Predicting change in core temperature during exercise-heat stress

Abstract

Controlling internal temperature is crucial when prescribing exercise-heat stress, particularly during interventions designed to induce thermoregulatory adaptations. This study aimed to determine the relationship between the rate of rectal temperature (Trec) increase, and various methods for prescribing exercise-heat stress, to identify the most efficient method of prescribing isothermic heat acclimation (HA) training. Thirty-five males cycled in hot conditions (40[degrees]C, 39%R.H.) for 29+/-2 min. Subjects exercised at 60+/-9%V[Combining Dot Above]O2peak, with methods for prescribing exercise retrospectively observed for each participant. Pearson product moment correlations were calculated for each prescriptive variable against the rate of change in Trec ([degrees]C.hr-1), with stepwise multiple regressions performed on statistically significant variables (p<0.05). Linear regression identified the predicted intensity required to increase Trec by 1.0-2.0[degrees]C between 20-45 min periods, and the duration taken to increase Trec by 1.5[degrees]C in response to incremental intensities to guide prescription. Significant (p<0.05) relationships with the rate of change in Trec were observed for prescriptions based upon relative power (W.kg-1; r=0.764), power (%Powermax; r=0.679), RPE (r=0.577), V[Combining Dot Above]O2 (%V[Combining Dot Above]O2peak; r=0.562), HR (%HRmax; r=0.534), and TS (r=0.311). Stepwise multiple regressions observed relative power and RPE as variables to improve the model (r=0.791), with no improvement following inclusion of any anthropometric variable. Prescription of exercise under heat stress utilizing power (W.kg-1 or %Powermax), has the strongest relationship with the rate of change in Trec with no additional requirement to correct for body composition within a normal range. Practitioners should therefore prescribe exercise intensity using relative power during isothermic HA training to increase Trec efficiently and maximize adaptation