<jats:p>[Purpose] This study aimed to evaluate the differences between predicted resting energy expenditure (REE), using fat-free mass (FFM)-based prediction equations, and measured REE in Korean male collegiate soccer players.[Methods] Fifteen male collegiate soccer players (18-21 years) participated in this study. The REE measurements were conducted using the Douglas bag method. Body composition was measured by dual-energy X-ray absorptiometry (DXA). The differences between the measured REE and predicted REE, using the five FFM-based REE equations, were analyzed using the t-test, calculation of errors, regression analysis, and the Bland-Altman method.[Results] The Cunningham (1980) and ten Haaf and Weijs (2014) equations showed significantly overestimated REE (1,808 ± 99 kcal/d, &lt;i&gt;p&lt;/i&gt; &lt;0.01; 1,838 ± 103 kcal/d, &lt;i&gt;p&lt;/i&gt; &lt;0.01; respectively), but the Owen (1988), Taguchi (2011), and Kim (2015) equations’ estimations were not significantly different from the measured REE (1,589 ± 106 kcal/d, 1,640 ± 124 kcal/d, and 1,622 ± 68 kcal/d, respectively). The Taguchi equation gave the best prediction of REE with the lowest constant error (-6 ± 125) and effect size (-0.05), and a non-significant proportional bias (&lt;i&gt;p&lt;/i&gt; = 0.95).[Conclusion] The Taguchi equation is recommended for predicting REE in Korean collegiate soccer players. The selection process of a REE-prediction equation must take into consideration the target population’s characteristics. Future studies are recommended to evaluate the validity of the different FFM-based REE-prediction equations in various Korean athletes.</jats:p>

[Purpose] The current study aimed to determine the association between serum uncarboxylated osteocalcin (ucOC) levels and dietary vitamin K intake in female Japanese athletes.[Methods] The nutritional profile and food group intake of 52 Japanese female athletes were investigated using a digital photographic method with data obtained from 3-day dietary records. The food groups were categorized into 18 groups in line with the standard tables of food composition in Japan. Fasting blood samples were collected for serum ucOC levels, and dual-energy X-ray absorptiometry (DXA) evaluated body composition and bone parameters.[Results] The results showed that dietary vitamin K intake level was 235 ± 148 µg/day, and approximately 70% (n = 36) of participants consumed more than the adequate intake (AI) level, based on the Dietary Reference Intakes for Japanese females aged 18–29. Serum ucOC levels were negatively associated with daily vitamin K intake (r = −0.388, &lt;i&gt;P&lt;/i&gt; = 0.004) and calcium (r = −0.596, &lt;i&gt;P&lt;/i&gt; = 0.004) after adjusting for energy intake.[Conclusion] Our study revealed that serum ucOC levels were negatively associated with dietary vitamin K intake in female Japanese athletes. Serum ucOC levels reflected dietary vitamin K intake in female athletes. In summary, female athletes consume more vitamin K than the general population to maintain bone health. Furthermore, our results indicated that serum ucOC levels might be linked to dietary calcium intake.

Daily muscle glycogen recovery after training is important for athletes. Few studies have reported a continuous change in muscle glycogen for 24 h. We aimed to investigate the changes in carbohydrate intake amount on muscle glycogen recovery for 24 h after exercise using 13C-magnetic resonance spectroscopy (13C-MRS). In this randomized crossover study, eight male participants underwent prolonged high-intensity exercise, and then consumed one of the three carbohydrate meals (5 g/kg body mass (BM)/d, 7 g/kg BM/d, or 10 g/kg BM/d). Glycogen content of thigh muscle was measured using 13C-MRS before, immediately after, and 4 h, 12 h and 24 h after exercise. Muscle glycogen concentration decreased to 29.9 ± 15.9% by exercise. Muscle glycogen recovery 4–12 h after exercise for the 5 g/kg group was significantly lower compared to those for 7 g/kg and 10 g/kg groups (p &lt; 0.05). Muscle glycogen concentration after 24 h recovered to the pre-exercise levels for 7 g/kg and 10 g/kg groups; however, there was a significant difference for the 5 g/kg group (p &lt; 0.05). These results suggest that carbohydrate intake of 5 g/kg BM/d is insufficient for Japanese athletes to recover muscle glycogen stores 24 h after completing a long-term high-intensity exercise.

<title>Abstract</title>The use of dual-energy X-ray absorptiometry (DXA) may be invalid for assessing athletes with larger bodies, larger lean body mass, and thicker trunks. This study compared the athletes' visceral adipose tissue (VAT) assessed using DXA and magnetic resonance imaging (MRI). Eighty-two Japanese male collegiate athletes from 18 sports participated in this study. VAT was assessed using the dual-energy scan that coincided with the 4th lumbar vertebra. The sum of eight magnetic resonance slices corresponding to the region of the dual-energy scan was used for comparison. The VAT volume was higher with the dual-energy scan than with MRI (difference: 35 cm3, p&lt;0.01). A significant correlation was noted between the volumes measured using both modalities (r=0.88, p&lt;0.01). Magnetic resonance-derived volumes less than 600 cm3 showed a stronger significant correlation with dual-energy-derived volumes. However, magnetic resonance-derived VAT volumes exceeding 600 cm3 were not significantly correlated with dual-energy-derived volumes. In conclusion, VAT volumes derived from DXA were larger and significantly correlated with those derived from MRI across a wide range of values. Methods using DXA for assessing the visceral fat volume may require adjustment to estimate abdominal visceral fat volume in athletes, with care taken when using such methods for heavyweight athletes.

Metabolic suppression due to relative energy deficiency can cause various physiological impairments in athletes. The purpose of this study was to evaluate within-day energy balance (WDEB) and the ratio between measured and predicted resting energy expenditure (REEratio) and to investigate the relationships between the markers of metabolic suppression. Ten male collegiate soccer players completed a 7-day food diary, physical activity, and heart rate records during the training and rest days. Energy intake (EI) and energy expenditure (EE) were analyzed to evaluate WDEB components. Body composition was measured using dual-energy X-ray absorptiometry (DXA), and blood sampling was conducted for hormonal analysis. The REE was measured using the Douglas bag method and predicted using the DXA-predicted method to calculate the REEratio. Participants were categorized into the normal (REEratio ≥ 0.94, n = 5) and suppressed (REEratio &lt; 0.94, n = 5) groups. There were no group differences in the components of WDEB, except diet-induced thermogenesis (DIT), but EI was significantly higher in the normal group than in the suppressed group (7-day total: 3660 ± 347 vs. 3024 ± 491 kcal/day, p = 0.046 and rest days: 3772 ± 463 vs. 2796 ± 800 kcal/day, p = 0.046). Analysis of hormonal markers of metabolic suppression only showed a significant positive association between insulin-like growth factor-1 (IGF-1) and REEratio (r = 0.771, p = 0.009). The relationships between metabolic suppression and the markers of energy deficiency were inconclusive. There are possible associations of insufficient EI and IGF-1 levels with metabolic suppression, and further study is required to understand energy deficiency in male soccer players.

The aim of the present study was to clarify the influence of inulin and lactulose-fortified prebiotic food intakes on bone metabolism turnover among Japanese female athletes. The participants included 29 female athletes aged 18–25 years. They were requested to consume their habitual foods or drinks with one pack of prebiotic food every day for 12 weeks. Dietary intake, training time, body composition, blood sample, and fecal microbiota were assessed during this intervention period. Body composition, total energy intake, and training time of the participants revealed no significant changes during the intervention period. The occupation ratio of Bifidobacterium spp. was significantly increased at 3 and 4 weeks (18.0 ± 8.3% and 17.6 ± 8.5%, respectively) compared to that of pre-intervention (11.7 ± 7.3%) (p = 0.019 and p = 0.035, respectively). The serum TRACP-5b level was significantly decreased at 12 weeks (363 ± 112 mU/dL) compared to that at baseline (430 ± 154 mU/dL) (p = 0.018). These results suggest that the prebiotic food used in this study might have beneficial effects on bone health and gut microbial environment among female athletes. Further studies are warranted to identify the mechanism of the prebiotics–gut–bone axis.

<title>Abstract</title><sec>
<title>Background</title>
Food frequency questionnaires are considered an effective method for assessing habitual dietary intake, but they must be developed or validated with the target population. Portion size, supplement use and food choice are thought to be especially important methodological considerations for assessing athletes’ dietary intake. This study aimed to develop and validate a food frequency questionnaire for Japanese athletes using data from this population.


</sec><sec>
<title>Methods</title>
We used dietary records from 440 Japanese athletes involved in our previous projects. Food items were analyzed using cumulative percentage contributions and multiple regression analysis, to give a selection of 62 basic food items and four supplemental items. The validity of the questionnaire was evaluated among another 77 Japanese athletes by comparing nutrient intakes assessed using the questionnaire with dietary records. Reproducibility was evaluated by comparing a second questionnaire completed 2–3 weeks later by 36 of the athletes in the validation study. Validity was assessed using crude Spearman’s correlation coefficients (CCs), energy-adjusted CCs, intraclass CCs (ICCs), and Kappa index values. Reproducibility was assessed by CCs, energy-adjusted CCs, and ICCs.


</sec><sec>
<title>Results</title>
In the validation analysis, the median crude CC for all of the nutrients was 0.407, ranging from 0.222 for dietary fiber to 0.550 for carbohydrate. The median energy-adjusted CC was 0.478, and the median ICC was 0.369. When we divided the athletes into quartiles, 65% (vitamin B₁) to 86% (iron) of athletes were classified into the same or adjacent categories using the questionnaire and dietary records, with a median Kappa statistic of 0.32. In the reproducibility analysis, the median crude CC between the two completed questionnaires was 0.654, ranging from 0.582 (carbohydrate) to 0.743 (vitamin B₂). The median energy-adjusted CC was 0.643, and the median ICC was 0.647.


</sec><sec>
<title>Conclusions</title>
The new 62-item food frequency questionnaire is both reliable and valid and may be useful for assessing food intake in Japanese athletes.


</sec>

For athletes to gain body mass, especially muscle, an increase in energy consumption is necessary. To increase their energy intake, many athletes consume more meals, including supplementary meals or snacks. However, the influence of meal frequency on changes in body composition and appetite is unclear. The aim of this study was to determine the effect of meal frequency on changes in body composition and appetite during weight gain in athletes through a well-controlled dietary intervention. Ten male collegiate rowers with weight gain goals were included in this study. The subjects were randomly classified into two groups, and dietary intervention was implemented using a crossover method. During the intervention period, all subjects were provided identical meals aimed to provide a positive energy balance. The meals were consumed at a frequency of either three times (regular frequency) or six times (high frequency) a day. Body composition was measured using dual energy X-ray absorptiometry, and the visual analog scale was used for the evaluation of appetite. In both trials, body weight, fat-free mass, and fat mass significantly increased; however, an interaction (Trial × Time) was not observed. Visual analog scale did not vary between trials. Our data suggest that partitioning identical excess dietary intakes over three or six meals does not influence changes in body composition or appetite during weight gain in athletes.

Low energy availability (EA) can impair physiological function in athletes. The purpose of this study was to investigate EA status, metabolic status, and bone metabolism with biochemical analysis in Korean male soccer players. Twelve male athletes (18–20 years) completed the study. Body composition and bone mineral density were measured using dual energy X-ray absorptiometry (DXA), while VO₂ max was determined by an incremental exercise test. Blood samples were taken for bone marker and hormone analyses. Resting energy expenditure (REE) was measured using the Douglas bag method and predicted using the DXA method. Food diaries and heart rates (HR) during training were recorded, and the Profile of Mood States 2 and Eating Attitude Test 26 were completed. Group differences between low EA (LEA &lt;30 kcal/kg FFM/d, n = 5) and high EA (HEA ≥30 kcal/kg FFM/d, n = 7) were evaluated. The mean EA of the all participants was 31.9 ± 9.8 kcal/kg FFM/d with only two participants having an EA above 45 kcal/kg FFM/d. LEA showed suppressed REE (LEA: 26.0 ± 1.7 kcal/kg/d, HEA: 28.8 ± 1.4 kcal/kg/d, p = .011) with a lower REE_ratio (LEA: 0.91 ± 0.06, HEA: 1.01 ± 0.05, p = .008) as well as a lower insulin-like growth factor 1 (IGF-1) level (LEA: 248.6 ± 51.2 ng/mL, HEA: 318.9 ± 43.4 ng/mL, p = .028) compared to HEA. There were no group differences in bone markers or other hormone levels. Korean male athletes exhibited low EA status with suppressed metabolism, but there was limited evidence on the effect of EA on bone metabolism, endocrine system, and psychological parameters.

It has been reported that male athletes face increased risk for low energy availability and resulting health consequences similar to female athletes. The present study aimed to reveal the energy status of Japanese male runners and to examine the association between energy deficiency and physiological characteristics such as energy metabolism, bone health, and hormonal status. Six male collegiate long-distance runners during a training season participated in this study. Energy intake (EI) was assessed using 3-day dietary records with food pictures. Exercise energy expenditure (EEE) was determined by the HR-VO₂ method. Body composition and bone status were measured by dual-energy X-ray absorptiometry. Energy availability (EA) was calculated by subtraction of EEE from EI and normalized by fat-free mass (FFM). Energy balance (EB) was calculated EI minus estimated total energy expenditure (TEE). Resting energy expenditure (REE) was measured by indirect calorimetry using the Douglas bag technique, and blood sampling was conducted to assess hormonal status. The mean EA of the subjects was 18.9 ± 6.8 kcal/kg FFM/day, and severe negative EB (range: −1444 ~ −722 kcal/d) was observed. REE of four runners was suppressed, and moreover, bone resorption was promoted in all subjects. The data in our study suggested that energy deficiency could promote bone resorption and energy metabolism suppression in Japanese male endurance runners. Additional short- and long-term studies are needed to clarify the health risks caused by energy deficiency in male athletes and explore strategies to prevent health problems related to energy deficiency in long-distance runners.

Objective: This study aimed to clarify the characteristics of error estimation in food weight using dietary records of male endurance athletes.

Methods: Data from dietary records of athletes and non-athletes were extracted from a laboratory database. Photographs of model menus were distributed to registered dietitians and the subsequent food selection, entry of food item number, and estimated weight based on the model menus were recorded. Thereafter, the research team calculated the nutrient intake to obtain nutrient values. The estimated values were compared with the reference values of the model menus.

Results: Compared to the reference values, there was an approximately 10% underestimation of energy and carbohydrates (average values of -13% and -16%, respectively); 40% and 10% overestimation of vitamin A and C intake, respectively; 23% underestimation of the rice weight; 48% and 68% overestimation of the carrot and spinach weights, respectively, which highly contribute to the vitamin A value; and 68% overestimation of the spinach weight, which highly contributes to the vitamin C value.

Conclusions: These data suggest that, compared to the reference values, the predicted amount of rice is generally underestimated and that of green and yellow vegetables is typically overestimated.

Herein, we attempted to prove the validity of a new approach to assessing total energy expenditure (TEE) that combines activity recording and accelerometry in athletes. Eight female endurance runners participated in this study. We measured TEE over 8 days in the regular training season by using the doubly labeled water (DLW) method. In the combined method, an activity record of the rating of perceived exertion (RPE) was used to estimate energy expenditure (EE) during the training period, whereas a triaxial accelerometer was used to evaluate EE during the nontraining time over the TEE measurement period using the DLW method. Training EE was calculated from the subjects' individual rating of perceived exertion-EE correlations provided by the exercise tolerance test. Resting metabolic rate (RMR) was measured using indirect calorimetry. There were no significant differences in TEE, activity-induced EE (AEE), or physical activity level (PAL; TEE/RMR) between the DLW method and the combined method (TEE, 3,032 +/- 344 vs. 3,033 +/- 495 kcal.d(-1); AEE, 1,585 +/- 303 vs. 1,586 +/- 442 kcal.d(-1); and PAL, 2.68 +/- 0.37 vs. 2.68 +/- 0.48, respectively). Significant positive correlations and no systematic errors were observed in AEE and PAL. Intraclass correlation coefficients were high (TEE, 0.785; AEE, 0.841; and PAL, 0.779, respectively). These findings suggest that the combined method has high validity against the DLW method. Thus, the combined method would be able to estimate free-living TEE in the regular training season for female endurance runners.

An intensive consecutive high-volume training camp may induce appetite loss in athletes. Therefore, this study aimed to investigate the changes in stress and appetite responses in male power-trained athletes during an intensive training camp. The measurements at Day 2 and at the end of a 9-day intensive training camp (Camp1 and Camp2, respectively) were compared with those of the resting period (Rest) and the regular training period (Regular; n = 13). The stress state was assessed based on plasma cortisol level, salivary immunoglobulin A level, and a profile of mood states score. The sensation of appetite was assessed using visual analog scale scores, and fasting plasma acylated ghrelin, insulin, and glucose were measured. The cortisol concentrations were significantly higher at Camp2 (466.7 +/- 60.7 nmol . L-1) than at Rest (356.3 +/- 100.9 nmol .L-1; p = 0.002) or Regular (361.7 +/- 111.4 nmol . L-1; p = 0.003). Both prospective and actual food consumption significantly decreased at Camp2, and acylated ghrelin concentration was significantly lower at Camp1 (34.2 +/- 8.0 pg . m L-1) and Camp2 (32.0 +/- 8.7 pg . m L-1) than at Rest (47.2 +/- 11.2 pg . m L-1) or Regular (53.4 +/- 12.6 pg . m L-1). Furthermore, the change in acylated ghrelin level was negatively correlated with the change in cortisol concentration. This study's findings suggest that an early-phase physiological stress response may decrease the acylated ghrelin level in male power-trained athletes during an intensive training camp.

Unfortunately, the original version of this article [1] contained an error. The caption for Fig. 1 was included incorrectly. The correct caption can now be found below. Fig. 1 Comparison of prevalence in cardiometabolic risk in terms of blood biochemical parameters. Prevalence of cardiometabolic risk presents the percentage over the referenced normal range of respective parameters. The cut-off referenced normal range were as follows: AST &gt
40 (U/L), ALT &gt
45 (U/L), γ-GTP ≥80 (U/L), HDL-C &lt
40 (mg/dL), LDL-C &gt
140 (mg/dL), TG ≥150 (mg/dL), UA &gt
7.0 (mg/dL), HOMA-IR ≥2.5.∗Significant differences compared with Nonheavyweight group, p &lt
0.05.

While the session-RPE (rating of perceived exertion) method can quantify training volume in athletes, this method is not able to evaluate energy expenditure (EE) during a training session. We developed an RPE-based activity record for assessing EE during athletic training, and we compared its results to those obtained using the flex-heart rate (flex-HR) method. The EE of nine female collegiate endurance runners was assessed by the RPE-based activity record and flex-HR methods during eight days in the normal training season. Subjects were asked to record their RPE in the record at 5-minute intervals, and to wear a HR monitor during training. All subjects also participated in an incremental treadmill exercise test, which was used to determine their RPE-EE and HR-EE regression equations. Although the RPE-based activity record significantly overestimated EE (RPE-activity record, 572 kcal/session
flex-HR method, 499 kcal/session
p = 0.031), it had high validity relative to the flex-HR method (intra-class correlation coefficient, 0.891
95% confidence interval, 0.845-0.923) and there were no systematic errors in EE estimation between the two methods. Therefore, the RPE-based activity record can be used to assess EE during training in female runners. However, RPE-based activity record might overestimate EE for athletes who have more intermittent activities during training than endurance runners, because RPE takes more time for returning to the resting level than HR when the intensity of activity declines. Further research is needed to verify the validity of the RPE-based activity record for assessing EE during other sporting activities or measurement conditions, and to identify the factors affecting the degree of estimation error associated with this method.

We compared the physical activity level (PAL) and training and non-training physical activity (PA) between rhythmic gymnasts and lacrosse players. In addition, we aimed to clarify the contribution of training and non-training PA to the PAL. Our study subjects were 11 female rhythmic gymnasts and 11 female lacrosse players. PAL was calculated from the total energy expenditure (TEE) as assessed by the doubly labeled water (DLW) method, and the resting metabolic rate (RMR) was measured using indirect calorimetry. Daily PA and sleep durations were assessed using an activity diary. The intensity (metabolic equivalent, MET) of non-training PA was measured using a tri-axial accelerometer. The amount (MET･h) of training was calculated by subtracting the amount of PA and sleep outside of training from the TEE. There were no significant differences in PAL between rhythmic gymnasts (2.59 ± 0.63) and lacrosse players (2.43 ± 0.46). Rhythmic gymnasts had a longer duration and larger amount of training PA and a shorter duration and smaller amount of non-training PA than did lacrosse players. The mean intensities of training and non-training PA were not significantly different between the groups. PAL was positively correlated with the amount of training in both rhythmic gymnasts (γs = 0.818) and lacrosse players (γs = 0.882). There were no significant relationships between PAL and non-training PA in both groups. Our results indicate that the amount of training strongly affects PAL in these athletes.

We have previously shown that resting energy expenditure (REE) adjusted by fat-free mass (FFM) in male college athletes remains consistent regardless of FFM. The FFM comprises internal organs with high metabolic activity, such as liver and brain, which account for 60 to 80% of REE in adults. The purpose of the present study is to examine the contribution of internal organs to the REE of the FFM fraction among male power athletes. The study included 37 American male college football players. REE was measured by indirect calorimetry and body composition was measured by dual energy X-ray absorptiometry (DXA). Mass of brain, liver, and kidneys was measured by MRI and mass of heart was estimated by echocardiography. Normal levels of thyroid hormone (triiodothyronine: T3) were confirmed in all subjects prior to the analysis. Multiple regression analysis was used to assess the influence of FFM, fat mass (FM), T3, and mass of organs on variance of REE. Average body weight and FFM were 81.26±11.3 kg and 67.76±7.4 kg, respectively. The relative contributions of liver, kidneys, and heart to REE were consistent regardless of FFM, while the REE of brain was negatively correlated with FFM (r=-0.672, p&lt
0.001). Only FFM and T3 were found to be independent factors influencing REE. These results suggest that a steady contribution of internal organs other than the brain is the major reason for the consistency of the REE/FFM ratio in male power athletes.

The aim of the present study was to evaluate the relation between basal metabolic rate (BMR) and body composition in 29 Japanese elite male athletes (age 25.6±3.7y, height 175.6±7.0cm, body weight 74.7±12.8kg, fat-free mass (FFM) 64.9±9.3kg). The subjects were classified into three groups according to their FFM. There was a significant difference in BMR/FFM between S-group (less than 0.5SD of average FFM) and L-group (more than 0.5SD). The parcentage of RM to body weight in S-group was significantly higher than in L-group. In conclusion, high basal metabolic rate/fat-free mass ratio in Japanese elite male athletes can be attributed to body composition.

The fat-free mass (PPM) of athletes is typically large, and thus the PPM is often utilized to estimate their resting energy expenditure (REP). While the proportional contribution of organ-tissues to the total influence of PPM on REE is known for untrained individuals and female athletes, the extent to which this is valid for male athletes is unclear. The purpose of this study was to clarify the contribution of the components of FFM to REP in male athletes. Fifty-seven male athletes participated in this study. REE was assessed by indirect calorimetry and body composition by dual X-ray absorptiometry. The athletes were equally divided into three groups based on PPM: Small (S), Medium (M), and Large (L). When measured REF (REEm) was compared with REE estimated (REEe) based on the four organ-tissue compartments with set metabolic rates, REEm and REEe had a strong association (r=0.76, p&lt;0.001). In addition. the absolute value of total REP became larger in accordance with body size (S: 1,643 +/- 144, M: 1,865 +/- 140, and L: 2,060 +/- 156 kcal/d) accompanied by increases in mass of all four organ-tissue compartments as body size increased. The consistency of REP/PPM in male athletes in spite of the difference in body size can be explained by the steadiness among the three groups of the relative contribution of each organ-tissue compartment to the FEM. Based on these results. the PPM is the major determinant of REE regardless of body size in male athletes.

Energy requirements can be estimated from resting energy expenditure (REE). However, little is known about factors influencing REE in Japanese female athletes. This study was performed to evaluate the relationship between REE and body composition in Japanese female athletes with a wide range of body sizes. Ninety-three athletes (age 20.3 +/- 1.2y, height 162.8 +/- 6.4 cm, body weight (BW) 57.0 +/- 9.2 kg, fat-free mass (FFM) 45.4 +/- 6.2 kg) were classified into three groups according to BW: small-size (S) (n=34), medium-size (M) (n=34), and large-size (L) (n=25). Systemic and regional body compositions (skeletal muscle (SM), fat mass (FM), bone mass (BM), and residual mass (RM)) were estimated by dual energy X-ray absorptiometry (DXA). Measured resting energy expenditure (REEm) was evaluated by indirect calorimetry. Marked differences were found in REEm (S: 1,111 +/- 150, M: 1,242 +/- 133, L: 1,478 +/- 138 kcal/d), and systemic and regional body compositions among the three groups. REEm was strongly correlated with PPM, and absolute values of RM and SM increased significantly according to body size. There was good agreement between REEm and estimated REE (REEe) from the specific metabolic rates of four major organ tissue level compartments. These data indicate that REE for female athletes can be attributed to changes in organ tissue mass, and not changes in organ tissue metabolic rate. That is, change in REE can be explained mainly by the change in PPM, and REE can be assessed by PPM in female athletes regardless of body size.

The aim of the present study was to examine the validation of prediction equation of basal metabolic rate (BMR) in Japanese female athletes. The study population consisted of 122 Japanese female athletes (age 20.2 ± 1.3 years, height 162.5 ± 6.3 cm, body weight (BW) 57.4 ± 7.7 kg, and fat-free mass (FFM) 45.5 ± 5.1 kg). Body composition was estimated by using air displacement plethysmography (BOD POD System). BMR was measured by indirect calorimetry using dougras bag tequnique, and predicted BMR was calculated from different equations based on FFM. When compared with measured BMR, predicted BMR from the equation of Taguchi et al. (BMR (kcal/day)=26.9 x FFM (kg) + 36) and equation of Owen et al. were not significantly different. Whereas, predicted values from equation of Japan Institute of Sports Sciences, National Institute of Health and Nutrition and Cunningham were significantly different from measured value. Estimation error and Total error were smaller in equation of Taguchi et al. and Owen et al., however, equation of Owen et al. had a larger estimation error in the subjects who was small body size (less than 42kg) or large body size (more than 69kg). Furthermore, newer equation of Taguchi et al. (BMR=27.5 x FFM+5) was developed from the pool data (n=205) in the present study. Standard error of estimation (SEE) of this equation was smaller than the equation of Taguchi et al., and systematic error was hardly observed. In conclusion, the newer equation of Taguchi et al. developed from measured BMR of Japanese female athletes was useful to predict BMR.

:The fat-free mass (FFM) of athletes is typically large, and thus the FFM is often utilized to estimate their resting energy expenditure (REE). While the proportional contribution of organ-tissues to the total influence of FFM on REE is known for untrained individuals and female athletes, the extent to which this is valid for male athletes is unclear. The purpose of this study was to clarify the contribution of the components of FFM to REE in male athletes. Fifty-seven male athletes participated in this study. REE was assessed by indirect calorimetry and body composition by dual X-ray absorptiometry. The athletes were equally divided into three groups based on FFM: Small (S), Medium (M), and Large (L). When measured REE (REEm) was compared with REE estimated (REEe) based on the four organ-tissue compartments with set metabolic rates, REEm and REEe had a strong association (r=0.76, p<0.001). In addition, the absolute value of total REE became larger in accordance with body size (S: 1,643±144, M: 1,865±140, and L: 2,060±156 kcal/d) accompanied by increases in mass of all four organ-tissue compartments as body size increased. The consistency of REE/FFM in male athletes in spite of the difference in body size can be explained by the steadiness among the three groups of the relative contribution of each organ-tissue compartment to the FFM. Based on these results, the FFM is the major determinant of REE regardless of body size in male athletes.

Medium-chain triacylglycerols (MCT) are known to hydrolyze readily and completely to fatty acids and to be metabolized more easily by beta-oxidation than long-chain triacylglycerols (LCT). Therefore, we investigated the effect of 2 wk of ingestion of food containing a small amount (6 g) of MCT on energy metabolism during moderate-intensity exercise and high-intensity exercise in recreational athletes. For comparison, the subjects were administered food containing MCT or LCT for 14 d, and were instructed to perform cycle ergometer exercise at a workload corresponding to 60% peak O(2) uptake (V) over dotO(2)) for 40 min followed by a workload corresponding to 80% peak (V) over dotO(2) until exhaustion. Blood lactate concentration, (V) over dotO(2), (V) over dotCO(2), and rating of perceived exertion (RPE) were measured at rest and during exercise. The exercise time to exhaustion at a workload corresponding to 80% peak (V) over dotO(2) was significantly (p&lt;0.05) longer in the MCT trial (10.2 +/- 7.6 min: mean +/- SD) than in the LCT trial (5.8 +/- 3.3 min). Blood lactate concentration and RPE during exercise were significantly (p&lt;0.05) lower after ingestion of MCT-containing food. Fat oxidation rate was higher and carbohydrate oxidation rate was lower during exercise in the MCT trial than in the LCT trial, but the differences were not significant. These results indicate that the ingestion of MCT-containing food may suppress utilization of carbohydrate for energy production because of increased utilization of fatty acids for generating energy In conclusion, our data suggest that short-term ingestion of food containing a small amount of MCT suppresses the increase in blood lactate concentration and RPE during moderate-intensity exercise and extends the duration of subsequent high-intensity exercise, at levels higher than those achieved by ingestion of LCT-containing food.

The nutritional status and exercise training programs were compared between adolescent Japanese and Chinese athletes who belonged to the top schools for track and field and basketball in their respective countries. The mean energy intake was about two times greater in Chinese athletes than in their Japanese counterparts. Chinese athletes consumed 1.5~2.0 times more carbohydrate, 1.9~2.3 times more protein, 3.5~7.5times more calcium, 2.9~3.7 times more iron, 1.7~2.2 times more vitamin Bt and 1.3~ 1.8 times more vitamin B2. Almost all the Chinese athletes consumed more than the Recommended Dietary Allowance standards for energy, protein, calcium, iron and vitamins A, Blf B2 and C, while many Japanese athletes did not meet them except for vitamin A and C. The Japanese athletes had more inadequate training schedules, insufficient weight training, and unsatisfactory amount and intervals of rest. These results indicate that Japanese athletes have certain deficiencies in their comprehensive training programs in consideration to nutrition, exercise and rest. © 1993, The Japanese Society of Physical Fitness and Sports Medicine. All rights reserved.