Bioelectrical Impedance Vector Analysis Discriminates Aerobic Power in Futsal Players: The Role of Body Composition

study aimed to assess the ability of bioelectrical impedance vector analysis (BIVA) in discriminating tness levels in futsal players, exploring the association of body composition and bioelectrical parameters with aerobic power. Methods: Forty-eight professional futsal players (age 23.8 5.3 years) were involved in a cross-sectional study during their pre-season phase. Fat mass (FM) and muscle mass were determined by dual-energy X-ray absorptiometry. VO 2maxwas obtained by indirect calorimetry through a graded exercise test performed on a treadmill. Bioelectrical resistance (R), reactance (Xc), and phase angle (PhA) were directly measured using a foot-to-hand bioimpedance technology at a 50 kHz frequency. Bioelectric R and Xc were standardized for the participants' height and used to plot the bioimpedance vector in the R-Xc graph according to the BIVA approach. Results: The participants divided into groups of VO 2maxlimited by tertiles showed signi cant differences in mean vector position in the R-Xc graph (p< 0.001), where a higher VO 2maxresulted in a longer vector and upper positioning. FM, muscle mass, and PhA differed (p< 0.01) among the athletes grouped by tertiles of VO 2max, where athletes with a greater aerobic power showed a lower percentage of FM and a higher percentage of muscle mass and PhA. FM and PhA were associated with VO 2max(FM: r = 0.658,p< 0.001; PhA: r = 0.493,p< 0.001). These relationships remained signi cant

muscle mass, and PhA differed (p< 0.01) among the athletes grouped by tertiles of VO 2max, where athletes with a greater aerobic power showed a lower percentage of FM and a higher percentage of muscle mass and PhA. FM and PhA were associated with VO 2max(FM: r = 0.658,p< 0.001; PhA: r = 0.493,p< 0.001). These relationships remained signi cant after adjusting for age and body mass (FM: ß = 0.335,p= 0.046; PhA: ß = 0.351,p= 0.003). Conclusions: Bioelectrical impedance vectors positioned on the lower pole of the R-Xc graph identi ed futsal players with a lower VO 2max, while longer vectors corresponded Biology2022,11, 505.

Biology2022,11, 505 2 of 11 to a greater aerobic power. Additionally, PhA, that describes the vector direction, was positively associated with VO 2max, while a higher FM negatively affected VO 2maxin the futsal players. BIVA and PhA evaluation may represent a valid support for screening the aerobic tness level in professional futsal players, when more sophisticated assessment methods are not available. Keywords:athletes; BIA; BIVA; fat mass; phase angle; performance; sports practice; VO 2max 1. Introduction Futsal is a 5-a-side indoor adaptation of soccer that is of cially recognized by the soccer's international governing body (FIFA). Despite increasing in popularity around the world, with over 12 million athletes participating in over 100 nations, the body of literature related to futsal is still scarce. The futsal game is played between two teams, each with ve players: one goalkeeper and four out elders, usually known as defenders, right or left-wingers, and pivots. Competitive matches include periods of intermittent and high-intensity activity that require signi cant physical, technical, and tactical effort [1,2]. The highest metabolic contribution is provided by the aerobic pathway as recently reported in professional futsal players during a simulated futsal game [3]. The maximal oxygen uptake (VO2max) is among the most important determinants for endurance performance, as well as mortality in the general population [4,5]. In this regard, VO2maxis considered the gold standard for assessing aerobic tness. However, it is possible to observe a lack of scienti c data related to aerobic capacity of futsal players. The VO2maxmirrors the maximum amount of oxygen an individual can use to support the oxidative production of energy [6]. The most common and reliable method to assess VO2maxis the cardiopulmonary exercise test, recognized a valuable measure not only to assess the functional status and oxygen availability during exercise training but also to discriminate cardiorespiratory, pulmonary and musculoskeletal function at the same average oxygen consumption [7]. For the rst time, Alvarez et al. [8] showed that high values of VO2maxwere essential for futsal athletes at the professional level, suggesting the relevance of aerobic power in futsal [8]. Subsequently, other authors con rmed that VO2maxmay be assumed

availability during exercise training but also to discriminate cardiorespiratory, pulmonary and musculoskeletal function at the same average oxygen consumption [7]. For the rst time, Alvarez et al. [8] showed that high values of VO2maxwere essential for futsal athletes at the professional level, suggesting the relevance of aerobic power in futsal [8]. Subsequently, other authors con rmed that VO2maxmay be assumed as a discriminative physiological parameter in futsal played at recreational or professional levels [9–11]. Nevertheless, differences in this regard may be a result of genetic factors [4], players role [8], training load [11] or body composition [12]. In general, increased body fat is associated with decreased value of VO2max, while FFM is positively correlated with VO2max[13,14]. Futsal players usually display a low percentage of fat (~15%) with a higher lean mass in high-level players [12]. Taken together, these data might suggest a close relationship between body composition and aerobic power in this sportive population. Body composition parameters can be accurately determined using laboratory tech- niques and procedures [15]. To date, the state-of-art method for determining body fat is identi ed in a speci c formula proposed by Wang et al. [15], which requires the assessment of bone mineral content by dual-energy X-ray absorptiometry (DXA), total body water (TBW) by deuterium dilution, and body volume by air displacement plethysmography. In addition to bone mineral content, for which it is considered the gold standard, DXA allows for accurate estimations of lean soft and muscle tissues [16]. However, these procedures are dif cult to use in the practical context due to their high cost and the need for specialized personnel [17]. The bioelectrical impedance analysis (BIA) has been suggested as an accu- rate method for assessing body composition in athletes, provided that speci c procedures are used [17]. In particular, single frequency BIA provides body composition estimations with a good agreement respect to the aforementioned reference methods [17,18]. However, the most innovative use of BIA consists in the evaluation of the raw bioelectrical parameters through the vector analysis (BIVA) [18,19]. Indeed, the bioimpedance can be considered as the bivariate result of the bioelectrical

c procedures are used [17]. In particular, single frequency BIA provides body composition estimations with a good agreement respect to the aforementioned reference methods [17,18]. However, the most innovative use of BIA consists in the evaluation of the raw bioelectrical parameters through the vector analysis (BIVA) [18,19]. Indeed, the bioimpedance can be considered as the bivariate result of the bioelectrical resistance (R) and reactance (Xc) and graphically represented as a vector into a graph [18,20]. Particularly, the direction of the vector is

Biology2022,11, 505 3 of 11 determinate by the phase angle (PhA), which can be directly calculated as the arctangent of Xc and R [18]. In BIVA, the vector length is representative of the TBW, where a higher uid content corresponds to long vectors. Additionally, PhA is positively associated with the intracellular-to-extracellular water (ICW/ECW) ratio [21] and can be evaluated when more sophisticate methods for determining body uids are not available. The evaluation of BIVA patterns represents a qualitative examination of body composition and avoids the use of prediction equations. Recent literature reviews have shown how BIVA is able to discriminate different body morphologies and identify adaptations related to sports performance in athletes [18,19,22]. To the best of our knowledge, the ability of BIVA and the role of the bioelectrical properties in discriminating aerobic power in futsal players is still unexplored. The use of BIVA could serve as a practical tool suited for nutritionists and futsal coaches and team staff in obtaining information on VO2max. Therefore, the present study aimed to investigate the ability of BIVA in de ning aerobic power in futsal players, clarifying the role of body composition in the VO2maxprediction. Our hypothesis was that BIVA would be informative for aerobic performance and that body composition would be highly correlated with VO2max. 2. Materials and Methods 2.1. Study Design and Participants In line with previous studies to evaluate the ability of BIVA in discriminating physical characteristics, by grouping the participants into tertiles of VO2max, a cross sectional study design is presented. DXA was used as a support to obtain additionally information related to body composition. The sample size was assessed a priori using GPower (version 3.1, Dusseldorf, Germany). It was calculated considering a large effect size (appropriate for calculating effect size within a multiple regression model with continuous independent and dependent variables), with a 5% type I error, 85% power, and an level = 0.05, which resulted in the appropriate sample size for conducting this study. The nal sample was comprised of both elite and sub elite players (age 23.8 5.3 years). The elite players (n = 16) participated

effect size within a multiple regression model with continuous independent and dependent variables), with a 5% type I error, 85% power, and an level = 0.05, which resulted in the appropriate sample size for conducting this study. The nal sample was comprised of both elite and sub elite players (age 23.8 5.3 years). The elite players (n = 16) participated in the Major Portuguese National Futsal League “LIGA PLACARD” and had a sport-speci c training frequency of 5 sessions per week and a game frequency of 1 per week. The sub elite players (n = 32) participated in either the second (n = 16) or third (n = 16) Portuguese National Futsal League and they endured 3 training sessions of ~1.5 h per week plus a weekend game. This investigation was approved by the Faculty of Human Kinetics Institutional Review Board (approval number 37/2021) and conformed to all standards of human research set out in the declaration of Helsinki. After a detailed explanation of the procedures, the participants signed an informed consent. 2.2. Procedures All evaluations of the participants were performed early in the morning (7.00 a.m.) after a 12-h fast and without consumption of alcohol, caffeine/stimulant beverages and at least 12 h from the last exercise session. Body composition assessments were performed at fast, while the cardiopulmonary exercise test (CPET) to access VO2maxwas made in a fed state, with a meal replacement bar (nutritional composition: 231 kcal, 14 g of fat, 12 g of carbohydrate and 13 g of protein) being provided prior to testing. All measurements were performed in the pre-season period following the timeline depicted in Figure. The participants had their weight and height measured wearing minimal clothes and without shoes to the nearest 0.1 kg and 0.1 cm, respectively with a scale and a sta- diometer (Seca, Hamburg, Germany). Body composition was determined through two methodologies: (a) recommended by the manufacturer. The DXA measurements included whole-body

0.1 cm, respectively with a scale and a sta- diometer (Seca, Hamburg, Germany). Body composition was determined through two methodologies: (a) recommended by the manufacturer. The DXA measurements included whole-body

Biology2022,11, 505 4 of 11 estimations of absolute and percentage of fat mass (FM, kg and %) and lean soft tissue, from which muscle mass was calculated using the Kim's formula [16]. (b)Whole-body BIA using a single frequency of 50 kHz device (BIA 101 BIVA®PRO, Akern Systems, Firenze, Italy). After cleaning the skin with isotropy alcohol, four low intrinsic impedance adhesive electrodes (Biatrodes Akern Srl, Firenze, Italy) were placed on the hands back and other four electrodes on the neck of the corresponding feet, according to the guidelines for athletes [18]. From the raw data R and Xc, PhA was calculated as the arctangent of Xc/R 180/ . BIVA was applied standardizing R and Xc for the subjects' stature in meters. After body composition assessments, a maximal incremental test with expired gas analysis (Quark, Cosmed, Italy) was performed on a motor-driven treadmill. After 3 min of warm-up at 5 km h 1 , participants began the test at 6 km h 1 and 2% grade. Each minute the speed increased 1 km h 1 until volitional exhaustion, so that fatigue would be induced within 8–12 min [23]. The highest 30 s average of VO2values reached during the exercise phase of the incremental test were considered to be the VO2max. At the end of the test, all subjects met at least two of the following criteria: respiratory quotient greater than 1.10; heart rate equal to or greater than 95% of predicted maximal HR; and increments in VO2 below 2 mL kg 1 min 1 despite an increase in speed [24]. Figure 1.Timeline of stations performed by the futsal players involved in the study. 2.3. Statistical Analysis Data were analyzed with IBM SPSS Statistics, version 24.0 (IBM Corp., Armonk, NY, USA). Descriptive statistics (mean standard deviation) were calculated for all mea- surements. To verify the normality of the data, the Shapiro-Wilk test was applied. The participants were divided into groups limited by tertiles of VO2max[ rst tertile (T1), sec- ond tertile (T2) and third tertile (T3)] and a one-way ANOVA was performed to evaluate differences in body composition. When a signi cant

statistics (mean standard deviation) were calculated for all mea- surements. To verify the normality of the data, the Shapiro-Wilk test was applied. The participants were divided into groups limited by tertiles of VO2max[ rst tertile (T1), sec- ond tertile (T2) and third tertile (T3)] and a one-way ANOVA was performed to evaluate differences in body composition. When a signi cant F ratio was obtained, the Bonferroni post hoc test was used to assess the differences between the three groups, setting the signif- icance atp< 0.016. The unpaired-sample Hotelling's T 2 test was used to compare the mean impedance vectors among the participants grouped into tertiles. Mahalanobis distance (D 2 ), which represents a multivariate measure of effect and a multivariate measure of distance, was calculated to determine the magnitude of changes in the mean group vectors. D 2 was interpreted according to the following Stevens's [25] guidelines: 0.25–0.49: small; 0.5–0.99; 1: large. Bivariate correlations were performed in preliminary analysis and multiple regression analysis was used to determine if body components were signi cant predictors of VO2maxafter correcting for age and body mass.

Biology2022,11, 505 5 of 11 3. Results No difference for age among the three groups was found (F = 0.41,p= 0.661). Table shows the descriptive characteristics for the athletes divided according to tertiles of VO2max. The athletes with lower VO2max(T1) showed higher body mass and absolute (kg) and relative (%) FM than the other groups. Additionally, athletes included into the T1 reported lower percentage of muscle mass, Xc/H, and PhA than the T3 group. Table 1. Body composition characteristics (mean standard deviation) for the athletes grouped by tertiles of VO 2maxand results of the analysis of variance (ANOVA) are shown. Variable T1, n = 16 (V02max= 42.9 3.7 mL/kg/min) T2, n = 16 (VO2max= 50.1 1.7 mL/kg/min) T3, n = 16 (VO2max= 58.2 3.9 mL/kg/min) ANOVA Body mass (kg) 81.0 0.6 2,3 71.5 7.5 1,3 66.2 5.4 1,2 F = 15.5,p< 0.001 BMI (kg/m 2 ) 24.3 3.1 3 23.3 1.5 22.0 1.6 1 F = 4.64,p= 0.015 DXA Muscle mass (kg) 33.3 3.6 31.2 4.2 31.8 4.2 F = 1.1, p= 0.349 Muscle mass (%) 41.6 6.8 3 43.8 3.9 48.3 7.5 1 F = 4.7,p= 0.014 Fat mass (kg) 17.9 6.0 2,3 12.8 3.0 1,3 9.8 2.1 1,2 F = 16.1,p< 0.001 Fat mass (%) 22.1 5.5 2,3 18.2 3.3 1,3 15.2 2.5 1,2 F = 11.8,p< 0.001 BIA R/H (ohm/m) 279.3 27.3 282.9 18.5 293.4 22.3 F = 1.6, p= 0.212 Xc/H (ohm/m) 33.7 3.0 3 35.5 3.0 38.4 3.3 1 F = 9.3,p< 0.001 Phase angle (degree) 6.9 0.4 3 7.2 0.4 7.5 0.5 1 F = 7.7,p= 0.001 Note: BMI = body mass index, DXA = dual-energy X-ray absorptiometry, BIA = bioelectrical impedance analysis, R/H = resistance standardized for height, Xc/H = reactance standardized for height. 1 = different (p< 0.016) from T1; 2 = different from T2; 3 = different from T3. Figure compartments tissue model. Figure 2. Body composition assessed with DXA according to the three-compartments tissue model in the futsal players grouped by tertiles of VO 2max. Figure VO2maxshowed a mean vector displaced in the higher part of the graph, out of

BIVA effectively discriminates aerobic power in futsal players based on body composition.