Seasonal variation in paroxysmal atrial fibrillation documented by 24-hour Holter electrocardiogram

Eiichi Watanabe, Yukiko Kuno, Hirohisa Takasuga, Mao Qing Tong, Yoshihiro Sobue, Tatsushi Uchiyama, Itsuo Kodama, Hitoshi Hishida

Research output: Contribution to journalArticle

21 Citations (Scopus)

Abstract

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 ≥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.

Original languageEnglish
Pages (from-to)27-31
Number of pages5
JournalHeart Rhythm
Volume4
Issue number1
DOIs
Publication statusPublished - 01-01-2007

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Atrial Fibrillation
Electrocardiography
Confidence Intervals
Incidence
Cardiovascular Diseases
Logistic Models
Regression Analysis

All Science Journal Classification (ASJC) codes

  • Cardiology and Cardiovascular Medicine
  • Physiology (medical)

Cite this

Watanabe, Eiichi ; Kuno, Yukiko ; Takasuga, Hirohisa ; Tong, Mao Qing ; Sobue, Yoshihiro ; Uchiyama, Tatsushi ; Kodama, Itsuo ; Hishida, Hitoshi. / Seasonal variation in paroxysmal atrial fibrillation documented by 24-hour Holter electrocardiogram. In: Heart Rhythm. 2007 ; Vol. 4, No. 1. pp. 27-31.
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abstract = "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 ≥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.",
author = "Eiichi Watanabe and Yukiko Kuno and Hirohisa Takasuga and Tong, {Mao Qing} and Yoshihiro Sobue and Tatsushi Uchiyama and Itsuo Kodama and Hitoshi Hishida",
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Watanabe, E, Kuno, Y, Takasuga, H, Tong, MQ, Sobue, Y, Uchiyama, T, Kodama, I & Hishida, H 2007, 'Seasonal variation in paroxysmal atrial fibrillation documented by 24-hour Holter electrocardiogram', Heart Rhythm, vol. 4, no. 1, pp. 27-31. https://doi.org/10.1016/j.hrthm.2006.09.030

Seasonal variation in paroxysmal atrial fibrillation documented by 24-hour Holter electrocardiogram. / Watanabe, Eiichi; Kuno, Yukiko; Takasuga, Hirohisa; Tong, Mao Qing; Sobue, Yoshihiro; Uchiyama, Tatsushi; Kodama, Itsuo; Hishida, Hitoshi.

In: Heart Rhythm, Vol. 4, No. 1, 01.01.2007, p. 27-31.

Research output: Contribution to journalArticle

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T1 - Seasonal variation in paroxysmal atrial fibrillation documented by 24-hour Holter electrocardiogram

AU - Watanabe, Eiichi

AU - Kuno, Yukiko

AU - Takasuga, Hirohisa

AU - Tong, Mao Qing

AU - Sobue, Yoshihiro

AU - Uchiyama, Tatsushi

AU - Kodama, Itsuo

AU - Hishida, Hitoshi

PY - 2007/1/1

Y1 - 2007/1/1

N2 - 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 ≥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.

AB - 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 ≥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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