Composición corporal en mujeres deportistas premenopáusicas y postmenopáusicas / Body composition in premenopausal and postmenopausal well-trained females

Objetivo: El propósito fue analizar la influencia de las hormonas sexuales en la composición corporal de deportistas con diferente estatus hormonal. Metodología: 46mujeres eumenorreicas, 41 usuarias de píldora anticonceptiva monofásica y 16mujeres postmenopáusicas bien entrenadas participaron en el estudio. Las voluntarias realizaron un Dual-energy X-ray Absorptiometry scan (DXA) y una bioimpedancia durante la fase folicular temprana y no hormonal, verificado con una analítica. Resultados: La prueba ANCOVA no mostró diferencias ni en las variables medidas con DXA (peso, masa grasa androide y ginoide, masa grasa total y masa libre de grasa) ni en las de bioimpedancia (peso, masa grasa, masa libre de grasa y agua corporal total). Conclusión: Las hormonas sexuales parecen no influir en la composición corporal de mujeres activas. Las mujeres postmenopáusicas activas presentan una distribución de masa grasa similar a las premenopáusicas, lo que podría explicarse por el efecto positivo de la actividad física. (AU)

Purpose: The aim was to analyse the influence of sex hormones on body composition in well-trained females with different hormonal environments.Methods: Sixty-six eumenorrheic, forty-one low-dose-monophasic oral contraceptive users and sixteen postmenopausal well-trained females participated in this study. Volunteers underwent a Dual-energy X-ray Absorptiometry scan (DXA) and a bioimpedance during the early-follicular and the withdrawal phase, verified with blood samples.Results: ANCOVA test reported no differences neither in DXA measurements (weight, fat free mass, fat mass, android and gynoid fat mass) nor in bioimpedance variables (weight, fat free mass, fat mass and total body water) among study groups.Conclusion: Sex hormones seems not to influence body composition in active women. Curiously, premenopausal and postmenopausal active women present the same fat mass distribution. It could be explained by the positive effect exercise has on body composition, and this in turn on preventing cardiovascular and metabolic diseases in this population. (AU)

Variabilidad de la frecuencia cardiaca y ejercicio. ¿Fundamentación fisiológica? / Heart Rate Variability and Exercise, Is There a Physilogical Basis?

Este trabajo pretende dos objetivos: 1º) dar una visión pedagógica de la complejidad relativa al tratamiento matemático de la variabilidad de la frecuencia cardiaca y 2º) analizar si el tratamiento matemático de la señal RR (distancia entre dos ondas R del electrocardiograma) tiene una base fisiológica. Se revisan los mecanismos fisiológicos que explican uno de los fenómenos de base para el análisis de la variabilidad: la arritmia sinusal respiratoria. Se analizan las bases matemáticas, así como los métodos matemáticos de valoración, de la variabilidad. Finalmente, se realiza una revisión del significado fisiológico de las bandas de frecuencia obtenidas mediante las diversas metodologías del tratamiento de la señal RR. No está claro si los métodos matemáticos de tratamiento de la señal RR pueden ser una herramienta de valoración de la función vegetativa. Por ello, debemos tener precaución al interpretar esta variable, sobre todo en el contexto del ejercicio físico y entrenamiento

This work has two objectives: 1) to give a pedagogical view about the complexity of the mathematical treatment of heart rate variability and 2) to analyze whether the mathematical treatment of the RR signal (distance between two R waves shown in an electrocardiogram) has a physiological basis. We reviewed the physiological mechanisms that explain one of the basic phenomena for the analysis of heart rate variability: respiratory sinus arrhythmia. The elementary mathematical bases as well as the mathematical methods of assessing the variability are analyzed. Finally, we offer a critical review of the physiological significance of the frequency bands obtained by the various methodologies of the RR signal processing. It is not clear whether the mathematical methods of RR signal processing can be an assessment tool for vegetative function. Therefore, this variable must be interpreted with caution, especially in the context of physical exercise and training

Validation of the SenseWear armband in circuit resistance training with different loads.

The use of the SenseWear™ armband (SWA), an objective monitor of physical activity, is a relatively new device used by researchers to measure energy expenditure. These monitors are practical, relatively inexpensive and easy-to-use. The aim of the present study was to assess the validity of SWAs for the measurement of energy expenditure (EE) in circuit resistance training (CRT) at three different intensities in moderately active, healthy subjects. The study subjects (17 females, 12 males) undertook CRT at 30, 50 and 70% of the 15 repetition maximum for each exercise component wearing an SWA as well as an Oxycon Mobile (OM) portable metabolic system (a gold standard method for measuring EE). The EE rose as exercise intensity increased, but was underestimated by the SWAs. For women, Bland-Altman plots showed a bias of 1.13 ± 1.48 METs and 32.1 ± 34.0 kcal in favour of the OM system, while for men values of 2.33 ± 1.82 METs and 75.8 ± 50.8 kcal were recorded.