Effect of outdoor airborne particulate matter on daily death counts.

National Institute of Statistical Sciences, Research Triangle Park, NC 27709-4162, USA.
Environmental Health Perspectives (Impact Factor: 7.26). 06/1995; 103(5):490-7.
Source: PubMed

ABSTRACT To investigate the possible relationship between airborne particulate matter and mortality, we developed regression models of daily mortality counts using meteorological covariates and measures of outdoor PM10. Our analyses included data from Cook County, Illinois, and Salt Lake County, Utah. We found no evidence that particulate matter < or = 10 microns (PM10) contributes to excess mortality in Salt Lake County, Utah. In Cook County, Illinois, we found evidence of a positive PM10 effect in spring and autumn, but not in winter and summer. We conclude that the reported effects of particulates on mortality are unconfirmed.

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    ABSTRACT: Recent epidemiological and toxicological studies have shown associations between particulate matter and human health. However, the estimates of adverse health effects are inconsistent across many countries and areas. The stratification and interaction models were employed within the context of the generalized additive Poisson regression equation to examine the acute effects of fine particles on respiratory health and to explore the possible joint modification of temperature, humidity, and season in Beijing, China, for the period 2004-2009. The results revealed that the respiratory health damage threshold of the PM2.5 concentration was mainly within the range of 20-60 μg/m(3), and the adverse effect of excessively high PM2.5 concentration maintained a stable level. In the most serious case, an increase of 10 μg/m(3) PM2.5 results in an elevation of 4.60 % (95 % CI 3.84-4.60 %) and 4.48 % (95 % CI 3.53-5.41 %) with a lag of 3 days, values far higher than the average level of 0.69 % (95 % CI 0.54-0.85 %) and 1.32 % (95 % CI 1.02-1.61 %) for respiratory mortality and morbidity, respectively. There were strong seasonal patterns of adverse effects with the seasonal variation of temperature and humidity. The growth rates of respiratory mortality and morbidity were highest in winter. And, they increased 1.4 and 1.8 times in winter, greater than in the full year as PM2.5 increased 10 μg/m(3).
    Environmental Science and Pollution Research 04/2013; · 2.76 Impact Factor
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    ABSTRACT: We investigated the association between particulate matter less than 10 µm in aerodynamic diameter (PM(10)) exposure and non-accidental mortality in Asian populations by meta-analysis, using both time-series and case-crossover analysis. Among the 819 published studies searched from PubMed and EMBASE using key words related to PM(10) exposure and non-accidental mortality in Asian countries, 8 time-series and 4 case-crossover studies were selected for meta-analysis after exclusion by selection criteria. We obtained the relative risk (RR) and 95% confidence intervals (CI) of non-accidental mortality per 10 µg/m(3) increase of daily PM(10) from each study. We used Q statistics to test the heterogeneity of the results among the different studies and evaluated for publication bias using Begg funnel plot and Egger test. Testing for heterogeneity showed significance (p<0.001); thus, we applied a random-effects model. RR (95% CI) per 10 µg/m(3) increase of daily PM(10) for both the time-series and case-crossover studies combined, time-series studies relative risk only, and case-crossover studies only, were 1.0047 (1.0033 to 1.0062), 1.0057 (1.0029 to 1.0086), and 1.0027 (1.0010 to 1.0043), respectively. The non-significant Egger test suggested that this analysis was not likely to have a publication bias. We found a significant positive association between PM(10) exposure and non-accidental mortality among Asian populations. Continued investigations are encouraged to contribute to the health impact assessment and public health management of air pollution in Asian countries.
    Journal of preventive medicine and public health = Yebang Ŭihakhoe chi. 01/2013; 46(1):10-8.
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    ABSTRACT: In this article, we examine data on the relationship between air quality and mortality in the United States using a published observational data set. Observational studies are complex and open to various interpretations. We show that there is geographic heterogeneity for the effect of air pollution on longevity. We also show that the relative importance of air pollution on longevity is much less than that of income or smoking. Most often authors do not address the relative importance of variables under consideration, choosing instead to concentrate on specific claims of significance. Yet good policy decisions require knowledge of the magnitude of relevant effects. Our analysis uses three methods for determining variable importance, showing how this puts predictor variables into a context that supports sound environmental policymaking. In particular, using both regression and recursive partitioning, we are able to confirm a spatial interaction with the air quality variable PM2.5; there is no significant association of PM2.5 with longevity in the west of the United States. We also determine the relative importance of PM2.5 in comparison to other predictor variables available in this data set. Our findings call into question the claim made by the original researchers. © 2013 Wiley Periodicals, Inc. Statistical Analysis and Data Mining, 2013
    Statistical Analysis and Data Mining 08/2013; 6(4).

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