Semiparametric Latent Variable Regression Models for Spatio-temporal Modeling of Mobile Source Particles in the Greater Boston Area

Traffic particle concentrations show considerable spatial variability within a metropolitan area. We consider latent variable semiparametric regression models for modeling the spatial and temporal variability of black carbon and elemental carbon concentrations in the greater Boston area. Measurements of these pollutants, which are markers of traffic particles, were obtained from several individual exposure studies conducted at specific household locations as well as 15 ambient monitoring sites in the city. The models allow for both flexible, nonlinear effects of covariates and for unexplained spatial and temporal variability in exposure. In addition, the different individual exposure studies recorded different surrogates of traffic particles, with some recording only outdoor concentrations of black or elemental carbon, some recording indoor concentrations of black carbon, and others recording both indoor and outdoor concentrations of black carbon. A joint model for outdoor and indoor exposure that specifies a spatially varying latent variable provides greater spatial coverage in the area of interest. We propose a penalised spline formation of the model that relates to generalised kringing of the latent traffic pollution variable and leads to a natural Bayesian Markov Chain Monte Carlo algorithm for model fitting. We propose methods that allow us to control the degress of freedom of the smoother in a Bayesian framework. Finally, we present results from an analysis that applies the model to data from summer and winter separatel

Municipal Liability and Liability of Supervisors: Litigation Significance of Recent Trends and Developments

The purpose of this presentation is to examine two recent Supreme Court decisions, Connick v. Thompson and Ashcroft v. Iqbal with an eye to their impact on how lower federal courts will assess such claims in the wake of new constraints imposed by these cases. The focus of the discussion will be on developments in single-incident liability cases after Connick and supervisory liability claims after Iqbal

Populations and determinants of airborne fungi in large office buildings

Bioaerosol concentrations in office environments and their roles in causing building-related symptoms have drawn much attention in recent years. Most bioaerosol studies have been cross-sectional. We conducted a longitudinal study to examine the characteristics of airborne fungal populations and correlations with other environmental parameters in office environments. We investigated four office buildings in Boston, Massachusetts, during 1 year beginning May 1997, recruiting 21 offices with open workstations. We conducted intensive bioaerosol sampling every 6 weeks resulting in 10 sets of measurement events at each workstation, and recorded relative humidity, temperature, and CO2 concentrations continuously. We used principal component analysis (PCA) to identify groups of culturable fungal taxa that covaried in air. Four major groupings (PCA factors) were derived where the fungal taxa in the same groupings shared similar ecological requirements. Total airborne fungal concentrations varied significantly by season (highest in summer, lowest in winter) and were positively correlated with relative humidity and negatively related to CO2 concentrations. The first and second PCA factors had similar correlations with environmental variables compared with total fungi. The results of this study provide essential information on the variability within airborne fungal populations in office environments over time. These data also provide background against which cross-sectional data can be compared to facilitate interpretation. More studies are needed to correlate airborne fungi and occupants' health, controlling for seasonal effects and other important environmental factors

Residential Exposure to Traffic-Related Air Pollution and Survival after Heart Failure

Background: Although patients with heart failure (HF) have been identified as particularly susceptible to the acute effects of air pollution, the effects of long-term exposure to air pollution on patients with this increasingly prevalent disease are largely unknown. Objective: This study was designed to examine the mortality risk associated with residential exposure to traffic-related air pollution among HF patients. Methods: A total of 1,389 patients hospitalized with acute HF in greater Worcester, Massachusetts, during 2000 were followed for survival through December 2005. We used daily traffic within 100 and 300 m of residence as well as the distance from residence to major roadways and to bus routes as proxies for residential exposure to traffic-related air pollution. We assessed mortality risks for each exposure variable using Cox proportional hazards models adjusted for prognostic factors. Results: After the 5-year follow-up, only 334 (24%) subjects were still alive. An interquartile range increase in daily traffic within 100 m of home was associated with a mortality hazard ratio (HR) of 1.15 [95% confidence interval (CI), 1.05–1.25], whereas for traffic within 300 m this association was 1.09 (95% CI, 1.01–1.19). The mortality risk decreased with increasing distance to bus routes (HR = 0.88; 95% CI, 0.81–0.96) and was larger for those living within 100 m of a major roadway or 50 m of a bus route (HR = 1.30; 95% CI, 1.13–1.49). Adjustment for area-based income and educational level slightly attenuated these associations. Conclusions: Residential exposure to traffic-related air pollution increases the mortality risk after hospitalization with acute HF. Reducing exposure to traffic-related emissions may improve the long-term prognosis of HF patients

Air conditioning and source-specific particles as modifiers of the effect of PM(10) on hospital admissions for heart and lung disease.

Studies on acute effects of particulate matter (PM) air pollution show significant variability in exposure-effect relations among cities. Recent studies have shown an influence of ventilation on personal/indoor-outdoor relations and stronger associations of adverse effects with combustion-related particles. We evaluated whether differences in prevalence of air conditioning (AC) and/or the contribution of different sources to total PM(10) emissions could partly explain the observed variability in exposure-effect relations. We used regression coefficients of the relation between PM(10) and hospital admissions for chronic obstructive pulmonary disease (COPD), cardiovascular disease (CVD), and pneumonia from a recent study in 14 U.S. cities. We obtained data on the prevalence of AC from the 1993 American Housing Survey and data on PM(10) emissions by source category, vehicle miles traveled (VMT), and population density from the U.S. EPA. We analyzed data using meta-regression techniques. PM(10) regression coefficients for CVD and COPD decreased significantly with increasing percentage of homes with central AC when cities were stratified by whether their PM(10) concentrations peaked in winter or non-winter months. PM(10) coefficients for CVD increased significantly with increasing percentage of PM(10) emission from highway vehicles, highway diesels, oil combustion, metal processing, decreasing percentage of PM(10) emission from fugitive dust, and increasing population density and VMT/mile(2). In multivariate analysis, only percentage of PM(subscript)10(/subscript) from highway vehicles/diesels and oil combustion remained significant. For COPD and pneumonia, associations were less significant but the patterns of the associations were similar to that for CVD. The results suggest that air conditioning and proportion of especially traffic-related particles significantly modify the effect of PM(10) on hospital admissions, especially for CVD

The impact of source contribution uncertainty on the effects of source-specific PM2.5 on hospital admissions: A case study in Boston, MA

Epidemiologic studies of particulate sources and adverse health do not account for the uncertainty in the source contribution estimates. Our goal was to assess the impact of uncertainty on the effect estimates of particulate sources on emergency cardiovascular (CVD) admissions. We examined the effects of PM2.5 sources, identified by positive matrix factorization (PMF) and absolute principle component analysis (APCA), on emergency CVD hospital admissions among Medicare enrollees in Boston, MA, during 2003–2010, given stronger associations for this period. We propagated uncertainty in source contributions using a block bootstrap procedure. We further estimated average across-methods source-specific effect estimates using bootstrap samples. We estimated contributions for regional, mobile, crustal, residual oil combustion, road dust, and sea salt sources. Accounting for uncertainty, same-day exposures to regional pollution were associated with an across-methods average effect of 2.00% (0.18, 3.78%) increase in the rate of CVD admissions. Weekly residual oil exposures resulted in an average 2.12% (0.19, 4.22%) increase. Same-day and 2-day exposures to mobile-related PM2.5 were also associated with increased admissions. Confidence intervals when accounting for the uncertainty were wider than otherwise. Agreement in PMF and APCA results was stronger when uncertainty was considered in health models. Accounting for uncertainty in source contributions leads to more stable effect estimates across methods and potentially to fewer spurious significant associations

Postural Changes in Blood Pressure Associated with Interactions between Candidate Genes for Chronic Respiratory Diseases and Exposure to Particulate Matter

BACKGROUND. Fine particulate matter [aerodynamic diameter ≤ 2.5 μm (PM2.5)] has been associated with autonomic dysregulation. OBJECTIVE. We hypothesized that PM2.5 influences postural changes in systolic blood pressure (ΔSBP) and in diastolic blood pressure (ΔDBP) and that this effect is modified by genes thought to be related to chronic lung disease. METHODS. We measured blood pressure in participants every 3-5 years. ΔSBP and ΔDBP were calculated as sitting minus standing SBP and DBP. We averaged PM2.5 over 48 hr before study visits and analyzed 202 single nucleotide polymorphisms (SNPs) in 25 genes. To address multiple comparisons, data were stratified into a split sample. In the discovery cohort, the effects of SNP x PM2.5 interactions on ΔSBP and ΔDBP were analyzed using mixed models with subject-specific random intercepts. We defined positive outcomes as p < 0.1 for the interaction; we analyzed only these SNPs in the replicate cohort and confirmed them if p < 0.025 with the same sign. Confirmed associations were analyzed within the full cohort in models adjusted for anthropometric and lifestyle factors. RESULTS. Nine hundred forty-five participants were included in our analysis. One interaction with rs9568232 in PHD finger protein 11 (PHF11) was associated with greater ΔDBP. Interactions with rs1144393 in matrix metalloprotease 1 (MMP1) and rs16930692, rs7955200, and rs10771283 in inositol 1,4,5-triphosphate receptor, type 2 (ITPR2) were associated with significantly greater ΔSBP. Because SNPs associated with ΔSBP in our analysis are in genes along the renin-angiotensin pathway, we then examined medications affecting that pathway and observed significant interactions for angiotensin receptor blockers but not angiotensin-converting enzyme inhibitors with PM2.5. CONCLUSIONS. PM2.5 influences blood pressure and autonomic function. This effect is modified by genes and drugs that also act along this pathway.National Institute of Environmental Health Sciences (T32 ES07069, ES0002, ES015172-01, ES014663, P01 ES09825); United States Environmental Protection Agency (R827353, R832416); National Institutes of Health/National Institute of Aging (AG027014); United States Department of Veterans Affairs; Massachusetts Veterans Epidemiology Research and Information Cente