Social Susceptibility to Multiple Air Pollutants in Cardiovascular Disease.

introductionCardiovascular disease (CVD) is the leading cause of death in the United States, and substantial research has linked ambient air pollution to elevated rates of CVD etiology and events. Much of this research identified increased effects of air pollution in lower socioeconomic position (SEP) communities, where pollution exposures are also often higher. The complex spatial confounding between air pollution and SEP makes it very challenging, however, to disentangle the impacts of these very different exposure types and to accurately assess their interactions. The specific causal components (i.e., specific social stressors) underlying this SEP-related susceptibility remain unknown, because there are myriad pathways through which poverty and/or lower-SEP conditions may influence pollution susceptibility - including diet, smoking, coexposures in the home and occupational environments, health behaviors, and healthcare access. Growing evidence suggests that a substantial portion of SEP-related susceptibility may be due to chronic psychosocial stress - given the known wide-ranging impacts of chronic stress on immune, endocrine, and metabolic function - and to a higher prevalence of unpredictable chronic stressors in many lower-SEP communities, including violence, job insecurity, and housing instability. As such, elucidating susceptibility to pollution in the etiology of CVD, and in the risk of CVD events, has been identified as a research priority. This interplay among social and environmental conditions may be particularly relevant for CVD, because pollution and chronic stress both impact inflammation, metabolic function, oxidative stress, hypertension, atherosclerosis, and other processes relevant to CVD etiology. Because pollution exposures are often spatially patterned by SEP, disentangling their effects - and quantifying any interplay - is especially challenging. Doing so, however, would help to improve our ability to identify and characterize susceptible populations and to improve our understanding of how community stressors may alter responses to multiple air pollutants. More clearly characterizing susceptible populations will improve our ability to design and target interventions more effectively (and cost-effectively) and may reveal greater benefits of pollution reduction in susceptible communities, strengthening cost-benefit and accountability analyses, ultimately reducing the disproportionate burden of CVD and reducing health disparities.

methodsIn the current study, we aimed to quantify combined effects of multiple pollutants and stressor exposures on CVD events, using a number of unique datasets we have compiled and verified, including the following. 1. Poverty metrics, violent crime rates, a composite socioeconomic deprivation index (SDI), an index of racial and economic segregation, noise disturbance metrics, and three composite spatial factors produced from a factor analysis of 27 community stressors. All indicators have citywide coverage and were verified against individual reports of stress and stressor exposure, in citywide focus groups and surveys. 2. Spatial surfaces for multiple pollutants from the New York City (NYC) Community Air Survey (NYCCAS), which monitored multiple pollutants year-round at 150 sites and used land use regression (LUR) modeling to estimate fine-scale (100-m) intra-urban spatial variance in fine particles (PM

resultsTo first understand the separate and combined associations with CVD for both stressors and pollutants measured at the same spatial and temporal scale of resolution, we used ecological cross-sectional models to examine spatial relationships between multiple chronic pollutant and stressor exposures and age-adjusted community CVD rates. Using census-tract-level annual averages (n = 2,167), we compared associations with CVD rates for multiple pollutant concentrations and social stressors. We found that associations with community CVD rates were consistently stronger for social stressors than for pollutants, in terms of both magnitude and significance. We note, however, that this result may be driven by the relatively greater variation (on a proportional basis) for stressors than for pollutants in NYC. We also tested effect modification of pollutant-CVD associations by each social stressor and found evidence of stronger associations for NO

conclusionsIn ecological models, we found stronger relationships with community CVD rates for social stressors than for pollutant exposures. In case-crossover analyses, higher exposures to NO