Fat-Free Mass Can Be Utilized to Assess Resting Energy Expenditure for Male Athletes of Different Body Size

Oshima, Satomi; Miyauchi, Sakiho; Kawano, Hiroshi; Ishijima, Toshimichi; Asaka, Masahiro; Taguchi, Masahiro; Torii, Suguru; Higuchi, Mitsuru

doi:10.3177/jnsv.57.394

Cited by 15 publications

(16 citation statements)

References 18 publications

(25 reference statements)

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“…However, the possibility that an underestimation of EI from the dietary survey affected the result cannot be ignored. The average REEm in this study (26.4 kcal/kg FFM/ day) was lower than the previously reported REE of Japanese male athletes (Oshima et al, 2011(Oshima et al, , 2013Taguchi & Oshima, 2015;Tatsuta et al, 2012). For predicting REE in this study, a tissue-organ level prediction model using data obtained from DXA was used.…”

Section: Discussionmentioning

confidence: 68%

Energy Intake Deficiency Promotes Bone Resorption and Energy Metabolism Suppression in Japanese Male Endurance Runners: A Pilot Study

et al. 2020

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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.

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Section: Discussionmentioning

confidence: 68%

Energy Intake Deficiency Promotes Bone Resorption and Energy Metabolism Suppression in Japanese Male Endurance Runners: A Pilot Study

et al. 2020

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“…In contrast, others have concluded that the relative contribution of the liver, heart, and kidneys to RMR is consistent across a wide range of FFM. 39,40 The brain is one of the most metabolically active organs consuming about one-fifth of total body oxygen. 39 The metabolic rate of the brain; however, is negatively correlated with FFM, 39 potentially identifying another source of variability RMR prediction equations do not model.…”

Section: Resultsmentioning

confidence: 99%

Cross-Validation of Resting Metabolic Rate Prediction Equations

Flack¹,

Siders²,

Johnson³

et al. 2016

Journal of the Academy of Nutrition and Dietetics

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“…In addition, FFM is strongly related to one repetition maximum load during squat, deadlift, and bench press [ 2 ], indicating that it is a potential indicator of force-generating capacity. Furthermore, FFM is often utilized to estimate resting energy expenditure [ 3 ]. From the viewpoint of physical resources, assessment of FFM may provide useful information for sports scientists and coaches to improve body composition for designing training regimens and managing body mass.…”

Section: Introductionmentioning

confidence: 99%

Body shape indices are predictors for estimating fat-free mass in male athletes

et al. 2018

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It is unknown whether body size and body shape parameters can be predictors for estimating whole body fat-free mass (FFM) in male athletes. This study aimed to investigate whether body size and shape variables can be predictors for FFM in male athletes. Using a whole-body dual-energy X-ray absorptiometry scanner, whole body fat mass (FM) and FFM were determined in 132 male athletes and 14 sedentary males. The sample was divided into two groups: validation (N = 98) and cross-validation (N = 48) groups. Body height (BH), body mass (BM), and waist circumference at immediately above the iliac crest (W) were measured. BM-to-W and W-to-BH ratios were calculated as indices of body shapes. Stepwise multiple regression analysis revealed that BM/W and W/BH were selected as explainable variables for predicting FFM. The equation developed in the validation group was FFM (kg) = 0.883 × BM/W (kg/m) + 43.674 × W/BH (cm/cm)– 41.480 [R2 = 0.900, SEE (%SEE) = 2.3 kg (3.8%)], which was validated in the cross-validation group. Thus, the current results demonstrate that an equation using BM/W and W/BH as independent variables is applicable for predicting FFM in male athletes.

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Fat-Free Mass Can Be Utilized to Assess Resting Energy Expenditure for Male Athletes of Different Body Size

Cited by 15 publications

References 18 publications

Energy Intake Deficiency Promotes Bone Resorption and Energy Metabolism Suppression in Japanese Male Endurance Runners: A Pilot Study

Energy Intake Deficiency Promotes Bone Resorption and Energy Metabolism Suppression in Japanese Male Endurance Runners: A Pilot Study

Cross-Validation of Resting Metabolic Rate Prediction Equations

Body shape indices are predictors for estimating fat-free mass in male athletes

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