亚北极地区人群急性心肌梗死发病率的季节变化:1974-2004年特罗姆瑟研究

Laila Arnesdatter Hopstock, Tom Wilsgaard, Inger Njølstad, Jan Mannsverk, Ellisiv B Mathiesen, Maja-Lisa Løchen, Kaare Harald Bønaa
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引用次数: 33

摘要

背景:急性心肌梗死(MI)具有较高冬季发病率和死亡率的季节性模式。高峰和低谷季节之间差异的大小与纬度有关,但结果并不一致。在以人群为基础的心肌梗死队列中,基于已判决的心肌梗死病例的季节性变化研究很少。我们调查了挪威北部特罗姆瑟人口中首次非致命性和致命性心肌梗死的月度和季节变化,该地区气候恶劣,日照季节变化极端。设计:前瞻性人群队列研究。方法:从1974年到2001年的特罗姆瑟研究中招募的37392名参与者在2004年进行了随访。对医疗记录和死亡证明的审查证实了每一起心梗事件。用泊松回归和余弦法分析不同月份和季节的心肌梗死发病率的季节模式。所有分析均按性别、年龄和吸烟状况进行分层。结果:共登记首例MIs 1893例,其中死亡592例。与非冬季相比,冬季(11月至1月)发生心肌梗死的风险增加了11%(95%可信区间:1.00-1.23,P=0.04),与性别、年龄、吸烟或日历年无统计学意义的相互作用。其他季节性模型也给出了类似但没有统计学意义的结果。结论:我们发现在最黑暗的冬季发生心肌梗死的风险略有增加。生活在亚北极地区的人口可以通过行为保护来适应冬季的气候暴露。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Seasonal variation in incidence of acute myocardial infarction in a sub-Arctic population: the Tromsø Study 1974-2004.

Background: A seasonal pattern with higher winter morbidity and mortality has been reported for acute myocardial infarction (MI). The magnitude of the difference between peak and nadir season has been associated with latitude, but results are inconsistent. Studies of seasonal variation of MI in population-based cohorts, based on adjudicated MI cases,are few.We investigated the monthly and seasonal variation in first-ever nonfatal and fatal MI in the population of Tromsø in northern Norway, a region with a harsh climate and extreme seasonal variation in daylight exposure.

Design: Prospective population-based cohort study.

Methods: A total of 37 392 participants from the Tromsø Study enrolled between 1974 and 2001 were followed throughout 2004. Each incident case of MI was validated by the review of medical records and death certificates. MI incidence rates for months and seasons were analyzed for seasonal patterns with Poisson regression and the Cosinor procedure. All analyses were stratified by sex, age and smoking status.

Results: A total of 1893 first-ever MIs were registered, of which 592 were fatal. There was an 11 % (95% confidence interval: 1.00-1.23, P=0.04) increased risk of incident MI during winter (November-January) compared with non-winter seasons, with no statistically significant interaction with sex, age, smoking or calendar year. Other seasonal modelling gave similar but not statistically significant results.

Conclusion: We found a small increase in risk of incident MI during the darkest winter months. Populations living in sub-Arctic areas may be adapted to face climate exposure during winter through behavioural protection.

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