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Resting heart rate is a population-level biomarker of cardiorespiratory fitness: The Fenland Study

INTRODUCTION: Few large studies have evaluated the relationship between resting heart rate (RHR) and cardiorespiratory fitness. Here we examine cross-sectional and longitudinal relationships between RHR and fitness, explore factors that influence these relationships, and demonstrate the utility of R...

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Detalles Bibliográficos
Autores principales: Gonzales, Tomas I., Jeon, Justin Y., Lindsay, Timothy, Westgate, Kate, Perez-Pozuelo, Ignacio, Hollidge, Stefanie, Wijndaele, Katrien, Rennie, Kirsten, Forouhi, Nita, Griffin, Simon, Wareham, Nick, Brage, Soren
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10174582/
https://www.ncbi.nlm.nih.gov/pubmed/37167327
http://dx.doi.org/10.1371/journal.pone.0285272
Descripción
Sumario:INTRODUCTION: Few large studies have evaluated the relationship between resting heart rate (RHR) and cardiorespiratory fitness. Here we examine cross-sectional and longitudinal relationships between RHR and fitness, explore factors that influence these relationships, and demonstrate the utility of RHR for remote population monitoring. METHODS: In cross-sectional analyses (The UK Fenland Study: 5,722 women, 5,143 men, aged 29-65y), we measured RHR (beats per min, bpm) while seated, supine, and during sleep. Fitness was estimated as maximal oxygen consumption (ml⋅min(-1)⋅kg(-1)) from an exercise test. Associations between RHR and fitness were evaluated while adjusting for age, sex, adiposity, and physical activity. In longitudinal analyses (6,589 participant subsample), we re-assessed RHR and fitness after a median of 6 years and evaluated the association between within-person change in RHR and fitness. During the coronavirus disease-2019 pandemic, we used a smartphone application to remotely and serially measure RHR (1,914 participant subsample, August 2020 to April 2021) and examined differences in RHR dynamics by pre-pandemic fitness level. RESULTS: Mean RHR while seated, supine, and during sleep was 67, 64, and 57 bpm. Age-adjusted associations (beta coefficients) between RHR and fitness were -0.26, -0.29, and -0.21 ml⋅kg(-1)⋅beat(-1) in women and -0.27, -0.31, and -0.19 ml⋅kg(-1)⋅beat(-1) in men. Adjustment for adiposity and physical activity attenuated the RHR-to-fitness relationship by 10% and 50%, respectively. Longitudinally, a 1-bpm increase in supine RHR was associated with a 0.23 ml⋅min(-1)⋅kg(-1) decrease in fitness. During the pandemic, RHR increased in those with low pre-pandemic fitness but was stable in others. CONCLUSIONS: RHR is a valid population-level biomarker of cardiorespiratory fitness. Physical activity and adiposity attenuate the relationship between RHR and fitness.