Resting Heart Rate Trajectory Pattern Predicts Arterial Stiffness in a Community-Based Chinese Cohort

Abstract

Objective— To examine whether the long-term resting heart rate (RHR) pattern can predict the risk of having arterial stiffness in a large ongoing cohort. Approach and Results— This community-based cohort included 12 554 participants in the Kailun study, who were free of myocardial infarction, stroke, arrhythmia, and cancer. We used latent mixture modeling to identify RHR trajectories in 2006, 2008, and 2010. We used multivariate linear regression model to examine the association between RHR trajectory patterns and the risk of having arterial stiffness, which was assessed by brachial–ankle pulse wave velocity in 2010 to 2016. We adjusted for possible confounding factors, including socioeconomic status, lifestyle factors, use of medications, comorbidities, and serum concentrations of lipids, glucose, and high-sensitivity C-reactive proteins. We identified 5 distinct RHR trajectory patterns based on their 2006 status and on the pattern of change during 2006 to 2010 (low–stable, moderate–stable, moderate–increasing, elevated–decreasing, and elevated–stable). We found that individuals with elevated–stable RHR trajectory pattern had the highest brachial–ankle pulse wave velocity value and individuals with the low–stable RHR trajectory pattern had the lowest value (adjusted mean difference=157 cm/s; P <0.001). Adjusted odds ratio for risk of having arterial stiffness (brachial–ankle pulse wave velocity ≥1400 cm/s) was 4.14 (95% confidence interval, 2.61–6.57) relative to these 2 extreme categories. Consistently, a higher average RHR, a higher annual RHR increase rate, and a higher RHR variability were all associated with a higher risk of having arterial stiffness. Conclusions— Long-term RHR pattern is a strong predictor of having arterial stiffness.