Body composition in athletes and sports nutrition: an examination of the bioimpedance analysis technique

Habitual water intake impacted the body composition of young male athletes in free-living conditions: a cross-sectional study

The study aimed to explore the associations between water intake and body composition and differences of body composition in different water itake and hydration statuses among young male athletes. A cross-sectional study was conducted among 111 young male athletes in Beijing, China. Total drinking fluids (TDF) and water from food were assessed using a 7-day, 24-h fluid intake record questionnaire and the duplicate portion method, respectively. The osmolality of 24-hour urine and blood samples was tested. Body composition was measured using a bioelectrical impedance analyzer twice at 5-min intervals. Participants were divided into two groups based on the recommendations of total water intake (TWI) and TDF in China, as well as into three groups based on 24-h urine osmolality. Pearson's correlation coefficients were calculated to determine the relationship between water intake and body composition. Chi-square tests and Student's t-tests were used to compare differences. A total of 109 participants completed the study. TDF (r = 0.230, p = 0.016; r = 0.234, p = 0.014; r = 0.242, p = 0.011) and TWI (r = 0.275, p = 0.004; r = 0.243, p = 0.011; r = 0.243, p = 0.011) were positively correlated with total body water (TBW), intracellular water (ICW), and extracellular water (ECW). TBW/body weight (BW) was positively associated with TDF percentage of BW (TDF/BW) (r = 0.267, p = 0.005), water from food percentage of BW (r = 0.217, p = 0.024), and TWI percentage of BW (TWI/BW) (r = 0.316, p = 0.001). Participants who met the TDF recommendation of China had 1.3 kg higher skeletal muscle mass (SMM), 0.9 kg higher ICW, and 0.5% higher TBW/BW than those who did not (all p < 0.05), with fat-free mass (FFM) and TBW being higher (p = 0.051; p = 0.050). Those who met the TWI recommendation of China had 1.3 kg higher SMM, 2.4 kg higher FFM, 1.1 kg higher ICW, 0.6 kg higher ECW, and 1.7 kg higher TBW than their counterparts (all p < 0.05). Moderate associations were found between water intake and body composition. No significant differences were observed among participants in three hydration statuses (all p > 0.05). Participants who met the TWI or TDF recommendations had better body composition distribution than their counterparts. Thus, habitual water intake, not hydration status, affects body composition among athletes in free-living conditions.

Variations in bioelectrical impedance devices impact raw measures comparisons and subsequent prediction of body composition using recommended estimation equations

BACKGROUND & AIMS

Bioelectrical impedance analysis (BIA) for body composition estimation is increasingly used in clinical and field settings to guide nutrition and training programs. Due to variations among BIA devices and the proprietary prediction equations used, studies have recommended the use of raw measures of resistance (R) and reactance (Xc) within population-specific equations to predict body composition.

OBJECTIVE

We compared raw measures from three BIA devices to assess inter-device variation and the impact of differences on body composition estimations.

METHODS

Raw R, Xc, impedance (Z) parameters were measured on a calibrated phantom and athletes using tetrapolar supine (BIASUP4), octapolar supine (BIASUP8), and octapolar standing (BIASTA8) devices. Measures of R and Xc were compared across devices and graphed using BIA vector analysis (BIVA) and raw parameters were entered into recommended athlete-specific equations for predicting fat-free mass (FFM) and appendicular lean soft tissue (ALST). Whole-body FFM and regional ALST were compared across devices and to a criterion five-compartment (5C) model and dual energy X-ray absorptiometry for ALST.

RESULTS

Data from 73 (23.2 ± 4.8 y) athletes were included in the analyses. Technical differences were observed between Z (range 12.2-50.1Ω) measures on the calibrated phantom. Differences in whole-body impedance were apparent due to posture (technological) and electrode placement (biological) factors. This resulted in raw measures for all three devices showing greater dehydration on BIVA compared to published norms for athletes using a separate BIA device. Compared to the 5C FFM, significant differences (p < 0.05) were observed on all three equations for BIASUP8 and BIASTA8, with constant error (CE) from -2.7 to -4.6 kg; no difference was observed for BIASUP4 or when device-specific algorithms were used. Published equations resulted in differences as large as 8.8 kg FFM among BIA devices. For ALST, even after a correction in the error of the published empirical equation, all three devices showed significant (p < 0.01) CE from -1.6 to -2.9 kg.

CONCLUSIONS

Raw bioimpedance measurements differ among devices due to technical, technological, and biological factors, limiting interchangeability of data across BIA systems. Professionals should be aware of these factors when purchasing systems, comparing data to published reference ranges, or when applying published empirical body composition prediction equations.

Advancing body composition assessment in patients with cancer: First comparisons of traditional versus multicompartment models

BACKGROUND AND AIMS

Measurement of body composition using computed tomography (CT) scans may be a viable clinical tool for low muscle mass assessment in oncology. However, longitudinal assessments are often infeasible with CT. Clinically accessible body composition technologies can be used to track changes in fat-free mass (FFM) or muscle, though their accuracy may be impacted by cancer-related physiological changes. The purpose of this study was to examine the agreement among accessible body composition method with criterion methods for measures of whole-body FFM measurements and, when possible, muscle mass for the classification of low muscle in patients with cancer.

METHODS

Patients with colorectal cancer were recruited to complete measures of whole-body DXA, air displacement plethysmography (ADP), and bioelectrical impedance analysis (BIA). These measures were used alone, or in combination to construct the criterion multicompartment (4C) mode for estimating FFM. Patients also underwent abdominal CT scans as part of routine clinical assessment. Agreement of each method with 4C model was analyzed using mean constant error (CE = criterion - alternative), linear regression including root mean square error (RMSE), Bland-Altman limits of agreement (LoA) and mean percentage difference (MPD). Additionally, appendicular lean soft tissue index (ALSTI) measured by DXA and predicted by CT were compared for the absolute agreement, while the ALSTI values and skeletal muscle index by CT were assessed for agreement on the classification of low muscle mass.

RESULTS

Forty-five patients received all measures for the 4C model and 25 had measures within proximity of clinical CT measures. Compared to 4C, DXA outperformed ADP and BIA by showing the strongest overall agreement (CE = 1.96 kg, RMSE = 2.45 kg, MPD = 98.15 ± 2.38%), supporting its use for body composition assessment in patients with cancer. However, CT cutoffs for skeletal muscle index or CT-estimated ALSTI were lower than DXA ALSTI (average 1.0 ± 1.2 kg/m2) with 24.0% to 32.0% of patients having a different low muscle classification by CT when compared to DXA.

CONCLUSIONS

Despite discrepancies between clinical body composition assessment and the criterion multicompartment model, DXA demonstrates the strongest agreement with 4C. Disagreement between DXA and CT for low muscle mass classification prompts further evaluation of the measures and cutoffs used with each technique. Multicompartment models may enhance our understanding of body composition variations at the individual patient level and improve the applicability of clinically accessible technologies for classification and monitoring change over time.

Estimation equation of limb lean soft tissue mass in Asian athletes using bioelectrical impedance analysis

BACKGROUND

The lean soft tissue mass (LSTM) of the limbs is approximately 63% of total skeletal muscle mass. For athletes, measurement of limb LSTM is the basis for rapid estimation of skeletal muscle mass. This study aimed to establish the estimation equation of LSTM in Asian athletes using bioelectrical impedance analysis (BIA).

METHODS

A total of 198 athletes (121 males, 77 females; mean age 22.04 ± 5.57 years) from different sports in Taiwan were enrolled. A modeling group (MG) of 2/3 (n = 132) of subjects and a validation group (VG) of 1/3 (n = 68) were randomly assigned. Using the InBody S-10, resistance and reactance were measured at 50 kHz from the right palm to the right sole while the participant was in the supine position. Predictor variables were height (h), weight (W), age, Sex, Xc, resistance index (RI; RI = h2 / R). LSTM of arms and legs measured by dual-energy X-ray absorptiometry (DXA) was the response variable. Multivariate stepwise regression analysis method was used to establish BIA estimation equations as ArmsLSTMBIA-Asian and LegsLSTMBIA-Asian. Estimation equations performance was confirmed by cross-validation.

RESULTS

Estimation equation "ArmsLSTMBIA-Asian = 0.096 h2/R- 1.132 Sex + 0.030 Weight + 0.022 Xc- 0.022 h + 0.905, r2 = 0.855, SEE = 0.757 kg, n = 132" and "LegsLSTMBIA Asian = 0.197h2/R" + 0.120 h- 1.242 Sex + 0.055 Weight- 0.052 Age + 0.033 Xc -16.136, r2 = 0.916, SEE = 1.431 kg, n = 132" were obtained from MG. Using DXA measurement results of VG for correlation analysis and Limit of Agreement (LOA) of Bland-Altman Plot, ArmsLST is 0.924, -1.53 to 1.43 kg, and LegsLST is 0.957, -2.68 to 2.90 kg.

CONCLUSION

The established single-frequency BIA hand-to-foot (whole body) estimation equation quickly and accurately estimates LSTM of the arms and legs of Asian athletes.

Validation of Bioelectrical Impedance Devices for the Determination of Body Fat Percentage in Firefighters

ABSTRACT

Jagim, AR, Luedke, J, Erickson, JL, Fields, JB, and Jones, MT. Validation of bioelectrical impedance devices for the determination of body fat percentage in firefighters. J Strength Cond Res 38(8): e448-e453, 2024-To cross-validate bioelectrical impedance devices for the determination of body fat percentage (BF%) in firefighters. Twenty-eight structural firefighters were evaluated (female, n = 2; male, n = 26 [mean ± SD] age: 38.2 ± 8.3 years; height: 180.2 ± 7.5 cm; body mass: 86.7 ± 20.8 kg; body mass index: 25.8 ± 7.8 kg·m-2) using multifrequency bioelectrical impedance analysis (MFBIA) hand-to-foot device, and single-frequency BIA foot scale (F2FBIA), and a single-frequency handheld BIA device (HHBIA). Dual X-ray absorptiometry served as the criterion. Validity metrics were examined to establish each method's performance. Body fat % values produced by MFBIA (r = 0.913), F2FBIA (r = 0.695), and HHBIA (r = 0.876) were strongly associated (p < 0.001) with criterion BF% measures. However, MFBIA, F2FBIA, and HHBIA all significantly (p < 0.001) underestimated BF% when compared with the criterion measure. Constant error ranged between 4.0 and 5.5% across all BIA devices. Despite strong associations between the BIA devices included in the current study and the criterion measure, all BIA devices underestimated BF%, which resulted in an overestimation of fat-free mass. In addition, proportional bias was observed in which BF% was overestimated at lower values and underestimated at higher values.

High-standard predictive equations for estimating body composition using bioelectrical impedance analysis: a systematic review

The appropriate use of predictive equations in estimating body composition through bioelectrical impedance analysis (BIA) depends on the device used and the subject's age, geographical ancestry, healthy status, physical activity level and sex. However, the presence of many isolated predictive equations in the literature makes the correct choice challenging, since the user may not distinguish its appropriateness. Therefore, the present systematic review aimed to classify each predictive equation in accordance with the independent parameters used. Sixty-four studies published between 1988 and 2023 were identified through a systematic search of international electronic databases. We included studies providing predictive equations derived from criterion methods, such as multi-compartment models for fat, fat-free and lean soft mass, dilution techniques for total-body water and extracellular water, total-body potassium for body cell mass, and magnetic resonance imaging or computerized tomography for skeletal muscle mass. The studies were excluded if non-criterion methods were employed or if the developed predictive equations involved mixed populations without specific codes or variables in the regression model. A total of 106 predictive equations were retrieved; 86 predictive equations were based on foot-to-hand and 20 on segmental technology, with no equations used the hand-to-hand and leg-to-leg. Classifying the subject's characteristics, 19 were for underaged, 26 for adults, 19 for athletes, 26 for elderly and 16 for individuals with diseases, encompassing both sexes. Practitioners now have an updated list of predictive equations for assessing body composition using BIA. Researchers are encouraged to generate novel predictive equations for scenarios not covered by the current literature.Registration code in PROSPERO: CRD42023467894.

Development and validation of a rapid multicompartment body composition model using 3-dimensional optical imaging and bioelectrical impedance analysis

BACKGROUND & AIMS

The multicompartment approach to body composition modeling provides a more precise quantification of body compartments in healthy and clinical populations. We sought to develop and validate a simplified and accessible multicompartment body composition model using 3-dimensional optical (3DO) imaging and bioelectrical impedance analysis (BIA).

METHODS

Samples of adults and collegiate-aged student-athletes were recruited for model calibration. For the criterion multicompartment model (Wang-5C), participants received measures of scale weight, body volume (BV) via air displacement, total body water (TBW) via deuterium dilution, and bone mineral content (BMC) via dual energy x-ray absorptiometry. The candidate model (3DO-5C) used stepwise linear regression to derive surrogate measures of BV using 3DO, TBW using BIA, and BMC using demographics. Test-retest precision of the candidate model was assessed via root mean square error (RMSE). The 3DO-5C model was compared to criterion via mean difference, concordance correlation coefficient (CCC), and Bland-Altman analysis. This model was then validated using a separate dataset of 20 adults.

RESULTS

67 (31 female) participants were used to build the 3DO-5C model. Fat-free mass (FFM) estimates from Wang-5C (60.1 ± 13.4 kg) and 3DO-5C (60.3 ± 13.4 kg) showed no significant mean difference (-0.2 ± 2.0 kg; 95 % limits of agreement [LOA] -4.3 to +3.8) and the CCC was 0.99 with a similar effect in fat mass that reflected the difference in FFM measures. In the validation dataset, the 3DO-5C model showed no significant mean difference (0.0 ± 2.5 kg; 95 % LOA -3.6 to +3.7) for FFM with almost perfect equivalence (CCC = 0.99) compared to the criterion Wang-5C. Test-retest precision (RMSE = 0.73 kg FFM) supports the use of this model for more frequent testing in order to monitor body composition change over time.

CONCLUSIONS

Body composition estimates provided by the 3DO-5C model are precise and accurate to criterion methods when correcting for field calibrations. The 3DO-5C approach offers a rapid, cost-effective, and accessible method of body composition assessment that can be used broadly to guide nutrition and exercise recommendations in athletic settings and clinical practice.

Accuracy and precision of multiple body composition methods and associations with muscle strength in athletes of varying hydration: The Da Kine Study

BACKGROUND

Athletes vary in hydration status due to ongoing training regimes, diet demands, and extreme exertion. With water being one of the largest body composition compartments, its variation can cause misinterpretation of body composition assessments meant to monitor strength and training progress. In this study, we asked what accessible body composition approach could best quantify body composition in athletes with a variety of hydration levels.

METHODS

The Da Kine Study recruited collegiate and intramural athletes to undergo a variety of body composition assessments including air-displacement plethysmography (ADP), deuterium-oxide dilution (D2O), dual-energy X-ray absorptiometry (DXA), underwater-weighing (UWW), 3D-optical (3DO) imaging, and bioelectrical impedance (BIA). Each of these methods generated 2- or 3-compartment body composition estimates of fat mass (FM) and fat-free mass (FFM) and was compared to equivalent measures of the criterion 6-compartment model (6CM) that accounts for variance in hydration. Body composition by each method was used to predict abdominal and thigh strength, assessed by isokinetic/isometric dynamometry.

RESULTS

In total, 70 (35 female) athletes with a mean age of 21.8 ± 4.2 years were recruited. Percent hydration (Body Water6CM/FFM6CM) had substantial variation in both males (63-73 %) and females (58-78 %). ADP and DXA FM and FF M had moderate to substantial agreement with the 6C model (Lin's Concordance Coefficient [CCC] = 0.90-0.95) whereas the other measures had lesser agreement (CCC <0.90) with one exception of 3DO FFM in females (CCC = 0.91). All measures of FFM produced excellent precision with %CV < 1.0 %. However, FM measures in general had worse precision (% CV < 2.0 %). Increasing quartiles (significant p < 0.001 trend) of 6CM FFM resulted in increasing strength measures in males and females. Moreover, the stronger the agreement between the alternative methods to the 6CM, the more robust their correlation with strength, irrespective of hydration status.

CONCLUSION

The criterion 6CM showed the best association to strength regardless of the hydration status of the athletes for both males and females. Simpler methods showed high precision for both FM and FFM and those with the strongest agreement to the 6CM had the highest strength associations.

SUMMARY BOX

This study compared various body composition analysis methods in 70 athletes with varying states of hydration to the criterion 6-compartment model and assessed their relationship to muscle strength. The results showed that accurate and precise estimates of body composition can be determined in athletes, and a more accurate body composition measurement produces better strength estimates. The best laboratory-based techniques were air displacement plethysmography and dual-energy x-ray absorptiometry, while the commercial methods had moderate-poor agreement. Prioritizing accurate body composition assessment ensures better strength estimates in athletes.

Athletic bioimpedance-based equations underestimate fat free mass components in male elite soccer players: development and validation of new soccer-specific predictive models

BACKGROUND

Bioelectrical impedance analysis (BIA) is a rapid and user-friendly technique for assessing body composition in sports. Currently, no sport-specific predictive equations are available, and the utilization of generalized formulas can introduce systematic bias. The objectives of this study were as follows: (i) to develop and validate new predictive models for estimating fat-free mass (FFM) components in male elite soccer players; (ii) to evaluate the accuracy of existing predictive equations.

METHODS

A total of 102 male elite soccer players (mean age 24.7 ± 5.7 years), participating in the Italian first league, underwent assessments during the first half of the in-season period and were randomly divided into development and validation groups. Bioelectrical resistance (R) and reactance (Xc), representing the bioimpedance components, were measured using a foot-to-hand BIA device at a single frequency of 50 kHz. Dual-energy X-ray absorptiometry was employed to acquire reference data for FFM, lean soft tissue (LST), and appendicular lean soft tissue (ALST). The validation of the newly developed predictive equations was conducted through regression analysis, Bland-Altman tests, and the area under the curves (AUC) of regression receiver operating characteristic (RROC) curves.

RESULTS

Developed models were: FFM = - 7.729 + (body mass × 0.686) + (stature2/R × 0.227) + (Xc × 0.086) + (age × 0.058), R2 = 0.97, Standard error of estimation (SEE) = 1.0 kg; LST = - 8.929 + (body mass × 0.635) + (stature2/R × 0.244) + (Xc × 0.093) + (age × 0.048), R2 = 0.96, SEE = 0.9 kg; ALST = - 24.068 + (body mass × 0.347) + (stature2/R × 0.308) + (Xc × 0.152), R2 = 0.88, SEE = 1.4 kg. Train-test validation, performed on the validation group, revealed that generalized formulas for athletes underestimated all the predicted FFM components (p < 0.01), while the new predictive models showed no mean bias (p > 0.05), with R2 values ranging from 0.83 to 0.91, and no trend (p > 0.05). The AUC scores of the RROC curves indicated an accuracy of 0.92, 0.92, and 0.74 for FFM, LST, and ALST, respectively.

CONCLUSIONS

The utilization of generalized predictive equations leads to an underestimation of FFM and ALST in elite soccer players. The newly developed soccer-specific formulas enable valid estimations of body composition while preserving the portability of a field-based method.

Hydration and Body Composition in Sports Practice: An Editorial

Assessing hydration status and monitoring body composition represent crucial aspects when discussing the advantages of embracing a healthy lifestyle, given its significant impact on both health and sports performance [...].

The effect of acute hydration on body composition assessed by multi-frequency and single-frequency bioelectrical impedance

BACKGROUND

Multi-frequency bioelectrical impedance (MF-BIA) provides an estimate of total body water. However, it is unknown if MF-BIA detects body water increases due to acute hydration, thus affecting the validity of MF-BIA body composition measurements. The purpose of this study was to compare the effects of pre-testing fluid ingestion on body composition estimation using single-frequency bioelectrical impedance (SF-BIA) and MF-BIA.

METHODS

Thirty-nine subjects (20 male, 19 female) were tested for body composition using DXA, SF-BIA and MF-BIA before and after consumption of 2 L of water.

RESULTS

Hydration significantly increased fat percentage in men and women for MF-BIA (+2.1±0.7% for men, +2.6±0.7% for women) and SF-BIA (+1.3±0.7% for men, +2.1±0.9% for women). Additionally, hydration significantly increased fat-free mass (FFM) for DXA (+1.4±0.8 kg for men, +1.7±0.4 kg for women) and SF-BIA (+0.5±0.6 kg) in men. Hydration significantly increased fat mass (FM) for all modes (DXA +0.3±0.3 kg, MF-BIA +2.0±0.7 kg, SF-BIA +1.3±0.6 kg) in males, and only for MF-BIA (+2.2±0.3 kg) and SF-BIA (+1.7±0.5 kg) in females. Increases in FM were highest for MF-BIA for both males and females. Total body water was unchanged in males and significantly decreased with acute hydration in females.

CONCLUSIONS

MF-BIA improperly categorizes increased mass due to acute hydration as fat mass, resulting in an increase in measured body fat percentage. These findings confirm the need to standardize hydration status for body composition measurements using MF-BIA.

Preliminary Assessment of the Acute Effects of Far Infrared-Emitting Garments: What Are the Possible Implications for Recovery and Performance?

Technical clothing has recently been brought into the spotlight as one of the most promising tools to improve sports performance and to enhance sports recovery. Among technical clothing items, garments engineered to emit far infrared (FIR) spectrum frequencies have come to the fore as a treatment for pain, muscle fatigue, and tissue healing due to their potential antioxidative and anti-inflammatory properties, with applications not only during recovery phases but also in the active phases of exercise. These garments, composed of fibers mixed with noble metals and/or bioceramics that respond to body infrared frequencies by returning an FIR emission backwards, are thought to improve muscle oxygenation and therefore recovery. In this double-blind, randomized, placebo-controlled, crossover study, ten male trail running athletes wore a whole-body-covering suit marketed as Accapì-FIR (Bruno Chiaruttini S.r.l., Rezzato, BS, Italy), while a total body suit with the same polyester fiber without metal components was used as control for the intervention. Parameters such as weight, height, bioimpedance parameters (BIVA), lactate from capillary sampling, salivary cortisol, and average temperatures of different body areas were obtained before and after a twelve-minute incremental work run protocol on a treadmill whilst wearing the two kinds of garment. Using the intervention suit, compared to control, statistically significant reductions in BIVA parameters such as body resistance (-6.7%) and reactance (-5.4%) were observed before and after exercise while a greater, but not significant, weight reduction was observed with the intervention suit. Decrease in resistance could be the result of a different distribution of fluids and ions due to FIR influence on capillary and superficial circulation, leading ultimately to more efficient management of body heat and promoting recovery and supercompensation. Further studies on larger samples will be necessary to confirm and clarify these results.

Assessment of the Dietary Intake and Nutritional Status of Polish Professional Futsal Players: A Descriptive Study-Do Futsal Players Require Nutritional Education?

Futsal is a discipline with high training and nutritional requirements. Despite growing research interest in athletes' diet and nutritional status, no studies have examined Polish male futsal players. Therefore, the aim of this descriptive study was an assessment of the dietary intake and nutritional status in a selected group of futsal players. The study comprised 11 members of a top Polish futsal team (aged 26 ± 3.62 years). Dietary intake was assessed using a standardized 3-day food record. Body composition, total energy expenditure, physical fitness level, and concentrations of the biochemical indices of each participant were estimated. The energy availability in the diet was lower than recommended. Moreover, low consumption of carbohydrates was stated, as well as an inadequate intake of Vitamins E and D. Higher protein and cholesterol intake than recommended were also observed. To conclude, our results point to the need for educating athletes and coaches, particularly teaching about proper food choices, promoting quality foods, and, in some cases, using individual dietary plans to meet energy and nutrient needs. Nutrition education would help to improve their dietary and health habits and optimize their performance in sports training.

Validation of skinfold equations and alternative methods for the determination of fat-free mass in young athletes

Intoduction

To cross-validate skinfold (SKF) equations, impedance devices, and air-displacement plethysmography (ADP) for the determination of fat-free mass (FFM).

Methods

Male and female youth athletes were evaluated (n = 91[mean ± SD] age: 18.19 ± 2.37 year; height: 172.1 ± 9.8 cm; body mass: 68.9 ± 14.5 kg; BMI: 23.15 ± 3.2 kg m-2; body fat: 19.59 ± 6.9%) using underwater weighing (UWW), ADP, and SKF assessments. A 3-compartment (3C) model (i.e., UWW and total body water) served as the criterion, and alternate body density (Db) estimates from ADP and multiple SKF equations were obtained. Validity metrics were examined to establish each method's performance. Bioelectrical impedance analysis (BIA), bioimpedance spectroscopy (BIS), and the SKF equations of Devrim-Lanpir, Durnin and Womersley, Jackson and Pollock (7-site), Katch, Loftin, Lohman, Slaughter, and Thorland differed from criterion.

Results

For females, Pearson's correlations between the 3C model and alternate methods ranged from 0.51 to 0.92, the Lin's concordance correlation coefficient (CCC) ranged from 0.41 to 0.89, with standard error of the estimate (SEE) ranges of 1.9-4.6 kg. For SKF, the Evans 7-site and J&P 3 Site equations performed best with CCC and SEE values of 0.82, 2.01 kg and 0.78, 2.21 kg, respectively. For males, Pearson's correlations between the 3C model and alternate methods ranged from 0.50 to 0.95, CCC ranges of 0.46-0.94, and SEE ranges of 3.3-7.6 kg. For SKF, the Evans 3-site equation performed best with a mean difference of 1.8 (3.56) kg and a CCC of 0.93.

Discussion

The Evans 7-site and 3-site SKF equations performed best for female and male athletes, respectively. The field 3C model can provide an alternative measure of FFM when necessary.

The effects of betaine supplementation on fluid balance and heat tolerance during passive heat stress in men

INTRODUCTION

Consuming intracellular osmolytes, like betaine (BET), may attenuate symptoms of heat stress. The purpose of this study was to examine the effects of BET supplementation on fluid balance and heat tolerance after a 7-day loading period and during passive heat exposure.

METHODS

A double-blind, placebo controlled, crossover study compared BET or placebo consumption (50 mg·kg-1 , twice daily) for 7 days in young, recreationally active men (N = 11).

RESULTS

During the loading period, no significant interactions were found for any marker of fluid balance between or within conditions. During heat exposure, significant time effects but no condition x time interactions, were found for plasma characteristics (i.e., volume, osmolality, sodium, albumin, and total protein). Plasma volume was significantly increased by min 30 in both conditions (PLA: +6.9. ± 5.0%, BET: +10.2 ± 7.4%) and remained elevated for the remainder of the experimental trial, but was not significantly different between conditions. After 60 min of passive heat exposure, both conditions experienced a similar increase in core temperature (PLA: +0.32 ± 0.22°C, BET: +0.31 ± 0.21°C; p = 0.912).

CONCLUSIONS

Supplemental BET did not improve markers of fluid balance or heat tolerance during 7 days of loading or during passive heat exposure.

Effect of body composition on the athletic performance of soccer referees

Nutrition plays an important role in improving sports performance. The present study aimed at nutritional assessment and examined the relationship between athletic performance and body composition in soccer referees at different levels. The study participants were 120 male soccer referees. 5, 10 and 30 metres (m) sprint tests to measure speed and cooper test for physical fitness were applied in the referees. Participants were divided into two groups as city and class soccer referee. The anthropometric measurements, excluding fat mass (FM) (%), were higher in class referees. Fat mass (%) differences (14⋅1 ± 4⋅28 v. 12⋅3 ± 4⋅41) were statistically significant (P < 0⋅05). Daily energy and nutrient intakes were similar. The inadequacy percentages of energy, vitamin A and calcium were the highest (29⋅2, 30⋅0 and 34⋅2 %, respectively). It was found that a negative significant correlation between FM% and cooper test score (P < 0⋅01; r = -0⋅35), a positive significant correlation between FM% and 5, 10 and 30 m sprint test scores (P < 0⋅01, r = 0⋅38; P < 0⋅01, r = 0⋅38 and P < 0⋅01, r = 0⋅48, respectively). Similarly, there was a negative significant correlation between waist circumference (WC) and cooper test score (P < 0⋅01; r = -0⋅31), a positive significant correlation between WC and 5, 10 and 30 m sprint test scores (P < 0⋅01, r = 0⋅33; P < 0⋅01, r = 0⋅40; P < 0⋅01, r = 0⋅33, respectively). Nutritional recommendations for soccer referees should be made specific to the individual, considering body composition, training intensity and match frequency by a dietician.

Impedance Analysis to Evaluate Nutritional Status in Physiological and Pathological Conditions

A thorough knowledge of body composition assessment techniques is the cornerstone for initiating a customized nutritional program. The second step is to consider the potential of their application in different physiological and pathological conditions and their effectiveness in the management of a monitoring pathway during dietary interventions. To date, bioimpedance analysis is the most effective and reliable method for assessing body composition due to its advantages in terms of speed of execution, non-invasiveness and low cost. Therefore, this review article aims to analyze the main concepts and application areas of bioimpedance measurement techniques, in particular vector frequency-based analysis (BIVA) systems, in order to assess their validity in both physiological and pathological conditions.

Fat-free mass estimation in male elite futsal players: Development and validation of a new bioelectrical impedance-based predictive equation

OBJECTIVES

The present study aimed to develop and cross-validate a futsal-specific bioelectrical equation for estimating fat-free mass (FFM) in male players.

METHODS

A total of 66 futsal players (age 23.3 ± 5.4 years) from the Major Portuguese Futsal League "LIGA PLACARD" and from the 2nd and 3rd National Futsal Leagues were included in this cross-sectional, observational study. The participants underwent a foot-to-hand bioelectrical impedance analysis (BIA) at 50 kHz and completed a dual-energy X-ray absorptiometry (DXA) scan for reference body composition data. The sport-specific model was developed by stepwise multiple regression using bioelectrical raw parameters [resistance (R) and reactance (Xc)] as independent variables. Validation was performed using the PRESS approach, least squares regression, concordance correlation coefficient (CCC) and Bland-Altman analyses.

RESULTS

A BIA-based model was developed for FFM [FFM (kg) = -8.865 + 0.437 * Body Mass (kg) + 0.186 * Xc + 0.415 * stature (cm)²/R (R² = 0.89, standard error of estimation = 2.38 kg)]. Results showed a substantial strength of agreement (CCC = 0.953), an r² of 0.88 with a standard error of estimation equal to 2.31 kg, no mean bias (0.04 kg, p>0.05), low limits of agreement (ranged from -4.5 to 4.6 kg), and no trend (r = -0.170, p = 0.172).

CONCLUSIONS

The present equation is the first to allow for a valid, accurate, and sport-specific assessment of FFM in male futsal players.

Evaluation of raw segmental bioelectrical impedance variables throughout anterior cruciate ligament reconstruction rehabilitation

Background.Raw bioelectrical impedance analysis (BIA) variables are related to physical function in healthy and diseased populations. Therefore, BIA may be an insightful, noninvasive method of assessment to track following anterior cruciate ligament reconstruction (ACLR).Objectives.Evaluate phase angle, reactance and impedance at 50 kHz (PhA₅₀, Xc₅₀, andZ₅₀, respectively) in the operative (OP) and non-operative (NOP) limbs during ACLR rehabilitation.Approach.Seventeen patient (12 M, 5 F; 18.8 ± 4.8 years) clinic reports were evaluated prior to ACLR (PRE), two- (2 W), six- (6 W), and twelve-weeks (12 W) post-ACLR and at return to sport testing (RTS).Setting.All observations occurred during the participant's physical therapy visits.Measurements.A multi-frequency BIA device measured segmental PhA, Xc, andZ. Linear mixed effects models were used to assess any leg and time interaction and changes over leg and time, independently. Any interactions or main effects were considered significant atp< 0.05.Main results.Significant legxtime interactions were observed for each variable. PhA₅₀and Xc₅₀of NOP were higher (p< 0.001) than OP at each time point by an average of by 0.9° and 4.9 Ω, respectively. In OP, PhA₅₀and Xc₅₀decreased from PRE to 2 W and increased from 6 to 12 W and 12 W to RTS (p< 0.01, for all). At RTS, PhA₅₀and Xc₅₀were similar to PRE in OP (p> 0.05). ForZ₅₀, the OP leg did not change over time (p> 0.05).Z₅₀was greater in NOP at 2 and 6 W (p< 0.01, for both). There were differences in PhA₅₀in NOP between PRE and 6 W and from 6 W to RTS (p< 0.05 for both). Xc₅₀did not change (p> 0.05), andZ₅₀PRE was lower than at 2 W (p< 0.05).Significance.A multi-frequency BIA device can detect changes in segmental BIA variables following ACLR.

Body Fat of Basketball Players: A Systematic Review and Meta-Analysis

Background

This study aimed to provide reference values for body fat (BF) of basketball players considering sex, measurement method, and competitive level.

Methods

A systematic literature research was conducted using five electronic databases (PubMed, Web of Science, SPORTDiscus, CINAHL, Scopus). BF values were extracted, with analyses conducted using random-effects models and data reported as percentages with 95% confidence intervals (CI).

Results

After screening, 80 articles representing 4335 basketball players were selected. Pooled mean BF was 13.1% (95% CI 12.4–13.8%) for male players and 20.7% (95% CI 19.9–21.5%) for female players. Pooled mean BF was 21.4% (95% CI 18.4–24.3%) measured by dual-energy X-ray absorptiometry (DXA), 15.2% (95% CI 12.8–17.6%) via bioelectrical impedance analysis (BIA), 12.4% (95% CI 10.6–14.2%) via skinfolds and 20.0% (95% CI 13.4–26.6%) via air displacement plethysmography. Pooled mean BF across competitive levels were 13.5% (95% CI 11.6–15.3%) for international, 15.7% (95% CI 14.2–17.2%) for national and 15.1% (95% CI 13.5–16.7%) for regional-level players. As the meta-regression revealed significant effects of sex, measurement method and competitive level on BF, the meta-analysis was adjusted for these moderators. The final model revealed significant differences in BF between male and female players (p < 0.001). BF measured by DXA was significantly higher than that measured by BIA or skinfolds (p < 0.001). International-level players had significantly lower BF than national and regional-level players (p < 0.05).

Conclusions

Despite the limitations of published data, this meta-analysis provides reference values for BF of basketball players. Sex, measurement method and competitive level influence BF values, and therefore must be taken into account when interpreting results.

Influence of “Sneznik-1/79” Mineral Water on Anthropometric, Functional and Biochemical Parameters of Professional Basketball Players: Role of Oxidative Stress

Adequate hydration represents the balance between the water intake and loss and has an unambiguous significance for public health and it is essential to sustain life. The changes in electrolyte balance which occur during and after training affect on athletes health and performance. Therefore, fluid replacement with adequate mineral composition is of utmost importance. The aim of the present study was to examine the influence of low mineral water from the well Sneznik-1/79 on anthropometric, functional, biochemical parameters and redox status of professional basketball players. In total, 17 male basketball players were included, during the pre-competitive mesocycle, and after the initial testing, they were randomly divided into two groups: group 1 - consumed the commercial drinking water for four weeks (n=7), and group 2 - consumed water from the well Sneznik-1/79 for four weeks (n=10). Determination of the anthropometric, functional, biochemical parameters and redox status was performed. Our results pointed out that consumption of mineral water from the well Sneznik is completely safe from the aspect of affecting various anthropometric, functional and biochemical parameters as well as systemic oxidative stress of professional athletes. In addition, existence of discretely better effects over commercial drinking water indicates that a long period of monitoring may certainly be of interest for further investigation.

A comparative analysis of body composition assessment by BIA and DXA in children with type II and III spinal muscular atrophy

BACKGROUND

Body composition analysis is a valuable tool for assessing and monitoring the nutritional status of children with spinal muscular atrophy (SMA). This study was designed to compare the consistency of bioelectrical impedance analysis (BIA) and dual-energy X-ray absorptiometry (DXA), as the gold standard method for assessing body composition in clinical practice when treating children with type II and III SMA.

METHODS

From 2019 to 2021, we performed a retrospective analysis of body composition by DXA and BIA measurement methods in patients with type II and III SMA treated at a Chinese tertiary children's hospital. Fat mass (FM), muscle mass (MM), bone mineral content (BMC), and visceral fat area (VFA) were compared using paired sample t-tests. We calculated Lin's concordance correlation coefficient (CCC) and Spearman correlation coefficient to verify the correlation between DXA and BIA measurements. Bland-Altman analysis was used to assess the consistency of the two methods.

RESULTS

Fifty-seven children with type II and III SMA were recruited. Compared with body composition measured by DXA, the average FM measured by BIA is significantly lower (P <0.001), whereas the average MM, BMC, and VFA measured by BIA are significantly higher (P < 0.001) in children with SMA. Overall, the difference between MM (Delta [BIA-DAX] = 1.6 kg) and FM (Delta [BIA-DAX] = -1.6 kg) measured by DXA and BIA was minor, whereas the difference of VFA (Delta [BIA-DAX] = -43.5 cm) was significantly large. Correlation analysis indicated a substantial correlation of MM (CCC = 0.96 [95% confidence interval (CI) = 0.93-0.98], r = 0.967 [P < 0.0001]) and FM (CCC = 0.95 [95% CI = 0.92-0.97], r = 0.953 [P < 0.0001]), and poor correlation of BMC (CCC = 0.61 [95% CI = 0.42-0.75], r = 0.612 [P < 0.0001]) and VFA (CCC = 0.54 [95% CI = 0.33-0.70], r = 0.689 [P < 0.0001]) measurements between the two methods. The Bland-Altman analysis suggests that the majority of participants were within LOA. In addition, differences in MM and VFA measurements between BIA and DAX increased according to patients' increasing height, whereas differences in FM and BMC did not differ with height.

CONCLUSION

BIA overestimates MM and underestimates the FM, BMC, and VFA in children with SMA compared with DXA measurements. Overall, the non-invasive, easy-to-use, and repeatable BIA measurements were found to be in good agreement with DXA measurements, especially for FM and MM, which are essential parameters for the nutritional evaluation of children with SMA.

Influence of Upper-Extremity and Lower-Extremity Resistance Exercise on Segmental Body Composition and Body Fluid Estimates

ABSTRACT

Rodriguez, C, Florez, CM, Prather, J, Zaragoza, J, Tinnin, M, Brennan, KL, Taylor, L, and Tinsley, GM. Influence of upper-extremity and lower-extremity resistance exercise on segmental body composition and body fluid estimates. J Strength Cond Res XX(X): 000-000, 2022-The purpose of this analysis was to determine if acute, localized resistance exercise (RE) artificially influences total and regional estimates of body composition from dual-energy X-ray absorptiometry (DXA) and bioelectrical impedance analysis (BIA). Recreationally active male (n = 14) and female (n = 18) subjects completed 3 testing visits: rest (R), upper-extremity RE (U), and lower-extremity RE (L). Dual-energy X-ray absorptiometry scans were completed before exercise and 60 minutes after exercise. Bioelectrical impedance analysis was completed immediately before and after exercise and at 15, 30, and 60 minutes after exercise. Subjects were not allowed to intake fluid during the exercise session or during the postexercise assessment period. The effects of the acute RE session on DXA and BIA estimates were analyzed using linear mixed-effects models with a random intercept for subject. Condition by time interactions were observed for most BIA outcomes. Relative to the reference model (i.e., R condition at baseline), total body water and fat-free mass estimates were, on average, approximately 1 and approximately 1.2 kg higher, in the U condition. In contrast, lower-extremity RE exerted little or no impact on most BIA variables. Some DXA estimates exhibited time main effects, but the magnitude of changes was negligible. An acute bout of localized RE, particularly upper-extremity RE, can artificially influence BIA body fluid and composition estimates, whereas DXA may be robust to the acute biological error introduced by RE. Although body composition assessments should ideally be conducted under standardized conditions, DXA may be suitable in less standardized situations. In addition, BIA is differentially influenced by upper-extremity and lower-extremity resistance exercise.

A New Strategy for Somatotype Assessment Using Bioimpedance Analysis: Stratification According to Sex

Body composition assessment is a relevant element in the biomedical field, in research and daily practice in the medical and nutritional fields, and in the management of athletes. This paper aimed to operate in an Italian sample investigating the possibility of predicting the somatotype from bioimpedance analysis and comparing the predicted results with those obtained from anthropometric measurements. This observational study was conducted with retrospective data collected from 2827 subjects. The somatotype of each subject was calculated both with the Heath−Carter method and by a multiple regression model based on bioimpedance and anthropometric parameters. Somatotypes (endomorph, mesomorph, and ectomorph) were predicted with a high goodness of fit (R2 adjusted > 0.80). Two different somatocharts were obtained from anthropometric measures and bioimpedance parameters and subsequentially compared. Bland−Altman plots showed acceptable accuracy. This study could be a first step in developing a new approach that allows the detection of a subject’s somatotype via bioimpedance analysis, stratified according to sex, with a time-saving and more standardized procedure. It would allow, for example, during the COVID-19 pandemic, to minimize operator−patient contact in having measurements.

The Impact of Physical Activity at School on Body Fat Content in School-Aged Children

(1) Background: Excessive amounts of adipose tissue is a health risk. The aim of this study was to assess the impact of increased physical activity (PA) at school on body fat content in children aged 10 to 12 years over a 2-year follow-up. (2) Methods: Children born in 2007 (n = 245) in two groups, (1) standard PA and (2) increased PA at school, 4 and 10 h of physical education lessons per week, respectively. BIA measurements of body fat content were taken twice a year. Results were interpreted based on children's fat content reference curves. (3) Results: During 2 years of observation, the percentage of children with excessive fat mass (overweight and obese) increased by one-third (from 28.11% to 39.67%) in the group of standard PA, while decreased by one-third in the increased PA one (from 28.92% to 21.00%); with normal fat content increased by one-quarter in the increased PA group (from 59.86% to 76.26%) and decreased by one-tenth in the standard PA one (from 61.61% to 56.29%). (4) Conclusions: An increase in PA at school has a positive impact on children's body fat content. It is recommended to increase the number of physical education lessons at school, which has a positive effect on children's health, reducing the risk of obesity.

Decline in skeletal muscle mass is associated with cognitive decline in type 2 diabetes mellitus

AIMS

To examine the longitudinal association between skeletal muscle mass (SMM) loss and cognitive decline over time in type 2 diabetes mellitus (T2DM).

METHODS

We conducted a prospective cohort study of 453 patients from SMART2D cohort with follow-up intervals of 1.6 to 6.4 years. Baseline and follow-up measurements included bio-impedance analysis (BIA) measure of skeletal muscle mass index (SMI) and Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) measure of cognitive function. We examined the association between annual rate of SMI and RBANS scores using linear regression, adjusting for demographics, education, depression, clinical co-variables and presence of apolipoprotein E4 (APOE) _Ɛ4 allele.

RESULTS

The mean age of participants was 60.3 ± 7.4 years. Compared to patients with Tertile 1 SMI change, the group with greater SMI decline (Tertile 3 SMI change) experienced 0.30 decline in RBANS total score (95%CI -0.57 to -0.03; p = 0.030) in the adjusted analysis. RBANS scores for subdomains in immediate memory and visuo-spatial/construction were lower in Tertile 3 SMI change group with corresponding coefficients -0.54 (95%CI -1.01 to -0.06; p = 0.026), and -0.71 (95%CI -1.30 to -0.12; p = 0.019) respectively.

CONCLUSION

In patients with T2DM, BIA measure of muscle mass loss over time was independently associated with cognitive decline globally and in the domains of memory and visuo-spatial/construction.

Proposal of a New Parameter for Evaluating Muscle Mass in Footballers through Bioimpedance Analysis

The evaluation of muscle mass in athletes correlates with sports performance directly. Bioimpedance vector analysis is a growing method of assessing body composition in athletes because it is independent of predictive formulas containing variables such as body weight, ethnicity, age, and sex. The study aims to propose a new parameter (Levi’s Muscle Index, LMI) that evaluates muscle mass through raw bioelectrical data. A total of 664 male footballers underwent bioimpedance assessment during the regular season. LMI was correlated with body cell mass (BCM) and phase angle (PA) to establish efficacy. The footballers were 24.5 ± 5.8 years old, 180.7 ± 5.9 cm tall and weighed 76.3 ± 7.1 kg. The relationships were: LMI-BMI: r = 0.908, r2 = 0.824, p < 0.001; LMI-PA: r = 0.704, r2 = 0.495, p = 0.009 and PA-BCM: r = 0.491, r2 = 0.241, p < 0.001. The results obtained confirm that LMI could be considered a new parameter that provides reliable information to evaluate the muscle mass of athletes. Furthermore, the higher LMI-BCM relationship than PA-BCM demonstrates specificity for muscle mass evaluation in athletes regardless of body weight, ethnicity, age, and sex.

A Comparative and Sex-Specific Study of Bio-Electrical Impedance Analysis and Dual Energy X-ray Absorptiometry for Estimating Whole-Body and Segmental Body Composition in Healthy Young Adults

Bio-electrical impedance analysis (BIA) and dual-energy X-ray absorptiometry (DXA) are methods to estimate human body composition. This study aimed to compare sex-specific outcomes for estimating segmental and whole-body composition in 83 healthy participants (21.9 ± 1.5 years, 56% men) using Inbody S10 BIA and Norland Elite DXA devices. One-way repeated measures ANOVAs showed significantly lower whole-body fat% and whole-body fat mass values alongside higher whole-body lean mass values resulting from BIA when compared to DXA (both sexes: p < 0.001). In men, whole-body bone mineral content was significantly higher using BIA against DXA (p < 0.001). Regardless of sex, no significant BIA versus DXA difference was found in arm fat mass (men: p = 0.180, women: p = 0.233), whereas significantly lower leg fat mass values were found with BIA versus DXA (both sexes: p < 0.001). Additionally, significantly higher arm lean mass (both sexes: p < 0.001) and leg lean mass (only women: p < 0.001) were found in BIA versus DXA. Moderate to very strong positive associations (p < 0.05) between BIA and DXA outcome measures were found, except for arm fat mass (men: p = 0.904, women: p = 0.130) and leg fat mass (only men: p = 0.845). This study highlights (sex-dependent) differences in corresponding test outcomes between BIA and DXA both at the segmental and whole-body level.

Regional Lean Soft Tissue and Intracellular Water Are Associated with Changes in Lower-Body Neuromuscular Performance: A Pilot Study in Elite Soccer Players

The assessment of body composition over a competitive season provides valuable information that can help sports professionals to evaluate the efficacy of training and nutritional strategies, as well as monitoring athletes’ health status. The purpose of this study was to examine the association of changes in body composition and hydration status with changes in lower-body neuromuscular performance in soccer. Twenty-two male professional soccer players (mean ± SD; age: 26.4 ± 4.8 years; height: 184.3 ± 5.7 cm; body mass: 81.1 ± 6.5 kg; body fat: 11.6 ± 1.5%) took part in the study, for which they were tested at the initial and final stage of the competitive season. Total (whole body) and regional (arms and legs) lean soft tissue (LST) were estimated to obtain the body composition profile. Total body water (TBW) content, including extracellular (ECW) and intracellular (ICW) water, was obtained to monitor players’ hydration status. Countermovement jump (CMJ) height, power, and strength were used to derive players’ lower-body neuromuscular performance. The results showed that changes in legs LST and ICW significantly (p < 0.01) explained (r2 = 0.39) the improvements in CMJ height, power, and strength from the initial to the final stage of the season. Given the high demand imposed on the lower limbs during a soccer season, being more susceptible to change compared to whole-body LST, assessing regional LST and ICW would be more appropriate to provide extended information on players’ readiness.

Can Bodybuilding Peak Week Manipulations Favorably Affect Muscle Size, Subcutaneous Thickness, and Related Body Composition Variables? A Case Study

BACKGROUND

The purpose of this case study was to implement an evidence-based dietary approach to peaking for a bodybuilding competition and monitor its impact on body composition, muscle thickness (MT), intra-to-extra-cellular fluid shifts, subcutaneous thickness (ST), and hydration status. Secondarily, to document any adverse events of this peak week approach in a small, controlled setting. Methods Dietary practices were recorded, and laboratory testing was conducted throughout peak week, including competition morning. Assessments included: dual-energy X-ray absorptiometry (DEXA) for body composition, B-mode ultrasound for MT and ST, bioimpedance spectroscopy (BIS) for total body water (TBW)/intracellular water (ICW)/extracellular water (ECW), and raw BIS data (i.e., resistance, reactance, and phase angle), urine specific gravity (USG) for hydration status, and subjective fullness. Sequential dietary manipulations were made (i.e., CHO depletion/fat loading, CHO/water loading, and a refinement phase) with specific physiological goals. This was reflected in changes observed across all assessments throughout the peak week.

RESULTS

From the carbohydrate-depleted state (three days out) to competition day, we observed increases in lean body mass, MT, TBW (primarily ICW), and subjective fullness. Kendall's Tau B revealed a strong relationship between carbohydrate intake and ∑MT (τ = 0.733, p = 0.056). Additionally, novel ST data demonstrated a 10% reduction for the summation of all seven sites, with some drastic changes in specific regions (e.g., -43% for triceps ST) from three days out to competition day.

CONCLUSIONS

These data suggest that the prototypical goals of bodybuilders' peak week (i.e., increasing muscle fullness, decreasing subcutaneous thickness) to enhance their aesthetics/muscularity presented can be achieved with a drug-free protocol involving dietary manipulations.

Effect of sports training on morphological characteristics in Bulgarian female tennis players

Abstract

Introduction: The intensity of tennis training together with specific exercises may be reflected in the morphological profile of tennis players.

Aim: To evaluate the impact of sports training on the body composition of female tennis players in the 11–13-year competition category.

Materials and methods: The study included an experimental group of 27 female tennis players (mean age 12.43±0.91 years) and 115 schoolgirls (mean age 12.55±0.88 years) as a control group. The following features were investigated: body height, body weight, body mass index, waist-to-hip ratio, muscle mass, fat mass, fat-free mass, percentage of body fat, total body water. The visceral adipose tissue and subcutaneous adipose tissue were computed using the Brambilla’s equation.

Results: In comparison with the control group, tennis players have higher values of muscle mass (p&lt;0.04), total body water (p&lt;0.05), fat-free mass (p&lt;0.04) and lower values of body fat percentage (p&lt;0.04). The rest of the parameters were not found to have statistically significant differences.

Conclusions: We conclude that sports training influences some morphological parameters of female tennis players.

Effect of total body water estimates via bioimpedance on bod pod-based three-compartment body fat models

BACKGROUND/OBJECTIVES

Previous research has compared 2- and 3-compartment (2C and 3C, respectively) models against criterion 4-compartment (4C) models while utilizing the same body density (D_b) method for all measures. This design induces an inherent bias and obscures the added benefit of a 3C model over the simpler 2-compartment (2C) models.

PURPOSE

The purpose of this study was to determine the effect of total body water estimates via single-frequency (SF-BIA) and multi-frequency (MF-BIA) bioimpedance analysis on body fat estimates derived from air displacement plethysmography (ADP)-derived 3C models.

SUBJECTS/METHODS

A sample of 95 females and 82 males (n = 177) participated in this study. Underwater weighing, dual energy X-ray absorptiometry, and bioimpedance spectroscopy were used to calculate percent fat (%Fat) via a criterion 4C model (4C_CRITERION). %Fat was predicted via 3C_MFBIA (ADP and MF-BIA), 3C_SFBIA (ADP and SF-BIA), and a stand-alone 2-compartment (2C) model, based upon ADP, when using Siri and Brozek body density conversion formulas (2C_SIRI and 2C_BROZEK. respectively).

RESULTS

The standard error of estimate (SEE) was lowest for 3C_SFBIA when evaluated in females and males (2.72% and 2.31%, respectively) and highest for 2C_SIRI (3.98% and 3.84%, respectively). Similarly, the total error (TE) for females and males was lowest for 3C_SFBIA (3.21% and 2.67%, respectively) and highest for 2C_SIRI (4.58% and 4.48%, respectively) and 2C_BROZEK (4.65% and 4.33%, respectively).

CONCLUSIONS

Results suggest that SF-BIA and MF-BIA can improve the estimation of %Fat, beyond simpler 2C models, when integrated with ADP in a more advanced 3C model. Furthermore, the present study revealed that 3C_SFBIA was the best overall prediction model based upon TE values. The current study results support the integration of ADP and bioimpedance technology as part of a 3C model for the improvement of %Fat estimates over simpler 2C models.

Comparison of Bioelectrical Impedance Analysis with DXA in Adolescents with Cystic Fibrosis before and after a Resistance Training Intervention

BACKGROUND

The purpose of this pilot study was to compare body composition metrics obtained by two portable bioelectrical impedance analysis (BIA) devices with dual-energy X-ray absorptiometry (DXA) among adolescents with cystic fibrosis (CF) before and after a resistance exercise training program.

METHODS

Participants with CF were assessed using DXA, single-frequency BIA (SFBIA), and multiple-frequency BIA (MFBIA) to quantify percent body fat (%Fat), fat mass (FM), and fat-free mass (FFM) at baseline and after a home-based resistance training intervention comprised of 36, 1 h sessions completed in 12-14 weeks. Repeated measures analysis of variance, paired samples t-tests, Cohen's d effect sizes, and Pearson's correlations were used to compare differences between and within methods at baseline and post-intervention.

RESULTS

Ten participants (15.8 ± 2.2 yr, 60.1 ± 15.1 kg) completed the assessments. At baseline, both SFBIA and MFBIA scales significantly underestimated %Fat and FM and overestimated FFM, with small to moderate effect sizes. Post-intervention, small, non-significant differences were found between DXA and both BIA scales for all body composition metrics. Significant changes in %Fat and FFM were observed with DXA. MFBIA displayed less constant error than SFBIA when compared to DXA for pre- and post-intervention assessments for %Fat (MFBIA: pre and post -2.8 and -0.8 vs. SFBIA: -4.6 and -2.0), FM (-0.4 and -0.4 vs. -3.0 and -1.1), and FFM (+0.8 and +0.6 vs. +3.1 and +1.3). Near-perfect correlations were observed at both time points between DXA and each BIA scale. Conclusions: Portable BIA results should be interpreted with caution, and further validation studies in CF patients are needed prior to clinical use.

Human Serum Betaine and Associated Biomarker Concentrations Following a 14 Day Supplemental Betaine Loading Protocol and during a 28 Day Washout Period: A Pilot Investigation

Several previous investigations have employed betaine supplementation in randomized controlled crossover designs to assess its ostensible ergogenic potential. Nevertheless, prior methodology is predicated on limited pharmacokinetic data and an appropriate betaine-specific washout period is hitherto undescribed. The purpose of the present pilot investigation was therein to determine whether a 28 day washout period was sufficient to return serum betaine concentrations to baseline following a supplementation protocol. Five resistance-trained men (26 ± 6 y) supplemented with 6 g/day betaine anhydrous for 14 days and subsequently visited the lab 10 additional times during a 28 day washout period. Participants underwent venipuncture to assess serum betaine and several other parameters before (PRE) and periodically throughout the washout timeframe (POST0, -4, -7, -10, -13, -16, -19, -22, -25 and -28). All analyses were performed at a significance level of p < 0.05. While analyses failed to detect any differences in any other serum biomarker (p > 0.05), serum betaine was significantly elevated from PRE-to-POST0 (p = 0.047; 2.31 ± 1.05 to 11.1 ± 4.91 µg·mL−1) and was statistically indistinguishable from baseline at POST4 (p = 1.00). Nevertheless, visual data assessment and an inability to assess skeletal muscle concentrations would otherwise suggest that a more conservative 7 day washout period is sufficient to truly return both serum-and-skeletal muscle betaine content to pre-supplementation levels.

Bioelectrical Impedance Vector and Creatine Phosphokinase Changes Induced by a High-Intensity Training Session in Rink Hockey Players

This study aimed to analyze anthropometric and whole-body/muscle-localized bioelectrical impedance vector analysis (BIVA) adaptations and their relation to creatine kinase (CK) as a biomarker of muscle damage in a group of seven male players in the maximum category of professional rink hockey. There were three checkpoint assessments in relation to a high-intensity training session: pre-session (PRE), post-session (POST), and 24 h-post-session (POST24H). The resistance, reactance, and impedance module were adjusted by height (R/h, Xc/h, and Z/h, respectively). The Wilcoxon signed-rank test was used to compare the data at baseline and follow-up, while Spearman correlation was used to explore the relationship between CK and the rest of the parameters. The results registered a decrease in body mass at POST (p = 0.03) and a reestablishment at POST24H (p = 0.02). Whole-body BIVA registered a significant increase in R/h between PRE–to–POST (p = 0.02) and returned to baseline values at POST24H (p = 0.02), which was expected since this parameter is related to hydration processes. Muscle-localized BIVA in the rectus femoris muscle showed an increase in both Xc/h and phase angle in POST (p = 0.04 and p = 0.03, respectively) and a decrease in Xc/h at POST24H (p = 0.02). CK correlated with R/h in the rectus femoris at all the checkpoints (PRE–to–POST: r = 0.75, p = 0.05; PRE–to–POST24H: r = 0.81, p = 0.03; POST–to–POST24H: r = 0.82, p = 0.02). Our results indicate that BIVA is a sensitive methodology to assess general and muscle-localized hydration induced by a high-intensity training session in rink hockey players. A correlation between BIVA and CK was also reported.

Validity of a 3-compartment body composition model using body volume derived from a novel 2-dimensional image analysis program

BACKGROUND/OBJECTIVES

The purpose of this study was: (1) to compare body volume (BV) estimated from a 2-dimensional (2D) image analysis program (BV_IMAGE), and a dual-energy x-ray absorptiometry (DXA) equation (BV_{DXA-Smith-Ryan}) to an underwater weighing (UWW) criterion (BV_UWW); (2) to compare relative adiposity (%Fat) derived from a 3-compartment (3C) model using BV_IMAGE (%Fat_3C-IMAGE), and a 4-compartment (4C) model using BV_{DXA-Smith-Ryan} (%Fat_{4C-DXA-Smith-Ryan}) to a 4C criterion model using BV_UWW (%Fat_4C-UWW).

SUBJECT/METHODS

Forty-eight participants were included (60% male, 22.9 ± 5.0 years, 24.2 ± 2.6 kg/m²). BV_IMAGE was derived using a single digital image of each participant taken from the rear/posterior view. DXA-derived BV was calculated according to Smith-Ryan et al. Bioimpedance spectroscopy and DXA were used to measure total body water and bone mineral content, respectively, in the 3C and 4C models. A standardized mean effect size (ES) assessed the magnitude of differences between models with values of 0.2, 0.5, and 0.8 for small, moderate, and large differences, respectively. Data are presented as mean ± standard deviation.

RESULTS

Near-perfect correlation (r = 0.998, p < 0.001) and no mean differences (p = 0.267) were observed between BV_IMAGE (69.6 ± 11.5 L) and BV_UWW (69.5 ± 11.4 L). No mean differences were observed between %Fat_{4C-DXA-Smith-Ryan} and the %Fat_4C-UWW criterion (p = 0.988). Small mean differences were observed between %Fat_3C-IMAGE and %Fat_4C-UWW (ES = 0.2, p < 0.001). %Fat_3C-IMAGE exhibited smaller SEE and TE, and tighter limits of agreement than %Fat_{4C-DXA-Smith-Ryan}.

CONCLUSIONS

The 2D image analysis program provided an accurate and non-invasive estimate of BV, and subsequently %Fat within a 3C model in generally healthy, young adults.

Body Composition and Bioelectrical-Impedance-Analysis-Derived Raw Variables in Pole Dancers

Few data are available on the body composition of pole dancers. Bioelectrical impedance analysis (BIA) is a method that is used to estimate fat-free mass (FFM) and fat mass (FM), while raw BIA variables, such as the impedance ratio (IR) and phase angle (PhA), are markers of body cell mass and the ratio between extracellular and total body water. The aim of this study was to evaluate the body composition of pole dancers compared to controls, in particular, those raw BIA variables that are considered as markers of muscle composition. Forty female pole dancers and 59 controls participated in the study. BIA was performed on the whole body and upper and lower limbs, separately, at 5, 50, 100 and 250 kHz. The FFM, FFM index, FM and body fat percentage (BF%) were predicted. The bioelectrical impedance indexes IR and PhA were also considered. Pole dancers exhibited higher FFMI and BI indexes and lower BF%. PhA was greater and IRs were smaller in pole dancers than in controls for the whole body and upper limbs. Considering the training level, FFM, whole-body IR and PhA were higher in the professionals than non-professionals. Raw BIA variables significantly differed between the pole dancers and controls, suggesting a higher BCM; furthermore, practicing pole dancing was associated with a greater FFM and lower FM.

Anthropometric profile, body composition, and somatotype in stand-up paddle (SUP) boarding international athletes: a cross-sectional study

Introduction

Introduction: the anthropometric characteristics of international stand-up paddle (SUP) boarders are relevant aspects when it comes to their performance. However, very little research has been carried out within this sport, almost none regarding the body composition and anthropometric characteristics of SUP practitioners. Therefore, the aim of this research will be to describe the anthropometric profile of international SUP boarders. Material and methods: a cross-sectional design in thirty-one international SUP boarders (34.2 ± 12.4 years). Height, body mass, 8 skinfolds, 2 bone diameters, and 5 perimeters were measured, and corrected perimeters were calculated by the same two level-2 internationally certified anthropometrists. Anthropometric measurements were taken following the International Society of Advancement of Kinanthropometry (ISAK) protocol. Body fat mass (FM) was calculated using Carter, Faulkner, Yuhasz, and Withers equations, whereas muscle mass (MM) was estimated using the Lee 2000 equation. Somatotype was calculated by applying the Heath and Carter equation. Bioimpedance (BIA) measurements were also recorded. Results: international SUP athletes had a body mass of 74.6 (6.6) kg, a body fat percentage of 7.6 % (2.1 %) (Carter), 11.3 % (3.5 %) (Faulkner), 7.6 % (2.1 %) (Yuhasz), and 9.0 % (3.6 %) (Whiters), and skinfold sums of 48.2 (20.6) mm for 6, and 57.8 (22.2) mm for 8 skinfolds. Muscle mass was 47.3 % (2.6 %) and somatotype was ecto-mesomorphic with values of 1.9 (0.9) for endomorphy, 5.4 (1.0) for mesomorphy, and 2.4 (0.9) for ectomorphy. BIA results for FM were 11.7 % (4.4 %), and for MM were 50.0 % (2.9 %). Conclusion: these results suggest that a low body fat percentage and high muscle mass are representative characteristics of international stand-up paddlers, as well as a balanced mesomorphic somatotype. According to these, a low skindfold sum and high arm muscle mass may represent key factors for performance in this sport because of their relation to acceleration and stroke force.

Association between Body Fat and Elevated Blood Pressure among Children and Adolescents Aged 7-17 Years: Using Dual-Energy X-ray Absorptiometry (DEXA) and Bioelectrical Impedance Analysis (BIA) from a Cross-Sectional Study in China

To investigate the associations between body fat percentage (BF%) with childhood blood pressure (BP) levels and elevated BP (EBP) risks, and further examine the validity of bioelectrical impedance analysis (BIA), we conducted a cross-sectional study of 1426 children and adolescents aged 7–17 years in Beijing, 2020. EBP, including elevated systolic BP (ESBP) and elevated diastolic BP (EDBP), was defined based on the age- and sex-specific 90th BP reference values of children and adolescents in China. BF% was measured by dual-energy X-ray absorptiometry (DEXA) and BIA devices, and was divided into four quartiles. Log-binomial models were applied to calculate odds ratios (ORs) and 95% confidence intervals (95%CI). Girls tended to have higher BF% levels than boys (p < 0.05). There was 41.0% of girls who developed EBP. High BF% was associated with increased BP levels with ORs of 0.364 (95%CI = 0.283–0.444) for SBP, 0.112 (95%CI = 0.059–0.165) for DBP, and 1.043 (95%CI = 1.027–1.059) for EBP, while the effects were more pronounced in girls and older-aged children. BIA devices agreed well with BF% assessment obtained by DEXA. High BF% might have negative effects on childhood BP. Convenient measurements of body fat might help to assess childhood obesity and potential risks of hypertension.

Generalized bioelectric impedance-based equations underestimate body fluids in athletes

The current study aimed: (i) to external validate total body water (TBW) and extracellular water (ECW) derived from athlete and non‐athlete predictive equations using radioisotope dilution techniques as a reference criterion in male and female athletes; (ii) in a larger sample, to determine the agreement between specific and generalized equations when estimating body fluids in male and female athletes practicing different sports. A total of 1371 athletes (men: n = 921, age 23.9 ± 1.4 y; women: n = 450, age 27.3 ± 6.8 y) participated in this study. All athletes underwent bioelectrical impedance analyses, while TBW and ECW were assessed with dilution techniques in a subgroup of 185 participants (men: n = 132, age 21.7 ± 5.1 y; women: n = 53, age 20.3 ± 4.5 y). Two specific and eight generalized predictive equations were tested. Compared to the criterion methods, no mean bias was observed using the athlete‐specific equations for TBW and ECW (−0.32 to 0.05, p > 0.05) and the coefficient of determination ranged from R² = 0.83 to 0.94. The majority of the generalized predictive equations underestimated TBW and ECW (p < 0.05); R² ranged from 0.66 to 0.89. In the larger sample, all the generalized equations showed lower TBW and ECW values (ranging from −6.58 to −0.19, p < 0.05) than specific predictive equations; except for TBW in female power/velocity (one equation) athletes and team sport (two equations). The use of generalized BIA‐based equations leads to an underestimation of TBW, and ECW compared to athlete‐specific predictive equations. Additionally, the larger sample indicates that generalized equations overall provided lower TBW and ECW compared to the athlete‐specific equations.

Effect of a Short HIIT Program with Specific Techniques on Physical Condition and Activity during Simulated Combat in National-Level Boxers

The present study investigated the effect of an additional short-duration HIIT program using boxing-specific techniques on activity during a simulated competition. Additionally, we investigated the impact on physical fitness, specifically aerobic performance and lower-body muscle power. Sixteen boxers were randomized into a control (n = 8) or experimental groups (n = 8). The experimental protocol consisted of 3 blocks of 5 repetitions of 30s all-out effort, with 6s recovery between repetitions and 1 min rest interval between blocks, conducted 3 days per week for 4 weeks. A two-way (group, two levels; moment, two levels) analysis of variance with repeated measurements in the second factor was used. For the experimental group, there was a change in body mass (ES = −0.13 (trivial)), body fat percentage (ES = −0.12 (trivial)), VO2max (ES = +0.42 (small)), CMJ (ES = +0.12 (trivial)), CMJ-left (ES = −0.11 (trivial)), CMJ-right (ES = +0.22 (trivial)), actions (ES = +0.68 (moderate)), time (ES = −0.29 (small)) and punches (ES = +0.56 (moderate)). For the control group, there was a change in body mass (ES = +0.04 (trivial)), body fat percentage (ES = −0.12 (trivial)), VO2max (ES = +0.11 (trivial)), CMJ (ES = −0.27 (small)), CMJ-left (ES = −0.39 (small)), CMJ-right (ES = +0.08 (trivial)), actions (ES = +0.08 (trivial)), time (ES = −0.65 (moderate)) and punches (ES = −0.57 (moderate)). The punches variable was significant concerning group-by-time interaction (F1,14 = 11.630; p = 0.004; n2 = 0.454). The present study indicated that the addition of a boxing-specific HIIT program is effective to increase the number of punches during a simulated match.

Assessment of anthropometric and body composition characteristics of elite Turkish wrestlers

Study aim: The aim of the study was to determine the anthropometric characteristics of elite Turkish wrestlers according to their weight categories.

Material and methods: In this study, 21 elite male wrestlers (age 22.9 ± 4.0) have been examined according to three weight categories: Light weight, middle weight, heavy weight. Height, weight, arm and calf girth, humerus and femur width, skinfolds (triceps, subscapular, calf, supraspinale) were measured. Arm anthropometry (upper arm muscle area, upper arm fat area, upper arm fat index), somatotype (Heath-Carter somatotype method), and body composition (bio-impedance analysis) were determined.

Results: In the light weight wrestlers, body fat was 9.95% and somatotype 2.15–6.68–1.62; in the middle weight wrestlers, body fat was 11.79% and somatotype 2.83–6.83–1.01; in the heavy weight wrestlers, body fat was 18.63% and somatotype 4.10–8.13–0.53 was determined. While the endomorphy component of the light weight wrestlers was significantly lower than the middle weight and heavy weight wrestlers (p < 0.017), the ectomorphy component was significantly higher than the heavy weight wrestlers (p < 0.05). Fat free mass differed significantly between the three weight categories (p < 0.017), while body fat was higher in heavy weight than both light weight and middle weight (p < 0.017). The weight showed a significant and positive relationship with all anthropometric and body composition values except AFI and ectomorphy (p < 0.05 with mesomorphy, p < 0.01 with others).

Conclusions: As a result of the study, it was determined that wrestlers have anthropometric characteristics specific to their weight categories. While the light weight wrestlers show a balanced mesomorph structure, the heavy weight wrestlers have adapted to the endomorphic mesomorph body type with the increase in fat and fat free mass.

Differences between Active and Semi-Active Students Regarding the Parameters of Body Composition Using Bioimpedance and Magnetic Bioresonance Technologies

The aim of the study was to identify differences in obesity-related parameters between active sports students and semi-active or sedentary students, differentiated by sex, in order to optimize health. The study sample included 286 students, of which the male experimental sample consisted of 86 active sports students, age X ± SD 21.25 ± 0.32 years; height X ± SD 181.08 ± 3.52 cm; control group consisting of 89 semi-active students aged X ± SD 21.07 ± 0.1.13 years; height X ± SD 182.11 ± 1.32. The female experimental sample includes 57 active sports students, age X ± SD 21.02 ± 0.92 years; height X ± SD 167.48 ± 1.34 cm; the control group includes 54 semi-active students aged X ± SD 21.57 ± 0.1.98 years; height X ± SD 168.42 ± 1.76. The study used a thalliometer, Tanita Health Ware software and Quantum Resonance Magnetic Analyzer equipment to investigate height (cm), Body Mass Index (BMI), muscle mass (kg, %), as well as the obesity analysis report, and componential analysis of body and nourishment. The differences registered between the samples of active and semi-active sports subjects were predominantly statistically significant for p < 0.05. The differences registered between the samples of active and semi-active sports subjects were predominantly statistically significant for p < 0.05. The most important parameters regarding obesity and body composition that registered significant differences between the two male groups were in favor of the group of active athletes: triglyceride content of abnormal coefficient 0.844 (CI95% 0.590–1.099), abnormal lipid metabolism coefficient 0.798 (CI95% 1.091–0.504), obesity degree of body (ODB %) 10.290 (CI95% 6.610–13.970), BMI 2.326 (CI95% 1.527–3.126), body fat (kg) 2.042 (CI95% 0.918–3.166), muscle volume (kg) 2.565 (CI95% 1.100–4.031), Lean body weight (kg) 2.841 (CI95% 5.265–0.418). In the case of female samples, the group of active sportswomen registered the biggest differences compared to the group of students who were significantly active in the parameters: abnormal lipid metabolism coefficient 1.063 (CI95% 1.380–0.746), triglyceride content of abnormal coefficient 0.807 (CI95% 0.437–1.178), obesity degree of body (ODB%) 8.082 (CI95% 2.983–13.181), BMI 2.285 (CI95% 1.247–3.324), body fat (kg) 2.586 (CI95% 0.905–4.267), muscle volume (kg) 2.570 (CI95% 0.154–4.985), lean body weight (kg) 4.118 (CI95% 1.160–7.077). The results of the study directly facilitate the understanding of the complexity of the impact of obesity on multiple parameters of body composition and health.

The Utility of Body Composition Assessment in Nutrition and Clinical Practice: An Overview of Current Methodology

Body composition is a key component for maintaining good general health and longevity. It can be influenced by a variety of factors, including genetics, environment, and lifestyle choices. The assessment of body composition is an essential tool for nutrition specialists to effectively evaluate nutritional status and monitor progression during dietary interventions. As humans age, there is a natural increase in fat mass coupled with a gradual decline in lean mass, specifically in bone and muscle mass. Individuals with a high body fat percentage are at a greater risk of cardiovascular diseases, type 2 diabetes, several types of cancer, and early mortality. Significant decreases in bone mineral density signify osteopenia and osteoporosis, while reductions in skeletal muscle mass increase the risk of developing sarcopenia. Moreover, undernutrition exacerbates the effects of many medical conditions and is important to address. Though weight tracking and calculation of BMI are used commonly by clinicians and dietitians, these measures do not provide insight on the relative contributions of fat mass and fat-free mass or the changes in these compartments that may reflect disease risk. Therefore, it is important that healthcare professionals have a critical understanding of body composition assessment and the strengths and limitations of the methods available.

Anthropometric and bioimpedance equations for fat and fat-free mass in Chilean children 7-9 years of age

Assessing children's growth adequately is important due to the necessary prevention of adequate body composition, especially at pre-pubertal age. Simpler measurements such as anthropometry or bioimpedance, using equations validated in Caucasian children, have been demonstrated to overestimate or underestimate fat mass percentage (FM%) or fat-free mass (FFM) in Chilean children. In a sample of 424 children (198 boys and 226 girls) of 7-9 years old, the three component (3C) model was assessed, where total body water was determined by 2H dilution and body volume by air displacement plethysmography, in order to design and validate anthropometry and bioimpedance equations. The FM (%) equation specific for Chilean children was validated as (1·743 × BMI z-score) + (0·727 × triceps skinfold) + (0·385 × biceps skinfold) + 15·985, against the 3C model (R2 0·79). The new FFM equation (kg) generated was (log FFM = (0·018 × age) + (0·047 × sex) + (0·006 × weight) + (0·027 × resistance) + 2·071), with an R2 0·93 (female = 1 and male = 2). The Bland-Altman analysis shows a mean difference of 0·27 (sd 3·5) for the FM% in the whole group as well as 0·004 (sd 0·9) kg is the mean difference for the bioelectrical impedance analysis (BIA) FFM (kg) equation. The new equations for FM (%) and FFM (kg) in Chilean children will provide a simple and valid tool for the assessment of body composition in cohort studies or to assess the impact of nutritional programmes or public policies.

High-Protein Energy-Restriction: Effects on Body Composition, Contractile Properties, Mood, and Sleep in Active Young College Students

Background: It is often advised to ensure a high-protein intake during energy-restricted diets. However, it is unclear whether a high-protein intake is able to maintain muscle mass and contractility in the absence of resistance training. Materials and Methods: After 1 week of body mass maintenance (45 kcal/kg), 28 male college students not performing resistance training were randomized to either the energy-restricted (ER, 30 kcal/kg, n = 14) or the eucaloric control group (CG, 45 kcal/kg, n = 14) for 6 weeks. Both groups had their protein intake matched at 2.8 g/kg fat-free-mass and continued their habitual training throughout the study. Body composition was assessed weekly using multifrequency bioelectrical impedance analysis. Contractile properties of the m. rectus femoris were examined with Tensiomyography and MyotonPRO at weeks 1, 3, and 5 along with sleep (PSQI) and mood (POMS). Results: The ER group revealed greater reductions in body mass (Δ -3.22 kg vs. Δ 1.90 kg, p < 0.001, partial η ² = 0.360), lean body mass (Δ -1.49 kg vs. Δ 0.68 kg, p < 0.001, partial η ² = 0.152), body cell mass (Δ -0.85 kg vs. Δ 0.59 kg, p < 0.001, partial η ² = 0.181), intracellular water (Δ -0.58 l vs. Δ 0.55 l, p < 0.001, partial η ² = 0.445) and body fat percentage (Δ -1.74% vs. Δ 1.22%, p < 0.001, partial η ² = 433) compared to the CG. Contractile properties, sleep onset, sleep duration as well as depression, fatigue and hostility did not change (p > 0.05). The PSQI score (Δ -1.43 vs. Δ -0.64, p = 0.006, partial η ² = 0.176) and vigor (Δ -2.79 vs. Δ -4.71, p = 0.040, partial η ² = 0.116) decreased significantly in the ER group and the CG, respectively. Discussion: The present data show that a high-protein intake alone was not able to prevent lean mass loss associated with a 6-week moderate energy restriction in college students. Notably, it is unknown whether protein intake at 2.8 g/kg fat-free-mass prevented larger decreases in lean body mass. Muscle contractility was not negatively altered by this form of energy restriction. Sleep quality improved in both groups. Whether these advantages are due to the high-protein intake cannot be clarified and warrants further study. Although vigor was negatively affected in both groups, other mood parameters did not change.

Specific Bioelectrical Impedance Vector Analysis Identifies Body Fat Reduction after a Lifestyle Intervention in Former Elite Athletes

Simple Summary

The ability of specific bioelectrical impedance vector analysis (BIVA) to classify subjects according to the percentage of fat mass has been recognized in different cross-sectional studies, but no longitudinal designs have yet been applied. The results of this investigations showed that specific BIVA can be used as a practical solution for assessing body composition management in former overweight/obese athletes. In particular, reductions in bioelectrical vector length adjusted according to the specific BIVA procedure were found to be associated with reductions in percentage of fat mass.

Abstract

Background: specific bioelectrical impedance vector analysis (BIVA) has been proposed as an alternative bioimpedance method for evaluating body composition. This investigation aimed to verify the ability of specific BIVA in identifying changes in fat mass after a 16-week lifestyle program in former athletes. Methods: The 94 participants included in the Champ4life project (clinicaltrials.gov: NCT03031951) were randomized into intervention (n = 49) and control (n = 45) groups, from which 82 athletes completed the intervention (age 43.9 ± 9.2 y; body mass index 31.1 ± 4.6 kg/m²). Fat mass was estimated by dual-energy X-ray absorptiometry. Bioelectric resistance, reactance, phase angle, and vector length were assessed by bioelectric impedance spectroscopy, and the BIVA procedure was applied. Results: A significant (p < 0.05) group x time interaction for fat mass, specific resistance, reactance, and vector length was found. Fat mass and vector length significantly (p < 0.05) decreased in the intervention group, while no change was measured in the control group. Considering the participants as a whole group, changes in vector length were associated with changes in fat mass percentage (r² = 0.246; β = 0.33; p < 0.001) even after adjusting for age, sex, and group (R² = 0.373; β = 0.23; p = 0.002). Conclusions: The specific BIVA approach is suitable to track fat mass changes during an intervention program aimed to reduce body fat in former athletes.

Case study: Effect of surgical metal implant on single frequency bioelectrical impedance measures of an athlete

This case study examined the influence of a surgical metal implant on the bioelectrical impedance analysis (BIA) readings of an athlete. Single-frequency BIA using a tetrapolar electrode configuration was applied to both the right and left sides of a 23-year-old female jumper who had an 8 × 345 mm titanium alloy nail implanted in her left tibia. The metal implant reduced BIA resistance and reactance on the implanted side by 27 and 6 ohms, respectively. This reduction in impedance resulted in a 0.4 kg-1.9 kg increase in the estimate of fat-free mass (FFM) depending on the prediction formula used. There was a concomitant decrease in the estimate of body fat percentage (%BF) with the underestimation ranging from 0.6% to 2.7% BF depending on the prediction formula. A metal implant of substantial size can alter the BIA reading. Technicians should apply BIA to the opposite side of the body when athletes present with a surgical implant in a limb.

Correlation of body composition parameters and anthropometric somatotypes with Prakriti body types among the Meitei adults of Manipur, India

BACKGROUND

Body composition and types are often considered essential health indicators for lifestyle-related disease. Assessment of body type based on tridosha is regarded as a prerequisite in Ayurveda.

AIM

To correlate body compositions and somatotypes with Prakriti body types.

SUBJECTS AND METHODS

A cross-sectional study on 463 adult individuals was done. Anthropometric and body composition parameters were measured. Heath-Carter somatotypes and Prakriti body types were also determined. Tests of association were calculated. Correlation and concordance analysis was also done to infer the correlation between body composition parameters and Prakriti body types.

RESULTS

Kapha Prakriti have significantly higher body weight, body mass index (BMI), body fat percentage and body fat mass. Vata have the lowest mean values in all body composition parameters with Pitta in the intermediate position compared to the other Prakriti types. There is a strong and positive statistical association between Prakriti body types and body composition parameters, except height. Cohen's Kappa analysis reveals there is a fair concordance between Prakriti body types and somatotype.

CONCLUSIONS

Prakriti assessment can explain an individual's fatness as it correlates with body composition parameters and could be used to predict risk susceptibility to various complex disorders.