Age, sex and disease-specific associations between resting heart rate and cardiovascular mortality in the UK BIOBANK

This study aimed to clarify how resting heart rate (RHR) relates to cardiovascular and all-cause mortality, specifically examining how these associations vary by sex, age, and underlying disease. While RHR is a known risk marker, previous research has been inconsistent regarding sex-specific differences and the influence of age, often suffering from small sample sizes or limited control for competing health risks.

The researchers analyzed data from 502,534 participants in the UK Biobank, tracking health outcomes over a 7–12 year follow-up period. They utilized Cox proportional hazards models and competing risks regression to evaluate the association between RHR and mortality, adjusting for a comprehensive set of confounders including age, BMI, smoking, physical activity, diabetes, hypertension, and the use of heart rate-modifying medications.

Elevated RHR was consistently linked to higher mortality across the cohort. For every 10 beats per minute (bpm) increase in RHR, men faced a 22% higher hazard of all-cause mortality, while women faced a 19% higher hazard. Cardiovascular mortality was also significantly associated with higher RHR, though the drivers differed by sex: ischaemic heart disease was a primary driver in men, whereas the relationship in women appeared more complex and less tied to fatal ischaemic events. Notably, the researchers found that RHR also predicted cancer mortality, suggesting that the risks associated with elevated RHR extend beyond cardiovascular disease. Furthermore, the predictive power of RHR was generally more pronounced in younger participants compared to older ones.

These findings reinforce the utility of RHR as a simple, inexpensive, and independent clinical risk marker. By identifying that the association between RHR and mortality is not solely driven by cardiovascular disease and varies significantly by age and sex, this study provides a more nuanced understanding of how heart rate reflects systemic health. The results support incorporating RHR into broader risk stratification algorithms to improve patient prognostication.