Faculty of Medicine, University of Porto, 4200-450 Porto, Portugal.
Coimbra Institute for Clinical and Biomedical Research (iCBR), Faculty of Medicine, University of Coimbra, 3000-370 Coimbra, Portugal.
Nutrients. 2024 May 30;16(11):1709. doi: 10.3390/nu16111709.
Despite decades of literature on (de)hydration in healthy individuals, many unanswered questions remain. To outline research and policy priorities, it is fundamental to recognize the literature trends on (de)hydration and identify current research gaps, which herein we aimed to pinpoint. From a representative sample of 180 (de)hydration studies with 4350 individuals, we found that research is mainly limited to small-scale laboratory-based sample sizes, with high variability in demographics (sex, age, and level of competition); to non-ecological (highly simulated and controlled) conditions; and with a focus on recreationally active male adults (e.g., Tier 1, non-athletes). The laboratory-simulated environments are limiting factors underpinning the need to better translate scientific research into field studies. Although, consistently, dehydration is defined as the loss of 2% of body weight, the hydration status is estimated using a very heterogeneous range of parameters. Water is the most researched hydration fluid, followed by alcoholic beverages with added carbohydrates (CHO). The current research still overlooks beverages supplemented with proteins, amino acids (AA), and glycerol. Future research should invest more effort in "real-world" studies with larger and more heterogeneous cohorts, exploring the entire available spectrum of fluids while addressing hydration outcomes more harmoniously.
尽管数十年来有许多关于健康个体脱水和水合的文献,但仍有许多未解答的问题。为了确定研究和政策重点,首先要认识到脱水和水合相关文献的趋势,并确定当前的研究差距,这也是我们在此处的目标。在对 180 项脱水研究中的 4350 名个体进行的代表性抽样中,我们发现研究主要局限于小规模的实验室样本量,在人口统计学特征(性别、年龄和竞技水平)方面存在很大差异;研究条件是非生态的(高度模拟和控制的);研究对象主要集中在热衷于运动的成年男性(例如,一级运动员,非运动员)。实验室模拟环境是将科学研究转化为实地研究的关键限制因素。尽管脱水被一致定义为体重损失 2%,但脱水状态是使用非常多样化的参数来估计的。水是研究最多的水合液,其次是添加碳水化合物(CHO)的酒精饮料。目前的研究仍然忽略了补充蛋白质、氨基酸(AA)和甘油的饮料。未来的研究应该投入更多的精力在“真实世界”的研究中,使用更大和更多样化的队列,同时更和谐地解决水合作用的结果,探索所有可用的液体。