Inter- and intraindividual variability in daily resting heart rate and its associations with age, sex, sleep, BMI, and time of year: Retrospective, longitudinal cohort study of 92,457 adults
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BACKGROUND: Heart rate is routinely measured as part of the clinical examination but is rarely acted upon unless it is well outside a population-based normal range. With wearable sensor technologies, heart rate can now be continuously measured, making it possible to accurately identify an individual's "normal" heart rate and potentially important variations in it over time. Our objective is to describe inter- and intra-individual variability in resting heart rate (RHR) collected over the course of two years using a wearable device, studying the variations of resting heart rate as a function of time of year, as well as individuals characteristics like age, sex, average sleep duration, and body mass index (BMI). METHODS AND FINDINGS: Our retrospective, longitudinal cohort study includes 92,457 de-identified individuals from the United States (all 50 states), who consistently-over at least 35 weeks in the period from March 2016 to February 2018, for at least 2 days per week, and at least 20 hours per day-wore a heart rate wrist-worn tracker. In this study, we report daily RHR and its association with age, BMI, sex, and sleep duration, and its variation over time. Individual daily RHR was available for a median of 320 days, providing nearly 33 million daily RHR values. We also explored the range in daily RHR variability between individuals, and the long- and short-term changes in the trajectory of an individual's daily RHR. Mean daily RHR was 65 beats per minute (bpm), with a range of 40 to 109 bpm among all individuals. The mean RHR differed significantly by age, sex, BMI, and average sleep duration. Time of year variations were also noted, with a minimum in July and maximum in January. For most subjects, RHR remained relatively stable over the short term, but 20% experienced at least 1 week in which their RHR fluctuated by 10 bpm or more. CONCLUSIONS: Individuals have a daily RHR that is normal for them but can differ from another individual's normal by as much as 70 bpm. Within individuals, RHR was much more consistent over time, with a small but significant seasonal trend, and detectable discrete and infrequent episodes outside their norms.
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Longitudinal HR data can establish what is normal for an individual and recognize important deviations earlier, before cardiovascular disease develops.
“Moreover, longitudinal HR data can establish what is normal for an individual and, subsequently, recognize important deviations in lifestyle earlier, before cardiovascular disease develops46.”
From Smart wearable devices in cardiovascular care: Where we are and how to move forward (2021) · cites this paper as [46]
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- Authors
- Quer, G., Gouda, P., Galarnyk, M., Topol, E. J., & Steinhubl, S. R.
- Affiliations
- University of Alberta (CA)
- Corresponding author
- Quer, Giorgio
- Venue
- PLOS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2020-02-05
- Volume
- 15
- Issue
- 2
- Pages
- e0227709
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC7001906
- OpenAlex
- W3005497886
- Cited by
- 185
- References
- 33
- Citations by year
- 2026: 17 · 2025: 33 · 2024: 33 · 2023: 29 · 2022: 38 · 2021: 25 · 2020: 10
- FWCI
- 15.77
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- PLoS ONE (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- eScholarship (California Digital Library) (submittedVersion, cc-by)
- Funders
- National Center for Advancing Translational Sciences (UL1TR001114)
- Topics
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Heart Rate Variability and Autonomic Control
- Health Sciences › Medicine › Physiology › Physical Activity and Health
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Keywords
- resting heart rate, interindividual variability, within-person variability, seasonal variation, sleep duration, body mass index, age and sex differences
- MeSH terms
- Adolescent, Adult, Age Factors, Aged, Aged, 80 and over, Female, Heart Rate, Humans, Longitudinal Studies, Male, Middle Aged, Rest, Retrospective Studies, Seasons, Sex Factors, Sleep, Body Mass Index, Young Adult
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