It has been recognized that alternate day calorie restriction (ADCR) or exercise has positive effects on cardio-metabolic risk factors. It is unclear whether the combined effect of ADCR and exercise (aerobic + resistance training) influences risk. We investigated effects of an 8-week ADCR and exercise program (aerobic + resistance training) on cardio-metabolic risk factors in overweight and obese adults. This study randomized 45 overweight or obese but healthy adults (F = 26, M = 19; aged about 32 to 40 years) into 4 groups: ADCR (n = 13), exercise (n = 10), exercise plus ADCR (n = 12), and control (n = 10) for 8 weeks. Body composition, blood lipids profile, and insulin resistance were measured. The intention to treat (ITT) method was used to analyze all participants that were randomized. A total of 35 participants completed the trial (78%). Body weight, body mass index, waist circumference, fat mass and percent body fat were reduced in the exercise plus ADCR group (− 3.3 ± 2.4 kg, p < 0.01; − 1.3 ± 1.0 kg/m2, p < 0.01; − 4.1 ± 3.9 cm, p < 0.01; − 2.7 ± 2.0 kg, p < 0.01; − 2. 5 ± 2.2%, p < 0.01). Insulin, glucose, homeostasis model assessment insulin resistance and triglyceride (− 2.9 ± 4.1 μIU/ml, p < 0.05; − 10.9 ± 16.9 mg/dl, p < 0.05; − 0.9 ± 1.3, p < 0.05; − 43.8 ± 41.9 mg/dl, p < 0.01) decreased in the exercise plus ADCR group only. ADCR and exercise both proved to be beneficial, but the combined intervention was most effective at inducing beneficial changes in body weight, body composition, glucose, insulin, insulin resistance and triglyceride in overweight and obese adults. ClinicalTrials.gov: NCT03652532 , Registered August 28, 2018, ‘retrospectively registered’.

Background: This study aimed to test the validity of three different submaximal tests (i.e., 3-min step test with 20.3-cm step box height (3MST₂₀), 3-min step test with 30-cm step box height (3MST₃₀), and 6-min walk test (6MWT)) in estimating maximal oxygen consumption (VO_2max) in young and healthy individuals. Methods: The 3MST₂₀, 3MST₃₀, 6MWT, as well as the cardiopulmonary exercise test (CPET) were performed in 73 participants (37 men and 36 women; mean age: 30.8 ± 9.3 years). All participants visited the clinic three times in a random order for anthropometric measurements, three submaximal tests, and the VO_2max test. Multiple linear regression analyses were conducted to construct the VO_2max prediction equations for each submaximal test. Results: The prediction equations developed based on multiple regression analyses for each submaximal tests were as follows: 3MST₂₀: VO_2max = 86.0 − 10.9 × sex (male = 1, female = 2) − 0.4 × age − 0.1 × weight − 0.1 × heart rate recovery at 30 s (HRR30s); 3MST₃₀: VO_2max = 84.5 − 10.2 × sex (male = 1, female = 2) − 0.4 × age − 0.1 × weight − 0.1 × HRR30s; and 6MWT: VO_2max = 61.1 − 11.1 × sex (male = 1, female = 2) − 0.4 × age − 0.2 × weight − 0.2 × (distance walked·10⁻¹). The estimated VO_2max values based on formulated equations were 37.0 ± 7.9, 37.3 ± 7.6, and 36.9 ± 7.9 mL∙kg⁻¹∙min⁻¹ derived from the 3MST₂₀, 3MST₃₀, and 6MWT, respectively. These estimated VO_2max values were not significantly different from the measured VO_2max value, 37.3 mL∙kg⁻¹∙min⁻¹. The estimated VO_2max based on the 3MST₂₀, 3MST₃₀, and 6MWT results explained 73.4%, 72.2%, and 74.4% of the variances in the measured VO_2max (p < 0.001), respectively. Conclusions: The 3MST₂₀, 3MST₃₀, and 6MWT were valid in estimating VO_2max in relatively young and healthy Asian individuals.

The bioelectrical impedance analysis (BIA) method is widely used to predict percent body fat (PBF). However, it requires four to eight electrodes, and it takes a few minutes to accurately obtain the measurement results. In this study, we propose a faster and more accurate method that utilizes a small dry electrode-based wearable device, which predicts whole-body impedance using only upper-body impedance values. Such a small electrode-based device typically needs a long measurement time due to increased parasitic resistance, and its accuracy varies by measurement posture. To minimize these variations, we designed a sensing system that only utilizes contact with the wrist and index fingers. The measurement time was also reduced to five seconds by an effective parameter calibration network. Finally, we implemented a deep neural network-based algorithm to predict the PBF value by the measurement of the upper-body impedance and lower-body anthropometric data as auxiliary input features. The experiments were performed with 163 amateur athletes who exercised regularly. The performance of the proposed system was compared with those of two commercial systems that were designed to measure body composition using either a whole-body or upper-body impedance value. The results showed that the correlation coefficient ( $r^2$ ) value was improved by about 9%, and the standard error of estimate (SEE) was reduced by 28%.

The aim of the study was to develop a simple submaximal walk test protocol and equation using heart rate (HR) response variables to predict maximal oxygen consumption (VO₂max). A total of 60 healthy adults were recruited to test the validity of 3 min walk tests (3MWT). VO₂max and HR responses during the 3MWTs were measured. Multiple regression analysis was used to develop prediction equations. As a result, HR response variables including resting HR and HR during walking and recovery at two different cadences were significantly correlated with VO₂max. The equations developed using multiple regression analyses were able to predict VO₂max values (r = 0.75–0.84; r² = 0.57–0.70; standard error of estimate (SEE) = 4.80–5.25 mL/kg/min). The equation that predicted VO₂max the best was at the cadence of 120 steps per minute, which included sex; age; height; weight; body mass index; resting HR; HR at 1 min, 2 min and 3 min; HR recovery at 1 min and 2 min; and other HR variables calculated based on these measured HR variables (r = 0.84; r² = 0.70; SEE = 4.80 mL/kg/min). In conclusion, the 3MWT developed in this study is a safe and practical submaximal exercise protocol for healthy adults to predict VO₂max accurately, even compared to the well-established submaximal exercise protocols, and merits further investigation.

PURPOSE: This study aimed to investigate the level of physical function, lower body strength, and muscle activation during various types of muscle contraction in participants with and without Parkinson’s disease (PD).METHODS: Twelve participants with PD (mean age=63.17±6.24 years) and 12 age- and sex-matched healthy adults (mean age = 58.67±6.39 years) were recruited. An isokinetic dynamometer was used to measure the length- and velocity-dependent maximum voluntary force and the rate of torque development (RTD) of the knee extensor muscles. Muscle activation of the vastus lateralis (VL), vastus medialis (VM), and rectus femoris (RF) muscles of both legs was examined using surface electromyography. The 6-minute walk test, chair stand test, timed up-and-go test, sit-and-reach test, and back-scratch test were performed to assess physical function.RESULTS: Compared to healthy individuals, participants with PD showed significantly lower maximum voluntary force and RTD (p<.05), performed fewer repetitions in the chair stand test (11.64±1.75 vs. 17.08±2.27, p<.001), were slower in the timed up-andgo test (8.36±1.42 vs. 5.65±1.07, p<.001), and walked shorter distances in the 6-minute walk test (424.17±65.97 vs. 539.47±63.18, p<.001). However, activation of the three different muscles during isometric and isokinetic muscle contraction was not different between participants with and without PD.CONCLUSIONS: Preserved muscle activation and significantly lower muscle strength during various types of muscle contractions may suggest lower muscle strength and efficiency. The lower physical function seen in participants with mild PD could be due to disease and low physical activity-related muscle atrophy rather than lower muscle activation.