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

Journal of Environmental Monitoring Pub Date : 2012-12-01 Epub Date: 2012-11-12 DOI:10.1039/c2em30430a
Ahmed H YoussefAgha, Wasantha P Jayawardene, David K Lohrmann, Gamal S El Afandi
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引用次数: 18

摘要

本研究的目的是确定工业化国家小学生哮喘加重(与气候季节有关)与每日暴露于含有颗粒物、二氧化硫、二氧化氮、氮氧化物、一氧化碳和臭氧的空气污染之间是否存在关系,并控制潜在的混杂因素;并且,如果是这样的话,推导出一个统计模型来预测小学生哮喘恶化的变化。采用生态研究设计,分析了宾夕法尼亚州49个县使用“学校健康电子工具”的168,25名小学生的健康记录。哮喘加重由护士记录,作为每天门诊就诊时给予的治疗。每日空气污染测量数据来自环保局的空气质量监测点。根据花粉和历法季节划分哮喘类群。采用泊松回归模型预测哮喘发作次数。哮喘发作以秋季最多,其次为夏季、春季和冬季。如果一天哮喘发作次数为N次,3年哮喘发作次数的日平均值为48次,那么树花粉季节和草花粉季节N > 48的概率分别为56.5%和40.8% (p < 0.001)。根据泊松回归,周数和前一天CO, SO₂,NO₂,NOx, PM₂。₅和O₃对学生的哮喘发作有显著影响。长期监测空气污染物可能是预测小学生哮喘恶化的可靠新手段。这样的预测可以帮助家长和学校护士实施有效的预防措施。
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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.

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 168,25 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, SO₂, NO₂, NOx, PM₂.₅, and O₃ 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.

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来源期刊
Journal of Environmental Monitoring
Journal of Environmental Monitoring 环境科学-分析化学
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