Personalised Prescription of Scalable High Intensity Interval Training to Inactive Female Adults of Different Ages

Mair, Jacqueline L.; Nevill, Alan M.; De Vito, Giuseppe; Boreham, Colin A.

Abstract

Stepping is a convenient form of scalable high-intensity interval training (HIIT) that may lead to health benefits. However, the accurate personalised prescription of stepping is hampered by a lack of evidence on optimal stepping cadences and step heights for various populations. This study examined the acute physiological responses to stepping exercise at various heights and cadences in young (n = 14) and middle-aged (n = 14) females in order to develop an equation that facilitates prescription of stepping at targeted intensities. Participants completed a step test protocol consisting of randomised three-minute bouts at different step cadences (80, 90, 100, 110 steps·min-1) and step heights (17, 25, 30, 34 cm). Aerobic demand and heart rate values were measured throughout. Resting metabolic rate was measured in order to develop female specific metabolic equivalents (METs) for stepping. Results revealed significant differences between age groups for METs and heart rate reserve, and within-group differences for METs, heart rate, and metabolic cost, at different step heights and cadences. At a given step height and cadence, middle-aged females were required to work at an intensity on average 1.9 ± 0.26 METs greater than the younger females. A prescriptive equation was developed to assess energy cost in METs using multilevel regression analysis with factors of step height, step cadence and age. Considering recent evidence supporting accumulated bouts of HIIT exercise for health benefits, this equation, which allows HIIT to be personally prescribed to inactive and sedentary women, has potential impact as a public health exercise prescription tool.

Citation

Mair, J. L., Nevill, A. M., De Vito, G., & Boreham, C. A. (2016). Personalised Prescription of Scalable High Intensity Interval Training to Inactive Female Adults of Different Ages. PLOS ONE, 11(2), Article e0148702. https://doi.org/10.1371/journal.pone.0148702

• Journal Article Type: Article
• Acceptance Date: Jan 20, 2016
• Online Publication Date: Feb 5, 2016
• Publication Date: Feb 5, 2016
• Deposit Date: Nov 2, 2017
• Publicly Available Date: Nov 2, 2017
• Journal: PLOS ONE
• Print ISSN: 1932-6203
• Publisher: Public Library of Science
• Peer Reviewed: Peer Reviewed
• Volume: 11
• Issue: 2
• Article Number: e0148702
• DOI: https://doi.org/10.1371/journal.pone.0148702
• Keywords: Exercise; Regression Analysis; Ageing
• Public URL: http://researchrepository.napier.ac.uk/Output/978589
• Contract Date: Nov 2, 2017