InVestiGation of the Association of Physical Activity and Sedentary Behavior with tHe Occurrence of Future Cardiovascular Disease and Long Term Outcome in General Population Using the HEALTHCARE Database (VGH-HEALTHCARE)

The Association between Physical Activity and Cardiovascular Implantable Electronic Device-Detected Atrial High Rate Episodes

BACKGROUND

Atrial fibrillation is the most common arrhythmia and it is associated with a higher risk of mortality and morbidity. The goal of this study was to assess the correlation between physical activity (PA) and atrial high rate episodes (AHREs) detected by cardiovascular implantable electronic devices (CIEDs).

METHODS

We prospectively collected data from 81 patients from March 2017 to June 2019. Device-detected PA (hours per day) through an accelerometer and occurrence/burden of AHREs were determined at each outpatient clinic visit. Modest AHREs and long AHREs were defined as at least 1 episode of AHREs lasting ≥ 12 hours and 24 hours, respectively. The percentage of total AHREs in the follow-up period was defined as the burden of AHREs. Generalized estimating equations were used to explore the association between PA and occurrence/burden of AHREs to account for repeated measures within a participant.

RESULTS

The patients had 336 follow-up visits (mean 4.1 visits each). The prevalence rates of device-detected modest AHREs and long AHREs were 4.8% and 3.9%, respectively. More PA (hours per day) was associated with a lower risk of modest AHREs [odds ratio (OR) 0.671, 95% confidence interval (CI) 0.452-0.997, p = 0.048] and long AHREs (OR 0.536, 95% CI 0.348-0.824, p = 0.004) after adjusting for age, sex, and basic characteristics. More PA had a trend of association with fewer AHREs (β -0.255, 95% CI -0.512 to 0.001, p = 0.051).

CONCLUSIONS

More PA was associated with a lower risk of AHREs detected by CIEDs in older patients. PA may reduce the risk of AHREs.

Factor analysis for the clustering of cardiometabolic risk factors and sedentary behavior, a cross-sectional study

Background

Few studies have reported on the clustering pattern of CVD risk factors, including sedentary behavior, systemic inflammation, and cadiometabolic components in the general population.

Objective

We aimed to explore the clustering pattern of CVD risk factors using exploratory factor analysis to investigate the underlying relationships between various CVD risk factors.

Methods

A total of 5606 subjects (3157 male, 51.5±11.7 y/o) were enrolled, and 14 cardiovascular risk factors were analyzed in an exploratory group (n = 3926) and a validation group (n = 1676), including sedentary behaviors.

Results

Five factor clusters were identified to explain 69.4% of the total variance, including adiposity (BMI, TG, HDL, UA, and HsCRP; 21.3%), lipids (total cholesterol and LDL-cholesterol; 14.0%), blood pressure (SBP and DBP; 13.3%), glucose (HbA1C, fasting glucose; 12.9%), and sedentary behavior (MET and sitting time; 8.0%). The inflammation biomarker HsCRP was clustered with only adiposity factors and not with other cardiometabolic risk factors, and the clustering pattern was verified in the validation group.

Conclusion

This study confirmed the clustering structure of cardiometabolic risk factors in the general population, including sedentary behavior. HsCRP was clustered with adiposity factors, while physical inactivity and sedentary behavior were clustered with each other.