Reference Values and Sensitivity for Different Body Fat Variables Measured by Bioimpedance Method in Female Athletes in Individual Sports: Discriminative and Comparative Study / Valores de Referencia y Sensibilidad para Diferentes Variables de Grasa Corporal Medidas por el Método de Bioimpedancia Eléctrica en Deportistas Femeninas en Deportes Individuales: Estudio Discriminativo y Comparativo

SUMMARY: Athletes differ among themselves and one of the main differences is observed in relation to body shape and composition. Achieving top sports performance requires more standardization in the processes of training and development of a unique methodology for individualizing the control specific adaptation of athletes. The aim of this study is to establish reference data for the most sensitive variables to define the amount and structure of body fat in female athletes in individual sports. The sample included 895 females, divided in: a control group (Cont) of young females (N = 688); International (N = 113), and National level female athletes (N = 94) in 13 individual sports. Four variables described the structureof of body fat: Percentage of body fat (PBF), Body Fat Mass Index (BFMI), Protein Fat Index (PFI) and Index of Body Composition (IBC). Results showed that considering the control group, female athletes have all examined Body Fat variables statistically significantly different (BFMI and PBF are lower, p = 0.011 and p = 0.000, while PFI and IBC are higher, p = 0.000, respectively). Female athletes are also statistically significantly different in relation to the level of competition (p = 0.000), and the investigated variables are responsible for 17.7 % of the variability of the difference between the groups. Competitively more successful female athletes have higher IBC (lower percentage of fat per overall body volume, p = 0.013), as well as, a statistically significantly higher protein mass in relation to body fat mass (PFI, p = 0.018). The most sensitive variables for defining body fat differences between the examined individual sports were IBC, with an influence of 37.9 %, then PFI (32.4 %), then PBF (22.8 %), and finally BFMI, with an influence of 11.4 % on the differences. Based on the results of this study, IBC and PFI are variables that have shown useful scientific-methodological potential for research in the future.

Los deportistas difieren entre sí y una de las principales diferencias se observa en relación a la forma y composición corporal. Alcanzar el máximo rendimiento deportivo requiere una mayor estandarización en los procesos de entrenamiento y en el desarrollo de una metodología única para individualizar el control de adaptación específico de los atletas. El objetivo de este estudio fue establecer datos de referencia de las variables más sensibles para definir la cantidad y estructura de la grasa corporal en mujeres deportistas en deportes individuales. La muestra estuvo compuesta por 895 mujeres, divididas en: un grupo control (Cont) de mujeres jóvenes (N = 688); Atletas femeninas de nivel internacional (N = 113) y nacional (N = 94) en 13 deportes individuales. Cuatro variables describieron la estructura de la grasa corporal: Porcentaje de grasa corporal (PBF), Índice de Masa Grasa Corporal (BFMI), Índice de Proteína Grasa (PFI) e Índice de Composición Corporal (IBC). Los resultados mostraron que, considerando el grupo control, todas las atletas tuvieron diferecias estadísticamente significativas respecto a las variables de grasa corporal (BFMI y PBF son más bajos, p = 0,011 y p = 0,000, mientras que PFI e IBC son más altos, p = 0,000, respectivamente). En relación al nivel de competencia, las atletas femeninas presentan diferencias estadísticamente significativas (p = 0,000), y las variables investigadas son responsables por el 17,7 % de la variabilidad de la diferencia entre los grupos. Las atletas femeninas competitivamente más exitosas tienen un IBC más alto (menor porcentaje de grasa por volumen corporal total, p = 0,013), así como una masa proteica estadísticamente más alta en relación con la masa de grasa corporal (PFI, p = 0,018). Las variables más sensibles para definir las diferencias de grasa corporal entre los deportes individuales examinados fueron IBC, con una influencia del 37,9 %, luego PFI (32,4 %), a seguir PBF (22,8 %) y finalmente BFMI, con una influencia del 11,4 % en las diferencias. En base a los resultados de este estudio, IBC y PFI son las variables que han mostrado un potencial científico-metodológico útil para la investigación en el futuro.

Multidimensional prediction approach in the assessment of male volleyball players' optimal body composition: the case of two elite European teams / Enfoque de predicción multidimensional en la evaluación de la composición corporal óptima de los jugadores de voleibol masculino: el caso de dos equipos europeos de élite

SUMMARY: This research aimed to create a multidimensional equation for predicting an optimal body composition model for elite-level European male volleyball players. The subject sample consisted of 36 elite volleyball players: national team members from two European countries - Slovenia and Serbia - in the 2017 season. Measurement of body composition was carried out using electrical multichannel bioimpedance (BIA - InBody 720), in which 11 variables were used (body height as a longitudinal one, and the other 10 as a system of body composition indicators). Based on the results of descriptive statistics, we can state that elite European male volleyball players are tall, heavy, and with nutritional status at the level of 198.5?6.5 cm, 92.3?5.9 kg and 23.44?1.44 kg•m-2, respectively. The percentage of body fat in the whole sample was 7.91?3.03 %, and the skeletal muscle mass index averaged 12.49?0.80 kg•m-2. For the evaluation and prediction of an optimal body composition model of elite male volleyball players, a multidimensional score (BC_Score) was defined, based on a simple, but sport-specific and playing position-sensitive model equation based on three dominant body characteristics of elite volleyball players: BH, PBF, and SMMI. In this manner, coaches can have a tool for managing the body composition status of players according to position, in terms of a deterministic, fully controlled system.

RESUMEN: Esta investigación tuvo como objetivo crear una ecuación multidimensional para predecir un modelo de composición corporal óptimo para los jugadores de voleibol masculinos europeos de élite. La muestra consistió en 36 jugadores de voleibol de élite, miembros del equipo nacional de dos países, Eslovenia y Serbia, en la temporada 2017. La composición corporal se realizó mediante bioimpedancia eléctrica multicanal (BIA - InBody 720), en la que se utilizaron 11 variables (la altura corporal como longitudinal y las otras 10 como sistema de indicadores de composición corporal). Con base en los resultados de las estadísticas descriptivas, observamos que los jugadores de voleibol de élite europeos son altos, pesados y con un estado nutricional de 198,5 ? 6,5 cm, 92,3 ? 5,9 kg y 23,44 ? 1,44 kg•m-2, respectivamente. El porcentaje de grasa corporal en toda la muestra fue de 7,91 ? 3,03 % y el índice de masa del músculo esquelético promedió 12,49 ? 0,80 kg•m-2. Para la evaluación y predicción de un modelo de composición corporal óptimo de jugadores de voleibol masculino de élite, se definió una puntuación multidimensional (BC_Score), basada en una ecuación de modelo simple, pero específica del deporte y sensible a la posición de juego, basada en tres características corporales dominantes de la élite. Jugadores de voleibol: BH, PBF y SMMI. De esta manera, los entrenadores pueden disponer de una herramienta para gestionar el estado de la composición corporal de los jugadores según la posición, en términos de un sistema determinista y totalmente controlado.

Body Composition in International Sprint Swimmers: Are There Any Relations with Performance?

The paper addresses relations between the characteristics of body composition in international sprint swimmers and sprint performance. The research included 82 swimmers of international level (N = 46 male and N = 36 female athletes) from 8 countries. We measured body composition using multifrequency bioelectrical impedance methods with "InBody 720" device. In the case of male swimmers, it was established that the most important statistically significant correlation with sprint performance is seen in variables, which define the quantitative relationship between their fat and muscle with the contractile potential of the body (Protein-Fat Index, r = 0.392, p = 0.007; Index of Body Composition, r = 0.392, p = 0.007; Percent of Skeletal Muscle Mass, r = 0.392, p = 0.016). In the case of female athletes, statistically significant relations with sprint performance were established for variables that define the absolute and relative amount of a contractile component in the body, but also with the variables that define the structure of body fat characteristics (Percent of Skeletal Muscle Mass, r = 0.732, p = 0.000; Free Fat Mass, r = 0.702, p = 0.000; Fat Mass Index, r = -0.642, p = 0.000; Percent of Body Fat, r = -0.621, p = 0.000). Using Multiple Regression Analysis, we managed to predict swimming performance of sprint swimmers with the help of body composition variables, where the models defined explained 35.1 and 75.1% of the mutual variability of performance, for male and female swimmers, respectively. This data clearly demonstrate the importance of body composition control in sprint swimmers as a valuable method for monitoring the efficiency of body adaptation to training process in order to optimize competitive performance.

Quantitative Contact-Less Estimation of Energy Expenditure from Video and 3D Imagery.

Measurement of energy expenditure is an important tool in sport science and medicine, especially when trying to estimate the extent and intensity of physical activity. However, most approaches still rely on sensors or markers, placed directly on the body. In this paper, we present a novel approach using a fully contact-less, fully automatic method, that relies on computer vision algorithms and widely available and inexpensive imaging sensors. We rely on the estimation of the optical and scene flow to calculate Histograms of Oriented Optical Flow (HOOF) descriptors, which we subsequently augment with the Histograms of Absolute Flow Amplitude (HAFA). Descriptors are fed into regression model, which allows us to estimate energy consumption, and to a lesser extent, the heart rate. Our method has been tested both in lab environment and in realistic conditions of a sport match. Results confirm that these energy expenditures could be derived from purely contact-less observations. The proposed method can be used with different modalities, including near infrared imagery, which extends its future potential.

Does Physical Fatigue Affect Color Vision?

The purpose of this study was to establish whether physical fatigue affects color vision. Thirty healthy participants were included in the study (M:F=15:15), age 25.3±4.4 y, all professional or top amateur athletes. They were exhausted using the Wingate test (WT). Physical fatigue was determined by blood lactate level before the WT and 1, 3, 5, 7 and 10 min after. Color vision was evaluated using the Hardy-Rand-Rittler (HRR) and the Mollon-Reffin Minimalist (MRM) tests before the WT and 5, 10 and 30 min after. Five minutes after the WT 2/30 (6%) showed affected color vision in the protan axis and 25/30 (83%) in the tritan axis. Ten and 30 min after the WT all the participants showed normal color vision in both the deutan and protan axes, whereas 12/30 (40%) and 8/30 (26%), respectively, showed affected color vision in the tritan axis. A gender difference was observed in color vision deficiency and improvement, with female participants being affected more and longer. The study showed that intense physical effort affects color vision with the tritan axis being predominantly affected.

Estimating Energy Expenditure With Multiple Models Using Different Wearable Sensors.

This paper presents an approach to designing a method for the estimation of human energy expenditure (EE). The approach first evaluates different sensors and their combinations. After that, multiple regression models are trained utilizing data from different sensors. The EE estimation method designed in this way was evaluated on a dataset containing a wide range of activities. It was compared against three competing state-of-the-art approaches, including the BodyMedia Fit armband, the leading consumer EE estimation device. The results show that the proposed method outperforms the competition by up to 10.2 percentage points.

Estimation of glomerular filtration rate by MDRD equation in athletes: role of body surface area.

Creatinine-based equations to estimate the glomerular filtration rate (GFR) have recently been advocated over serum creatinine values as a valuable tool to more accurately assess kidney function. The Cockcroft-Gault (CG) equation requires a body weight parameter, whereas the Chronic Kidney Disease-Epidemiology Collaboration (CKD-EPI) and Modification of Diet in Renal Disease (MDRD) Study equations do not. In this study we evaluated the effect of the calculated body surface area (BSA) on MDRD values in professional athletes characterized from different body mass index, gender, and sport discipline. Serum creatinine concentration was measured by Jaffe reaction in 17 male rugby players and 28 male and 26 female swimmers, before the start of training and throughout the competitive season. The values of estimated GFR (eGFR) calculated for creatinine determination by means of CG and CDK-EPI with respect to MDRD formula showed a significant difference in different groups of athletes. The statistical significance was confirmed for BSA-corrected MDRD-derived eGFR values in rugby players and in male swimmers, but not in female swimmers, who showed a BSA close to the "standard" value of 1.73 m(2) traditionally included in MDRD equation. The CG equation can overestimate the eGFR in healthy overweight subjects such as rugby players, whereas the MDRD formula systematically underestimates it. The differences between the two equations increase as a function of BMI, appearing highest in rugby players and lowest in female swimmers. Real BSA correction of the MDRD equation could help to avoid an overestimation of renal excretory function in subjects with increased BSA.

Haematological and iron-related parameters in male and female athletes according to different metabolic energy demands.

We investigated the iron-related haematological parameters in both male and female athletes participating in different sporting disciplines necessitating different metabolic energy demands. A total of 873 athletes (514 males, mean age: 22.08 ± 4.95 years and 359 females, mean age: 21.38 ± 3.88 years) were divided according to gender and to the predominant energy system required for participation in sport (aerobic, anaerobic or mixed) and haematological and iron-related parameters were measured. For both male and female athletes, significant differences related to the predominant energy system were found at a general level: male (Wilks' λ = 0.798, F = 3.047, p < 0.001) and female (Wilks' λ = 0.762, F = 2.591, p < 0.001). According to the ferritin cutoff value of 35 µg/L, whole body iron and sTfR significantly differed in all three groups of male and female athletes (p < 0.001). The percentage of hypochromic erythrocytes in male athletes was significantly higher only in those who required an anaerobic energy source (p < 0.001), whilst in the females hypochromic erythrocytes (p < 0.001) and haemoglobin (anaerobic, p = 0.042; mixed, p = 0.006) were significantly different only in anaerobic and mixed energy source athletes. According to the ferritin cutoff value of 22 µg/L, in females, whole body iron, sTfR and hypochromic erythrocytes were significantly higher in all three groups of athletes than those below the aforementioned cutoff value (p < 0.001). We conclude that the predominant energy system required for participation in sport affects haematological parameters. sTfR and body iron proved to be reliable parameters for monitoring the dynamics of iron metabolism and could contribute to successful iron-deficiency prevention.

Serum creatinine concentrations in male and female elite swimmers. Correlation with body mass index and evaluation of estimated glomerular filtration rate.

BACKGROUND: Creatinine concentrations in athletes could be higher than in sedentary people due to higher muscle mass; a correlation between body mass index (BMI) and creatinine concentrations has been described only in male athletes participating in different sports. METHODS: Elite swimmers (28 males and 26 females) belonging to the National Teams of Slovenia were recruited during the period 1999-2009. The evaluation of possible modifications to serum creatinine concentrations during a single season were performed in 10 males and seven females who were evaluated four times during a season. Serum creatinine was analyzed using the Jaffe method. Pearson's simple correlation analysis was used to test the association between serum creatinine and BMI. Creatinine values and BMI were compared using the unpaired Student t-test. Creatinine values during the different phases of the season were compared using a one-way analysis of variance test. RESULTS: The values for creatinine are related to BMI in male and female swimmers. It should be noted that there is a significant difference (p < 0.001) for estimated glomerular filtration rate (eGFR) values obtained by Cockcroft and Gault equation, but not for the Modification of Diet in Renal Disease (MDRD) equation. The values of creatinine were stable in each athlete during various training cycle periods in the observed competition year. CONCLUSIONS: The study confirms that in a large and representative group of elite swimmers, creatinine concentration is strictly correlated to BMI. The use of creatinine-based eGFR formulas should be used with caution in athletes.