Resting Heart Rate Predicts Fitness Level
Is there any scientific evidence of resting heart rate being considered for estimating fitness level in many smart wearables?
@sajjan The study covered in this summary was published in papers.ssrn.com as a preprint and has not yet been peer-reviewed.
The inverse relation between resting heart rate and maximal oxygen consumption is directly correlated with physical fitness and adiposity.
Resting heart rate is a biomarker for fitness and, therefore, a predictor of cardiorespiratory health.
Why This Matters
An increase in resting heart rate has been linked to an increase in all-cause mortality from chronic diseases, such as type 2 diabetes and cancer.
Resting heart rate can be used as a low-cost, noninvasive way to assess risk for cardiovascular disease and the effectiveness of interventions related to physical activity.
The population-based study cohort consisted of 5722 women and 5143 men 29 to 65 years of age.
Resting heart rate and fitness were assessed at baseline and a median of 6 years later.
Resting heart rate was measured with two standard electrocardiogram electrodes while the patient was seated, supine, and sleeping.
A sensor worn for 6 days and nights was used to monitor heart rate during sleep.
To measure fitness, participants walked, walked on an incline, and ran on a treadmill.
Physical activity was measured over a 6-day period using a combined heart rate and movement sensor, and those data were correlated with data collected from the treadmill exercise.
Other parameters assessed, along with their possible influence, included body mass index, alcohol consumption, smoking status, ethnicity, and body composition (assessed with dual-energy x-ray absorptiometry).
Mean resting heart rate while seated was 67 beats per minute, while supine was 64 beats per minute, and while sleeping was 57 beats per minute.
An increase of one beat per minute in supine heart rate was associated with a decrease in fitness level of 0.23 mL/min per kg.