Nakagata, T, Yamada, Y, and Naito, H. Estimating energy cost of body weight resistance exercise using a multistage exercise test. J Strength Cond Res 36(5): 1290-1296, 2022-The purpose of this study ...was to examine energy cost of body weight resistance exercises with slow movement in young men using a multistage exercise test. Fifteen men aged 21-29 years performed 3 exercises (heel-raise, squat, and push-up) at different frequencies (1, 2, 3, 4, 5, and 6 repetitions·min-1). Oxygen consumption was measured using indirect calorimetry; we then computed a simple linear regression between aerobic energy expenditure (EE) and repetition frequency. The slope coefficient in the regression represents the energy cost of those exercises; we compared the extrapolated EE for a frequency of 10 repetitions·min-1. Gross EE increased linearly with repetition frequency in all subjects (y = ax + b). Energy cost was significantly greater in the case of the push-up than in the case of the squat {squat: 0.50 ± 0.14 (95% confidence interval CI, 0.42-0.58); push-up: 0.77 ± 0.20 kcal (95% CI, 0.66-0.88); and the heel-raise elicited the lowest energy cost: 0.13 ± 0.04 kcal (95% CI, 0.11-0.15)}. Extrapolated EE at 10 repetitions·min-1 was 2.7 ± 0.5 kcal (2.3 metabolic equivalents METs), 6.3 ± 1.4 kcal (5.4 METs), and 9.2 ± 2.1 kcal (7.8 METs), respectively, according to the regression based on aerobic EE. These results will be useful for health professionals in prescribing resistance exercise programs improving muscle fitness and considering for weight management.
The National Health and Nutrition Survey consistently assesses the prevalence of exercise habits, step counts, and sedentary behaviors in a strategically selected random sample of the Japanese ...population. The aim of this study was to provide descriptive epidemiological data on the average frequency of exercise habits, daily step counts, and sedentary behavior among Japanese adults from 2003 to 2019 using the National Health and Nutrition Survey database in Japan. Data were obtained from electronically available aggregate reports on the official survey website. To prepare for the third term of Health Japan 21, scheduled to start in 2024, we summarized population-level trends in exercise habits, step counts, and sedentary behavior among Japanese adults. The results could improve our understanding of trends in physical activity with respect to age and gender, providing a basis for public health monitoring and policy-making.
The phase angle (PhA), measured via bioelectrical impedance analysis, is considered an indicator of cellular health, where higher values reflect higher cellularity, cell membrane integrity, and ...better cell function. This study aimed to examine the relationship between PhA and exercise habits or objectively measured physical activity. We included 115 people aged 32-69 years. The body composition and PhA were measured using a bioelectrical impedance device. Physical activity and sedentary behavior (SB) were assessed using a triaxial accelerometer. Exercise habits were also obtained through structured interviews, and participants were categorized into the no exercise habit (No-Ex), resistance training exercise habit (RT), or aerobic training exercise habit (AT) groups. Objectively measured moderate-to-vigorous physical activity or step count significantly correlated with PhA, independent of age, sex, height, percent body fat, body cell mass, and leg muscle power. In contrast, SB was not significant determinants of PhA. People who exercised regularly (RT or AT) had significantly higher PhA values than did those in the No-Ex group. Furthermore, the PhA was not significantly different between the RT and AT groups. Regularly engaging in exercise with moderate-to-vigorous intensity may improve or maintain muscle cellular health and muscle quality.
Many activity trackers have been developed, but steps can still be inconsistent from one monitor to another.
What are the differences and associations between the steps of 13 selected consumer-based ...and research-grade wearable devices during 1 standardized day in a metabolic chamber and 15-day free-living trials?
In total, 19 healthy adults between 21 and 50 years-old participated in this study. Participants were equipped with 12 accelerometer-based active trackers and one pedometer (Yamasa) in order to monitor the number of steps per day. The devices were worn on the waist (ActiGraph, Omron, Actimarker, Lifedorder, Withings, and Yamasa) or non-dominant wrist (Fitbit, Garmin, Misfit, EPSON, and Jawbone), or placed in a pocket (Omron CaloriScan, and TANITA). Participants performed structured activities over a 24 h period in a chamber (Standardized day), and steps were monitored in the same participants in free-living trials for 15 successive days using the same monitors (free-living days).
When the 13 monitors were ranked by their steps, waist-worn ActiGraph was located at the center (7th) of the monitors both in the Standardized (12,252 ± 598 steps/day, mean ± SD) and free-living days (9295 ± 4027 steps/day). The correlation between the accelerometer-based devices was very high (r = 0.87–0.99). However, the steps of Yamasa was significantly lower in both trials than ActiGraph. The wrist-worn accelerometers had significantly higher steps than other devices both trials (P < 0.05). The differences between ActiGraph and Actimarker or Lifecorder was less than 100 steps/day in the Standardized day, and the differences between ActiGraph and Active Style Pro was less than 100 steps/day in the free-living days. Regression equation was also performed for inter-device compatibility.
Step obtained from the wrist-worn, waist-worn, and pocket-type activity trackers were significantly different from each other but still highly correlated in free-living conditions.
•Daily step count is one of the simplest indices of daily physical activity.•We examined the difference and associations among step counts during in a metabolic chamber and 15-day free-living trials.•Steps from 13 selected consumer-based and research-grade wearable devices varied (maximum range, 2000–2500) in both trials.•But, step counts obtained from 13 wearable devices were highly correlated with each other in free-living trail.•Researchers and clinicians should be aware of the current differences.
Abstract
Objective
In Japan, while it is known that underweight women over the age of 40 years have a high risk for type 2 diabetes, there is a lack of clarity on the association between glucose ...tolerance and underweight in younger women. Accordingly, we investigate the prevalence and features of impaired glucose tolerance (IGT) in young underweight Japanese women.
Designs and Methods
In this cross-sectional study, we recruited 56 normal weight and 98 underweight young Japanese women and evaluated their glucose tolerance levels using an oral glucose tolerance test. Then, we compared the clinical characteristics associated with normal glucose tolerance (NGT) and IGT in the underweight women. Insulin secretion, whole-body insulin sensitivity, and adipose tissue insulin resistance values were measured using the insulinogenic index, whole-body insulin sensitivity index (Matsuda index), and adipose insulin resistance index (Adipo-IR), respectively. Fitness level (peak VO2) was measured using an ergometer.
Results
The prevalence of IGT was higher in the underweight women than the normal weight women (13.3% vs 1.8%). The underweight women with IGT showed a lower insulinogenic index, lower peak VO2, and Matsuda index and a higher fasting free fatty acid level and Adipo-IR than those with NGT. The whole-body composition was comparable between the NGT and IGT groups.
Conclusions
The prevalence of IGT was higher in young Japanese women with underweight than those with a normal weight. The underweight women with IGT showed impaired early-phase insulin secretion, low fitness levels, and reduced whole-body and adipose tissue insulin sensitivity levels.
This study determined the relationship between intra-individual variability in day-to-day nutrition-related lifestyle behaviors (meal timing, eating window, food intake, movement behaviors, sleep ...conditions, and body weight) and glycemic outcomes under free-living conditions in adults without type 2 diabetes.
We analyzed 104 adults without type 2 diabetes. During the 7-day measurement period, dietary intake, movement behaviors, sleep conditions, and glucose outcomes were assessed. Daily food intake was assessed using a mobile-based health application. Movement behaviors and sleep conditions were assessed using a tri-axial accelerometer. Meal timing was assessed from the participant’s daily life record. Blood glucose levels were measured continuously using a glucose monitor. Statistical analyses were conducted using a linear mixed-effects model, with mealtime, food intake, body weight, movement behaviors, and sleep conditions as fixed effects and participants as a random effect.
Dinner time and eating window were positively significantly correlated with mean (dinner time, p = 0.003; eating window, p = 0.001), standard deviation (SD; both at p < 0.001), and maximum (both at p < 0.001) blood glucose levels. Breakfast time was negatively associated with glucose outcomes (p < 0.01). Sedentary time was positively significantly associated with blood glucose SD (p = 0.040). Total sleep time was negatively significantly correlated with SD (p = 0.035) and maximum (p = 0.032) blood glucose levels. Total daily energy intake (p = 0.001), carbohydrate intake (p < 0.001), and body weight (p < 0.05) were positively associated with mean blood glucose levels.
Intra-individual variations in nutrition-related lifestyle behaviors, especially morning and evening body weight, and food intake, were associated with mean blood glucose levels, and a long sedentary time and total sleep time were associated with glucose variability. Earlier dinner times and shorter eating windows per day resulted in better glucose control.
Inter-individual variations in gut microbiota composition are observed even among healthy populations. The gut microbiota may exhibit a unique composition depending on the country of origin and race ...of individuals. To comprehensively understand the link between healthy gut microbiota and host state, it is beneficial to conduct large-scale cohort studies. The aim of the present study was to elucidate the integrated and non-redundant factors associated with gut microbiota composition within the Japanese population by 16S rRNA sequencing of fecal samples and questionnaire-based covariate analysis.
A total of 1596 healthy Japanese individuals participated in this study via two independent cohorts, NIBIOHN cohort (n = 954) and MORINAGA cohort (n = 642). Gut microbiota composition was described and the interaction of these microorganisms with metadata parameters such as anthropometric measurements, bowel habits, medical history, and lifestyle were obtained. Thirteen genera, including Alistipes, Anaerostipes, Bacteroides, Bifidobacterium, Blautia, Eubacterium halli group, Faecalibacterium, Fusicatenibacter, Lachnoclostridium, Parabacteroides, Prevotella_9, Roseburia, and Subdoligranulum were predominant among the two cohorts. On the basis of univariate analysis for overall microbiome variation, 18 matching variables exhibited significant association in both cohorts. A stepwise redundancy analysis revealed that there were four common covariates, Bristol Stool Scale (BSS) scores, gender, age, and defecation frequency, displaying non-redundant association with gut microbial variance.
We conducted a comprehensive analysis of gut microbiota in healthy Japanese individuals, based on two independent cohorts, and obtained reliable evidence that questionnaire-based covariates such as frequency of bowel movement and specific dietary habit affects the microbial composition of the gut. To our knowledge, this was the first study to investigate integrated and non-redundant factors associated with gut microbiota among Japanese populations.
Previous cross-sectional studies have indicated that low relative appendicular lean mass (ALM) against body weight (divided by body weight, ALM/Wt, or divided by body mass index, ALM/BMI) was ...negatively associated with metabolic syndrome (MetS). Conversely, previous cross-sectional studies have indicated that the absolute ALM or ALM divided by squared height (ALM/Ht.sup.2) were positively associated with MetS. The aim of this longitudinal study was to investigate the association between low absolute or relative skeletal muscle mass, leg muscle power, or percent body fat and the development of MetS in Japanese women in a 7-y prospective study. The study participants included 346 Japanese women aged 26 to 85 years. The participants were divided into low and high groups based on the median values of ALM/Wt, ALM/BMI, ALM/Ht.sup.2, absolute ALM, or leg power. The longitudinal relationship between ALM indices or leg power and MetS development was examined using Kaplan-Meier curves and Cox regression models (average follow-up duration 7 years, range 1 to 10 years). During follow-up, 24 participants developed MetS. MetS incidence was higher in the low ALM/Wt group than the high ALM/Wt group even after controlling for age, obesity, waist circumference, family history of diabetes, smoking, and physical activity adjusted hazard ratio = 5.60 (95% CI; 1.04-30.0). In contrast, MetS incidence was lower in the low ALM/Ht.sup.2 group than the high ALM/Ht.sup.2 group adjusted hazard ratio = 10.6 (95%CI; 1.27-89.1). MetS incidence was not significantly different between the low and high ALM/BMI, absolute ALM, and leg power groups. Both ALM/Ht.sup.2 and ALM/Wt were not significant predictive variables for MetS development when fat mass or percent body fat was taken into account in the Cox model. At the very least, the results of this study underscore the importance of body composition measurements in that percent body fat, but not ALM, is associated with MetS development.
Escherichia coli harboring polyketide synthase (pks
E. coli) has been suggested to contribute to colorectal cancer development. Physical activity is strongly associated with lower colorectal cancer ...risks, but its effects on pks
E. coli remain unclear. The aim of this study was to investigate the association between pks
E. coli prevalence and physical activity. A cross-sectional study was conducted on 222 Japanese adults (27-79-years-old, 73.9% female). Triaxial accelerometers were used to measure light-intensity physical activity, moderate-to-vigorous intensity physical activity, the physical activity level, step-count, and time spent inactive. Fecal samples collected from participants were used to determine the prevalence of pks
E. coli. Multivariate logistic regression analysis and restricted cubic spline curves were used to examine the association between pks
E. coli prevalence and physical activity. The prevalence of pks
E. coli was 26.6% (59/222 participants). The adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for the highest tertile with reference to the lowest tertile of physical activity variables were as follows: light-intensity physical activity (OR 0.63; 95% CI 0.26-1.5), moderate-to-vigorous intensity physical activity (OR 0.85; 95% CI 0.39-1.87), physical activity level (OR 0.69; 95% CI 0.32-1.51), step-count (OR 0.92; 95% CI 0.42-2.00) and time spent inactive (OR 1.30; 95% CI 0.58-2.93). No significant dose-response relationship was found between all physical activity variables and pks
E. coli prevalence. Our findings did not suggest that physical activity has beneficial effects on the prevalence of pks
E. coli. Longitudinal studies targeting a large population are needed to clarify this association.
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