Thermal strain and fluid balance during a 72-km military route march in a field setting.

Introduction: A physiological profiling study was conducted to evaluate thermal strain as well as fluid and electrolyte balances on heat-acclimatised men performing a 72-km route march in a field setting. Methods: 38 male soldiers (age range 18-23 years) participated in the study, as part of a cohort that marched for 72 km, with loads for about 26 hours. Core temperature and heart rate sensors were used for the duration of the march. Fluid and food intake and output were monitored for the duration of the march. Blood samples were taken one day before the march (pre-march), immediately after the march (Post 1) and on the 15th day after the march to ascertain recovery (Post 2) to assess fluid and electrolyte profiles. Results: Mean core temperature was within safe limits, ranging from 37.1 to 38.1°C throughout the march. There was an overall decrease in serum sodium levels, a decline in serum sodium concentration in 28 participants and three instances of hyponatraemia (serum sodium concentration <135 mmol/L). Conclusion: Our study found low thermal strain heat-acclimatised individuals during a 72-km route march. However, there was an overall decrease in serum sodium levels, even when the participants were allowed to drink ad libitum. Challenges of exercise-associated hyponatraemia during prolonged activities remain to be addressed.

Nonlinear mixed effects modelling for the analysis of longitudinal body core temperature data in healthy volunteers.

Many longitudinal studies have collected serial body core temperature (T c) data to understand thermal work strain of workers under various environmental and operational heat stress environments. This provides the opportunity for the development of mathematical models to analyse and forecast temporal T c changes across populations of subjects. Such models can reduce the need for invasive methods that continuously measure T c. This current work sought to develop a nonlinear mixed effects modelling framework to delineate the dynamic changes of T c and its association with a set of covariates of interest (e.g. heart rate, chest skin temperature), and the structure of the variability of T c in various longitudinal studies. Data to train and evaluate the model were derived from two laboratory investigations involving male soldiers who participated in either a 12 (N = 18) or 15 km (N = 16) foot march with varied clothing, load and heat acclimatisation status. Model qualification was conducted using nonparametric bootstrap and cross validation procedures. For cross validation, the trajectory of a new subject's T c was simulated via Bayesian maximum a posteriori estimation when using only the baseline T c or using the baseline T c as well as measured T c at the end of every work (march) phase. The final model described T c versus time profiles using a parametric function with its main parameters modelled as a sigmoid hyperbolic function of the load and/or chest skin temperature. Overall, T c predictions corresponded well with the measured data (root mean square deviation: 0.16 °C), and compared favourably with those provided by two recently published Kalman filter models.