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Background: Living in areas with higher levels of surrounding greenness and access to urban green areas have been associated with beneficial health outcomes. Some studies suggested a beneficial influence on mortality, but the evidence is still controversial. Objectives: We used longitudinal data from a large cohort to estimate associations of two measures of residential greenness exposure with cause-specific mortality and stroke incidence. Methods: We studied a population-based cohort of 1,263,721 residents in Rome aged [greater than or equal to]30 y, followed from 2001 to 2013. As greenness exposure, we utilized the leaf area index (LAI), which expresses the tree canopy as the leaf area per unit ground surface area, and the normalized difference vegetation index (NDVI) within 300- and 1,000-m buffers around home addresses. We estimated the association between the two measures of residential greenness and the outcomes using Cox models, after controlling for relevant individual covariates and contextual characteristics, and explored potential mediation by air pollution [fine particulate matter with aerodynamic diameter [less than or equal to]2.5 pm (P[M.sub.2.5]) and N[O.sub.2]] and road traffic noise. Results: We observed 198,704 deaths from nonaccidental causes, 81,269 from cardiovascular diseases [CVDs; 29,654 from ischemic heart disease (IHD)], 18,090 from cerebrovascular diseases, and 29,033 incident cases of stroke. Residential greenness, expressed as interquartile range (IQR) increase in LAI within 300m, was inversely associated with stroke incidence {hazard ratio (HR) 0.977 [95% confidence interval (CI): 0.961, 0.994]} and mortality for nonaccidental [HR 0.988 (95% CI: 0.981, 0.994)], cardiovascular [HR 0.984 (95% CI: 0.974, 0.994)] and cerebrovascular diseases [HR 0.964 (95% CI: 0.943, 0.985)]. Similar results were obtained using NDVI with 300- or 1,000-m buffers. Conclusions: Living in greener areas was associated with better health outcomes in our study, which could be partly due to reduced exposure to environmental hazards. Further research is required to understand the underlying mechanisms. https://doi.org/10.1289/EHP2854, Introduction Urban settings are often characterized by artificial environments and buildings, high levels of stress, traffic, noise, air pollution, and heat, and the opportunities to have contact with nature are [...]

Introduction: Air pollution represents a serious threat to health on a global scale, being responsible for a large portion of the global burden of disease from environmental factors. Current evidence about the association between air pollution exposure and Diabetes Mellitus (DM) is still controversial. We aimed to evaluate the association between area-level ambient air pollution and self-reported DM in a large population sample in Italy. Materials and methods: We extracted information about self-reported and physician diagnosed DM, risk factors and socio-economic status from 12 surveys conducted nationwide between 1999 and 2013. We obtained annual averaged air pollution levels for the years 2003, 2005, 2007 and 2010 from the AMS-MINNI national integrated model, which simulates the dispersion and transformation of pollutants. The original maps, with a resolution of 4 x 4 km2, were normalized and aggregated at the municipality class of each Italian region, in order to match the survey data. We fit logistic regression models with a hierarchical structure to estimate the relationship between PM10, PM2.5, NO2 and O3 four-years mean levels and the risk of being affected by DM. Results: We included 376,157 individuals aged more than 45 years. There were 39,969 cases of DM, with an average regional prevalence of 9.8% and a positive geographical North-to-South gradient, opposite to that of pollutants’ concentrations. For each 10 μg/m3 increase, the resulting ORs were 1.04 (95% CI 1.01–1.07) for PM10, 1.04 (95% CI 1.02–1.07) for PM2.5, 1.03 (95% CI 1.01–1.05) for NO2 and 1.06 (95% CI 1.01–1.11) for O3, after accounting for relevant individual risk factors. The associations were robust to adjustment for other pollutants in two-pollutant models tested (ozone plus each other pollutant). Conclusions: We observed a significant positive association between each examined pollutant and prevalent DM. Risk estimates were consistent with current evidence, and robust to sensitivity analysis. Our study adds evidence about the effects of air pollution on diabetes and suggests a possible role of ozone as an independent factor associated with the development of DM. Such relationship is of great interest for public health and deserves further investigation. [ABSTRACT FROM AUTHOR]