Prediction of work metabolism from heart rate measurements in forest work: some practical methodological issues

Abstract

Individual heart rate (HR) to workload relationships were determined using 93 submaximal step-tests administered to 26 healthy participants attending physical activities in a university training centre (laboratory study) and 41 experienced forest workers (field study). Predicted maximum aerobic capacity (MAC) was compared to measured MAC from a maximal treadmill test (laboratory study) to test the effect of two age-predicted maximum HR Equations (220-age and 207-0.7 × age) and two clothing insulation levels (0.4 and 0.91 clo) during the step-test. Work metabolism (WM) estimated from forest work HR was compared against concurrent work measurements while taking into account the HR thermal component. Results show that MAC and WM can be accurately predicted from work HR measurements and simple regression models developed in this study (1% group mean prediction bias and up to 25% expected prediction bias for a single individual). Clothing insulation had no impact on predicted MAC nor age-predicted maximum HR equations.

Abstract

Practitioner summary: This study sheds light on four practical methodological issues faced by practitioners regarding the use of HR methodology to assess WM in actual work environments. More specifically, the effect of wearing work clothes and the use of two different maximum HR prediction equations on the ability of a submaximal step-test to assess MAC are examined, as well as the accuracy of using an individual's step-test HR to workload relationship to predict WM from HR data collected during actual work in the presence of thermal stress.

Keywords:

• heart rate
• work metabolism
• prediction bias
• maximum aerobic capacity
• forest work

Acknowledgements

The authors wish to thank Dr Laurent Bosquet and Mr Arthur Long of the Kinesiology Laboratory of University of Montréal for making their research facilities available and for providing technical assistance that made the Laboratory study possible. The authors also wish to acknowledge the contribution of Olivier Waddell, Steve Lemay, Adam Page, Dr Yeni Arias, Dr Laurent Giraud, Bastien Thibodeau, Marie-Ève Pelchat and Merieme Kerchi with data collection and preparation.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the Ministère des Forêts, de la Faune et des Parcs; the Fonds de recherche du Québec – Nature et technologies (FRQNT); and the Natural Sciences and Engineering Research Council of Canada (NSERC), through the Canada Research Chair in Ergonomics of Polytechnique de Montréal.