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Due to growing interest in the investigation of exercise induced sweat biomarkers to assess an individual's health and the increasing prevalence of tattoos in the world's population, investigators sought to determine whether local sweat concentrations and excretion rates of epidermal growth factor (EGF), interleukin (IL) -1α, IL-6, IL-8, cortisol, glucose, blood urea nitrogen (BUN), and lactate differ between tattooed and contralateral non-tattooed skin during exercise. Sixteen recreational exercisers [female (50%)] (age = 25–48 years) with ≥ 1 unilateral permanent tattoo [median tattoo age = 6 years, IQR = 5] on the arm/torso completed an outdoor group fitness session. There were no significant differences between tattooed and non-tattooed skin for sweat EGF, IL-1α, IL-8, cortisol, glucose, BUN, or lactate concentrations. There were no significant differences between tattooed and non-tattooed skin for sweat EGF, IL-1α, IL-8, cortisol, glucose, BUN, or lactate excretion rate. Findings suggest that permanent tattoos older than 1 year may not impact local sweat EGF, IL-1α, IL-8, cortisol, glucose, BUN, and lactate concentrations or excretion rates during exercise. Clinical trial identifier NCT04920266 was registered on June 9, 2021. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The article presents a study focusing on the association of weight status with mortality in adults with incident diabetes. It states that type 2 diabetes in normal-weight adults with body mass index (BMI) less than 25 is a representation of the metabolically obese normal-weight phenotype with unknown mortality consequences. It showed that the rates of total, cardiovascular, and noncardiovascular mortality were higher in normal-weight persons than in overweight persons. It concludes that adults who were normal weight at the time of incident diabetes had higher mortality incomparison to overweight or obese adults. It states that during the study the normal weight was determined based on BMI and not on measure of adiposity.

The purpose of this study was to determine the effect of hydration status on the change in sweat sodium (Na+), chloride (Cl−), and potassium (K+) concentrations during exercise‐heat stress. Fifteen subjects (Six female, nine male; 29 ± 9 y; 71 ± 14 kg) completed 90 min of cycling (81% HRmax) in the heat (~33°C, 42% rh) with fluid replacement to maintain euhydration (EUH) or without fluid to dehydrate to 2.4 ± 0.4% body mass loss (DEH). Sweat was collected from the forehead (FH), right scapula (SCAP), and left (LVFA) and right (RVFA) ventral forearms using the absorbent pad technique at the beginning (0–30 min) and end of exercise (60–90 min). Sweat was analyzed for Na+, Cl−, and K+ concentrations using ion chromatography. Data are reported as mean ± SD or median ± IQR. There were no differences (Paired t‐tests or Wilcoxon signed‐rank tests) between EUH and DEH in the change in sweat Na+ (FH: 24.3 ± 21.5 vs. 30.8 ± 22.4 mmol/L; SCAP: 9.7 ± 6.2 vs. 9.6 ± 8.2 mmol/L; LVFA: 7.5 ± 6.0 vs. 5.6 ± 5.9 mmol/L; RVFA: 8.2 ± 8.6 vs. 7.8 ± 5.2 mmol/L), sweat Cl−, or sweat K+ at any site (p = 0.07–0.99). The change in sweat electrolyte concentrations during 90 min of exercise in the heat was not significantly influenced by mild dehydration in recreational to moderately‐trained male and female athletes. [ABSTRACT FROM AUTHOR]

Background: Diabetes (DM) is more common among adults with lower socioeconomic status (SES). However, it is not known whether the socioeconomic disparities in DM are obscured by the overall rising prevalence of DM. Our objective was to test whether disparities in diabetes by SES have changed between 1999 and 2010. Methods: Participants from National Health and Nutrition Examination Surveys aged > 20 years with data available to determine DM at each examination were included (n= 11,952). DM was determined as fasting glucose =126 mg/dL or self-report of DM medication use. Educational attainment was used to represent SES and categorized into 4 groups. Predictive marginal probabilities from logistic regression models were used to calculate the age-standardized prevalence of DM by educational category across 3 survey periods (1999-2002, 2003-2006, 2007- 2010). We tested whether the relationship of SES with DM changed over time using interaction terms between education and survey period. Results: The age-standardized prevalence of diabetes was 8.5% (95% CI: 7.3-9.7) in 1999-2002, 9.6% (95% CI: 8.4-10.7) in 2003-2006 and 11.3% (95% CI: 10.0-12.5) in 2007-2010. In each survey period, DM prevalence was highest among adults with the least education (p<0.01) and that relationship did not change over time (p=0.50 for education*year). When we stratified by race/ethnicity, non-Hispanic whites and blacks had the same socioeconomic patterning over time as the total population (Figure). However, education was not associated with DM in Mexican Americans, and this did not change over time. Conclusion: Socioeconomic disparities in DM persist over time; however, the inverse gradient in DM prevalence is not present in Mexican Americans. [ABSTRACT FROM AUTHOR]

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-1β, 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-1β 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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Dehydration has many deleterious effects on cognitive and physical performance as well as physiological function, in the context of sports, industrial work, clinical rehabilitation, and military applications. Because sweat loss and electrolyte loss vary across individuals, conventional sweat testing strategies using absorbent patch techniques are employed in laboratory settings to characterize sweat biomarkers; however, these techniques are not suitable for remote environments. Here, an updated wearable microfluidic sweat testing system targeted for recreational athletes is presented that includes a microfluidic patch accommodating a broad range of sweating rates, and a smartphone app incorporating digital image processing algorithms to enable real‐time analysis under different lighting conditions and patch orientations. Expansive field trials (n = 148 subjects) show significant correlations between the microfluidic patch and standard absorbent patch in measuring sweating rate and sweat chloride concentration during recreational exercise. This validation study demonstrates the applicability of the microfluidic patch and software platform for field testing in recreational athletes. [ABSTRACT FROM AUTHOR]

American football is a high-intensity intermittent sport consisting of various movements and repeated collisions which highlights the importance of adequate recovery from a game to prepare for the next competition. Therefore, the purpose of this study was to determine the time course of recovery markers after a youth American football game. Thirteen male American football youth players were monitored for 7 days after a single football game. Baseline measures were taken 28 hours pregame for lower-body neuromuscular function by countermovement jumps (CMJs) to determine peak power (PP), jump height (JH), flight time (FT), and takeoff velocity (TOV). Saliva was analyzed for cortisol, testosterone, and C-reactive protein (CRP). Perceptual recovery was assessed by the modified profile of mood states (POMS), perceived recovery status (PRS), and a daily wellness questionnaire. These measures were repeated immediately postgame (30 minutes) and at 20, 44, 68, 92, 116, and 140 hours postgame. Compared with baseline values, there was a significant decrease (p<0.05) in CMJ PP, JH, and TOV up to 68 hours postgame and FT 44 hours postgame. No significant difference existed among time points for salivary testosterone and CRP. Cortisol levels significantly increased postgame compared with baseline (p< 0.05). Total mood disturbance, assessed by POMS, and daily wellness markers for energy were significantly decreased (p< 0.05), whereas daily wellness markers for soreness were significantly increased (p< 0.05) immediately after the game. Players exhibited a significant decrease in PRS up to 44 hours postgame (p<0.05), similar to the decrease in neuromuscular function. Neuromuscular function and PRS are impaired for up to 44-68 h postgame. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The aims of this study were to determine: (1) trapped sweat (TS) in basketball uniforms and the effect on sweat loss (SL) estimates during a laboratory-based basketball simulation protocol; (2) the impact of exercise intensity, body mass, age, and SL on TS; and (3) TS during on-court training to assess the ecological validity of the laboratory-based results. Twenty-four recreational/competitive male basketball players (23 ± 10 years, 77.0 ± 16.7 kg) completed three randomized laboratory-based trials (Low, Moderate, and High intensity) consisting of 150-min intermittent exercise. Eighteen elite male players (23 ± 4 years, 92.0 ± 20.6 kg) were observed during coach-led, on-court training. Nude and clothed body mass were measured pre and postexercise to determine TS. Data are mean ± SD. There was a significant effect of intensity on SL and TS (P < 0.001, Low

Several letters to the editor are presented in response to the article "Association of weight status with mortality in adults with incident diabetes," by M.R. Carnethon and colleagues in the previous issue and a response from the author of the article is also presented.