背景:水球在水上运动和其他运动中是独特的,因为它包括游泳中典型的循环元素和主要发生在球类运动中的非循环元素。此外,水球需要高水平的技术和战术技能。运动员需要最佳的营养和身体状况来实现高运动成绩,这在很大程度上受到营养习惯的影响。我们的目标是强调与团队中的位置相关的球员营养摄入可能存在的不足。
方法:在本研究中,我们确定了人体测量和身体成分特征,在锦标赛开始之前和常规赛结束时,精英成年男水球运动员(n=19)的饮食习惯和实验室参数,这意味着4个月的干预期。使用生物阻抗分析仪InBody770和3天营养日记进行身体成分特征和营养习惯的分析,分别。使用配对样本t检验来确定锦标赛前后测量的变量之间的差异。使用线性相关计算分析了人体测量和身体成分特征与不同血清参数之间的相关性。使用运动员的人体测量和身体成分特征进行K均值聚类分析。
结果:根据人体测量和身体成分特征,玩家可以分为两个明显不同的集群,显示出与特定游戏位置的关联。第一组包括守门员和边锋球员,而捍卫者,中心,枪手属于二组.我们观察到集群的物理组成存在显着差异,而营养习惯存在轻微但不显着差异。I组球员平均矮5厘米,而他们的平均体重,骨骼肌质量和身体脂肪质量数据降低了19公斤,7公斤,7公斤,分别。我们研究了常规季节前后初始人体测量和身体成分参数与实验室参数变化之间的相关性。因此,我们检测到两个集群之间的许多显著差异,比如葡萄糖和镁水平的变化,这与集群II中的几个身体成分参数有很强的相关性,
结论:人体测量和身体组成特征之间的聚类差异,实验室参数的变化可以帮助将来制定针对特定位置的培训和营养建议。因此,结果可能适用于体育科学精英运动员和体育教练。
BACKGROUND: Water polo is unique among aquatic-and generally other-sports as it includes cyclic elements typical in swimming and acyclic elements occurring mainly in ball games. Moreover, water polo demands high level of technical and tactical skills. Players need an optimal nutritional and physical condition to achieve high athletic performance, which is to a great extend influenced by nutritional habits. We aim to highlight possible shortfalls in players\' nutritional intake in relation to positions played within the team.
METHODS: In the present study, we determined the anthropometric and body composition characteristics, dietary habits and laboratory parameters of elite adult male water polo players (n = 19) before the start of the championship and at the end of the regular season, which meant a 4-month intervention period. Analyses of body composition characteristics and nutritional habits were performed using bioimpedance analyzer InBody 770 and a 3-day nutrition diary, respectively. Paired-sample t-test were used to determine the differences between the variables measured before and after the championship. Correlations between the anthropometric and body composition characteristics and different serum parameters were analyzed using linear correlation calculation. K-mean cluster analysis was performed using the anthropometric and body composition characteristics of the athletes.
RESULTS: Based on anthropometric and body composition characteristics, players can be divided into two significantly different clusters that shows an association with specific playing positions. Cluster I included goalkeepers and wing players, while defenders, centers, and shooters belonged to Cluster II. We observed significant differences in the physical composition and slight but not significant differences in nutritional habits of the clusters. Cluster I players were 5 cm shorter on average, while their mean body weight, skeletal muscle mass and body fat mass data were lower by 19 kg, 7 kg, and 7 kg, respectively. We studied the correlation between initial anthropometric and body composition parameters and the changes in laboratory parameters before and after the regular season. As a result, we detected numerous significant differences between the two clusters, such as the changes in glucose and magnesium levels, which showed a strong correlation with several body composition parameters in cluster II, but did not in cluster I.
CONCLUSIONS: Cluster differences between anthropometric and body compositional characteristics, and the changes in laboratory parameters can help to develop position-specific training and nutritional recommendations in the future. Therefore, the results may be applicable in sport sciences for elite athletes and sports coaches.