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      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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          Abstract

          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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          Most cited references24

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          Accuracy in Wrist-Worn, Sensor-Based Measurements of Heart Rate and Energy Expenditure in a Diverse Cohort

          The ability to measure physical activity through wrist-worn devices provides an opportunity for cardiovascular medicine. However, the accuracy of commercial devices is largely unknown. The aim of this work is to assess the accuracy of seven commercially available wrist-worn devices in estimating heart rate (HR) and energy expenditure (EE) and to propose a wearable sensor evaluation framework. We evaluated the Apple Watch, Basis Peak, Fitbit Surge, Microsoft Band, Mio Alpha 2, PulseOn, and Samsung Gear S2. Participants wore devices while being simultaneously assessed with continuous telemetry and indirect calorimetry while sitting, walking, running, and cycling. Sixty volunteers (29 male, 31 female, age 38 ± 11 years) of diverse age, height, weight, skin tone, and fitness level were selected. Error in HR and EE was computed for each subject/device/activity combination. Devices reported the lowest error for cycling and the highest for walking. Device error was higher for males, greater body mass index, darker skin tone, and walking. Six of the devices achieved a median error for HR below 5% during cycling. No device achieved an error in EE below 20 percent. The Apple Watch achieved the lowest overall error in both HR and EE, while the Samsung Gear S2 reported the highest. In conclusion, most wrist-worn devices adequately measure HR in laboratory-based activities, but poorly estimate EE, suggesting caution in the use of EE measurements as part of health improvement programs. We propose reference standards for the validation of consumer health devices (http://precision.stanford.edu/).
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            Digital Health: Tracking Physiomes and Activity Using Wearable Biosensors Reveals Useful Health-Related Information

            A new wave of portable biosensors allows frequent measurement of health-related physiology. We investigated the use of these devices to monitor human physiological changes during various activities and their role in managing health and diagnosing and analyzing disease. By recording over 250,000 daily measurements for up to 43 individuals, we found personalized circadian differences in physiological parameters, replicating previous physiological findings. Interestingly, we found striking changes in particular environments, such as airline flights (decreased peripheral capillary oxygen saturation [SpO2] and increased radiation exposure). These events are associated with physiological macro-phenotypes such as fatigue, providing a strong association between reduced pressure/oxygen and fatigue on high-altitude flights. Importantly, we combined biosensor information with frequent medical measurements and made two important observations: First, wearable devices were useful in identification of early signs of Lyme disease and inflammatory responses; we used this information to develop a personalized, activity-based normalization framework to identify abnormal physiological signals from longitudinal data for facile disease detection. Second, wearables distinguish physiological differences between insulin-sensitive and -resistant individuals. Overall, these results indicate that portable biosensors provide useful information for monitoring personal activities and physiology and are likely to play an important role in managing health and enabling affordable health care access to groups traditionally limited by socioeconomic class or remote geography.
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              Accuracy of Wrist-Worn Heart Rate Monitors.

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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: MethodologyRole: SoftwareRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: Writing – original draft
                Role: Data curationRole: Formal analysisRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: ResourcesRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: MethodologyRole: ResourcesRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                5 February 2020
                2020
                : 15
                : 2
                : e0227709
                Affiliations
                [1 ] Scripps Research Translational Institute, La Jolla, California, United States of America
                [2 ] University of Alberta, Division of Cardiology, Edmonton, Alberta, Canada
                Texas A&M University, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0003-2208-7912
                http://orcid.org/0000-0002-8158-4786
                http://orcid.org/0000-0002-1478-4729
                Article
                PONE-D-19-26393
                10.1371/journal.pone.0227709
                7001906
                32023264
                15811cad-2503-47c0-ab5a-326e8c67876a
                © 2020 Quer et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 18 September 2019
                : 24 December 2019
                Page count
                Figures: 5, Tables: 0, Pages: 12
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/100006108, National Center for Advancing Translational Sciences;
                Award ID: UL1TR001114
                Award Recipient :
                EJT and SRS were supported in part by the US National Institutes of Health/National Center for Advancing Translational Sciences grant UL1TR001114. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Medicine and Health Sciences
                Cardiology
                Heart Rate
                Biology and Life Sciences
                Physiology
                Physiological Processes
                Sleep
                Medicine and Health Sciences
                Physiology
                Physiological Processes
                Sleep
                Research and Analysis Methods
                Bioassays and Physiological Analysis
                Electrophysiological Techniques
                Cardiac Electrophysiology
                Electrocardiography
                Engineering and Technology
                Equipment
                Measurement Equipment
                Research and Analysis Methods
                Research Design
                Cohort Studies
                Medicine and Health Sciences
                Endocrinology
                Endocrine Physiology
                Menstrual Cycle
                Biology and Life Sciences
                Physiology
                Endocrine Physiology
                Menstrual Cycle
                Medicine and Health Sciences
                Physiology
                Endocrine Physiology
                Menstrual Cycle
                Biology and Life Sciences
                Physiology
                Reproductive Physiology
                Menstrual Cycle
                Medicine and Health Sciences
                Physiology
                Reproductive Physiology
                Menstrual Cycle
                Medicine and Health Sciences
                Pulmonology
                Asthma
                People and Places
                Population Groupings
                Age Groups
                Adults
                Custom metadata
                The owner of the third party data analyzed in our manuscript has restrictions upon sharing it publicly. As instructed, we provide the requested information. The data is owned by the device manufacturer, Fitbit, Inc., San Francisco, California, USA. Given the concrete risk of re-identification of the data, and the potential serious privacy and ethical risk for the individuals in the study, it would not be possible to share the data with interested researchers. However, Fitbit does offer interested researchers the ability to request similar data sets via https://healthsolutions.fitbit.com/contact/#researcher. The authors did not have special access or privileges for this data.

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