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 ≤2.5 µm (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 5 µg/m3, BC (1.26 (1.03-1.53) per 0.5 × 10- 5/m), NO2 (1.13 (0.93-1.38) per 10 µg/m3) and inverse for O3 (0.71 (0.54-0.93) per 10 µg/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.

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 (PM2.5 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, PM2.5, 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.

Long-term exposure to air pollution and road traffic noise and incidence of dementia in the Danish Nurse Cohort.

INTRODUCTION: We examined the association of long-term exposure to air pollution and road traffic noise with dementia incidence in the Danish Nurse Cohort. METHODS: Female nurses were followed for dementia incidence (hospital contact or medication prescription) from 1993/1999 to 2020. Air pollution and road traffic noise levels were estimated at nurses' residences, and their associations with dementia were examined using Cox regression models. RESULTS: Of 25,233 nurses 1409 developed dementia. Particulate matter with a diameter of ≤2.5 µm (PM2.5) was associated with dementia incidence, after adjusting for lifestyle, socioeconomic status, and road traffic noise (hazard ratio [95% confidence interval] 1.35 [1.15-1.59] per interquartile range of 2.6 µg/m3). There was no association of PM2.5 with dementia in physically active nurses. Association with road traffic noise diminished after adjusting for PM2.5 (1.02 [0.93-1.11] per 7.6 dB). DISCUSSION: Long-term exposure to air pollution increases risk of dementia, and physical activity may moderate this risk. HIGHLIGHTS: Long-term exposure to air pollution was associated with increased risk of dementia among female nurses from the Danish Nurse Cohort. Association of air pollution with dementia was independent of road traffic noise. Association of road traffic noise with dementia diminished after adjusting for air pollution. Physical activity moderated adverse effects of air pollution on dementia.

Exploring Relevant Time Windows in the Association Between PM2.5 Exposure and Amyotrophic Lateral Sclerosis: A Case-Control Study in Denmark.

Studies suggest a link between particulate matter less than or equal to 2.5 µm in diameter (PM2.5) and amyotrophic lateral sclerosis (ALS), but to our knowledge critical exposure windows have not been examined. We performed a case-control study in the Danish population spanning the years 1989-2013. Cases were selected from the Danish National Patient Registry based on International Classification of Diseases codes. Five controls were randomly selected from the Danish Civil Registry and matched to a case on vital status, age, and sex. PM2.5 concentration at residential addresses was assigned using monthly predictions from a dispersion model. We used conditional logistic regression to estimate odds ratios (ORs) and 95% confidence intervals (CIs), adjusting for confounding. We evaluated exposure to averaged PM2.5 concentrations 12-24 months, 2-6 years, and 2-11 years pre-ALS diagnosis; annual lagged exposures up to 11 years prediagnosis; and cumulative associations for exposure in lags 1-5 years and 1-10 years prediagnosis, allowing for varying association estimates by year. We identified 3,983 cases and 19,915 controls. Cumulative exposure to PM2.5 in the period 2-6 years prediagnosis was associated with ALS (OR = 1.06, 95% CI: 0.99, 1.13). Exposures in the second, third, and fourth years prediagnosis were individually associated with higher odds of ALS (e.g., for lag 1, OR = 1.04, 95% CI: 1.00, 1.08). Exposure to PM2.5 within 6 years before diagnosis may represent a critical exposure window for ALS.

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.

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.

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 (PM2.5), 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 PM2.5 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 PM2.5 changed only little, whereas ORs for EC or NO2 approached the null. In an analysis of persons below 55 years, PM2.5 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 PM2.5. 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.

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 (PM2.5), 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 ß-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 PM2.5, 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.

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 (PM2.5), 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). PM2.5 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 PM2.5 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.

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 Air Pollution Exposure and Pneumonia-related Mortality in a Large Pooled European Cohort.

Rationale: Ambient air pollution exposure has been linked to mortality from chronic cardiorespiratory diseases, while evidence on respiratory infections remains more limited. Objectives: We examined the association between long-term exposure to air pollution and pneumonia-related mortality in adults in a pool of eight European cohorts. Methods: Within the multicenter project ELAPSE (Effects of Low-Level Air Pollution: A Study in Europe), we pooled data from eight cohorts among six European countries. Annual mean residential concentrations in 2010 for fine particulate matter, nitrogen dioxide (NO2), black carbon (BC), and ozone 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 pneumonia, influenza, and acute lower respiratory infections (ALRI) mortality. Measurements and Main Results: Of 325,367 participants, 712 died from pneumonia and influenza combined, 682 from pneumonia, and 695 from ALRI during a mean follow-up of 19.5 years. NO2 and BC were associated with 10-12% increases in pneumonia and influenza combined mortality, but 95% confidence intervals included unity (hazard ratios, 1.12 [0.99-1.26] per 10 µg/m3 for NO2; 1.10 [0.97-1.24] per 0.5 10-5m-1 for BC). Associations with pneumonia and ALRI mortality were almost identical. We detected effect modification suggesting stronger associations with NO2 or BC in overweight, employed, or currently smoking participants compared with normal weight, unemployed, or nonsmoking participants. Conclusions: Long-term exposure to combustion-related air pollutants NO2 and BC may be associated with mortality from lower respiratory infections, but larger studies are needed to estimate these associations more precisely.

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.

Long-term exposure to ambient air pollution and bladder cancer incidence in a pooled European cohort: the ELAPSE project.

BACKGROUND: The evidence linking ambient air pollution to bladder cancer is limited and mixed. METHODS: We assessed the associations of bladder cancer incidence with residential exposure to fine particles (PM2.5), nitrogen dioxide (NO2), black carbon (BC), warm season ozone (O3) and eight PM2.5 elemental components (copper, iron, potassium, nickel, sulfur, silicon, vanadium, and zinc) in a pooled cohort (N = 302,493). Exposures were primarily assessed based on 2010 measurements and back-extrapolated to the baseline years. We applied Cox proportional hazard models adjusting for individual- and area-level potential confounders. RESULTS: During an average of 18.2 years follow-up, 967 bladder cancer cases occurred. We observed a positive though statistically non-significant association between PM2.5 and bladder cancer incidence. Hazard Ratios (HR) were 1.09 (95% confidence interval (CI): 0.93-1.27) per 5 µg/m3 for 2010 exposure and 1.06 (95% CI: 0.99-1.14) for baseline exposure. Effect estimates for NO2, BC and O3 were close to unity. A positive association was observed with PM2.5 zinc (HR 1.08; 95% CI: 1.00-1.16 per 10 ng/m3). CONCLUSIONS: We found suggestive evidence of an association between long-term PM2.5 mass exposure and bladder cancer, strengthening the evidence from the few previous studies. The association with zinc in PM2.5 suggests the importance of industrial emissions.

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.

Air pollution and fecundability: Results from a Danish preconception cohort study.

BACKGROUND: Animal and epidemiologic studies indicate that air pollution may adversely affect fertility. Epidemiologic studies have been restricted largely to couples undergoing fertility treatment or have retrospectively ascertained time-to-pregnancy among pregnant women. OBJECTIVES: We examined the association between residential ambient air pollution and fecundability, the per-cycle probability of conception, in a large preconception cohort of Danish pregnancy planners. METHODS: During 2007-2018, we used the Internet to recruit and follow women who were trying to conceive without the use of fertility treatment. Participants completed an online baseline questionnaire eliciting socio-demographic characteristics, lifestyle factors, and medical and reproductive histories and follow-up questionnaires every 8 weeks to ascertain pregnancy status. We determined concentrations of ambient nitrogen oxides (NOx ), nitrogen dioxide (NO2 ), carbon monoxide (CO), ozone (O3 ), particulate matter <2.5 µm (PM2.5 ) and <10 µm (PM10 ), and sulphur dioxide (SO2 ) at each participant's residential address. We calculated average exposure during the year before baseline, during each menstrual cycle over follow-up and during the entire pregnancy attempt time. We used proportional probabilities regression models to estimate fecundability ratios (FRs) and 95% confidence intervals (CIs), adjusting for potential confounders and co-pollutants. The analysis was restricted to the 10,183 participants who were trying to conceive for <12 cycles at study entry whose addresses could be geocoded. RESULTS: During 12 months of follow-up, 73% of participants conceived. Higher concentrations of PM2.5 and PM10 were associated with small reductions in fecundability. For example, the FRs for a one interquartile range (IQR) increase in PM2.5 (IQR = 3.2 µg/m3 ) and PM10 (IQR = 5.3 µg/m3 ) during each menstrual cycle were 0.93 (95% CI: 0.87, 0.99) and 0.91 (95% CI: 0.84, 0.99), respectively. Other air pollutants were not appreciably associated with fecundability. CONCLUSIONS: In this preconception cohort study of Danish women, residential exposures to PM2.5 and PM10 were associated with reduced fecundability.

Mixed-Effects Modeling Framework for Amsterdam and Copenhagen for Outdoor NO2 Concentrations Using Measurements Sampled with Google Street View Cars.

High-resolution air quality (AQ) maps based on street-by-street measurements have become possible through large-scale mobile measurement campaigns. Such campaigns have produced data-only maps and have been used to produce empirical models [i.e., land use regression (LUR) models]. Assuming that all road segments are measured, we developed a mixed model framework that predicts concentrations by an LUR model, while allowing road segments to deviate from the LUR prediction based on between-segment variation as a random effect. We used Google Street View cars, equipped with high-quality AQ instruments, and measured the concentration of NO2 on every street in Amsterdam (n = 46.664) and Copenhagen (n = 28.499) on average seven times over the course of 9 and 16 months, respectively. We compared the data-only mapping, LUR, and mixed model estimates with measurements from passive samplers (n = 82) and predictions from dispersion models in the same time window as mobile monitoring. In Amsterdam, mixed model estimates correlated rs (Spearman correlation) = 0.85 with external measurements, whereas the data-only approach and LUR model estimates correlated rs = 0.74 and 0.75, respectively. Mixed model estimates also correlated higher rs = 0.65 with the deterministic model predictions compared to the data-only (rs = 0.50) and LUR model (rs = 0.61). In Copenhagen, mixed model estimates correlated rs = 0.51 with external model predictions compared to rs = 0.45 and rs = 0.50 for data-only and LUR model, respectively. Correlation increased for 97 locations (rs = 0.65) with more detailed traffic information. This means that the mixed model approach is able to combine the strength of data-only mapping (to show hyperlocal variation) and LUR models by shrinking uncertain concentrations toward the model output.

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 (PM2.5) in a pooled European cohort of 323,782 participants. Cox proportional hazard models were applied to estimate mortality hazard ratios (HRs) for source-specific PM2.5 identified through a source apportionment analysis. Exposure to 2010 annual average concentrations of source-specific PM2.5 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 PM2.5 had the strongest association (HR: 1.13; 95% CI: 1.05 and 1.22), which was substantially higher than that for generic PM2.5 mass, suggesting that past estimates using the generic PM2.5 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.

Occupational noise exposure and risk of incident stroke: a pooled study of five Scandinavian cohorts.

OBJECTIVES: To investigate the association between occupational noise exposure and stroke incidence in a pooled study of five Scandinavian cohorts (NordSOUND). METHODS: We pooled and harmonised data from five Scandinavian cohorts resulting in 78 389 participants. We obtained job data from national registries or questionnaires and recoded these to match a job-exposure matrix developed in Sweden, which specified the annual average daily noise exposure in five exposure classes (LAeq8h): <70, 70-74, 75-79, 80-84, ≥85 dB(A). We identified residential address history and estimated 1-year average road traffic noise at baseline. Using national patient and mortality registers, we identified 7777 stroke cases with a median follow-up of 20.2 years. Analyses were conducted using Cox proportional hazards models adjusting for individual and area-level potential confounders. RESULTS: Exposure to occupational noise at baseline was not associated with overall stroke in the fully adjusted models. For ischaemic stroke, occupational noise was associated with HRs (95% CI) of 1.08 (0.98 to 1.20), 1.09 (0.97 to 1.24) and 1.06 (0.92 to 1.21) in the 75-79, 80-84 and ≥85 dB(A) exposure groups, compared with <70 dB(A), respectively. In subanalyses using time-varying occupational noise exposure, we observed an indication of higher stroke risk among the most exposed (≥85 dB(A)), particularly when restricting analyses to people exposed to occupational noise within the last year (HR: 1.27; 95% CI: 0.99 to 1.63). CONCLUSIONS: We found no association between occupational noise and risk of overall stroke after adjustment for confounders. However, the non-significantly increased risk of ischaemic stroke warrants further investigation.

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.