The study aimed to compare thermal sensation in response to a fixed warm stimulus across 31 body locations in resting and active males and females. Twelve males (20.6 ± 1.0 years, 78.1 ± 15.6 kg, 180 ± 8.9 cm, 34.4 ± 5.2 ml kg⁻¹ min⁻¹) and 12 females (20.6 ± 1.4 years, 62.9 ± 5.5 kg, 167 ± 5.7 cm, 36.5 ± 6.6 ml kg⁻¹ min⁻¹) rested in a thermoneutral (22.2 ± 2.2 °C, 35.1 ± 5.8 % RH) room whilst a thermal probe (25 cm²), set at 40 °C was applied in a balanced order to 31 locations across the body. Participants reported their thermal sensation 10 s after initial application. Following this, participants began cycling at 50 % \(\dot{V}{\text{O}}_{{ 2 {\text{max}}}}\) for 20 min, which was then lowered to 30 % \(\dot{V}{\text{O}}_{{ 2 {\text{max}}}}\) and the sensitivity test repeated. Females had significantly warmer magnitude sensations than males at all locations (4.7 ± 1.8 vs 3.6 ± 2.2, p < 0.05, respectively). Regional differences in thermal sensation were evident but were more prominent for females. Thermal sensation was greatest at the head then the torso and declined towards the extremities. In comparison to rest, exercise caused a significant reduction in thermal sensation for males (∆thermal sensation; 0.86 ± 0.3, p < 0.05), but only at select locations in females (0.31 ± 0.56, p > 0.05). The data provide evidence that the thermal sensation response to warmth varies between genders and between body regions and reduces during exercise. These findings have important implications for clothing design and thermophysiological modelling.

Height = 1.82 ± 0.72 m, body mass = 77.9 ± 9.8 kg; mean ± SD) completed a standardized 15-min intermittent warm-up on a cycle ergometer, followed by a 30-min passive recovery period before completing a 30-s maximal sprint test. Muscle temperature was measured in the vastus lateralis at 1, 2, and 3 cm depth before and after the warm-up and immediately before the sprint test. Absolute and relative peak power output was determined and blood lactate concentration was measured immediately after exercise. During the recovery period, participants wore a tracksuit top and (i) standard tracksuit pants (CONT), (ii) insulated athletic pants (INS), or (iii) insulated athletic pants with integrated electric heating elements (HEAT). Results Warm-up increased Tm by approximately 2.5°C at all depths, with no differences between conditions. During recovery, Tm remained elevated in HEAT compared with INS and CONT at all depths (P < 0.001). Both peak and relative power output were elevated by 9.6% and 9.1%, respectively, in HEAT compared with CONT (both P < 0.05). The increase in blood lactate concentration was greater (P < 0.05) after sprint in HEAT (6.3 ± 1.8 mmol·L−1) but not INS (4.0 ± 1.8 mmol·L−1) versus CONT (4.1 ± 1.9 mmol·L−1). Conclusions Passive heating of the thighs between warm-up completion and performance execution using pants incorporating electrically heated pads can attenuate the decline in Tm and improve sprint cycling performance....

It is essentially unknown how humans adapt or will adapt to heat stress caused by climate change over a long-term interval. A possible indicator of adaptation may be the minimum mortality temperature (MMT), which is defined as the mean daily temperature at which the lowest mortality occurs. Another possible indicator may be the heat sensitivity, i.e., the percentage change in mortality per 1°C above the MMT threshold, or heat attributable fraction (AF), i.e., the percentage relative excess mortality above MMT. We estimated MMT and heat sensitivity/AF over a period of 23 years for older adults (≥65 years) in the Netherlands using three commonly used methods. These methods are segmented Poisson regression (SEG), constrained segmented distributed lag models (CSDL), and distributed lag non-linear models (DLNM). The mean ambient temperature increased by 0.03°C/year over the 23 year period. The calculated mean MMT over the 23-year period differed considerably between methods [16.4 ± 1.2°C (SE) (SEG), 18.9 ± 0.5°C (CSDL), and 15.3 ± 0.4°C DLNM]. MMT increased during the observed period according to CSDL (0.11 ± 0.05°C/year) and DLNM (0.15 ± 0.02°C/year), but not with SEG. The heat sensitivity, however, decreased for the latter method (0.06%/°C/year) and did not change for CSDL. Heat AF was calculated for the DLNM method and decreased with 0.07%/year. Based on these results we conclude that the susceptibility of humans to heat decreases over time, regardless which method was used, because human adaptation is shown by either an increase in MMT (CSDL and DLNM) or a decrease in heat sensitivity for unchanged MMT (SEG). Future studies should focus on what factors (e.g., physiological, behavioral, technological, or infrastructural adaptations) influence human adaptation the most, so it can be promoted through adaptation policies. Furthermore, future studies should keep in mind that the employed method influences the calculated MMT, which hampers comparability between studies.

Purpose: To reduce the need for invasive and expensive measures of human biomarkers, sweat is becoming increasingly popular in use as an alternative to blood. Therefore, the (in)dependency of blood and sweat composition has to be explored.Methods: In an environmental chamber (33 °C, 65% relative humidity; RH), 12 participants completed three subsequent 20-min cycling stages to elicit three different local sweat rates (LSR) while aiming to limit changes in blood composition: at 60% of their maximum heart rate (HR_max), 70% HR_maxand 80% HR_max, with 5 min of seated-rest in between. Sweat was collected from the arm and back during each stage and post-exercise. Blood was drawn from a superficial antecubital vein in the middle of each stage. Concentrations of sodium, chloride, potassium, ammonia, lactate and glucose were determined in blood plasma and sweat.Results: With increasing exercise intensity, LSR, sweat sodium, chloride and glucose concentrations increased (P ≤ 0.026), while simultaneously limited changes in blood composition were elicited for these components (P ≥ 0.093). Sweat potassium, lactate and ammonia concentrations decreased (P ≤ 0.006), while blood potassium decreased (P = 0.003), and blood ammonia and lactate concentrations increased with higher exercise intensities (P = 0.005;P = 0.007, respectively). The vast majority of correlations between blood and sweat parameters were non-significant (P > 0.05), with few exceptions.Conclusion: The data suggest that sweat composition is at least partly independent of blood composition. This has important consequences when targeting sweat as non-invasive alternative for blood measurements.

Regional differences in thermal sensation to a hot or cold stimulus are often limited to male participants, in a rested state and cover minimal locations. Therefore, magnitude sensation to both a hot and cold stimulus were investigated during rest and exercise in 8 females (age: 20.4 ± 1.4 years, mass: 61.7 ± 4.0 kg, height: 166.9 ± 5.4 cm, VO2max: 36.8 ± 4.5 ml·kg(-1)·min(-1)). Using a repeated measures cross over design, participants rested in a stable environment (22.3 ± 0.9°C, 37.7 ± 5.5% RH) whilst a thermal probe (25 cm(2)), set at either 40°C or 20°C, was applied in a balanced order to 29 locations across the body. Participants reported their thermal sensation after 10s of application. Following this, participants cycled at 50% VO2max for 20 min and then 30% VO2max whilst the sensitivity test was repeated. Females experienced significantly stronger magnitude sensations to the cold than the hot stimulus (5.5 ± 1.7 and 4.3 ± 1.3, p<0.05, respectively). A significant effect of location was found during the cold stimulation (p<0.05). Thermal sensation was greatest at the head then the torso and declined towards the extremities. No significant effect of location was found in response to the hot stimulation and the pattern across the body was more homogenous. In comparison to rest, exercise caused a significant overall reduction in thermal sensation (5.2 ± 1.5 and 4.6 ± 1.7, respectively, p<0.05). Body maps were produced for both stimuli during rest and exercise, which highlight sensitive areas across the body.

This article was published in the serial, Journal of Thermal Biology [© Elsevier]. The definitive version is available at: http://dx.doi.org/10.1016/j.jtherbio.2013.09.003The relationship between local thermal comfort, local skin wettedness (w) and local galvanic skin conductance (GSC) in four body segments during two different exercise intensities was compared in 10 males. In a balanced order, participants walked at 35% VO for 45min (WALK) (29.0±1.9°C, 29.8±3.6% RH, no wind) in one test and in a separate test ran at 70% VO for 45min (RUN) (26.2±2.1°C, 31.1±7.0% RH, no wind). During both tests, participants wore a loose fitting 100% polyester long sleeve top and trouser ensemble with a low resistance to heat and vapour transfer (total thermal resistance of 0.154mKW and total water vapour resistance of 35.9mPaW). w, change from baseline in GSC (δGSC) and local thermal comfort were recorded every 5min. The results suggest that both w and δGSC are strong predictors of thermal comfort during the WALK when sweat production is low and thermal discomfort minimal (r>0.78 and r>0.71, respectively). Interestingly, during the RUN w plateaued at ~0.6 to 0.8 due to the high sweat production, whilst δGSC gradually increased throughout the experiment. δGSC had a similar relationship with thermal comfort to w during the RUN (r>0.95 and r>0.94, respectively). Despite the strength of these relationships, the ability of w to predict local thermal comfort accurately dramatically reduces in the exponential part of the curve. In a situation of uncompensated heat stress such as high metabolic rate in hot climate, where sweat production is high, δGSC shows to be a better predictor of local thermal comfort than w. The w data shows regional differences in the threshold which triggers local discomfort during the WALK than RUN; lower values are found for upper arms (0.22±0.03 and 0.28 ±0.22) and upper legs (0.22±0.11 and 0.22±0.10), higher values for upper back (0.30±0.12 and 0.36 ±0.10) and chest (0.27±0.10 and 0.39 ±0.32), respectively. However, no regional differences in the threshold of discomfort are found in the {increment}GSC data. Instead, the data suggests that the degree of discomfort experienced appears to be related to the amount of sweat within and around the skin (as indirectly measured by δGSC) at each body site. © 2013 Elsevier Ltd