首页> 外文期刊>Journal of environmental monitoring: JEM >Air pollution indicators predict outbreaks of asthma exacerbations among elementary school children: Integration of daily environmental and school health surveillance systems in Pennsylvania
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Air pollution indicators predict outbreaks of asthma exacerbations among elementary school children: Integration of daily environmental and school health surveillance systems in Pennsylvania

机译:空气污染指标预测小学生哮喘发作的爆发:宾夕法尼亚州日常环境和学校健康监测系统的整合

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Objectives of this study are to determine if a relationship exists between asthma exacerbations among elementary school children in industrialized countries (with climatic seasons) and exposure to daily air pollution with particulate matter, sulfur dioxide, nitrogen dioxide, nitrogen oxides, carbon monoxide, and ozone, when controlled for potential confounders; and, if so, to derive a statistical model that predicts variation of asthma exacerbations among elementary school children. Using an ecological study design, health records of 168 825 students from elementary schools in 49 Pennsylvania counties employing "Health eTools for Schools" were analyzed. Asthma exacerbations were recorded by nurses as treatment given during clinic visits each day. Daily air pollution measurements were obtained from the EPA's air quality monitoring sites. The distribution of asthmatic grouping for pollen and calendar seasons was developed. A Poisson regression model was used to predict the number of asthma exacerbations. The greatest occurrence of asthma exacerbations was in autumn, followed by summer, spring and winter. If the number of asthma exacerbations on a day is N and the daily mean of asthma exacerbations for the three-year period is 48, the probabilities of N > 48 in tree pollen and grass pollen seasons were 56.5% and 40.8%, respectively (p < 0.001). According to the Poisson regression, the week number and prior day CO, SO_2, NO_2, NO_x, PM_(2.5), and O_3 had significant effects on asthma exacerbations among students. Monitoring of air pollutants over time could be a reliable new means for predicting asthma exacerbations among elementary school children. Such predictions could help parents and school nurses implement effective precautionary measures.
机译:这项研究的目的是确定工业化国家(气候季节)的小学生哮喘急性发作与每天接触的颗粒物,二氧化硫,二氧化氮,氮氧化物,一氧化碳和臭氧所致的空气污染之间是否存在关系。 ,在控制潜在的混杂因素时;如果是,则推导一个统计模型来预测小学生哮喘发作的变化。使用生态研究设计,分析了宾夕法尼亚州49个县使用“学校健康电子工具”的168 825名学生的健康记录。护士将哮喘恶化记录为每天在诊所就诊期间给予的治疗。每日空气污染测量值是从EPA的空气质量监测点获得的。确定了花粉和日历季节的哮喘分组分布。使用Poisson回归模型预测哮喘发作的次数。哮喘发作最严重的是秋季,其次是夏季,春季和冬季。如果一天中哮喘发作的次数为N,并且三年期间的哮喘发作的日平均值为48,则在树花粉和草花粉季节N> 48的概率分别为56.5%和40.8%(p <0.001)。根据Poisson回归,周数和前一天的CO,SO_2,NO_2,NO_x,PM_(2.5)和O_3对学生的哮喘加重有显着影响。随着时间的推移监测空气污染物可能是预测小学生哮喘发作的可靠新方法。这样的预测可以帮助父母和学校护士实施有效的预防措施。

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