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BACKGROUND: Studies across the globe generally reported increased mortality risks associated with particulate matter with aerodynamic diameter ≤2.5 μm (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. [ABSTRACT FROM AUTHOR]

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 (PM 2.5 ) 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 PM 2.5 , but increasingly associations with nitrogen dioxide (NO 2 ) are being reported, particularly in studies that accounted for the fine spatial scale variation of NO 2 . Very few studies have evaluated the effects of long-term exposure to low concentrations of ozone (O 3 ). Health effects of black carbon (BC), representing primary combustion particles, have not been studied in most large cohort studies of PM 2.5 . 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 (PM 2.5 , NO 2 , BC, and O 3 ) 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 PM 2.5 composition, specifically the copper, iron, zinc, and sulfur content of PM 2,5 ., 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 PM 2.5 , NO 2 , and O 3 . 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 PM 2.5 , NO 2 , and O 3 , and ESCAPE monitoring data for BC and PM 2.5 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 PM 2.5 models developed within the companion HEI-funded Canadian MAPLE study (Brauer et al. 2019) and O 3 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 PM 2.5 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 PM 2.5 and NO 2 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 PM 2.5 25 μg/m 3 (EU limit value), 20, 15, 12 μg/m 3 (U.S. EPA National Ambient Air Quality Standard), and 10 μg/m 3 (WHO Air Quality Guideline value). Finally, threshold models were evaluated to investigate whether the associations persisted below specific concentration values. For PM 2.5 , we evaluated 10, 7.5, and 5 μg/m 3 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 PM 2.5 and NO 2 annual average exposures below the EU limit values (25 μg/m 3 and 40 μg/m 3 , respectively). More than 50,000 had a residential PM 2.5 exposure below the U.S. EPA NAAQS (12 μg/m 3 ). More than 25,000 subjects had a residential PM 2.5 exposure below the WHO guideline (10 μg/m 3 ). We found significant positive associations between PM 2.5 , NO 2 , 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/m 3 PM 2.5 , 1.09 (CI = 1.07, 1.10) for an increase of 10 μg/m 3 NO 2 , 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 O 3 were negative, both in the fine spatial scale of the main ELAPSE model and in large spatial scale exposure models. For PM 2.5 , NO 2 , 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/m 3 for PM 2.5 and 20 μg/m 3 for NO 2 . HRs were similar to the full cohort HRs for subjects with exposures below the EU limit values for PM 2.5 and NO 2 , the U.S. NAAQS values for PM 2.5 , and the WHO guidelines for PM 2.5 and NO 2 . The mortality associations were robust to alternative specifications of exposure, including different time periods, PM 2.5 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 PM 2.5 and NO 2 . In two-pollutant models of PM 2.5 and NO 2 HRs for natural-cause mortality were 1.08 (CI = 1.05, 1.11) for PM 2.5 and 1.05 (CI = 1.03, 1.07) for NO 2 . Associations with O 3 were attenuated but remained negative in two-pollutant models with NO 2 , BC, and PM 2.5 . We found significant positive associations between PM 2.5 , NO 2 , and BC and incidence of stroke and asthma and COPD hospital admissions. Furthermore, NO 2 was significantly related to acute coronary heart disease and PM 2.5 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 NO 2 and acute coronary heart disease, which was sublinear. Subset analyses documented that associations remained even with PM 2.5 below 20 μg/m 3 and possibly 12 μg/m 3 . Associations remained even when NO 2 was below 30 μg/m 3 and in some cases 20 μg/m 3 . In two-pollutant models, NO 2 was most consistently associated with acute coronary heart disease, stroke, asthma, and COPD hospital admissions. PM 2.5 was not associated with these outcomes in two-pollutant models with NO 2 . PM 2.5 was the only pollutant that was associated with lung cancer incidence in two-pollutant models. Associations with O 3 were negative though generally not statistically significant. In the administrative cohorts, virtually all subjects in 2010 had PM 2.5 and NO 2 annual average exposures below the EU limit values. More than 3.9 million subjects had a residential PM 2.5 exposure below the U.S. EPA NAAQS (12 μg/m 3 ) and more than 1.9 million had residential PM 2.5 exposures below the WHO guideline (10 μg/m 3 ). We found significant positive associations between PM 2.5 , NO 2 , 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/m 3 PM 2.5 , 1.04 (CI = 1.02, 1.07) for an increase of 10 μg/m 3 NO 2 , 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/m 3 O 3 . 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/m 3 for PM 2.5 and 20 μg/m 3 for NO 2 . BC and NO 2 remained significantly associated with mortality in two-pollutant models with PM 2.5 and O 3 . The PM 2.5 HR attenuated to unity in a two-pollutant model with NO 2 . The negative O 3 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 PM 2.5 model did not differ from the MAPLE PM 2.5 model on average, but in individual cohorts, substantial differences were found., Conclusions: Long-term exposure to PM 2.5 , NO 2 , 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 PM 2.5 and NO 2 . 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 NO 2 and PM 2.5 . We mostly found negative associations with O 3 . In two-pollutant models with NO 2 , the negative associations with O 3 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 O 3 remained in two-pollutant models. Long-term exposure to PM 2.5 , NO 2 , and BC was also positively associated with morbidity outcomes in the pooled cohort. For stroke, asthma, and COPD, positive associations were found for PM 2.5 , NO 2 , and BC. For acute coronary heart disease, an increased HR was observed for NO 2 . For lung cancer, an increased HR was found only for PM 2.5 . Associations mostly showed steeper slopes at low exposures with no indication of a threshold., (© 2021 Health Effects Institute. All rights reserved.)