Issues Related to Combining Multiple Speciated PM2.5 Data Sources in Spatio-Temporal Exposure Models for Epidemiology: The NPACT Case Study

Background: Regulatory monitoring data have been the most common exposure data resource in studies of the association between long-term PM2.5 components and health. However, data collected for regulatory purposes may not be compatible with epidemiological study. Objectives: We aimed to explore three important features of the PM2.5 component monitoring data obtained from multiple sources to combine all available data for developing spatio-temporal prediction models in the National Particle Component and Toxicity (NPACT) study. Methods: The NPACT monitoring data were collected in an extensive monitoring campaign targeting cohort participants. The regulatory monitoring data were obtained from the Chemical Speciation Network (CSN) and the Interagency Monitoring of Protected Visual Environments (IMPROVE). We performed exploratory analyses to examine three features that could affect our approach to combining data: comprehensiveness of spatial coverage, comparability of analysis methods, and consistency in sampling protocols. In addition, we considered the viability of developing a spatio-temporal prediction model given: 1) all available data; 2) NPACT data only; and 3) NPACT data with temporal trends estimated from other pollutants. Results: The number of CSN/IMPROVE monitors was limited in all study areas. The different laboratory analysis methods and the protocol differences for sampling resulted in incompatible measurements between networks. Given these features, we determined that it was preferable to develop our spatio-temporal model using only the NPACT data and under simplifying assumptions. Conclusions: Investigators conducting epidemiological studies of long-term PM2.5 components need to be mindful of the features of the monitoring data and incorporate this understanding into exposure model development

Particulate matter components and subclinical atherosclerosis: common approaches to estimating exposure in a Multi-Ethnic Study of Atherosclerosis cross-sectional study

Abstract Background Concentrations of outdoor fine particulate matter (PM2.5) have been associated with cardiovascular disease. PM2.5 chemical composition may be responsible for effects of exposure to PM2.5. 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 PM2.5 mass and PM2.5 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 PM2.5 (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 PM2.5 components considered, except silicon, were associated with increased CIMT, with the evidence being strongest for OC; no component was associated with increased CAC. PM2.5 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.http://deepblue.lib.umich.edu/bitstream/2027.42/112668/1/12940_2013_Article_651.pd

Prediction of fine particulate matter chemical components for the Multi-Ethnic Study of Atherosclerosis cohort: A comparison of two modeling approaches

Recent epidemiological cohort studies of the health effects of PM2.5 have developed exposure estimates from advanced exposure prediction models. Such models represent spatial variability across participant residential locations. However, few cohort studies have developed exposure predictions for PM2.5 components. We used two exposure modeling approaches to obtain long-term average predicted concentrations for four PM2.5 components: sulfur, silicon, and elemental and organic carbon (EC and OC). The models were specifically developed for the Multi-Ethnic Study of Atherosclerosis (MESA) cohort as a part of the National Particle Component and Toxicity (NPACT) study. The spatio-temporal model used 2-week average measurements from a monitoring campaign focusing on MESA participants, whereas the national spatial model relied on long-term means of daily measurements from the existing federally directed monitoring network. The spatio-temporal modeling framework consisted of long-term means, temporal trends, and spatio-temporal residuals. Spatial fields for long-term means and temporal trends were characterized in universal kriging with a land use regression component based on selected geographic covariates. The national spatial model was also constructed in a universal kriging approach with the mean model characterized by partial least squares scores instead of selected covariates. The cross-validation statistics of the two exposure models were 0.59 to 0.94 for sulfur, EC, and OC but 0.38 to 0.45 for silicon across the six study areas. Predicted long-term concentrations of PM2.5 components from the two models were fairly or highly correlated across cities within each of all four components except for OC, largely dominated by the between-city contrast. However, predictions were less correlated within each city than across cities. The national spatial model gave lower magnitude and less variable predictions than the spatio-temporal model. Different sources of monitoring data and modeling approaches between the two models contributed to these results. Predictions of long-term average concentrations for PM2.5 components for study subjects will allow us to investigate health effects of PM2.5 components and identify PM2.5 components responsible for the PM2.5 association

Fine Particulate Air Pollution and the Progression of Carotid Intima-Medial Thickness: A Prospective Cohort Study from the Multi-Ethnic Study of Atherosclerosis and Air Pollution

Background Fine particulate matter (PM2.5) has been linked to cardiovascular disease, possibly via accelerated atherosclerosis. We examined associations between the progression of the intima-medial thickness (IMT) of the common carotid artery, as an indicator of atherosclerosis, and long-term PM2.5 concentrations in participants from the Multi-Ethnic Study of Atherosclerosis (MESA). Methods and Results MESA, a prospective cohort study, enrolled 6,814 participants at the baseline exam (2000–2002), with 5,660 (83%) of those participants completing two ultrasound examinations between 2000 and 2005 (mean follow-up: 2.5 years). PM2.5 was estimated over the year preceding baseline and between ultrasounds using a spatio-temporal model. Cross-sectional and longitudinal associations were examined using mixed models adjusted for confounders including age, sex, race/ethnicity, smoking, and socio-economic indicators. Among 5,362 participants (5% of participants had missing data) with a mean annual progression of 14 µm/y, 2.5 µg/m3 higher levels of residential PM2.5 during the follow-up period were associated with 5.0 µm/y (95% CI 2.6 to 7.4 µm/y) greater IMT progressions among persons in the same metropolitan area. Although significant associations were not found with IMT progression without adjustment for metropolitan area (0.4 µm/y [95% CI −0.4 to 1.2 µm/y] per 2.5 µg/m3), all of the six areas showed positive associations. Greater reductions in PM2.5 over follow-up for a fixed baseline PM2.5 were also associated with slowed IMT progression (−2.8 µm/y [95% CI −1.6 to −3.9 µm/y] per 1 µg/m3 reduction). Study limitations include the use of a surrogate measure of atherosclerosis, some loss to follow-up, and the lack of estimates for air pollution concentrations prior to 1999. Conclusions This early analysis from MESA suggests that higher long-term PM2.5 concentrations are associated with increased IMT progression and that greater reductions in PM2.5 are related to slower IMT progression. These findings, even over a relatively short follow-up period, add to the limited literature on air pollution and the progression of atherosclerotic processes in humans. If confirmed by future analyses of the full 10 years of follow-up in this cohort, these findings will help to explain associations between long-term PM2.5 concentrations and clinical cardiovascular events. Please see later in the article for the Editors' Summar

The short-term association of selected components of fine particulate matter and mortality in the Denver Aerosol Sources and Health (DASH) study

Background: Associations of short-term exposure to fine particulate matter (PM2.5) with daily mortality may be due to specific PM2.5&nbsp;chemical components. Daily concentrations of PM2.5&nbsp;components were measured over five years in Denver to investigate whether specific PM2.5&nbsp;components are associated with daily mortality. Methods: 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&nbsp;and four PM2.5&nbsp;component concentrations at single and distributed lags between the current and three previous days, while controlling for longer-term time trend and meteorology. Results: RR of total non-accidental mortality for an inter-quartile increase of 4.55 &mu;g/m3&nbsp;in PM2.5&nbsp;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 &mu;g/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&ndash;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. Conclusions: PM2.5 components possibly from combustion-related sources are more strongly associated with daily mortality than are secondary inorganic aerosols.</p

Individual and Neighborhood Socioeconomic Status and the Association between Air Pollution and Cardiovascular Disease

BACKGROUND: Long-term fine particulate matter (PM2.5) exposure is linked with cardiovascular disease, and disadvantaged status may increase susceptibility to air pollution-related health effects. In addition, there are concerns that this association may be partially explained by confounding by socioeconomic status (SES). OBJECTIVES: We examined the roles that individual- and neighborhood-level SES (NSES) play in the association between PM2.5 exposure and cardiovascular disease. METHODS: The study population comprised 51,754 postmenopausal women from the Women's Health Initiative Observational Study. PM2.5 concentrations were predicted at participant residences using fine-scale regionalized universal kriging models. We assessed individual-level SES and NSES (Census-tract level) across several SES domains including education, occupation, and income/wealth, as well as through an NSES score, which captures several important dimensions of SES. Cox proportional-hazards regression adjusted for SES factors and other covariates to determine the risk of a first cardiovascular event. RESULTS: A 5 μg/m3 higher exposure to PM2.5 was associated with a 13% increased risk of cardiovascular event [hazard ratio (HR) 1.13; 95% confidence interval (CI): 1.02, 1.26]. Adjustment for SES factors did not meaningfully affect the risk estimate. Higher risk estimates were observed among participants living in low-SES neighborhoods. The most and least disadvantaged quartiles of the NSES score had HRs of 1.39 (95% CI: 1.21, 1.61) and 0.90 (95% CI: 0.72, 1.07), respectively. CONCLUSIONS: Women with lower NSES may be more susceptible to air pollution-related health effects. The association between air pollution and cardiovascular disease was not explained by confounding from individual-level SES or NSES. Citation: Chi GC, Hajat A, Bird CE, Cullen MR, Griffin BA, Miller KA, Shih RA, Stefanick ML, Vedal S, Whitsel EA, Kaufman JD. 2016. Individual and neighborhood socioeconomic status and the association between air pollution and cardiovascular disease. Environ Health Perspect 124:1840-1847; http://dx.doi.org/10.1289/EHP199

Positive Matrix Factorization of PM2.5 - Eliminating the Effects of Gas/Particle Partitioning of Semivolatile Organic Compounds

Gas-phase concentrations of semi-volatile organic compounds (SVOCs) were calculated from gas/particle (G/P) partitioning theory using their measured particle-phase concentrations. The particle-phase data were obtained from an existing filter measurement campaign (27 January 2003-2 October 2005) as a part of the Denver Aerosol Sources and Health (DASH) study, including 970 observations of 71 SVOCs (Xie et al., 2013). In each compound class of SVOCs, the lighter species (e.g. docosane in n-alkanes, fluoranthene in PAHs) had higher total concentrations (gas + particle phase) and lower particle-phase fractions. The total SVOC concentrations were analyzed using positive matrix factorization (PMF). Then the results were compared with source apportionment results where only particle-phase SVOC concentrations were used (filter-based study; Xie et al., 2013). For the filter-based PMF analysis, the factors primarily associated with primary or secondary sources (n-alkane, EC/sterane and inorganic ion factors) exhibit similar contribution time series (r = 0.92-0.98) with their corresponding factors (n-alkane, sterane and nitrate + sulfate factors) in the current work. Three other factors (light n-alkane/PAH, PAH and summer/odd n-alkane factors) are linked with pollution sources influenced by atmospheric processes (e.g. G/P partitioning, photochemical reaction), and were less correlated (r = 0.69-0.84) with their corresponding factors (light SVOC, PAH and bulk carbon factors) in the current work, suggesting that the source apportionment results derived from filter-based SVOC data could be affected by atmospheric processes. PMF analysis was also performed on three temperature-stratified subsets of the total SVOC data, representing ambient sampling during cold (daily average temperature20°C) periods. Unlike the filter-based study, in this work the factor characterized by the low molecular weight (MW) compounds (light SVOC factor) exhibited strong correlations (r = 0.82-0.98) between the full data set and each sub-data set solution, indicating that the impacts of G/P partitioning on receptor-based source apportionment could be eliminated by using total SVOC concentrations