4.7 Article

Higher stroke incidence in the spring season regardless of conventional risk factors - Takashima Stroke Registry, Japan, 1988-2001

期刊

STROKE
卷 39, 期 3, 页码 745-752

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LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1161/STROKEAHA.107.495929

关键词

epidemiology; incidence; risk factor; season; stroke

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Background and Purpose - Seasonal variation in stroke incidence was examined using 14-year stroke registration data in a Japanese population. We also examined if this variation was modified by conventional stroke risk factors hypertension, diabetes mellitus, drinking, and smoking. Methods - Data were obtained from the Takashima Stroke Registry, which covers a stable population of approximate to 55 000 in Takashima County in central Japan. There were 1665 ( men, 893; women, 772) registered first-ever stroke cases during 1988 to 2001. The average age of stroke onset for men and women patients was 69.4 and 74.2 years, respectively. Incidence rates ( per 100 000 person-years) and 95% CI were calculated by gender, age, and stroke subtype for winter, spring, summer, and autumn. After stratifying patients by their risk factor history, the OR ( with 95% CI) of having a stroke in autumn, winter, and spring were calculated, with summer serving as a reference. Results - Among the seasons, stroke incidence per 100 000 person-years was highest in the spring ( 231.3; 95% CI, 211.1 to 251.5). Spring incidence was highest in both men ( 240.8; 95% CI, 211.5 to 270.2) and women ( 222.1; 95% CI, 194.4 to 249.9), and in subjects younger than 65 years ( 72.6; 95% CI, 60.0 to 85.3) and 65 years or older ( 875.9; 95% CI, 787.5 to 964.3). Among stroke subtypes, spring incidence was highest for cerebral infarction ( 154.7; 95% CI, 138.2 to 171.2) and cerebral hemorrhage ( 53.7; 95% CI, 44.0 to 63.4). The spring excess in stroke incidence was observed regardless of the presence or absence of the risk factor histories. Conclusions - Stroke incidence appears to be highest in the spring among a Japanese population regardless of conventional risk factor history. Factors that explain this excess need further investigation.

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