这项研究确定了几个个体特征和饮食的相对重要性,环境,和运动因素在运动过程中确定汗液[Na+]。收集1944年汗液测试的数据进行回顾性分析。使用逐步多元回归(P<0.05阈值)和T值表示模型中每个因素的相对重要性。根据可用的自变量开发了三个单独的模型:模型1(来自1,304名受试者的1,944次汗水测试);模型2(具有能量消耗的子集:来自607名受试者的1,003次汗水测试);模型3(具有能量消耗的子集,膳食钠,和V♪o2max:n=48)。从模型1和2中的前臂汗液斑块预测全身汗液[Na+],并在模型3中使用全身冲洗直接测量。年龄组没有显著影响,种族/民族,相对湿度,锻炼持续时间,运动前尿液比重,运动液体平衡,或任何型号的饮食或运动钠摄入量。模型1中的重要预测因子(调整后的r2=0.17,P<0.001)是一年中的季节(温暖,T=-6.8),锻炼模式(骑自行车,T=6.8),性别(男性,T=4.9),全身出汗率(T=4.5),和体重(T=-3.0)。模型2中的重要预测因子(调整后的r2=0.19,P<0.001)是一年中的季节(温暖,T=-5.2),能量消耗(T=4.7),锻炼模式(骑自行车,T=3.6),空气温度(T=3.0),和性别(男性,T=2.7)。模型3中唯一显著的预测因子(r2=0.23,P<0.001)是能量消耗(T=3.8)。总之,模型占全身汗液[Na]变化的17%-23%,能量消耗和一年中的季节(代表热适应)是最重要的因素。新的和新的,不同的数据集有助于我们全面了解影响全身汗液[Na+]的因素。主要发现是能量消耗与全身汗液[Na+]直接相关,可能通过能量消耗与全身出汗率(WBSR)之间的关系。温暖的月份(代表热适应)与较低的全身汗液[Na]有关。锻炼模式,空气温度,性也可能有小影响,但其他变量(年龄组,种族/民族,流体平衡,钠摄入量,相对V♪o2max)与全身汗液[Na+]无关联。一起来看,这些模型解释了17%-23%的全身汗液[Na+]变化。
This study determined the relative importance of several individual characteristics and dietary, environmental, and exercise factors in determining sweat [Na+] during exercise. Data from 1944 sweat tests were compiled for a retrospective analysis. Stepwise multiple regression (P < 0.05 threshold for inclusion) and T values were used to express the relative importance of each factor in a model. Three separate models were developed based on available independent variables: model 1 (1,944 sweat tests from 1,304 subjects); model 2 (subset with energy expenditure: 1,003 sweat tests from 607 subjects); model 3 (subset with energy expenditure, dietary sodium, and V̇o2max: n = 48). Whole body sweat [Na+] was predicted from forearm sweat patches in models 1 and 2 and directly measured using whole body washdown in model 3. There were no significant effects of age group, race/ethnicity, relative humidity, exercise duration, pre-exercise urine specific gravity, exercise fluid balance, or dietary or exercise sodium intake on any model. Significant predictors in model 1 (adjusted r2 = 0.17, P < 0.001) were season of the year (warm, T = -6.8), exercise mode (cycling, T = 6.8), sex (male, T = 4.9), whole body sweating rate (T = 4.5), and body mass (T = -3.0). Significant predictors in model 2 (adjusted r2 = 0.19, P < 0.001) were season of the year (warm, T = -5.2), energy expenditure (T = 4.7), exercise mode (cycling, T = 3.6), air temperature (T = 3.0), and sex (male, T = 2.7). The only significant predictor in model 3 (r2 = 0.23, P < 0.001) was energy expenditure (T = 3.8). In summary, the models accounted for 17%-23% of the variation in whole body sweat [Na+] and energy expenditure and season of the year (proxy for heat acclimatization) were the most important factors.NEW & NOTEWORTHY This comprehensive analysis of a large, diverse data set contributes to our overall understanding of the factors that influence whole body sweat [Na+]. The main finding was that energy expenditure was directly associated with whole body sweat [Na+], potentially via the relation between energy expenditure and whole body sweating rate (WBSR). Warmer months (proxy for heat acclimatization) were associated with lower whole body sweat [Na+]. Exercise mode, air temperature, and sex may also have small effects, but other variables (age group, race/ethnicity, fluid balance, sodium intake, relative V̇o2max) had no association with whole body sweat [Na+]. Taken together, the models explained 17%-23% of the variation in whole body sweat [Na+].