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AbstractObjectiveTo investigate the associations between air pollution and mortality, focusing on associations below current European Union, United States, and World Health Organization standards and guidelines.DesignPooled analysis of eight cohorts.SettingMulticentre project Effects of Low-Level Air Pollution: A Study in Europe (ELAPSE) in six European countries.Participants325 367 adults from the general population recruited mostly in the 1990s or 2000s with detailed lifestyle data. Stratified Cox proportional hazard models were used to analyse the associations between air pollution and mortality. Western Europe-wide land use regression models were used to characterise residential air pollution concentrations of ambient fine particulate matter (PM2.5), nitrogen dioxide, ozone, and black carbon.Main outcome measuresDeaths due to natural causes and cause specific mortality.ResultsOf 325 367 adults followed-up for an average of 19.5 years, 47 131 deaths were observed. Higher exposure to PM2.5, nitrogen dioxide, and black carbon was associated with significantly increased risk of almost all outcomes. An increase of 5 µg/m3 in PM2.5 was associated with 13% (95% confidence interval 10.6% to 15.5%) increase in natural deaths; the corresponding figure for a 10 µg/m3 increase in nitrogen dioxide was 8.6% (7% to 10.2%). Associations with PM2.5, nitrogen dioxide, and black carbon remained significant at low concentrations. For participants with exposures below the US standard of 12 µg/m3 an increase of 5 µg/m3 in PM2.5 was associated with 29.6% (14% to 47.4%) increase in natural deaths.ConclusionsOur study contributes to the evidence that outdoor air pollution is associated with mortality even at low pollution levels below the current European and North American standards and WHO guideline values. These findings are therefore an important contribution to the debate about revision of air quality limits, guidelines, and standards, and future assessments by the Global Burden of Disease.

Several studies have evaluated whether the distribution of natural environments differs between marginalized and privileged neighborhoods. However, most studies restricted their analyses to a single or handful of cities and used different natural environment measures. We evaluated whether natural environments are inequitably distributed based on socioeconomic status (SES) and race/ethnicity in the contiguous United States. We obtained SES and race/ethnicity data (2015-2019) for all U.S. Census tracts. For each tract, we calculated the Normalized Different Vegetation Index (NDVI) for 2020, NatureScore (a proprietary measure of the quantity and quality of natural elements) for 2019, park cover for 2020, and blue space for 1984-2018. We used generalized additive models with adjustment for potential confounders and spatial autocorrelation to evaluate associations of SES and race/ethnicity with NDVI, NatureScore, park cover, and odds of containing blue space in all tracts ( ) and in urban tracts ( ). To compare effect estimates, we standardized NDVI, NatureScore, and park cover so that beta coefficients presented a percentage increase or decrease of the standard deviation (SD). Tracts with higher SES had higher NDVI, NatureScore, park cover, and odds of containing blue space. For example, urban tracts in the highest median household income quintile had higher NDVI [44.8% of the SD (95% CI: 42.8, 46.8)] and park cover [16.2% of the SD (95% CI: 13.5, 19.0)] compared with urban tracts in the lowest median household income quintile. Across all tracts, a lower percentage of non-Hispanic White individuals and a higher percentage of Hispanic individuals were associated with lower NDVI and NatureScore. In urban tracts, we observed weak positive associations between percentage non-Hispanic Black and NDVI, NatureScore, and park cover; we did not find any clear associations for percentage Hispanics. Multiple facets of the natural environment are inequitably distributed in the contiguous United States. https://doi.org/10.1289/EHP11164.

Background Everyday people are exposed to multiple environmental factors, such as surrounding green, air pollution and traffic noise. These exposures are generally spatially correlated. Hence, when estimating associations of surrounding green, air pollution or traffic noise with health outcomes, the other exposures should be taken into account. The aim of this study was to evaluate associations of long-term residential exposure to surrounding green, air pollution and traffic noise with mortality. Methods We followed approximately 10.5 million adults (aged ≥ 30 years) living in the Netherlands from 1 January 2013 until 31 December 2018. We used Cox proportional hazard models to evaluate associations of residential surrounding green (including the average Normalized Difference Vegetation Index (NDVI) in buffers of 300 and 1000 m), annual average ambient air pollutant concentrations [including particulate matter (PM 2.5 ), nitrogen dioxide (NO 2 )] and traffic noise with non-accidental and cause-specific mortality, adjusting for potential confounders. Results In single-exposure models, surrounding green was negatively associated with all mortality outcomes, while air pollution was positively associated with all outcomes. In two-exposure models, associations of surrounding green and air pollution attenuated but remained. For respiratory mortality, in a two-exposure model with NO 2 and NDVI 300 m, the HR of NO 2 was 1.040 (95%CI: 1.022, 1.059) per IQR increase (8.3 µg/m 3 ) and the HR of NDVI 300 m was 0.964 (95%CI: 0.952, 0.976) per IQR increase (0.14). Road-traffic noise was positively associated with lung cancer mortality only, also after adjustment for air pollution or surrounding green. Conclusions Lower surrounding green and higher air pollution were associated with a higher risk of non-accidental and cause-specific mortality. Studies including only one of these correlated exposures may overestimate the associations with mortality of that exposure.

Most spatial epidemiological studies of nature-health relationships use generalized greenspace measures. For instance, coarse-resolution spatial data containing normalized difference vegetative index (NDVI) values are prominent despite criticisms, such as the inability to restrain exposure estimates to public and private land. Non-threatening natural landscapes can improve health by building capacities for health-promoting behaviors. Recreational and accessible parks may best activate such behaviors. We curated the Parks and Protected Areas Database of the U.S. (PAD-US) to identify parks that are accessible for outdoor recreation. Our title adds “AR” to “PAD-US” where A = Accessible and R = Recreational. We validated the PAD-US-AR by comparisons with greenspace datasets and sociodemographics, which demonstrated its uniqueness from other commonly employed metrics of nature exposure. The PAD-US-AR presents reliable estimates of parks in the contiguous U.S. that are accessible for outdoor recreation. It has strong associations with home prices, shares of female residents, and shares of older residents. This dataset can accompany other nature exposure metrics in environmental epidemiology and allied research fields. Measurement(s) park Technology Type(s) Geographic Information System Sample Characteristic - Environment County • Tract Sample Characteristic - Location United States

Background Long-term exposure to air pollution and noise is detrimental to health; but studies that evaluated both remain limited. This study explores associations with natural and cause-specific mortality for a range of air pollutants and transportation noise. Methods Over 4 million adults in Switzerland were followed from 2000 to 2014. Exposure to PM 2.5 , PM 2.5 components (Cu, Fe, S and Zn), NO 2 , black carbon (BC) and ozone (O 3 ) from European models, and transportation noise from source-specific Swiss models, were assigned at baseline home addresses. Cox proportional hazards models, adjusted for individual and area-level covariates, were used to evaluate associations with each exposure and death from natural, cardiovascular (CVD) or non-malignant respiratory disease. Analyses included single and two exposure models, and subset analysis to study lower exposure ranges. Results During follow-up, 661,534 individuals died of natural causes (36.6% CVD, 6.6% respiratory). All exposures including the PM 2.5 components were associated with natural mortality, with hazard ratios (95% confidence intervals) of 1.026 (1.015, 1.038) per 5 µg/m 3 PM 2.5 , 1.050 (1.041, 1.059) per 10 µg/m 3 NO 2 , 1.057 (1.048, 1.067) per 0.5 × 10 –5 /m BC and 1.045 (1.040, 1.049) per 10 dB Lden total transportation noise. NO 2 , BC, Cu, Fe and noise were consistently associated with CVD and respiratory mortality, whereas PM 2.5 was only associated with CVD mortality. Natural mortality associations persisted < 20 µg/m 3 for PM 2.5 and NO 2 , < 1.5 10 –5 /m BC and < 53 dB Lden total transportation noise. The O 3 association was inverse for all outcomes. Including noise attenuated all outcome associations, though many remained significant. Across outcomes, noise was robust to adjustment to air pollutants (e.g. natural mortality 1.037 (1.033, 1.042) per 10 dB Lden total transportation noise, after including BC). Conclusion Long-term exposure to air pollution and transportation noise in Switzerland contribute to premature mortality. Considering co-exposures revealed the importance of local traffic-related pollutants such as NO 2 , BC and transportation noise.

[...]dense and complex road networks and building configurations can affect noise levels because noise waves can be reflected and refracted by buildings and noise barriers. [...]after adjustment for socioeconomic status (SES), green space, and ambient fine particulate matter PM2.5 PM 2.5 , associations of 10-y mean road traffic noise at the most exposed façade attenuated from hazard ratio (HR)=1.07 hazard ratio(HR ) = 1.07 [95% confidence interval (CI): 1.07, 1.08] to 1.03 (95% CI: 1.03, 1.04) per 10-dB increase. [...]the well-conducted study by Thacher et al.

Surrounding green, air pollution, and noise have been associated with cardiometabolic diseases, but most studies have assessed only one of these correlated exposures. We aimed to evaluate associations of combined exposures to green, air pollution, and road traffic noise with cardiometabolic diseases. In this cross-sectional study, we studied associations between self-reported physician-diagnosed diabetes, hypertension, heart attack, and stroke from a Dutch national health survey of 387,195 adults and residential surrounding green, annual average air pollutant concentrations [including particulate matter with aerodynamic diameter [Formula: see text] ([Formula: see text]), PM with aerodynamic diameter [Formula: see text] ([Formula: see text]), nitrogen dioxide ([Formula: see text]), and oxidative potential (OP) with the dithiothreitol (DTT) assay ([Formula: see text])] and road traffic noise. Logistic regression models were used to analyze confounding and interaction of surrounding green, air pollution, and noise exposure. In single-exposure models, surrounding green was inversely associated with diabetes, while air pollutants ([Formula: see text], [Formula: see text]) and road traffic noise were positively associated with diabetes. In two-exposure analyses, associations with green and air pollution were attenuated but remained. The association between road traffic noise and diabetes was reduced to unity when adjusted for surrounding green or air pollution. Air pollution and surrounding green, but not road traffic noise, were associated with hypertension in single-exposure models. The weak inverse association of surrounding green with hypertension attenuated and lost significance when adjusted for air pollution. Only [Formula: see text] was associated with stroke and heart attack. Studies including only one of the correlated exposures surrounding green, air pollution, and road traffic noise may overestimate the association of diabetes and hypertension attributed to the studied exposure. https://doi.org/10.1289/EHP3857.

Climate change is one of the greatest health threats facing humanity. Multiple studies have documented the impact of short-term temperature exposure on human health. However, long-term temperature exposures are far less studied. We examined whether exposures to higher or lower summer and winter average temperatures compared to long-term average temperatures were associated with cardiovascular disease (CVD) incidence in three US-based cohorts. We followed 276,618 participants from the Nurses' Health Study (NHS) (1991-2018), the Nurses' Health Study II (NHSII) (1994-2017), and the Health Professionals' Follow-Up Study (1991-2015). We used data (1986-2018) from PRISM Spatial Climate Datasets ( spatial resolution) to calculate differences between the summer (June-August) and winter (December-February) average temperatures and the previous 5-year summer and winter average temperatures at residential addresses of each participant. CVD incidence was defined as first nonfatal or fatal myocardial infarction (MI) or nonfatal or fatal stroke. Cox proportional hazard models were used to examine associations with between average temperatures and CVD incidence. Hazard ratios (HRs) and 95% confidence intervals (95% CI) were pooled using random effect meta-analysis. We also examined associations in the populations and years of age. After pooling HRs, we found no association of summer average temperatures higher than the previous 5-year average temperature, with CVD incidence. A winter average temperature lower than the previous 5-year average was associated with CVD incidence ( per 2.7°C increase; 95% CI: 0.89, 1.01). Among persons years of age, we observed increased CVD risks with higher summer average temperatures (pooled per 1.3°C increase; 95% CI: 1.00, 1.07) and lower winter average temperatures (pooled per 2.7°C increase; 95% CI: 0.87, 0.95) compared to the previous 5-year average temperature. Exposure to a winter average temperature lower than the previous 5-year average was suggestively associated with an increased CVD risk. Exposure to a summer average temperature higher than the previous 5-year average was associated with CVD incidence in the population years of age but not in the full population. https://doi.org/10.1289/EHP14677.

Inconsistent associations between long-term exposure to particles with an aerodynamic diameter [fine particulate matter ( )] components and mortality have been reported, partly related to challenges in exposure assessment. We investigated the associations between long-term exposure to elemental components and mortality in a large pooled European cohort; to compare health effects of components estimated with two exposure modeling approaches, namely, supervised linear regression (SLR) and random forest (RF) algorithms. We pooled data from eight European cohorts with 323,782 participants, average age 49 y at baseline (1985-2005). Residential exposure to 2010 annual average concentration of eight components [copper (Cu), iron (Fe), potassium (K), nickel (Ni), sulfur (S), silicon (Si), vanadium (V), and zinc (Zn)] was estimated with Europe-wide SLR and RF models at a scale. We applied Cox proportional hazards models to investigate the associations between components and natural and cause-specific mortality. In addition, two-pollutant analyses were conducted by adjusting each component for mass and nitrogen dioxide ( ) separately. We observed 46,640 natural-cause deaths with 6,317,235 person-years and an average follow-up of 19.5 y. All SLR-modeled components were statistically significantly associated with natural-cause mortality in single-pollutant models with hazard ratios (HRs) from 1.05 to 1.27. Similar HRs were observed for RF-modeled Cu, Fe, K, S, V, and Zn with wider confidence intervals (CIs). HRs for SLR-modeled Ni, S, Si, V, and Zn remained above unity and (almost) significant after adjustment for both and . HRs only remained (almost) significant for RF-modeled K and V in two-pollutant models. The HRs for V were 1.03 (95% CI: 1.02, 1.05) and 1.06 (95% CI: 1.02, 1.10) for SLR- and RF-modeled exposures, respectively, per , adjusting for mass. Associations with cause-specific mortality were less consistent in two-pollutant models. Long-term exposure to V in was most consistently associated with increased mortality. Associations for the other components were weaker for exposure modeled with RF than SLR in two-pollutant models. https://doi.org/10.1289/EHP8368.

Studies across the globe generally reported increased mortality risks associated with particulate matter with aerodynamic diameter ≤2.5μm (PM2.5) exposure with large heterogeneity in the magnitude of reported associations and the shape of concentration-response functions (CRFs). We aimed to evaluate the impact of key study design factors (including confounders, applied exposure model, population age, and outcome definition) on PM2.5 effect estimates by harmonizing analyses on three previously published large studies in Canada [Mortality-Air Pollution Associations in Low Exposure Environments (MAPLE), 1991-2016], the United States (Medicare, 2000-2016), and Europe [Effects of Low-Level Air Pollution: A Study in Europe (ELAPSE), 2000-2016] as much as possible.BACKGROUNDStudies across the globe generally reported increased mortality risks associated with particulate matter with aerodynamic diameter ≤2.5μm (PM2.5) exposure with large heterogeneity in the magnitude of reported associations and the shape of concentration-response functions (CRFs). We aimed to evaluate the impact of key study design factors (including confounders, applied exposure model, population age, and outcome definition) on PM2.5 effect estimates by harmonizing analyses on three previously published large studies in Canada [Mortality-Air Pollution Associations in Low Exposure Environments (MAPLE), 1991-2016], the United States (Medicare, 2000-2016), and Europe [Effects of Low-Level Air Pollution: A Study in Europe (ELAPSE), 2000-2016] as much as possible.We harmonized the study populations to individuals 65+ years of age, applied the same satellite-derived PM2.5 exposure estimates, and selected the same sets of potential confounders and the same outcome. We evaluated whether differences in previously published effect estimates across cohorts were reduced after harmonization among these factors. Additional analyses were conducted to assess the influence of key design features on estimated risks, including adjusted covariates and exposure assessment method. A combined CRF was assessed with meta-analysis based on the extended shape-constrained health impact function (eSCHIF).METHODSWe harmonized the study populations to individuals 65+ years of age, applied the same satellite-derived PM2.5 exposure estimates, and selected the same sets of potential confounders and the same outcome. We evaluated whether differences in previously published effect estimates across cohorts were reduced after harmonization among these factors. Additional analyses were conducted to assess the influence of key design features on estimated risks, including adjusted covariates and exposure assessment method. A combined CRF was assessed with meta-analysis based on the extended shape-constrained health impact function (eSCHIF).More than 81 million participants were included, contributing 692 million person-years of follow-up. Hazard ratios and 95% confidence intervals (CIs) for all-cause mortality associated with a 5-μg/m3 increase in PM2.5 were 1.039 (1.032, 1.046) in MAPLE, 1.025 (1.021, 1.029) in Medicare, and 1.041 (1.014, 1.069) in ELAPSE. Applying a harmonized analytical approach marginally reduced difference in the observed associations across the three studies. Magnitude of the association was affected by the adjusted covariates, exposure assessment methodology, age of the population, and marginally by outcome definition. Shape of the CRFs differed across cohorts but generally showed associations down to the lowest observed PM2.5 levels. A common CRF suggested a monotonically increased risk down to the lowest exposure level. https://doi.org/10.1289/EHP12141.RESULTSMore than 81 million participants were included, contributing 692 million person-years of follow-up. Hazard ratios and 95% confidence intervals (CIs) for all-cause mortality associated with a 5-μg/m3 increase in PM2.5 were 1.039 (1.032, 1.046) in MAPLE, 1.025 (1.021, 1.029) in Medicare, and 1.041 (1.014, 1.069) in ELAPSE. Applying a harmonized analytical approach marginally reduced difference in the observed associations across the three studies. Magnitude of the association was affected by the adjusted covariates, exposure assessment methodology, age of the population, and marginally by outcome definition. Shape of the CRFs differed across cohorts but generally showed associations down to the lowest observed PM2.5 levels. A common CRF suggested a monotonically increased risk down to the lowest exposure level. https://doi.org/10.1289/EHP12141.