Childhood exposure to outdoor air pollution in different microenvironments and cognitive and fine motor function in children from six European cohorts.

BACKGROUND: Exposure to air pollution during childhood has been linked with adverse effects on cognitive development and motor function. However, limited research has been done on the associations of air pollution exposure in different microenvironments such as home, school, or while commuting with these outcomes. OBJECTIVE: To analyze the association between childhood air pollution exposure in different microenvironments and cognitive and fine motor function from six European birth cohorts. METHODS: We included 1301 children from six European birth cohorts aged 6-11 years from the HELIX project. Average outdoor air pollutants concentrations (NO2, PM2.5) were estimated using land use regression models for different microenvironments (home, school, and commute), for 1-year before the outcome assessment. Attentional function, cognitive flexibility, non-verbal intelligence, and fine motor function were assessed using the Attention Network Test, Trail Making Test A and B, Raven Colored Progressive Matrices test, and the Finger Tapping test, respectively. Adjusted linear regressions models were run to determine the association between each air pollutant from each microenvironment on each outcome. RESULTS: In pooled analysis we observed high correlation (rs = 0.9) between air pollution exposures levels at home and school. However, the cohort-by-cohort analysis revealed correlations ranging from low to moderate. Air pollution exposure levels while commuting were higher than at home or school. Exposure to air pollution in the different microenvironments was not associated with working memory, attentional function, non-verbal intelligence, and fine motor function. Results remained consistently null in random-effects meta-analysis. CONCLUSIONS: No association was observed between outdoor air pollution exposure in different microenvironments (home, school, commute) and cognitive and fine motor function in children from six European birth cohorts. Future research should include a more detailed exposure assessment, considering personal measurements and time spent in different microenvironments.

Associations between combined urban and lifestyle factors and respiratory health in European children.

INTRODUCTION: Previous studies identified some environmental and lifestyle factors independently associated with children respiratory health, but few focused on exposure mixture effects. This study aimed at identifying, in pregnancy and in childhood, combined urban and lifestyle environment profiles associated with respiratory health in children. METHODS: This study is based on the European Human Early-Life Exposome (HELIX) project, combining six birth cohorts. Associations between profiles of pregnancy (38 exposures) and childhood (84 exposures) urban and lifestyle factors, identified by clustering analysis, and respiratory health were estimated by regression models adjusted for confounders. RESULTS: Among the 1033 included children (mean ± standard-deviation (SD) age: 8.2 ± 1.6 years old, 47% girls) the mean ± SD forced expiratory volume in 1s (FEV1) and forced vital capacity (FVC) were 99 ± 13% and 101 ± 14%, respectively, and 12%, 12% and 24% reported ever-asthma, wheezing and rhinitis, respectively. Four profiles of pregnancy exposures and four profiles of childhood exposures were identified. Compared to the reference childhood exposure profile (low exposures), two exposure profiles were associated with lower levels of FEV1. One profile was characterized by few natural spaces in the surroundings and high exposure to the built environment and road traffic. The second profile was characterized by high exposure to meteorological factors and low levels of all other exposures and was also associated with an increased risk of ever-asthma and wheezing. A pregnancy exposure profile characterized by high exposure levels to all risk factors, but a healthy maternal lifestyle, was associated with a lower risk of wheezing and rhinitis in children, compared to the reference pregnancy profile (low exposures). CONCLUSION: This comprehensive approach revealed pregnancy and childhood profiles of urban and lifestyle exposures associated with lung function and/or respiratory conditions in children. Our findings highlight the need to pursue the study of combined exposures to improve prevention strategies for multifactorial diseases such as asthma.

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.

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.

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.

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.

Long-term exposure to air pollution and mortality in a Danish nationwide administrative cohort study: Beyond mortality from cardiopulmonary disease and lung cancer.

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 (PM2.5), nitrogen dioxide (NO2), 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 PM2.5 (mean: 12.4 µg/m3), NO2 (20.3 µg/m3), and/or BC (1.0 × 10-5/m) was statistically significantly associated with all studied mortality outcomes except CKD. A 5 µg/m3 increase in PM2.5 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/m3) 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 PM2.5, NO2, and/or BC in Denmark were associated with mortality beyond cardiorespiratory diseases, including diabetes, dementia, psychiatric disorders, asthma, and ALRI.

Long-term exposure to low ambient air pollution concentrations and mortality among 28 million people: results from seven large European cohorts within the ELAPSE project.

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 (PM2·5), nitrogen dioxide (NO2), black carbon, and tropospheric warm-season ozone (O3) 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 PM2·5, NO2, and black carbon, with a hazard ratio (HR) of 1·053 (95% CI 1·021-1·085) per 5 µg/m3 increment in PM2·5, 1·044 (1·019-1·069) per 10 µg/m3 NO2, and 1·039 (1·018-1·059) per 0·5 × 10-5/m black carbon. Associations with PM2·5, NO2, and black carbon were slightly weaker for cardiovascular mortality, similar for non-malignant respiratory mortality, and stronger for lung cancer mortality. Warm-season O3 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 PM2·5 (10 µg/m3) and NO2 (40 µg/m3) were 1·078 (1·046-1·111) per 5 µg/m3 PM2·5 and 1·049 (1·024-1·075) per 10 µg/m3 NO2. 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 PM2·5 and NO2 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.

Variability in the association between long-term exposure to ambient air pollution and mortality by exposure assessment method and covariate adjustment: A census-based country-wide cohort study.

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 (PM2.5), nitrogen dioxide (NO2), black carbon (BC) and ozone (O3) 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/m3 increase for NO2 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/m3 increase for PM2.5 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.

Long-term exposure to fine particle elemental components and mortality in Europe: Results from six European administrative cohorts within the ELAPSE project.

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 (PM2.5) 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 PM2.5 total mass or nitrogen dioxide (NO2) 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/m3 Cu; 1.069 (1.031, 1.108) per 100 ng/m3 Fe; 1.039 (1.018, 1.062) per 50 ng/m3 K; 1.024 (1.006, 1.043) per 1 ng/m3 Ni; 1.036 (1.016, 1.057) per 200 ng/m3 S; 1.152 (1.048, 1.266) per 100 ng/m3 Si; 1.020 (1.006, 1.034) per 2 ng/m3 V]. Only K and Si were robust to PM2.5 or NO2 adjustment [pooled HRs (95% CI) per 50 ng/m3 in K: 1.025 (1.008, 1.044), 1.020 (0.999, 1.042) and per 100 ng/m3 in Si: 1.121 (1.039, 1.209), 1.068 (1.022, 1.117) adjusted for PM2.5 and NO2 correspondingly]. Our findings indicate an association of natural mortality with most components, which was reduced after adjustment for PM2.5 and especially NO2.

Long-term exposure to low-level ambient air pollution and incidence of stroke and coronary heart disease: a pooled analysis of six European cohorts within the ELAPSE project.

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 (PM2·5), nitrogen dioxide (NO2), black carbon, and warm-season ozone (O3) 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 PM2·5 (hazard ratio 1·10 [95% CI 1·01-1·21] per 5 µg/m3 increase), NO2 (1·08 [1·04-1·12] per 10 µg/m3 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 NO2 (1·04 [1·01-1·07]). Warm-season O3 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 PM2·5 and NO2 remained elevated even when restricting analyses to participants exposed to pollutant concentrations lower than the EU limit values of 25 µg/m3 for PM2·5 and 40 µg/m3 for NO2. 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.

Long term exposure to low level air pollution and mortality in eight European cohorts within the ELAPSE project: pooled analysis.

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

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 Natural and Cause-Specific Mortality-a Pooled Analysis of Eight European Cohorts within the ELAPSE Project.

BACKGROUND: Inconsistent associations between long-term exposure to particles with an aerodynamic diameter ≤2.5 µm [fine particulate matter (PM2.5)] components and mortality have been reported, partly related to challenges in exposure assessment. OBJECTIVES: We investigated the associations between long-term exposure to PM2.5 elemental components and mortality in a large pooled European cohort; to compare health effects of PM2.5 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 PM2.5 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 PM2.5 mass and nitrogen dioxide (NO2) 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 PM2.5 and NO2. 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/m3, adjusting for PM2.5 mass. Associations with cause-specific mortality were less consistent in two-pollutant models. CONCLUSION: Long-term exposure to V in PM2.5 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.

Tinnitus and associations with chronic pain: The population-based Tromsø Study (2015-2016).

Tinnitus and pain have many similarities. Both are subjective sensations that may turn chronic, they are often accompanied by hypersensitivity in their respective sensory system, and overlapping brain changes have been observed. Since no population study has examined the empirical association between chronic pain and tinnitus, the present study aimed to explore the relationship in a general adult population. We used data from the seventh survey of the Tromsø Study (2015-2016). Participants (aged ≥40) responded to questions about pain and tinnitus. Using multiple logistic regression, we analysed the adjusted relationship between chronic pain and tinnitus in the full sample (n = 19,039), using several tinnitus definitions ranging from tinnitus >5 minutes within the past 12 months (broadest definition) to at least weekly and highly bothersome tinnitus (strictest definition). We also analysed relationships between number of body regions with pain, pain intensity and bothering, and tinnitus >5 minutes, among participants with chronic pain (n = 11,589). We found an association between chronic pain and tinnitus that was present irrespective of tinnitus definition, but was stronger with more bothersome tinnitus. With chronic pain, the odds of tinnitus >5 minutes was 64% higher, while odds of at least weekly, highly bothersome tinnitus was 144% higher than without chronic pain. Among participants with chronic pain, the number of pain regions was the pain variable most strongly associated with tinnitus >5 minutes (OR = 1.17 (95% CI: 1.14-1.20) for an increase of one region), whereas the other pain variables (intensity and bothering) showed weaker associations. All chronic pain variables had significant interactions with age, with the strongest associations for the youngest individuals (40-54 years). Our findings support the existence of an association between chronic pain and tinnitus and emphasises the importance of examining for comorbid pain in tinnitus patients to provide a more comprehensive treatment of tinnitus.

Modeling multi-level survival data in multi-center epidemiological cohort studies: Applications from the ELAPSE project.

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 (PM2.5 and NO2) 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.

Comparison of associations between mortality and air pollution exposure estimated with a hybrid, a land-use regression and a dispersion model.

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 NO2, PM2.5 and BC exposure estimates based on two stochastic models (Dutch LUR, European-wide hybrid) and deterministic Dutch dispersion models. RESULTS: Spatial variability of PM2.5 and BC exposure was smaller for LUR compared to hybrid and dispersion models. NO2 exposure variability was similar for the three methods. Pearson correlations between hybrid, LUR and dispersion modeled NO2 and BC ranged from 0.72 to 0.83; correlations for PM2.5 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/m3 for hybrid modeled NO2, a HR of 1.003 (95% CI: 0.993, 1.013) per 10 µg/m3 for LUR modeled NO2 and a HR of 1.015 (95% CI: 1.005, 1.024) per 10 µg/m3 for dispersion modeled NO2. 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.

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 forPM2.5 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.

Long-term exposure to low-level air pollution and incidence of chronic obstructive pulmonary disease: The ELAPSE project.

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 (PM2.5), nitrogen dioxide (NO2), 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/m3 for PM2.5, 1.11 (1.06, 1.16) per 10 µg/m3 for NO2, and 1.11 (1.06, 1.15) per 0.5 10-5m-1 for BC. Associations persisted in subset participants with PM2.5 or NO2 levels below current EU and US limit values and WHO guidelines, with no evidence for a threshold. HRs for NO2 and BC remained unchanged in two-pollutant models with PM2.5, whereas the HR for PM2.5 was attenuated to unity with NO2 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 NO2 and BC may be the most relevant.

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.