Ambient Air Pollution and Atherosclerosis in Los Angeles

Associations have been found between long-term exposure to ambient air pollution and cardiovascular morbidity and mortality. The contribution of air pollution to atherosclerosis that underlies many cardiovascular diseases has not been investigated. Animal data suggest that ambient particulate matter (PM) may contribute to atherogenesis. We used data on 798 participants from two clinical trials to investigate the association between atherosclerosis and long-term exposure to ambient PM up to 2.5 μm in aerodynamic diameter (PM(2.5)). Baseline data included assessment of the carotid intima-media thickness (CIMT), a measure of subclinical atherosclerosis. We geocoded subjects’ residential areas to assign annual mean concentrations of ambient PM(2.5). Exposure values were assigned from a PM(2.5) surface derived from a geostatistical model. Individually assigned annual mean PM(2.5) concentrations ranged from 5.2 to 26.9 μg/m3 (mean, 20.3). For a cross-sectional exposure contrast of 10 μg/m3 PM(2.5), CIMT increased by 5.9% (95% confidence interval, 1–11%). Adjustment for age reduced the coefficients, but further adjustment for covariates indicated robust estimates in the range of 3.9–4.3% (p-values, 0.05–0.1). Among older subjects (≥60 years of age), women, never smokers, and those reporting lipid-lowering treatment at baseline, the associations of PM(2.5) and CIMT were larger with the strongest associations in women ≥60 years of age (15.7%, 5.7–26.6%). These results represent the first epidemiologic evidence of an association between atherosclerosis and ambient air pollution. Given the leading role of cardiovascular disease as a cause of death and the large populations exposed to ambient PM(2.5), these findings may be important and need further confirmation

A national study of the association between traffic-related air pollution and adverse pregnancy outcomes in Canada, 1999–2008

AbstractNumerous studies have examined the association of air pollution with preterm birth and birth weight outcomes. Traffic-related air pollution has also increasingly been identified as an important contributor to adverse health effects of air pollution. We employed a national nitrogen dioxide (NO2) exposure model to examine the association between NO2 and pregnancy outcomes in Canada between 1999 and 2008. National models for NO2 (and particulate matter of median aerodynamic diameter <2.5µm (PM2.5) as a covariate) were developed using ground-based monitoring data, estimates from remote-sensing, land use variables and, for NO2, deterministic gradients relative to road traffic sources. Generalized estimating equations were used to examine associations with preterm birth, term low birth weight (LBW), small for gestational age (SGA) and term birth weight, adjusting for covariates including infant sex, gestational age, maternal age and marital status, parity, urban/rural place of residence, maternal place of birth, season, year of birth and neighbourhood socioeconomic status and per cent visible minority. Associations were reduced considerably after adjustment for individual covariates and neighbourhood per cent visible minority, but remained significant for SGA (odds ratio 1.04, 95%CI 1.02–1.06 per 20ppb NO2) and term birth weight (16.2g reduction, 95% CI 13.6–18.8g per 20ppb NO2). Associations with NO2 were of greater magnitude in a sensitivity analysis using monthly monitoring data, and among births to mothers born in Canada, and in neighbourhoods with higher incomes and a lower proportion of visible minorities. In two pollutant models, associations with NO2 were less sensitive to adjustment for PM2.5 than vice versa, and there was consistent evidence of a dose-response relationship for NO2 but not PM2.5. In this study of approximately 2.5 million Canadian births between 1999 and 2008, we found significant associations of NO2 with SGA and term birth weight which remained significant after adjustment for PM2.5, suggesting that traffic may be a particularly important source with respect to the role of air pollution as a risk factor for adverse pregnancy outcomes

A Hybrid Approach to Estimating National Scale Spatiotemporal Variability of PM 2.5 in the Contiguous United States

Airborne fine particulate matter exhibits spatiotemporal variability at multiple scales, which presents challenges to estimating exposures for health effects assessment. Here we created an model to predict ambient particulate matter less than 2.5 microns in aerodynamic diameter (PM2.5) across the contiguous United States to be applied to health effects modeling. We developed a hybrid approach combining a land use regression model (LUR) selected with a machine learning method, and Bayesian Maximum Entropy (BME) interpolation of the LUR space-time residuals. The PM2.5 dataset included 104,172 monthly observations at 1,464 monitoring locations with approximately 10% of locations reserved for cross-validation. LUR models were based on remote sensing estimates of PM2.5, land use and traffic indicators. Normalized cross-validated R2 values for LUR were 0.63 and 0.11 with and without remote sensing, respectively, suggesting remote sensing is a strong predictor of ground-level concentrations. In the models including the BME interpolation of the residuals, cross-validated R2 were 0.79 for both configurations; the model without remotely sensed data described more fine-scale variation than the model including remote sensing. Our results suggest that our modeling framework can predict ground-level concentrations of PM2.5 at multiple scales over the contiguous U.S

Multi-pollutant exposure profiles associated with term low birth weight in Los Angeles County

Research indicates that multiple outdoor air pollutants and adverse neighborhood conditions are spatially correlated. Yet health risks associated with concurrent exposure to air pollution mixtures and clustered neighborhood factors remain underexplored. Statistical models to assess the health effects from pollutant mixtures remain limited, due to problems of collinearity between pollutants and area-level covariates, and increases in covariate dimensionality. Here we identify pollutant exposure profiles and neighborhood contextual profiles within Los Angeles (LA) County. We then relate these profiles with term low birth weight (TLBW). We used land use regression to estimate NO2, NO, and PM2.5 concentrations averaged over census block groups to generate pollutant exposure profile clusters and census block group-level contextual profile clusters, using a Bayesian profile regression method. Pollutant profile cluster risk estimation was implemented using a multilevel hierarchical model, adjusting for individual-level covariates, contextual profile cluster random effects, and modeling of spatially structured and unstructured residual error. Our analysis found 13 clusters of pollutant exposure profiles. Correlations between study pollutants varied widely across the 13 pollutant clusters. Pollutant clusters with elevated NO2, NO, and PM2.5 concentrations exhibited increased log odds of TLBW, and those with low PM2.5, NO2, and NO concentrations showed lower log odds of TLBW. The spatial patterning of pollutant cluster effects on TLBW, combined with between-pollutant correlations within pollutant clusters, imply that traffic-related primary pollutants influence pollutant cluster TLBW risks. Furthermore, contextual clusters with the greatest log odds of TLBW had more adverse neighborhood socioeconomic, demographic, and housing conditions. Our data indicate that, while the spatial patterning of high-risk multiple pollutant clusters largely overlaps with adverse contextual neighborhood cluster, both contribute to TLBW while controlling for the other.Health Effects Institute (HEI), an organization jointly funded by the United States Environmental Protection Agency (EPA) (Assistance Award No. R-82811201

Modeling spatial effects of PM₂.₅ on term low birth weight in Los Angeles County

Air pollution epidemiological studies suggest that elevated exposure to fine particulate matter (PM₂.₅) is associated with higher prevalence of term low birth weight (TLBW). Previous studies have generally assumed the exposure–response of PM₂.₅ on TLBW to be the same throughout a large geographical area. Health effects related to PM₂.₅ exposures, however, may not be uniformly distributed spatially, creating a need for studies that explicitly investigate the spatial distribution of the exposure–response relationship between individual-level exposure to PM₂.₅ and TLBW. Here, we examine the overall and spatially varying exposure–response relationship between PM₂.₅ and TLBW throughout urban Los Angeles (LA) County, California. We estimated PM₂.₅ from a combination of land use regression (LUR), aerosol optical depth from remote sensing, and atmospheric modeling techniques. Exposures were assigned to LA County individual pregnancies identified from electronic birth certificates between the years 1995-2006 (N=1,359,284) provided by the California Department of Public Health. We used a single pollutant multivariate logistic regression model, with multilevel spatially structured and unstructured random effects set in a Bayesian framework to estimate global and spatially varying pollutant effects on TLBW at the census tract level. Overall, increased PM₂.₅ level was associated with higher prevalence of TLBW county-wide. The spatial random effects model, however, demonstrated that the exposure–response for PM₂.₅ and TLBW was not uniform across urban LA County. Rather, the magnitude and certainty of the exposure–response estimates for PM₂.₅ on log odds of TLBW were greatest in the urban core of Central and Southern LA County census tracts. These results suggest that the effects may be spatially patterned, and that simply estimating global pollutant effects obscures disparities suggested by spatial patterns of effects. Studies that incorporate spatial multilevel modeling with random coefficients allow us to identify areas where air pollutant effects on adverse birth outcomes may be most severe and policies to further reduce air pollution might be most effectiveKEYWORDS: Multilevel modeling, Term low birth weight, Air pollution, PM2.5, Spatial effects, PM₂.₅This is the publisher’s final pdf. The published article is copyrighted by the author(s) and published by Elsevier. The published article can be found at: http://www.journals.elsevier.com/environmental-research

Comparing the Health Effects of Ambient Particulate Matter Estimated Using Ground-Based versus Remote Sensing Exposure Estimates

BACKGROUND: Remote sensing (RS) is increasingly used for exposure assessment in epidemiological and burden of disease studies, including those investigating whether chronic exposure to ambient fine particulate matter (PM2.5) is associated with mortality. OBJECTIVES: To compare relative risk estimates of mortality from diseases of the circulatory system for PM2.5 modeled from RS with that for PM2.5 modeled using ground-level information. METHODS: We geocoded the baseline residence of 668,629 American Cancer Society Cancer Prevention Study II (CPS-II) cohort participants followed from 1982 to 2004 and assigned PM2.5 levels to all participants using seven different exposure models. Most of the exposure models were averaged for the years 2002-2004, while one RS estimate was for a longer, contemporaneous period. We used Cox proportional hazards regression to estimate relative risks (RR) for the association of PM2.5 with circulatory mortality and ischemic heart disease. RESULTS: Estimates of mortality risk differed among exposure models. The smallest relative risk was observed for the RS estimates that excluded ground-based monitors for circulatory deaths (RR = 1.02 (95% confidence interval (CI): 1.00-1.04 per 10 microg/m3 increment in PM2.5). The largest relative risk was observed for the land use regression model that included traffic information (RR = 1.14, 95% CI: 1.11-1.17 per 10 microg/m3 increment in PM2.5). CONCLUSIONS: We found significant associations between PM2.5 and mortality in every model; however, relative risks estimated from exposure models using ground-based information were generally larger than those estimated with RS alone

Comparing Notes: Recording and Criticism

This chapter charts the ways in which recording has changed the nature of music criticism. It both provides an overview of the history of recording and music criticism, from the advent of Edison’s Phonograph to the present day, and examines the issues arising from this new technology and the consequent transformation of critical thought and practice

Wider Still and Wider: British Music Criticism since the Second World War

This chapter provides the first historical examination of music criticism in Britain since the Second World War. In the process, it also challenges the simplistic prevailing view of this being a period of decline from a golden age in music criticism