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

Takai, Yoshiaki; Nakatani, Miyuki; Aoki, Takuya; Komori, Daisuke; Oyamada, Kazuyuki; Murata, Kenichi; Fujita, Eiji; Akamine, Takuya; Urita, Yoshihisa; Yamamoto, Masayoshi; Kanehisa, Hiroaki

doi:10.1371/journal.pone.0189836

Cited by 15 publications

(17 citation statements)

References 21 publications

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“…The BM BP s of the whole-body FM-and FFSTM-BM relationships (FM, 81.8 kg of BM; FFSTM, 82.2 kg of BM) were different from those reported in the earlier findings [8,9]. The values obtained here were considerably smaller than that reported for American footballers (114 kg of BM) [8].…”

Section: Discussioncontrasting

confidence: 95%

“…The values obtained here were considerably smaller than that reported for American footballers (114 kg of BM) [8]. However, the BM BP in FFSTM-BM relationship was greater as compared to that observed in our previous study [9] which examined male athletes and untrained males (72.4 kg of BM). Distribution of FM and FFSTM within a body has been shown to be influenced by training status and ethnicity [19,23].…”

Section: Discussioncontrasting

confidence: 90%

“…Whole-body FM and FFM strongly associates with body size (e.g., height and BM) in athletes and untrained individuals [6][7][8][9]. However, some studies have shown that there is a breakpoint (BP), at which the regression slope alters below and above the BP, in the FM and FFM-BM [8], and FFSTM-BM relationships [9], respectively. For example, Bosch et al [8] observed the BP at 114 kg of BM in American football players.…”

Section: Introductionmentioning

confidence: 99%

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Profile of regional fat and fat-free soft tissue accumulation in male athletes

Takai

Nakatani

Aoki

et al. 2020

J Physiol Anthropol

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Background: It is unclear whether or not the breakpoint (BP), at which the proportion of each of fat mass (FM) and fat-free soft tissue mass (FFSTM) to body mass (BM) alter, exists in male athletes. We examined the hypothesis that in male athletes, the regional FM and FFSTM-BM relationships have a BP, but the body mass at BP (BM BP ) differs among the arms, trunk, and legs. Methods: By using a dual X-ray absorptiometry, whole-body and regional FMs and FFSTMs in the arms, trunk, and legs were estimated in 198 male athletes (20.8 ± 2.1 years; 1.73 ± 0.07 m; 72.7 ± 14.8 kg). To detect the BP in the relationship between each of FM and FFSTM and BM, a piecewise linear regression analysis was used. If a BP was detected in the corresponding relationship, the significant difference between the regression slopes above and below the BP was examined. Results: The regression analysis indicated that the BM BP existed in the FM-and FFSTM-BM relationships regardless of region and whole body. For the whole body, BM BP was 81.8 kg for FM and 82.2 kg for FFSTM. In regional FM-BM relationships, BM BP was 80.5 kg for arms, 82.6 kg for trunk, and 63.3 kg for legs, and the regression slopes above the BM BP became higher than those below the BP, and vice versa in regional FFSTM-BM relationships (BM BP 104.6 kg for arms, 80.9 kg for trunk, and 79.0 kg for legs). The relative differences in the slopes between below and above BM BP in the regional FM-BM relationships were higher in the arms and trunk than in the legs, and those in the regional FFSTM-BM relationships in the legs than in the trunk. Conclusion: Whole-body and regional FM-and FFSTM-BM relationships for male athletes have breakpoints at which the proportion of the tissue masses to BM alters. The BM BP and differences in the distribution of regional FM and FFSTM around the breakpoint are region specific.

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Section: Discussioncontrasting

confidence: 95%

Section: Discussioncontrasting

confidence: 90%

Section: Introductionmentioning

confidence: 99%

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Profile of regional fat and fat-free soft tissue accumulation in male athletes

Takai

Nakatani

Aoki

et al. 2020

J Physiol Anthropol

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“…These results are consistent with other studies that have indicated that anthropometric variables continue to be excellent predictors of body components. This is especially the case when the Electric Bio-impedance (21, 22) and DXA methods (23–25) are used as criteria.…”

Section: Discussionmentioning

confidence: 99%

Muscle Mass in Children and Adolescents: Proposed Equations and Reference Values for Assessment

Bolaños

Andruske²,

Arruda

et al. 2019

Front. Endocrinol.

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Objectives: The goal of this study was to develop regression equations to estimate LM with anthropometric variables and to propose percentiles for evaluating by age and sex. Methods: A cross sectional study was conducted with 2,182 Chilean students (1,347 males and 835 females). Ages ranged from 5.0 to 17.9 years old. A total body scan was carried out with the double energy X-ray anthropometry (DXA) to examine and measure lean muscle mass of the entire body. Weight, height, and the circumference of the relaxed right arm were also measured. Results: Four anthropometric equations were generated to predict lean mass for both sexes ( R 2 = 83–88%, SEE = 3.7–5.0%, precision = 0.90–0.93, and accuracy = 0.99). The Lambda-mu-sigma method was used to obtain the sex-specific and age-specific percentile curves of lean mass (p3, p5, p10, p15, p25, p50, p75, p85, p90, p95, and p97). Conclusion: The four proposed equations were acceptable in terms of precision and accuracy to estimate lean mass in children and adolescents. The percentiles were created by means of anthropometric equations and real values for DXA. These are fundamental tools for monitoring LM in Chilean children and adolescents of both sexes.

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“…In other words, gymnasts repeat highly intense and sustained upper arm muscle activities during competitions and training. The unique use of upper limb muscles by gymnasts is one factor yielding the hypertrophied muscularity of this segment (Claessens et al, 1991;Ichinose et al, 1998;Spenst, Martin & Drinkwater, 1993;Takai et al, 2018) The muscle size (e.g., muscle cross-sectional area and muscle volume) is a significant determinant of force-and power-generating capacities of the upper arms (Fukunaga et al, 2001;Wakahara et al, 2013). There is little information from earlier studies on the isometric and dynamic strength of the upper limb muscles of gymnasts.…”

Section: Introductionmentioning

confidence: 99%

Force-velocity relationship profile of elbow flexors in male gymnasts

Nakatani

Murata

Kanehisa

et al. 2021

PeerJ

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Background The theoretical maximum force (F0), velocity (V0), and power (Pmax) of athletes calculated from the relationship between force and velocity (F-V relationship) and the slope of the F-V relationship, reflect their competitive and training activity profiles. Evaluating the F-V relationship of athletes facilitates categorizing the profiles of dynamic muscle functions in relation to long-term sport-specific training. For gymnastics, however, no studies have tried to examine the profiles of F-V relation and power output for upper limb muscles in relation to the muscularity, while the use of the upper extremities in this sport is very unique as described earlier. Purpose It was hypothesized that the F-V relationship of the elbow flexion in gymnasts might be characterized by low capacity for generating explosive force, notably in terms of the force normalized to muscle size. Methods The F0, V0, and Pmax derived from the force-velocity relationship during explosive elbow flexion against six different loads (unloaded condition, 15, 30, 45, 60, and 75% of maximal voluntary isometric elbow flexion force (MVFEF)) for 16 gymnasts (GYM) and 22 judo athletes (JD). F0 and Pmax were expressed as values relative to the cross-sectional area index (CSAindex) of elbow flexors (F0/CSAindex and Pmax/CSAindex, respectively), which was calculated from muscle thickness in the anterior upper arm. The electromyogram (EMG) activities of the biceps brachii (BB) during the maximal isometric and dynamic tasks were also determined. Results There were no significant differences in CSAindex of elbow flexors between GYM and JD. MVFEF/CSAindex for GYM was significantly lower than that for JD. Force was linearly associated with velocity in the dynamic elbow flexion for all the participants (r = − 0.997 to −0.905 for GYM, r = − 0.998 to −0.840 for JD). F0, F0/ CSAindex, V0, Pmax, Pmax/CSAindex, and MVFEF were significantly lower in GYM than in JD. The activity levels of BB during the dynamic tasks tended to be lower in GYM than in JD at load of <45%MVC. Conclusion Gymnasts cannot generate explosive elbow flexion force corresponding to their muscle size. This may be due to low neuromuscular activities during the maximal dynamic tasks against relatively low loads.

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

Cited by 15 publications

References 21 publications

Profile of regional fat and fat-free soft tissue accumulation in male athletes

Profile of regional fat and fat-free soft tissue accumulation in male athletes

Muscle Mass in Children and Adolescents: Proposed Equations and Reference Values for Assessment

Force-velocity relationship profile of elbow flexors in male gymnasts

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