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Updated: Jul 17, 2026

Estimating Bilateral Atrial Function by Cardiovascular Magnetic Resonance Feature Tracking in Patients with Paroxysmal Atrial Fibrillation
Published on: July 20, 2022
Seasonal variation in paroxysmal atrial fibrillation documented by 24-hour Holter electrocardiogram
Eiichi Watanabe1, Yukiko Kuno, Hirohisa Takasuga
1Division of Cardiology, Department of Internal Medicine, Fujita Health University School of Medicine, Toyoake, Japan. enwatan@fujita-hu.ac.jp
Background:
The incidence of various cardiovascular diseases is known to exhibit seasonal variations, but seasonal patterns of paroxysmal atrial fibrillation (AF) have not been well characterized.
Objective:
The objective of this study was to determine whether seasonal variation affects the incidence of paroxysmal AF and whether this pattern is affected by patient age.
Methods:
We identified 258 paroxysmal AF episodes in 237 patients (age 65 +/- 14 years, mean +/- standard deviation; age range 16-95 years) among 12,390 consecutive 24-hour Holter electrocardiogram recordings obtained from 2001 to 2005 at our institute. Seasonal variations were analyzed by both month and by season. The relative risk (RR) of AF for each period was determined as being high or low in relation to the overall mean incidence. The association among clinical covariates and risk of paroxysmal AF was tested by logistic regression analysis.
Results:
The incidence of paroxysmal AF was highest in September (RR = 1.40, 95% confidence interval [CI] 1.36-1.44) and lowest in June (RR = 0.52, 95% CI 0.50-0.54), with an RR difference of 63% (P < .001) among all patients. Patients aged > or =65 years demonstrated a peak incidence in September (RR = 1.46, 95% CI 1.41-1.51) and a minimum in June (RR = 0.55, 95% CI 0.52-0.58), while those aged <65 years showed a peak incidence in December (RR = 1.33, 95% CI 1.27-1.39) and a minimum in June (RR = 0.49, 95% CI 0.45-0.53). The incidence of paroxysmal AF also showed an autumn peak (RR = 1.21, 95% CI 1.16-1.27) and a summer minimum (RR = 0.66, 95% CI 0.62-0.70), with an RR difference of 53% (P < .001) among all patients. This seasonal variation in paroxysmal AF did not differ between patients of different age ranges. Clinical covariates including underlying disease or medications did not influence the monthly or seasonal variation in paroxysmal AF. There was a significant inverse relationship between the incidence of paroxysmal AF and the length of daylight in patients aged <65 years (r = -0.57, P < .05).
Conclusion:
There was a significant seasonal variation in paroxysmal AF, with maximum and minimum incidences in autumn and summer, respectively, and this pattern was not age dependent.
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