Predicting Intra-Urban Variation in Air Pollution Concentrations with Complex Spatio-Temporal Interactions

We describe a methodology for assigning individual estimates of long-term average air pollution concentrations that accounts for a complex spatio-temporal correlation structure and can accommodate unbalanced observations. This methodology has been developed as part of the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air), a prospective cohort study funded by the U.S. EPA to investigate the relationship between chronic exposure to air pollution and cardiovascular disease. Our hierarchical model decomposes the space-time field into a “mean” that includes dependence on covariates and spatially varying seasonal and long-term trends and a “residual” that accounts for spatially correlated deviations from the mean model. The model accommodates complex spatio-temporal patterns by characterizing the temporal trend at each location as a linear combination of empirically derived temporal basis functions, and embedding the spatial fields of coefficients for the basis functions in separate linear regression models with spatially correlated residuals (universal kriging). This approach allows us to implement a scalable single-stage estimation procedure that easily accommodates a significant number of missing observations at some monitoring locations. We apply the model to predict long-term average concentrations of oxides of nitrogen (NOx) from 2005-2007 in the Los Angeles area, based on data from 18 EPA Air Quality System regulatory monitors. The cross-validated R2 is 0.67. The MESA Air study is also collecting additional concentration data as part of a supplementary monitoring campaign. We describe the sampling plan and demonstrate in a simulation study that the additional data will contribute to improved predictions of long-term average concentrations

How much are built environments changing, and where?: Patterns of change by neighborhood sociodemographic characteristics across seven U.S. metropolitan areas

Investments in neighborhood built environments could increase physical activity and overall health. Disproportionate distribution of these changes in advantaged neighborhoods could inflate health disparities. Little information exists on where changes are occurring. This paper aims to 1) identify changes in the built environment in neighborhoods and 2) investigate associations between high levels of change and sociodemographic characteristics. Using Geographic Information Systems, neighborhood land-use, local destinations (for walking, social engagement, and physical activity), and sociodemographics were characterized in 2000 and 2010 for seven U.S. cities. Linear and change on change models estimated associations of built environment changes with baseline (2000) and change (2010–2000) in sociodemographics. Spatial patterns were assessed using Global Moran’s I to measure overall clustering of change and Local Moran’s I to identify statistically significant clusters of high increases surrounded by high increases (HH). Sociodemographic characteristics were compared between HH cluster and other tracts using Analysis of Variance (ANOVA). We observed small land-use changes but increases in the destination types. Greater increases in destinations were associated with higher percentage non-Hispanic whites, percentage households with no vehicle, and median household income. Associations were present for both baseline sociodemographics and changes over time. Greater increases in destinations were associated with lower baseline percentage over 65 but higher increases in percentage over 65 between 2000 and 2010. Global Moran’s indicated changes were spatially clustered. HH cluster tracts started with a higher percentage non-Hispanic whites and higher percentage of households without vehicles. Between 2000 and 2010, HH cluster tracts experienced increases in percent non-Hispanic white, greater increases in median household income, and larger decreases in percent of households without a vehicle. Changes in the built environment are occurring in neighborhoods across a diverse set of U.S. metropolitan areas, but are patterned such that they may lead to increased health disparities over time

Modeling the Residential Infiltration of Outdoor PM2.5 in the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air)

Background: Epidemiologic studies of fine particulate matter [aerodynamic diameter ≤ 2.5 μm (PM2.5)] typically use outdoor concentrations as exposure surrogates. Failure to account for variation in residential infiltration efficiencies (Finf) will affect epidemiologic study results

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

Erratum: Factors influencing time-location patterns and their impact on estimates of exposure: the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air)

We assessed time-location patterns and the role of individual- and residential-level characteristics on these patterns within the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air) cohort and also investigated the impact of individual-level time-location patterns on individual-level estimates of exposure to outdoor air pollution. Reported time-location patterns varied significantly by demographic factors such as age, gender, race/ethnicity, income, education, and employment status. On average Chinese participants reported spending significantly more time indoors and less time outdoors and in transit than white, black, or Hispanic participants. Using a tiered linear regression approach, we predicted time indoors at home and total time indoors. Our model, developed using forward selection procedures, explained 43 percent of the variability in time spent indoors at home, and incorporated demographic, health, lifestyle, and built environment factors. Time-weighted air pollution predictions calculated using recommended time indoors from USEPA(1) overestimated exposures as compared to predictions made with MESA Air participant-specific information. These data fill an important gap in the literature by describing the impact of individual and residential characteristics on time-location patterns and by demonstrating the impact of population-specific data on exposure estimates

Original Contribution Do Psychosocial Stress and Social Disadvantage Modify the Association Between Air Pollution and Blood Pressure? The Multi-Ethnic Study of Atherosclerosis

Researchers have theorized that social and psychosocial factors increase vulnerability to the deleterious health effects of environmental hazards. We used baseline examination data (2000)(2001)(2002) from the Multi-Ethnic Study of Atherosclerosis. Participants were 45-84 years of age and free of clinical cardiovascular disease at enrollment (n = 6814). The modifying role of social and psychosocial factors on the association between exposure to air pollution comprising particulate matter less than 2.5 µm in aerodynamic diameter (PM 2.5 ) and blood pressure measures were examined using linear regression models. There was no evidence of synergistic effects of higher PM 2.5 and adverse social/psychosocial factors on blood pressure. In contrast, there was weak evidence of stronger associations of PM 2.5 with blood pressure in higher socioeconomic status groups. For example, those in the 10th percentile of the income distribution (i.e., low income) showed no association between PM 2.5 and diastolic blood pressure (b = −0.41 mmHg; 95% confidence interval: −1.40, 0.61), whereas those in the 90th percentile of the income distribution (i.e., high income) showed a 1.52-mmHg increase in diastolic blood pressure for each 10-µg/m 3 increase in PM 2.5 (95% confidence interval: 0.22, 2.83). Our results are not consistent with the hypothesis that there are stronger associations between PM 2.5 exposures and blood pressure in persons of lower socioeconomic status or those with greater psychosocial adversity. air pollution; blood pressure; population groups; social environment; social medicine; social psychology Abbreviations: CVD, cardiovascular disease; DBP, diastolic blood pressure; ETS, exposure to second-hand smoke; MAP, mean arterial pressure; MESA, Multi-Ethnic Study of Atherosclerosis; PM 2.5 , particulate matter less than 2.5 µm in aerodynamic diameter; PP, pulse pressure; SBP, systolic blood pressure; SES, socioeconomic status

Air pollution and the microvasculature: A cross-sectional assessment of in vivo retinal images in the population-based multi-ethnic study of atherosclerosis (MESA)

10.1371/journal.pmed.1000372PLoS Medicine711

Exposure to air pollution as a potential contributor to cognitive function, cognitive decline, brain imaging, and dementia: A systematic review of epidemiologic research.

BACKGROUND: Dementia is a devastating condition typically preceded by a long prodromal phase characterized by accumulation of neuropathology and accelerated cognitive decline. A growing number of epidemiologic studies have explored the relation between air pollution exposure and dementia-related outcomes. METHODS: We undertook a systematic review, including quality assessment, to interpret the collective findings and describe methodological challenges that may limit study validity. Articles, which were identified according to a registered protocol, had to quantify the association of an air pollution exposure with cognitive function, cognitive decline, a dementia-related neuroimaging feature, or dementia. RESULTS: We identified 18 eligible published articles. The quality of most studies was adequate to exemplary. Almost all reported an adverse association between at least one pollutant and one dementia-related outcome. However, relatively few studies considered outcomes that provide the strongest evidence for a causal effect, such as within-person cognitive or pathologic changes. Reassuringly, differential selection would likely bias toward a protective association in most studies, making it unlikely to account for observed adverse associations. Likewise, using a formal sensitivity analysis, we found that unmeasured confounding is also unlikely to explain reported adverse associations. DISCUSSION: We also identified several common challenges. First, most studies of incident dementia identified cases from health system records. As dementia in the community is underdiagnosed, this could generate either non-differential or differential misclassification bias. Second, almost all studies used recent air pollution exposures as surrogate measures of long-term exposure. Although this approach may be reasonable if the measured and etiologic exposure windows are separated by a few years, its validity is unknown over longer intervals. Third, comparing the magnitude of associations may not clearly pinpoint which, if any, pollutants are the probable causal agents, because the degree of exposure misclassification differs across pollutants. The epidemiologic evidence, alongside evidence from other lines of research, provides support for a relation of air pollution exposure to dementia. Future studies with improved design, analysis and reporting would fill key evidentiary gaps and provide a solid foundation for recommendations and possible interventions