03 Dec Non-Exercise Algorithm Predicts Fitness and Lifestyle-Related Disease

MedicalResearch.com Interview with:
Bjarne M. Nes, PhD
K.G. Jebsen Center for Exercise in
Medicine, Department of Circulation and Medical Imaging
Norwegian University of Science and Technology
Trondheim, Norway.

MedicalResearch.com: What is the background for this study? What are the main findings?

Response: It is well known that cardiorespiratory fitness is an important predictor of future cardiovascular disease risk. Still, fitness levels are rarely measured in clinical practice, likely because of costly and time-consuming procedures that requires quite a lot of training.

Therefore, we wanted to test the ability of a simple estimation of fitness, from a so-called non-exercise algorithm, to identify individuals at high and low risk of cardiovascular mortality. We tested fitness alone and in combination with traditional risk factors such as high blood pressure, cholesterol, smoking and family history of heart disease and diabetes, among 38,480 men and women from the Nord-Trondelag Health Study in Norway. We found that estimated fitness strongly predicts premature deaths from all causes and that traditional clinical risk factors added little above and beyond fitness in terms of predicting risk.

MedicalResearch.com: What should readers take away from your report?

Response: Using an available non-exercise algorithm to estimate fitness is an alternative to direct measurement by treadmills or cycle ergometers in healthcare settings, that strongly predicts risk of lifestyle-related diseases and in a cost-effective way. We are not neglecting the importance of traditional risk factors such as blood pressure and cholesterol, that have been instrumental in clinical decision making for decades, however, this study once again emphasizes the importance of taking fitness into the equation.

MedicalResearch.com: What recommendations do you have for future research as a result of this study?

Response: I think it is time to implement fitness estimation in clinical settings where direct measurements are not justified and thereby test the practical utility and how improved communication around this may enhance fitness and risk factors as well as the prognostic value related to outcomes.

MedicalResearch.com: Thank you for your contribution to the MedicalResearch.com community.

Citation:

Prediction of Cardiovascular Mortality by Estimated Cardiorespiratory Fitness Independent of Traditional Risk Factors: The HUNT Study
Nauman, Javaid et al.
Mayo Clinic Proceedings , Volume 0 , Issue 0 ,
DOI: http://dx.doi.org/10.1016/j.mayocp.2016.10.007
Published online:November 17, 2016

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Last Updated on December 3, 2016 by Marie Benz MD FAAD