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The working platforms for heavy construction machines demand a reliable, safe and economical ultimate limit state design procedure which enables a complete verification of safety against different failure modes. Despite considerable advances in the analysis of geogrid-reinforced working platforms through the contribution of several research studies, their proof of the stability against some crucial failure modes is still neglected in the current engineering practice. In fact, there is no universal method for the design procedure and the application of current methods and models leads to dissimilar outcomes. In this study, a comprehensive review and analysis of the current knowledge and models is performed for design of working platforms subject to the high localized forces. Accordingly, a comparative analysis is conducted to evaluate the current design models and identify the weaknesses and strengths of each prediction model.

Background: Little is known about the impact of environmental exposures on mortality risk after a myocardial infarction (MI)., Objective: The goal of this study was to evaluate associations of long-term temperature, air pollution and greenness exposures with mortality among survivors of an MI., Methods: We used data from the US-based Nurses' Health Study to construct an open cohort of survivors of a nonfatal MI 1990-2017. Participants entered the cohort when they had a nonfatal MI, and were followed until death, loss to follow-up, end of follow-up, or they reached 80 years old, whichever came earliest. We assessed residential 12-month moving average fine particulate matter (PM 2.5 ) and nitrogen dioxide (NO 2 ), satellite-based annual average greenness (in a circular 1230 m buffer), summer average temperature and winter average temperature. We used Cox proportional hazard models adjusted for potential confounders to assess hazard ratios (HR and 95% confidence intervals). We also assessed potential effect modification., Results: Among 2262 survivors of a nonfatal MI, we observed 892 deaths during 19,216 person years of follow-up. In single-exposure models, we observed a HR (95%CI) of 1.20 (1.04, 1.37) per 10 ppb NO 2 increase and suggestive positive associations were observed for PM 2.5 , lower greenness, warmer summer average temperature and colder winter average temperature. In multi-exposure models, associations of summer and winter average temperature remained stable, while associations of NO 2 , PM 2.5 and greenness attenuated. The strength of some associations was modified by other exposures. For example, associations of greenness (HR = 0.88 (0.78, 0.98) per 0.1) were more pronounced for participants in areas with a lower winter average temperature., Conclusion: We observed associations of air pollution, greenness and temperature with mortality among MI survivors. Some associations were confounded or modified by other exposures, indicating that it is important to explore the combined impact of environmental exposures., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Introduction: Protective associations of greenspace with Parkinson's disease (PD) have been observed in some studies. Visual exposure to greenspace seems to be important for some of the proposed pathways underlying these associations. However, most studies use overhead-view measures (e.g., satellite imagery, land-classification data) that do not capture street-view greenspace and cannot distinguish between specific greenspace types. We aimed to evaluate associations of street-view greenspace measures with hospitalizations with a PD diagnosis code (PD-involved hospitalization)., Methods: We created an open cohort of about 45.6 million Medicare fee-for-service beneficiaries aged 65 + years living in core based statistical areas (i.e. non-rural areas) in the contiguous US (2007-2016). We obtained 350 million Google Street View images across the US and applied deep learning algorithms to identify percentages of specific greenspace features in each image, including trees, grass, and other green features (i.e., plants, flowers, fields). We assessed yearly average street-view greenspace features for each ZIP code. A Cox-equivalent re-parameterized Poisson model adjusted for potential confounders (i.e. age, race/ethnicity, socioeconomic status) was used to evaluate associations with first PD-involved hospitalization., Results: There were 506,899 first PD-involved hospitalizations over 254,917,192 person-years of follow-up. We found a hazard ratio (95% confidence interval) of 0.96 (0.95, 0.96) per interquartile range (IQR) increase for trees and a HR of 0.97 (0.96, 0.97) per IQR increase for other green features. In contrast, we found a HR of 1.06 (1.04, 1.07) per IQR increase for grass. Associations of trees were generally stronger for low-income (i.e. Medicaid eligible) individuals, Black individuals, and in areas with a lower median household income and a higher population density., Conclusion: Increasing exposure to trees and other green features may reduce PD-involved hospitalizations, while increasing exposure to grass may increase hospitalizations. The protective associations may be stronger for marginalized individuals and individuals living in densely populated areas., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: PM 2.5 has been positively associated with cardiovascular disease (CVD) incidence. Most evidence has come from cohorts and administrative databases. Cohorts typically have extensive information on potential confounders and residential-level exposures. Administrative databases are usually more representative but typically lack information on potential confounders and often only have exposures at coarser geographies (e.g., ZIP code). The weaknesses in both types of studies have been criticized for potentially jeopardizing the validity of their findings for regulatory purposes., Methods: We followed 101,870 participants from the US-based Nurses' Health Study (2000-2016) and linked residential-level PM 2.5 and individual-level confounders, and ZIP code-level PM 2.5 and confounders. We used time-varying Cox proportional hazards models to examine associations with CVD incidence. We specified basic models (adjusted for individual-level age, race and calendar year), individual-level confounder models, and ZIP code-level confounder models., Results: Residential- and ZIP code-level PM 2.5 were strongly correlated (Pearson r = 0.88). For residential-level PM 2.5 , the hazard ratio (HR, 95 % confidence interval) per 5 μg/m 3 increase was 1.06 (1.01, 1.11) in the basic and 1.04 (0.99, 1.10) in the individual-level confounder model. For ZIP code-level PM 2.5 , the HR per 5 μg/m 3 was 1.04 (0.99, 1.08) in the basic and 1.02 (0.97, 1.08) in the ZIP code-level confounder model., Conclusion: We observed suggestive positive, but not statistically significant, associations between long-term PM 2.5 and CVD incidence, regardless of the exposure or confounding model. Although differences were small, associations from models with individual-level confounders and residential-level PM 2.5 were slightly stronger than associations from models with ZIP code-level confounders and PM 2.5 ., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Jochem Klompmaker reports financial support was provided by National Institute of Environmental Health Sciences. Jaime E Hart reports financial support was provided by National Institute of Environmental Health Sciences. Francesca Dominici reports financial support was provided by National Institute of Environmental Health Sciences. Peter James reports financial support was provided by National Institute of Environmental Health Sciences. Charlie Roscoe reports financial support was provided by National Institute of Environmental Health Sciences. Joel Schwartz reports financial support was provided by National Institute of Environmental Health Sciences. Jeff D Yanosky reports financial support was provided by National Institute of Environmental Health Sciences. Antonella Zanobetti reports financial support was provided by National Institute of Environmental Health Sciences. Francine Laden reports financial support was provided by National Institute of Environmental Health Sciences. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: Few studies have investigated the relationship between the food and physical activity environment and odds of gestational diabetes mellitus (GDM). This study quantifies the association between densities of several types of food establishments and fitness centers with the odds of having GDM., Methods: The density of supermarkets, fast-food restaurants, full-service restaurants, convenience stores and fitness centers at 500, 1000 and 1500 m (m) buffers was counted at residential addresses of 68,779 pregnant individuals from Eastern Massachusetts during 2000-2016. The 'healthy food index' assessed the relative availability of healthy (supermarkets) vs unhealthy (fast-food restaurants, convenience stores) food retailers. Multivariable logistic regression quantified the cross-sectional association between exposure variables and the odds of having GDM, adjusting for individual and area-level characteristics. Effect modification by area-level socioeconomic status (SES) was assessed., Findings: In fully adjusted models, pregnant individuals living in the highest density tertile of fast-food restaurants had higher GDM odds compared to those living in the lowest density tertile (500 m: odds ratio (OR):1.17 95% CI: [1.04, 1.31]; 1000 m: 1.33 95% CI: [1.15, 1.53]); 1500 m: 1.18 95% CI: [1.01, 1.38]). Greater residential density of supermarkets was associated with lower odds of GDM (1000 m: 0.86 95% CI: [0.74, 0.99]; 1500 m: 0.86 95% CI: [0.72, 1.01]). Similarly, living in the highest fitness center density tertile was associated with decreased GDM odds (500 m:0.87 95% CI: [0.76, 0.99]; 1500 m: 0.89 95% CI: [0.79, 1.01]). There was no evidence of effect modification by SES and no association found between the healthy food index and GDM odds., Interpretation: In Eastern Massachusetts, living near a greater density of fast-food establishments was associated with higher GDM odds. Greater residential access to supermarkets and fitness centers was associated with lower the odds of having GDM., Funding: NIH., Competing Interests: Jean-Philippe Drouin-Chartier received consulting fees from Dairy Farmers of Canada (unrelated to this manuscript)., (© 2024 Published by Elsevier Ltd.)

Background: Studies across the globe generally reported increased mortality risks associated with particulate matter with aerodynamic diameter ≤ 2.5 μ m ( PM 2.5 ) 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 PM 2.5 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., Methods: We harmonized the study populations to individuals 65 + years of age, applied the same satellite-derived PM 2.5 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)., Results: 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 - μ g / m 3 increase in PM 2.5 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 PM 2.5 levels. A common CRF suggested a monotonically increased risk down to the lowest exposure level. https://doi.org/10.1289/EHP12141.

Introduction: Most climate-health studies focus on temperature; however, less is known about health effects of exposure to atmospheric moisture. Humid air limits sweat evaporation from the body and can in turn exert strain on the cardiovascular system. We evaluated associations of long-term exposure to summer specific humidity with cardiovascular disease (CVD), coronary heart disease (CHD) and cerebrovascular disease (CBV) hospitalization., Methods: We built an open cohort consisting of ∼63 million fee-for-service Medicare beneficiaries, aged ≥65, living in the contiguous US (2000-2016). We assessed zip code level summer average specific humidity and specific humidity variability, based on daily estimates from the Gridded Surface Meteorological dataset (∼4km spatial resolution). To estimate associations of summer specific humidity with first CVD, CHD, and CBV hospitalization, we used Cox-equivalent Poisson models adjusted for individual and area-level socioeconomic status indicators, temperature, and winter specific humidity., Results: Higher summer average specific humidity was associated with an increased risk of CVD, CHD, and CBV hospitalization. We found hazard ratios (HRs) of 1.07 (95%CI: 1.07, 1.08) for CVD hospitalization, 1.08 (95%CI: 1.08, 1.09) for CHD hospitalization, and 1.07 (95%CI: 1.07, 1.08) for CBV hospitalization per IQR increase (4.0 g of water vapor/kg of dry air) in summer average specific humidity. Associations of summer average specific humidity were strongest for beneficiaries eligible for Medicaid and for beneficiaries with an unknown or other race. Higher summer specific humidity variability was also associated with increased risk of CVD, CHD, and CBV hospitalization. Associations were not affected by adjustment for temperature and regions of the US, as well as exclusion of potentially prevalent cases., Conclusion: Long-term exposure to higher summer average specific humidity and specific humidity variability were positively associated with CVD hospitalization. As global warming could increase humidity levels, our findings are important to assess potential health impacts of climate change., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Jochem O Klompmaker reports financial support was provided by National Institute of Environmental Health Sciences. Francine Laden reports financial support was provided by National Institute of Environmental Health Sciences. Peter James reports financial support was provided by National Heart Lung and Blood Institute. Peter James reports financial support was provided by National Institute of Environmental Health Sciences. M Benjamin Sabath reports financial support was provided by National Institute of Environmental Health Sciences. Xiao Wu reports financial support was provided by National Institute of Environmental Health Sciences. Francesca Dominici reports financial support was provided by National Institute of Environmental Health Sciences. Antonella Zanobetti reports financial support was provided by National Institute on Aging. Antonella Zanobetti reports financial support was provided by National Institute of Environmental Health Sciences. Jaime E Hart reports financial support was provided by National Institute of Environmental Health Sciences., (Copyright © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: Fine particulate matter (PM 2.5 ) is a well-recognized risk factor for premature death. However, evidence on which PM 2.5 components are most relevant is unclear., Methods: We evaluated the associations between mortality and long-term exposure to eight PM 2.5 elemental components [copper (Cu), iron (Fe), zinc (Zn), sulfur (S), nickel (Ni), vanadium (V), silicon (Si), and potassium (K)]. Studied outcomes included death from diabetes, chronic kidney disease (CKD), dementia, and psychiatric disorders as well as all-natural causes, cardiovascular disease (CVD), respiratory diseases (RD), and lung cancer. We followed all residents in Denmark (aged ≥30 years) from January 1, 2000 to December 31, 2017. We used European-wide land-use regression models at a 100 × 100 m scale to estimate the residential annual mean levels of exposure to PM 2.5 components. The models were developed with supervised linear regression (SLR) and random forest (RF). The associations were evaluated by Cox proportional hazard models adjusting for individual- and area-level socioeconomic factors and total PM 2.5 mass., Results: Of 3,081,244 individuals, we observed 803,373 death from natural causes during follow-up. We found significant positive associations between all-natural mortality with Si and K from both exposure modeling approaches (hazard ratios; 95% confidence intervals per interquartile range increase): SLR-Si (1.04; 1.03-1.05), RF-Si (1.01; 1.00-1.02), SLR-K (1.03; 1.02-1.04), and RF-K (1.06; 1.05-1.07). Strong associations of K and Si were detected with most causes of mortality except CKD and K, and diabetes and Si (the strongest associations for psychiatric disorders mortality). In addition, Fe was relevant for mortality from RD, lung cancer, CKD, and psychiatric disorders; Zn with mortality from CKD, RD, and lung cancer, and; Ni and V with lung cancer mortality., Conclusions: We present novel results of the relevance of different PM 2.5 components for different causes of death, with K and Si seeming to be most consistently associated with mortality in Denmark., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier Inc.)

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., (© 2023. The Author(s).)

Green spaces may be protective against COVID-19 incidence. They may provide outdoor, ventilated, settings for physical and social activities and therefore decrease transmission risk. We examined the association between neighborhood greenness and COVID-19-like illness incidence using individual-level data., Methods: The study population includes participants enrolled in the COVID Symptom Study smartphone application in the United Kingdom and the United States (March-November 2020). All participants were encouraged to report their current health condition and suspected risk factors for COVID-19. We used a validated symptom-based classifier that predicts COVID-19-like illness. We estimated the Normalized Difference Vegetation Index (NDVI), for each participant's reported neighborhood of residence for each month, using images from Landsat 8 (30 m 2 ). We used time-varying Cox proportional hazards models stratified by age, country, and calendar month at study entry and adjusted for the individual- and neighborhood-level risk factors., Results: We observed 143,340 cases of predicted COVID-19-like illness among 2,794,029 participants. Neighborhood NDVI was associated with a decreased risk of predicted COVID-19-like illness incidence in the fully adjusted model (hazard ratio = 0.965, 95% confidence interval = 0.960, 0.970, per 0.1 NDVI increase ). Stratified analyses showed protective associations among U.K. participants but not among U.S. participants. Associations were slightly stronger for White individuals, for individuals living in rural neighborhoods, and for individuals living in high-income neighborhoods compared to individuals living in low-income neighborhoods., Conclusions: Higher levels of greenness may reduce the risk of predicted COVID-19-like illness incidence, but these associations were not observed in all populations., Competing Interests: The authors declare that they have no conflicts of interest with regard to the content of this report., (Copyright © 2023 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of The Environmental Epidemiology. All rights reserved.)

Background: Short-term exposure to high or low temperatures is associated with increased mortality and morbidity. Less is known about effects of long-term exposure to high or low temperatures. Prolonged exposure to high or low temperatures might contribute to pathophysiological mechanisms, thereby influencing the development of diseases. Our aim was to evaluate associations of long-term temperature exposure with cardiovascular disease (CVD) hospitalizations., Methods: We constructed an open cohort consisting of all fee-for-service Medicare beneficiaries, aged ≥65, living in the contiguous US from 2000 through 2016 (∼61.6 million individuals). We used data from the 4 km Gridded Surface Meteorological dataset to assess the summer (June-August) and winter (December-February) average daily maximum temperature for each year for each zip code. Cox-equivalent Poisson models were used to estimate associations with first CVD hospitalization, after adjustment for potential confounders. We performed stratified analyses to assess potential effect modification by sex, age, race, Medicaid eligibility and relative humidity., Results: Higher summer average and lower winter average temperatures were associated with an increased risk of CVD hospitalization. We found a HR of 1.068 (95% CI: 1.063, 1.074) per IQR increase (5.2 °C) for summer average temperature and a HR of 1.022 (95% CI: 1.017, 1.028) per IQR decrease (11.7 °C) for winter average temperature. Positive associations of higher summer average temperatures were strongest for individuals aged <75 years, Medicaid eligible, and White individuals. Positive associations of lower winter average temperatures were strongest for individuals aged <75 years and Black individuals, and individuals living in low relative humidity areas., Conclusions: Living in areas with high summer average temperatures or low winter average temperatures could increase the risk of CVD hospitalizations. The magnitude of the associations of summer and winter average temperatures differs by demographics and relative humidity levels., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Francine Laden reports financial support was provided by National Institute of Environmental Health Sciences. Francesca Dominici reports financial support was provided by National Institute of Environmental Health Sciences. Antonella Zanobetti reports financial support was provided by National Institute of Environmental Health Sciences. Peter James reports financial support was provided by National Heart Lung and Blood Institute. Antonella Zanobetti reports financial support was provided by National Institute on Aging. Jaime Hart reports financial support was provided by National Institute of Environmental Health Sciences. Joel Schwartz reports financial support was provided by National Institute of Environmental Health Sciences, (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: 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., Objectives: We evaluated whether natural environments are inequitably distributed based on socioeconomic status (SES) and race/ethnicity in the contiguous United States., Methods: 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 ( n = 71,532 ) and in urban tracts ( n = 45,338 ). 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)., Results: 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., Discussion: Multiple facets of the natural environment are inequitably distributed in the contiguous United States. https://doi.org/10.1289/EHP11164.

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., (© 2022. The Author(s).)

Importance: Exposure to natural environments has been associated with health outcomes related to neurological diseases. However, the few studies that have examined associations of natural environments with neurological diseases report mixed findings., Objective: To evaluate associations of natural environments with hospital admissions for Alzheimer disease and related dementias (ADRD) and Parkinson disease (PD) among older adults in the US., Design, Setting, and Participants: This open cohort study included fee-for-service Medicare beneficiaries aged 65 years or older who lived in the contiguous US from January 1, 2000, to December 31, 2016. Beneficiaries entered the cohort on January 1, 2000, or January 1 of the year after enrollment. Data from US Medicare enrollment and Medicare Provider Analysis and Review files, which contain information about individual-level covariates and all hospital admissions for Medicare fee-for-service beneficiaries, were analyzed between January 2021 and September 2022., Exposures: Differences in IQRs for zip code-level greenness (normalized difference vegetation index [NDVI]), percentage park cover, and percentage blue space cover (surface water; ≥1.0% vs <1.0%)., Main Outcomes and Measures: The main outcome was first hospitalizations with a primary or secondary discharge diagnosis of ADRD or PD. To examine associations of exposures to natural environments with ADRD and PD hospitalization, we used Cox-equivalent Poisson models., Results: We included 61 662 472 and 61 673 367 Medicare beneficiaries in the ADRD and PD cohorts, respectively. For both cohorts, 55.2% of beneficiaries were women. Most beneficiaries in both cohorts were White (84.4%), were not eligible for Medicaid (87.6%), and were aged 65 to 74 years (76.6%) at study entry. We observed 7 737 609 and 1 168 940 first ADRD and PD hospitalizations, respectively. After adjustment for potential individual- and area-level confounders (eg, Medicaid eligibility and zip code-level median household income), NDVI was negatively associated with ADRD hospitalization (hazard ratio [HR], 0.95 [95% CI, 0.94-0.96], per IQR increase). We found no evidence of an association of percentage park and blue space cover with ADRD hospitalization. In contrast, NDVI (HR, 0.94 [95% CI, 0.93-0.95], per IQR increase), percentage park cover (HR, 0.97 [95% CI, 0.97-0.98], per IQR increase), and blue space cover (HR, 0.97 [95% CI, 0.96-0.98], ≥1.0% vs <1.0%) were associated with a decrease in PD hospitalizations. Patterns of effect modification by demographics differed between exposures., Conclusions and Relevance: The findings of this cohort study suggest that some natural environments are associated with a decreased risk of ADRD and PD hospitalization.

Natural environments have been linked to decreased risk of cardiovascular disease (CVD) and respiratory disease (RSD) mortality. However, few cohort studies have looked at associations of natural environments with CVD or RSD hospitalization. The aim of this study was to evaluate these associations in a cohort of U.S. Medicare beneficiaries (∼63 million individuals). Our open cohort included all fee-for-service Medicare beneficiaries (2000-2016), aged ≥65, living in the contiguous U.S. We assessed zip code-level park cover based on the United States Geological Survey Protected Areas Database, average greenness (Normalized Difference Vegetation Index, NDVI), and percent blue space cover based on Landsat satellite images. Cox-equivalent Poisson models were used to estimate associations of the exposures with first CVD and RSD hospitalization in the full cohort and among those living in urban zip codes (≥1000 persons/mile 2 ). NDVI was weakly negatively correlated with percent park cover (Spearman ρ = -0.23) and not correlated with percent blue space (Spearman ρ = 0.00). After adjustment for potential confounders, percent park cover was not associated with CVD or RSD hospitalization in the full or urban population. An IQR (0.27) increase in NDVI was negatively associated with CVD (HR: 0.97, 95%CI: 0.96, 0.97), but not with RSD hospitalization (HR: 0.99, 95%CI: 0.98, 1.00). In urban zip codes, an IQR increase in NDVI was positively associated with RSD hospitalization (HR: 1.02, 95%CI: 1.00, 1.03). In stratified analyses, percent park cover was negatively associated with CVD and RSD hospitalization for Medicaid eligible individuals and individuals living in low socioeconomic status neighborhoods in the urban population. We observed no associations of percent blue space cover with CVD or RSD hospitalization. This study suggests that natural environments may benefit cardiorespiratory health; however, benefits may be limited to certain contexts and certain health outcomes., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:, (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: The association between long-term exposure to air pollution and mortality from cardiorespiratory diseases is well established, yet the evidence for other diseases remains limited., Objectives: To examine the associations of long-term exposure to air pollution with mortality from diabetes, dementia, psychiatric disorders, chronic kidney disease (CKD), asthma, acute lower respiratory infection (ALRI), as well as mortality from all-natural and cardiorespiratory causes in the Danish nationwide administrative cohort., Methods: We followed all residents aged ≥ 30 years (3,083,227) in Denmark from 1 January 2000 until 31 December 2017. Annual mean concentrations of fine particulate matter (PM 2.5 ), nitrogen dioxide (NO 2 ), black carbon (BC), and ozone (warm season) were estimated using European-wide hybrid land-use regression models (100 m × 100 m) and assigned to baseline residential addresses. We used Cox proportional hazard models to evaluate the association between air pollution and mortality, accounting for demographic and socioeconomic factors. We additionally applied indirect adjustment for smoking and body mass index (BMI)., Results: During 47,023,454 person-years of follow-up, 803,881 people died from natural causes. Long-term exposure to PM 2.5 (mean: 12.4 µg/m 3 ), NO 2 (20.3 µg/m 3 ), and/or BC (1.0 × 10 -5 /m) was statistically significantly associated with all studied mortality outcomes except CKD. A 5 µg/m 3 increase in PM 2.5 was associated with higher mortality from all-natural causes (hazard ratio 1.11; 95% confidence interval 1.09-1.13), cardiovascular disease (1.09; 1.07-1.12), respiratory disease (1.11; 1.07-1.15), lung cancer (1.19; 1.15-1.24), diabetes (1.10; 1.04-1.16), dementia (1.05; 1.00-1.10), psychiatric disorders (1.38; 1.27-1.50), asthma (1.13; 0.94-1.36), and ALRI (1.14; 1.09-1.20). Associations with long-term exposure to ozone (mean: 80.2 µg/m 3 ) were generally negative but became significantly positive for several endpoints in two-pollutant models. Generally, associations were attenuated but remained significant after indirect adjustment for smoking and BMI., Conclusion: Long-term exposure to PM 2.5 , NO 2 , and/or BC in Denmark were associated with mortality beyond cardiorespiratory diseases, including diabetes, dementia, psychiatric disorders, asthma, and ALRI., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Green space, air pollution and traffic noise exposure may be associated with mental health in adolescents. We assessed the associations of long-term exposure to residential green space, ambient air pollution and traffic noise with mental wellbeing from age 11 to 20 years., Methods: We included 3059 participants of the Dutch PIAMA birth cohort who completed the five-item Mental Health Inventory (MHI-5) at ages 11, 14, 17 and/or 20 years. We estimated exposure to green space (the average Normalized Difference Vegetation Index (NDVI) and percentages of green space in circular buffers of 300 m, 1000 m and 3000 m), ambient air pollution (particulate matter (PM 10 and PM 2.5 ), nitrogen dioxide, PM 2.5 absorbance and the oxidative potential of PM 2.5 ) and road traffic and railway noise (L den ) at the adolescents' home addresses at the times of completing the MHI-5. Associations with poor mental wellbeing (MHI-5 score ≤ 60) were assessed by generalized linear mixed models with a logit link, adjusting for covariates., Results: The odds of poor mental wellbeing at age 11 to 20 years decreased with increasing exposure to green space in a 3000 m buffer (adjusted odds ratio (OR) 0.78 [95% CI 0.68-0.88] per IQR increase in the average NDVI; adjusted OR 0.77 [95% CI 0.67-0.88] per IQR increase in the total percentage of green space). These associations persisted after adjustment for air pollution and road traffic noise. Relationships between mental wellbeing and green space in buffers of 300 m and 1000 m were less consistent. Higher air pollution exposure was associated with higher odds of poor mental wellbeing, but these associations were strongly attenuated after adjustment for green space in a buffer of 3000 m, traffic noise and degree of urbanization. Traffic noise was not related to mental wellbeing throughout adolescence., Conclusions: Residential exposure to green space may be associated with a better mental wellbeing in adolescents., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Evidence for the association between long-term exposure to ambient particulate matter components and mortality from natural causes is sparse and inconsistent. We evaluated this association in six large administrative cohorts in the framework of the Effects of Low-Level Air Pollution: A Study in Europe (ELAPSE) project. We analyzed data from country-wide administrative cohorts in Norway, Denmark, the Netherlands, Belgium, Switzerland and in Rome (Italy). Annual 2010 mean concentrations of copper (Cu), iron (Fe), potassium (K), nickel (Ni), sulfur (S), silicon (Si), vanadium (V) and zinc (Zn) in fine particulate matter (PM 2.5 ) were estimated using 100 × 100 m Europe-wide hybrid land use regression models assigned to the participants' residential addresses. We applied cohort-specific Cox proportional hazard models controlling for area- and individual-level covariates to evaluate associations with natural mortality. Two pollutant models adjusting for PM 2.5 total mass or nitrogen dioxide (NO 2 ) were also applied. We pooled cohort-specific estimates using a random effects meta-analysis. We included almost 27 million participants contributing more than 240 million person-years. All components except Zn were significantly associated with natural mortality [pooled Hazard Ratios (HRs) (95% CI): 1.037 (1.014, 1.060) per 5 ng/m 3 Cu; 1.069 (1.031, 1.108) per 100 ng/m 3 Fe; 1.039 (1.018, 1.062) per 50 ng/m 3 K; 1.024 (1.006, 1.043) per 1 ng/m 3 Ni; 1.036 (1.016, 1.057) per 200 ng/m 3 S; 1.152 (1.048, 1.266) per 100 ng/m 3 Si; 1.020 (1.006, 1.034) per 2 ng/m 3 V]. Only K and Si were robust to PM 2.5 or NO 2 adjustment [pooled HRs (95% CI) per 50 ng/m 3 in K: 1.025 (1.008, 1.044), 1.020 (0.999, 1.042) and per 100 ng/m 3 in Si: 1.121 (1.039, 1.209), 1.068 (1.022, 1.117) adjusted for PM 2.5 and NO 2 correspondingly]. Our findings indicate an association of natural mortality with most components, which was reduced after adjustment for PM 2.5 and especially NO 2 ., Competing Interests: Declaration of competing interest None declared., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Background: Ambient air pollution exposure has been associated with higher mortality risk in numerous studies. We assessed potential variability in the magnitude of this association for non-accidental, cardiovascular disease, respiratory disease, and lung cancer mortality in a country-wide administrative cohort by exposure assessment method and by adjustment for geographic subdivisions., Methods: We used the Belgian 2001 census linked to population and mortality register including nearly 5.5 million adults aged ≥30 (mean follow-up: 9.97 years). Annual mean concentrations for fine particulate matter (PM 2.5 ), nitrogen dioxide (NO 2 ), black carbon (BC) and ozone (O 3 ) were assessed at baseline residential address using two exposure methods; Europe-wide hybrid land use regression (LUR) models [100x100m], and Belgium-wide interpolation-dispersion (RIO-IFDM) models [25x25m]. We used Cox proportional hazards models with age as the underlying time scale and adjusted for various individual and area-level covariates. We further adjusted main models for two different area-levels following the European Nomenclature of Territorial Units for Statistics (NUTS); NUTS-1 (n = 3), or NUTS-3 (n = 43)., Results: We found no consistent differences between both exposure methods. We observed most robust associations with lung cancer mortality. Hazard Ratios (HRs) per 10 μg/m 3 increase for NO 2 were 1.060 (95%CI 1.042-1.078) [hybrid LUR] and 1.040 (95%CI 1.022-1.058) [RIO-IFDM]. Associations with non-accidental, respiratory disease and cardiovascular disease mortality were generally null in main models but were enhanced after further adjustment for NUTS-1 or NUTS-3. HRs for non-accidental mortality per 5 μg/m 3 increase for PM 2.5 for the main model using hybrid LUR exposure were 1.023 (95%CI 1.011-1.035). After including random effects HRs were 1.044 (95%CI 1.033-1.057) [NUTS-1] and 1.076 (95%CI 1.060-1.092) [NUTS-3]., Conclusion: Long-term air pollution exposure was associated with higher lung cancer mortality risk but not consistently with the other studied causes. Magnitude of associations varied by adjustment for geographic subdivisions, area-level socio-economic covariates and less by exposure assessment method., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Background: Long-term exposure to ambient air pollution has been associated with premature mortality, but associations at concentrations lower than current annual limit values are uncertain. We analysed associations between low-level air pollution and mortality within the multicentre study Effects of Low-Level Air Pollution: A Study in Europe (ELAPSE)., Methods: In this multicentre longitudinal study, we analysed seven population-based cohorts of adults (age ≥30 years) within ELAPSE, from Belgium, Denmark, England, the Netherlands, Norway, Rome (Italy), and Switzerland (enrolled in 2000-11; follow-up until 2011-17). Mortality registries were used to extract the underlying cause of death for deceased individuals. Annual average concentrations of fine particulate matter (PM 2·5 ), nitrogen dioxide (NO 2 ), black carbon, and tropospheric warm-season ozone (O 3 ) from Europe-wide land use regression models at 100 m spatial resolution were assigned to baseline residential addresses. We applied cohort-specific Cox proportional hazard models with adjustment for area-level and individual-level covariates to evaluate associations with non-accidental mortality, as the main outcome, and with cardiovascular, non-malignant respiratory, and lung cancer mortality. Subset analyses of participants living at low pollutant concentrations (as per predefined values) and natural splines were used to investigate the concentration-response function. Cohort-specific effect estimates were pooled in a random-effects meta-analysis., Findings: We analysed 28 153 138 participants contributing 257 859 621 person-years of observation, during which 3 593 741 deaths from non-accidental causes occurred. We found significant positive associations between non-accidental mortality and PM 2·5 , NO 2 , and black carbon, with a hazard ratio (HR) of 1·053 (95% CI 1·021-1·085) per 5 μg/m 3 increment in PM 2·5 , 1·044 (1·019-1·069) per 10 μg/m 3 NO 2 , and 1·039 (1·018-1·059) per 0·5 × 10 -5 /m black carbon. Associations with PM 2·5 , NO 2 , and black carbon were slightly weaker for cardiovascular mortality, similar for non-malignant respiratory mortality, and stronger for lung cancer mortality. Warm-season O 3 was negatively associated with both non-accidental and cause-specific mortality. Associations were stronger at low concentrations: HRs for non-accidental mortality at concentrations lower than the WHO 2005 air quality guideline values for PM 2·5 (10 μg/m 3 ) and NO 2 (40 μg/m 3 ) were 1·078 (1·046-1·111) per 5 μg/m 3 PM 2·5 and 1·049 (1·024-1·075) per 10 μg/m 3 NO 2 . Similarly, the association between black carbon and non-accidental mortality was highest at low concentrations, with a HR of 1·061 (1·032-1·092) for exposure lower than 1·5× 10 -5 /m, and 1·081 (0·966-1·210) for exposure lower than 1·0× 10 -5 /m., Interpretation: Long-term exposure to concentrations of PM 2·5 and NO 2 lower than current annual limit values was associated with non-accidental, cardiovascular, non-malignant respiratory, and lung cancer mortality in seven large European cohorts. Continuing research on the effects of low concentrations of air pollutants is expected to further inform the process of setting air quality standards in Europe and other global regions., Funding: Health Effects Institute., Competing Interests: Declaration of interests We declare no competing interests., (Copyright © 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Particulate matter air pollution and diesel engine exhaust have been classified as carcinogenic for lung cancer, yet few studies have explored associations with liver cancer. We used six European adult cohorts which were recruited between 1985 and 2005, pooled within the "Effects of low-level air pollution: A study in Europe" (ELAPSE) project, and followed for the incidence of liver cancer until 2011 to 2015. The annual average exposure to nitrogen dioxide (NO 2 ), particulate matter with diameter <2.5 μm (PM 2.5 ), black carbon (BC), warm-season ozone (O 3 ), and eight elemental components of PM 2.5 (copper, iron, zinc, sulfur, nickel, vanadium, silicon, and potassium) were estimated by European-wide hybrid land-use regression models at participants' residential addresses. We analyzed the association between air pollution and liver cancer incidence by Cox proportional hazards models adjusting for potential confounders. Of 330 064 cancer-free adults at baseline, 512 developed liver cancer during a mean follow-up of 18.1 years. We observed positive linear associations between NO 2 (hazard ratio, 95% confidence interval: 1.17, 1.02-1.35 per 10 μg/m 3 ), PM 2.5 (1.12, 0.92-1.36 per 5 μg/m 3 ), and BC (1.15, 1.00-1.33 per 0.5 10 -5 /m) and liver cancer incidence. Associations with NO 2 and BC persisted in two-pollutant models with PM 2.5 . Most components of PM 2.5 were associated with the risk of liver cancer, with the strongest associations for sulfur and vanadium, which were robust to adjustment for PM 2.5 or NO 2 . Our study suggests that ambient air pollution may increase the risk of liver cancer, even at concentrations below current EU standards., (© 2021 The Authors. International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC.)

Background: Studies have observed associations between long-term air pollution and cardiovascular disease hospitalization. Little is known, however, about effect modification of these associations by greenness, temperature and humidity., Methods: We constructed an open cohort consisting of all fee-for-service Medicare beneficiaries, aged ≥ 65, living in the contiguous US from 2000 through 2016 (~63 million individuals). We assigned annual average PM 2.5 , NO 2 and ozone zip code concentrations. Cox-equivalent Poisson models were used to estimate associations with first cardiovascular disease (CVD), coronary heart disease (CHD) and cerebrovascular disease (CBV) hospitalization., Results: PM 2.5 and NO 2 were both positively associated with CVD, CHD and CBV hospitalization, after adjustment for potential confounders. Associations were substantially stronger at the lower end of the exposure distributions. For CVD hospitalization, the hazard ratio (HR) of PM 2.5 was 1.041 (1.038, 1.045) per IQR increase (4.0 µg/m 3 ) in the full study population and 1.327 (1.305, 1.350) per IQR increase for a subgroup with annual exposures always below 10 µg/m 3 PM 2.5 . Ozone was only positively associated with CVD, CHD and CBV hospitalization for the low-exposure subgroup (<40 ppb). Associations of PM 2.5 were stronger in areas with higher greenness, lower ozone and O x , lower summer and winter temperature and lower summer and winter specific humidity., Conclusion: PM 2.5 and NO 2 were positively associated with CVD, CHD and CBV hospitalization. Associations were more pronounced at low exposure levels. Associations of PM 2.5 were stronger with higher greenness, lower ozone and O x , lower temperature and lower specific humidity., (Copyright © 2021. Published by Elsevier Ltd.)

Background: Long-term exposure to outdoor air pollution increases the risk of cardiovascular disease, but evidence is unclear on the health effects of exposure to pollutant concentrations lower than current EU and US standards and WHO guideline limits. Within the multicentre study Effects of Low-Level Air Pollution: A Study in Europe (ELAPSE), we investigated the associations of long-term exposures to fine particulate matter (PM 2·5 ), nitrogen dioxide (NO 2 ), black carbon, and warm-season ozone (O 3 ) with the incidence of stroke and acute coronary heart disease., Methods: We did a pooled analysis of individual data from six population-based cohort studies within ELAPSE, from Sweden, Denmark, the Netherlands, and Germany (recruited 1992-2004), and harmonised individual and area-level variables between cohorts. Participants (all adults) were followed up until migration from the study area, death, or incident stroke or coronary heart disease, or end of follow-up (2011-15). Mean 2010 air pollution concentrations from centrally developed European-wide land use regression models were assigned to participants' baseline residential addresses. We used Cox proportional hazards models with increasing levels of covariate adjustment to investigate the association of air pollution exposure with incidence of stroke and coronary heart disease. We assessed the shape of the concentration-response function and did subset analyses of participants living at pollutant concentrations lower than predefined values., Findings: From the pooled ELAPSE cohorts, data on 137 148 participants were analysed in our fully adjusted model. During a median follow-up of 17·2 years (IQR 13·8-19·5), we observed 6950 incident events of stroke and 10 071 incident events of coronary heart disease. Incidence of stroke was associated with PM 2·5 (hazard ratio 1·10 [95% CI 1·01-1·21] per 5 μg/m 3 increase), NO 2 (1·08 [1·04-1·12] per 10 μg/m 3 increase), and black carbon (1·06 [1·02-1·10] per 0·5 10 -5 /m increase), whereas coronary heart disease incidence was only associated with NO 2 (1·04 [1·01-1·07]). Warm-season O 3 was not associated with an increase in either outcome. Concentration-response curves indicated no evidence of a threshold below which air pollutant concentrations are not harmful for cardiovascular health. Effect estimates for PM 2·5 and NO 2 remained elevated even when restricting analyses to participants exposed to pollutant concentrations lower than the EU limit values of 25 μg/m 3 for PM 2·5 and 40 μg/m 3 for NO 2 ., Interpretation: Long-term air pollution exposure was associated with incidence of stroke and coronary heart disease, even at pollutant concentrations lower than current limit values., Funding: Health Effects Institute., Competing Interests: Declaration of interests We declare no competing interests., (Copyright © 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Background: COVID-19 is an infectious disease that has killed more than 555,000 people in the US. During a time of social distancing measures and increasing social isolation, green spaces may be a crucial factor to maintain a physically and socially active lifestyle while not increasing risk of infection., Objectives: We evaluated whether greenness was related to COVID-19 incidence and mortality in the US., Methods: We downloaded data on COVID-19 cases and deaths for each US county up through June 7, 2020, from Johns Hopkins University, Center for Systems Science and Engineering Coronavirus Resource Center. We used April-May 2020 Normalized Difference Vegetation Index (NDVI) data, to represent the greenness exposure during the initial COVID-19 outbreak in the US. We fitted negative binomial mixed models to evaluate associations of NDVI with COVID-19 incidence and mortality, adjusting for potential confounders such as county-level demographics, epidemic stage, and other environmental factors. We evaluated whether the associations were modified by population density, proportion of Black residents, median home value, and issuance of stay-at-home orders., Results: An increase of 0.1 in NDVI was associated with a 6% (95% Confidence Interval: 3%, 10%) decrease in COVID-19 incidence rate after adjustment for potential confounders. Associations with COVID-19 incidence were stronger in counties with high population density and in counties with stay-at-home orders. Greenness was not associated with COVID-19 mortality in all counties; however, it was protective in counties with higher population density., Discussion: Exposures to NDVI were associated with reduced county-level incidence of COVID-19 in the US as well as reduced county-level COVID-19 mortality rates in densely populated counties., (Copyright © 2021 Elsevier Inc. All rights reserved.)

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., (© 2021. The Author(s).)

Background: Long-term exposure to ambient air pollution has been linked to childhood-onset asthma, although evidence is still insufficient. Within the multicentre project Effects of Low-Level Air Pollution: A Study in Europe (ELAPSE), we examined the associations of long-term exposures to particulate matter with a diameter <2.5 µm (PM 2.5 ), nitrogen dioxide (NO 2 ) and black carbon (BC) with asthma incidence in adults., Methods: We pooled data from three cohorts in Denmark and Sweden with information on asthma hospital diagnoses. The average concentrations of air pollutants in 2010 were modelled by hybrid land-use regression models at participants' baseline residential addresses. Associations of air pollution exposures with asthma incidence were explored with Cox proportional hazard models, adjusting for potential confounders., Results: Of 98 326 participants, 1965 developed asthma during a mean follow-up of 16.6 years. We observed associations in fully adjusted models with hazard ratios of 1.22 (95% CI 1.04-1.43) per 5 μg·m -3 for PM 2.5 , 1.17 (95% CI 1.10-1.25) per 10 µg·m -3 for NO 2 and 1.15 (95% CI 1.08-1.23) per 0.5×10 -5  m -1 for BC. Hazard ratios were larger in cohort subsets with exposure levels below the European Union and US limit values and possibly World Health Organization guidelines for PM 2.5 and NO 2 . NO 2 and BC estimates remained unchanged in two-pollutant models with PM 2.5 , whereas PM 2.5 estimates were attenuated to unity. The concentration-response curves showed no evidence of a threshold., Conclusions: Long-term exposure to air pollution, especially from fossil fuel combustion sources such as motorised traffic, was associated with adult-onset asthma, even at levels below the current limit values., Competing Interests: Conflict of interest: S. Liu has nothing to disclose. Conflict of interest: J.T. Jørgensen has nothing to disclose. Conflict of interest: P. Ljungman has nothing to disclose. Conflict of interest: G. Pershagen has nothing to disclose. Conflict of interest: T. Bellander has nothing to disclose. Conflict of interest: K. Leander has nothing to disclose. Conflict of interest: P.K.E. Magnusson has nothing to disclose. Conflict of interest: D. Rizzuto has nothing to disclose. Conflict of interest: U.A. Hvidtfeldt has nothing to disclose. Conflict of interest: O. Raaschou-Nielsen has nothing to disclose. Conflict of interest: K. Wolf has nothing to disclose. Conflict of interest: B. Hoffmann has nothing to disclose. Conflict of interest: B. Brunekreef has nothing to disclose. Conflict of interest: M. Strak has nothing to disclose. Conflict of interest: J. Chen has nothing to disclose. Conflict of interest: A. Mehta has nothing to disclose. Conflict of interest: R.W. Atkinson has nothing to disclose. Conflict of interest: M. Bauwelinck has nothing to disclose. Conflict of interest: R. Varraso has nothing to disclose. Conflict of interest: M-C. Boutron-Ruault has nothing to disclose. Conflict of interest: J. Brandt has nothing to disclose. Conflict of interest: G. Cesaroni has nothing to disclose. Conflict of interest: F. Forastiere has nothing to disclose. Conflict of interest: D. Fecht has nothing to disclose. Conflict of interest: J. Gulliver has nothing to disclose. Conflict of interest: O. Hertel has nothing to disclose. Conflict of interest: K. de Hoogh has nothing to disclose. Conflict of interest: N.A.H. Janssen has nothing to disclose. Conflict of interest: K. Katsouyanni has nothing to disclose. Conflict of interest: M. Ketzel has nothing to disclose. Conflict of interest: J.O. Klompmaker has nothing to disclose. Conflict of interest: G. Nagel has nothing to disclose. Conflict of interest: B. Oftedal has nothing to disclose. Conflict of interest: A. Peters has nothing to disclose. Conflict of interest: A. Tjønneland has nothing to disclose. Conflict of interest: S.P. Rodopoulou has nothing to disclose. Conflict of interest: E Samoli has nothing to disclose. Conflict of interest: D.T. Kristoffersen has nothing to disclose. Conflict of interest: T. Sigsgaard has nothing to disclose. Conflict of interest: M. Stafoggia has nothing to disclose. Conflict of interest: D. Vienneau has nothing to disclose. Conflict of interest: G. Weinmayr has nothing to disclose. Conflict of interest: G. Hoek has nothing to disclose. Conflict of interest: Z.J. Andersen has nothing to disclose., (Copyright ©ERS 2021.)

Green space, air pollution, and traffic noise exposure may be associated with stress levels in children. A flattened diurnal cortisol slope (the decline in cortisol concentrations from awakening to evening) is an indicator of chronic stress. We examined associations of green space, ambient air pollution, and traffic noise with the diurnal cortisol slope in children 12 years of age., Methods: At age 12 years, 1,027 participants of the Dutch PIAMA birth cohort collected three saliva samples during 1 day. We estimated residential exposure to green space (i.e., the average Normalized Difference Vegetation Index [NDVI] and percentages of green space in circular buffers of 300 m and 3,000 m), air pollution, and traffic noise. Associations of these exposures with the diurnal cortisol slope (in nmol/L per hour) were assessed by multiple linear regression, adjusting for potential confounders., Results: Higher average NDVI and total percentage of green space in a 3,000 m buffer were associated with a larger diurnal decrease in cortisol levels (adjusted difference [95% confidence interval] = -0.11 nmol/L/hr [-0.21, 0.00 nmol/L/hr] per interquartile range increase in the average NDVI; -0.13 nmol/L/hr [-0.26, 0.00 nmol/L/hr] per interquartile range increase in the total percentage of green space). These associations were largely driven by associations with the percentage of agricultural green space and by associations in children living in nonurban areas. We observed no relationships between air pollution or traffic noise and the diurnal cortisol slope., Conclusions: Residential exposure to green space in a buffer of 3,000 m may be associated with lower stress levels in children 12 years of age., Competing Interests: The authors declare that they have no conflicts of interest with regard to the content of this report.The data underlying the findings presented in this article are available on request. Requests can be submitted to the PIAMA Principal Investigators. Their names and e-mail addresses are listed on the PIAMA website (http://piama.iras.uu.nl/index-en.php#collaboration). The PIAMA data are not freely accessible in the public domain, because this would be in conflict with the agreement between the PIAMA study team and the PIAMA participants. The information participants received at the start of the study (in 1996–1997) included the statement “the information that we receive from you will only be used for the PIAMA project” and participants gave written informed consent based on this information., (Copyright © 2021 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of The Environmental Epidemiology. All rights reserved.)

Background: Inconsistent associations between long-term exposure to particles with an aerodynamic diameter ≤ 2.5   μ m [fine particulate matter ( PM 2.5 )] components and mortality have been reported, partly related to challenges in exposure assessment., Objectives: We investigated the associations between long-term exposure to PM 2.5 elemental components and mortality in a large pooled European cohort; to compare health effects of PM 2.5 components estimated with two exposure modeling approaches, namely, supervised linear regression (SLR) and random forest (RF) algorithms., Methods: 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 PM 2.5 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 100 × 100   m 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 PM 2.5 mass and nitrogen dioxide ( NO 2 ) separately., Results: 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 PM 2.5 and NO 2 . 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 2   ng / m 3 , adjusting for PM 2.5 mass. Associations with cause-specific mortality were less consistent in two-pollutant models., Conclusion: Long-term exposure to V in PM 2.5 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.

Background: We evaluated methods for the analysis of multi-level survival data using a pooled dataset of 14 cohorts participating in the ELAPSE project investigating associations between residential exposure to low levels of air pollution (PM 2.5 and NO 2 ) and health (natural-cause mortality and cerebrovascular, coronary and lung cancer incidence)., Methods: We applied five approaches in a multivariable Cox model to account for the first level of clustering corresponding to cohort specification: (1) not accounting for the cohort or using (2) indicator variables, (3) strata, (4) a frailty term in frailty Cox models, (5) a random intercept under a mixed Cox, for cohort identification. We accounted for the second level of clustering due to common characteristics in the residential area by (1) a random intercept per small area or (2) applying variance correction. We assessed the stratified, frailty and mixed Cox approach through simulations under different scenarios for heterogeneity in the underlying hazards and the air pollution effects., Results: Effect estimates were stable under approaches used to adjust for cohort but substantially differed when no adjustment was applied. Further adjustment for the small area grouping increased the effect estimates' standard errors. Simulations confirmed identical results between the stratified and frailty models. In ELAPSE we selected a stratified multivariable Cox model to account for between-cohort heterogeneity without adjustment for small area level, due to the small number of subjects and events in the latter., Conclusions: Our study supports the need to account for between-cohort heterogeneity in multi-center collaborations using pooled individual level data., (Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: An association between long-term exposure to fine particulate matter (PM 2.5 ) and lung cancer has been established in previous studies. PM 2.5 is a complex mixture of chemical components from various sources and little is known about whether certain components contribute specifically to the associated lung cancer risk. The present study builds on recent findings from the "Effects of Low-level Air Pollution: A Study in Europe" (ELAPSE) collaboration and addresses the potential association between specific elemental components of PM 2.5 and lung cancer incidence., Methods: We pooled seven cohorts from across Europe and assigned exposure estimates for eight components of PM 2.5 representing non-tail pipe emissions (copper (Cu), iron (Fe), and zinc (Zn)), long-range transport (sulfur (S)), oil burning/industry emissions (nickel (Ni), vanadium (V)), crustal material (silicon (Si)), and biomass burning (potassium (K)) to cohort participants' baseline residential address based on 100 m by 100 m grids from newly developed hybrid models combining air pollution monitoring, land use data, satellite observations, and dispersion model estimates. We applied stratified Cox proportional hazards models, adjusting for potential confounders (age, sex, calendar year, marital status, smoking, body mass index, employment status, and neighborhood-level socio-economic status)., Results: The pooled study population comprised 306,550 individuals with 3916 incident lung cancer events during 5,541,672 person-years of follow-up. We observed a positive association between exposure to all eight components and lung cancer incidence, with adjusted HRs of 1.10 (95% CI 1.05, 1.16) per 50 ng/m 3 PM 2.5  K, 1.09 (95% CI 1.02, 1.15) per 1 ng/m 3 PM 2.5 Ni, 1.22 (95% CI 1.11, 1.35) per 200 ng/m 3 PM 2.5  S, and 1.07 (95% CI 1.02, 1.12) per 200 ng/m 3 PM 2.5  V. Effect estimates were largely unaffected by adjustment for nitrogen dioxide (NO 2 ). After adjustment for PM 2.5 mass, effect estimates of K, Ni, S, and V were slightly attenuated, whereas effect estimates of Cu, Si, Fe, and Zn became null or negative., Conclusions: Our results point towards an increased risk of lung cancer in connection with sources of combustion particles from oil and biomass burning and secondary inorganic aerosols rather than non-exhaust traffic emissions. Specific limit values or guidelines targeting these specific PM 2.5 components may prove helpful in future lung cancer prevention strategies., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Background: Air pollution has been suggested as a risk factor for chronic obstructive pulmonary disease (COPD), but evidence is sparse and inconsistent., Objectives: We examined the association between long-term exposure to low-level air pollution and COPD incidence., Methods: Within the 'Effects of Low-Level Air Pollution: A Study in Europe' (ELAPSE) study, we pooled data from three cohorts, from Denmark and Sweden, with information on COPD hospital discharge diagnoses. Hybrid land use regression models were used to estimate annual mean concentrations of particulate matter with a diameter < 2.5 µm (PM 2.5 ), nitrogen dioxide (NO 2 ), and black carbon (BC) in 2010 at participants' baseline residential addresses, which were analysed in relation to COPD incidence using Cox proportional hazards models., Results: Of 98,058 participants, 4,928 developed COPD during 16.6 years mean follow-up. The adjusted hazard ratios (HRs) and 95% confidence intervals for associations with COPD incidence were 1.17 (1.06, 1.29) per 5 µg/m 3 for PM 2.5 , 1.11 (1.06, 1.16) per 10 µg/m 3 for NO 2 , and 1.11 (1.06, 1.15) per 0.5 10 -5 m -1 for BC. Associations persisted in subset participants with PM 2.5 or NO 2 levels below current EU and US limit values and WHO guidelines, with no evidence for a threshold. HRs for NO 2 and BC remained unchanged in two-pollutant models with PM 2.5 , whereas the HR for PM 2.5 was attenuated to unity with NO 2 or BC., Conclusions: Long-term exposure to low-level air pollution is associated with the development of COPD, even below current EU and US limit values and possibly WHO guidelines. Traffic-related pollutants NO 2 and BC may be the most relevant., (Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Introduction: To characterize air pollution exposure at a fine spatial scale, different exposure assessment methods have been applied. Comparison of associations with health from different exposure methods are scarce. The aim of this study was to evaluate associations of air pollution based on hybrid, land-use regression (LUR) and dispersion models with natural cause and cause-specific mortality., Methods: We followed a Dutch national cohort of approximately 10.5 million adults aged 29+ years from 2008 until 2012. We used Cox proportional hazard models with age as underlying time scale and adjusted for several potential individual and area-level socio-economic status confounders to evaluate associations of annual average residential NO 2 , PM 2.5 and BC exposure estimates based on two stochastic models (Dutch LUR, European-wide hybrid) and deterministic Dutch dispersion models., Results: Spatial variability of PM 2.5 and BC exposure was smaller for LUR compared to hybrid and dispersion models. NO 2 exposure variability was similar for the three methods. Pearson correlations between hybrid, LUR and dispersion modeled NO 2 and BC ranged from 0.72 to 0.83; correlations for PM 2.5 were slightly lower (0.61-0.72). In general, all three models showed stronger associations of air pollutants with respiratory disease and lung cancer mortality than with natural cause and cardiovascular disease mortality. The strength of the associations differed between the three exposure models. Associations of air pollutants estimated by LUR were generally weaker compared to associations of air pollutants estimated by hybrid and dispersion models. For natural cause mortality, we found a hazard ratio (HR) of 1.030 (95% confidence interval (CI): 1.019, 1.041) per 10 µg/m 3 for hybrid modeled NO 2 , a HR of 1.003 (95% CI: 0.993, 1.013) per 10 µg/m 3 for LUR modeled NO 2 and a HR of 1.015 (95% CI: 1.005, 1.024) per 10 µg/m 3 for dispersion modeled NO 2 ., Conclusion: Air pollution was positively associated with natural cause and cause-specific mortality, but the strength of the associations differed between the three exposure models. Our study documents that the selected exposure model may contribute to heterogeneity in effect estimates of associations between air pollution and health., (Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background/aim: Ambient air pollution has been associated with lung cancer, but the shape of the exposure-response function - especially at low exposure levels - is not well described. The aim of this study was to address the relationship between long-term low-level air pollution exposure and lung cancer incidence., Methods: The "Effects of Low-level Air Pollution: a Study in Europe" (ELAPSE) collaboration pools seven cohorts from across Europe. We developed hybrid models combining air pollution monitoring, land use data, satellite observations, and dispersion model estimates for nitrogen dioxide (NO 2 ), fine particulate matter (PM 2.5 ), black carbon (BC), and ozone (O 3 ) to assign exposure to cohort participants' residential addresses in 100 m by 100 m grids. We applied stratified Cox proportional hazards models, adjusting for potential confounders (age, sex, calendar year, marital status, smoking, body mass index, employment status, and neighborhood-level socio-economic status). We fitted linear models, linear models in subsets, Shape-Constrained Health Impact Functions (SCHIF), and natural cubic spline models to assess the shape of the association between air pollution and lung cancer at concentrations below existing standards and guidelines., Results: The analyses included 307,550 cohort participants. During a mean follow-up of 18.1 years, 3956 incident lung cancer cases occurred. Median (Q1, Q3) annual (2010) exposure levels of NO 2 , PM 2.5 , BC and O 3 (warm season) were 24.2 µg/m 3 (19.5, 29.7), 15.4 µg/m 3 (12.8, 17.3), 1.6 10 -5 m -1 (1.3, 1.8), and 86.6 µg/m 3 (78.5, 92.9), respectively. We observed a higher risk for lung cancer with higher exposure to PM 2.5 (HR: 1.13, 95% CI: 1.05, 1.23 per 5 µg/m 3 ). This association was robust to adjustment for other pollutants. The SCHIF, spline and subset analyses suggested a linear or supra-linear association with no evidence of a threshold. In subset analyses, risk estimates were clearly elevated for the subset of subjects with exposure below the EU limit value of 25 µg/m 3 . We did not observe associations between NO 2 , BC or O 3 and lung cancer incidence., Conclusions: Long-term ambient PM 2.5 exposure is associated with lung cancer incidence even at concentrations below current EU limit values and possibly WHO Air Quality Guidelines., (Copyright © 2020 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: Most previous studies that investigated associations of surrounding green, air pollution or traffic noise with mortality focused on single exposures., Objectives: The aim of this study was to evaluate combined associations of long-term residential exposure to surrounding green, air pollution and traffic noise with total non-accidental and cause-specific mortality., Methods: We linked a national health survey (Public Health Monitor, PHM) conducted in 2012 to the Dutch longitudinal mortality database. Subjects of the survey who were 30 years or older on 1 January 2013 (n = 339,633) were followed from 1 January 2013 till 31 December 2017. 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 m and 1000 m), annual average air pollutant concentrations (including particulate matter (PM 10 , PM 2.5 ), nitrogen dioxide (NO 2 )) and traffic noise with non-accidental, circulatory disease, respiratory disease, lung cancer and neurodegenerative disease mortality., Results: We observed 26,886 non-accidental deaths over 1.627.365 person-years of follow-up. Surrounding green, air pollution and traffic noise exposure were not significantly associated with non-accidental or cause-specific mortality. For non-accidental mortality, we found a hazard ratio (HR) of 0.99 (0.98, 1.01) per IQR increase in NDVI 300 m, a HR of 0.99 (95% CI: 0.97, 1.01) per IQR increase in NO 2 , a HR of 0.98 (0.97, 1.00) per IQR increase in PM 2.5 and a HR of 0.99 (95% CI: 0.97, 1.01) per IQR increase in road-traffic noise. Analyses restricted to non-movers or excluding subjects aged 85+ years did not change the findings., Conclusion: We found no evidence for associations of long-term residential exposures to surrounding green, air pollution and traffic noise with non-accidental or cause-specific mortality in a large population based survey in the Netherlands, possibly related to the relatively short follow-up period., (Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Self-perceived general health (SGH) is one of the most inclusive and widely used measures of health status and a powerful predictor of mortality. However, only a limited number of studies evaluated associations of combined environmental exposures on SGH. Our aim was to evaluate associations of combined residential exposure to surrounding green, air pollution and traffic noise with poor SGH in the Netherlands. We linked data on long-term residential exposure to surrounding green based on the Normalized Difference Vegetation Index (NDVI) and a land-use database (TOP10NL), air pollutant concentrations (including particulate matter (PM 10 , PM 2.5 ), and nitrogen dioxide (NO 2 )) and road- and rail-traffic noise with a Dutch national health survey, resulting in a study population of 354,827 adults. We analyzed associations of single and combined exposures with poor SGH. In single-exposure models, NDVI within 300 m was inversely associated with poor SGH [odds ratio (OR) = 0.91, 95% CI: 0.89, 0.94 per IQR increase], while NO 2 was positively associated with poor SGH (OR = 1.07, 95% CI: 1.04, 1.11 per IQR increase). In multi-exposure models, associations with surrounding green and air pollution generally remained, but attenuated. Joint odds ratios (JOR) of combined exposure to air pollution, rail-traffic noise and decreased surrounding green were higher than the odds ratios of single-exposure models. Studies including only one of these correlated exposures may overestimate the risk of poor SGH attributed to the studied exposure, while underestimating the risk of combined exposures., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Green space has been hypothesized to improve cardiometabolic health of adolescents, whereas air pollution and traffic noise may negatively impact cardiometabolic health., Objectives: To examine the associations of green space, air pollution and traffic noise with cardiometabolic health in adolescents aged 12 and 16 years., Methods: Waist circumference, blood pressure, cholesterol and glycated hemoglobin (HbA1c) were measured in subsets of participants of the Dutch PIAMA birth cohort, who participated in medical examinations at ages 12 (n = 1505) and/or 16 years (n = 797). We calculated a combined cardiometabolic risk score for each participant, with a higher score indicating a higher cardiometabolic risk. We estimated exposure to green space (i.e. the average Normalized Difference Vegetation Index (NDVI) and percentages of green space in circular buffers of 300 m and 3000 m), air pollution (by land-use regression models) and traffic noise (using the Standard Model Instrumentation for Noise Assessments (STAMINA) model) at the adolescents' home addresses at the time of the medical examinations. We assessed associations of these exposures with cardiometabolic health outcomes at ages 12 and 16 by multiple linear regression, adjusting for potential confounders., Results: We did not observe consistent patterns of associations of green space, air pollution and traffic noise with the cardiometabolic risk score, blood pressure, total cholesterol levels, the total/HDL cholesterol ratio and HbA1c. We found inverse associations of air pollution with waist circumference at both age 12 and 16. These associations weakened after adjustment for region, except for particulate matter with a diameter of <2.5 μm (PM 2.5 ) at age 12. The association of PM 2.5 with waist circumference at age 12 remained after adjustment for green space and road traffic noise (adjusted difference - 1.42 cm [95% CI -2.50, -0.35 cm] per 1.16 μg/m 3 increase in PM 2.5 )., Conclusion: This study does not provide evidence for beneficial effects of green space or adverse effects of air pollution and traffic noise on cardiometabolic health in adolescents., (Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Surrounding green, air pollution, and noise have been associated with cardiometabolic diseases, but most studies have assessed only one of these correlated exposures., Objectives: We aimed to evaluate associations of combined exposures to green, air pollution, and road traffic noise with cardiometabolic diseases., Methods: 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., Results: 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., Conclusions: 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.

Background: Evidence is emerging that poor mental health is associated with the environmental exposures of surrounding green, air pollution and traffic noise. Most studies have evaluated only associations of single exposures with poor mental health., Objectives: To evaluate associations of combined exposure to surrounding green, air pollution and traffic noise with poor mental health., Methods: In this cross-sectional study, we linked data from a Dutch national health survey among 387,195 adults including questions about psychological distress, based on the Kessler 10 scale, to an external database on registered prescriptions of anxiolytics, hypnotics & sedatives and antidepressants. We added data on residential surrounding green in a 300 m and a 1000 m buffer based on the Normalized Difference Vegetation Index (NDVI) and a land-use database (TOP10NL), modeled annual average air pollutant concentrations (including particulate matter (PM 10 , PM 2.5 ), and nitrogen dioxide (NO 2 )) and modeled road- and rail-traffic noise (Lden and Lnight) to the survey. We used logistic regression to analyze associations of surrounding green, air pollution and traffic noise exposure with poor mental health., Results: In single exposure models, surrounding green was inversely associated with poor mental health. Air pollution was positively associated with poor mental health. Road-traffic noise was only positively associated with prescription of anxiolytics, while rail-traffic noise was only positively associated with psychological distress. For prescription of anxiolytics, we found an odds ratio [OR] of 0.88 (95% CI: 0.85, 0.92) per interquartile range [IQR] increase in NDVI within 300 m, an OR of 1.14 (95% CI: 1.10, 1.19) per IQR increase in NO 2 and an OR of 1.07 (95% CI: 1.03, 1.11) per IQR increase in road-traffic noise. In multi exposure analyses, associations with surrounding green and air pollution generally remained but attenuated. Joint odds ratios [JOR], based on the Cumulative Risk Index (CRI) method, of combined exposure to air pollution, traffic noise and decreased surrounding green were higher than the ORs of single exposure models. Associations of environmental exposures with poor mental health differed somewhat by age., Conclusions: Studies including only one of these three correlated exposures may overestimate the influence of poor mental health attributed to the studied exposure, while underestimating the influence of combined environmental exposures., (Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Air pollution, traffic noise and absence of green space may contribute to the development of overweight in children., Objectives: To investigate the combined associations of air pollution, traffic noise and green space with overweight throughout childhood., Methods: We used data for 3680 participants of the Dutch PIAMA birth cohort. We estimated exposure to air pollution, traffic noise and green space (i.e. the average Normalized Difference Vegetation Index (NDVI) and percentages of green space in circular buffers of 300 m and 3000 m) at the children's home addresses at the time of parental reported weight and height measurements. Associations of these exposures with overweight from age 3 to 17 years were analyzed by generalized linear mixed models, adjusting for potential confounders. Odds ratios (OR's) are presented for an interquartile range increase in exposure., Results: odds of being overweight increased with increasing exposure to NO 2 (adjusted OR 1.40 [95% confidence interval (CI) 1.12-1.74] per 8.90 µg/m 3 ) and tended to decrease with increasing exposure to green space in a 3000 m buffer (adjusted OR 0.86 [95% CI 0.71-1.04] per 0.13 increase in the NDVI; adjusted OR 0.86 [95% CI 0.71-1.03] per 29.5% increase in the total percentage of green space). After adjustment for NO 2 , the associations with green space in a 3000 m buffer weakened. No associations of traffic noise with overweight throughout childhood were found. In children living in an urban area, living further away from a park was associated with a lower odds of being overweight (adjusted OR 0.67 [95% CI 0.52-0.85] per 359.6 m)., Conclusions: Exposure to traffic-related air pollution, but not traffic noise or green space, may contribute to childhood overweight. Future studies examining the associations of green space with childhood overweight should account for air pollution exposure., (Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Green space may influence health through several pathways, for example, increased physical activity, enhanced social cohesion, reduced stress, and improved air quality. For green space to increase physical activity and social cohesion, spending time in green spaces is likely to be important., Objectives: We examined whether adolescents visit green spaces and for what purposes. Furthermore, we assessed the predictors of green space visits., Methods: In this cross-sectional study, data for 1911 participants of the Dutch PIAMA (Prevention and Incidence of Asthma and Mite Allergy) birth cohort were analyzed. At age 17, adolescents reported how often they visited green spaces for physical activities, social activities, relaxation, and to experience nature and quietness. We assessed the predictors of green space visits altogether and for different purposes by log-binomial regression., Results: Fifty-three percent of the adolescents visited green spaces at least once a week in summer, mostly for physical and social activities. Adolescents reporting that a green environment was (very) important to them visited green spaces most frequently {adjusted prevalence ratio (PR) [95% confidence interval (CI)] very vs. not important: 6.84 (5.10, 9.17) for physical activities and 4.76 (3.72, 6.09) for social activities}. Boys and adolescents with highly educated fathers visited green spaces more often for physical and social activities. Adolescents who own a dog visited green spaces more often to experience nature and quietness. Green space visits were not associated with the objectively measured quantity of residential green space, i.e., the average normalized difference vegetation index (NDVI) and percentages of urban, agricultural, and natural green space in circular buffers around the adolescents' homes., Conclusions: Subjective variables are stronger predictors of green space visits in adolescents than the objectively measured quantity of residential green space. https://doi.org/10.1289/EHP2429.

Introduction: In epidemiological studies, exposure to green space is inconsistently associated with being overweight and physical activity, possibly because studies differ widely in their definition of green space exposure, inclusion of important confounders, study population and data analysis., Objectives: We evaluated whether the association of green space with being overweight and physical activity depended upon definition of greenspace., Methods: We conducted a cross-sectional study using data from a Dutch national health survey of 387,195 adults. Distance to the nearest park entrance and surrounding green space, based on the Normalized Difference Vegetation Index (NDVI) or a detailed Dutch land-use database (TOP10NL), was calculated for each residential address. We used logistic regression analyses to study the association of green space exposure with being overweight and being moderately or vigorously physically active outdoors at least 150min/week (self-reported). To study the shape of the association, we specified natural splines and quintiles., Results: The distance to the nearest park entrance was not associated with being overweight or outdoor physical activity. Associations of surrounding green space with being overweight or outdoor physical activity were highly non-linear. For NDVI surrounding greenness, we observed significantly decreased odds of being overweight [300m buffer, odds ratio (OR) = 0.88; 95% CI: 0.86, 0.91] and increased odds for outdoor physical activity [300m buffer, OR = 1.14; 95% CI: 1.10, 1.17] in the highest quintile compared to the lowest quintile. For TOP10NL surrounding green space, associations were mostly non-significant. Associations were generally stronger for subjects living in less urban areas and for the smaller buffers., Conclusion: Associations of green space with being overweight and outdoor physical activity differed considerably between different green space definitions. Associations were strongest for NDVI surrounding greenness., (Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.)

Mobile and short-term monitoring campaigns are increasingly used to develop land-use regression (LUR) models for ultrafine particles (UFP) and black carbon (BC). It is not yet established whether LUR models based on mobile or short-term stationary measurements result in comparable models and concentration predictions. The goal of this paper is to compare LUR models based on stationary (30 min) and mobile UFP and BC measurements from a single campaign. An electric car collected both repeated stationary and mobile measurements in Amsterdam and Rotterdam, The Netherlands. A total of 2964 road segments and 161 stationary sites were sampled over two seasons. Our main comparison was based on predicted concentrations of the mobile and stationary monitoring LUR models at 12 682 residential addresses in Amsterdam. Predictor variables in the mobile and stationary LUR model were comparable, resulting in highly correlated predictions at external residential addresses (R 2 of 0.89 for UFP and 0.88 for BC). Mobile model predictions were, on average, 1.41 and 1.91 times higher than stationary model predictions for UFP and BC, respectively. LUR models based upon mobile and stationary monitoring predicted highly correlated UFP and BC concentration surfaces, but predicted concentrations based on mobile measurements were systematically higher.

Health effects of long-term exposure to ultrafine particles (UFP) have not been investigated in epidemiological studies because of the lack of spatially resolved UFP exposure data. Short-term monitoring campaigns used to develop land use regression (LUR) models for UFP typically had moderate performance. The aim of this study was to develop and evaluate spatial and spatiotemporal LUR models for UFP and Black Carbon (BC), including their ability to predict past spatial contrasts. We measured 30 min at each of 81 sites in Amsterdam and 80 in Rotterdam, The Netherlands in three different seasons. Models were developed using traffic, land use, reference site measurements, routinely measured pollutants and weather data. The percentage explained variation (R(2)) was 0.35-0.40 for BC and 0.33-0.42 for UFP spatial models. Traffic variables were present in every model. The coefficients for the spatial predictors were similar in spatial and spatiotemporal models. The BC LUR model explained 61% of the spatial variation in a previous campaign with longer sampling duration, better than the model R(2). The UFP LUR model explained 36% of UFP spatial variation measured 10 years earlier, similar to the model R(2). Short-term monitoring campaigns may be an efficient tool to develop LUR models.