Shawn E. Bearden

A simple and valid method to determine thermoregulatory sweating threshold and sensitivity

Sweating threshold temperature and sweating sensitivity responses are measured to evaluate thermoregulatory control. However, analytic approaches vary, and no standardized methodology has been validated. This study validated a simple and standardized method, segmented linear regression (SReg), for determination of sweating threshold temperature and sensitivity. Archived data were extracted for analysis from studies in which local arm sweat rate (m(sw); ventilated dew-point temperature sensor) and esophageal temperature (T(es)) were measured under a variety of conditions. The relationship m(sw)/T(es) from 16 experiments was analyzed by seven experienced raters (Rater), using a variety of empirical methods, and compared against SReg for the determination of sweating threshold temperature and sweating sensitivity values. Individual interrater differences (n = 324 comparisons) and differences between Rater and SReg (n = 110 comparisons) were evaluated within the context of biologically important limits of magnitude (LOM) via a modified Bland-Altman approach. The average Rater and SReg outputs for threshold temperature and sensitivity were compared (n = 16) using inferential statistics. Rater employed a very diverse set of criteria to determine the sweating threshold temperature and sweating sensitivity for the 16 data sets, but interrater differences were within the LOM for 95% (threshold) and 73% (sensitivity) of observations, respectively. Differences between mean Rater and SReg were within the LOM 90% (threshold) and 83% (sensitivity) of the time, respectively. Rater and SReg were not different by conventional t-test (P > 0.05). SReg provides a simple, valid, and standardized way to determine sweating threshold temperature and sweating sensitivity values for thermoregulatory studies.

VO(2) slow component: to model or not to model?

PURPOSE The purpose of this study was to compare several techniques often used in the literature for measuring the amplitude of the slow component of oxygen uptake kinetics. METHODS Eight healthy male volunteer cyclists performed two identical bouts of square wave cycle ergometry, from a VO(2) of 60% of the lactic acid threshold (LAT) to 30% of the difference between LAT and VO(2) peak. Predetermined intervals (3--6 and 3--10 min) were chosen to reflect those often used in the literature, namely 3-6 min and 3 min to the end of exercise. Several procedures were used to estimate the 3, 6, and 10-min VO(2) values (20-s averaging, 60-s averaging, and mono-exponential modeling). These were compared with the modeled slow component amplitude using a two-phase model with independent time delays: VO(2)(t) = B VO(2) + A(1)(1 -- e(-(t-TD1)/tau(1)) + A(2)(1 -- e(-(t-TD2)/tau(2)). CONCLUSIONS The results showed a significant underestimation for all methods of slow component amplitude estimation (P < 0.05) when compared with the actual (modeled) amplitude. In so far as research on oxygen uptake kinetics is used to understand the underlying physiology, it is imperative that the components of the kinetics be determined accurately. The use of a predetermined time frame for estimation of the amplitude of the slow component is not supported by this study. Future investigations should consider these results and make every effort to model the underlying response.

Leg electromyography and the VO2-power relationship during bicycle ergometry.

PURPOSE The relationship between oxygen consumption and power is not linear. The purpose of this investigation was to examine the nature of the relationship and the cause of the nonlinearity. METHODS Eight male cyclists (60.5 +/- 3.8 mL O2.min-1.kg(-1) VO2 peak) completed an incremental exercise test (1 W.5 s(-1)) to exhaustion. VO2 was measured every breath, and rmsEMG was recorded continuously over the belly of vastus lateralis, biceps femoris, and lateral gastrocnemius. RESULTS VO2 is a linear function of power in moderate exercise; the slope of the linear portion was approximately 9.7 mL O2.min(-1).W(-1), which is consistent with the steady state gain for moderate exercise. Beyond this initial break from linearity, the VO2.W(-1) plot demonstrates a second break that is not different from the point of respiratory compensation (break in VE.VCO2(-1)). These breaks were coincident with increased neuromuscular activity (1st break: 194 +/- 27 W for VO2, 191 +/- 25 W for vastus lateralis; 2nd break: 262 +/- 34 W for VO2, 258 +/- 27 W for vastus lateralis) and corresponded to approximately 58% VO2 peak for the first and 75% VO2 peak for the second break. CONCLUSIONS VO2 is not a linear function of power. During an incremental test, neuromuscular activity and VO2 increase more rapidly in heavy exercise. Both VO2 and neuromuscular activity exhibit a second break at very high power output, which may mark an upper limit for sustainable exercise.