Long-term exposure to ambient air pollution and risk of lung cancer - A comparative analysis of incidence and mortality in four administrative cohorts in the ELAPSE study.

BACKGROUND: Studies have linked air pollution to lung cancer incidence and mortality, but few have compared these associations, which may differ due to cancer survival variations. We aimed to evaluate the association between long-term air pollution exposure and lung cancer incidence and compare findings with previous lung cancer mortality analyses within the same cohorts. METHODS: We analyzed four population-based administrative cohorts in Denmark (2000-2015), England (2011-2017), Norway (2001-2016) and Rome (2001-2015). We assessed residential exposure to annual average fine particulate matter (PM2.5), nitrogen dioxide (NO2), black carbon (BC), and warm-season ozone (O3) using Europe-wide land use regression models. We used Cox proportional hazard models to evaluate cohort-specific hazard ratios (HRs) and 95% confidence intervals (CIs) for lung cancer incidence identified using hospital admission records (English and Roman cohorts) or cancer registries (Danish and Norwegian cohorts). We evaluated the associations at low exposure levels using subset analyses and natural cubic splines. Cohort-specific HRs were pooled using random-effects meta-analyses, separately for incidence and mortality. RESULTS: Over 93,733,929 person-years of follow-up, 111,949 incident lung cancer cases occurred. Incident lung cancer was positively associated with PM2.5, NO2 and BC, and negatively associated with O3. The negative O3 association became positive after adjustment for NO2. Associations were almost identical or slightly stronger for lung cancer incidence than mortality in the same cohorts, with respective meta-analytic HRs (95% CIs) of 1.14 (1.06, 1.22) and 1.12 (1.02, 1.22) per 5 µg/m3 increase in PM2.5, and 1.10 (1.04, 1.16) and 1.09 (1.02, 1.16) per 10 µg/m3 increase in NO2. Positive associations persisted for both incidence and mortality at low pollution levels with similar magnitude. CONCLUSIONS: We found similarly elevated risks of lung cancer incidence and mortality in association with residential exposure to PM2.5, NO2 and BC in meta-analyses of four European administrative cohorts, which persisted at low pollution levels.

Long-term exposure to elemental components of fine particulate matter and all-natural and cause-specific mortality in a Danish nationwide administrative cohort study.

BACKGROUND: Fine particulate matter (PM2.5) is a well-recognized risk factor for premature death. However, evidence on which PM2.5 components are most relevant is unclear. METHODS: We evaluated the associations between mortality and long-term exposure to eight PM2.5 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 PM2.5 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 PM2.5 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 PM2.5 components for different causes of death, with K and Si seeming to be most consistently associated with mortality in Denmark.

Association between exposure to multiple air pollutants, transportation noise and cause-specific mortality in adults in Switzerland.

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 PM2.5, PM2.5 components (Cu, Fe, S and Zn), NO2, black carbon (BC) and ozone (O3) 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 PM2.5 components were associated with natural mortality, with hazard ratios (95% confidence intervals) of 1.026 (1.015, 1.038) per 5 µg/m3 PM2.5, 1.050 (1.041, 1.059) per 10 µg/m3 NO2, 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. NO2, BC, Cu, Fe and noise were consistently associated with CVD and respiratory mortality, whereas PM2.5 was only associated with CVD mortality. Natural mortality associations persisted < 20 µg/m3 for PM2.5 and NO2, < 1.5 10-5/m BC and < 53 dB Lden total transportation noise. The O3 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 NO2, BC and transportation noise.

Residential green space and mental health-related prescription medication sales: An ecological study in Belgium.

BACKGROUND: Residential green space has been associated with mental health benefits, but how such associations vary with green space types is insufficiently known. OBJECTIVE: We aimed to investigate associations between types and quantities of green space and sales of mood disorder medication in Belgium. METHODS: We used aggregated sales data of psycholeptics and psychoanaleptics prescribed to adults from 2006 to 2014. Generalized mixed effects models were used to investigate associations between relative covers of woodland, low-green, grassland, and garden, and average annual medication sales. Models were adjusted for socio-economic background variables, urban-rural differences, and administrative region, and included random effects of latitude and longitude. RESULTS: Urban census tracts were associated with 9-10% higher medication sales. In nationwide models, a 10% increase in relative cover of woodland, garden, and grass was associated with a 1-2% decrease in medication sales. The same association was found for low green but only for men. In stratified models, a 10% increase in relative cover of any green space type in urban census tracts was associated with a decrease of medication sales by 1-3%. In rural census tracts, no protective associations between green space and mood disorder medication sales were observed, with the exception of relative woodland cover for women (-1%), and low green was associated with higher medication sales (+6-7%). CONCLUSIONS: Taken together, these results suggest that living in green environments may be beneficial for adult mental health. Woodland exposure seemed the most beneficial, but the amount of green space was more important than the type. Results underline the importance of conserving green space in our living environment, for the conservation of biodiversity and for human health.

Long-term exposure to residential greenness and neurodegenerative disease mortality among older adults: a 13-year follow-up cohort study.

BACKGROUND: Living in greener areas is associated with slower cognitive decline and reduced dementia risk among older adults, but the evidence with neurodegenerative disease mortality is scarce. We studied the association between residential surrounding greenness and neurodegenerative disease mortality in older adults. METHODS: We used data from the 2001 Belgian census linked to mortality register data during 2001-2014. We included individuals aged 60 years or older and residing in the five largest Belgian urban areas at baseline (2001). Exposure to residential surrounding greenness was assessed using the 2006 Normalized Difference Vegetation Index (NDVI) within 500-m from residence. We considered all neurodegenerative diseases and four specific outcomes: Alzheimer's disease, vascular dementia, unspecified dementia, and Parkinson's disease. We fitted Cox proportional hazard models to obtain hazard ratios (HR) and 95% confidence intervals (CI) of the associations between one interquartile range (IQR) increment in surrounding greenness and neurodegenerative disease mortality outcomes, adjusted for census-based covariates. Furthermore, we evaluated the potential role of 2010 air pollution (PM2.5 and NO2) concentrations, and we explored effect modification by sociodemographic characteristics. RESULTS: From 1,134,502 individuals included at baseline, 6.1% died from neurodegenerative diseases during follow-up. After full adjustment, one IQR (0.22) increment of surrounding greenness was associated with a 4-5% reduction in premature mortality from all neurodegenerative diseases, Alzheimer's disease, vascular and unspecified dementia [e.g., for Alzheimer's disease mortality: HR 0.95 (95%CI: 0.93, 0.98)]. No association was found with Parkinson's disease mortality. Main associations remained for all neurodegenerative disease mortality when accounting for air pollution, but not for the majority of specific mortality outcomes. Associations were strongest in the lower educated and residents from most deprived neighbourhoods. CONCLUSIONS: Living near greener spaces may reduce the risk of neurodegenerative disease mortality among older adults, potentially independent from air pollution. Socioeconomically disadvantaged groups may experience the greatest beneficial effect.

Long-term exposure to air pollution and liver cancer incidence in six European cohorts.

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 (NO2 ), particulate matter with diameter <2.5 µm (PM2.5 ), black carbon (BC), warm-season ozone (O3 ), and eight elemental components of PM2.5 (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 NO2 (hazard ratio, 95% confidence interval: 1.17, 1.02-1.35 per 10 µg/m3 ), PM2.5 (1.12, 0.92-1.36 per 5 µg/m3 ), and BC (1.15, 1.00-1.33 per 0.5 10-5 /m) and liver cancer incidence. Associations with NO2 and BC persisted in two-pollutant models with PM2.5 . Most components of PM2.5 were associated with the risk of liver cancer, with the strongest associations for sulfur and vanadium, which were robust to adjustment for PM2.5 or NO2 . Our study suggests that ambient air pollution may increase the risk of liver cancer, even at concentrations below current EU standards.

Long-term exposure to low-level air pollution and incidence of asthma: the ELAPSE project.

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 (PM2.5), nitrogen dioxide (NO2) 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 PM2.5, 1.17 (95% CI 1.10-1.25) per 10 µg·m-3 for NO2 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 PM2.5 and NO2. NO2 and BC estimates remained unchanged in two-pollutant models with PM2.5, whereas PM2.5 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.

Long-term exposure to fine particle elemental components and lung cancer incidence in the ELAPSE pooled cohort.

BACKGROUND: An association between long-term exposure to fine particulate matter (PM2.5) and lung cancer has been established in previous studies. PM2.5 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 PM2.5 and lung cancer incidence. METHODS: We pooled seven cohorts from across Europe and assigned exposure estimates for eight components of PM2.5 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/m3 PM2.5 K, 1.09 (95% CI 1.02, 1.15) per 1 ng/m3 PM2.5 Ni, 1.22 (95% CI 1.11, 1.35) per 200 ng/m3 PM2.5 S, and 1.07 (95% CI 1.02, 1.12) per 200 ng/m3 PM2.5 V. Effect estimates were largely unaffected by adjustment for nitrogen dioxide (NO2). After adjustment for PM2.5 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 PM2.5 components may prove helpful in future lung cancer prevention strategies.

Mortality and Morbidity Effects of Long-Term Exposure to Low-Level PM2.5, BC, NO2, and O3: An Analysis of European Cohorts in the ELAPSE Project.

INTRODUCTION: Epidemiological cohort studies have consistently found associations between long-term exposure to outdoor air pollution and a range of morbidity and mortality endpoints. Recent evaluations by the World Health Organization and the Global Burden of Disease study have suggested that these associations may be nonlinear and may persist at very low concentrations. Studies conducted in North America in particular have suggested that associations with mortality persisted at concentrations of particulate matter with an aerodynamic diameter of less than 2.5 µm (PM2.5) well below current air quality standards and guidelines. The uncertainty about the shape of the concentration-response function at the low end of the concentration distribution, related to the scarcity of observations in the lowest range, was the basis of the current project. Previous studies have focused on PM2.5, but increasingly associations with nitrogen dioxide (NO2) are being reported, particularly in studies that accounted for the fine spatial scale variation of NO2. Very few studies have evaluated the effects of long-term exposure to low concentrations of ozone (O3). Health effects of black carbon (BC), representing primary combustion particles, have not been studied in most large cohort studies of PM2.5. Cohort studies assessing health effects of particle composition, including elements from nontailpipe traffic emissions (iron, copper, and zinc) and secondary aerosol (sulfur) have been few in number and reported inconsistent results. The overall objective of our study was to investigate the shape of the relationship between long-term exposure to four pollutants (PM2.5, NO2, BC, and O3) and four broad health effect categories using a number of different methods to characterize the concentration-response function (i.e., linear, nonlinear, or threshold). The four health effect categories were (1) natural- and cause-specific mortality including cardiovascular and nonmalignant as well as malignant respiratory and diabetes mortality; and morbidity measured as (2) coronary and cerebrovascular events; (3) lung cancer incidence; and (4) asthma and chronic obstructive pulmonary disease (COPD) incidence. We additionally assessed health effects of PM2.5 composition, specifically the copper, iron, zinc, and sulfur content of PM2,5. METHODS: We focused on analyses of health effects of air pollutants at low concentrations, defined as less than current European Union (EU) Limit Values, U.S. Environmental Protection Agency (U.S. EPA), National Ambient Air Quality Standards (NAAQS), and/or World Health Organization (WHO) Air Quality Guideline values for PM2.5, NO2, and O3. We address the health effects at low air pollution levels by performing new analyses within selected cohorts of the ESCAPE study (European Study of Cohorts for Air Pollution Effects; Beelen et al. 2014a) and within seven very large European administrative cohorts. By combining well-characterized ESCAPE cohorts and large administrative cohorts in one study the strengths and weaknesses of each approach can be addressed. The large administrative cohorts are more representative of national or citywide populations, have higher statistical power, and can efficiently control for area-level confounders, but have fewer possibilities to control for individual-level confounders. The ESCAPE cohorts have detailed information on individual confounders, as well as country-specific information on area-level confounding. The data from the seven included ESCAPE cohorts and one additional non-ESCAPE cohort have been pooled and analyzed centrally. More than 300,000 adults were included in the pooled cohort from existing cohorts in Sweden, Denmark, Germany, the Netherlands, Austria, France, and Italy. Data from the administrative cohorts have been analyzed locally, without transfer to a central database. Privacy regulations prevented transfer of data from administrative cohorts to a central database. More than 28 million adults were included from national administrative cohorts in Belgium, Denmark, England, the Netherlands, Norway, and Switzerland as well as an administrative cohort in Rome, Italy. We developed central exposure assessment using Europewide hybrid land use regression (LUR) models, which incorporated European routine monitoring data for PM2.5, NO2, and O3, and ESCAPE monitoring data for BC and PM2.5 composition, land use, and traffic data supplemented with satellite observations and chemical transport model estimates. For all pollutants, we assessed exposure at a fine spatial scale, 100 × 100 m grids. These models have been applied to individual addresses of all cohorts including the administrative cohorts. In sensitivity analyses, we applied the PM2.5 models developed within the companion HEI-funded Canadian MAPLE study (Brauer et al. 2019) and O3 exposures on a larger spatial scale for comparison with previous studies. Identification of outcomes included linkage with mortality, cancer incidence, hospital discharge registries, and physician-based adjudication of cases. We analyzed natural-cause, cardiovascular, ischemic heart disease, stroke, diabetes, cardiometabolic, respiratory, and COPD mortality. We also analyzed lung cancer incidence, incidence of coronary and cerebrovascular events, and incidence of asthma and COPD (pooled cohort only). We applied the Cox proportional hazard model with increasing control for individual- and area-level covariates to analyze the associations between air pollution and mortality and/or morbidity for both the pooled cohort and the individual administrative cohorts. Age was used as the timescale because of evidence that this results in better adjustment for potential confounding by age. Censoring occurred at the time of the event of interest, death from other causes, emigration, loss to follow-up for other reasons, or at the end of follow-up, whichever came first. A priori we specified three confounder models, following the modeling methods of the ESCAPE study. Model 1 included only age (time axis), sex (as strata), and calendar year of enrollment. Model 2 added individual-level variables that were consistently available in the cohorts contributing to the pooled cohort or all variables available in the administrative cohorts, respectively. Model 3 further added area-level socioeconomic status (SES) variables. A priori model 3 was selected as the main model. All analyses in the pooled cohort were stratified by subcohort. All analyses in the administrative cohorts accounted for clustering of the data in neighborhoods by adjusting the variance of the effect estimates. The main exposure variable we analyzed was derived from the Europewide hybrid models based on 2010 monitoring data. Sensitivity analyses were conducted using earlier time periods, time-varying exposure analyses, local exposure models, and the PM2.5 models from the Canadian MAPLE project. We first specified linear single-pollutant models. Two-pollutant models were specified for all combinations of the four main pollutants. Two-pollutant models for particle composition were analyzed with PM2.5 and NO2 as the second pollutant. We then investigated the shape of the concentration-response function using natural splines with two, three, and four degrees of freedom; penalized splines with the degrees of freedom determined by the algorithm and shape-constrained health impact functions (SCHIF) using confounder model 3. Additionally, we specified linear models in subsets of the concentration range, defined by removing concentrations above a certain value from the analysis, such as for PM2.5 25 µg/m3 (EU limit value), 20, 15, 12 µg/m3 (U.S. EPA National Ambient Air Quality Standard), and 10 µg/m3 (WHO Air Quality Guideline value). Finally, threshold models were evaluated to investigate whether the associations persisted below specific concentration values. For PM2.5, we evaluated 10, 7.5, and 5 µg/m3 as potential thresholds. Performance of threshold models versus the corresponding no-threshold linear model were evaluated using the Akaike information criterion (AIC). RESULTS: In the pooled cohort, virtually all subjects in 2010 had PM2.5 and NO2 annual average exposures below the EU limit values (25 µg/m3 and 40 µg/m3, respectively). More than 50,000 had a residential PM2.5 exposure below the U.S. EPA NAAQS (12 µg/m3). More than 25,000 subjects had a residential PM2.5 exposure below the WHO guideline (10 µg/m3). We found significant positive associations between PM2.5, NO2, and BC and natural-cause, respiratory, cardiovascular, and diabetes mortality. In our main model, the hazard ratios (HRs) (95% [confidence interval] CI) were 1.13 (CI = 1.11, 1.16) for an increase of 5 µg/m3 PM2.5, 1.09 (CI = 1.07, 1.10) for an increase of 10 µg/m3 NO2, and 1.08 (CI = 1.06, 1.10) for an increase of 0.5 × 10-5/m BC for natural-cause mortality. The highest HRs were found for diabetes mortality. Associations with O3 were negative, both in the fine spatial scale of the main ELAPSE model and in large spatial scale exposure models. For PM2.5, NO2, and BC, we generally observed a supralinear association with steeper slopes at low exposures and no evidence of a concentration below which no association was found. Subset analyses further confirmed that these associations remained at low levels: below 10 µg/m3 for PM2.5 and 20 µg/m3 for NO2. HRs were similar to the full cohort HRs for subjects with exposures below the EU limit values for PM2.5 and NO2, the U.S. NAAQS values for PM2.5, and the WHO guidelines for PM2.5 and NO2. The mortality associations were robust to alternative specifications of exposure, including different time periods, PM2.5 from the MAPLE project, and estimates from the local ESCAPE model. Time-varying exposure natural spline analyses confirmed associations at low pollution levels. HRs in two-pollutant models were attenuated but remained elevated and statistically significant for PM2.5 and NO2. In two-pollutant models of PM2.5 and NO2 HRs for natural-cause mortality were 1.08 (CI = 1.05, 1.11) for PM2.5 and 1.05 (CI = 1.03, 1.07) for NO2. Associations with O3 were attenuated but remained negative in two-pollutant models with NO2, BC, and PM2.5. We found significant positive associations between PM2.5, NO2, and BC and incidence of stroke and asthma and COPD hospital admissions. Furthermore, NO2 was significantly related to acute coronary heart disease and PM2.5 was significantly related to lung cancer incidence. We generally observed linear to supralinear associations with no evidence of a threshold, with the exception of the association between NO2 and acute coronary heart disease, which was sublinear. Subset analyses documented that associations remained even with PM2.5 below 20 µg/m3 and possibly 12 µg/m3. Associations remained even when NO2 was below 30 µg/m3 and in some cases 20 µg/m3. In two-pollutant models, NO2 was most consistently associated with acute coronary heart disease, stroke, asthma, and COPD hospital admissions. PM2.5 was not associated with these outcomes in two-pollutant models with NO2. PM2.5 was the only pollutant that was associated with lung cancer incidence in two-pollutant models. Associations with O3 were negative though generally not statistically significant. In the administrative cohorts, virtually all subjects in 2010 had PM2.5 and NO2 annual average exposures below the EU limit values. More than 3.9 million subjects had a residential PM2.5 exposure below the U.S. EPA NAAQS (12 µg/m3) and more than 1.9 million had residential PM2.5 exposures below the WHO guideline (10 µg/m3). We found significant positive associations between PM2.5, NO2, and BC and natural-cause, respiratory, cardiovascular, and lung cancer mortality, with moderate to high heterogeneity between cohorts. We found positive but statistically nonsignificant associations with diabetes mortality. In our main model meta-analysis, the HRs (95% CI) for natural-cause mortality were 1.05 (CI = 1.02, 1.09) for an increase of 5 µg/m3 PM2.5, 1.04 (CI = 1.02, 1.07) for an increase of 10 µg/m3 NO2, and 1.04 (CI = 1.02, 1.06) for an increase of 0.5 × 10-5/m BC, and 0.95 (CI = 0.93, 0.98) for an increase of 10 µg/m3 O3. The shape of the concentration-response functions differed between cohorts, though the associations were generally linear to supralinear, with no indication of a level below which no associations were found. Subset analyses documented that these associations remained at low levels: below 10 µg/m3 for PM2.5 and 20 µg/m3 for NO2. BC and NO2 remained significantly associated with mortality in two-pollutant models with PM2.5 and O3. The PM2.5 HR attenuated to unity in a two-pollutant model with NO2. The negative O3 association was attenuated to unity and became nonsignificant. The mortality associations were robust to alternative specifications of exposure, including time-varying exposure analyses. Time-varying exposure natural spline analyses confirmed associations at low pollution levels. Effect estimates in the youngest participants (<65 years at baseline) were much larger than in the elderly (>65 years at baseline). Effect estimates obtained with the ELAPSE PM2.5 model did not differ from the MAPLE PM2.5 model on average, but in individual cohorts, substantial differences were found. CONCLUSIONS: Long-term exposure to PM2.5, NO2, and BC was positively associated with natural-cause and cause-specific mortality in the pooled cohort and the administrative cohorts. Associations were found well below current limit values and guidelines for PM2.5 and NO2. Associations tended to be supralinear, with steeper slopes at low exposures with no indication of a threshold. Two-pollutant models documented the importance of characterizing the ambient mixture with both NO2 and PM2.5. We mostly found negative associations with O3. In two-pollutant models with NO2, the negative associations with O3 were attenuated to essentially unity in the mortality analysis of the administrative cohorts and the incidence analyses in the pooled cohort. In the mortality analysis of the pooled cohort, significant negative associations with O3 remained in two-pollutant models. Long-term exposure to PM2.5, NO2, and BC was also positively associated with morbidity outcomes in the pooled cohort. For stroke, asthma, and COPD, positive associations were found for PM2.5, NO2, and BC. For acute coronary heart disease, an increased HR was observed for NO2. For lung cancer, an increased HR was found only for PM2.5. Associations mostly showed steeper slopes at low exposures with no indication of a threshold.

Development of Europe-Wide Models for Particle Elemental Composition Using Supervised Linear Regression and Random Forest.

We developed Europe-wide models of long-term exposure to eight elements (copper, iron, potassium, nickel, sulfur, silicon, vanadium, and zinc) in particulate matter with diameter <2.5 µm (PM2.5) using standardized measurements for one-year periods between October 2008 and April 2011 in 19 study areas across Europe, with supervised linear regression (SLR) and random forest (RF) algorithms. Potential predictor variables were obtained from satellites, chemical transport models, land-use, traffic, and industrial point source databases to represent different sources. Overall model performance across Europe was moderate to good for all elements with hold-out-validation R-squared ranging from 0.41 to 0.90. RF consistently outperformed SLR. Models explained within-area variation much less than the overall variation, with similar performance for RF and SLR. Maps proved a useful additional model evaluation tool. Models differed substantially between elements regarding major predictor variables, broadly reflecting known sources. Agreement between the two algorithm predictions was generally high at the overall European level and varied substantially at the national level. Applying the two models in epidemiological studies could lead to different associations with health. If both between- and within-area exposure variability are exploited, RF may be preferred. If only within-area variability is used, both methods should be interpreted equally.

Residential urban greenspace and hypertension: A comparative study in two European cities.

BACKGROUND: Living in green areas has been associated with several health benefits; however, the available evidence on such benefits for hypertension is still limited. This study aimed to investigate and compare the association between residential exposure to greenspace and hypertension in Barcelona, Spain and Brussels, Belgium. METHODS: This cross-sectional study was based on data from the 2016 Barcelona Health Interview Survey (HIS) (n = 3400) and the 2013 Belgian HIS (n = 2335). Both surveys were harmonized in terms of outcomes, confounders and exposure assessment. Residential exposure to greenspace was characterized as 1) surrounding greenspace (normalized difference vegetation index (NDVI) and modified soil-adjusted vegetation index 2 (MSAVI2)) across buffers of 100 m, 300 m, and 500 m; 2) surrounding green space across 300 m and 500 m buffers; and 3) Euclidean distance to the nearest green space. Our outcome was self-reported hypertension. We developed logistic regression models to evaluate the city-specific association between each greenspace measure and hypertension, adjusting for relevant covariates. RESULTS: One interquartile range (IQR) increase in residential distance to the nearest green space was associated with higher risk of hypertension in Barcelona [odds ratio (OR): 1.15; 95%CI 1.03-1.29 (IQR: 262.2)], but not in Brussels [OR: 0.95; 95%CI 0.77-1.17 (IQR: 215.2)]. Stratified analyses suggested stronger associations in older participants (≥65 years) for both cities. Findings for residential surrounding green space and greenspace were not conclusive. However, in Brussels, we found protective associations in older participants for both residential surrounding greenspace metrics [NDVI 300 m buffer OR: 0.51; 95%CI 0.32-0.81 (IQR: 0.21) and MSAVI2 300 m buffer OR: 0.51; 95%CI 0.32-0.83 (IQR: 0.18)]. We did not find any indication for the modification of our evaluated associations by sex and education level. CONCLUSION: Our study suggests that living closer to greenspace could be associated with lower risk of hypertension, particularly in older age. Future research is needed to replicate our findings in other settings and shed light on potential underlying mechanism(s).

Heat related mortality in the two largest Belgian urban areas: A time series analysis.

BACKGROUND: Summer temperatures are expected to increase and heat waves will occur more frequently, be longer, and be more intense as a result of global warming. A growing body of evidence indicates that increasing temperature and heatwaves are associated with excess mortality and therefore global heating may become a major public health threat. However, the heat-mortality relationship has been shown to be location-specific and differences could largely be explained by the most frequent temperature. So far, in Belgium there is little known regarding the heat-mortality relationship in the different urban areas. OBJECTIVES: The objective of this study is to assess the heat-mortality relationship in the two largest urban areas in Belgium, i.e. Antwerp and Brussels for the warm seasons from 2002 until 2011 taking into account the effect of air pollution. METHODS: The threshold in temperature above which mortality increases was determined using segmented regressions for both urban areas. The relationship between daily temperature and mortality above the threshold was investigated using a generalized estimated equation with Poisson distribution to finally determine the percentage of deaths attributable to the effect of heat. RESULTS: Although only 50 km apart, the heat-mortality curves for the two urban areas are different. More specifically, an increase in mortality occurs above a maximum temperature of 25.2 °C in Antwerp and 22.8 °C in Brussels. We estimated that above these thresholds, there is an increase in mortality of 4.9% per 1 °C in Antwerp and of 3.1% in Brussels. During the study period, 1.5% of the deaths in Antwerp and 3.5% of the deaths in Brussels can be attributed to the effect of heat. The thresholds differed considerably from the most frequent temperature, particularly in Antwerp. Adjustment for air pollution attenuated the effect of temperature on mortality and this attenuation was more pronounced when adjusting for ambient ozone. CONCLUSION: Our results show a significant effect of temperature on mortality above a city-specific threshold, both in Antwerp and in Brussels. These findings are important given the ongoing global warming. Recurrent, intense and longer episodes of high temperature and expected changes in air pollutant levels will have an important impact on health in urban areas.

Residential green space and medication sales for childhood asthma: A longitudinal ecological study in Belgium.

BACKGROUND: Living in green environments has been associated with various health benefits, but the evidence for positive effects on respiratory health in children is ambiguous. OBJECTIVE: To investigate if residential exposure to different types of green space is associated with childhood asthma prevalence in Belgium. METHODS: Asthma prevalence was estimated from sales data of reimbursed medication for obstructive airway disease (OAD) prescribed to children between 2010 and 2014, aggregated at census tract level (n = 1872) by sex and age group (6-12 and 13-18 years). Generalized log-linear mixed effects models with repeated measures were used to estimate effects of relative covers of forest, grassland and garden in the census tract of the residence on OAD medication sales. Models were adjusted for air pollution (PM10), housing quality and administrative region. RESULTS: Consistent associations between OAD medication sales and relative covers of grassland and garden were observed (unadjusted parameter estimates per IQR increase of relative cover, range across four strata: grassland, ß = 0.15-0.17; garden, ß = 0.13-0.17). The associations remained significant after adjusting for housing quality and chronic air pollution (adjusted parameter estimates per IQR increase of relative cover, range across four strata: grassland, ß = 0.10-0.14; garden, ß = 0.07-0.09). There was no association between OAD medication sales and forest cover. CONCLUSIONS: Based on aggregated data, we found that living in close proximity to areas with high grass cover (grasslands, but also residential gardens) may negatively impact child respiratory health. Potential allergic and non-allergic mechanisms that underlie this association include elevated exposure to grass pollen and fungi and reduced exposure to environmental biodiversity. Reducing the dominance of grass in public and private green space might be beneficial to reduce the childhood asthma burden and may simultaneously improve the ecological value of urban green space.

Does air pollution trigger suicide? A case-crossover analysis of suicide deaths over the life span.

In addition to underlying health disorders and socio-economic or community factors, air pollution may trigger suicide mortality. This study evaluates the association between short-term variation in air pollution and 10 years of suicide mortality in Belgium. In a bidirectional time-stratified case-crossover design, 20,533 suicide deaths registered between January 1st 2002 and December 31st 2011 were matched by temperature with control days from the same month and year. We used municipality-level air pollution [particulate matter (PM10) and O3 concentrations] data and meteorology data. We applied conditional logistic regression models adjusted for duration of sunshine and day of the week to obtain odds ratios (OR) and their 95% CI for an increase of 10 µg/m3 in pollutant concentrations over different lag periods (lag 0, 0-1, 0-2, 0-3, 0-4, 0-5, and 0-6 days). Effect modification by season and age was investigated by including interaction terms. We observed significant associations of PM10 and O3 with suicide during summer (OR ranging from 1.02 to 1.07, p-values <0.05). For O3, significant associations were also observed during spring and autumn. Age significantly modified the associations with PM10, with statistically significant associations observed only among 5-14 year old children (lag 0-6: OR = 1.45; 95% CI: 1.03-2.04) and ≥85 years old (e.g. lag 0-4: OR = 1.17; 95% CI: 1.06-1.29). Recent increases in outdoor air pollutants such as PM10 or O3 can trigger suicide, particularly during warm periods, even at concentrations below the European thresholds. Furthermore, PM10 may have strong trigger effects among children and elderly population.

Suicide mortality in Belgium at the beginning of the 21st century: differences according to migrant background.

Background: Suicidal behaviour has long been recognized to vary widely between countries. Yet, rates of suicidal behaviour do not only vary between, but also within countries. Gender and socioeconomic differences in suicidal behaviour are well established, but the literature on suicidal behaviour and migrants is sparse, particularly in Belgium. The present study maps out the occurrence of suicide mortality across three of the largest migrant groups (Italians, Turks and Moroccans) versus the native population in Belgium, and verifies whether this association persists after accounting for socioeconomic variables. Methods: Census-linked mortality follow-up data covering the period 2001­2011 were used to probe into suicide mortality. To compare absolute differences by migrant background, indirect standardisation analyses were carried out. To assess relative differences, Cox proportional hazards models were performed. Analyses were restricted to 18- to 64-year-olds. Results: Belgian men and women have the highest suicide mortality risk, persons of Moroccan/Turkish origin the lowest, and Italians are somewhere in between. When migration generation is considered, the risk is higher for second-generation groups compared to that of the first-generation. Accounting for socioeconomic determinants, the difference between the native population and the various nationality groups intensifies. Conclusion: Although the risk is generally lower for minorities compared to the majority population, the results across migration generations underscore minorities' increased vulnerability to suicide over time. Future research should focus on understanding the risks and protective factors of suicidal behaviour across different nationality groups. This way, tailored policy recommendations can be developed in order to tackle the burden of suicide.

Greenspace exposure and the retinal microvasculature in healthy adults across three European cities.

BACKGROUND: Emerging evidence points to the beneficial role of greenspace exposure in promoting cardiovascular health. Most studies have evaluated such associations with conventional cardiovascular endpoints such as mortality, morbidity, or macrovascular markers. In comparison, the microvasculature, a crucial compartment of the vascular system where early subclinical signs of cardiovascular problems appear, has not been studied in association with greenspace exposure. The current study assessed the association between surrounding greenness and microvascular status, as assessed by retinal vessel diameters. METHODS: This study included a sample of healthy adults (n = 114 and 18-65 years old) residing in three European cities [Antwerp (Belgium), Barcelona (Spain), and London (UK)]. The exposures to greenspace at the home and work/school locations were characterized as average surrounding greenness [normalized difference vegetation index (NDVI)] within buffers of 100 m, 300 m, and 500 m. The central retinal arteriolar equivalent (CRAE) and central retinal venular equivalent (CRVE) were calculated from fundus pictures taken at three different time points. We developed linear mixed-effect models to estimate the association of greenspace exposure with indicators of retinal microvasculature, adjusted for relevant individual and area-level covariates. RESULTS: We observed the most robust associations with CRVE. Higher levels of greenspace at work/school were associated with smaller retinal venules [(seasonal NDVI) 300m: 3.85, 95%CI -6.67,-1.03; 500m: 5.11, 95%CI -8.04, -2.18]. Findings for surrounding greenness and CRAE were not conclusive. CONCLUSION: Our study suggests an association of greenspace exposure with better microvascular status, specifically for retinal venules. Future research is needed to confirm our findings across different contextual settings.

Comparison of traditional Cox regression and causal modeling to investigate the association between long-term air pollution exposure and natural-cause mortality within European cohorts.

Most studies investigating the health effects of long-term exposure to air pollution used traditional regression models, although causal inference approaches have been proposed as alternative. However, few studies have applied causal models and comparisons with traditional methods are sparse. We therefore compared the associations between natural-cause mortality and exposure to fine particulate matter (PM2.5) and nitrogen dioxide (NO2) using traditional Cox and causal models in a large multicenter cohort setting. We analysed data from eight well-characterized cohorts (pooled cohort) and seven administrative cohorts from eleven European countries. Annual mean PM2.5 and NO2 from Europe-wide models were assigned to baseline residential addresses and dichotomized at selected cut-off values (PM2.5: 10, 12, 15 µg/m³; NO2: 20, 40 µg/m³). For each pollutant, we estimated the propensity score as the conditional likelihood of exposure given available covariates, and derived corresponding inverse-probability weights (IPW). We applied Cox proportional hazards models i) adjusting for all covariates ("traditional Cox") and ii) weighting by IPW ("causal model"). Of 325,367 and 28,063,809 participants in the pooled and administrative cohorts, 47,131 and 3,580,264 died from natural causes, respectively. For PM2.5 above vs. below 12 µg/m³, the hazard ratios (HRs) of natural-cause mortality were 1.17 (95% CI 1.13-1.21) and 1.15 (1.11-1.19) for the traditional and causal models in the pooled cohort, and 1.03 (1.01-1.06) and 1.02 (0.97-1.09) in the administrative cohorts. For NO2 above vs below 20 µg/m³, the HRs were 1.12 (1.09-1.14) and 1.07 (1.05-1.09) for the pooled and 1.06 (95% CI 1.03-1.08) and 1.05 (1.02-1.07) for the administrative cohorts. In conclusion, we observed mostly consistent associations between long-term air pollution exposure and natural-cause mortality with both approaches, though estimates partly differed in individual cohorts with no systematic pattern. The application of multiple modelling methods might help to improve causal inference. 299 of 300 words.

Long-Term Exposure to Low-Level PM2.5 and Mortality: Investigation of Heterogeneity by Harmonizing Analyses in Large Cohort Studies in Canada, United States, and Europe.

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

Long-term exposure to objective and perceived residential greenness and diabetes mortality: A census-based cohort study.

BACKGROUND: Residing close to green spaces might reduce diabetes mellitus (DM) risk; however, evidence for diabetes mortality is limited. Moreover, individual and neighbourhood social factors may determine DM risk. Exposure to green spaces may also depend on socioeconomic position (SEP). This study examined the associations between residential greenness and diabetes-related mortality, and the role of the social environment in these associations. METHODS: We used the 2001 Belgian census linked to mortality register data for the period 2001-2014. We included individuals aged 40-79 years old and residing in the five largest Belgian urban areas at baseline. Exposure to residential greenness was assessed with surrounding greenness using the Normalized Difference Vegetation Index (NDVI) within 500-m of residence (objective indicator), and perceived neighbourhood greenness (subjective indicator). We conducted mixed-effects Cox proportional hazards models to obtain hazard ratios (HR) for diabetes-related mortality per interquartile range (IQR) increments of residential greenness. We assessed effect modification by social factors through stratification. RESULTS: From 2,309,236 individuals included at baseline, 1.2% died from DM during follow-up. Both residential greenness indicators were inversely associated with diabetes-related mortality after adjustment for individual social factors. After controlling for neighbourhood SEP, the beneficial association with surrounding greenness disappeared [HR 1.02 (95%CI:0.99,1.06)], but persisted with perceived neighbourhood greenness [HR 0.93 (95%CI:0.91,0.95)]. After stratification the inverse associations with perceived neighbourhood greenness were strongest for women, the lowest educated, and individuals residing in least deprived neighbourhoods. CONCLUSIONS: Our findings suggest that an overall positive perception of neighbourhood green spaces reduces independently the risk of diabetes-related mortality, regardless of the neighbourhood social environment. Nevertheless, neighbourhood SEP may be a strong confounder in the associations between diabetes-related mortality and greenness indicators derived from satellite images. Perception factors not captured by objective measurements of green spaces are potentially relevant in the association with DM, especially among disadvantaged groups.

Residential Exposure to Urban Trees and Medication Sales for Mood Disorders and Cardiovascular Disease in Brussels, Belgium: An Ecological Study.

BACKGROUND: The available evidence for positive associations between urban trees and human health is mixed, partly because the assessment of exposure to trees is often imprecise because of, for instance, exclusion of trees in private areas and the lack of three-dimensional (3D) exposure indicators (e.g., crown volume). OBJECTIVES: We aimed to quantify all trees and relevant 3D structural traits in Brussels (Belgium) and to investigate associations between the number of trees, tree traits, and sales of medication commonly prescribed for mood disorders and cardiovascular disease. METHODS: We developed a workflow to automatically isolate all individual trees from airborne light detection and ranging (LiDAR) data collected in 2012. Trait data were subsequently extracted for 309,757 trees in 604 census tracts. We used the average annual age-standardized rate of medication sales in Brussels for the period 2006 to 2014, calculated from reimbursement information on medication prescribed to adults (19-64 years of age). The medication sales data were provided by sex at the census tract level. Generalized log-linear models were used to investigate associations between the number of trees, the crown volume, tree structural variation, and medication sales. Models were run separately for mood disorder and cardiovascular medication and for men and women. All models were adjusted for indicators of area-level socioeconomic status. RESULTS: Single-factor models showed that higher stem densities and higher crown volumes are both associated with lower medication sales, but opposing associations emerged in multifactor models. Higher crown volume [an increase by one interquartile range (IQR) of 1.4×104 m³/ha] was associated with 34% lower mood disorder medication sales [women, ß=-0.341 (95% CI: -0.379, -0.303); men, ß=-0.340 (95% CI: -0.378, -0.303)] and with 21-25% lower cardiovascular medication sales [women, ß=-0.214 (95% CI: -0.246, -0.182); men, ß=-0.252 (95% CI: -0.285, -0.219)]. Conversely, a higher stem density (an increase by one IQR of 21.8 trees/ha) was associated with 28-32% higher mood disorder medication sales [women, ß=0.322 (95% CI: 0.284, 0.361); men, ß=0.281 (95% CI: 0.243, 0.319)] and with 20-24% higher cardiovascular medication sales [women, ß=0.202 (95% CI: 0.169, 0.236); men, ß=0.240 (95% CI: 0.206, 0.273)]. DISCUSSION: We found a trade-off between the number of trees and the crown volumes of those trees for human health benefits in an urban environment. Our results demonstrate that conserving large trees in urban environments may not only support conservation of biodiversity but also human health. https://doi.org/10.1289/EHP9924.