Accuracy of a smart bottle in measuring fluid intake by American football players during pre-season training.

Rehydration is important for athlete performance and recovery. However, it can be challenging to follow appropriate fluid replacement practices due in part to difficulties in tracking fluid intake in real time. The purpose of this study was to determine the accuracy of a smart bottle in measuring fluid intake during exercise. Thirty male American football athletes drank from bottles equipped with a smart cap during outdoor pre-season practices (110 ± 30 min; 29.3 ± 3.0 °C; 75 ± 11% rh). The cap technology included optical sensors, microprocessors, batteries, and wireless connectivity that transmitted fluid volume data to a smartphone application in real-time. Reference measurements of fluid intake from the smart bottle were determined by gravimetry followed by conversion to volume using the density of the fluid consumed. There was no significant mean difference in fluid intake between the smart bottle and reference method (1220 ± 371 ml vs. 1236 ± 389 ml, p = 0.39 paired t test). Bland-Altman 95% limits of agreement between methods was - 212 to 180 ml. The smart bottle provided accurate measurements of fluid intake during exercise in real-world field conditions on a group level and within limits of agreement of - 212 to 180 ml (or approximately ± 15% of overall fluid intake) on an individual level.

Regional and time course differences in sweat cortisol, glucose, and select cytokine concentrations during exercise.

INTRODUCTION: The use of sweat as a biofluid for non-invasive sampling and diagnostics is a popular area of research. However, concentrations of cortisol, glucose, and cytokines have not been described across anatomical regions or as time progresses throughout exercise. PURPOSE: To determine regional and time course differences in sweat cortisol, glucose, and select cytokines (EGF, IFN-γ, IL-1ß, IL-1α, IL-1ra, TNF-α, IL-6, IL-8, and IL-10). METHODS: Sweat was collected with absorbent patches from eight subjects (24-44 y; 80.2 ± 10.2 kg) on the forehead (FH), right dorsal forearm (RDF), right scapula (RS), and right triceps (RT) at 0-25 min, 30-55 min, and 60-85 min during 90 min of cycling (~ 82% HRmax) in a heated chamber (32 °C, 50% rh). ANOVA was used to determine the effect of site and time on outcomes. Data are reported as LS means ± SE. RESULTS: There was a significant effect of location on sweat analyte concentrations with FH having higher values than most other regions for cortisol (FH: 1.15 ± 0.08 ng/mL > RDF: 0.62 ± 0.09 ng/mL and RT: 0.65 ± 0.12 ng/mL, P = 0.02), IL-1ra (P < 0.0001), and IL-8 (P < 0.0001), but lower concentrations for glucose (P = 0.01), IL-1α (P < 0.0001), and IL-10 (P = 0.02). Sweat IL-1ß concentration was higher on the RS than RT (P < 0.0001). Sweat cortisol concentration increased (25 min: 0.34 ± 0.10 ng/mL < 55 min: 0.89 ± 0.07 ng/mL < 85 min: 1.27 ± 0.07 ng/mL; P < 0.0001), while EGF (P < 0.0001), IL-1ra (P < 0.0001), and IL-6 (P = 0.02) concentrations decreased over time. CONCLUSION: Sweat analyte concentrations varied with time of sampling and anatomical region, which is essential information to consider when conducting future work in this area. CLINICAL TRIAL IDENTIFIER: NCT04240951 registered January 27, 2020.

Explaining variation in sweat sodium concentration: effect of individual characteristics and exercise, environmental, and dietary factors.

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+].

Multiple regression analyses to determine the effect of sweating rate and tattoo characteristics on sweat outcome measures during exercise.

PURPOSE: To compare local sweating rate (LSR) and local sweat sodium ([Na+]), chloride ([Cl-]), and potassium ([K+]) concentrations of tattooed skin and contralateral non-tattooed skin during exercise. METHODS: Thirty-three recreational exercisers (17 men, 16 women) with ≥ 1 unilateral permanent tattoo on the torso/arms were tested during cycling, running, or fitness sessions (26 ± 4 °C and 54 ± 13% relative humidity). Forty-eight tattoos with a range of ink colors, ages (3 weeks to 20 years), and densities (10-100%) were included. Before exercise, the skin was cleaned with alcohol and patches (3 M Tegaderm + Pad) were placed on the tattooed and contralateral non-tattooed skin. LSR was calculated from sweat mass (0.80 ± 0.31 g), patch surface area (11.9 cm2), and duration (62 ± 14 min). Sweat [Na+], [Cl-], and [K+] were measured via ion chromatography. RESULTS: Based on the analysis of variance results, there were no differences between tattooed and non-tattooed skin for LSR (1.16 ± 0.52 vs. 1.12 ± 0.53 mg/cm2/min; p = 0.51), sweat [Na+] (60.2 ± 23.5 vs. 58.5 ± 22.7 mmol/L; p = 0.27), sweat [Cl-] (52.1 ± 22.4 vs. 50.6 ± 22.0 mmol/L; p = 0.31), or sweat [K+] (5.8 ± 1.6 vs. 5.9 ± 1.4 mmol/L; p = 0.31). Multiple regression analyses suggested that younger tattoos were associated with higher sweat [Na+] (p = 0.045) and colorful tattoos were associated with higher sweat [Cl-] (p = 0.04) compared with contralateral non-tattooed skin. Otherwise, there were no effects of LSR or tattoo characteristics on regression models for LSR or sweat electrolyte concentrations. CONCLUSION: There were no effects of tattoos on LSR and sweat [K+] during exercise-induced sweating, but tattoo age and color had small effects on sweat [Na+] and sweat [Cl-], respectively. CLINICAL TRIAL IDENTIFIERS: NCT04240951 was registered on January 27, 2020 and NCT04920266 was registered on June 9, 2021.

Sweating Rate and Sweat Chloride Concentration of Elite Male Basketball Players Measured With a Wearable Microfluidic Device Versus the Standard Absorbent Patch Method.

The purpose of this study was to compare a wearable microfluidic device and standard absorbent patch in measuring local sweating rate (LSR) and sweat chloride concentration ([Cl-]) in elite basketball players. Participants were 53 male basketball players (25 ± 3 years, 92.2 ± 10.4 kg) in the National Basketball Association's development league. Players were tested during a moderate-intensity, coach-led practice (98 ± 30 min, 21.0 ± 1.2 °C). From the right ventral forearm, sweat was collected using an absorbent patch (3M Tegaderm™ + Pad). Subsequently, LSR and local sweat [Cl-] were determined via gravimetry and ion chromatography. From the left ventral forearm, LSR and local sweat [Cl-] were measured using a wearable microfluidic device and associated smartphone application-based algorithms. Whole-body sweating rate (WBSR) was determined from pre- to postexercise change in body mass corrected for fluid/food intake (ad libitum), urine loss, and estimated respiratory water and metabolic mass loss. The WBSR values predicted by the algorithms in the smartphone application were also recorded. There were no differences between the absorbent patch and microfluidic patch for LSR (1.25 ± 0.91 mg·cm-2·min-1 vs. 1.14 ±0.78 mg·cm-2·min-1, p = .34) or local sweat [Cl-] (30.6 ± 17.3 mmol/L vs. 29.6 ± 19.4 mmol/L, p = .55). There was no difference between measured and predicted WBSR (0.97 ± 0.41 L/hr vs. 0.89 ± 0.35 L/hr, p = .22; 95% limits of agreement = 0.61 L/hr). The wearable microfluidic device provides similar LSR, local sweat [Cl-], and WBSR results compared with standard field-based methods in elite male basketball players during moderate-intensity practices.

In-Season Nutrition Strategies and Recovery Modalities to Enhance Recovery for Basketball Players: A Narrative Review.

Basketball players face multiple challenges to in-season recovery. The purpose of this article is to review the literature on recovery modalities and nutritional strategies for basketball players and practical applications that can be incorporated throughout the season at various levels of competition. Sleep, protein, carbohydrate, and fluids should be the foundational components emphasized throughout the season for home and away games to promote recovery. Travel, whether by air or bus, poses nutritional and sleep challenges, therefore teams should be strategic about packing snacks and fluid options while on the road. Practitioners should also plan for meals at hotels and during air travel for their players. Basketball players should aim for a minimum of 8 h of sleep per night and be encouraged to get extra sleep during congested schedules since back-to back games, high workloads, and travel may negatively influence night-time sleep. Regular sleep monitoring, education, and feedback may aid in optimizing sleep in basketball players. In addition, incorporating consistent training times may be beneficial to reduce bed and wake time variability. Hydrotherapy, compression garments, and massage may also provide an effective recovery modality to incorporate post-competition. Future research, however, is warranted to understand the influence these modalities have on enhancing recovery in basketball players. Overall, a strategic well-rounded approach, encompassing both nutrition and recovery modality strategies, should be carefully considered and implemented with teams to support basketball players' recovery for training and competition throughout the season.

Predicted sweat rates for group water planning in sport: accuracy and application.

This study tested the accuracy of a novel, limited-availability web application (H2Q™) for predicting sweat rates in a variety of sports using estimates of energy expenditure and air temperature only. The application of predictions for group water planning was investigated for soccer match play. Fourteen open literature studies were identified where group sweat rates were reported (n = 20 group means comprising 230 individual observations from 179 athletes) with fidelity. Sports represented included: walking, cycling, swimming, and soccer match play. The accuracy of H2Q™ sweat rates was tested by comparing to measured group sweat rates using the concordance correlation coefficient (CCC) with 95% confidence interval [CI]. The relative absolute error (RAE) with 95% [CI] was also assessed, whereby the mean absolute error was expressed relative to an acceptance limit of 0.250 L/h. The CCC was 0.98 [0.95, 0.99] and the RAE was 0.449 [0.279, 0.620], indicating that the prediction error was on average 0.112 L/h. The RAE was < 1.0 for 19/20 observations (95%). Drink volumes modeled as a proxy for sweat losses during soccer match play prevented dehydration (< 1% loss of body mass). The H2Q™ web application demonstrated high group sweat prediction accuracy for the variety of sports activities tested. Water planning for soccer match play suggests the feasibility of easily and accurately predicting sweat rates to plan group water needs and promote optimal hydration in training and/or competition.

Nutritional considerations to counteract gastrointestinal permeability during exertional heat stress.

Intestinal barrier integrity and function are compromised during exertional heat stress (EHS) potentially leading to consequences that range from minor gastrointestinal (GI) disturbances to fatal outcomes in exertional heat stroke or septic shock. This mini-review provides a concise discussion of nutritional interventions that may protect against intestinal permeability during EHS and suggests physiological mechanisms responsible for this protection. Although diverse nutritional interventions have been suggested to be protective against EHS-induced GI permeability, the ingestion of certain amino acids, carbohydrates, and fluid per se is potentially effective strategy, whereas evidence for various polyphenols and pre/probiotics is developing. Plausible physiological mechanisms of protection include increased blood flow, epithelial cell proliferation, upregulation of intracellular heat shock proteins, modulation of inflammatory signaling, alteration of the GI microbiota, and increased expression of tight junction (TJ) proteins. Further clinical research is needed to propose specific nutritional candidates and recommendations for their application to prevent intestinal barrier disruption and elucidate mechanisms during EHS.

Skin-interfaced microfluidic system with personalized sweating rate and sweat chloride analytics for sports science applications.

Advanced capabilities in noninvasive, in situ monitoring of sweating rate and sweat electrolyte losses could enable real-time personalized fluid-electrolyte intake recommendations. Established sweat analysis techniques using absorbent patches require post-collection harvesting and benchtop analysis of sweat and are thus impractical for ambulatory use. Here, we introduce a skin-interfaced wearable microfluidic device and smartphone image processing platform that enable analysis of regional sweating rate and sweat chloride concentration ([Cl-]). Systematic studies (n = 312 athletes) establish significant correlations for regional sweating rate and sweat [Cl-] in a controlled environment and during competitive sports under varying environmental conditions. The regional sweating rate and sweat [Cl-] results serve as inputs to algorithms implemented on a smartphone software application that predicts whole-body sweating rate and sweat [Cl-]. This low-cost wearable sensing approach could improve the accessibility of physiological insights available to sports scientists, practitioners, and athletes to inform hydration strategies in real-world ambulatory settings.

Cross-validation of equations to predict whole-body sweat sodium concentration from regional measures during exercise.

We have previously published equations to estimate whole-body (WB) sweat sodium concentration ([Na+ ]) from regional (REG) measures; however, a cross-validation is needed to corroborate the applicability of these prediction equations between studies. The purpose of this study was to determine the validity of published equations in predicting WB sweat [Na+ ] from REG measures when applied to a new data set. Forty-nine participants (34 men, 15 women; 75 ± 12 kg) cycled for 90 min while WB sweat [Na+ ] was measured using the washdown technique. REG sweat [Na+ ] was measured from seven regions using absorbent patches (3M Tegaderm + Pad). Published equations were applied to REG sweat [Na+ ] to determine predicted WB sweat [Na+ ]. Bland-Altman analysis of mean bias (raw and predicted minus measured) and 95% limits of agreement (LOA) were used to compare raw (uncorrected) REG sweat [Na+ ] and predicted WB sweat [Na+ ] to measured WB sweat [Na+ ]. Mean bias (±95% LOA) between raw REG sweat [Na+ ] and measured WB sweat [Na+ ] was 10(±20), 0(±19), 9(±20), 22(±25), 23(±24), 0(±15), -4(±18) mmol/L for the dorsal forearm, ventral forearm, upper arm, chest, upper back, thigh, and calf, respectively. The mean bias (±95% LOA) between predicted WB sweat [Na+ ] and measured WB sweat [Na+ ] was 3(±14), 4(±12), 0(±14), 2(±17), -2(±16), 5(±13), 4(±15) mmol/L for the dorsal forearm, ventral forearm, upper arm, chest, upper back, thigh, and calf, respectively. Prediction equations improve the accuracy of estimating WB sweat [Na+ ] from REG and are therefore recommended for use when determining individualized sweat electrolyte losses.

Permanent tattooing has no impact on local sweat rate, sweat sodium concentration and skin temperature or prediction of whole-body sweat sodium concentration during moderate-intensity cycling in a warm environment.

PURPOSES: This study investigated the impact of permanently tattooed skin on local sweat rate, sweat sodium concentration and skin temperature and determined whether tattoos alter the relationship between local and whole-body sweat sodium concentration. METHODS: Thirteen tattooed men (27 ± 6 years) completed a 1 h (66 ± 4% of [Formula: see text]) cycling trial at 32 °C, 35% relative humidity. Sweat rate and sweat sodium concentration were measured using the whole-body washdown and local absorbent patch techniques. Patches and skin-temperature probes were applied over the right/left thighs and tattooed/non-tattooed (contralateral) regions. RESULTS: Local sweat rates did not differ (p > 0.05) between the right (1.11 ± 0.38) and left (1.21 ± 0.37) thighs and the permanently tattooed (1.93 ± 0.82) and non-tattooed (1.72 ± 0.81 mg cm-2 min-1) regions. There were no differences in local sweat sodium concentration between the right (58.2 ± 19.4) and left (55.4 ± 20.3) thighs and the permanently tattooed (73.0 ± 22.9) and non-tattooed (70.2 ± 18.9 mmol L-1) regions. Difference in local skin temperature between the right and left thighs (- 0.043) was similar to that between the permanently tattooed and non-tattooed (- 0.023 °C) regions. Prediction of whole-body sweat sodium concentration for the permanently tattooed (41.0 ± 6.7) and the non-tattooed (40.2 ± 5.3 mmol L-1) regions did not differ. CONCLUSION: Permanent tattoos do not alter local sweat rate, sweat sodium concentration or local skin temperature during moderate-intensity cycling exercise in a warm environment. Results from a patch placed over a tattooed surface correctly predicts whole-body sweat sodium concentration from an equation developed from a non-tattooed region.

Physiological mechanisms determining eccrine sweat composition.

PURPOSE: The purpose of this paper is to review the physiological mechanisms determining eccrine sweat composition to assess the utility of sweat as a proxy for blood or as a potential biomarker of human health or nutritional/physiological status. METHODS: This narrative review includes the major sweat electrolytes (sodium, chloride, and potassium), other micronutrients (e.g., calcium, magnesium, iron, copper, zinc, vitamins), metabolites (e.g., glucose, lactate, ammonia, urea, bicarbonate, amino acids, ethanol), and other compounds (e.g., cytokines and cortisol). RESULTS: Ion membrane transport mechanisms for sodium and chloride are well established, but the mechanisms of secretion and/or reabsorption for most other sweat solutes are still equivocal. Correlations between sweat and blood have not been established for most constituents, with perhaps the exception of ethanol. With respect to sweat diagnostics, it is well accepted that elevated sweat sodium and chloride is a useful screening tool for cystic fibrosis. However, sweat electrolyte concentrations are not predictive of hydration status or sweating rate. Sweat metabolite concentrations are not a reliable biomarker for exercise intensity or other physiological stressors. To date, glucose, cytokine, and cortisol research is too limited to suggest that sweat is a useful surrogate for blood. CONCLUSION: Final sweat composition is not only influenced by extracellular solute concentrations, but also mechanisms of secretion and/or reabsorption, sweat flow rate, byproducts of sweat gland metabolism, skin surface contamination, and sebum secretions, among other factors related to methodology. Future research that accounts for these confounding factors is needed to address the existing gaps in the literature.

Physiology of sweat gland function: The roles of sweating and sweat composition in human health.

The purpose of this comprehensive review is to: 1) review the physiology of sweat gland function and mechanisms determining the amount and composition of sweat excreted onto the skin surface; 2) provide an overview of the well-established thermoregulatory functions and adaptive responses of the sweat gland; and 3) discuss the state of evidence for potential non-thermoregulatory roles of sweat in the maintenance and/or perturbation of human health. The role of sweating to eliminate waste products and toxicants seems to be minor compared with other avenues of excretion via the kidneys and gastrointestinal tract; as eccrine glands do not adapt to increase excretion rates either via concentrating sweat or increasing overall sweating rate. Studies suggesting a larger role of sweat glands in clearing waste products or toxicants from the body may be an artifact of methodological issues rather than evidence for selective transport. Furthermore, unlike the renal system, it seems that sweat glands do not conserve water loss or concentrate sweat fluid through vasopressin-mediated water reabsorption. Individuals with high NaCl concentrations in sweat (e.g. cystic fibrosis) have an increased risk of NaCl imbalances during prolonged periods of heavy sweating; however, sweat-induced deficiencies appear to be of minimal risk for trace minerals and vitamins. Additional research is needed to elucidate the potential role of eccrine sweating in skin hydration and microbial defense. Finally, the utility of sweat composition as a biomarker for human physiology is currently limited; as more research is needed to determine potential relations between sweat and blood solute concentrations.

Practical Hydration Solutions for Sports.

Personalized hydration strategies play a key role in optimizing the performance and safety of athletes during sporting activities. Clinicians should be aware of the many physiological, behavioral, logistical and psychological issues that determine both the athlete's fluid needs during sport and his/her opportunity to address them; these are often specific to the environment, the event and the individual athlete. In this paper we address the major considerations for assessing hydration status in athletes and practical solutions to overcome obstacles of a given sport. Based on these solutions, practitioners can better advise athletes to develop practices that optimize hydration for their sports.

Normative data for sweating rate, sweat sodium concentration, and sweat sodium loss in athletes: An update and analysis by sport.

The purpose of this study was to expand our previously published sweat normative data/analysis (n = 506) to establish sport-specific normative data for whole-body sweating rate (WBSR), sweat [Na+], and rate of sweat Na+ loss (RSSL). Data from 1303 athletes were compiled from observational testing (2000-2017) using a standardized absorbent sweat patch technique to determine local sweat [Na+] and normalized to whole-body sweat [Na+]. WBSR was determined from change in exercise body mass, corrected for food/fluid intake and urine/stool loss. RSSL was the product of sweat [Na+] and WBSR. There were significant differences between sports for WBSR, with highest losses in American football (1.51 ± 0.70 L/h), then endurance (1.28 ± 0.57 L/h), followed by basketball (0.95 ± 0.42 L/h), soccer (0.94 ± 0.38 L/h) and baseball (0.83 ± 0.34 L/h). For RSSL, American football (55.9 ± 36.8 mmol/h) and endurance (51.7 ± 27.8 mmol/h) were greater than soccer (34.6 ± 19.2 mmol/h), basketball (34.5 ± 21.2 mmol/h), and baseball (27.2 ± 14.7 mmol/h). After ANCOVA, significant between-sport differences in adjusted means for WBSR and RSSL remained. In summary, due to the significant sport-specific variation in WBSR and RSSL, American football and endurance have the greatest need for deliberate hydration strategies. Abbreviations: WBSR: whole body sweating rate; SR: sweating rate; Na+: sodium; RSSL: rate of sweat sodium loss.

Narrative Review of Hydration and Selected Health Outcomes in the General Population.

Although adequate hydration is essential for health, little attention has been paid to the effects of hydration among the generally healthy population. This narrative review presents the state of the science on the role of hydration in health in the general population, specifically in skin health, neurological function (i.e., cognition, mood, and headache), gastrointestinal and renal functions, and body weight and composition. There is a growing body of evidence that supports the importance of adequate hydration in maintaining proper health, especially with regard to cognition, kidney stone risk, and weight management. However, the evidence is largely associative and lacks consistency, and the number of randomized trials is limited. Additionally, there are major gaps in knowledge related to health outcomes due to small variations in hydration status, the influence of sex and sex hormones, and age, especially in older adults and children.

Exercise intensity effects on total sweat electrolyte losses and regional vs. whole-body sweat [Na+], [Cl-], and [K+].

PURPOSE: To quantify total sweat electrolyte losses at two relative exercise intensities and determine the effect of workload on the relation between regional (REG) and whole body (WB) sweat electrolyte concentrations. METHODS: Eleven recreational athletes (7 men, 4 women; 71.5 ± 8.4 kg) completed two randomized trials cycling (30 °C, 44% rh) for 90 min at 45% (LOW) and 65% (MOD) of VO2max in a plastic isolation chamber to determine WB sweat [Na+] and [Cl-] using the washdown technique. REG sweat [Na+] and [Cl-] were measured at 11 REG sites using absorbent patches. Total sweat electrolyte losses were the product of WB sweat loss (WBSL) and WB sweat electrolyte concentrations. RESULTS: WBSL (0.86 ± 0.15 vs. 1.27 ± 0.24 L), WB sweat [Na+] (32.6 ± 14.3 vs. 52.7 ± 14.6 mmol/L), WB sweat [Cl-] (29.8 ± 13.6 vs. 52.5 ± 15.6 mmol/L), total sweat Na+ loss (659 ± 340 vs. 1565 ± 590 mg), and total sweat Cl- loss (931 ± 494 vs. 2378 ± 853 mg) increased significantly (p < 0.05) from LOW to MOD. REG sweat [Na+] and [Cl-] increased from LOW to MOD at all sites except thigh and calf. Intensity had a significant effect on the regression model predicting WB from REG at the ventral wrist, lower back, thigh, and calf for sweat [Na+] and [Cl-]. CONCLUSION: Total sweat Na+ and Cl- losses increased by ~ 150% with increased exercise intensity. Regression equations can be used to predict WB sweat [Na+] and [Cl-] from some REG sites (e.g., dorsal forearm) irrespective of intensity (between 45 and 65% VO2max), but other sites (especially ventral wrist, lower back, thigh, and calf) require separate prediction equations accounting for workload.

Skin-interfaced systems for sweat collection and analytics.

Recent interdisciplinary advances in materials, mechanics, and microsystem designs for biocompatible electronics, soft microfluidics, and electrochemical biosensors establish the foundations for emerging classes of thin, skin-interfaced platforms capable of capturing, storing, and performing quantitative, spatiotemporal measurements of sweat chemistry, instantaneous local sweat rate, and total sweat loss. This review summarizes scientific and technical progress in this area and highlights the implications in real time and ambulatory modes of deployment during physical activities across a broad range of contexts in clinical health, physiology research, fitness/wellness, and athletic performance.

Body map of regional vs. whole body sweating rate and sweat electrolyte concentrations in men and women during moderate exercise-heat stress.

This study determined the relations between regional (REG) and whole body (WB) sweating rate (RSR and WBSR, respectively) as well as REG and WB sweat Na+ concentration ([Na+]) during exercise. Twenty-six recreational athletes (17 men, 9 women) cycled for 90 min while WB sweat [Na+] was measured using the washdown technique. RSR and REG sweat [Na+] were measured from nine regions using absorbent patches. RSR and REG sweat [Na+] from all regions were significantly ( P < 0.05) correlated with WBSR ( r = 0.58-0.83) and WB sweat [Na+] ( r = 0.74-0.88), respectively. However, the slope and y-intercept of the regression lines for most models were significantly different than 1 and 0, respectively. The coefficients of determination ( r2) were 0.44-0.69 for RSR predicting WBSR [best predictors: dorsal forearm ( r2 = 0.62) and triceps ( r2 = 0.69)] and 0.55-0.77 for REG predicting WB sweat [Na+] [best predictors: ventral forearm ( r2 = 0.73) and thigh ( r2 = 0.77)]. There was a significant ( P < 0.05) effect of day-to-day variability on the regression model predicting WBSR from RSR at most regions but no effect on predictions of WB sweat [Na+] from REG. Results suggest that REG cannot be used as a direct surrogate for WB sweating responses. Nonetheless, the use of regression equations to predict WB sweat [Na+] from REG can provide an estimation of WB sweat [Na+] with an acceptable level of accuracy, especially using the forearm or thigh. However, the best practice for measuring WBSR remains conventional WB mass balance calculations since prediction of WBSR from RSR using absorbent patches does not meet the accuracy or reliability required to inform fluid intake recommendations. NEW & NOTEWORTHY This study developed a body map of regional sweating rate and regional (REG) sweat electrolyte concentrations and determined the effect of within-subject (bilateral and day-to-day) and between-subject (sex) factors on the relations between REG and the whole body (WB). Regression equations can be used to predict WB sweat Na+ concentration from REG, especially using the forearm or thigh. However, prediction of WB sweating rate from REG sweating rate using absorbent patches does not reach the accuracy or reliability required to inform fluid intake recommendations.

Sweat Sodium, Potassium, and Chloride Concentrations Analyzed Same Day as Collection Versus After 7 Days Storage in a Range of Temperatures.

The purpose of this study was to determine the effect of storage temperature on sodium ([Na+]), potassium ([K+]), and chloride ([Cl-]) concentrations of sweat samples analyzed 7 days after collection. Using the absorbent patch technique, 845 sweat samples were collected from 39 subjects (32 ± 7 years, 72.9 ± 10.5 kg) during exercise. On the same day as collection (PRESTORAGE), 609 samples were analyzed for [Na+], [Cl-], and [K+] by ion chromatography (IC) and 236 samples were analyzed for [Na+] using a compact ion-selective electrode (ISE). Samples were stored at one of the four conditions: -20 °C (IC, n = 138; ISE, n = 60), 8 °C (IC, n = 144; ISE, n = 59), 23 °C (IC, n = 159; ISE, n = 59), or alternating between 8 °C and 23 °C (IC, n = 168; ISE, n = 58). After 7 days in storage (POSTSTORAGE), samples were reanalyzed using the same technique as PRESTORAGE. PRESTORAGE sweat electrolyte concentrations were highly related to that of POSTSTORAGE (intraclass correlation coefficient: .945-.989, p < .001). Mean differences (95% confidence intervals) between PRESTORAGE and POSTSTORAGE were statistically, but not practically, significant for most comparisons: IC [Na+]: -0.5(0.9) to -2.1(0.9) mmol/L; IC [K+]: -0.1(0.1) to -0.2(0.1) mmol/L; IC [Cl-]: -0.4(1.4) to -1.3(1.3) mmol/L; ISE [Na+]: -2.0(1.1) to 1.3(1.1) mmol/L. Based on typical error of measurement results, 95% of the time PRESTORAGE and POSTSTORAGE sweat [Na+], [K+], and [Cl-] by IC analysis fell within ±7-9, ±0.6-0.7, and ±9-13 mmol/L, respectively, while sweat [Na+] by ISE was ±6 mmol/L. All conditions produced high reliability and acceptable levels of agreement in electrolyte concentrations of sweat samples analyzed on the day of collection versus after 7 days in storage.