) kg and was not significantly different from the MRI-measured SM mass of 20.2 (6.5) kg. Bland-Altman analysis did not indicate a bias in prediction of the total SM mass for the validation group (r=0.00, NS). These results suggested that ultrasound-derived prediction equations are a valid method to predict SM mass and an alternative to MRI measurement in healthy Japanese adults.

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TANAKA, CHIAKI, SHIGEHO TANAKA, JUNKO KAWAHARA, AND TAISHI MIDORIKAWA. Triaxial accelerometry for assessment of physical activity in young children. Obesity. 2007;15:1233-1241. Objective: The purpose of the present study was to derive linear and non-linear regression equations that estimate energy expenditure (EE) from triaxial accelerometer counts that can be used to quantitate activity in young children. We are unaware of any data regarding the validity of triaxial accelerometry for assessment of physical activity intensity in this age group. Research Methods and Procedures: EE for 27 girls and boys (6.0 Ϯ 0.3 years) was assessed for nine activities (lying down, watching a video while sitting and standing, line drawing for coloring-in, playing blocks, walking, stair climbing, ball toss, and running) using indirect calorimetry and was then estimated using a triaxial accelerometer (ActivTracer, GMS). Results: Significant correlations were observed between synthetic (synthesized tri-axes as the vector), vertical, and horizontal accelerometer counts and EE for all activities (0.878 to 0.932 for EE). However, linear and non-linear regression equations underestimated EE by Ͼ30% for stair climbing (up and down) and performing a ball toss. Therefore, linear and non-linear regression equations were calculated for all activities except these two activities, and then evaluated for all activities. Linear and non-linear regression equations using combined vertical and horizontal acceleration counts, synthetic counts, and horizontal counts demonstrated a better relationship between accelerometer counts and EE than did regression equations using vertical acceleration counts. Adjustment of the predicted value by the regression equations using the vertical/horizontal counts ratio improved the overestimation of EE for performing a ball toss. Discussion: The results suggest that triaxial accelerometry is a good tool for assessing daily EE in young children.

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/height 2 (men: r = 0.81, women: r = 0.73) and DXA-measured ASM/height 2 (men: r = 0.78, women: r = 0.76). In the subgroup analyses by obesity and age, calf circumference was also positively correlated with ASM/height 2. The optimal calf circumference cutoffs 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.

Research Methods and Procedures:Twenty-one Japanese adults were fitted with a triaxial accelerometer while also in a whole-body human calorimeter for 22.5 hours. The protocol time was composed of sleep (8 hours), four structured activity periods totaling 4 hours (sitting, standing, housework, and walking on a treadmill at speeds of 71 and 95 m/min, 2 ϫ 30 minutes for each activity), and residual time (10.5 hours). Acceleration data (milligausse) from the different periods and their relationship to physical activity ratio obtained from the human calorimeter allowed for the development of EE equations for each activity. The EE equations were validated on the residual times, and the percentage difference for the prediction errors was calculated as (predicted value Ϫ measured value)/measured value ϫ 100. Results: Using data from triaxial accelerations and the ratio of horizontal to vertical accelerations, there was relatively high accuracy in identifying the four different periods of activity. The predicted EE (882 Ϯ 150 kcal/10.5 hours) was strongly correlated with the actual EE measured by human calorimetry (846 Ϯ 146 kcal/10.5 hours, r ϭ 0.94 p Ͻ 0.01), although the predicted EE was slightly higher than the measured EE. Discussion: Triaxial accelerometry, when total, vertical, and horizontal accelerations are utilized, can effectively evaluate different types of activities and estimate EE for low-intensity physical activities associated with modern lifestyles.

The high REE for Sumo wrestlers can be attributed not to an elevation of the organ-tissue metabolic rate, but to a larger absolute amount of low and high metabolically active tissue including SM, liver, and kidney.