Abstract
The aim of this study was to investigate the relationship between heart rate and heart rate variability (HRV) with respect to individual characteristics and acute stressors. In particular, the relationship between heart rate, HRV, age, sex, body mass index (BMI), and physical activity level was analyzed cross-sectionally in a large sample of 28,175 individuals. Additionally, the change in heart rate and HRV in response to common acute stressors such as training of different intensities, alcohol intake, the menstrual cycle, and sickness was analyzed longitudinally. Acute stressors were analyzed over a period of 5 years for a total of 9 million measurements ( measurements per person). HRV at the population level reduced with age (p < 0.05, r = −0.35, effect size = moderate) and was weakly associated with physical activity level (p < 0.05, r = 0.21, effect size = small) and not associated with sex (p = 0.35, d = 0.02, effect size = negligible). Heart rate was moderately associated with physical activity level (p < 0.05, r = 0.30, effect size = moderate) and sex (p < 0.05, d = 0.63, effect size = moderate) but not with age (p = 0.35, r = −0.01). Similar relationships between BMI, resting heart rate (p < 0.05, r = 0.19, effect size = small), and HRV (p < 0.05, r = −0.10, effect size = small) are shown. In response to acute stressors, we report a 4.6% change in HRV (p < 0.05, d = 0.36, effect size = small) and a 1.3% change in heart rate (p < 0.05, d = 0.38, effect size = small) in response to training, a 6% increase in heart rate (p < 0.05, d = 0.97, effect size = large) and a 12% reduction in HRV (p < 0.05, d = 0.55, effect size = moderate) after high alcohol intake, a 1.6% change in heart rate (p < 0.05, d = 1.41, effect size = large) and a 3.2% change in HRV (p < 0.05, d = 0.80, effect size = large) between the follicular and luteal phases of the menstrual cycle, and a 6% increase in heart rate (p < 0.05, d = 0.97, effect size = large) and 10% reduction in HRV (p < 0.05, d = 0.47, effect size = moderate) during sickness. Acute stressors analysis revealed how HRV is a more sensitive but not specific marker of stress. In conclusion, a short resting heart rate and HRV measurement upon waking using a smartphone app can effectively be used in free-living to quantify individual stress responses across a large range of individuals and stressors.
Highlights
We have shown how a camera-based, smartphone app could be used to collect longitudinal data in free-living in a large sample of individuals
One minute measurement upon waking, we could confirm the results of previously published studies as well as provide additional insights on the relationship between resting heart rate, heart rate variability (HRV), population-level characteristics, and acute stressors
Targeting improvements in HRV as intervention goals might not be realistic, given the strong heritability coupled with age and low explained variance associated with lifestyle factors such as physical activity levels
Summary
Autonomic control impacts heart rhythm in response to stress [1,2,3,4]. The heart has its own pacemaker, beating at approximately 100 beats per minute. Heart rate at rest is typically lower than the intrinsic firing rate of the sinoatrial node (the pacemaker) due to the influence of the autonomic nervous system (ANS) via its two main branches: the parasympathetic system and the sympathetic system. The parasympathetic branch of the ANS slows down heart rate and increases heart rate variability (HRV), while the sympathetic branch of the ANS increases heart rate and reduces
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