BackgroundEpidemiological, controlled human exposure, and toxicological studies have demonstrated a variety of health effects in response to particulate matter (PM) exposure with some of these studies indicating that populations with certain characteristics may be disproportionately affected.ObjectiveTo identify populations potentially at greatest risk for PM-related health effects, we evaluated epidemiological studies that examined various characteristics that may influence susceptibility, while using results from controlled human exposure and toxicological studies as supporting evidence. Additionally, we formulated a definition of susceptibility, building from the varied and inconsistent definitions of susceptibility and vulnerability used throughout the literature.Data synthesisWe evaluated recent epidemiological studies to identify characteristics of populations potentially susceptible to PM-related health effects. Additionally, we evaluated controlled human exposure and toxicological studies to provi...

Objectives. To quantify nationwide disparities in the location of particulate matter (PM)-emitting facilities by the characteristics of the surrounding residential population and to illustrate various spatial scales at which to consider such disparities. Methods. We assigned facilities emitting PM in the 2011 National Emissions Inventory to nearby block groups across the 2009 to 2013 American Community Survey population. We calculated the burden from these emissions for racial/ethnic groups and by poverty status. We quantified disparities nationally and for each state and county in the country. Results. For PM of 2.5 micrometers in diameter or less, those in poverty had 1.35 times higher burden than did the overall population, and non-Whites had 1.28 times higher burden. Blacks, specifically, had 1.54 times higher burden than did the overall population. These patterns were relatively unaffected by sensitivity analyses, and disparities held not only nationally but within most states and counties as well. Conclusions. Disparities in burden from PM-emitting facilities exist at multiple geographic scales. Disparities for Blacks are more pronounced than are disparities on the basis of poverty status. Strictly socioeconomic considerations may be insufficient to reduce PM burdens equitably across populations.

Exposure to fine particulate matter (PM_2.5), an ambient air pollutant with mass-based standards promulgated under the Clean Air Act, and black carbon (BC), a common component of PM_2.5, are both associated with cardiovascular health effects. To elucidate whether BC is associated with distinct, or stronger, cardiovascular responses compared to PM_2.5, we conducted a systematic review. We evaluated the associations of short- and long-term BC, or the related component elemental carbon (EC), with cardiovascular endpoints including heart rate variability, heart rhythm, blood pressure and vascular function, ST segment depression, repolarization abnormalities, atherosclerosis and heart function, in the context of what is already known about PM_2.5. We conducted a stepwise systematic literature search of the PubMed, Web of Science and TOXLINE databases and applied Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines for reporting our results. Studies reporting effect estimates for the association of quantitative measurements of ambient BC (or EC) and PM_2.5, with relevant cardiovascular endpoints (i.e. meeting inclusion criteria) were included in the review. Included studies were evaluated for risk of bias in study design and results. Risk of bias evaluations assessed aspects of internal validity of study findings based on study design, conduct, and reporting to identify potential issues related to confounding or other biases. Study results are presented to facilitate comparison of the consistency of associations with PM_2.5 and BC within and across studies. Our results demonstrate similar associations for BC (or EC) and PM_2.5 with the cardiovascular endpoints examined. Across studies, associations for BC and PM_2.5 varied in their magnitude and precision, and confidence intervals were generally overlapping within studies. Where differences in the magnitude of the association between BC or EC and PM_2.5 within a study could be discerned, no consistent pattern across the studies examined was apparent. We were unable to assess the independence of the effect of BC, relative the effect of PM_2.5, on the cardiovascular system, nor was information available to understand the impact of differential exposure misclassification. Overall, the evidence indicates that both BC (or EC) and PM_2.5 are associated with cardiovascular effects but the available evidence is not sufficient to distinguish the effect of BC (or EC) from that of PM_2.5 mass.

Multi-city population-based epidemiological studies have observed heterogeneity between city-specific fine particulate matter (PM2.5)-mortality effect estimates. These studies typically use ambient monitoring data as a surrogate for exposure leading to potential exposure misclassification. The level of exposure misclassification can differ by city affecting the observed health effect estimate. The objective of this analysis is to evaluate whether previously developed residential infiltration-based city clusters can explain city-to-city heterogeneity in PM2.5 mortality risk estimates. In a prior paper 94 cities were clustered based on residential infiltration factors (e.g. home age/size, prevalence of air conditioning (AC)), resulting in 5 clusters. For this analysis, the association between PM2.5 and all-cause mortality was first determined in 77 cities across the United States for 2001–2005. Next, a second stage analysis was conducted evaluating the influence of cluster assignment on heterogeneity in the risk estimates. Associations between a 2-day (lag 0–1 days) moving average of PM2.5 concentrations and non-accidental mortality were determined for each city. Estimated effects ranged from −3.2 to 5.1% with a pooled estimate of 0.33% (95% CI: 0.13, 0.53) increase in mortality per 10 μg/m3 increase in PM2.5. The second stage analysis determined that cluster assignment was marginally significant in explaining the city-to-city heterogeneity. The health effects estimates in cities with older, smaller homes with less AC (Cluster 1) and cities with newer, smaller homes with a large prevalence of AC (Cluster 3) were significantly lower than the cluster consisting of cities with older, larger homes with a small percentage of AC. This is the first study that attempted to examine whether multiple exposure factors could explain the heterogeneity in PM2.5-mortality associations. The results of this study were found to explain a small portion (6%) of this heterogeneity.