This study was designed to examine 1) the role of exercise physical activity (EPA), and then 2) physical fitness and body composition upon variation of the total energy expenditure (TEE) in healthy ...Japanese men aged 30 to 69 y (n=40). EPA and TEE Were as-sessed over 14 d using an accelerometer and a doubly labeled water (DLW) method, respectively. Basal metabolic rate (BMR) was measured after 10 h fasting on the morning of the day of DLW dosing. Physical activity-induced energy expenditure (PAEE) was calculated by subtracting BMR and diet-induced thermogenesis (DIT=10% TEE) from TEE. EPA was subdivided into three intensities: low, moderate and high and the accumulated duration (time expressed in minutes) of each of these was calculated. Body composition and physical fitness (VO2max) were determined using an underwater weighing method and a treadmill exercise test, respectively. BMR (mean±SD: 1, 459±181 kcal/d) declined significantly with age (r=-0.37, p<0.05), but PAEE (946±320 kcal/d) and TEE (2, 672±369 kcal/d) did not. A multiple stepwise regression analysis was used to develop an empirical model that relates energy expenditure measured by the DLW (TEE) to age, height, body mass index, FM, FFM, percentage body fat, VO2max, and accumulated duration spent for low-, moderate-, and high-intensity EPA. The results revealed that FFM and high-intensity EPA were identified as important determinants of TEE and accounted for 51%. We may therefore conclude that 1) high-intensity EPA appears to be relevant in determining TEE, especially among active individuals, and 2) body composition was more important than physical fitness in determining TEE in this population.
In this study we investigated the effects of hydrogen (H2) supplement, in the form of calcium bound H2 powder capsules, on aerobic and anaerobic cycling exercise.
Trained male subjects participated ...in a randomized, double-blind, crossover design trial and received H2-rich calcium powder (HCP) supplement (1500 mg/day, 2.544 μg/day of H2 gas) or H2-depleted placebo (PLA) (1500 mg/day) for 3 consecutive days.
Aerobic experiment: Eighteen subjects carried out a cycling incremental exercise starting at 20 watts (W) work rate, and increasing by 20 W/2 minutes until exhaustion. Blood gases including pH, bicarbonate ion (HCO3–), partial pressures of CO2 (PCO2), metabolic profile including lactate (Lac), and electrolytes including chloride (Cl–) were measured at rest and at 120-, 200-, and 240-W work rates.
Anaerobic experiment: Six subjects carried out a 30 second Wingate anaerobic exercise test (WAnT) bout with a resistive load of 7.5% of body mass. Lac was then measured at 1-, 3-, 5-, and 15-minutes following the WAnT exercise.
Aerobic experiment: At rest, HCP had a significantly lower pH (P = 0.048), Cl– (P = 0.011), and a higher HCO3– (P = 0.041), PCO2 (P = 0.026) compared to the PLA group. During exercise, pH decrease (supplement effect: P = 0.043) and the HCO3– increase (supplement effect: P = 0.030) continued in the HCP group. Additionally, HCP did not affect peak work load and exercise duration. And no changes were noted in Lac at rest or during exercise.
Anaerobic experiment: HCP did not affect peak power output or Lac recovery following WAnT. However the average power output during exercise was significantly higher in the HCP group (P = 0.019) compared to the PLA group.
HCP supplementation following 3 days of intake, slightly lowered pH during aerobic exercise, and increased average power output in the anaerobic WAnT exercise compared to the PLA group. HCP supplement might have an ergogenic effect in an anaerobic exercise setting.
This study was supported by The Japan Society for the Promotion of Science, and the Ministry of Education, Science, and Culture of Japan. In addition, we received a research grant from the company ENAGEGATE Inc. and they provided the HCP supplement and placebo. However, no intercession, restrictions or agreements of any kind was imposed between parties regarding research design, results or publications.
Evaluation of total energy expenditure (TEE) and physical activity level (PAL) is important for treatment of patients with type 2 diabetes mellitus (T2DM). However, the validity of accelerometers ...(ACC) and physical activity questionnaires (PAQ) for estimating TEE and PAL remains unknown in elderly populations with T2DM. We evaluated the accuracy of TEE and PAL results estimated by an ACC (TEEACC and PALACC) and a PAQ (TEEPAQ and PALPAQ) in elderly patients with T2DM.
Fifty-one elderly patients with T2DM (aged 61-79 years) participated in this study. TEEACC was calculated with PALACC using a triaxial ACC (Active style Pro HJA-750c) over 2 weeks and predicted basal metabolic rate (BMR) by Ganpule's equation. TEEPAQ was estimated using predicted BMR and the PALPAQ from the -Japan Public Health Center Study-Long questionnaire. We compared the results to TEEDLW measured with the doubly labeled water (DLW) method and PALDLW calculated with BMR using indirect calorimetry.
TEEDLW was 2,165 ± 365 kcal/day, and TEEACC was 2,014 ± 339 kcal/day; TEEACC was strongly correlated with TEEDLW (r = 0.87, p < 0.01) but significantly underestimated (-150 ± 183 kcal/day, p < 0.05). There was no significant difference in TEEPAQ and TEEDLW (-49 ± 284 kcal/day), while the range of difference seemed to be larger than TEEACC. PALDLW, PALACC, and PALPAQ were calculated to be 1.71 ± 0.17, 1.69 ± 0.16, and 1.78 ± 0.24, respectively. -PALACC was strongly correlated with PALDLW (r = 0.71, p < 0.01), and there was no significant difference between the 2 values. PALPAQ was moderately correlated with PALDLW (r = 0.43, p < 0.01) but significantly overestimated. Predicted BMR was significantly lower than the BMR -measured by indirect calorimetry (1,193 ± 186 vs. 1,262 ± 155 kcal/day, p < 0.01).
The present ACC and questionnaire showed acceptable correlation of TEE and PAL compared with DLW method in elderly patients with T2DM. Systematic errors in estimating TEE may be improved by the better equation for predicting BMR.
The present study clarified the prevalence of poor sleep quality and its relation to lifestyle habits, competitive-based activities, and psychological distress among Japanese student-athletes in the ...initial pandemic period (2020) and 1 year later (2021).
In the present study, student-athletes were defined as individuals belonging to university athletic clubs. The data of two cross-sectional surveys (2020:
= 961 and 2021:
= 711) were collected from student-athletes in 6 universities in Japan. First, the prevalence of poor sleep quality (Pittsburgh sleep quality index score > 5) was investigated. Relationships between poor sleep quality and lifestyle habits, competition-based activities, and psychological distress were then explored using multivariate logistic regression analysis adjusted for age, sex, and body mass index.
The prevalence of poor sleep quality was 33.6% in 2020 and 36.6% in 2021. Poor sleep quality in 2020 was related to late bedtime, taking supplements before bed, part-time job (no late night), stressors of expectations and pressure from others, and psychological distress, whereas that in 2021 was related to early wake-up time, skipping breakfast, taking caffeinated drinks before bed, use of smartphone/cellphone after lights out, stressors of motivation loss, and psychological distress.
In both 2020 and 2021, one-third of student-athletes had poor sleep quality and psychological distress was its common risk factor. Lifestyle habits and competition stressors associated with poor sleep quality were pandemic-specific in 2020, but similar to the prepandemic period in 2021.
The number of long-term care (LTC) users and the associated expenditures in Japan are increasing dramatically. The national government recommends LTC prevention through activation of communities. ...However, there is no clear evidence of the effect of population-based comprehensive geriatric intervention program (CGIP) for restraints of LTC users and the associated expenditures in the future. The aims of the current paper are to describe the study protocol and progress of a cluster randomized controlled trial (RCT) with a CGIP in Kameoka City.
The cluster RCT involved random allocation of regions as intervention (n=4,859) and nonintervention (n=7,195). Participants were elderly persons aged ≥65 years without LTC certification who had responded to a mailing survey. The residents living in intervention regions were invited to a physical check-up, and 1,463 people participated (30.3%). These individuals were invited to the CGIP, and 526 accepted. The CGIP comprised instructions on: 1) low-load resistance training using bodyweight, ankle weights, and elastic bands; 2) increasing daily physical activity; 3) oral motor exercise and care; and 4) a well-balanced diet based on a program from Ministry of Health, Labour and Welfare. We allocated the intervention regions randomly into home-based self-care program alone (HB group, 5 regions, n=275) and home-based program+weekly class-style session (CS group, 5 regions, n=251). We evaluated the effects of the CGIP at 12 weeks and at 12 or 15 months on physical function, and are conducting follow-up data collection for an indefinite period regarding LTC certification, medical costs, and mortality.
The study was launched with good response rates in each phase. Participants of both groups significantly increased their step counts by ~1,000 per day from the baseline during the CGIP. This RCT will provide valuable information and evidence about effectiveness of a community-based CGIP.
The Effects of Foot Baths on Energy Consumption NAKAMURA, Masatoshi; TOUDOH, Moe; EBINE, Naoyuki ...
The Journal of The Japanese Society of Balneology, Climatology and Physical Medicine,
2018/08/31, Volume:
81, Issue:
2
Journal Article
Open access
Foot baths reportedly reduce pain and improve sleeplessness. In addition, foot baths may induce vasodilation, and thereby improve blood flow, reduce swelling, induce relaxation, and increase deep ...body temperature. However, the influence of foot baths on energy metabolism and physiological indices are unclear. Therefore, the present study aimed to clarify the effects of foot baths on energy consumption and physiological indices (e.g., heart rate, tympanic temperature, and blood pressure). Nine healthy males were included in this study (age, 23.0±1.0 years; body weight, 66.5±5.6 kg; body fat percentage, 15.1±4.3%). Expired gas composition (i.e., oxygen and carbon dioxide consumption) was analyzed using the Food method in an environmentally-controlled room (room temperature 25°Cand humidity 40%). Subjects were rested in the hood during the measurement. After 30 min rest in the sitting position, a 30 min foot bath was performed, after which the subjects sat for 60 min. Expired gas composition and heart rate were measured over time, and tympanic temperature and blood pressure were measured every 15 min. The foot bath involved immersion of the knees, and the temperature of the water was maintained at 41°C. There were no significant changes in energy consumption after the foot bath, and no significant changes in heart rate, tympanic temperature, and blood pressure. Therefore, our results suggested that there were no significant energy metabolism changes after 30 min of foot bathing at 41°C.
ObjectiveAssessment of total energy expenditure (TEE) is essential for appropriate recommendations regarding dietary intake and physical activity in patients with and without diabetes mellitus (DM). ...However, few reports have focused on TEE in patients with DM, particularly in Asian countries. Therefore, we evaluated TEE in Japanese patients with DM using the doubly labeled water (DLW) method and physical activity level (PAL).Research design and methodsIn this cross-sectional observational study, we evaluated 52 patients with type 2 DM and 15 patients without DM. Free-living TEE was measured over 12–16 days by the DLW method, and PAL was calculated as TEE divided by the basal metabolic rate (BMR) as assessed by indirect calorimetry. The equivalence margin was defined as 5 kcal/kg/day.ResultsThe numbers of patients with DM treated with insulin, oral antidiabetic drugs, and diet were 18 (34.6%), 20 (38.5%), and 14 (26.9%), respectively. The mean±SD level of glycated hemoglobin was 6.9%±0.8% and 5.5%±0.3% in the DM and non-DM group, respectively (p<0.001). The mean body mass index was 23.3±3.0 and 22.7±2.1 kg/m2 in the DM and non-DM group, respectively. The mean TEE per kilogram body weight adjusted for sex and age was 36.5 kcal/kg/day and 37.5 kcal/kg/day in the DM and non-DM group, respectively, with no significant difference (mean difference, −1.0 kcal/kg/day; 95% CI -4.2 to 2.3 kcal/kg/day). The BMR tended to be higher in the DM than in the non-DM group (mean difference, 33 kcal/day; 95% CI, −15 to 80 kcal/day). The mean PAL adjusted for sex and age was 1.71 and 1.81 in the DM and non-DM group, respectively, without a significant difference (mean difference, −0.10; 95% CI −0.21 to 0.01).ConclusionTEE was comparable between Japanese patients with and without DM.Trial registration numberUMIN000023051.
Continuum issues of methodological accuracy and feasibility for energy intake (EI) assessment that are effective for determining daily energy needs in free-living older individuals are still ...requiring a systematic development of valid and inexpensive methods. Thus, the objective of this study was to evaluate the use of dietary records combined with advanced photo system (APS) camera for EI assessment over a 3-day-period against doubly labeled water (DLW) method for total energy expenditure (TEE) measurement over a 14-day-period in Japanese men n=44; age=51±14year, body mass index (BMI)23.3±2.6kg/m2 and body fat (%BF=20.8±6.2%). Body composition and physical fitness (VO2max) were determined by underwater weighing method and treadmill exercise test, respectively. Subjects were asked not to change their habitual lifestyle and were in a stable body weight over the assessment period. Mean EI of 2, 482±425kcal/day were lower (p<0.02) than mean TEE of 2, 654±361kcal/day. Reporting accuracy (reported EI/TEE×100%) was 94±16% assuming a degree of discrepancy between EI and TEE about 6±16% (-172±448kcal/day), which was significantly correlated with the physical activity level (PAL=TEE/basal metabolic rate) of r=-0.30 (p<0.05), but not with age, body weight, %BF, fat mass, fat-free mass, BMI, and VO2max. In conclusion, we may presume that the difference between EI and TEE in this study would be described neither as under-eating nor under-reporting. The magnitude of discrepancy between EI and TEE is independently predicted by PAL. The use of 3-day dietary records with APS camera is an effective technique for assessing accurately EI assuming that it can be used as a proxy tool to determine energy needs especially in this population.
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