Skin temperature is a fundamental variable in human thermo-physiology, and yet skin temperature measurement remains impractical in most free-living, exercise and clinical settings, using currently available hard-wired methods. The purpose of this study was to compare wireless iButtons and hard-wired thermistors for human skin temperature measurement. In the first of two investigations, iButtons and thermistors monitored temperature in a controlled water bath (range: 10-40 degrees C) and were referenced against a certified, mercury thermometer. In the second investigation, eight healthy males completed three randomized trials (ambient temperature = 10 degrees C, 20 degrees C and 30 degrees C) while both devices recorded skin temperature at rest (in low and high wind velocities) and during cycle-ergometry exercise. The results are as follows. Investigation 1: both devices displayed very high validity correlation with the reference thermometer (r > 0.999). Prior to correction, the mean bias was +0.121 degrees C for iButtons and +0.045 degrees C for thermistors. Upon calibration correction the mean bias for iButtons and thermistors was not significantly different from zero bias. Interestingly, a typical error of the estimate of iButtons (0.043 degrees C) was 1.5 times less than that of thermistors (0.062 degrees C), demonstrating iButtons' lower random error. Investigation 2: the offset between iButton and thermistor readings was generally consistent across conditions; however, thermistor responses gave readings that were always closer to ambient temperature than those given by iButtons, suggesting potential thermistor drift towards environmental conditions. Mean temperature differences between iButtons and thermistors during resting trials ranged from 0.261 degrees C to 1.356 degrees C. Mean temperature differences between iButtons and thermistors during exercise were 0.989 degrees C (ambient temperature = 10 degrees C), 0.415 degrees C (ambient temperature = 20 degrees C) and 0.318 degrees C (ambient temperature = 30 degrees C). Observed error estimates were within the acceptable limits for the skin temperature method comparison, with typical errors 0.9 and CV <1% under all conditions. These findings indicate that wireless iButtons provide a valid alternative for human skin temperature measurement during laboratory and field investigations particularly when skin temperature measurement using other currently available methods may prove problematic.

Background: Accurate, continuous heart rate measurements are important for health assessment, physical activity, and sporting performance, and the integration of heart rate measurements into wearable devices has extended its accessibility. Although the use of photoplethysmography technology is not new, the available data relating to the validity of measurement are limited, and the range of activities being performed is often restricted to one exercise domain and/or limited intensities. Objective: The primary objective of this study was to assess the validity of the Polar OH1 and Fitbit Charge 3 devices for measuring heart rate during rest, light, moderate, vigorous, and sprint-type exercise. Methods: A total of 20 healthy adults (9 female; height: mean 1.73 [SD 0.1] m; body mass: mean 71.6 [SD 11.0] kg; and age: mean 40 [SD 10] years) volunteered and provided written informed consent to participate in the study consisting of 2 trials. Trial 1 was split into 3 components: 15-minute sedentary activities, 10-minute cycling on a bicycle ergometer, and incremental exercise test to exhaustion on a motorized treadmill (18-42 minutes). Trial 2 was split into 2 components: 4 × 15-second maximal sprints on a cycle ergometer and 4 × 30- to 50-m sprints on a nonmotorized resistance treadmill. Data from the 3 devices were time-aligned, and the validity of Polar OH1 and Fitbit Charge 3 was assessed against Polar H10 (criterion device). Validity was evaluated using the Bland and Altman analysis, Pearson moment correlation coefficient, and mean absolute percentage error. Results: Overall, there was a very good correlation between the Polar OH1 and Polar H10 devices (r=0.95), with a mean bias of −1 beats·min-1 and limits of agreement of −20 to 19 beats·min-1. The Fitbit Charge 3 device underestimated heart rate by 7 beats·min-1 compared with Polar H10, with a limit of agreement of −46 to 33 beats·min-1 and poor correlation (r=0.8). The mean absolute percentage error for both devices was deemed acceptable (<5%). Polar OH1 performed well across each phase of trial 1; however, validity was worse for trial 2 activities. Fitbit Charge 3 performed well only during rest and nonsprint-based treadmill activities. Conclusions: Compared with our criterion device, Polar OH1 was accurate at assessing heart rate, but the accuracy of Fitbit Charge 3 was generally poor. Polar OH1 performed worse during trial 2 compared with the activities in trial 1, and the validity of the Fitbit Charge 3 device was particularly poor during our cycling exercises.

Acute bouts of high-intensity exercise modulate peripheral appetite regulating hormones to transiently suppress hunger. However, the effects of physical activity on central appetite regulation have yet to be fully investigated. We used functional magnetic resonance imaging (fMRI) to compare neural responses to visual food stimuli after intense exercise and rest. Fifteen lean healthy men [mean ± SD age: 22.5 ± 3.1 y; mean ± SD body mass index (in kg/m(2)): 24.2 ± 2.4] completed two 60-min trials-exercise (EX; running at ∼70% maximum aerobic capacity) and a resting control trial (REST)-in a counterbalanced order. After each trial, an fMRI assessment was completed in which images of high- and low-calorie foods were viewed. EX significantly suppressed subjective appetite responses while increasing thirst and core-body temperature. Furthermore, EX significantly suppressed ghrelin concentrations and significantly enhanced peptide YY release. Neural responses to images of high-calorie foods significantly increased dorsolateral prefrontal cortex activation and suppressed orbitofrontal cortex (OFC) and hippocampus activation after EX compared with REST. After EX, low-calorie food images increased insula and putamen activation and reduced OFC activation compared with REST. Furthermore, left pallidum activity was significantly elevated after EX when low-calorie images were viewed and was suppressed when high-calorie images were viewed, and these responses correlated significantly with thirst. Exercise increases neural responses in reward-related regions of the brain in response to images of low-calorie foods and suppresses activation during the viewing of high-calorie foods. These central responses are associated with exercise-induced changes in peripheral signals related to appetite-regulation and hydration status. This trial was registered at www.clinicaltrials.gov as NCT01926431.

The abundant exposure to food cues in our environment is one of the main drivers of overconsumption. Food evaluation is important for the regulation of food intake by the brain and it's interaction with hunger state. Children are especially susceptible to food cues. Understanding the mechanisms behind this regulation in healthy individuals across the life span can help to elucidate the mechanisms underlying overconsumption and aid the development of future obesity prevention strategies. Few functional neuroimaging studies have been done in children and elderly. Furthermore, it is unknown how hunger state affects neural food cue reactivity in these groups, since this has not been examined consistently. We examined the effects of hunger state and age on the brain responses to low- and high calorie foods. On two mornings, 122 participants (17 children; 38 teens; 36 adults; 31 elderly) performed a food image viewing task while being scanned using fMRI, either fasted or sated. Hunger induced greater activation during high versus low calorie food image viewing than satiety in the bilateral dorsomedial (dmPFC) and in the right dorsolateral prefrontal cortex (dlPFC) across all age groups. There was no significant main effect of age group on high versus low calorie food image viewing and no interaction between age group and hunger state. The greater activation of the dlPFC across all age groups during high calorie food image viewing in a fasted state might reflect increased inhibitory control in response to these foods. This may underlie the ability to resist overconsumption of high calorie foods. Furthermore, increased medial prefrontal cortex activation during hunger might reflect increased reward value of high calorie foods, which declines with satiation. Further studies are needed to better understand these results. Notably, overweight and obese individuals should be included to examine whether these responses are altered by weight status across the life span.

Exercise in cold water has been shown to simulate postexercise energy intake (EI) in normal-weight individuals. However, the effect of cold exercise on EI in overweight individuals has yet to be examined. The present study investigated the effect of brisk walking in a cold (8°C) and neutral (20°C) environment on postexercise EI and appetite hormone responses. Sixteen overweight participants (10 men and six women; age, 50.1 ± 11.6 yr; body mass index, 28.9 ± 4.2 kg·m) completed a 45-min treadmill walk at 8°C and 20°C in a randomized counterbalanced design. Participants were presented with an ad libitum buffet meal 45 min after exercise, and EI was covertly measured. Skin and rectal temperature were monitored throughout exercise and for 30 min after exercise, and concentrations of the appetite hormones total ghrelin, acylated ghrelin, and total peptide YY were assessed before and after exercise and before and after meal. EI was significantly greater after exercise in the cold (1299 ± 657 kcal (mean ± SD)) compared with that after exercise in the neutral environment (1172 ± 537 kcal (mean ± SD)) (P < 0.05). The change in the acylated ghrelin concentrations and the acylated ghrelin AUC values were significantly greater during walking in the cold versus those during walking in the neutral condition (P < 0.05). These findings show that in overweight individuals, exercise in the cold stimulates postexercise EI to a greater extent than exercise in a neutral environment.

Food cue exposure can trigger eating. Food cue reactivity (FCR) is a conditioned response to food cues and includes physiological responses and activation of reward-related brain areas. FCR can be affected by hunger and weight status. The appetite-regulating hormones ghrelin and leptin play a pivotal role in homeostatic as well as hedonic eating. We examined the association between ghrelin and leptin levels and neural FCR in the fasted and sated state and the association between meal-induced changes in ghrelin and neural FCR, and in how far these associations are related to BMI and HOMA-IR. Data from 109 participants from three European centers (age 50±18 y, BMI 27±5 kg/m²) who performed a food viewing task during fMRI after an overnight fast and after a standardized meal were analyzed. Blood samples were drawn prior to the viewing task in which high-caloric, low-caloric and non-food images were shown. Fasting ghrelin was positively associated with neural FCR in the inferior and superior occipital gyrus in the fasted state. This was partly attributable to BMI and HOMA-IR. These brain regions are involved in visual attention, suggesting that individuals with higher fasting ghrelin have heightened attention to food cues. Leptin was positively associated with high calorie FCR in the medial prefrontal cortex (PFC) in the fasted state and to neural FCR in the left supramarginal gyrus in the fasted versus sated state, when correcting for BMI and HOMA-IR, respectively. This PFC region is involved in assessing anticipated reward value, suggesting that for individuals with higher leptin levels high-caloric foods are more salient than low-caloric foods, but foods in general are not more salient than non-foods. There were no associations between ghrelin and leptin and neural FCR in the sated state, nor between meal-induced changes in ghrelin and neural FCR. In conclusion, we show modest associations between ghrelin and leptin and neural FCR in a relatively large sample of European adults with a broad age and BMI range. Our findings indicate that people with higher leptin levels for their weight status and people with higher ghrelin levels may be more attracted to high caloric foods when hungry. The results of the present study form a foundation for future studies to test whether food intake and (changes in) weight status can be predicted by the association between (mainly fasting) ghrelin and leptin levels and neural FCR.