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Samuel Chalmers, Adrian Esterman, Roger Eston and Kevin Norton


Athletes often seek the minimum required time that might elicit a physiological or performance change. It is reasonable to suggest that heat training may improve aerobic-based performance in mild conditions. Therefore, rather than providing a traditional heat-exposure stimulus (ie, 7–10 × 60–100 min sessions), the current article details 2 studies that aimed to determine the effect of brief (≤240 min exposure) heat training on the second lactate threshold (LT2) in mild conditions.


Forty-one participants completed 5 (study 1, n = 18) or 4 (study 2, n = 23) perceptually regulated treadmill exercise training sessions in 35°C and 30% relative humidity (RH) (experimental group) or 19°C and 30% RH (control group). Preincremental and postincremental exercise testing occurred in mild conditions (19°C and 30% RH). Linear mixed-effects models analyzed the change in LT2.


Heat training did not substantially change LT2 in either study 1 (+1.2%, d = 0.38, P = .248) or study 2 (+1.9%, d = 0.42, P = .163). LT2 was not substantially changed in the control group in study 1 (+1.3%, d = 0.43, P = .193), but a within-group change was evident in study 2 (+2.3%, d = 1.04, P = .001).


Brief heat training was inadequate to improve the speed at LT2 in mild conditions more than comparable training in mild conditions. The brief nature of the heattraining protocol did not allow adaptations to develop to the extent required to potentially confer a performance advantage in an environment that is less thermally stressful than the training conditions.

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James Dollman, Tim S. Olds, Adrian Esterman and Tim Kupke

The study aimed to establish pedometer step cut points in relation to weight status among 2,071 5–16 year old Australians. Height, weight and waist circumference were measured, and participants wore a pedometer for seven days. Pedometer values were taken as the average number of steps per day and weighted according to the ratio of weekdays to weekends. Receiver operating characteristic (ROC) curves were used to identify the optimal pedometer counts to predict overweight. Analysis of covariance (ANCOVA) was used to compare anthropometric variables across pedometer step quintiles. The ROC model for older females was nonsignificant. Optimal cut points were 12,000 for younger males, 11,000 for older males and 10,000 for younger females. These were largely confirmed by ANCOVA. The cut points were lower than previously reported for equivalent age groups. Cultural and environmental differences may necessitate population-specific guidelines to be established.