Long-term exposure to air pollution and incidence of gastric and the upper aerodigestive tract cancers in a pooled European cohort: The ELAPSE project

Air pollution has been shown to significantly impact human health including cancer. Gastric and upper aerodigestive tract (UADT) cancers are common and increased risk has been associated with smoking and occupational exposures. However, the association with air pollution remains unclear. We pooled European subcohorts (N = 287,576 participants for gastric and N = 297,406 for UADT analyses) and investigated the association between residential exposure to fine particles (PM2.5), nitrogen dioxide (NO2), black carbon (BC) and ozone in the warm season (O3w) with gastric and UADT cancer. We applied Cox proportional hazards models adjusting for potential confounders at the individual and area-level. During 5,305,133 and 5,434,843 person-years, 872 gastric and 1139 UADT incident cancer cases were observed, respectively. For gastric cancer, we found no association with PM2.5, NO2 and BC while for UADT the hazard ratios (95% confidence interval) were 1.15 (95% CI: 1.00-1.33) per 5 μg/m3 increase in PM2.5, 1.19 (1.08-1.30) per 10 μg/m3 increase in NO2, 1.14 (1.04-1.26) per 0.5 × 10-5 m-1 increase in BC and 0.81 (0.72-0.92) per 10 μg/m3 increase in O3w. We found no association between long-term ambient air pollution exposure and incidence of gastric cancer, while for long-term exposure to PM2.5, NO2 and BC increased incidence of UADT cancer was observed.

Long-term exposure to air pollution and chronic kidney disease-associated mortality - results from the pooled cohort of the European multicentre ELAPSE-study

Despite the known link between air pollution and cause-specific mortality, its relation to chronic kidney disease (CKD)-associated mortality is understudied. Therefore, we investigated the association between long-term exposure to air pollution and CKD-related mortality in a large multicentre population-based European cohort. Cohort data were linked to local mortality registry data. CKD-death was defined as ICD10 codes N18-N19 or corresponding ICD9 codes. Mean annual exposure at participant's home address was determined with fine spatial resolution exposure models for nitrogen dioxide (NO2), black carbon (BC), ozone (O3), particulate matter ≤2.5μm (PM2.5) and several elemental constituents of PM2.5. Cox regression models were adjusted for age, sex, cohort, calendar year of recruitment, smoking status, marital status, employment status and neighbourhood mean income. Over a mean follow-up time of 20.4 years, 313 of 289 564 persons died from CKD. Associations were positive for PM2.5 (hazard ratio (HR) with 95% confidence interval (CI) of 1.31 (1.03-1.66) per 5μg/m3, BC (1.26 (1.03-1.53) per 0.5×10- 5/m), NO2 (1.13 (0.93-1.38) per 10μg/m3) and inverse for O3 (0.71 (0.54-0.93) per 10μg/m3). Results were robust to further covariate adjustment. Exclusion of the largest sub-cohort contributing 226 cases, led to null associations. Among the elemental constituents, Cu, Fe, K, Ni, S and Zn, representing different sources including traffic, biomass and oil burning and secondary pollutants, were associated with CKD-related mortality. In conclusion, our results suggest an association between air pollution from different sources and CKD-related mortality.

Impact of anthropogenic emission control in reducing future PM2.5 concentrations and the related oxidative potential across different regions of China

Affected by both future anthropogenic emissions and climate change, future prediction of PM2.5 and its Oxidative Potential (OP) distribution is a significant challenge, especially in developing countries like China. To overcome this challenge, we estimated historical and future PM2.5 concentrations and associated OP using the Danish Eulerian Hemispheric Model (DEHM) system with meteorological input from WRF weather forecast model. Considering different future socio-economic pathways and emission scenario assumptions, we quantified how the contribution from various anthropogenic emission sectors will change under these scenarios. Results show that compared to the CESM_SSP2-4.5_CLE scenario (based on moderate radiative forcing and Current Legislation Emission), the CESM_SSP1-2.6_MFR scenario (based on sustainability development and Maximum Feasible Reductions) is projected to yield greater environmental and health benefits in the future. Under the CESM_SSP1-2.6_MFR scenario, annual average PM2.5 concentrations (OP) are expected to decrease to 30 (0.8 nmolmin-1m-3) in almost all regions by 2030, which will be 65 % (67 %) lower than that in 2010. From a long-term perspective, it is anticipated that OP in the Fen-Wei Plain region will experience the maximum reduction (82.6 %) from 2010 to 2049. Largely benefiting from the effective control of PM2.5 in the region, it has decreased by 82.1 %. Crucially, once emission reduction measures reach a certain level (in 2040), further reductions become less significant. This study also emphasized the significant role of secondary aerosol formation and biomass-burning sources in influencing OP during both historical and future periods. In different scenarios, the reduction range of OP from 2010 to 2049 is estimated to be between 71 % and 85 % by controlling precursor emissions involved in secondary aerosol formation and emissions from biomass burning. Results indicate that strengthening the control of anthropogenic emissions in various regions are key to achieving air quality targets and safeguarding human health in the future.

Monthly average air pollution models using geographically weighted regression in Europe from 2000 to 2019

Detailed spatial models of monthly air pollution levels at a very fine spatial resolution (25 m) can help facilitate studies to explore critical time-windows of exposure at intermediate term. Seasonal changes in air pollution may affect both levels and spatial patterns of air pollution across Europe. We built Europe-wide land-use regression (LUR) models to estimate monthly concentrations of regulated air pollutants (NO2, O3, PM10 and PM2.5) between 2000 and 2019. Monthly average concentrations were collected from routine monitoring stations. Including both monthly-fixed and -varying spatial variables, we used supervised linear regression (SLR) to select predictors and geographically weighted regression (GWR) to estimate spatially-varying regression coefficients for each month. Model performance was assessed with 5-fold cross-validation (CV). We also compared the performance of the monthly LUR models with monthly adjusted concentrations. Results revealed significant monthly variations in both estimates and model structure, particularly for O3, PM10, and PM2.5. The 5-fold CV showed generally good performance of the monthly GWR models across months and years (5-fold CV R2: 0.31-0.66 for NO2, 0.4-0.79 for O3, 0.4-0.78 for PM10, 0.46-0.87 for PM2.5). Monthly GWR models slightly outperformed monthly-adjusted models. Correlations between monthly GWR model were generally moderate to high (Pearson correlation >0.6). In conclusion, we are the first to develop robust monthly LUR models for air pollution in Europe. These monthly LUR models, at a 25 m spatial resolution, enhance epidemiologists to better characterize Europe-wide intermediate-term health effects related to air pollution, facilitating investigations into critical exposure time windows in birth cohort studies.

Long-Term Exposure to Air Pollution and Risk of Acute Lower Respiratory Infections in the Danish Nurse Cohort

RATIONALE

Air pollution is a major risk factor for chronic cardiorespiratory diseases, affecting both the immune and respiratory systems' functionality, while the epidemiological evidence on respiratory infections remains sparse.

OBJECTIVE

We aimed to assess the association of long-term exposure to ambient air pollution with risk of developing new and recurrent ALRIs that characterized by persistently severe symptoms necessitating hospital contact, and identify the potential susceptible populations by socio-economic status (SES), smoking, physical activity status, overweight, and co-morbidity with chronic lung disease.

METHODS

We followed 23,912 female nurses from the Danish Nurse Cohort (> 44 years) from baseline (1993 or 1999) until 2018 for the incident and recurrent ALRIs defined by hospital contact (in-, outpatient, and emergency room) data from the National Patient Register. Residential annual mean concentrations of fine particulate matter (PM2.5), nitrogen dioxide (NO2), and black carbon (BC) were modelled using Danish DEHM/UBM/AirGIS system. We used marginal Cox models with time-varying exposures to assess the association of 3-year running-mean air pollution with incident and recurrent ALRIs and examine effect modification by age, socio-economic status (SES), smoking, physical activity, body mass index, and comorbidity with asthma or chronic obstructive pulmonary disease (COPD).

RESULTS

During a 21.3 years mean follow-up, 4,746 ALRIs were observed, of which 2,553 were incident. We observed strong positive associations of all three pollutants with incident ALRIs, with hazard ratios and 95% confidence intervals of 1.19 (1.08-1.31) per 2.5 µg/m3 for PM2.5, 1.17 (1.11-1.24) per 8.0 µg/m3 for NO2, and 1.09 (1.05-1.12) per 0.3 µg/m3 for BC, and slightly stronger associations with recurrent ALRIs. Associations were strongest in COPD patients and nurses with low physical activity.

CONCLUSION

Long-term exposure to air pollution at low levels was associated with risk of new and recurrent ALRIs, with COPD patients and physically inactive subjects most vulnerable. Primary Source of Funding: This study was supported by the Novo Nordisk Foundation Challenge Programme (NNF17OC0027812).

Ambient air pollution and hypertensive disorders of pregnancy in Rome

BACKGROUND

Ambient air pollution has been associated with hypertensive disorders of pregnancy (HDP), but few studies rely on assessment of fine-scale variation in air quality, specific subtypes and multi-pollutant exposures.

AIM

To study the impact of long-term exposure to individual and mixture of air pollutants on all and specific subtypes of HDP.

METHODS

We obtained data from 130,470 liveborn singleton pregnacies in Rome during 2014-2019. Spatiotemporal land-use random-forest models at 1 km spatial resolution assigned to the maternal residential addresses were used to estimate the exposure to particulate matter (PM2.5 and PM10), nitrogen dioxide (NO2), and ozone (O3).

RESULTS

For PM2.5, PM10 and NO2, there was suggestive evidence of increased risk of preeclampsia (PE, n = 442), but no evidence of increased risk for all subtypes of HDP (n = 2297) and gestational hypertension (GH, n = 1901). For instance, an interquartile range of 7.0 μg/m3 increase in PM2.5 exposure during the first trimester of pregnancy was associated with an odds ratio (OR) of 1.06 (95% confidence interval: 0.81, 1.39) and 1.04 (0.92, 1.17) after adjustment for NO2 and the corresponding results for a 15.7 μg/m3 increase in NO2 after adjustment for PM2.5 were 1.11 (0.92, 1.34) for PE and 0.83 (0.76, 0.90) for HDP. Increased risks for HDP and GH were suggested for O3 in single-pollutant models and for PM after adjustment for NO2, but all other associations were stable or attenuated in two-pollutant models.

CONCLUSIONS

The results of our study suggest that PM2.5, PM10 and NO2 increases the risk of PE and that these effects are robust to adjustment for O3 while the increased risks for GH and HDP suggested for O3 attenuated after adjustment for PM or NO2. Additional studies are needed to evaluate the effects of source-specific component of PM on subtypes as well as all types of HDP which would help to target preventive actions.

Lifetime exposure to air pollution and academic achievement: A nationwide cohort study in Denmark

Recent research suggests a link between air pollution and cognitive development in children, and studies on air pollution and academic achievement are emerging. We conducted a nationwide cohort study in Denmark to explore the associations between lifetime exposure to air pollution and academic performance in 9th grade. The study encompassed 785,312 children born in Denmark between 1989 and 2005, all of whom completed 9th-grade exit examinations. Using linear mixed models with a random intercept for each school, we assessed the relationship between 16 years of exposure to PM2.5, PM10, and gaseous pollutants and Grade Point Averages (GPA) in exit examinations, covering subjects such as Danish literature, Danish writing, English, mathematics, and natural sciences. The study revealed that a 5 µg/m3 increase in PM2.5 and PM10 was associated with a decrease of 0.99 (95 % Confidence Intervals: -1.05, -0.92) and 0.46 (-0.50, -0.41) in GPA, respectively. Notably, these negative associations were more pronounced in mathematics and natural sciences compared to language-related subjects. Additionally, girls and children with non-Danish mothers were found to be particularly susceptible to the adverse effects of air pollution exposure. These results underscore the potential long-term consequences of air pollution on academic achievement, emphasizing the significance of interventions that foster healthier environments for children's cognitive development.

Long-term exposure to several constituents and sources of PM2.5 is associated with incidence of upper aerodigestive tract cancers but not gastric cancer: Results from the large pooled European cohort of the ELAPSE project

It is unclear whether cancers of the upper aerodigestive tract (UADT) and gastric cancer are related to air pollution, due to few studies with inconsistent results. The effects of particulate matter (PM) may vary across locations due to different source contributions and related PM compositions, and it is not clear which PM constituents/sources are most relevant from a consideration of overall mass concentration alone. We therefore investigated the association of UADT and gastric cancers with PM2.5 elemental constituents and sources components indicative of different sources within a large multicentre population based epidemiological study. Cohorts with at least 10 cases per cohort led to ten and eight cohorts from five countries contributing to UADT- and gastric cancer analysis, respectively. Outcome ascertainment was based on cancer registry data or data of comparable quality. We assigned home address exposure to eight elemental constituents (Cu, Fe, K, Ni, S, Si, V and Zn) estimated from Europe-wide exposure models, and five source components identified by absolute principal component analysis (APCA). Cox regression models were run with age as time scale, stratified for sex and cohort and adjusted for relevant individual and neighbourhood level confounders. We observed 1139 UADT and 872 gastric cancer cases during a mean follow-up of 18.3 and 18.5 years, respectively. UADT cancer incidence was associated with all constituents except K in single element analyses. After adjustment for NO2, only Ni and V remained associated with UADT. Residual oil combustion and traffic source components were associated with UADT cancer persisting in the multiple source model. No associations were found for any of the elements or source components and gastric cancer incidence. Our results indicate an association of several PM constituents indicative of different sources with UADT but not gastric cancer incidence with the most robust evidence for traffic and residual oil combustion.

Long-term exposure to ambient air pollution and risk of leukemia and lymphoma in a pooled European cohort

Leukemia and lymphoma are the two most common forms of hematologic malignancy, and their etiology is largely unknown. Pathophysiological mechanisms suggest a possible association with air pollution, but little empirical evidence is available. We aimed to investigate the association between long-term residential exposure to outdoor air pollution and risk of leukemia and lymphoma. We pooled data from four cohorts from three European countries as part of the "Effects of Low-level Air Pollution: a Study in Europe" (ELAPSE) collaboration. We used Europe-wide land use regression models to assess annual mean concentrations of fine particulate matter (PM2.5), nitrogen dioxide (NO2), black carbon (BC) and ozone (O3) at residences. We also estimated concentrations of PM2.5 elemental components: copper (Cu), iron (Fe), zinc (Zn); sulfur (S); nickel (Ni), vanadium (V), silicon (Si) and potassium (K). We applied Cox proportional hazards models to investigate the associations. Among the study population of 247,436 individuals, 760 leukemia and 1122 lymphoma cases were diagnosed during 4,656,140 person-years of follow-up. The results showed a leukemia hazard ratio (HR) of 1.13 (95% confidence intervals [CI]: 1.01-1.26) per 10 μg/m3 NO2, which was robust in two-pollutant models and consistent across the four cohorts and according to smoking status. Sex-specific analyses suggested that this association was confined to the male population. Further, the results showed increased lymphoma HRs for PM2.5 (HR = 1.16; 95% CI: 1.02-1.34) and potassium content of PM2.5, which were consistent in two-pollutant models and according to sex. Our results suggest that air pollution at the residence may be associated with adult leukemia and lymphoma.

Concomitant exposure to air pollution, green space and noise, and risk of myocardial infarction: a cohort study from Denmark

AIMS

The three correlated environmental exposures (air pollution, road traffic noise, and green space) have all been associated with the risk of myocardial infarction (MI). The present study aimed to analyse their independent and cumulative association with MI.

METHODS AND RESULTS

In a cohort of all Danes aged 50 or older in the period 2005-17, 5-year time-weighted average exposure to fine particles (PM2.5), ultrafine particles, elemental carbon, nitrogen dioxide (NO2), and road traffic noise at the most and least exposed façades of residence was estimated. Green space around residences was estimated from land use maps. Cox proportional hazard models were used to estimate hazard ratios (HRs) and 95% confidence interval (CI), and cumulative risk indices (CRIs) were calculated. All expressed per interquartile range. Models were adjusted for both individual and neighbourhood-level socio-demographic covariates. The cohort included 1 964 702 persons. During follow-up, 71 285 developed MI. In single-exposure models, all exposures were associated with an increased risk of MI. In multi-pollutant analyses, an independent association with risk of MI was observed for PM2.5 (HR: 1.026; 95% CI: 1.002-1.050), noise at most exposed façade (HR: 1.024; 95% CI: 1.012-1.035), and lack of green space within 150 m of residence (HR: 1.018; 95% CI: 1.010-1.027). All three factors contributed significantly to the CRI (1.089; 95% CI: 1.076-1.101).

CONCLUSION

In a nationwide cohort study, air pollution, noise, and lack of green space were all independently associated with an increased risk of MI. The air pollutant PM2.5 was closest associated with MI risk.

Exposure to air pollution and risk of respiratory tract infections in the adult Danish population-a nationwide study

OBJECTIVES

The association between air pollution and risk of respiratory tract infection (RTI) in adults needs to be clarified in settings with low to moderate levels of air pollution. We investigated this in the Danish population between 2004 and 2016.

METHODS

We included 3 653 490 persons aged 18-64 years in a nested case-control study. Exposure was defined as the average daily concentration at the individual's residential address of CO, NOX, NO2, O3, SO2, NH3, PPM2.5, black carbon, organic carbon, mineral dust, sea salt, secondary inorganic aerosols, SO42-, NO3-, NH4+, secondary organic aerosols, PM2.5, and PM10 during a 3-month exposure window. RTIs were defined by hospitalization for RTIs. Incidence rate ratios (IRRs) and 95% CIs were estimated comparing highest with lowest decile of exposure using conditional logistic regression models.

RESULTS

In total, 188 439 incident cases of RTI were identified. Exposure to most air pollutants was positively associated with risk of RTI. For example, NO2 showed an IRR of 1.52 (CI: 1.48-1.55), and PM2.5 showed an IRR of 1.45 (CI: 1.40-1.50). In contrast, exposure to sea salt, PM10, NH3, and O3 was negatively associated with a risk of RTIs.

DISCUSSION

In this nationwide study comprising adults, exposure to air pollution was associated with risk of RTIs and subgroups hereof. Sea salt, PM10, NH3, and O3 may be proxies for rural areas, as the levels of these species in Denmark are higher near the western coastlines and/or in rural areas with fewer combustion sources.

Multiple myeloma risk in relation to long-term air pollution exposure - A pooled analysis of four European cohorts

BACKGROUND

Air pollution is a growing concern worldwide, with significant impacts on human health. Multiple myeloma is a type of blood cancer with increasing incidence. Studies have linked air pollution exposure to various types of cancer, including leukemia and lymphoma, however, the relationship with multiple myeloma incidence has not been extensively investigated.

METHODS

We pooled four European cohorts (N = 234,803) and assessed the association between residential exposure to nitrogen dioxide (NO2), fine particles (PM2.5), black carbon (BC), and ozone (O3) and multiple myeloma. We applied Cox proportional hazards models adjusting for potential confounders at the individual and area-level.

RESULTS

During 4,415,817 person-years of follow-up (average 18.8 years), we observed 404 cases of multiple myeloma. The results of the fully adjusted linear analyses showed hazard ratios (95% confidence interval) of 0.99 (0.84, 1.16) per 10 μg/m³ NO2, 1.04 (0.82, 1.33) per 5 μg/m³ PM2.5, 0.99 (0.84, 1.18) per 0.5 10-5 m-1 BCE, and 1.11 (0.87, 1.41) per 10 μg/m³ O3.

CONCLUSIONS

We did not observe an association between long-term ambient air pollution exposure and incidence of multiple myeloma.

Long-Term Exposure to AIR Pollution and COVID-19 Mortality and Morbidity in DENmark: Who Is Most Susceptible? (AIRCODEN)

INTRODUCTION

Early ecological studies have suggested a link between air pollution and Coronavirus Diseases 2019 (COVID-19); however, the evidence from individual-level prospective cohort studies is still sparse. Here, we have examined, in a general population, whether long-term exposure to air pollution is associated with the risk of contracting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and developing severe COVID-19, resulting in hospitalization or death and who is most susceptible. We also examined whether long-term exposure to air pollution is associated with hospitalization or death due to COVID-19 in those who have tested positive for SARS-CoV-2.

METHODS

We included all Danish residents 30 years or older who resided in Denmark on March 1, 2020. and followed them in the National COVID-19 Surveillance System until first positive test (incidence), COVID-19 hospitalization, or death until April 26, 2021. We estimated mean levels of nitrogen dioxide (NO2), particulate matter with an aerodynamic diameter <2.5 μm (PM2.5), black carbon (BC), and ozone (O3) at cohort participants' residence in 2019 by the Danish Eulerian Hemispheric Model/Urban Background Model. We used Cox proportional hazard models to estimate the associations of air pollutants with COVID-19 incidence, hospitalization, and mortality adjusting for age, sex, and socioeconomic status (SES) at the individual and area levels. We examined effect modification by age, sex, SES (education, income, wealth, employment), and comorbidities with cardiovascular disease, respiratory disease, acute lower respiratory infections, diabetes, lung cancer, and dementia. We used logistic regression to examine association of air pollutants with COVID-19-related hospitalization or death among SARS-CoV-2 positive patients, adjusting for age, sex, individual- and area-level SES.

RESULTS

Of 3,721,810 people, 138,742 were infected, 11,270 hospitalized, and 2,557 died from COVID-19 during 14 months of follow-up. We detected strong positive associations with COVID-19 incidence, with hazard ratio (HR) and 95% confidence interval (CI) of 1.10 (CI: 1.05-1.14) per 0.5-μg/m3 increase in PM2.5 and 1.18 (CI: 1.14-1.23) per 3.6-μg/m3 increase in NO2. For COVID-19 hospitalizations and for COVID-19 deaths, corresponding HRs and 95% CIs were 1.09 (CI: 1.01-1.17) and 1.19 (CI: 1.12-1.27), respectively for PM2.5, and 1.23 (CI: 1.04-1.44) and 1.18 (CI: 1.03-1.34), respectively for NO2. We also found strong positive and statistically significant associations with BC and negative associations with O3. Associations were strongest in those aged 65 years old or older, participants with the lowest SES, and patients with chronic cardiovascular, respiratory, metabolic, lung cancer, and neurodegenerative disease. Among 138,742 individuals who have tested positive for SARS-Cov-2, we detected positive association with COVID-19 hospitalizations (N = 11,270) with odds ratio and 95% CI of 1.04 (CI: 1.01- 1.08) per 0.5-μg/m3 increase in PM2.5 and 1.06 (CI: 1.01-1.12) per 3.6-μg/m3 increase in NO2, but no association with PM with an aerodynamic diameter <10 μm (PM10), BC, or O3, and no association between any of the pollutants and COVID-19 mortality (N = 2,557).

CONCLUSIONS

This large nationwide study provides strong new evidence in support of association between long-term exposure to air pollution and COVID-19.

Long-term exposure to low-level air pollution and greenness and mortality in Northern Europe. The Life-GAP project

BACKGROUND

Air pollution has been linked to mortality, but there are few studies examining the association with different exposure time windows spanning across several decades. The evidence for the effects of green space and mortality is contradictory.

OBJECTIVE

We investigated all-cause mortality in relation to exposure to particulate matter (PM2.5 and PM10), black carbon (BC), nitrogen dioxide (NO2), ozone (O3) and greenness (normalized difference vegetation index - NDVI) across different exposure time windows.

METHODS

The exposure assessment was based on a combination of the Danish Eulerian Hemispheric Model and the Urban Background Model for the years 1990, 2000 and 2010. The analysis included a complete case dataset with 9,135 participants from the third Respiratory Health in Northern Europe study (RHINE III), aged 40-65 years in 2010, with mortality follow-up to 2021. We performed Cox proportional hazard models, adjusting for potential confounders.

RESULTS

Altogether, 327 (3.6 %) persons died in the period 2010-2021. Increased exposures in 1990 of PM2.5, PM10, BC and NO2 were associated with increased all-cause mortality hazard ratios of 1.40 (95 % CI1.04-1.87 per 5 μg/m3), 1.33 (95 % CI: 1.02-1.74 per 10 μg/m3), 1.16 (95 % CI: 0.98-1.38 per 0.4 μg/m3) and 1.17 (95 % CI: 0.92-1.50 per 10 μg/m3), respectively. No statistically significant associations were observed between air pollution and mortality in other time windows. O3 showed an inverse association with mortality, while no association was observed between greenness and mortality. Adjusting for NDVI increased the hazard ratios for PM2.5, PM10, BC and NO2 exposures in 1990. We did not find significant interactions between greenness and air pollution metrics.

CONCLUSION

Long term exposure to even low levels of air pollution is associated with mortality. Opening up for a long latency period, our findings indicate that air pollution exposures over time may be even more harmful than anticipated.

Medium term moderate to low-level air pollution exposure is associated with higher C-reactive protein among healthy Danish blood donors

Air pollution is a significant contributor to the global burden of disease with a plethora of associated health effects such as pulmonary and systemic inflammation. C-reactive protein (CRP) is associated with a wide range of diseases and is associated with several exposures. Studies on the effect of air pollution exposure on CRP levels in low to moderate pollution settings have shown inconsistent results. In this cross-sectional study high sensitivity CRP measurements on 18,463 Danish blood donors were linked to modelled air pollution data for NOx, NO2, O3, CO, SO2, NH3, mineral dust, black carbon, organic carbon, sea salt, secondary inorganic aerosols and its components, primary PM2.5, secondary organic aerosols, total PM2.5, and total PM10 at their residential address over the previous month. Associations were analysed using ordered logistic regression with CRP quartile as individuals outcome and air pollution exposure as scaled deciles. Analyses were adjusted for health related and socioeconomic covariates using health questionnaires and Danish register data. Exposure to different air pollution components was generally associated with higher CRP (odds ratio estimates ranging from 1.11 to 1.67), while exposure to a few air pollution components was associated with lower CRP. For example, exposure to NO2 increased the odds of high CRP 1.32-fold (95%CI 1.16-1.49), while exposure to NH3 decreased the odds of high CRP 0.81-fold (95%CI 0.73-0.89). This large study among healthy individuals found air pollution exposure to be associated with increased levels of CRP even in a setting with low to moderate air pollution levels.

Long-term air pollution exposure and malignant intracranial tumours of the central nervous system: a pooled analysis of six European cohorts

BACKGROUND

Risk factors for malignant tumours of the central nervous system (CNS) are largely unknown.

METHODS

We pooled six European cohorts (N = 302,493) and assessed the association between residential exposure to nitrogen dioxide (NO2), fine particles (PM2.5), black carbon (BC), ozone (O3) and eight elemental components of PM2.5 (copper, iron, potassium, nickel, sulfur, silicon, vanadium, and zinc) and malignant intracranial CNS tumours defined according to the International Classification of Diseases ICD-9/ICD-10 codes 192.1/C70.0, 191.0-191.9/C71.0-C71.9, 192.0/C72.2-C72.5. We applied Cox proportional hazards models adjusting for potential confounders at the individual and area-level.

RESULTS

During 5,497,514 person-years of follow-up (average 18.2 years), we observed 623 malignant CNS tumours. The results of the fully adjusted linear analyses showed a hazard ratio (95% confidence interval) of 1.07 (0.95, 1.21) per 10 μg/m³ NO2, 1.17 (0.96, 1.41) per 5 μg/m³ PM2.5, 1.10 (0.97, 1.25) per 0.5 10-5m-1 BC, and 0.99 (0.84, 1.17) per 10 μg/m³ O3.

CONCLUSIONS

We observed indications of an association between exposure to NO2, PM2.5, and BC and tumours of the CNS. The PM elements were not consistently associated with CNS tumour incidence.

Exposure to long-term source-specific transportation noise and incident breast cancer: A pooled study of eight Nordic cohorts

BACKGROUND

Environmental noise is an important environmental exposure that can affect health. An association between transportation noise and breast cancer incidence has been suggested, although current evidence is limited. We investigated the pooled association between long-term exposure to transportation noise and breast cancer incidence.

METHODS

Pooled data from eight Nordic cohorts provided a study population of 111,492 women. Road, railway, and aircraft noise were modelled at residential addresses. Breast cancer incidence (all, estrogen receptor (ER) positive, and ER negative) was derived from cancer registries. Hazard ratios (HR) were estimated using Cox Proportional Hazards Models, adjusting main models for sociodemographic and lifestyle variables together with long-term exposure to air pollution.

RESULTS

A total of 93,859 women were included in the analyses, of whom 5,875 developed breast cancer. The median (5th-95th percentile) 5-year residential road traffic noise was 54.8 (40.0-67.8) dB Lden, and among those exposed, the median railway noise was 51.0 (41.2-65.8) dB Lden. We observed a pooled HR for breast cancer (95 % confidence interval (CI)) of 1.03 (0.99-1.06) per 10 dB increase in 5-year mean exposure to road traffic noise, and 1.03 (95 % CI: 0.96-1.11) for railway noise, after adjustment for lifestyle and sociodemographic covariates. HRs remained unchanged in analyses with further adjustment for PM2.5 and attenuated when adjusted for NO2 (HRs from 1.02 to 1.01), in analyses using the same sample. For aircraft noise, no association was observed. The associations did not vary by ER status for any noise source. In analyses using <60 dB as a cutoff, we found HRs of 1.08 (0.99-1.18) for road traffic and 1.19 (0.95-1.49) for railway noise.

CONCLUSIONS

We found weak associations between road and railway noise and breast cancer risk. More high-quality prospective studies are needed, particularly among those exposed to railway and aircraft noise before conclusions regarding noise as a risk factor for breast cancer can be made.

Concomitant exposure to air pollution, green space, and noise and risk of stroke: a cohort study from Denmark

Background

Air pollution, road traffic noise, and green space are correlated factors, associated with risk of stroke. We investigated their independent relationship with stroke in multi-exposure analyses and estimated their cumulative stroke burden.

Methods

For all persons, ≥50 years of age and living in Denmark from 2005 to 2017, we established complete address histories and estimated running 5-year mean exposure to fine particles (PM_2.5), ultrafine particles, elemental carbon, nitrogen dioxide (NO₂), and road traffic noise at the most, and least exposed façade. For air pollutants, we estimated total, and non-traffic contributions. Green space around the residence was estimated from land use maps. Hazard ratios (HR) and 95% confidence limits (CL) were estimated with Cox proportional hazards models and used to calculate cumulative risk indices (CRI). We adjusted for the individual and sociodemographic covariates available in our dataset (which did not include information about individual life styles and medical conditions).

Findings

The cohort accumulated 18,344,976 years of follow-up and 94,256 cases of stroke. All exposures were associated with risk of stroke in single pollutant models. In multi-pollutant analyses, only PM_2.5 (HR: 1.058, 95% CI: 1.040-1.075) and noise at most exposed façade (HR: 1.033, 95% CI: 1.024-1.042) were independently associated with a higher risk of stroke. Both noise and air pollution contributed substantially to the CRI (1.103, 95% CI: 1.092-1.114) in the model with noise, green space, and total PM_2.5 concentrations.

Interpretation

Environmental exposure to air pollution and noise were both independently associated with risk of stroke.

Funding

Health Effects Institute (HEI) (Assistance Award No. R-82811201).

Long-term exposure to low-level particulate air pollution and Parkinson's disease diagnosis - A Finnish register-based study

BACKGROUND

There is mixed evidence for an association between particulate matter air pollution and Parkinson's disease despite biological plausibility.

OBJECTIVES

We studied the association between particulate air pollution, its components and Parkinson's disease (PD) risk.

METHODS

We conducted a nested case-control study within the population of Finland using national registers. A total of 22,189 incident PD cases diagnosed between 1996 and 2015 were matched by age, sex and region with up to seven controls (n = 148,009) per case. Time weighted average air pollution exposure to particulate matter and its components was modelled at the residential addresses, accounting for move history, for the 16 years preceding diagnosis. Conditional logistic regression analysis was used to evaluate the association between air pollution and PD. Different exposure periods (6-16 years, 11-16 years, 5-10 years, 0-5 years) before the index date (date of PD diagnosis) were applied.

RESULTS

Time-weighted average exposures were relatively low at 12.1 ± 6.5 μg/m3 (mean ± SD) for PM10 and 7.7 ± 3.2 μg/m3 for PM2.5. No associations were found between PM2.5 or PM10 exposure 6-16 years before index date and PD (OR: 0.99; 95% CI: 0.96, 1.02; per IQR of 3.9 μg/m3 and OR: 0.99; 95% CI: 0.96, 1.01; per IQR of 7.8 μg/m3, respectively). However, inverse associations were observed for the same exposure period with black carbon (OR: 0.96; 95% CI: 0.93, 0.99; per IQR of 0.6 μg/m3), sulphate (OR: 0.79; 95% CI: 0.68, 0.92; per IQR of 1.2 μg/m3), secondary organic aerosols (OR: 0.86; 95% CI: 0.80, 0.93; per IQR of 0.1 μg/m3) and sea salt (OR: 0.92; 95% CI: 0.87, 0.98; per IQR of 0.1 μg/m3).

DISCUSSION

Low-level particulate matter air pollution was not associated with increased risk of incident PD in this Finnish nationwide population. The observed weak inverse associations with specific particle components should be investigated further.

Long-term exposure to residential transportation noise and mortality: A nationwide cohort study

Studies have indicated that transportation noise is associated with higher cardiovascular mortality, whereas evidence of noise as a risk factor for respiratory and cancer mortality is scarce and inconclusive. Also, knowledge on effects of low-level noise on mortality is very limited. We aimed to investigate associations between road and railway noise and natural-cause and cause-specific mortality in the Danish population. We estimated address-specific road and railway noise at the most (LdenMax) and least (LdenMin) exposed façades for all residential addresses in Denmark from 1990 to 2017 using high-quality exposure models. Using these data, we calculated 10-year time-weighted mean noise exposure for 2.6 million Danes aged >50 years, of whom 600,492 died from natural causes during a mean follow-up of 11.7 years. We analyzed data using Cox proportional hazards models with adjustment for individual and area-level sociodemographic variables and air pollution (PM_2.5 and NO₂). We found that a 10-year mean exposure to road LdenMax and road LdenMin per 10 dB were associated with hazard ratios (95% confidence intervals) of, respectively, 1.09 (1.09; 1.10) and 1.10 (1.10; 1.11) for natural-cause mortality, 1.09 (1.08; 1.10) and 1.09 (1.08; 1.10) for cardiovascular mortality, 1.13 (1.12; 1.14) and 1.17 (1.16; 1.19) for respiratory mortality and 1.03 (1.02; 1.03) and 1.06 (1.05; 1.07) for cancer mortality. For LdenMax, the associations followed linear exposure-response relationships from 35 dB to 60-<65 dB, after which the function levelled off. For LdenMin, exposure-response relationships were linear from 35 dB and up, with some levelling off at high noise levels for natural-cause and cardiovascular mortality. Railway noise did not seem associated with higher mortality in an exposure-response dependent manner. In conclusion, road traffic noise was associated with higher mortality and the increase in risk started well below the current World Health Organization guideline limit for road traffic noise of 53 dB.

Long-term exposure to air pollution and risk of SARS-CoV-2 infection and COVID-19 hospitalisation or death: Danish nationwide cohort study

BACKGROUND

Early ecological studies have suggested links between air pollution and risk of coronavirus disease 2019 (COVID-19), but evidence from individual-level cohort studies is still sparse. We examined whether long-term exposure to air pollution is associated with risk of COVID-19 and who is most susceptible.

METHODS

We followed 3 721 810 Danish residents aged ≥30 years on 1 March 2020 in the National COVID-19 Surveillance System until the date of first positive test (incidence), COVID-19 hospitalisation or death until 26 April 2021. We estimated residential annual mean particulate matter with diameter ≤2.5 μm (PM2.5), nitrogen dioxide (NO2), black carbon (BC) and ozone (O3) in 2019 by the Danish DEHM/UBM model, and used Cox proportional hazards regression models to estimate the associations of air pollutants with COVID-19 outcomes, adjusting for age, sex, individual- and area-level socioeconomic status, and population density.

RESULTS

138 742 individuals were infected, 11 270 were hospitalised and 2557 died from COVID-19 during 14 months. We detected associations of PM2.5 (per 0.53 μg·m-3) and NO2 (per 3.59 μg·m-3) with COVID-19 incidence (hazard ratio (HR) 1.10 (95% CI 1.05-1.14) and HR 1.18 (95% CI 1.14-1.23), respectively), hospitalisations (HR 1.09 (95% CI 1.01-1.17) and HR 1.19 (95% CI 1.12-1.27), respectively) and death (HR 1.23 (95% CI 1.04-1.44) and HR 1.18 (95% CI 1.03-1.34), respectively), which were strongest in the lowest socioeconomic groups and among patients with chronic respiratory, cardiometabolic and neurodegenerative diseases. We found positive associations with BC and negative associations with O3.

CONCLUSION

Long-term exposure to air pollution may contribute to increased risk of contracting severe acute respiratory syndrome coronavirus 2 infection as well as developing severe COVID-19 disease requiring hospitalisation or resulting in death.

Perspectives on environment and health research in Denmark

AIMS

We provide an overview of nationwide environmental data available for Denmark and its linkage potentials to individual-level records with the aim of promoting research on the potential impact of the local surrounding environment on human health.

BACKGROUND

Researchers in Denmark have unique opportunities for conducting large population-based studies treating the entire Danish population as one big, open and dynamic cohort based on nationally complete population and health registries. So far, most research in this area has utilised individual- and family-level information to study the clustering of disease in families, comorbidities, risk of, and prognosis after, disease onset, and social gradients in disease risk. Linking environmental data in time and space to individuals enables novel possibilities for studying the health effects of the social, built and physical environment.

METHODS

We describe the possible linkage between individuals and their local surrounding environment to establish the exposome - that is, the total environmental exposure of an individual over their life course.

CONCLUSIONS

The currently available nationwide longitudinal environmental data in Denmark constitutes a valuable and globally rare asset that can help explore the impact of the exposome on human health.

Early-Life Exposure to Ambient Air Pollution from Multiple Sources and Asthma Incidence in Children: A Nationwide Birth Cohort Study from Denmark

BACKGROUND

Ambient air pollution exposure has been associated with childhood asthma, but previous studies have primarily focused on prevalence of asthma and asthma-related outcomes and urban traffic-related exposures.

OBJECTIVE

We examined nationwide associations between pre- and postnatal exposure to ambient air pollution components and asthma incidence in children age 0-19 y.

METHODS

Asthma incidence was identified from hospital admission, emergency room, and outpatient contacts among all live-born singletons born in Denmark between 1998 and 2016. We linked registry data with monthly mean concentrations of particulate matter (PM) with aerodynamic diameter ≤2.5μm (PM2.5) and PM with aerodynamic diameter ≤10μm (PM10), nitrogen dioxide (NO2), nitrogen oxides, elemental carbon, and organic carbon (OC), sulfur dioxide, ozone, sulfate, nitrate, ammonium, secondary organic aerosols, and sea salt. Associations were estimated with Cox proportional hazard models using fixed prenatal exposure means and time-varying postnatal exposures.

RESULTS

Of the 1,060,154 children included, 6.1% had asthma during the mean follow-up period of 8.8 y. The risk of asthma increased with increasing prenatal exposure to all pollutants except for O3 and sea salt. We also observed increased risk after restriction to asthma after age 4 y, after additional adjustment for area-specific socioeconomic status, and for postnatal exposure to most pollutants. The hazard ratio (HR) associated with an interquartile range increase of 2.4 and 8.7 μg/m3 in prenatal exposure was 1.06 [95% confidence interval (CI): 1.04, 1.08] for PM2.5 and 1.04 (95% CI: 1.02, 1.05) for NO2, respectively. This association with PM2.5 was stable after adjustment for NO2, whereas it attenuated for NO2 to 1.01 (95% CI: 0.99, 1.03) after adjustment for PM2.5. For a 0.5-μg/m3 increase in prenatal OC exposure, for which biomass is an important source, the HR was 1.08 (95% CI: 1.06, 1.10), irrespective of adjustment for PM2.5.

DISCUSSION

These findings suggest that early-life exposure to ambient air pollution from multiple sources contributes to asthma development. https://doi.org/10.1289/EHP11539.

Source-Specific Air Pollution Including Ultrafine Particles and Risk of Myocardial Infarction: A Nationwide Cohort Study from Denmark

BACKGROUND

Air pollution is negatively associated with cardiovascular health. Impediments to efficient regulation include lack of knowledge about which sources of air pollution contributes most to health burden and few studies on effects of the potentially more potent ultrafine particles (UFP).

OBJECTIVE

The authors aimed to investigate myocardial infarction (MI) morbidity and specific types and sources of air pollution.

METHODS

We identified all persons living in Denmark in the period 2005-2017, age >50 y and never diagnosed with MI. We quantified 5-y running time-weighted mean concentrations of air pollution at residencies, both total and apportioned to traffic and nontraffic sources. We evaluated particulate matter (PM) with aerodynamic diameter ≤2.5μm (PM2.5), <0.1μm (UFP), elemental carbon (EC), and nitrogen dioxide (NO2). We used Cox proportional hazards models, with adjustment for time-varying exposures, and personal and area-level demographic and socioeconomic covariates from high-quality administrative registers.

RESULTS

In this nationwide cohort of 1,964,702 persons (with 18 million person-years of follow-up and 71,285 cases of MI), UFP and PM2.5 were associated with increased risk of MI with hazard ratios (HRs) per interquartile range (IQR) of 1.040 [95% confidence interval (CI): 1.025, 1.055] and 1.053 (95% CI: 1.035, 1.071), respectively. HRs per IQR of UFP and PM2.5 from nontraffic sources were similar to the total (1.034 and 1.051), whereas HRs for UFP and PM2.5 from traffic sources were smaller (1.011 and 1.011). The HR for EC from traffic sources was 1.013 (95% CI: 1.003, 1.023). NO2 from nontraffic sources was associated with MI (HR=1.048; 95% CI: 1.034, 1.062) but not from traffic sources. In general, nontraffic sources contributed more to total air pollution levels than national traffic sources.

CONCLUSIONS

PM2.5 and UFP from traffic and nontraffic sources were associated with increased risk of MI, with nontraffic sources being the dominant source of exposure and morbidity. https://doi.org/10.1289/EHP10556.

Long-term exposure to traffic noise and risk of incident colon cancer: A pooled study of eleven Nordic cohorts

Background Colon cancer incidence is rising globally, and factors pertaining to urbanization have been proposed involved in this development. Traffic noise may increase colon cancer risk by causing sleep disturbance and stress, thereby inducing known colon cancer risk-factors, e.g. obesity, diabetes, physical inactivity, and alcohol consumption, but few studies have examined this. Objectives The objective of this study was to investigate the association between traffic noise and colon cancer (all, proximal, distal) in a pooled population of 11 Nordic cohorts, totaling 155,203 persons. Methods We identified residential address history and estimated road, railway, and aircraft noise, as well as air pollution, for all addresses, using similar exposure models across cohorts. Colon cancer cases were identified through national registries. We analyzed data using Cox Proportional Hazards Models, adjusting main models for harmonized sociodemographic and lifestyle data. Results During follow-up (median 18.8 years), 2757 colon cancer cases developed. We found a hazard ratio (HR) of 1.05 (95% confidence interval (CI): 0.99-1.10) per 10-dB higher 5-year mean time-weighted road traffic noise. In sub-type analyses, the association seemed confined to distal colon cancer: HR 1.06 (95% CI: 0.98-1.14). Railway and aircraft noise was not associated with colon cancer, albeit there was some indication in sub-type analyses that railway noise may also be associated with distal colon cancer. In interaction-analyses, the association between road traffic noise and colon cancer was strongest among obese persons and those with high NO₂-exposure. Discussion A prominent study strength is the large population with harmonized data across eleven cohorts, and the complete address-history during follow-up. However, each cohort estimated noise independently, and only at the most exposed façade, which may introduce exposure misclassification. Despite this, the results of this pooled study suggest that traffic noise may be a risk factor for colon cancer, especially of distal origin.

Air pollution and stroke; effect modification by sociodemographic and environmental factors. A cohort study from Denmark

OBJECTIVES

Air pollution increases the risk of stroke, but the literature on identifying susceptible subgroups of populations is scarce and inconsistent. The aim of this study was to investigate if the association between air pollution and risk of stroke differed by sociodemographic factors, financial stress, comorbid conditions, and residential road traffic noise, population density and green space.

METHODS

We assessed long-term exposure to air pollution with ultrafine particles, PM_2.5, elemental carbon and NO₂ for a cohort of 1,971,246 Danes aged 50-85 years. During follow-up from 2005 to 2017, we identified 83,211 incident stroke cases. We used Cox proportional hazards model (relative risk) and Aalen additive hazards models (absolute risk) to estimate associations and confidence intervals (CI) between 5-year running means of air pollution at the residence and risk of stroke in population strata.

RESULTS

All four pollutants were associated with higher risk of stroke. The association between air pollution and stroke was strongest among individuals with comorbidities, with shorter education, lower income and being retired. The results also indicated stronger associations among individuals living in less populated areas, and with low noise levels and more green space around the residence. Estimates of absolute risk seemed better suited to detect such interactions than estimates of relative risk. For example for PM_2.5 the hazard ratio for stroke was 1.28 (95%CI: 1.22-1.34) and 1.26 (95%CI: 1.16-1.37) among those with mandatory and medium/long education respectively. The corresponding rate difference estimates per 100,000 person years were 568 (95%CI: 543-594) and 423(95%CI: 390-456) CONCLUSION: The associations between air pollution and risk of stroke was stronger among individuals of lower socioeconomic status or with pre-existing comorbid conditions. Absolute risk estimates were better suited to identify such effect modification.

Air pollution and myocardial infarction; effect modification by sociodemographic and environmental factors. A cohort study from Denmark

Air pollution is associated with increased risk of myocardial infarction (MI), but it is unresolved to what extent the association is modified by factors such as socioeconomic status, comorbidities, financial stress, residential green space, or road traffic noise. We formed a cohort of all (n = 1,964,702) Danes, aged 50-85 years, with 65,311 cases of MI during the followed-up period 2005-2017. For all participants we established residential five-year running average exposure to particulate matter <2.5  μm (PM_2.5), ultrafine particles (UFP, <0.1  μm), elemental carbon (EC) and nitrogen dioxide (NO₂). We evaluated risk in population strata, using Aalen additive hazards models to estimate absolute risk and Cox proportional hazards models to estimate relative risk of MI with 95% confidence intervals (CI). PM_2.5 and the other pollutant were associated with MI. Lower education and lower income were associated with higher absolute risks of MI from air pollution, whereas no clear effect modification was apparent for relative risk estimates. For example, 5 μg/m³ higher PM_2.5 was associated with HR for MI of 1.16 (95% CI: 1.10-1.22) among those with only mandatory education and 1.13 (95% CI: 1.03-1.24) among those with long education. The corresponding rate differences per 100,000 person years were 243 (95% CI: 216-271) and 358 (95% CI: 338-379), respectively. Higher level of comorbidity was consistently across all four pollutants associated with both higher absolute and relative risk of MI. In conclusion, people with comorbid conditions or of lower SES appeared more vulnerable to long-term exposure to air pollution and more cases of MI may be prevented by focused interventions in these groups.

'Source-specific' air pollution and risk of stroke in Denmark

BACKGROUND

Long-term air pollution is a risk factor for stroke. Which types and sources of air pollution contribute most to stroke in populations is unknown. We investigated whether risk of stroke differed by type and source of air pollution.

METHODS

We selected all persons aged >50 years and living in Denmark in the period 2005-17. We estimated running 5-year mean residential air-pollution concentrations of particulate matter <2.5 µm (PM2.5), ultrafine particles (UFP), elemental carbon (EC) and nitrogen dioxide (NO2). Pollutants were modelled as total air pollution from all emission sources, as well as apportioned into contributions from non-traffic and traffic sources. Hazard ratios (HRs) and CIs were estimated by using Cox proportional hazards models, adjusting for area-level and personal demographic and socio-economic covariates. We identified all primary strokes from hospital and mortality registers.

RESULTS

The cohort numbered 2 million people and 94 256 cases of stroke. Interquartile ranges (IQR) of air pollution were associated with risk of stroke with HRs of 1.077 (95% CI: 1.061-1.094, IQR: 1.85 µg/m3) for PM2.5, 1.039 (1.026-1.052, IQR: 4248 particles/cm3) for UFP, 1.009 (1.001-1.018, IQR: 0.28 µg/m3) for EC and 1.028 (1.017-1.040, IQR: 7.15 µg/m3) for NO2. Traffic sources contributed little to the total exposure. HRs associated with air pollution from traffic were close to the null, whereas non-traffic sources tended to be associated with HRs higher than those for total air pollution, e.g. for non-traffic PM2.5, the HR was 1.091 (1.074-1.108).

CONCLUSIONS

Air pollution, including UFP, was associated with risk of stroke. The risk appeared attributable mainly to air pollution from non-traffic sources.

Exposure to ambient air pollution and lipid levels and blood pressure in an adult, Danish cohort

BACKGROUND

Air pollution is a well-recognized risk factor for cardiovascular disease. However, the mechanistic pathways underlying the association are not completely understood. Hence, further studies are required to shed light on potential mechanisms, through which air pollution may affect the development from subclinical to clinical cardiovascular disease.

OBJECTIVES

To investigate associations between short-term exposure to air pollution and high-density lipoprotein (HDL), non-high density lipoprotein (non-HDL), systolic and diastolic blood pressure.

METHODS

The study was conducted among 32,851 Danes from the Diet, Cancer and Health - Next Generations cohort, who had a blood sample taken and blood pressure measured. We measured HDL and non-HDL in the blood samples. We modelled exposure to fine particulate matter (PM_2.5), ultrafine particles (UFP), elemental carbon (EC) and nitrogen dioxide (NO₂) in time-windows from 24 h up to 90 days before blood sampling. Pollutants were modelled as total air pollution from all sources, and apportioned into contributions from non-traffic and traffic sources. We analyzed data using linear and logistic regression, with adjustment for socio-economic and lifestyle factors.

RESULTS

Air pollution exposure over 24 h to 30 days was generally adversely associated with lipid profile and blood pressure, e.g. for 30-day UFP-exposure, adjusted β-estimates were: -0.025 (-0.043; -0.006) for HDL, 0.086 (0.042; 0.130) for non-HDL, 2.45 (1.70; 3.11) for systolic and 1.56 (1.07; 20.4) for diastolic blood pressure, per 10,000 particles/cm³. The strongest associations were found for the non-traffic components of air pollution, and among those who were overweight/obese.

DISCUSSION

In this large study of air pollution and lipid levels and blood pressure, we found that 24-h to 30-day PM_2.5, UFP, EC and NO₂ concentrations were generally adversely associated with lipid profile and blood pressure, two important cardiovascular risk factors. The study suggests potential pathways, through which air pollution could affect the development of cardiovascular disease.

Effects of Sociodemographic Characteristics, Comorbidity, and Coexposures on the Association between Air Pollution and Type 2 Diabetes: A Nationwide Cohort Study

BACKGROUND

Exposure to air pollution has been associated with a higher risk of type 2 diabetes (T2D), but studies investigating whether deprived groups are more susceptible to the harmful effects of air pollution are inconsistent.

OBJECTIVES

We aimed to investigate whether the association between air pollution and T2D differed according to sociodemographic characteristics, comorbidity, and coexposures.

METHODS

We estimated residential exposure to PM2.5, ultrafine particles (UFP), elemental carbon, and NO2 for all persons living in Denmark in the period 2005-2017. In total, 1.8 million persons 50-80 y of age were included for main analyses of whom 113,985 developed T2D during follow-up. We conducted additional analyses on 1.3 million persons age 35-50 y. Using Cox proportional hazards model (relative risk) and Aalens additive hazard model (absolute risk), we calculated associations between 5-y time-weighted running means of air pollution and T2D in strata of sociodemographic variables, comorbidity, population density, road traffic noise, and green space proximity.

RESULTS

Air pollution was associated with T2D, especially among people age 50-80 y, with hazard ratios of 1.17 [95% confidence interval (CI): 1.13, 1.21] per 5 μg/m3 PM2.5 and 1.16 (95% CI: 1.13, 1.19) per 10,000  UFP/cm3. In the age 50-80 y population, we found higher associations between air pollution and T2D among men in comparison with women, people with lower education vs. individuals with high education, people with medium income vs. those with low or high income, people cohabiting vs. those living alone, and people with comorbidities vs. those without comorbidities. We observed no marked changes according to occupation, population density, road noise, or surrounding greenness. In the age 35-50 y population, similar tendencies were observed, except in relation to sex and occupation, where we observed associations with air pollution only among women and blue-collar workers.

DISCUSSION

We found stronger associations between air pollution and T2D among people with existing comorbidities and weaker associations among people with high socioeconomic status in comparison with those with lower socioeconomic status. https://doi.org/10.1289/EHP11347.

Breast Cancer Incidence in Relation to Long-Term Low-Level Exposure to Air Pollution in the ELAPSE Pooled Cohort

BACKGROUND

Established risk factors for breast cancer include genetic disposition, reproductive factors, hormone therapy, and lifestyle-related factors such as alcohol consumption, physical inactivity, smoking, and obesity. More recently a role of environmental exposures, including air pollution, has also been suggested. The aim of this study, was to investigate the relationship between long-term air pollution exposure and breast cancer incidence.

METHODS

We conducted a pooled analysis among six European cohorts (n = 199,719) on the association between long-term residential levels of ambient nitrogen dioxide (NO2), fine particles (PM2.5), black carbon (BC), and ozone in the warm season (O3) and breast cancer incidence in women. The selected cohorts represented the lower range of air pollutant concentrations in Europe. We applied Cox proportional hazards models adjusting for potential confounders at the individual and area-level.

RESULTS

During 3,592,885 person-years of follow-up, we observed a total of 9,659 incident breast cancer cases. The results of the fully adjusted linear analyses showed a HR (95% confidence interval) of 1.03 (1.00-1.06) per 10 μg/m³ NO2, 1.06 (1.01-1.11) per 5 μg/m³ PM2.5, 1.03 (0.99-1.06) per 0.5 10-5 m-1 BC, and 0.98 (0.94-1.01) per 10 μg/m³ O3. The effect estimates were most pronounced in the group of middle-aged women (50-54 years) and among never smokers.

CONCLUSIONS

The results were in support of an association between especially PM2.5 and breast cancer.

IMPACT

The findings of this study suggest a role of exposure to NO2, PM2.5, and BC in development of breast cancer.

PM2.5 air pollution components and mortality in Denmark

BACKGROUND

Ambient fine particulate matter (PM_2.5) causes millions of deaths every year worldwide. Identification of the most harmful types of PM_2.5 would facilitate efficient prevention strategies.

OBJECTIVES

The aim of this study was to investigate associations between components of PM_2.5 and mortality in a nation-wide Danish population.

METHODS

Our study base was Danes born 1921-1985 and aged 30-85 years, who were followed up for mortality from 1991 to 2015. We included 678,465 natural cause mortality cases and selected five age, sex and calendar time matched controls to each case from the study base. We retrieved the address history of the study population from Danish registries and assessed five-year average concentrations of eight PM_2.5 components using deterministic Chemistry-Transport Models air pollution models. We estimated mortality rate ratios (MRRs) by conditional logistic regression and adjusted for socio-demographical factors at individual and neighborhood level.

RESULTS

Single pollutant models showed the strongest associations between natural cause mortality and an interquartile increase in sulfate particles (SO₄^--) (MRR: 1.123; 95 % CI: 1.100-1.147 per 1.5 µg/m³) and secondary organic aerosol (SOA) (MRR: 1.054; 95 % CI: 1.048-1.061 per 0.050 µg/m³). Two-pollutant models showed robust associations between SO₄^-- and SOA and natural cause mortality. Elemental carbon and mineral dust showed robust associations with higher respiratory and lung cancer mortality.

CONCLUSION

This nation-wide study found robust associations between natural cause mortality and SO₄^-- particles and SOA, which is in line with the results of previous studies. Elemental carbon and mineral dust showed robust associations with higher respiratory and lung cancer mortality.

Air pollution with NO2, PM2.5, and elemental carbon in relation to risk of breast cancer- a nationwide case-control study from Denmark

Air pollution with particulate matter is an established lung carcinogen. Studies have suggested an association with breast cancer, but the evidence is inconsistent.

METHODS

From nationwide registers, we identified all breast cancer cases (n = 55 745) in Denmark between 2000 and 2014. We matched one control for each case on age and year of birth. We used a multi-scale dispersion model to estimate outdoor concentrations of particulate matter <2.5 μm (PM_2.5), elemental carbon (EC) and nitrogen dioxide (NO₂) as time-weighted average over all addresses up to 20 years prior to diagnosis. We calculated odds ratios (OR) and 95% confidence intervals (CI) by conditional logistic regression with adjustment for marital status, educational level, occupational status, personal income, region of origin, medication and area-level socio-economic indicators.

RESULTS

A 10 μg/m³ higher PM_2.5 was associated with an OR for breast cancer of 1.21 (95% CI: 1.11-1.33). The corresponding ORs for EC (per 1 μg/m³) and NO₂ (per 10 μg/m³) were 1.03 (95% CI: 1.00-1.07) and 1.03 (95% CI: 1.01-1.06), respectively. In multi-pollutant models, the OR for PM_2.5 changed only little, whereas ORs for EC or NO₂ approached the null. In an analysis of persons below 55 years, PM_2.5 was associated with an OR of 1.32 (95% CI: 1.09-1.60) per 10 μg/m³ increase.

CONCLUSION

We found evidence of an association between the investigated air pollutants and breast cancer, especially PM_2.5. There were indications that the association differed by age at diagnosis. We were not able to include all potential confounders and thus, results should be interpreted with caution.

Prenatal exposure to ambient air pollution is associated with early life immune perturbations

BACKGROUND

Exposure to ambient air pollution has been linked to asthma, allergic rhinitis, and other inflammatory disorders, but little is known about the underlying mechanisms.

OBJECTIVE

We studied the potential mechanisms leading from prenatal ambient air pollution exposure to asthma and allergy in childhood.

METHODS

Long-term exposure to nitrogen dioxide (NO₂) as well as to particulate matter with a diameter of ≤2.5 and ≤10 μm (PM_2.5 and PM₁₀) were modeled at the residence level from conception to 6 years of age in 700 Danish children followed clinically for development of asthma and allergy. Nasal mucosal immune mediators were assessed at age 4 weeks and 6 years, inflammatory markers in blood at 6 months, and nasal epithelial DNA methylation and gene expression at age 6 years.

RESULTS

Higher prenatal air pollution exposure with NO₂, PM_2.5, and PM₁₀ was associated with an altered nasal mucosal immune profile at 4 weeks, conferring an increased odds ratio [95% confidence interval] of 2.68 [1.58, 4.62] for allergic sensitization and 2.63 [1.18, 5.81] for allergic rhinitis at age 6 years, and with an altered immune profile in blood at age 6 months conferring increased risk of asthma at age 6 years (1.80 [1.18, 2.76]). Prenatal exposure to ambient air pollution was not robustly associated with immune mediator, epithelial DNA methylation, or gene expression changes in nasal cells at age 6 years.

CONCLUSION

Prenatal exposure to ambient air pollution was associated with early life immune perturbations conferring risk of allergic rhinitis and asthma. These findings suggest potential mechanisms of prenatal exposure to ambient air pollution on the developing immune system.

Present-day and future PM2.5 and O3-related global and regional premature mortality in the EVAv6.0 health impact assessment model

We used the EVAv6.0 system to estimate the present (2015) and future (2015-2050) global PM_2.5 and O₃-related premature mortalities, using simulated surface concentrations from the GISS-E2.1-G Earth system model. The PM_2.5-related global premature mortality is estimated to be 4.3 and 4.4 million by the non-linear and linear models, respectively. Ischemic heart diseases are found to be the leading cause of PM_2.5-related premature deaths, contributing by 35% globally. Both long-term and short-term O₃-related premature deaths are estimated to be around 1 million, globally. Overall, PM_2.5 and O₃-related premature mortality leads to 5.3-5.4 million premature deaths, globally. The global burden of premature deaths is mainly driven by the Asian region, which in 2015 contributes by 75% of the total global premature deaths. An increase from 6.2% to 8% in the PM_2.5 relative risk as recommended by the WHO leads to an increase of PM_2.5-related premature mortality by 28%, to 5.7 million. Finally, bias correcting the simulated PM_2.5 concentrations in 2015 leads to an increase of up to 73% in the global PM_2.5-related premature mortality, leading to a total number of global premature deaths of up to 7.7 million, implying the necessity of bias correction to get more robust health burden estimates. PM_2.5 and O₃-related premature mortality in 2050 decreases by up to 57% and 18%, respectively, due to emission reductions alone. However, the projected increase and aging of the population leads to increases of premature mortality by up to a factor of 2, showing that the population exposed to air pollution is more important than the level of air pollutants, highlighting that the population dynamics should be considered when setting up health assessment systems.

Long-term air pollution exposure and Parkinson's disease mortality in a large pooled European cohort: An ELAPSE study

BACKGROUND

The link between exposure to ambient air pollution and mortality from cardiorespiratory diseases is well established, while evidence on neurodegenerative disorders including Parkinson's Disease (PD) remains limited.

OBJECTIVE

We examined the association between long-term exposure to ambient air pollution and PD mortality in seven European cohorts.

METHODS

Within the project 'Effects of Low-Level Air Pollution: A Study in Europe' (ELAPSE), we pooled data from seven cohorts among six European countries. Annual mean residential concentrations of fine particulate matter (PM_2.5), nitrogen dioxide (NO₂), black carbon (BC), and ozone (O₃), as well as 8 PM_2.5 components (copper, iron, potassium, nickel, sulphur, silicon, vanadium, zinc), for 2010 were estimated using Europe-wide hybrid land use regression models. PD mortality was defined as underlying cause of death being either PD, secondary Parkinsonism, or dementia in PD. We applied Cox proportional hazard models to investigate the associations between air pollution and PD mortality, adjusting for potential confounders.

RESULTS

Of 271,720 cohort participants, 381 died from PD during 19.7 years of follow-up. In single-pollutant analyses, we observed positive associations between PD mortality and PM_2.5 (hazard ratio per 5 µg/m³: 1.25; 95% confidence interval: 1.01-1.55), NO₂ (1.13; 0.95-1.34 per 10 µg/m³), and BC (1.12; 0.94-1.34 per 0.5 × 10^-5m^-1), and a negative association with O₃ (0.74; 0.58-0.94 per 10 µg/m³). Associations of PM_2.5, NO₂, and BC with PD mortality were linear without apparent lower thresholds. In two-pollutant models, associations with PM_2.5 remained robust when adjusted for NO₂ (1.24; 0.95-1.62) or BC (1.28; 0.96-1.71), whereas associations with NO₂ or BC attenuated to null. O₃ associations remained negative, but no longer statistically significant in models with PM_2.5. We detected suggestive positive associations with the potassium component of PM_2.5.

CONCLUSION

Long-term exposure to PM_2.5, at levels well below current EU air pollution limit values, may contribute to PD mortality.

Long-Term Exposure to Transportation Noise and Ischemic Heart Disease: A Pooled Analysis of Nine Scandinavian Cohorts

BACKGROUND

Transportation noise may induce cardiovascular disease, but the public health implications are unclear.

OBJECTIVES

The study aimed to assess exposure-response relationships for different transportation noise sources and ischemic heart disease (IHD), including subtypes.

METHODS

Pooled analyses were performed of nine cohorts from Denmark and Sweden, together including 132,801 subjects. Time-weighted long-term exposure to road, railway, and aircraft noise, as well as air pollution, was estimated based on residential histories. Hazard ratios (HRs) were calculated using Cox proportional hazards models following adjustment for lifestyle and socioeconomic risk factors.

RESULTS

A total of 22,459 incident cases of IHD were identified during follow-up from national patient and mortality registers, including 7,682 cases of myocardial infarction. The adjusted HR for IHD was 1.03 [95% confidence interval (CI) 1.00, 1.05] per 10 dB Lden for both road and railway noise exposure during 5 y prior to the event. Higher risks were indicated for IHD excluding angina pectoris cases, with HRs of 1.06 (95% CI: 1.03, 1.08) and 1.05 (95% CI: 1.01, 1.08) per 10 dB Lden for road and railway noise, respectively. Corresponding HRs for myocardial infarction were 1.02 (95% CI: 0.99, 1.05) and 1.04 (95% CI: 0.99, 1.08). Increased risks were observed for aircraft noise but without clear exposure-response relations. A threshold at around 55 dB Lden was suggested in the exposure-response relation for road traffic noise and IHD.

DISCUSSION

Exposure to road, railway, and aircraft noise in the prior 5 y was associated with an increased risk of IHD, particularly after exclusion of angina pectoris cases, which are less well identified in the registries. https://doi.org/10.1289/EHP10745.

Long term exposure to air pollution and kidney parenchyma cancer - Effects of low-level air pollution: a Study in Europe (ELAPSE)

BACKGROUND

Particulate matter (PM) is classified as a group 1 human carcinogen. Previous experimental studies suggest that particles in diesel exhaust induce oxidative stress, inflammation and DNA damage in kidney cells, but the evidence from population studies linking air pollution to kidney cancer is limited.

METHODS

We pooled six European cohorts (N = 302,493) to assess the association of residential exposure to fine particles (PM2.5), nitrogen dioxide (NO2), black carbon (BC), warm season ozone (O3) and eight elemental components of PM2.5 (copper, iron, potassium, nickel, sulfur, silicon, vanadium, and zinc) with cancer of the kidney parenchyma. The main exposure model was developed for year 2010. We defined kidney parenchyma cancer according to the International Classification of Diseases 9th and 10th Revision codes 189.0 and C64. We applied Cox proportional hazards models adjusting for potential confounders at the individual and area-level.

RESULTS

The participants were followed from baseline (1985-2005) to 2011-2015. A total of 847 cases occurred during 5,497,514 person-years of follow-up (average 18.2 years). Median (5-95%) exposure levels of NO2, PM2.5, BC and O3 were 24.1 μg/m3 (12.8-39.2), 15.3 μg/m3 (8.6-19.2), 1.6 10-5 m-1 (0.7-2.1), and 87.0 μg/m3 (70.3-97.4), respectively. The results of the fully adjusted linear analyses showed a hazard ratio (HR) of 1.03 (95% confidence interval [CI]: 0.92, 1.15) per 10 μg/m³ NO2, 1.04 (95% CI: 0.88, 1.21) per 5 μg/m³ PM2.5, 0.99 (95% CI: 0.89, 1.11) per 0.5 10-5 m-1 BCE, and 0.88 (95% CI: 0.76, 1.02) per 10 μg/m³ O3. We did not find associations between any of the elemental components of PM2.5 and cancer of the kidney parenchyma.

CONCLUSION

We did not observe an association between long-term ambient air pollution exposure and incidence of kidney parenchyma cancer.

Long-term exposure to air pollution and mortality from dementia, psychiatric disorders, and suicide in a large pooled European cohort: ELAPSE study

Ambient air pollution is an established risk factor for premature mortality from chronic cardiovascular, respiratory and metabolic diseases, while evidence on neurodegenerative diseases and psychiatric disorders remains limited. We examined the association between long-term exposure to air pollution and mortality from dementia, psychiatric disorders, and suicide in seven European cohorts. Within the multicenter project 'Effects of Low-Level Air Pollution: A Study in Europe' (ELAPSE), we pooled data from seven European cohorts from six countries. Based on the residential addresses, annual mean levels of fine particulate matter (PM_2.5), nitrogen dioxide (NO₂), black carbon (BC), ozone (O₃), and 8 PM_2.5 components were estimated using Europe-wide hybrid land-use regression models. We applied stratified Cox proportional hazard models to investigate the associations between air pollution and mortality from dementia, psychiatric disorders, and suicide. Of 271,720 participants, 900 died from dementia, 241 from psychiatric disorders, and 164 from suicide, during a mean follow-up of 19.7 years. In fully adjusted models, we observed positive associations of NO₂ (hazard ratio [HR] = 1.38; 95 % confidence interval [CI]: 1.13, 1.70 per 10 µg/m³), PM_2.5 (HR = 1.29; 95 % CI: 0.98, 1.71 per 5 µg/m³), and BC (HR = 1.37; 95 % CI: 1.11, 1.69 per 0.5 × 10^-5/m) with psychiatric disorders mortality, as well as with suicide (NO₂: HR = 1.13 [95 % CI: 0.92, 1.38]; PM_2.5: HR = 1.19 [95 % CI: 0.76, 1.87]; BC: HR = 1.08 [95 % CI: 0.87, 1.35]), and no association with dementia mortality. We did not detect any positive associations of O₃ and 8 PM_2.5 components with any of the three mortality outcomes. Long-term exposure to NO₂, PM_2.5, and BC may lead to premature mortality from psychiatric disorders and suicide.

Air pollution, road traffic noise and lack of greenness and risk of type 2 diabetes: A multi-exposure prospective study covering Denmark

OBJECTIVE

Air pollution, road traffic noise and lack of greenness coexist in urban environments and have all been associated with type 2 diabetes. We aimed to investigate how these co-exposures were associated with type 2 diabetes in a multi-exposure perspective.

METHODS

We estimated 5-year residential mean exposure to fine particles (PM_2.5), ultrafine particles (UFP), elemental carbon (EC), nitrogen dioxide (NO₂) and road traffic noise at the most (LdenMax) and least (LdenMin) exposed facade for all persons aged > 50 years living in Denmark in 2005 to 2017. For each air pollutant, we estimated total concentrations and traffic contributions. Based on land use maps, we estimated proportion of green and non-green space within 150 and 1000 m of all residences. In total, 1.9 million persons were included and 128,358 developed type 2 diabetes during follow-up. We performed analyses using Cox proportional hazards models, with adjustment for individual and neighborhood-level sociodemographic co-variates.

RESULTS

In single-pollutant models, all air pollutants, noise and lack of green space were associated with higher risk of diabetes. In two-, three- and four-pollutant analyses of the air pollutants, only UFP and NO₂ remained associated with higher diabetes risk in all models. LdenMax, LdenMin and the two proxies of green space remained associated with diabetes in two-pollutant models of, respectively, noise and green space. In a multi-pollutant analysis, we found hazard ratios (95 % confidence intervals) per interquartile range of 1.021 (1.005; 1.038) for UFP, 1.012 (0.996; 1.028) for NO₂, 1.022 (1.012; 1.033) for LdenMin, 1.013 (1.004; 1.022) for LdenMax, and 1.038 (1.031; 1.044) and 1.018 (1.010; 1.025) for lack of green space within, respectively, 150 m and 1000 m, and a cumulative risk index of 1.131 (1.113; 1.149).

CONCLUSIONS

Air pollution, road traffic noise and lack of green space were independently associated with higher risk of type 2 diabetes.

Long-term Traffic-related Air Pollutant Exposure and Amyotrophic Lateral Sclerosis Diagnosis in Denmark: A Bayesian Hierarchical Analysis

BACKGROUND

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease. Limited evidence suggests ALS diagnosis may be associated with air pollution exposure and specifically traffic-related pollutants.

METHODS

In this population-based case-control study, we used 3,937 ALS cases from the Danish National Patient Register diagnosed during 1989-2013 and matched on age, sex, year of birth, and vital status to 19,333 population-based controls free of ALS at index date. We used validated predictions of elemental carbon (EC), nitrogen oxides (NO x ), carbon monoxide (CO), and fine particles (PM 2.5 ) to assign 1-, 5-, and 10-year average exposures pre-ALS diagnosis at study participants' present and historical residential addresses. We used an adjusted Bayesian hierarchical conditional logistic model to estimate individual pollutant associations and joint and average associations for traffic-related pollutants (EC, NO x , CO).

RESULTS

For a standard deviation (SD) increase in 5-year average concentrations, EC (SD = 0.42 µg/m 3 ) had a high probability of individual association with increased odds of ALS (11.5%; 95% credible interval [CrI] = -1.0%, 25.6%; 96.3% posterior probability of positive association), with negative associations for NO x (SD = 20 µg/m 3 ) (-4.6%; 95% CrI = 18.1%, 8.9%; 27.8% posterior probability of positive association), CO (SD = 106 µg/m 3 ) (-3.2%; 95% CrI = 14.4%, 10.0%; 26.7% posterior probability of positive association), and a null association for nonelemental carbon fine particles (non-EC PM 2.5 ) (SD = 2.37 µg/m 3 ) (0.7%; 95% CrI = 9.2%, 12.4%). We found no association between ALS and joint or average traffic pollution concentrations.

CONCLUSIONS

This study found high probability of a positive association between ALS diagnosis and EC concentration. Further work is needed to understand the role of traffic-related air pollution in ALS pathogenesis.

Europe-wide air pollution modeling from 2000 to 2019 using geographically weighted regression

Previous European land-use regression (LUR) models assumed fixed linear relationships between air pollution concentrations and predictors such as traffic and land use. We evaluated whether including spatially-varying relationships could improve European LUR models by using geographically weighted regression (GWR) and random forest (RF). We built separate LUR models for each year from 2000 to 2019 for NO2, O3, PM2.5 and PM10 using annual average monitoring observations across Europe. Potential predictors included satellite retrievals, chemical transport model estimates and land-use variables. Supervised linear regression (SLR) was used to select predictors, and then GWR estimated the potentially spatially-varying coefficients. We developed multi-year models using geographically and temporally weighted regression (GTWR). Five-fold cross-validation per year showed that GWR and GTWR explained similar spatial variations in annual average concentrations (average R2 = NO2: 0.66; O3: 0.58; PM10: 0.62; PM2.5: 0.77), which are better than SLR (average R2 = NO2: 0.61; O3: 0.46; PM10: 0.51; PM2.5: 0.75) and RF (average R2 = NO2: 0.64; O3: 0.53; PM10: 0.56; PM2.5: 0.67). The GTWR predictions and a previously-used method of back-extrapolating 2010 model predictions using CTM were overall highly correlated (R2 > 0.8) for all pollutants. Including spatially-varying relationships using GWR modestly improved European air pollution annual LUR models, allowing time-varying exposure-health risk models.

Residential road traffic and railway noise and risk of childhood cancer: A nationwide register-based case-control study in Denmark

BACKGROUND

The aetiology of most childhood cancers remains poorly understood. We conducted a nationwide register-based case-control study to assess the association between residential road traffic and railway noise exposure and risk of childhood cancers.

METHODS

We identified all cases of first cancers diagnosed in children aged 0-19 years in 1985-2013 from the Danish Cancer Registry (N = 3962) and sampled four individually matched (by sex and date of birth) controls per case (N = 14,790) using the Central Population Register. We estimated time-weighted exposure averages of residential road traffic and railway noise at the most (Lden max) and least (Lden min) exposed façades from birth to index-date (for additional analysis: in utero period) based on the individual address history for the respective time windows. We fitted conditional logistic regression models to estimate odds ratios (OR) and their 95% confidence intervals (CI).

RESULTS

ORs varied by noise estimate and cancer type, with generally wide CIs mostly including 1.00. We found a tendency of higher ORs with increasing railway and road traffic noise for Hodgkin lymphoma (ORs for railway and road Lden min were 1.63 (95% CI 1.00; 2.66) and 1.14 (95% CI 0.87; 1.48) per 10 dB), as well as a tendency of higher ORs with increasing railway noise for non-Hodgkin lymphoma. For embryonal CNS tumours and astrocytoma and other glioma we observed also some weak suggestions of a positive association. Analysing exposure to traffic noise in utero revealed similar patterns to those of the main analyses.

CONCLUSIONS

This nationwide study with minimal risk of bias suggests no strong associations between traffic noise and risk of most childhood cancers. We found however some suggestive evidence for a positive association with Hodgkin lymphoma, non-Hodgkin lymphoma and some CNS tumours. Further research is warranted to confirm these associations in other populations and elucidate the underlying biological mechanisms.

Exposure to surrounding greenness and natural-cause and cause-specific mortality in the ELAPSE pooled cohort

BACKGROUND

The majority of studies have shown higher greenness exposure associated with reduced mortality risks, but few controlled for spatially correlated air pollution and traffic noise exposures. We aim to address this research gap in the ELAPSE pooled cohort.

METHODS

Mean Normalized Difference Vegetation Index (NDVI) in a 300-m grid cell and 1-km radius were assigned to participants' baseline home addresses as a measure of surrounding greenness exposure. We used Cox proportional hazards models to estimate the association of NDVI exposure with natural-cause and cause-specific mortality, adjusting for a number of potential confounders including socioeconomic status and lifestyle factors at individual and area-levels. We further assessed the associations between greenness exposure and mortality after adjusting for fine particulate matter (PM2.5), nitrogen dioxide (NO2) and road traffic noise.

RESULTS

The pooled study population comprised 327,388 individuals who experienced 47,179 natural-cause deaths during 6,374,370 person-years of follow-up. The mean NDVI in the pooled cohort was 0.33 (SD 0.1) and 0.34 (SD 0.1) in the 300-m grid and 1-km buffer. In the main fully adjusted model, 0.1 unit increment of NDVI inside 300-m grid was associated with 5% lower risk of natural-cause mortality (Hazard Ratio (HR) 0.95 (95% CI: 0.94, 0.96)). The associations attenuated after adjustment for air pollution [HR (95% CI): 0.97 (0.96, 0.98) adjusted for PM2.5; 0.98 (0.96, 0.99) adjusted for NO2]. Additional adjustment for traffic noise hardly affected the associations. Consistent results were observed for NDVI within 1-km buffer. After adjustment for air pollution, NDVI was inversely associated with diabetes, respiratory and lung cancer mortality, yet with wider 95% confidence intervals. No association with cardiovascular mortality was found.

CONCLUSIONS

We found a significant inverse association between surrounding greenness and natural-cause mortality, which remained after adjusting for spatially correlated air pollution and traffic noise.

Exposure to transportation noise and risk for cardiovascular disease in a nationwide cohort study from Denmark

BACKGROUND

Transportation noise increases the risk of ischemic heart disease (IHD), but few studies have investigated subtypes of IHD, such as myocardial infarction (MI), angina pectoris, or heart failure. We aimed to study whether exposure to road, railway and aircraft noise increased risk for ischemic heart disease (IHD), IHD subtypes, and heart failure in the entire adult Danish population, investigating exposures at both maximum exposed and silent façades of each residence.

METHODS

We modelled road, railway, and aircraft noise at the most and least exposed façades for the period 1995-2017 for all addresses in Denmark and calculated 10-year time-weighted running means for 2.5 million individuals age ≥50 years, of whom 122,523 developed IHD and 79,358 developed heart failure during follow-up (2005-2017). Data were analyzed using Cox proportional hazards models, adjusted for individual and area-level sociodemographic covariates and air pollution.

RESULTS

We found road traffic noise at the most exposed façade (L_den) to be associated with higher risk of IHD, myocardial infarction (MI), angina pectoris, and heart failure, with hazard ratios (HRs) (95% confidence intervals (CI)) of 1.052 (1.044-1.059), 1.041 (1.032-1.051), 1.095 (1.071-1.119), and 1.039 (1.033-1.045) per 10 dB higher 10-year mean exposure, respectively. These associations followed a near-linear exposure-response relationship and were robust to adjustment for air pollution with PM_2.5. Railway noise at the least exposed façade was associated with heart failure (HR 1.28; 95% CI: 1.004-1.053), but not the other outcomes. Exposure to aircraft noise (>45 dB) seemed associated with increased risk for MI and heart failure.

CONCLUSIONS

We found road traffic noise and potentially railway and aircraft noise to increase risk of various major cardiovascular outcomes, highlighting the importance of preventive actions towards transportation noise.

Long-Term Exposure to Source-Specific Fine Particles and Mortality─A Pooled Analysis of 14 European Cohorts within the ELAPSE Project

We assessed mortality risks associated with source-specific fine particles (PM_2.5) in a pooled European cohort of 323,782 participants. Cox proportional hazard models were applied to estimate mortality hazard ratios (HRs) for source-specific PM_2.5 identified through a source apportionment analysis. Exposure to 2010 annual average concentrations of source-specific PM_2.5 components was assessed at baseline residential addresses. The source apportionment resulted in the identification of five sources: traffic, residual oil combustion, soil, biomass and agriculture, and industry. In single-source analysis, all identified sources were significantly positively associated with increased natural mortality risks. In multisource analysis, associations with all sources attenuated but remained statistically significant with traffic, oil, and biomass and agriculture. The highest association per interquartile increase was observed for the traffic component (HR: 1.06; 95% CI: 1.04 and 1.08 per 2.86 μg/m³ increase) across five identified sources. On a 1 μg/m³ basis, the residual oil-related PM_2.5 had the strongest association (HR: 1.13; 95% CI: 1.05 and 1.22), which was substantially higher than that for generic PM_2.5 mass, suggesting that past estimates using the generic PM_2.5 exposure response function have underestimated the potential clean air health benefits of reducing fossil-fuel combustion. Source-specific associations with cause-specific mortality were in general consistent with findings of natural mortality.