Effects of energy loads on energy and nutrient absorption rates and gut microbiome in humans: A randomized crossover trial.

OBJECTIVE: This study aimed to determine the effects of different energy loads on the gut microbiota composition and the rates of energy and nutrient excretion via feces and urine. METHODS: A randomized crossover dietary intervention study was conducted with three dietary conditions: overfeeding (OF), control (CON), and underfeeding (UF). Ten healthy men were subjected to each condition for 8 days (4 days and 3 nights in nonlaboratory and laboratory settings each). The effects of dietary conditions on energy excretion rates via feces and urine were assessed using a bomb calorimeter. RESULTS: Short-term energy loads dynamically altered the gut microbiota at the α-diversity (Shannon index), phylum, and genus levels (p < 0.05). Energy excretion rates via urine and urine plus feces decreased under OF more than under CON (urine -0.7%; p < 0.001, urine plus feces -1.9%; p = 0.049) and UF (urine -1.0%; p < 0.001, urine plus feces -2.1%; p = 0.031). However, energy excretion rates via feces did not differ between conditions. CONCLUSIONS: Although short-term overfeeding dynamically altered the gut microbiota composition, the energy excretion rate via feces was unaffected. Energy excretion rates via urine and urine plus feces were lower under OF than under CON and UF conditions.

Effects of sleep restriction on food intake and appetite under free-living conditions: A randomized crossover trial.

To investigate changes in subjective psychological factors and dietary intake during sleep restriction, we carried out a randomized crossover trial with a 3-day sleep restriction condition (SR; 5 h of sleep) and control sleep condition (CS; 8 h of sleep). Days 3 and 4 involved free-living and laboratory (in the morning) conditions, respectively. Subjective psychological factors (hunger, appetite, desire for sweets and fatty foods, sleepiness, and fatigue) were assessed using a 0.0-10.0 cm visual analog scale (VAS) every hour throughout the day on day 3, and at 8:00 a.m. on day 4. Dietary intake on day 3 was assessed on the basis of the food purchased and eaten. Fasting blood samples were collected at 8:00 a.m. on day 4. Dietary intake during the ad libitum breakfast was assessed on day 4. The participants were 13 women and 11 men (mean age, 21.4 ± 1.0 years; mean body mass index, 19.8 ± 1.7 kg/m2). The areas under the curve 0-16 h after waking for hunger, desire for fatty foods, sleepiness, and fatigue were higher in the SR than CS on day 3 (P < 0.05). Energy and carbohydrate intakes from snacks (daytime and nighttime) on day 3 were higher in the SR than CS (P < 0.05) but total dietary intake on day 3 was not different between the conditions (P > 0.05). The 2-arachidonoylglycerol level was different between the conditions (P < 0.05), but was not associated with sweet taste preference, dietary intake, or the active ghrelin level on day 4 (P > 0.05). In conclusion, ratings for subjective psychological factors and energy and carbohydrate intakes from snacks increased in association with sleep restriction under free-living conditions.

Delayed Eating Schedule Raises Mean Glucose Levels in Young Adult Males: a Randomized Controlled Cross-Over Trial.

BACKGROUND: Misalignment of meals to the biological clock may cause adverse effects on glucose metabolism. However, the effects of repeated different eating schedules (early compared with late) on glucose concentration throughout the day are poorly understood. OBJECTIVES: We examined the effects of different eating schedules on the 24-h glucose response using a continuous glucose monitor (CGM). METHODS: Eight young adult males (age, 20.9 ± 3.4 y; body mass index: 21.3 ± 1.8 kg/m2) each followed 2 different eating schedules (early [08:30, 13:30, and 19:30] and late [12:00, 17:00, and 23:00]) in random order. These diet interventions were conducted for 8 d, with an experimental period of 3 d and 2 nights (from dinner on day 7) after 7 d of free living. The 3 meals in each intervention were nutritionally equivalent (55% carbohydrate, 15% protein, and 30% fat). The 24-h mean interstitial glucose concentration on day 8 was obtained under controlled conditions using the CGM (primary outcome). These concentrations were compared among the following 3 schedules using Dunnett's test, with the early eating schedule as reference (1 compared with 2 and 1 compared with 3): 1) early eating schedule (control), 2) late eating schedule according to the clock time (08:00 on day 8 to 08:00 on day 9), and 3) late eating schedule according to the time elapsed since the first meal for 24 h. RESULTS: The 24-h mean ± SD interstitial glucose concentrations when participants followed the late eating schedule were higher than those when they followed the early eating schedule in terms of clock time (91.2 ± 2.9 compared with 99.2 ± 4.6 mg/dL, P = 0.003) and time elapsed (91.2 ± 2.9 compared with 98.3 ± 3.8 mg/dL, P < 0.001). CONCLUSIONS: A late eating schedule increases the mean 24-h interstitial glucose concentration in young adult males. This insight will have useful implications in determining meal timings, especially for those with conditions such as diabetes.

Relationship between intra-individual variability in nutrition-related lifestyle behaviors and blood glucose outcomes under free-living conditions in adults without type 2 diabetes.

AIMS: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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.

Long-term Effects of the Use of a Step Count-Specific Smartphone App on Physical Activity and Weight Loss: Randomized Controlled Clinical Trial.

BACKGROUND: Some studies on weight loss promotion using smartphone apps have shown a weight loss effect but not an increase in physical activity. However, the long-term effects of smartphone apps on weight loss and increasing physical activity have not been rigorously examined to date. OBJECTIVE: The aim of this study was to assess whether the use of a smartphone app will increase physical activity and reduce body weight. METHODS: In this parallel randomized clinical trial, participants recruited between April 2018 and June 2019 were randomized in equal proportions to a smartphone app group (n=55) or a control group (n=54). The intention-to-treat approach was used to analyze the data from December 2019 through November 2021. Before the intervention, an hour-long lecture on weight loss instruction and increasing physical activity was conducted once for both groups. Participants in both groups were instructed to weigh themselves immediately after waking up at least once daily from the start of the intervention. Monthly emails were sent advising the participants in both groups on how to lose weight and increase physical activity in order to maintain or increase motivation. Participants in the smartphone app group were instructed to open the app at least once a day to check their step count and rank. The primary outcome was daily accelerometer-measured physical activity (step count) and the secondary outcome was body weight. Since there was a significant difference in the wear time of the accelerometer depending on the intervention period (P<.001), the number of steps and moderate-to-vigorous physical activity were also evaluated per wear time. RESULTS: The mean age of the 109 participants in this study was 47 (SD 8) years. At baseline, the mean daily total steps were 7259 (SD 3256) steps per day for the smartphone app group and 8243 (SD 2815) steps per day for the control group. The difference in the step count per wear time between preintervention and postintervention was significantly different between the app group and the control group (average difference [95% CI], 65 [30 to 101] steps per hour vs -9 [-56 to 39] steps per hour; P=.042). The weight loss was -2.2 kg (SD -3.1%) in the smartphone app group and -2.2 kg (SD -3.1%) in the control group, with no significant difference between the groups. In addition, when divided into weekdays (Monday through Friday) and weekends (Saturday and Sunday), there was a significant interaction between step counts (P=.004) and MVPA (P=.003) during the intervention, with the app group showing higher interaction on weekends than the control group. CONCLUSIONS: In this trial, the group with the smartphone app intervention showed increased physical activity, especially on weekends. However, this increased physical activity did not lead to increased weight loss. TRIAL REGISTRATION: University Hospital Medical Information Network UMIN000033397; https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000037956.

Association between skeletal muscle mass or percent body fat and metabolic syndrome development in Japanese women: A 7-year prospective study.

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/Ht2) 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/Ht2, 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/Ht2 group than the high ALM/Ht2 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/Ht2 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.

Determination of Optimal Daily Magnesium Intake among Physically Active People: A Scoping Review.

Little is known about the optimal daily magnesium (Mg) intake for individuals with high levels of physical activity. The aim of this study was to clarify the optimal dietary Mg intake for people with high levels of physical activity in a scoping review. In this review, we searched MEDLINE and Japan Medical Abstracts Society for studies published up to May 31, 2020. We conducted two searches, one for studies using gold standard measurement methods such as the balance method and factorial calculation (Search 1), and the other for studies using estimation from daily food intake (Search 2). We also performed a meta-analysis of studies that compared the Mg intake among physically active people with the Mg intake among controls. After the primary and secondary screening, 31 studies were included in the final review. All of the included studies examined professional or recreational athletes. We found no studies that examined the optimal intake of Mg using gold standard measurement methods. The Mg intake among physically active individuals was below the recommended dietary allowance in most studies. In five studies that conducted meta-analyses, physically active individuals had significantly higher intakes of Mg than controls, although these levels were still below the recommended dietary allowance. The present review revealed that evidence regarding the optimal daily magnesium intake is currently scarce, and further studies are needed.

An Earlier First Meal Timing Associates with Weight Loss Effectiveness in A 12-Week Weight Loss Support Program.

Recent studies have reported that meal timing may play an important role in weight regulation, however it is unknown whether the timing of meals is related to the amount of weight loss. This study aimed to examine the relationship between indices of meal timing and weight loss during weight loss intervention in adults. A 12-week weight loss support program was conducted for 97 adults (age: 47.6 ± 8.3 years, BMI: 25.4 ± 3.7 kg/m2). After the program, body weight decreased by -3.0 ± 2.7%. Only the start of the eating window was positively correlated with the weight change rate in both sexes (men: r = 0.321, p = 0.022; women: r = 0.360, p = 0.014). The participants were divided into two groups based on the start of the eating window as follows: the early group (6:48 ± 0:21 AM) and the late group (8:11 ± 1:05 AM). The weight loss rate in the early group was significantly higher (-3.8 ± 2.7%) than that in the late group (-2.2 ± 2.5%). The present results showed that the start of the early eating window was associated with weight loss and suggested paying attention to meal timing when doing weight loss.

Doubly labelled water-calibration approach attenuates the underestimation of energy intake calculated from self-reported dietary assessment data in Japanese older adults.

OBJECTIVE: Self-reported energy intake (EI) estimation may incur systematic errors that could be attenuated through biomarker calibration. We aimed to confirm whether calibrated EI was comparable to total energy expenditure (TEE) measured using the doubly labelled water (DLW) technique. DESIGN: Cross-sectional study. SETTING: General older population from the Kyoto-Kameoka Study, Japan. PARTICIPANTS: This study included sub- and main cohorts of 72 and 8058 participants aged≥ 65 years, respectively. EI was evaluated using a validated FFQ, and calibrated EI was obtained using a previously developed equation based on the DLW method. TEE was considered representative of true EI and also measured using the DLW method. We used a Wilcoxon signed-rank test and correlation analysis to compare the uncalibrated and calibrated EI with TEE. RESULTS: In the sub-cohort, the median TEE, uncalibrated EI and calibrated EI were 8559 kJ, 7088 kJ and 9269 kJ, respectively. The uncalibrated EI was significantly lower than the TEE (median difference = -1847 kJ; interquartile range (IQR): -2785 to -1096), although the calibrated EI was not (median difference = 463 kJ; IQR: -330 to 1541). The uncalibrated (r = 0·275) and calibrated EI (r = 0·517) significantly correlated with TEE. The reproducibility was higher for calibrated EI (interclass correlation coefficient (ICC) = 0·982) than for uncalibrated EI (ICC = 0·637). Similar findings were observed when stratifying the sample by sex. For medians, uncalibrated EI was lower (about 17 %) than calibrated EI in the main cohort. CONCLUSIONS: Biomarker calibration may improve the accuracy of self-reported dietary intake estimation.

Eating Dinner Early Improves 24-h Blood Glucose Levels and Boosts Lipid Metabolism after Breakfast the Next Day: A Randomized Cross-Over Trial.

Aim: To examine whether mild early time-restricted eating (eating dinner at 18:00 vs. at 21:00) improves 24-h blood glucose levels and postprandial lipid metabolism in healthy adults. Methods: Twelve participants (2 males and 10 females) were included in the study. In this 3-day (until the morning of day 3) randomized crossover study, two different conditions were tested: eating a late dinner (at 21:00) or an early dinner (at 18:00). During the experimental period, blood glucose levels were evaluated by each participant wearing a continuous blood glucose measuring device. Metabolic measurements were performed using the indirect calorimetry method on the morning of day 3. The study was conducted over three days; day 1 was excluded from the analysis to adjust for the effects of the previous day's meal, and only data from the mornings of days 2 and 3 were used for the analysis. Results: Significant differences were observed in mean 24-h blood glucose levels on day 2 between the two groups (p = 0.034). There was a significant decrease in the postprandial respiratory quotient 30 min and 60 min after breakfast on day 3 in the early dinner group compared with the late dinner group (p < 0.05). Conclusion: Despite a difference of only 3 h, eating dinner early (at 18:00) has a positive effect on blood glucose level fluctuation and substrate oxidation compared with eating dinner late (at 21:00).

The effects of breaking sedentary time with different intensity exercise bouts on energy metabolism: A randomized cross-over controlled trial.

BACKGROUND AND AIMS: Breaking up sedentary periods, particularly with light activity, increases total energy expenditure (EE), and helps provide better glycemic control. However, the effects of activities of various intensities to interrupt prolonged sedentary time are unclear. The purpose of the present study was to examine potential differences in glycemic control and EE from breaking up sedentary time with short exercise bouts of different intensities. METHODS AND RESULTS: Nine overweight/obesity young men underwent whole body indirect calorimetry at 19:00 on day 1 and stayed overnight. After awakening on day 2, they performed short duration jogging every 30 min over 8 h (16-time bouts in total) under 3 different conditions with the same running distance: (1) lactate threshold (LT) for 2 min, (2) 60% LT for 200 s, and (3) onset of blood lactate accumulation (OBLA) for 75 s. The 24-h EE and interstitial glucose concentration (from 8:00 to 19:00 on day 2) was continuously measured throughout the trials. The standard deviation during intervention and indexes of postprandial of the interstitial glucose concentration was significantly lower at LT and OBLA than at 60% LT (p < 0.05). The 24-h EE was not significantly different among conditions, but EE at OBLA during intervention was slightly but significantly higher than at 60% LT and LT. CONCLUSION: Breaking up sedentary time with short-duration jogging at LT and with OBLA intensities may have better glycemic control and increased use of carbohydrate as a fuel, while short-duration a jogging at OBLA intensity may increase EE. TRIAL REGISTRATION: UMIN000041361.

Changes in Season Affect Body Weight, Physical Activity, Food Intake, and Sleep in Female College Students: A Preliminary Study.

The current study examined how body weight and lifestyle fluctuate between spring, autumn, and winter in Japanese female college students and whether weight gain is associated with changes in physical activity, food intake, and sleep. We measured body weight and lifestyle factors in 31 participants from May 2017 to January 2018. Weight was measured daily in participants' homes. Physical activity and sleep were measured for three weeks in three seasons using two accelerometers. Food intake was assessed using a validated food frequency questionnaire. Body weight significantly decreased in autumn compared with spring (p < 0.001). Body weight in winter tended to increase compared with autumn (p = 0.052). Step counts and energy intake were significantly different between seasons (p < 0.05). Total time in bed was not significantly different between seasons. In comparisons of changes in lifestyle patterns from autumn to winter between the weight gain (≥0.5 kg) and weight maintenance groups, seasonal changes in lifestyle factors were not significantly different between groups (p > 0.05). The results indicated that body weight and lifestyle were affected by seasonal variability in female college students, but no significant relationships existed between seasonal weight gain and changes in lifestyle patterns.

Acute Sleep Curtailment Increases Sweet Taste Preference, Appetite and Food Intake in Healthy Young Adults: A Randomized Crossover Trial.

This study aimed to examine the effect of acute sleep curtailment on sweet taste preference, appetite and food intake, and the correlation between food intake and sweet taste preference or active ghrelin using a randomized crossover design (5 h sleep curtailment vs. 8 h control). Twenty-four participants (11 men) aged 21.4 ± 1.0 years, with BMI 19.8 ± 1.7 kg/m2, who habitually slept 5 h/night or more experienced interventions lasting three consecutive nights. Participants came into the laboratory for testing on day 4. Fasting blood tests were conducted at 8:00 a.m. to measure active ghrelin and leptin levels. Sweet taste preference was assessed by presenting five different concentration sucrose solutions at 9:00 a.m. Ad libitum intake at breakfast was assessed for 30 min from 9:30 a.m. Sweet taste preference was higher following sleep curtailment than control. Active ghrelin was likewise higher following sleep curtailment than control. Leptin did not differ between conditions. Energy intake was higher following sleep curtailment than control, being derived primarily from carbohydrates. However, sweet taste preference and active ghrelin did not correlate with energy intake. These results suggest that acute consecutive sleep curtailment increases sweet taste preference, active ghrelin, and energy intake in healthy young adults.

Physical Activity and/or High Protein Intake Maintains Fat-Free Mass in Older People with Mild Disability; the Fukuoka Island City Study: A Cross-Sectional Study.

Body composition changes with age, with fat mass (FM) increasing and fat-free mass (FFM) decreasing. Higher physical activity and high or adequate protein intake are thought to be beneficial in preventing the loss of skeletal muscle mass in the elderly. We aimed to investigate the relationships between physical activity, protein intake, and FFM in older people with mild disability. Total energy expenditure (TEE) under free-living conditions was assessed using the doubly-labelled water (DLW) method, and physical activity was measured using a triaxial accelerometer. Dietary intake was assessed using a self-recorded food intake diary during the DLW period. Percent FFM was significantly positively correlated with protein intake and physical activity level (PAL) after adjustment for age and sex (protein intake r = 0.652, p < 0.001, PAL r = 0.345, p = 0.011). In multiple linear regression analysis, when PAL, moderate-to-vigorous physical activity (MVPA), or protein intake were included, 31%, 32%, and 55%, respectively, of the variation in %FFM was explained. Moreover, the addition of both PAL/MVPA and protein intake explained 61%/60%, respectively, of the variation in %FFM. Either protein intake above the currently recommended level or higher levels of physical activity would be beneficial for the maintenance of high %FFM.

Association between breakfast skipping and postprandial hyperglycaemia after lunch in healthy young individuals.

Breakfast skipping has become an increasing trend in the modern lifestyle and may play a role in obesity and type 2 diabetes. In our previous studies in healthy young individuals, a single incident of breakfast skipping increased the overall 24-h blood glucose and elevated the postprandial glycaemic response after lunch; however, it was difficult to determine whether this response was due to breakfast omission or the extra energy (i.e. lunch plus breakfast contents). The present study aimed to assess the postprandial glycaemic response and to measure their hormone levels when healthy young individuals had identical lunch and dinner, and the 24-h average blood glucose as a secondary outcome. Nine healthy young men (19-24 years) participated in two-meal trials: with breakfast (three-meal condition) or without breakfast (breakfast skipping condition). During the meals, each individual's blood glucose was continuously monitored. Skipping breakfast resulted in a significantly higher (P < 0·001) glycaemic response after lunch as compared with the glycaemic response after an identical lunch when breakfast was consumed. Despite the difference in the total energy intake, the 24-h average blood glucose was similar between the two-meal conditions (P = 0·179). Plasma NEFA level was significantly higher (P < 0·05) after lunch when breakfast was omitted, and NEFA level positively correlated with the postprandial glycaemic response (r 0·631, P < 0·01). In conclusion, a single incident of breakfast skipping increases postprandial hyperglycaemia, and associated impaired insulin response, after lunch. The present study showed that skipping breakfast influences glucose regulation even in healthy young individuals.

Assessment of energy expenditure using doubly labeled water, physical activity by accelerometer and reported dietary intake in Japanese men with type 2 diabetes: A preliminary study.

The aim of the present study was to determine the total energy expenditure, physical activity and dietary intake of men with type 2 diabetes mellitus and control participants without type 2 diabetes mellitus who were matched for age and body mass index. The participants in the present study were 12 well-controlled type 2 diabetes mellitus patients and 10 controls, aged 40-75 years, with a body mass index <30 kg/m2 . Total energy expenditure under free-living conditions was assessed using the doubly labeled water method, and physical activity was measured using a triaxial accelerometer. Dietary intake was assessed using a self-recorded food intake diary during the measurement period. Participants were instructed to record their dietary intake over 3 days, including 2 weekdays. Total energy expenditure was not significantly different between the groups (P = 0.153), nor were energy (P = 0.969) or macronutrient intakes. In conclusion, when age and body mass index are matched, total energy expenditure and self-reported energy intake are not significantly different between type 2 diabetes mellitus patients and healthy controls.

The effects of rapid weight loss and 3-h recovery on energy expenditure, carbohydrate, and fat oxidation in boxing athletes.

BACKGROUND: Boxers need to consider energy metabolism during rapid weight loss (RWL) followed by rapid weight regain. We examined the effects of RWL and a 3-h acute weight recovery on energy expenditure, carbohydrate oxidation, and fat oxidation in boxing athletes. METHODS: The analysis was based on the data of seven healthy young male athletes who underwent rapid weight loss followed by acute weight recovery. Energy expenditure was evaluated at three time points: one week prior to the acute weight loss (baseline); after the 1-week weight loss period; after a 3-h acute weight recovery period. This three-component model was used to estimate body composition. Sleeping metabolic rate and diet-induced thermogenesis (DIT) were measured in an indirect calorimetry room over a 17-h period. After an overnight fast, a prescribed meal was provided and the DIT was measured over a 3-h period. This was followed by a three-step treadmill running protocol. RESULTS: Weight loss produced a significant decrease in fat mass, fat free mass, and body mass, with recovery of body mass within 3 h (1.7±0.3 kg). Postprandial carbohydrate oxidation was significantly lower during the recovery period than at baseline, while fat oxidation was higher, although there was no change in the DIT. CONCLUSIONS: RWL, followed by a short-term of acute weight recovery, produces an increase in fat oxidation and a decrease in carbohydrate oxidation, with the increase in fat oxidation being maintained through an overnight sleep period, as well as in the postprandial and exercise periods.

Association between echo intensity and attenuation of skeletal muscle in young and older adults: a comparison between ultrasonography and computed tomography.

BACKGROUND: Skeletal muscle experiences both quantitative and qualitative changes with aging. Echo intensity (EI) of the skeletal muscle obtained by ultrasonography (US) has been considered to reflect muscle quality. This technique is noninvasive, easily accessible, and is relatively inexpensive than that of other imaging techniques such as computed tomography (CT). Previous studies have reported that EI is related to several physical performances. However, few studies have investigated the validity of EI against other imaging methods in case of imaging of the skeletal muscle. We compared quantitative and qualitative indices evaluated by the US and CT imaging systems to strengthen their validity. PARTICIPANTS AND METHODS: A total of 40 adults participated in this study: 19 young (10 men and 9 women; their mean (±SD) age was 22.7±1.5 years) and 21 older adults (13 men and 8 women; their mean age was 70.6±4.8 years). Both thighs of each participant were evaluated using US and CT imaging systems. RESULTS: With respect to the US indices, the young group had significantly higher muscle thickness (MT) of the front thigh (P<0.001) and lower EI (P=0.001) than that of the older group. With respect to the CT indices, the cross-sectional area (CSA) and mean CT value (Hounsfield unit [HU]) of the muscle were found to be significantly higher in the young group (P<0.001) than that of the older group, whereas the percentage of low-density muscle area (%LDMA) was found to be significantly higher in the older group (P<0.001) than that of the young group. A significant, strong, and positive correlation was observed between MT and CSA, which reflects the muscle quantity (r=0.774; P<0.001). With respect to the indices of muscle quality, we found significant and moderate correlations between EI and CT values (r=-0.502; P<0.001) and between EI and %LDMA (r=0.441; P<0.001). However, these correlations were found to be decreased in the older group [between EI and CT value (r=-0.363; P=0.018) and between EI and %LDMA (r=0.257; P=0.100)]. CONCLUSION: Results of this study indicate that the EI is moderately associated with muscle attenuation as assessed by CT, which means that higher EI at least partly reflects intramuscular lipid infiltration.

Effect of diurnal variations in the carbohydrate and fat composition of meals on postprandial glycemic response in healthy adults: a novel insight for the second-meal phenomenon.

Background: Meals, particularly carbohydrate intake, determine diurnal blood glucose (BG) excursions. However, the effect of meals with variable carbohydrate content on diurnal BG excursions remains poorly understood, despite routine consumption of meals that vary daily. Objective: The aim of this study was to verify our hypothesis that glycemic response is elevated when a meal with a higher carbohydrate content follows a meal with a lower carbohydrate content. Design: This was a secondary analysis of a study whose primary endpoint was energy metabolism (e.g., energy expenditure and substrate oxidation). This crossover study was designed to test BG responses to 3 types of meals with different macronutrient contents [regular meals (R), meals with a high-carbohydrate breakfast (CB), and meals with a high-fat breakfast (FB)] using a continuous glucose monitoring system. The R test included 3 meals/d with the same macronutrient composition; the CB test, a high-carbohydrate meal at breakfast, a high-fat meal at lunch, and a high-carbohydrate meal at dinner; and the FB test, a high-fat meal at breakfast, a high-carbohydrate meal at lunch, and a high-carbohydrate meal at dinner. Each test had similar daily macronutrient compositions, except CB and FB had larger variations in carbohydrate content than R. Fourteen healthy young men were tested in random order and underwent whole-body indirect calorimetry. Results: Daily peak BG concentrations were higher for the CB (mean ± SD: 143.9 ± 25.3 mg/dL) and FB (140.2 ± 24.8 mg/dL) conditions than for the R condition (127.5 ± 15.7 mg/dL). Postprandial BG peaks after a high-carbohydrate meal were ∼20 mg/dL higher when a previous meal was relatively high-fat than when not high-fat (P < 0.05 for all). A multiple regression analysis indicated that the postprandial glycemic response was negatively associated with the preprandial respiratory quotient. Conclusions: Our findings indicate that switching from high-fat to high-carbohydrate meals contributes to larger postprandial BG excursions, along with alterations in prioritization of carbohydrate utilization. This study was registered at the UMIN Clinical Trials Registry as UMIN000028895.

Sex Difference in the Association Between Protein Intake and Frailty: Assessed Using the Kihon Checklist Indexes Among Older Adults.

BACKGROUND: Dietary protein intake is inversely associated with physical frailty risk. However, it is unknown whether an association exists between dietary protein intake and comprehensive frailty. OBJECTIVE: To evaluate the association between protein intake and comprehensive frailty in older Japanese adults. DESIGN, SETTING AND PARTICIPANTS: This cross-sectional study included 5638 Japanese participants (2707 men and 2931 women) aged ≥65 years from Kameoka City, Kyoto, Japan. MEASUREMENTS: Dietary intake was estimated using a validated self-administered food frequency questionnaire. Comprehensive frailty was assessed using a 25-item Kihon Checklist (KCL), which comprised instrumental activities of daily living, mobility disability, malnutrition, oral or eating function, socialization and housebound, cognitive function, and depression domains. A KCL score of 4 to 6 was defined as prefrailty, and ≥7 as frailty. RESULTS: In women, but not in men, protein intake showed a lower prevalence for prefrailty (Q1-Q4, 40.2%, 34.3%, 34.3%, and 36.0%). Higher protein intake was associated with lower prevalence of frailty both in men (32.5%, 28.4%, 28.3%, and 27.3%) and women (35.7%, 31.4%, 27.6%, and 28.2%). Moreover, higher dietary protein intake decreased the odds ratio (OR) for frailty after adjustment for potential confounding factors in both men (OR for highest vs lowest quartile, 0.62; 95% CI, 0.43-0.89; P for trend = 0.016) and women (OR 0.64; 95% CI, 0.45-0.91; P for trend = 0.017). CONCLUSIONS/IMPLICATIONS: The higher dietary protein intake may be inversely associated with the prevalence of comprehensive frailty in Japanese men and women. Future studies are needed to examine associations of dietary protein intake within KCL domains.