Personal protective equipment (PPE) can potentiate heat stress which may negatively impact wearer’s performance, safety and well-being. In view of this, a survey was distributed to healthcare workers (HCWs) required to wear PPE during the COVID-19 pandemic in the UK to evaluate perceived levels of heat stress and its consequences. Respondents reported experiencing several heat-related illness symptoms and that heat stress impaired both cognitive and physical performance. The majority also reported PPE made their job more difficult. These, and additional responses, suggest that modification to current working practices is urgently required to improve HCWs’ resilience to wearing PPE during pandemics.

The measurement of core body temperature is an efficient method for monitoring heat stress amongst workers in hot conditions. However, invasive measurement of core body temperature (e.g. rectal, intestinal, oesophageal temperature) is impractical for such applications. Therefore, the aim of this study was to define relevant non-invasive measures to predict core body temperature under various conditions. We conducted two human subject studies with different experimental protocols, different environmental temperatures (10 °C, 30 °C) and different subjects. In both studies the same non-invasive measurement methods (skin temperature, skin heat flux, heart rate) were applied. A principle component analysis was conducted to extract independent factors, which were then used in a linear regression model. We identified six parameters (three skin temperatures, two skin heat fluxes and heart rate), which were included for the calculation of two factors. The predictive value of these factors for core body temperature was evaluated by a multiple regression analysis. The calculated root mean square deviation (rmsd) was in the range from 0.28 °C to 0.34 °C for all environmental conditions. These errors are similar to previous models using non-invasive measures to predict core body temperature. The results from this study illustrate that multiple physiological parameters (e.g. skin temperature and skin heat fluxes) are needed to predict core body temperature. In addition, the physiological measurements chosen in this study and the algorithm defined in this work are potentially applicable as real-time core body temperature monitoring to assess health risk in broad range of working conditions.

Major sporting events are often held in hot and humid environmental conditions. Cooling techniques have been used to reduce the risk of heat illness following exercise. This study compared the efficacy of five cooling techniques, hand immersion (HI), whole body fanning (WBF), an air cooled garment (ACG), a liquid cooled garment (LCG) and a phase change garment (PCG), against a natural cooling control condition (CON) over two periods between and following exercise bouts in 31 degrees C, 70%RH air. Nine males [age 22 (3) years; height 1.80 (0.04) m; mass 69.80 (7.10) kg] exercised on a treadmill at a maximal sustainable work intensity until rectal temperature (T (re)) reached 38.5 degrees C following which they underwent a resting recovery (0-15 min; COOL 1). They then recommenced exercise until T (re) again reached 38.5 degrees C and then undertook 30 min of cooling with (0-15 min; COOL 2A), and without face fanning (15-30 min; COOL 2B). Based on mean body temperature changes (COOL 1), WBF was most effective in extracting heat: CON 99 W; WBF: 235 W; PCG: 141 W; HI: 162 W; ACG: 101 W; LCG: 49 W) as a consequence of evaporating more sweat. Therefore, WBF represents a cheap and practical means of post-exercise cooling in hot, humid conditions in a sporting setting.

This paper aims to improve the prediction of rectal temperature (T re) from insulated skin temperature (T is) and micro-climate temperature (T mc) previously reported (Richmond et al., Insulated skin temperature as a measure of core body temperature for individuals wearing CBRN protective clothing. Physiol Meas 2013; 34:1531-43.) using additional physiological and/or environmental variables, under several clothing and climatic conditions. Twelve male (25.8±5.1 years; 73.6±11.5kg; 178±6cm) and nine female (24.2±5.1 years; 62.4±11.5kg; 169±3cm) volunteers completed six trials, each consisting of two 40-min periods of treadmill walking separated by a 20-min rest, wearing permeable or impermeable clothing, under neutral (25°C, 50%), moderate (35°C, 35%), and hot (40°C, 25%) conditions, with and without solar radiation (600W m(-2)). Participants were measured for heart rate (HR) (Polar, Finland), skin temperature (T s) at 11 sites, T is (Grant, Cambridge, UK), and breathing rate (f) (Hidalgo, Cambridge, UK). T mc and relative humidity were measured within the clothing. T re was monitored as the 'gold standard' measure of T c for industrial or military applications using a 10cm flexible probe (Grant, Cambridge, UK). A stepwise multiple regression analysis was run to determine which of 30 variables (T is, T s at 11 sites, HR, f, T mc, temperature, and humidity inside the clothing front and back, body mass, age, body fat, sex, clothing, Thermal comfort, sensation and perception, and sweat rate) were the strongest on which to base the model. Using a bootstrap methodology to develop the equation, the best model in terms of practicality and validity included T is, T mc, HR, and 'work' (0 = rest; 1 = exercise), predicting T re with a standard error of the estimate of 0.27°C and adjusted r (2) of 0.86. The sensitivity and specificity for predicting individuals who reached 39°C was 97 and 85%, respectively. Insulated skin temperature was the most important individual parameter for the prediction of T re. This paper provides novel information about the viability of predicting T c under a wide range of conditions, using predictors which can practically be measured in a field environment.