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Impact of weather and pollution on the rate of cerebrovascular events in a large metropolitan area.

机译:天气和污染对大都市地区脑血管事件发生率的影响。

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摘要

Despite mounting evidence, there is uncertainty on the impact of the interplay between weather and pollution features on the risk of acute cerebrovascular events (CVE). We aimed at appraising role of weather and pollution on the daily risk of CVE. Anonymized data from a hub CVE center in a large metropolitan area were collected and analyzed according to weather (temperature, pressure, humidity, and rainfall) and pollution (carbon monoxide CO, nitrogen dioxide NO2, nitrogen oxides NOX, ozone O3, and particulate matter PM) on the same and the preceding days. Poisson regression and time series analyses were used to appraise the association between environmental features and daily CVE, distinguishing also several subtypes of events. We included a total of 2534 days, with 1363 days having ≥1 CVE, from 2012 to 2017. Average daily rate was 1.56 (95 confidence interval: 1.49; 1.63) for CVE, with other event rates ranging between 1.42 for stroke and 0.01 for ruptured intracranial aneurysm. Significant associations were found between CVE and temperature, pressure, CO, NO2, NOX, O3, and PM <10 μm (all P<0.05), whereas less stringent associations were found for humidity, rainfall, and PM <2.5 μm. Time series analysis exploring lag suggested that associations were stronger at same-day analysis (lag 0), but even environmental features predating several days or weeks were significantly associated with events. Multivariable analysis suggested that CO (point estimate 1.362 1.011; 1.836, P=0.042) and NO2 (1.011 1.005; 1.016, P<0.001) were the strongest independent predictors of CVE. Environmental features are significantly associated with CVE, even several days before the actual event. Levels of CO and NO2 can be potentially leveraged for population-level interventions to reduce the burden of CVE.
机译:尽管有越来越多的证据,但天气和污染特征之间的相互作用对急性脑血管事件 (CVE) 风险的影响仍存在不确定性。我们旨在评估天气和污染对CVE日常风险的作用。根据天气(温度、压力、湿度和降雨量)和污染(一氧化碳 [CO]、二氧化氮 [NO2]、氮氧化物 [NOX]、臭氧 [O3] 和颗粒物 [PM])收集和分析来自大都市地区中心 CVE 中心的匿名数据。泊松回归和时间序列分析用于评估环境特征与日常CVE之间的关联,并区分了事件的几种亚型。从2012年到2017年,我们总共纳入了2534天,其中1363天有≥1个CVE。CVE 的平均每日发生率为 1.56(95% 置信区间:1.49;1.63),其他事件发生率介于卒中 1.42 和颅内动脉瘤破裂 0.01 之间。CVE与温度、压力、CO、NO2、NOX、O3和PM<10 μm(均P<0.05)之间存在显著相关性,而湿度、降雨量和PM<2.5 μm的相关性较差。探索滞后的时间序列分析表明,在同一天分析中,关联性更强(滞后0),但即使是几天或几周前的环境特征也与事件显着相关。多因素分析表明,CO(点估计值 1.362 [1.011;1.836,P=0.042)和NO2(1.011 [1.005;1.016],P<0.001)是CVE最强的独立预测因子。环境特征与CVE显著相关,甚至在实际事件发生前几天也是如此。CO 和 NO2 水平可用于人群水平的干预,以减轻 CVE 的负担。

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