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      PM 10 Exposure and Non-accidental Mortality in Asian Populations: A Meta-analysis of Time-series and Case-crossover Studies

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          Abstract

          Objectives

          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.

          Methods

          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.

          Results

          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.

          Conclusions

          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.

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          Most cited references42

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          Ozone and short-term mortality in 95 US urban communities, 1987-2000.

          Ozone has been associated with various adverse health effects, including increased rates of hospital admissions and exacerbation of respiratory illnesses. Although numerous time-series studies have estimated associations between day-to-day variation in ozone levels and mortality counts, results have been inconclusive. To investigate whether short-term (daily and weekly) exposure to ambient ozone is associated with mortality in the United States. Using analytical methods and databases developed for the National Morbidity, Mortality, and Air Pollution Study, we estimated a national average relative rate of mortality associated with short-term exposure to ambient ozone for 95 large US urban communities from 1987-2000. We used distributed-lag models for estimating community-specific relative rates of mortality adjusted for time-varying confounders (particulate matter, weather, seasonality, and long-term trends) and hierarchical models for combining relative rates across communities to estimate a national average relative rate, taking into account spatial heterogeneity. Daily counts of total non-injury-related mortality and cardiovascular and respiratory mortality in 95 large US communities during a 14-year period. A 10-ppb increase in the previous week's ozone was associated with a 0.52% increase in daily mortality (95% posterior interval [PI], 0.27%-0.77%) and a 0.64% increase in cardiovascular and respiratory mortality (95% PI, 0.31%-0.98%). Effect estimates for aggregate ozone during the previous week were larger than for models considering only a single day's exposure. Results were robust to adjustment for particulate matter, weather, seasonality, and long-term trends. These results indicate a statistically significant association between short-term changes in ozone and mortality on average for 95 large US urban communities, which include about 40% of the total US population. The findings indicate that this widespread pollutant adversely affects public health.
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            Particulate air pollution and acute health effects.

            Epidemiological studies have consistently shown an association between particulate air pollution and not only exacerbations of illness in people with respiratory disease but also rises in the numbers of deaths from cardiovascular and respiratory disease among older people. Meta-analyses of these studies indicate that the associations are unlikely to be explained by any confounder, and suggest that they represent cause and effect. We propose that the explanation lies in the nature of the urban particulate cloud, which may contain up to 100000 nanometer-sized particles per mL, in what may be a gravimetric concentration of only 100-200 micrograms/m3 of pollutant. We suggest that such ultra-fine particles are able to provoke alveolar inflammation, with release of mediators capable, in susceptible individuals, of causing exacerbations of lung disease and of increasing blood coagulability, thus also explaining the observed increases in cardiovascular deaths associated with urban pollution episodes. This hypothesis is testable both experimentally and epidemiologically.
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              On the use of generalized additive models in time-series studies of air pollution and health.

              F Dominici (2002)
              The widely used generalized additive models (GAM) method is a flexible and effective technique for conducting nonlinear regression analysis in time-series studies of the health effects of air pollution. When the data to which the GAM are being applied have two characteristics--1) the estimated regression coefficients are small and 2) there exist confounding factors that are modeled using at least two nonparametric smooth functions--the default settings in the gam function of the S-Plus software package (version 3.4) do not assure convergence of its iterative estimation procedure and can provide biased estimates of regression coefficients and standard errors. This phenomenon has occurred in time-series analyses of contemporary data on air pollution and mortality. To evaluate the impact of default implementation of the gam software on published analyses, the authors reanalyzed data from the National Morbidity, Mortality, and Air Pollution Study (NMMAPS) using three different methods: 1) Poisson regression with parametric nonlinear adjustments for confounding factors; 2) GAM with default convergence parameters; and 3) GAM with more stringent convergence parameters than the default settings. The authors found that pooled NMMAPS estimates were very similar under the first and third methods but were biased upward under the second method.
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                Author and article information

                Journal
                J Prev Med Public Health
                J Prev Med Public Health
                JPMPH
                Journal of Preventive Medicine and Public Health
                The Korean Society for Preventive Medicine
                1975-8375
                2233-4521
                January 2013
                31 January 2013
                : 46
                : 1
                : 10-18
                Affiliations
                [1 ]Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Korea.
                [2 ]Institute of Environmental Medicine, Seoul National University Medical Research Center, Seoul, Korea.
                Author notes
                Corresponding author: Yun-Chul Hong, MD, PhD. 103 Daehak-ro, Jongno-gu, Seoul 110-799, Korea. Tel: +82-2-740-8394, Fax: +82-2-747-4830, ychong1@ 123456snu.ac.kr
                Article
                10.3961/jpmph.2013.46.1.10
                3567321
                23407325
                29cf4932-8fda-495c-8702-cb651fa98b3a
                Copyright © 2013 The Korean Society for Preventive Medicine

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 21 September 2012
                : 22 November 2012
                Categories
                Original Article

                Public health
                asia,meta-analysis,non-accidental mortality,pm10
                Public health
                asia, meta-analysis, non-accidental mortality, pm10

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