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.

Background: Because ambient air pollution exposure occurs as mixtures, consideration of joint effects of multiple pollutants may advance our understanding of the health effects of air pollution. Methods: We assessed the joint effect of air pollutants on pediatric asthma emergency department visits in Atlanta during 1998–2004. We selected combinations of pollutants that were representative of oxidant gases and secondary, traffic, power plant, and criteria pollutants, constructed using combinations of criteria pollutants and fine particulate matter (PM_2.5) components. Joint effects were assessed using multipollutant Poisson generalized linear models controlling for time trends, meteorology, and daily nonasthma upper respiratory emergency department visit counts. Rate ratios (RRs) were calculated for the combined effect of an interquartile range increment in each pollutant’s concentration. Results: Increases in all of the selected pollutant combinations were associated with increases in warm-season pediatric asthma emergency department visits (eg, joint-effect RR = 1.13 [95% confidence interval = 1.06–1.21] for criteria pollutants, including ozone, carbon monoxide, nitrogen dioxide, sulfur dioxide, and PM_2.5). Cold-season joint effects from models without nonlinear effects were generally weaker than warm-season effects. Joint-effect estimates from multipollutant models were often smaller than estimates based on single-pollutant models, due to control for confounding. Compared with models without interactions, joint-effect estimates from models including first-order pollutant interactions were largely similar. There was evidence of nonlinear cold-season effects. Conclusions: Our analyses illustrate how consideration of joint effects can add to our understanding of health effects of multipollutant exposures and also illustrate some of the complexities involved in calculating and interpreting joint effects of multiple pollutants.

Objective: This study describes associations of ozone and fine particulate matter with Parkinson's disease observed among farmers in North Carolina and Iowa. Methods: We used logistic regression to determine the associations of these pollutants with self-reported, doctor-diagnosed Parkinson's disease. Daily predicted pollutant concentrations were used to derive surrogates of long-term exposure and link them to study participants' geocoded addresses. Results: We observed positive associations of Parkinson's disease with ozone (odds ratio = 1.39; 95% CI: 0.98 to 1.98) and fine particulate matter (odds ratio = 1.34; 95% CI: 0.93 to 1.93) in North Carolina but not in Iowa. Conclusions: The plausibility of an effect of ambient concentrations of these pollutants on Parkinson's disease risk is supported by experimental data demonstrating damage to dopaminergic neurons at relevant concentrations. Additional studies are needed to address uncertainties related to confounding and to examine temporal aspects of the associations we observed.

Retinal degeneration is the leading cause of visual impairment in older adults. An association between retinal degeneration and fungicide use was observed previously among farmer pesticide applicators in the Agricultural Health Study, a large study of farm families from Iowa and North Carolina. The objective of this investigation was to determine whether wives of these farmer pesticide applicators were at increased risk of retinal degeneration. Self-reported cross-sectional data obtained via questionnaire between 1993 and 1997 from 31,173 wives were used. Associations of specific pesticides and groups of pesticides based on function (fungicides, herbicides, insecticides, and fumigants) or chemical structure (organophosphates, organochlorines, and carbamates) with eye disorders were evaluated using logistic and hierarchical logistic regression analyses. Self-reported retinal degeneration was associated with the wife's fungicide use (odds ratio = 1.9, 95% confidence interval: 1.2, 3.1) after adjustment for age and state of residence. Specific fungicides that appeared to drive this association were maneb or mancozeb and ziram. No associations between pesticide use and other eye disorders were found. Although these findings for retinal degeneration are based solely on self-reported disease, they are consistent with those reported for farmer pesticide applicators. These findings suggest that exposure to some fungicides and other pesticides may increase the risk of retinal degeneration and warrant further investigation.