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.

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.

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.

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).

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.

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.

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.

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.

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.

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.

Air pollution at the residence of Danish adults, by socio-demographic characteristics, morbidity, and address level characteristics

BACKGROUND

Exposure to outdoor air pollution is associated with adverse health effects. Previous studies have indicated higher levels of air pollution in socially deprived areas.

AIM

To investigate associations between air pollution and socio-demographic variables, comorbidity, stress, and green space at the residence in Denmark.

METHODS

We included 2,237,346 persons living in Denmark, aged 35 years or older in 2017. We used the high resolution, multi-scale DEHM/UBM/AirGIS air pollution modelling system to calculate mean concentrations of air pollution with PM_2.5, elemental carbon, ultrafine particles and NO₂ at residences held the preceding five years. We used nationwide registries to retrieve information about socio-demographic indicators at the individual and neighborhood levels. We used general linear regression models to analyze associations between socio-demographic indicators and air pollution at the residence.

RESULTS

Individuals with high SES (income, higher white-collar worker and high educational level) and of non-Danish origin were exposed to higher levels of air pollution than individuals of low SES and of Danish origin, respectively. We found comparable levels of air pollution according to sex, stress events and morbidity. For neighborhood level SES indicators, we found high air pollution levels in neighborhoods with low SES measured as proportion of social housing, sole providers, low income and unemployment. In contrast, we found higher air pollution levels in neighborhoods with higher educational level and a low proportion of manual labor. People living in an apartment and/or with little green space had higher air pollution levels.

CONCLUSION

In Denmark, high levels of residential air pollution were associated with higher individual SES and non-Danish origin. For neighborhood-level indicators of SES, no consistent pattern was observed. These results highlight the need for analyzing many different socio-demographic indicators to understand the complex associations between SES and exposure to air pollution.

Exposure to source-specific air pollution and risk for type 2 diabetes: a nationwide study covering Denmark

BACKGROUND

Only few epidemiological studies have investigated whether chronic exposure to air pollution from different sources have different impacts on risk of diabetes. We aimed to investigate associations between air pollution from traffic versus non-traffic sources and risk of type 2 diabetes in the Danish population.

METHODS

We estimated long-term exposure to traffic and non-traffic contributions of particulate matter with a diameter <2.5 µg (PM2.5), elemental carbon (EC), ultrafine particles (UFP) and nitrogen dioxide (NO2) for all persons living in Denmark for the period 2005-17. In total, 2.6 million persons aged >35 years were included, of whom 148 020 developed type 2 diabetes during follow-up. We applied Cox proportional hazards models for analyses, using 5-year time-weighted running means of air pollution and adjustment for individual- and area-level demographic and socioeconomic covariates.

RESULTS

We found that 5-year exposure to all particle measures (PM2.5, UFP and EC) and NO2 were associated with higher type 2 diabetes risk. We observed that for UFP, EC and potentially PM2.5, the pollution originating from traffic was associated with higher risks than the non-traffic contributions, whereas for NO2 similar hazard ratios (HR) were observed. For example, in two-source models, hazard ratios (HRs) per interquartile change in traffic UFP, EC and PM2.5 were 1.025, 1.045 and 1.036, respectively, whereas for non-traffic UFP, EC and PM2.5, the HRs were 1.013, 1.018 and 1.001, respectively.

CONCLUSIONS

Our finding of stronger associations with particulate matter from traffic compared with non-traffic sources implies that prevention strategies should focus on limiting traffic-related particulate matter air pollution.

The effect of adjustment to register-based and questionnaire-based covariates on the association between air pollution and cardiometabolic disease

OBJECTIVE

Recent studies on air pollution and disease have been based on millions of participants within a region or country, relying entirely on register-based confounder adjustment. We aimed to investigate the effects of increasing adjustment for register- and questionnaire-based covariates on the association between air pollution and cardiometabolic diseases.

METHODS

In a population-based cohort of 246,766 eligible participants randomly selected across Denmark in 2010 and 2013 and followed up until December 31, 2017, we identified 3,247 myocardial infarction (MI) cases, 4,166 stroke cases and 6,366 type 2 diabetes cases. Based on historical address-information, we calculated 5-year time-weighted exposure to PM_2.5 and NO₂ modelled using a validated air pollution model. We used Cox proportional hazards models to calculate hazard ratios (HR) with increasing adjustment for a number of individual- and area-level register-based covariates as well as lifestyle covariates assessed through questionnaires.

RESULTS

We found that a 5 μg/m³ higher PM_2.5 was associated with HRs (95% CI) for MI, stroke and diabetes, of respectively, 1.18 (0.91-1.52), 1.11 (0.88-1.40) and 1.24 (1.03-1.50) in the fully adjusted models. For all three diseases, adjustment for either individual-level, area-level or lifestyle covariates, or combinations of these resulted in higher HRs compared to HRs adjusted only for age, sex and calendar-year, most marked for MI and diabetes. Further adjustment for lifestyle in models with full register-based individual- and area-level adjustment resulted in only minor changes in HRs for all three diseases.

CONCLUSIONS

Our findings suggest that in studies of air pollution and cardiometabolic disease, which use an adjustment strategy with a broad range of register-based socioeconomic variables, there is no effect on risk estimates from subsequent lifestyle adjustment.

Long-term exposure to road traffic noise and stroke incidence: a Danish Nurse Cohort study

BACKGROUND

Road traffic noise has been linked to increased risk of ischemic heart disease, yet evidence on stroke shows mixed results. We examine the association between long-term exposure to road traffic noise and incidence of stroke, overall and by subtype (ischemic or hemorrhagic), after adjustment for air pollution.

METHODS

Twenty-five thousand six hundred and sixty female nurses from the Danish Nurse Cohort recruited in 1993 or 1999 were followed for stroke-related first-ever hospital contact until December 31st, 2014. Full residential address histories since 1970 were obtained and annual means of road traffic noise (L_den [dB]) and air pollutants (particulate matter with diameter < 2.5 μm and < 10 μm [PM_2.5 and PM₁₀], nitrogen dioxide [NO₂], nitrogen oxides [NOx]) were determined using validated models. Time-varying Cox regression models were used to estimate hazard ratios (HR) (95% confidence intervals [CI]) for the associations of one-, three-, and 23-year running means of L_den preceding stroke (all, ischemic or hemorrhagic), adjusting for stroke risk factors and air pollutants. The World Health Organization and the Danish government's maximum exposure recommendations of 53 and 58 dB, respectively, were explored as potential L_den thresholds.

RESULTS

Of 25,660 nurses, 1237 developed their first stroke (1089 ischemic, 148 hemorrhagic) during 16 years mean follow-up. For associations between a 1-year mean of L_den and overall stroke incidence, the estimated HR (95% CI) in the fully adjusted model was 1.06 (0.98-1.14) per 10 dB, which attenuated to 1.01 (0.93-1.09) and 1.00 (0.91-1.09) in models further adjusted for PM_2.5 or NO₂, respectively. Associations for other exposure periods or separately for ischemic or hemorrhagic stroke were similar. There was no evidence of a threshold association between L_den and stroke.

CONCLUSIONS

Long-term exposure to road traffic noise was suggestively positively associated with the risk of overall stroke, although not after adjusting for air pollution.

Exposure to ambient air pollution during childhood and subsequent risk of self-harm: A national cohort study

A growing body of evidence indicates that exposure to air pollution not only impacts on physical health but is also linked with a deterioration in mental health. We conducted the first study to investigate exposure to ambient particulate matter with an aerodynamic diameter of less than 2.5 μm (PM_2.5) and nitrogen dioxide (NO₂) during childhood and subsequent self-harm risk. The study cohort included persons born in Denmark between January 1, 1979 and December 31, 2006 (N = 1,424,670), with information on daily exposures to PM_2.5 and NO₂ at residence from birth to 10th birthday. Follow-up began from 10th birthday until first hospital-presenting self-harm episode, death, or December 31, 2016, whichever came first. Incidence rate ratios estimated by Poisson regression models revealed a dose relationship between increasing PM_2.5 exposure and rising self-harm risk. Exposure to 17-19 μg/m³ of PM_2.5 on average per day from birth to 10th birthday was associated with a 1.45 fold (95% CI 1.37-1.53) subsequently elevated self-harm risk compared with a mean daily exposure of <13 μg/m³, whilst those exposed to 19 μg/m³ or above on average per day had a 1.59 times (1.45-1.75) elevated risk. Higher mean daily exposure to NO₂ during childhood was also linked with increased self-harm risk, but the dose-response relationship observed was less evident than for PM_2.5. Covariate adjustment attenuated the associations, but risk remained independently elevated. Although causality cannot be assumed, these novel findings indicate a potential etiological involvement of ambient air pollution in the development of mental ill health.

Early childhood exposure to ambient air pollution is associated with increased risk of paediatric asthma: An administrative cohort study from Stockholm, Sweden

INTRODUCTION

Asthma is a complex, heterogeneous disease and one of the most common chronic diseases among children. Exposure to ambient air pollution in early life and childhood may influence asthma aetiology, but it is uncertain which specific components of air pollution and exposure windows are of importance. The role of socio-economic status (SES) is also unclear. The aims of the present study are, therefore, to investigate how various exposure windows of different pollutants affect risk-induced asthma in early life and to explore the possible effect SES has on that relationship.

METHODS

The study population was constructed using register data on all singleton births in the greater Stockholm area between 2006 and 2013. Exposure to ambient black carbon (BC), fine particulate matter (PM_2.5), primary organic carbon (pOC) secondary organic aerosols (SOA), secondary inorganic aerosols, and oxidative potential at the residential address was modelled as mean values for the entire pregnancy period, the first year of life and the first three years of life. Swedish national registers were used to define the outcome: asthma diagnosis assessed at hospital during the first six years of life. Hazard ratios (HRs) and their 95% confidence intervals (CIs) were modelled with Cox proportional hazards model with age as the underlying time-scale, adjusting for relevant potential confounding variables.

RESULTS

An increased risk for developing childhood asthma was observed in association with exposure to PM_2.5, pOC and SOA during the first three years of life. With an interquartile range increase in exposure, the HRs were 1.06 (95% CI: 1.01-1.10), 1.05 (95% CI: 1.02-1.09) and 1.02 (95% CI: 1.00-1.04), for PM_2.5, pOC and SOA, respectively, in the fully adjusted models. Exposure during foetal life or the first year of life was not associated with asthma risk, and the other pollutants were not statistically significantly associated with increased risk. Furthermore, the increase in risk associated with PM_2.5 and the components BC, pOC and SOA were stronger in areas with lower SES.

CONCLUSION

Our results suggest that exposure to air pollution during the first three years of life may increase the risk for asthma in early childhood. The findings further imply a possible increased vulnerability to air pollution-attributed asthma among low SES children.

Long-Term Residential Exposure to Particulate Matter and Its Components, Nitrogen Dioxide and Ozone-A Northern Sweden Cohort Study on Mortality

This study aims to estimate the mortality risk associated with air pollution in a Swedish cohort with relatively low exposure. Air pollution models were used to estimate annual mean concentrations of particulate matter with aerodynamic diameter ≤ 2.5 µm (PM_2.5), primary emitted carbonaceous particles (BC/pOC), sea salt, chemically formed particles grouped as secondary inorganic and organic aerosols (SIA and SOA) as well as ozone (O₃) and nitrogen dioxide (NO₂). The exposure, as a moving average was calculated based on home address for the time windows 1 year (lag 1), 1-5 years (lag 1-5) and 1-10 years (lag 1-10) preceding the death. During the study period, 1151 cases of natural mortality, 253 cases of cardiovascular disease (CVD) mortality and 113 cases of respiratory and lung cancer mortality were observed during 369,394 person-years of follow-up. Increased natural mortality was observed in association with NO₂ (3% [95% CI -8-14%] per IQR) and PM_2.5 (2% [95% CI -5-9%] for an IQR increase) and its components, except for SOA where a decreased risk was observed. Higher risk increases were observed for CVD mortality (e.g., 18% [95% CI 1-39%] per IQR for NO₂). These findings at low exposure levels are relevant for future decisions concerning air quality policies.

Long-Term Exposure to Road Traffic Noise and Air Pollution, and Incident Atrial Fibrillation in the Danish Nurse Cohort

BACKGROUND

Associations between long-term exposure to air pollution and road traffic noise have been established for ischemic heart disease, but findings have been mixed for atrial fibrillation (AF).

OBJECTIVES

The goal of the study was to examine associations of long-term exposure to road traffic noise and air pollution with AF.

METHODS

Time-varying Cox regression models were used to estimate associations of 1-, 3-, and 23-y mean road traffic noise and air pollution exposures with AF incidence in 23,528 women enrolled in the Danish Nurse Cohort (age >44y at baseline in 1993 or 1999). AF diagnoses were ascertained via the Danish National Patient Register. Annual mean weighted 24-h average road traffic noise levels (Lden) at the nurses' residences, since 1970, were estimated using the Nord2000 model, and annual mean levels of particulate matter with a diameter <2.5μm (PM2.5) and nitrogen dioxide (NO2) were estimated using the DEHM/UBM/AirGIS model.

RESULTS

Of 23,528 nurses with no prior AF diagnosis at the cohort baseline, 1,522 developed AF during follow-up. In a fully adjusted model (including PM2.5), the estimated risk of AF was 18% higher [hazard ratio (HR); 95% confidence interval (CI): 1.18; 1.02, 1.36] in nurses with residential 3-y mean Lden levels >58 dB vs. <48 dB, with similar findings for 1-y mean exposures. A 3.9-μg/m3 increase in 3-y mean PM2.5 was associated with incident AF before and after adjustment for concurrent exposure to road traffic noise (HR 1.09; 95% CI: 1.00, 1.20 and 1.08; 95% CI: 0.97, 1.19, respectively). Associations with 1-y mean PM2.5 exposures were positive but closer to the null and not significant. Associations with NO2 were null for all time periods before and after adjustment for road traffic noise and inverse when adjusted for concurrent PM2.5.

CONCLUSION

Our analysis of prospective data from a cohort of Danish female nurses followed for up to 14 y provided suggestive evidence of independent associations between incident AF and 1- and 3-y exposures to road traffic noise and PM2.5. https://doi.org/10.1289/EHP8090.

Long-term exposure to ambient air pollution and road traffic noise and asthma incidence in adults: The Danish Nurse cohort

BACKGROUND

Ambient air pollution is likely a risk factor for asthma, and recent evidence suggests the possible relevance of road traffic noise.

OBJECTIVES

We examined the associations of long-term exposure to air pollution and road traffic noise with adult-asthma incidence.

METHODS

We followed 28,731 female nurses (age > 44 years) from the Danish Nurse Cohort, recruited in 1993 and 1999, for first hospital contact for asthma from 1977 until 2015. We estimated residential annual mean concentrations of particulate matter with diameter < 2.5 µm (PM_2.5) since 1990 and nitrogen dioxide (NO₂) since 1970 with the Danish DEHM/UBM/AirGIS modeling system, and road traffic noise (L_den) since 1970 with the Nord2000 model. Time-varying Cox regression models were used to associate air pollution and road traffic noise exposure with asthma incidence.

RESULTS

During 18.6 years' mean follow-up, 528 out of 23,093 participants had hospital contact for asthma. The hazard ratios (HR) and 95% confidence intervals for asthma incidence associated with 3-year moving average exposures were 1.29 (1.03, 1.61) per 6.3 µg/m³ for PM_2.5, 1.16 (1.07, 1.27) per 8.2 µg/m³ for NO₂, and 1.12 (1.00, 1.25) per 10 dB for L_den. The HR for NO₂ remained unchanged after adjustment for either PM_2.5 or L_den, while the HRs for PM_2.5 and L_den attenuated to unity after adjustment for NO₂.

CONCLUSIONS

Long-term exposure to air pollution was associated with adult-asthma incidence independently of road traffic noise, with NO₂ most relevant. Road traffic noise was not independently associated with adult-asthma incidence.

Long-term air pollution and road traffic noise exposure and COPD: the Danish Nurse Cohort

BACKGROUND

While air pollution has been linked to the development of chronic obstructive pulmonary disease (COPD), evidence on the role of environmental noise is just emerging. We examined the associations of long-term exposure to air pollution and road traffic noise with COPD incidence.

METHODS

We defined COPD incidence for 24 538 female nurses from the Danish Nurse Cohort (age>44 years) as the first hospital contact between baseline (1993 or 1999) and 2015. We estimated residential annual mean concentrations of particulate matter with diameter<2.5 µm (PM_2.5) since 1990 and nitrogen dioxide (NO₂) since 1970 by the Danish DEHM/UBM/AirGIS modeling system, and road traffic noise (L_den) since 1970 by the Nord2000 model. Time-varying Cox regression models were applied to assess the associations of air pollution and road traffic noise with COPD incidence.

RESULTS

977 nurses developed COPD during 18.6 years' mean follow-up. We observed associations with COPD for all three exposures with hazard ratios (HRs) and 95% confidence intervals (CIs) of 1.19 (1.01, 1.41) per 6.26 µg·m^-3 for PM_2.5, 1.13 (1.05, 1.20) per 8.19 µg·m^-3 for NO₂, and 1.15 (1.06, 1.25) per 10 dB for L_den. Associations with NO₂ and L_den attenuated slightly after mutual adjustment, but were robust to adjustment for PM_2.5. Associations with PM_2.5 were attenuated to null after adjustment for either NO₂ or L_den. No potential interaction effect was observed between air pollutants and noise.

CONCLUSIONS

Long-term exposure to air pollution, especially traffic-related NO₂, and road traffic noise were independently associated with COPD.

Relation between Accumulated Air Pollution Exposure and Sub-Clinical Cardiovascular Disease in 33,723 Danish 60-74-Year-Old Males from the Background Population (AIR-CARD): A Method Article

Cardiovascular disease is one of the main causes of death and disability in the Western world, and there is increasing evidence that air pollution is a risk factor for developing sub-clinical cardiovascular diseases. Previous studies have shown a correlation between cardiovascular disease and short-term exposure to elevated air pollution levels. However, the literature on the impact of long-term effect of air pollution is limited. We have a unique opportunity to evaluate this correlation. The DEHM/UBM/AirGIS model system calculates air pollution in a high temporal and spatial resolution and traces air pollution retrospectively to year 1979. The model calculates accumulated exposure using annual exposure from PM2.5 in relation to home and work addresses and takes into account working hours and holidays. We link the results from this model system to a population-based cardiovascular screening cohort of 33,723 individuals in the age of 60-74 to assess the contribution of the specific accumulated air pollution to the presence of sub-clinical arteriosclerosis in the coronary vessels, abdominal aortic aneurysms, and peripheral arterial disease. This correlation will be further analyzed in relation to specific air pollutants. This study will introduce more precise data for a longer period of time and incorporate participant's home and work addresses.

Long-term exposure to air pollution and mortality in the Danish population a nationwide study

BACKGROUND

Studies have shown higher mortality in association with exposure to air pollution. We investigated this association with focus on differences between socioeconomic groups.

METHODS

We included all Danes born between 1921 and 1985 aged 30-85 years from 1991 to 2015 (N = 4,401,348). We applied a nested case-control design and identified those who died during follow-up and selected five controls per case. We modelled NO2, fine particulate matter (PM2·5), black carbon (BC) particles, and ozone (O3) as five-year average concentrations at the residential addresses of 672,895 all natural cause mortality cases and 3,426,533 controls in conditional logistic regression with adjustment for individual and neighbourhood level socio-demographic variables.

FINDINGS

In single pollutant models, a 10 μg/m3 (BC: 1 μg/m3) increase in NO2, PM2·5, BC, and O3 was associated with natural cause mortality rate ratios (MRR) of 1·05 (95% confidence interval 1·04-1·06), 1·08 (1·04-1·13), 1·05 (1·02-1·08), and 0·96 (0·95-0·97), respectively. The patterns were similar for respiratory disease and lung cancer mortality. O3 was associated with higher risk of CVD mortality. The rate differences for a unit increase in PM2·5, NO2, and BC were largest among those with the lowest income; this pattern was not detected when considering the relative risk measure, MRR.

INTERPRETATION

Long-term concentration of air pollution at the residence was associated with higher natural cause mortality in the Danish population and the strength of the association differed by socioeconomic group. We recommend that future studies express socioeconomic differences in absolute rather than relative risk.

Air pollution exposure at the residence and risk of childhood cancers in Denmark: A nationwide register-based case-control study

BACKGROUND

The etiology of childhood cancer is poorly understood. The role of environmental factors, including air pollution (AP) exposure, has been addressed previously, but results so far have been inconclusive. In this study, we investigate the association between long-term AP exposures in relation to childhood cancer subtypes in Denmark (1981-2013).

METHODS

We conducted a nationwide register-based case-control study. We identified 7745 incident cases of childhood cancers (<20 years) in the Danish Cancer Registry. Four randomly selected (cancer-free) controls were matched to each case according to sex and date of birth. We modelled concentrations of nitrogen dioxide (NO₂), fine particles (PM_2·5), and black carbon (BC) at all addresses and calculated a time-weighted average from birth to index-date with a state-of-the-art multiscale AP modelling system. We analyzed the risk of childhood cancer in conditional logistic regression models adjusted for socio-demographic variables obtained from registers at the individual and neighborhood level.

FINDINGS

The main analyses included 5045 cases and 18,179 controls. For all cancers combined, we observed odds ratios (ORs) and 95% confidence intervals (95% CI) of 0·97 (0·94, 1·01) per 10 µg/m³ NO₂, 0·89 (0·82, 0·98) per 5 µg/m³ PM_2·5, and 0·94 (0·88, 1·01) per 1 µg/m³ BC, respectively. Most notably, we observed a higher risk of Non-Hodgkin Lymphoma (NHL) with higher childhood AP exposure with ORs and 95% CIs of 1·21 (0·94, 1·55) per 10 µg/m³ NO₂, 2·11 (1·10, 4·01) per 5 µg/m³ PM_2·5, and 1·68 (1·06, 2·66) per 1 µg/m³ BC, respectively. We observed indications of increased risks for other types of childhood cancer, however, with very wide CIs including 1.

INTERPRETATIONS

The findings of this nation-wide study propose a role of AP in the development of childhood NHL, but more large-scale studies are needed.

FUNDING

NordForsk Project #75007.

Long-term exposure to low levels of air pollution and mortality adjusting for road traffic noise: A Danish Nurse Cohort study

BACKGROUND

The association between air pollution and mortality is well established, yet some uncertainties remain: there are few studies that account for road traffic noise exposure or that consider in detail the shape of the exposure-response function for cause-specific mortality outcomes, especially at low-levels of exposure.

OBJECTIVES

We examined the association between long-term exposure to particulate matter [(PM) with a diameter of <2.5 µm (PM_2.5), <10 µm (PM₁₀)], and nitrogen dioxide (NO₂) and total and cause-specific mortality, accounting for road traffic noise.

METHODS

We used data on 24,541 females (age > 44 years) from the Danish Nurse Cohort, who were recruited in 1993 or 1999, and linked to the Danish Causes of Death Register for follow-up on date of death and its cause, until the end of 2013. Annual mean concentrations of PM_2.5, PM_10, and NO₂ at the participants' residences since 1990 were estimated using the Danish DEHM/UBM/AirGIS dispersion model, and annual mean road traffic noise levels (L_den) were estimated using the Nord2000 model. We examined associations between the three-year running mean of PM_2.5, PM₁₀, and NO₂ with total and cause-specific mortality by using time-varying Cox Regression models, adjusting for individual characteristics and residential road traffic noise.

RESULTS

During the study period, 3,708 nurses died: 843 from cardiovascular disease (CVD), 310 from respiratory disease (RD), and 64 from diabetes. In the fully adjusted models, including road traffic noise, we detected associations of three-year running mean of PM_2.5 with total (hazard ratio; 95% confidence interval: 1.06; 1.01-1.11), CVD (1.14; 1.03-1.26), and diabetes mortality (1.41; 1.05-1.90), per interquartile range of 4.39 μg/m³. In a subset of the cohort exposed to PM_2.5 < 20 µg/m³, we found even stronger association with total (1.19; 1.11-1.27), CVD (1.27; 1.01-1.46), RD (1.27; 1.00-1.60), and diabetes mortality (1.44; 0.83-2.48). We found similar associations with PM₁₀ and none with NO₂. All associations were robust to adjustment for road traffic noise.

DISCUSSION

Long-term exposure to low-levels of PM_2.5 and PM₁₀ is associated with total mortality, and mortality from CVD, RD, and diabetes. Associations were even stronger at the PM_2.5 levels below EU limit values and were independent of road traffic noise.

Long-term exposure to air pollution and stroke incidence: A Danish Nurse cohort study

Ambient air pollution has been linked to stroke, but few studies have examined in detail stroke subtypes and confounding by road traffic noise, which was recently associated with stroke. Here we examined the association between long-term exposure to air pollution and incidence of stroke (overall, ischemic, hemorrhagic), adjusting for road traffic noise. In a nationwide Danish Nurse Cohort consisting of 23,423 nurses, recruited in 1993 or 1999, we identified 1,078 incident cases of stroke (944 ischemic and 134 hemorrhagic) up to December 31, 2014, defined as first-ever hospital contact. The full residential address histories since 1970 were obtained for each participant and the annual means of air pollutants (particulate matter with diameter < 2.5 µm and < 10 µm (PM_2.5 and PM₁₀), nitrogen dioxide (NO₂), nitrogen oxides (NOx)) and road traffic noise were determined using validated models. Time-varying Cox regression models were used to estimate hazard ratios (HR) (95% confidence intervals (CI)) for the associations of one-, three, and 23-year running mean of air pollutants with stroke adjusting for potential confounders and noise. In fully adjusted models, the HRs (95% CI) per interquartile range increase in one-year running mean of PM_2.5 and overall, ischemic, and hemorrhagic stroke were 1.12 (1.01-1.25), 1.13 (1.01-1.26), and 1.07 (0.80-1.44), respectively, and remained unchanged after adjustment for noise. Long-term exposure to ambient PM_2.5 was associated with the risk of stroke independent of road traffic noise.

Copenhagen--a significant source of birch (Betula) pollen?

Current aerobiological research applies the hypothesis that the main source of atmospheric birch (Betula) pollen is forest trees. Our results indicate that the measured levels in Copenhagen are not only due to birch trees in Danish forests but that the urban areas also seem to be a significant source of birch pollen. A number of episodes in 2003 with enhanced pollen levels in Copenhagen seem to be associated with parks and gardens inside and just outside the city. Our results also indicate one long-range transport episode from remote sources in Poland and Germany. Finally, our results show that the pollen levels vary considerably over the day and geographically between Copenhagen and the city of Roskilde, 40 km away. We suggest, that these differences in time and space in the pollen levels are mapped using an integrated monitoring strategy.

The role of the snowpack on the fate of alpha-HCH in an atmospheric chemistry-transport model

A dynamic snowpack module was implemented in the Danish Eulerian Hemispheric Model Persistant Organic Pollutants (DEHM-POP), an atmospheric chemistry-transport model designed to study the environmental fate of persistent organic pollutants in the Northern Hemisphere. The role of the snowpack on the fate of alpha-hexachlorocyclohexane (alpha-HCH) was investigated by making simulations both with and without the formation of a snowpack and comparing model results with data from 21 air monitoring sites. The inclusion of a dynamic snowpack module in the DEHM-POP model generally improves the fit between modeled and observed alpha-HCH air concentrations for the winter and spring seasons and the overall correlation coefficient between predicted and observed concentrations are improved at 8 of the sites. The predicted snowpack concentrations are in good agreement with the few available snow measurements from the Arctic. The presence of a snowpack increases surface boundary layer air concentrations of alpha-HCH at midlatitudes, while the effect is more pronounced in the Arctic due to the longer periods of snow cover. The results indicate that the snowpack module in DEHM-POP acts as a fast-exchanging temporary storage medium for alpha-HCH, as significant fractions were rapidly revolatilized back into the atmosphere following deposition with snowfall, although the current parametrization for vapor-exchange probably over emphasizes this process. Nonetheless, increased air concentrations observed between March and May ("spring maximum events"; SME) at several high latitude monitoring stations are also predicted by the model. The model results indicate that the SMEs are associated with the revolatilization of previously deposited chemical from the snowpack, following a reduction in the capacity of the snowpack to retain alpha-HCH with increasing temperatures toward the end of the winter period, rather than the actual melting of the snowpack. The SMEs are not predicted at all the Arctic monitoring sites by the model, and the significance of the snowpack in controlling these in the model is, therefore, open to question given the uncertainties in the snow-air partition coefficient (K(sa)) and the reliance of the model on a one-layer snowpack rather than a multilayered snowpack.

Identifying the European fossil fuel plumes in the atmosphere over the Northeast Atlantic Region through isotopic observations and numerical modelling

As part of the Danish NEAREX project the origin and variability of anthropogenic atmospheric CO(2) over the Northeast Atlantic Region (NEAR) has been studied. The project consisted of a combination of experimental and modelling activities. Local volunteers operated CO(2) sampling stations, built at University of Copenhagen, for (14)C analysis at four locations (East Denmark, Shetland Isles, Faroe Isles and Iceland). The samples were only collected during winter periods of south-easterly winds in an attempt to trace air enriched in fossil-fuel derived CO(2) due to combustion of fossil fuels within European countries. In order to study the transport and concentration fields over the region in detail, a three-dimensional Eulerian hemispheric air pollution model has been extended to include the main anthropogenic sources for atmospheric CO(2). During the project period (1998-2001) only a few episodes of transport from Central Europe towards NEAR arose, which makes the data set for the evaluation of the method sparse. The analysed samples indicate that the signal for fossil CO(2), as expected, is largest (up to 3.7+/-0.4% fossil CO(2)) at the Danish location closest to the European emissions areas and much weaker (up to approximately 1.5+/-0.6% fossil CO(2)) at the most remote location. As the anthropogenic signal is weak in the clean atmosphere over NEAR these numbers will, however, be very sensitive to the assumed background (14)CO(2) activity and the precision of the measurements. The model simulations include the interplay between the driving processes from the emission into the boundary layer and the following horizontal/vertical mixing and atmospheric transport and are used to analyse the meteorological conditions leading to the observed events of high fossil CO(2) over NEAR. This information about the history of the air masses is essential if an observed signal is to be utilised for identifying and quantifying sources for fossil CO(2).