The Effects of Dehydration on Metabolic and Neuromuscular Functionality during Cycling

Abstract

This study aimed to determine the effects of dehydration on metabolic and neuromuscular functionality performance during a cycling exercise. Ten male subjects (age 23.4 ± 2.7 years; body weight 74.6 ± 10.4 kg; height 177.3 ± 4.6 cm) cycled at 65% VO2max for 60 min followed by a time-to-trial (TT) at 95% VO2max, in two different conditions: dehydration (DEH) and hydration (HYD). The bioelectrical impedance vector analysis (BIVA) and body weight measurements were performed to assess body fluid changes. Heart rate (HR), energy cost, minute ventilation, oxygen uptake, and metabolic power were evaluated during the experiments. In addition, neuromuscular activity of the vastus medialis and biceps femoris muscles were assessed by surface electromyography. After exercise induced dehydration, the bioimpedance vector significantly lengthens along the major axis of the BIVA graph, in conformity with the body weight change (−2%), that indicates a fluid loss. Metabolic and neuromuscular parameters significantly increased during TT at 95% VO2max with respect to constant workload at 65% of VO2max. Dehydration during a one-hour cycling test and subsequent TT caused a significant increase in HR, while neuromuscular function showed a lower muscle activation in dehydration conditions on both constant workload and on TT. Furthermore, a significant difference between HYD and DEH for TT duration was found.

Bioimpedance Vector Patterns Changes in Response to Swimming Training: An Ecological Approach

“…Another aspect that affects performance and can occur after a training macrocycle is an inadequate recovery of cellular homeostasis, as it can lead to fatigue of motor units and thus the potential recruitment of less efficient motor units in order to maintain performance and power output [9]. Moreover, a balance of fluids and hydration status play an important role, as hypohydration may affect physical function, cognitive performance, and health status [10,11]. However, the taper phase, occurring in the weeks before the major competition of the macrocycle, allows for physiological and psychological recovery from the accumulated training stress through a marked decrease of the training load [12].…”

“…The bioimpedance vector analysis (BIVA), which considers both R and Xc values on the R-Xc graph [20], appears to be more accurate, as it considers both influential variables, PhA and vector length definite, as the BIVA patterns [19]. The use of BIVA in the sports field has grown in recent years [21,22] as its reliability in monitoring the change in fluids during a competitive season [23] as well as in the short term [10,24] has been recognized. In particular, Carrasco-Marginet [25] suggested how BIVA, being a practical and fast method, can be used to monitor hydration status after a swimming competition.…”

Effects of Resistance Training with Different Pyramid Systems on Bioimpedance Vector Patterns, Body Composition, and Cellular Health in Older Women: A Randomized Controlled Trial

“…The aging-associated alterations in body composition, manifested by reduction of skeletal muscle mass and increased body fat, may influence BIVA parameters resulting in PhA decreases [8][9][10][11][12]. In contrast, exercise practice promotes positive changes in BIVA and PhA, followed by benefits on psychological, cognitive, and physical aspects, hydration, nutritional status, muscle function, and quality of life in the elderly [11][12][13][14][15][16][17][18][19][20]. Resistance training (RT) is one of the potential strategies to reverse the adverse effects of aging on cellular integrity and function, improve BIA parameters, and induce changes in the cellular volume of skeletal muscle tissue and cell membrane potential [8][9][10][11][12][13].…”

Body Water Content and Morphological Characteristics Modify Bioimpedance Vector Patterns in Volleyball, Soccer, and Rugby Players

“…Recent studies have focused on evaluating factors influencing the vector position of athletes, including maturity status, [ 7 , 8 , 9 , 10 ] dehydration [ 11 , 12 , 13 , 14 ], and fitness level [ 15 ]. Since the bioelectric properties of body tissues depend on body fluids and cells’ membrane integrity [ 16 ], the main determinant of the vector position in the R-Xc graph is the TBW and the distribution of the fluids among the two compartments (ICW and ECW).…”