Estimated and measured core temperature responses to high-intensity warm weather military training: implications for...

Humans avoid overheating through physiological and behavioral mechanisms. However, elite athletes, industrial workers, and military personnel, driven by the tasks at hand, may choose to continue working and face an increased risk of exertional heat illness (EHI). We wanted to examine the efficacy of a new core temperature (Tcr) estimation algorithm in assessing EHI risk.

Physiological responses of 21 male Royal Marines recruits (age 21 ± 2 y, height 1.79 ± 0.05 m, weight 80.5 ± 7.2 kg) were collected during a physically-demanding criterion road march (14.5 km in 90 min with a 9.6 kg load; air temperature 16 °C, relative humidity ≥ 84%). Measured Tcr (thermometer pill) and estimated Tcr (ECTemp^TM Tcr-est) were compared.

Measured Tcr either increased to an asymptote Tcr < 39.5 °C (WARM; n= 11), or progressively increased to Tcr > 40.0 °C (HOT; n= 10). In the HOT group, Tcr-est reflected measured Tcr up to Tcr = 40.0 °C (Bias = - 0.10 ± 0.37 °C, root mean square error = 0.37 ± 0.13 °C). In the WARM group, Tcr-est overestimated Tcr (Bias = 0.34 ± 0.40 °C) and was higher from mid-point to end. A logistic regression (Skin temperature approximate entropy and mean heart rate) was able to predict group membership (95% accuracy) at 20 min, allowing a WARM group ECTemp^TM correction factor (corrected Bias = 0.00 ± 0.29 °C).

The Tcr-est successfully tracked Tcr in the HOT group with high risk of exertional heat illness (EHI) (40% incidence). Skin temperature complexity shows promise as a non-invasive means of insight into the state of thermoregulatory control mechanisms.