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Association between clustering of cardiovascular risk factors and resting heart rate in Chinese population: a
Fu-Yu Jing1, Xiu-Ling Wang1, Jia-Li Song1
1National Clinical Research Center for Cardiovascular Diseases, NHC Key Laboratory of Clinical Research for Cardiovascular Medications, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, National Center for Cardiovascular Diseases, Beijing, China.
Insights
The clustering of multiple cardiovascular risk factors significantly increases the risk of elevated resting heart rate (RHR). This association is particularly strong in young males, with metabolic factors posing a greater risk than behavioral ones.
Area of Science:
- Cardiology
- Public Health
- Epidemiology
Background:
- Limited research exists on the association between multiple cardiovascular risk factors (CVRFs) and resting heart rate (RHR).
- Previous studies primarily focused on single CVRFs and their relation to RHR.
Purpose of the Study:
- To investigate the association between the clustering of multiple CVRFs and the risk of elevated RHR.
- To explore differences in this association based on the type of risk factors (metabolic vs. behavioral) and demographic subgroups.
Main Methods:
- Cross-sectional study involving over 1 million adults aged 35-75 years.
- Data collected from the China PEACE Million Persons Projects (September 2015 - August 2020).
- Seven CVRFs analyzed: hypertension, diabetes mellitus, dyslipidemia, obesity, smoking, alcohol use, and low physical activity. Elevated RHR defined as > 80 beats/min. Multivariate logistic regression used to calculate odds ratios (OR).
Main Results:
- A significant positive association was found between the number of CVRFs and elevated RHR (ORs ranging from 1.11 to 2.58 for 1 to ≥5 risk factors).
- The association was more pronounced in young males compared to other age-sex subgroups.
- Clusters with more metabolic risk factors showed a higher risk of elevated RHR than those with more behavioral risk factors.
Conclusions:
- The clustering of multiple CVRFs is independently associated with an increased risk of elevated RHR.
- Elevated RHR may serve as a marker for the cumulative impact of multiple cardiovascular risk factors.
- Targeting metabolic risk factors and focusing on young males could be crucial for managing elevated RHR.
Background:
Epidemiologic studies have explored the association between a single cardiovascular risk factor (CVRF) and resting heart rate (RHR), but the research on the relation of multiple risk factors with RHR remains scarce. This study aimed to explore the associations between CVRFs clustering and the risk of elevated RHR.
Methods:
In this cross-sectional study, adults aged 35-75 years from 31 provinces were recruited by the China PEACE Million Persons Projects from September 2015 to August 2020. We focused on seven risk factors: hypertension, diabetes mellitus, dyslipidemia, obesity, smoking, alcohol use, and low physical activity. Multivariate logistic regression was used to calculate odds ratios (OR) for elevated RHR (> 80 beats/min).
Results:
Among 1,045,405 participants, the mean age was 55.67 ± 9.86 years, and 60.4% of participants were women. The OR (95% CI) for elevated RHR for the groups with 1, 2, 3, 4 and ≥ 5 risk factor were 1.11 (1.08-1.13), 1.36 (1.33-1.39), 1.68 (1.64-1.72), 2.01 (1.96-2.07) and 2.58 (2.50-2.67), respectively (P trend < 0.001). The association between the CVRFs clustering number and elevated RHR was much more pronounced in young males than in other age-sex subgroups. Clusters comprising more metabolic risk factors were associated with a higher risk of elevated RHR than those comprising more behavioral risk factors.
Conclusions:
There was a significant positive association between the CVRFs clustering number and the risk of elevated RHR, particularly in young males. Compared clusters comprising more behavioral risk factors, clusters comprising more metabolic risk factors were associated with a higher risk of elevated RHR. RHR may serve as an indicator of the cumulative effect of multiple risk factors.
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