Fitness tests as predictors of physical exertion on graded hiking trails

Abstract

Lack of information regarding the level of fitness required to complete a hiking trail may create perceived and real health risks for inexperienced hikers. In this study, the link between current fitness levels of potential hikers and actual exertion on hiking trails is investigated. In particular, we investigated whether simple, pre-hike fitness tests (Step-up and Cooper tests) could be used to predict physical exertion on two graded hiking trails (Trail 1: graded easy; Trail 2: graded moderate). Fifty participants completed the pre-hike fitness tests and the two hiking trails. Correlations between relevant sets of variables were calculated, together with the associated p-value. Analysis of covariance (ANCOVA) models followed by model selection were used to investigate if the exertion levels on the two trails, as characterised by the minimum heart rate (HR), mean HR and maximum HR at the end of the trail, could be predicted by the pre-hike fitness tests. A statistical model was created that predicts the mean HR and maximum HR of hikers undertaking an easy and a moderate hike; the Step-up test best predicted mean and maximum HR on Trial 1, and maximum HR on Trail 2, while the combination of Step-up and Cooper tests best predicted mean HR on Trail 2. Park managers are continuously looking to implement new and novel techniques that will increase customer enjoyment, while simultaneously minimise customer risk. By using an accurate predictive model such as the one proposed, managers can improve users' experiences. Satisfied customers are more likely to return to these facilities and positive reviews may increase facility usage.