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Application of Multivariate Geostatistics in Environmental Epidemiology: Case Study from Houston, Texas 被引量:3
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作者 Faye Anderson 《Journal of Geoscience and Environment Protection》 2016年第4期110-115,共6页
This study represents an example of investigating the associations between the joint exposure to ozone (O3) and particulate matter of sizes less than or equal to 2.5 micrometers in aerodynamic diameter (PM2.5) and car... This study represents an example of investigating the associations between the joint exposure to ozone (O3) and particulate matter of sizes less than or equal to 2.5 micrometers in aerodynamic diameter (PM2.5) and cardiovascular disease (CVD) emergency room (ER) visits and chronic obstructive pulmonary disease (COPD) ER visits using multivariate geostatistics in Houston, Texas, from 2004 to 2009. Analyses showed lack of strong pair-wise association among the predictors of O3, PM2.5, wind speed, relative humidity, and temperature. Whereas CVD and COPD ER visits exhibited a strong positive correlation. Both outcomes drastically increased from 2006 possibly due to immigration from neighboring locations. Parametric testing showed that the data differed significantly between the years. Multivariate multiple regression results on the 2009 data showed that PM2.5, relative humidity, and temperature were significant to both CVD and COPD ER visits. Codispersion coefficients were constant which justified the assumption of intrinsic correlation. That is, our predictors had strong influence on the spatial variability of CVD and COPD ER visits. This multivariate geostatistics approach predicted an increase of 34% in CVD ER visits and 24% increase in COPD ER visits, which calls for more attention from policy makers. The use of multivariate geostatistics analyses enabled us to successfully detect the effects of risk factors on both outcomes. 展开更多
关键词 multivariate geostatistics COPD CVD HARRIS HOUSTON PM2.5 OZONE
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Assessing the Association between Heart Attack, High Blood Pressure, and Heart Disease Mortality Rates and Particulate Matter and Socioeconomic Status Using Multivariate Geostatistical Model 被引量:2
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作者 Faye Anderson 《Occupational Diseases and Environmental Medicine》 2016年第1期8-15,共8页
This study addresses the public concerns of potential adverse health effects from ambient fine particulate matter as well as socioeconomic factors. Heart attack, high blood pressure, and heart disease mortality rates ... This study addresses the public concerns of potential adverse health effects from ambient fine particulate matter as well as socioeconomic factors. Heart attack, high blood pressure, and heart disease mortality rates were investigated against fine particulate matter and socioeconomic status, for all counties in the United States in 2013. Multivariate multiple regressions as well as multivariate geostatistical predictions show that these are significant factors towards assessing the causal inferences between exposure to air pollution and socioeconomic status and the three mortality rates. 展开更多
关键词 Heart Attack High Blood Pressure Heart Disease MORTALITY United States multivariate geostatistics Coregionalization multivariate Multiple Linear
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