Literature DB >> 18079759

Influence of exposure error and effect modification by socioeconomic status on the association of acute cardiovascular mortality with particulate matter in Phoenix.

William E Wilson1, Therese F Mar, Jane Q Koenig.   

Abstract

Using ZIP code-level mortality data, the association of cardiovascular mortality with PM(2.5) and PM(10-2.5), measured at a central monitoring site, was determined for three populations at different distances from the monitoring site but with similar numbers of deaths and therefore similar statistical power. The % risk and statistical significance for the association of mortality with PM(2.5) fell off with distance from the monitor, as would be expected if exposure error increased with distance. However, the % risk for PM(10-2.5) increased in going from the population in Central Phoenix, where the monitoring site was located, to a population in a Middle Ring around Phoenix and fell off in an Outer Ring population. The % risks for the Outer Ring were low for each of the six lag days (0-5) and for the 6-day moving average. The lag structures for PM(2.5) and PM(10-2.5) also differed for the Central Phoenix and Middle Ring populations. These differences led us to examine the socioeconomic status (SES) of the populations. On the basis of education and income, the population in Central Phoenix had a lower SES than the Middle Ring. Thus, the differences between Central Phoenix and the Middle Ring may be due to effect modification by SES and differences in exposure error. However, the effect modification by SES may be different for thoracic coarse particulate matter (PM) than for fine PM. This study provides new information on the association of PM(10-2.5) with cardiovascular mortality. In the Middle Ring, the % risk per 10 microg/m3 increase in PM(10-2.5) concentration (lower and upper 95% confidence levels) for lag day 1 was 3.4 (1.0, 5.8) and for the 6-day distributed-lag was 3.8 (0.3, 7.5). The differences in lag structure for PM(2.5) and PM(10-2.5) provide evidence that the two particle size classes have health effects that are different and independent. This study also helps explain the high % risks for PM(2.5) found for Central Phoenix, 6.6 (1.1, 12.5) for lag day 1, and 11.5 (2.8, 20.9) for the 6-day moving average. The smaller area may have a lower exposure error, and the lower SES population may be more susceptible to fine PM as compared to the larger areas and more heterogeneous populations used in many studies.

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Year:  2007        PMID: 18079759     DOI: 10.1038/sj.jes.7500620

Source DB:  PubMed          Journal:  J Expo Sci Environ Epidemiol        ISSN: 1559-0631            Impact factor:   5.563


  12 in total

Review 1.  Evidence on vulnerability and susceptibility to health risks associated with short-term exposure to particulate matter: a systematic review and meta-analysis.

Authors:  Michelle L Bell; Antonella Zanobetti; Francesca Dominici
Journal:  Am J Epidemiol       Date:  2013-07-25       Impact factor: 4.897

2.  Ambient air pollutant measurement error: characterization and impacts in a time-series epidemiologic study in Atlanta.

Authors:  Gretchen T Goldman; James A Mulholland; Armistead G Russell; Abhishek Srivastava; Matthew J Strickland; Mitchel Klein; Lance A Waller; Paige E Tolbert; Eric S Edgerton
Journal:  Environ Sci Technol       Date:  2010-10-01       Impact factor: 9.028

3.  The effect of particle size, location and season on the toxicity of urban and rural particulate matter.

Authors:  Jaime Mirowsky; Christina Hickey; Lori Horton; Martin Blaustein; Karen Galdanes; Richard E Peltier; Steven Chillrud; Lung Chi Chen; James Ross; Arthur Nadas; Morton Lippmann; Terry Gordon
Journal:  Inhal Toxicol       Date:  2013-11       Impact factor: 2.724

4.  An examination of exposure measurement error from air pollutant spatial variability in time-series studies.

Authors:  Stefanie E Sarnat; Mitchel Klein; Jeremy A Sarnat; W Dana Flanders; Lance A Waller; James A Mulholland; Armistead G Russell; Paige E Tolbert
Journal:  J Expo Sci Environ Epidemiol       Date:  2009-03-11       Impact factor: 5.563

5.  Characterization of Ambient Air Pollution Measurement Error in a Time-Series Health Study using a Geostatistical Simulation Approach.

Authors:  Gretchen T Goldman; James A Mulholland; Armistead G Russell; Katherine Gass; Matthew J Strickland; Paige E Tolbert
Journal:  Atmos Environ (1994)       Date:  2012-09       Impact factor: 4.798

6.  Study on sandstorm PM10 exposure assessment in the large-scale region: a case study in Inner Mongolia.

Authors:  Hongmei Wang; Shihai Lv; Zhaoyan Diao; Baolu Wang; Han Zhang; Caihong Yu
Journal:  Environ Sci Pollut Res Int       Date:  2018-04-12       Impact factor: 4.223

7.  Health impact assessment of exposure to fine particulate matter based on satellite and meteorological information.

Authors:  Hak-Kan Lai; Hilda Tsang; Thuan-Quoc Thach; Chit-Ming Wong
Journal:  Environ Sci Process Impacts       Date:  2014-02       Impact factor: 4.238

Review 8.  Particulate matter-induced health effects: who is susceptible?

Authors:  Jason D Sacks; Lindsay Wichers Stanek; Thomas J Luben; Douglas O Johns; Barbara J Buckley; James S Brown; Mary Ross
Journal:  Environ Health Perspect       Date:  2010-10-20       Impact factor: 9.031

Review 9.  Ambient Coarse Particulate Matter and Human Health: A Systematic Review and Meta-Analysis.

Authors:  Sara D Adar; Paola A Filigrana; Nicholas Clements; Jennifer L Peel
Journal:  Curr Environ Health Rep       Date:  2014-08-08

10.  Association between Ambient Air Pollution and Emergency Room Visits for Respiratory Diseases in Spring Dust Storm Season in Lanzhou, China.

Authors:  Yuxia Ma; Bingshuang Xiao; Chang Liu; Yuxin Zhao; Xiaodong Zheng
Journal:  Int J Environ Res Public Health       Date:  2016-06-21       Impact factor: 3.390

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