Long-term exposure to outdoor particulate matter with an aerodynamic diameter less than or equal to 2.5 µm (PM_2.5) has been associated with cardiovascular morbidity and mortality. The chemical composition of PM_2.5 that may be most responsible for producing these associations has not been identified. We assessed cross-sectional associations between long-term concentrations of PM_2.5 and 4 of its chemical components (sulfur, silicon, elemental carbon, and organic carbon (OC)) and subclinical atherosclerosis, measured as carotid intima-media thickness (CIMT) and coronary artery calcium, between 2000 and 2002 among 5,488 Multi-Ethnic Study of Atherosclerosis participants residing in 6 US metropolitan areas. Long-term concentrations of PM_2.5 components at participants' homes were predicted using both city-specific spatiotemporal models and a national spatial model. The estimated differences in CIMT associated with interquartile-range increases in sulfur, silicon, and OC predictions from the spatiotemporal model were 0.022 mm (95% confidence interval (CI): 0.014, 0.031), 0.006 mm (95% CI: 0.000, 0.012), and 0.026 mm (95% CI: 0.019, 0.034), respectively. Findings were generally similar using the national spatial model predictions but were often sensitive to adjustment for city. We did not find strong evidence of associations with coronary artery calcium. Long-term concentrations of sulfur and OC, and possibly silicon, were associated with CIMT using 2 distinct exposure prediction modeling approaches.

Background: Concentrations of outdoor fine particulate matter (PM_2.5) have been associated with cardiovascular disease. PM_2.5 chemical composition may be responsible for effects of exposure to PM_2.5. Methods: Using data from the Multi-Ethnic Study of Atherosclerosis (MESA) collected in 2000–2002 on 6,256 US adults without clinical cardiovascular disease in six U.S. metropolitan areas, we investigated cross-sectional associations of estimated long-term exposure to total PM_2.5 mass and PM_2.5 components (elemental carbon [EC], organic carbon [OC], silicon and sulfur) with measures of subclinical atherosclerosis (coronary artery calcium [CAC] and right common carotid intima-media thickness [CIMT]). Community monitors deployed for this study from 2007 to 2008 were used to estimate exposures at baseline addresses using three commonly-used approaches: (1) nearest monitor (the primary approach), (2) inverse-distance monitor weighting and (3) city-wide average. Results: Using the exposure estimate based on nearest monitor, in single-pollutant models, increased OC (effect estimate [95% CI] per IQR: 35.1 μm [26.8, 43.3]), EC (9.6 μm [3.6,15.7]), sulfur (22.7 μm [15.0,30.4]) and total PM_2.5 (14.7 μm [9.0,20.5]) but not silicon (5.2 μm [−9.8,20.1]), were associated with increased CIMT; in two-pollutant models, only the association with OC was robust to control for the other pollutants. Findings were generally consistent across the three exposure estimation approaches. None of the PM measures were positively associated with either the presence or extent of CAC. In sensitivity analyses, effect estimates for OC and silicon were particularly sensitive to control for metropolitan area. Conclusion: Employing commonly-used exposure estimation approaches, all of the PM_2.5 components considered, except silicon, were associated with increased CIMT, with the evidence being strongest for OC; no component was associated with increased CAC. PM_2.5 chemical components, or other features of the sources that produced them, may be important in determining the effect of PM exposure on atherosclerosis. These cross-sectional findings await confirmation in future work employing longitudinal outcome measures and using more sophisticated approaches to estimating exposure.

Associations of short-term exposure to fine particulate matter (PM2.5) with daily mortality may be due to specific PM2.5 chemical components. Daily concentrations of PM2.5 components were measured over five years in Denver to investigate whether specific PM2.5 components are associated with daily mortality. Daily counts of total and cause-specific deaths were obtained for the 5-county Denver metropolitan region from 2003 through 2007. Daily 24-hour concentrations of PM2.5, elemental carbon (EC), organic carbon (OC), sulfate and nitrate were measured at a central residential monitoring site. Using generalized additive models, we estimated relative risks (RRs) of daily death counts for daily PM2.5 and four PM2.5 component concentrations at single and distributed lags between the current and three previous days, while controlling for longer-term time trend and meteorology. RR of total non-accidental mortality for an inter-quartile increase of 4.55 μg/m3 in PM2.5 distributed over 4 days was 1.012 (95 % confidence interval: 0.999, 1.025); RRs for EC and OC were larger (1.024 [1.005, 1.043] and 1.020 [1.000, 1.040] for 0.33 and 1.67 μg/m3 increases, respectively) than those for sulfate and nitrate. We generally did not observe associations with cardiovascular and respiratory mortality except for associations with ischemic heart disease mortality at lags 3 and 0–3 depending on the component. In addition, there were associations with cancer mortality, particularly for EC and OC, possibly reflecting advanced deaths of a frail population. PM2.5 components possibly from combustion-related sources are more strongly associated with daily mortality than are secondary inorganic aerosols.

No cohort studies in China on the health effects of long-term air pollution exposure have employed exposure estimates at the fine spatial scales desirable for cohort studies with individual-level health outcome data. Here we assess an array of modern air pollution exposure estimation approaches for assigning within-city exposure estimates in Beijing for individual pollutants and pollutant sources to individual members of a cohort. Issues considered in selecting specific monitoring data or new monitoring campaigns include: needed spatial resolution, exposure measurement error and its impact on health effect estimates, spatial alignment and compatibility with the cohort, and feasibility and expense. Sources of existing data largely include administrative monitoring data, predictions from air dispersion or chemical transport models and remote sensing (specifically satellite) data. New air monitoring campaigns include additional fixed site monitoring, snapshot monitoring, passive badge or micro-sensor saturation monitoring and mobile monitoring, as well as combinations of these. Each of these has relative advantages and disadvantages. It is concluded that a campaign in Beijing that at least includes a mobile monitoring component, when coupled with currently available spatio-temporal modeling methods, should be strongly considered. Such a campaign is economical and capable of providing the desired fine-scale spatial resolution for pollutants and sources.