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

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

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    4 Citations (Scopus)
    44 Downloads (Pure)


    Stepping is a convenient form of scalable high-intensity interval training (HIIT) that may leadto health benefits. However, the accurate personalised prescription of stepping is hamperedby 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 variousheights and cadences in young (n = 14) and middle-aged (n = 14) females in order todevelop an equation that facilitates prescription of stepping at targeted intensities. Participantscompleted a step test protocol consisting of randomised three-minute bouts at differentstep 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 ratewas measured in order to develop female specific metabolic equivalents (METs) for stepping.Results revealed significant differences between age groups for METs and heart ratereserve, and within-group differences for METs, heart rate, and metabolic cost, at differentstep heights and cadences. At a given step height and cadence, middle-aged females wererequired to work at an intensity on average 1.9 ± 0.26 METs greater than the youngerfemales. A prescriptive equation was developed to assess energy cost in METs using multilevelregression analysis with factors of step height, step cadence and age. Consideringrecent evidence supporting accumulated bouts of HIIT exercise for health benefits, thisequation, which allows HIIT to be personally prescribed to inactive and sedentary women,has potential impact as a public health exercise prescription tool.
    Original languageEnglish
    Article numbere0148702
    Pages (from-to)1-11
    JournalPLoS ONE
    Issue number2
    Publication statusPublished (in print/issue) - 5 Feb 2016


    • Exercise
    • Regression Analysis
    • Ageing


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