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Additonal file 1: Table S1: Supplemental Figure simulation scenario parameters. Figure S1. Results using 10,000 sparrpowR iterations simulating six scenarios with changing incidence and sample size, detailed in Table S1. Each scenario was conducted assuming multivariate normal distributions for cases and controls with standard deviations of 0.83 and 1.67 km, respectively. The green-colored areas are sufficiently powered to detect spatial clusters of cases relative to controls. The blue-colored areas are insufficiently powered to detect spatial clusters of cases relative to controls. The identified concentrated animal feeding operation (CAFO) is signified by the black “X” and the base map is of Fort Dodge, Iowa. The blue lines represent regions with radii of 5 and 10 km from the identified CAFO.

BackgroundAmbient air pollution is a modifiable risk factor for cardiovascular disease, yet uncertainty remains about the size of risks at lower levels of fine particulate matter (PM2.5) exposure which now occur in the USA and elsewhere.MethodsWe investigated the relationship of ambient PM2.5 exposure with cause-specific cardiovascular disease mortality in 565477 men and women, aged 50 to 71 years, from the National Institutes of Health-AARP Diet and Health Study. During 7.5 x 106 person-years of follow up, 41286 cardiovascular disease deaths, including 23328 ischaemic heart disease (IHD) and 5894 stroke deaths, were ascertained using the National Death Index. PM2.5 was estimated using a hybrid land use regression (LUR) geostatistical model. Multivariate Cox regression models were used to estimate relative risks (RRs) and 95% confidence intervals (CI).ResultsEach increase of 10 μg/m3 PM2.5 (overall range, 2.9-28.0 μg/m3) was associated, in fully adjusted models, with a 16% increase in mortality from ischaemic heart disease [hazard ratio (HR) 1.16; 95% CI 1.09-1.22] and a 14% increase in mortality from stroke (HR 1.14; CI 1.02-1.27). Compared with PM2.5 exposure

Additional file 1: Table S1. Cross-sectional Relationship between LAN and odds of obesity at baseline (N = 239,781). Table S2. The association between LAN at baseline and changes in weight between baseline and follow up. Table S3. Prospective association a between baseline LAN and risk of developing obesity at follow-up among non-obese women (N = 75,899) at baseline according to subgroups with different education, race, and neighborhood characteristics. Table S4. Prospective association a between baseline LAN and risk of developing obesity at follow-up among non-obese men (N = 114,305) at baseline according to different education, race, and neighborhood characteristics.

Additional file 1: Supplemental Table 1. State of residence at time of tissue donation. Supplemental Table 2. Mean concentrations and quartile cut-points for PM2.5 total massa, PM2.5 componentsb, and gaseous pollutantsc. Supplemental Table 3. Associations between PM2.5 total massa and terminal duct lobular unit (TDLU) counts restricted to Indiana residents. Supplemental Table 4. Associations between PM2.5 total massa and TDLU span. Supplemental Table 5. Associations between PM2.5 total massa and acini count/TDLU. Supplemental Table 6. Associations between PM2.5 components and gaseous pollutantsa and terminal duct lobular unit (TDLU) counts restricted to Indiana residents. Supplemental Table 7. Associations between PM2.5 components and gaseous pollutantsa and TDLU span. Supplemental Table 8. Associations between PM2.5 components and gaseous pollutantsa and acini count/TDLU. Supplemental Table 9. State of residence at time of tissue donation by PM2.5 component cluster. Supplemental Table 10. Participant characteristics by PM2.5 component cluster. Supplemental Figure 1. Directed acyclic graph for the relationship between air pollution and TDLU measures. Supplemental Figure 2. Spearman correlations between PM2.5 total mass, PM2.5 components, and gaseous pollutants.