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An analysis of asthma hospitalizations air pollution and weather conditions in Los Angeles County California

机译:加利福尼亚州洛杉矶县的哮喘住院空气污染和天气状况分析

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摘要

There is now a large body of literature supporting a linkage between exposure to air pollutants and asthma morbidity. However, the extent and significance of this relationship varies considerably between pollutants, location, scale of analysis, and analysis methods. Our primary goal is to evaluate the relationship between asthma hospitalizations, levels of ambient air pollution, and weather conditions in Los Angeles (LA) County, California, an area with a historical record of heavy air pollution. County-wide measures of Carbon Monoxide (CO), Nitrogen Dioxide (NO2), Ozone (O3), Particulate Matter < 10 μ m (PM10), Particulate Matter < 2.5 μ m (PM2.5), maximum temperature, and relative humidity were collected for all months from 2001 to 2008. We then related these variables to monthly asthma hospitalization rates using Bayesian regression models with temporal random effects. We evaluated model performance using a goodness of fit criterion and predictive ability. Asthma hospitalization rates in LA County decreased between 2001 and 2008. Traffic-related pollutants, CO and NO2, were significant and positively correlated with asthma hospitalizations. PM2.5 also had a positive, significant association with asthma hospitalizations. PM10, relative humidity, and maximum temperature produced mixed results, whereas O3 was non-significant in all models. Inclusion of temporal random effects satisfies statistical model assumptions, improves model fit, and yields increased predictive accuracy and precision compared to their non-temporal counterparts. Generally, pollution levels and asthma hospitalizations decreased during the 9 year study period. Our findings also indicate that after accounting for seasonality in the data, asthma hospitalization rate has a significant positive relationship with ambient levels of CO, NO2, and PM2.5.
机译:现在有一个大型的文献,支持在暴露于空气污染物和哮喘发病率之间的联系。然而,这种关系的程度和意义在污染物,位置,分析规模和分析方法之间变化了很大。我们的主要目标是评估哮喘住院,环境空气污染水平,加利福尼亚州洛杉矶(LA)县的天气状况的关系,该地区具有历史风险污染的历史记录。县域各种含量的一氧化碳(CO),二氧化氮(NO2),臭氧(O3),颗粒物<10μm(PM10),颗粒物<2.5μm(PM2.5),最大温度和相对湿度从2001年到2008年的所有月份收集。然后,我们将这些变量与每月哮喘住院费率相关使用贝叶斯回归模型,具有时间随机效应。我们使用拟合标准和预测能力的良好评估模型性能。 La County的哮喘住院费率在2001年至2008年期间减少。交通相关的污染物,CO和No2,与哮喘住院有关,与哮喘住院有关。 PM2.5还与哮喘住院治疗持久性,有关。 PM10,相对湿度和最高温度产生的混合结果,而O3在所有模型中是非显着的。包含时间随机效应满足统计模型假设,提高了模型适合,与其非时间对应物相比,产生的预测精度和精确度提高了预测精度和精度。一般来说,9年的研究期间,污染水平和哮喘住院治疗减少。我们的调查结果还表明,在数据中核算季节性后,哮喘住院率与CO,NO2和PM2.5的环境水平具有显着的阳性关系。

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