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Updated: Dec 30, 2025

Determining the Contribution of the Energy Systems During Exercise
Published on: March 20, 2012
Nonexercise Equations for Determining Change in Cardiorespiratory Fitness
Louise DE Lannoy1, Robert Ross
1School of Kinesiology and Health Studies, Queen's University, Kingston, Ontario, CANADA.
Purpose:
This study aimed to determine whether change in estimated cardiorespiratory fitness (eCRF) is associated with change in measured cardiorespiratory fitness (mCRF) independent of exercise amount and intensity over 24 wk.
Methods:
Participants were 163 sedentary adults with abdominal obesity (mean ± SD waist circumference, 109.9 ± 11.5 cm) randomly assigned to (i) no-exercise control (n = 42); (ii) low-amount, low-intensity exercise (LALI; n = 39); (iii) high-amount, low-intensity exercise (HALI; n = 51); and (iv) high-amount, high-intensity exercise (HAHI; n = 31). mCRF was measured using a maximal treadmill test at baseline, 8, 16, and 24 wk. eCRF was calculated using a published nonexercise equation with the following variables: sex, age, waist circumference, resting heart rate, and self-selected physical activity.
Results:
Participants attended 115 of 120 exercise sessions prescribed (96.0% ± 4.0% adherence). eCRF change from baseline to 8, 16, and 24 wk was not different from mCRF change for control, LALI, or HALI (P = 0.03). In HAHI, eCRF change was significantly greater than mCRF change at all time points (P < 0.001). Further analysis revealed that change in eCRF systematically overestimated and underestimated small and large changes in mCRF, respectively, in all groups (P < 0.001).
Conclusions:
eCRF change was associated with mCRF change at 24 wk independent of exercise amount but not intensity. Systematic variation between eCRF and mCRF highlights a possible limitation when using eCRF to follow change in mCRF, specifically that eCRF does not capture the individual variability of the mCRF response.
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