TAILIEUCHUNG - COMBINING EVIDENCE ON AIR POLLUTION AND DAILY MORTALITY FROM THE 20 LARGEST US CITIES: A HIERARCHICAL MODELLING STRATEGY

When technology was introduced to control air pollution by reducing emissions of particles, it was found that the gaseous emissions continued and caused problems of their own. Currently efforts to control both particulate and gaseous emissions have been partially successful in much of the developed world, but there is recent evidence that air pollution is a health risk even under these relatively favorable conditions. In societies that are rapidly developing sufficient resources may not be invested in air pollution control because of other economic and social priorities. The rapid expansion of the industry in these countries has. | J. R. Statist. Soc. A 2000 163 Part 3 Combining evidence on air pollution and daily mortality from the 20 largest US cities a hierarchical modelling strategy Francesca Dominici Jonathan M. Samet and Scott L. Zeger Johns Hopkins University Baltimore USA Read before The Royal Statistical Society on Wednesday January 12th 2000 the President Professor D. A. Lievesley in the Chair Summary. Reports over the last decade of association between levels of particles in outdoor air and daily mortality counts have raised concern that air pollution shortens life even at concentrations within current regulatory limits. Criticisms of these reports have focused on the statistical techniques that are used to estimate the pollution-mortality relationship and the inconsistency in findings between cities. We have developed analytical methods that address these concerns and combine evidence from multiple locations to gain a unified analysis of the data. The paper presents log-linear regression analyses of daily time series data from the largest 20 US cities and introduces hierarchical regression models for combining estimates of the pollution-mortality relationship across cities. We illustrate this method by focusing on mortality effects of PM10 particulate matter less than 10 pm in aerodynamic diameter and by performing univariate and bivariate analyses with PM10 and ozone O3 level. In the first stage of the hierarchical model we estimate the relative mortality rate associated with PM10 for each of the 20 cities by using semiparametric log-linear models. The second stage of the model describes between-city variation in the true relative rates as a function of selected city-specific covariates. We also fit two variations of a spatial model with the goal of exploring the spatial correlation of the pollutant-specific coefficients among cities. Finally to explore the results of considering the two pollutants jointly we fit and compare univariate and bivariate models. All .

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