Statistical Analysis Plan for the AIRCARD Study: Individual Long-term Air and Noise Pollution Exposure and Cardiovascular Disease Incidence and Mortality (AIRCARD): A Prospective Cohort Study Utilizing DANCAVAS and VIVA Screening Trials.

INTRODUCTION: The AIRCARD study is designed to investigate the relationship between long-term exposure to air and noise pollution and cardiovascular disease incidence and mortality. We aim to conduct a robust prospective cohort analysis assessing the cumulative and differential impacts of air and noise pollution exposure on cardiovascular disease and mortality. This study will adjust for relevant confounders, including traditional cardiovascular risk factors, socioeconomic indicators, and lipid-lowering agents. METHODS: This prospective cohort study will include 27,022 male participants aged 65-74, recruited from the two large Danish DANCAVAS and VIVA trials, both population-based randomized, multicentered, clinically controlled studies. We will assess long-term exposure to air pollutants using the state-of-the-art DEHM/UBM/AirGIS modelling system and noise pollution through the Nord2000 and SoundPLAN models, covering data from 1979 to 2019. This statistical analysis plan is strictly formulated to predefine the analytical approach for all outcomes and key study variables before data access. The primary analysis will utilize Cox proportional hazards models, adjusted for confounders identified in our cohort (age, body mass index, hypertension, diabetes, smoking status, family history of heart disease, socioeconomic factors, and lipid-lowering agents). This statistical analysis plan further includes Spearman rank correlation to explore inter-pollutant associations. CONCLUSION: The AIRCARD study addresses global concerns about the impact of air and noise pollution on cardiovascular disease. This research is important for understanding how the pollutants contribute to cardiovascular disease. We aim to provide insights into this area, emphasizing the need for public health measures to mitigate pollution exposure. Our goal is to provide policymakers and healthcare professionals with information on the role of environmental factors in cardiovascular health that could influence global strategies to reduce the cardiovascular disease burden associated with pollution. The design of this SAP ensures transparency and.

Associations of long-term exposure to air pollution and greenness with incidence of chronic obstructive pulmonary disease in Northern Europe: The Life-GAP project.

BACKGROUND: Prolonged exposure to air pollution has been linked to adverse respiratory health, yet the evidence concerning its association with chronic obstructive pulmonary disease (COPD) is inconsistent. The evidence of a greenness effect on chronic respiratory diseases is limited. OBJECTIVE: This study aimed to investigate the association between long-term exposure to particulate matter (PM2.5 and PM10), black carbon (BC), nitrogen dioxide (NO2), ozone (O3) and greenness (as measured by the normalized difference vegetation index - NDVI) and incidence of self-reported chronic bronchitis or COPD (CB/COPD). METHODS: We analyzed data from 5355 adults from 7 centers participating in the Respiratory Health in Northern Europe (RHINE) study. Mean exposures to air pollution and greenness were assessed at available residential addresses in 1990, 2000 and 2010 using air dispersion models and satellite data, respectively. Poisson regression with log person-time as an offset was employed to analyze the association between air pollution, greenness, and CB/COPD incidence, adjusting for confounders. RESULTS: Overall, there were 328 incident cases of CB/COPD during 2010-2023. Despite wide statistical uncertainty, we found a trend for a positive association between NO2 exposure and CB/COPD incidence, with incidence rate ratios (IRRs) per 10 µg/m³ difference ranging between 1.13 (95% CI: 0.90-1.41) in 1990 and 1.18 (95% CI: 0.96-1.45) in 2000. O3 showed a tendency for inverse association with CB/COPD incidence (IRR from 0.84 (95% CI: 0.66-1.07) in 2000 to 0.88 (95% CI: 0.69-1.14) in 2010. No consistent association was found between PM, BC and greenness with CB/COPD incidence across different exposure time windows. CONCLUSION: Consistent with prior research, our study suggests that individuals exposed to higher concentrations of NO2 may face an elevated risk of developing COPD, although evidence remains inconclusive. Greenness was not associated with CB/COPD incidence, while O3 showed a tendency for an inverse association with the outcome.

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 transportation noise and risk of type 2 diabetes: A cohort study.

BACKGROUND: Some studies have found transportation noise to be associated with higher diabetes risk. This includes studies based on millions of participants, relying entirely on register-based confounder adjustment, which raises concern about residual lifestyle confounding. We aimed to investigate associations between noise and type 2 diabetes (T2D), including investigation of effects of increasing confounder adjustment for register-data and lifestyle. METHODS: In a cohort of 286,151 participants randomly selected across Denmark in 2010-2013 and followed up until 2017, we identified 7574 incident T2D cases. Based on residential address-history for all participants linked with exposure assessment of high spatial resolution, we calculated 10-year time-weighted mean road and railway noise at the most (LdenMax) and least (LdenMin) exposed façades and air pollution (PM2.5). We used Cox models to calculate hazard ratios (HR) with increasing adjustment for individual- and area-level register-based sociodemographic covariates, self-reported lifestyle and air pollution. RESULTS: We found that a 10 dB increase in 10-year mean road LdenMin was associated with HRs (95% CI) of 1.06 (1.02-1.10) after adjustment for age, sex and year, 1.08 (1.04-1.13) after further adjustment for register-based sociodemographic covariates, 1.07 (1.03-1.12) after further lifestyle adjustment (e.g. smoking, diet and alcohol) and 1.06 (1.02-1.11) after further PM2.5 adjustment. For road LdenMax, the corresponding HRs were 1.07 (1.04-1.10), 1.05 (1.02-1.08), 1.04 (1.01-1.07) and 1.03 (1.00-1.06). Railway noise was associated with HRs of 1.04 (0.98-1.11) for LdenMax and 1.02 (0.92-1.12) for LdenMin after adjustment for sociodemographic and lifestyle covariates and PM2.5. CONCLUSIONS: Long-term exposure to road traffic noise was associated with T2D, which together with previous literature indicates that T2D should be considered when calculating health impacts of noise. After sociodemographic adjustment, further lifestyle adjustment only changed HRs slightly, suggesting that large register-based studies with adjustment for key sociodemographic covariates can produce reliable results.

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.

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.

Analysis of mortality metrics associated with a comprehensive range of disorders in Denmark, 2000 to 2018: A population-based cohort study.

BACKGROUND: The provision of different types of mortality metrics (e.g., mortality rate ratios [MRRs] and life expectancy) allows the research community to access a more informative set of health metrics. The aim of this study was to provide a panel of mortality metrics associated with a comprehensive range of disorders and to design a web page to visualize all results. METHODS AND FINDINGS: In a population-based cohort of all 7,378,598 persons living in Denmark at some point between 2000 and 2018, we identified individuals diagnosed at hospitals with 1,803 specific categories of disorders through the International Classification of Diseases-10th Revision (ICD-10) in the National Patient Register. Information on date and cause of death was obtained from the Registry of Causes of Death. For each of the disorders, a panel of epidemiological and mortality metrics was estimated, including incidence rates, age-of-onset distributions, MRRs, and differences in life expectancy (estimated as life years lost [LYLs]). Additionally, we examined models that adjusted for measures of air pollution to explore potential associations with MRRs. We focus on 39 general medical conditions to simplify the presentation of results, which cover 10 broad categories: circulatory, endocrine, pulmonary, gastrointestinal, urogenital, musculoskeletal, hematologic, mental, and neurologic conditions and cancer. A total of 3,676,694 males and 3,701,904 females were followed up for 101.7 million person-years. During the 19-year follow-up period, 1,034,273 persons (14.0%) died. For 37 of the 39 selected medical conditions, mortality rates were larger and life expectancy shorter compared to the Danish general population. For these 37 disorders, MRRs ranged from 1.09 (95% confidence interval [CI]: 1.09 to 1.10) for vision problems to 7.85 (7.77 to 7.93) for chronic liver disease, while LYLs ranged from 0.31 (0.14 to 0.47) years (approximately 16 weeks) for allergy to 17.05 (16.95 to 17.15) years for chronic liver disease. Adjustment for air pollution had very little impact on the estimates; however, a limitation of the study is the possibility that the association between the different disorders and mortality could be explained by other underlying factors associated with both the disorder and mortality. CONCLUSIONS: In this study, we show estimates of incidence, age of onset, age of death, and mortality metrics (both MRRs and LYLs) for a comprehensive range of disorders. The interactive data visualization site (https://nbepi.com/atlas) allows more fine-grained analysis of the link between a range of disorders and key mortality estimates.

Road and railway noise and risk for breast cancer: A nationwide study covering Denmark.

OBJECTIVE: Previous studies have suggested that transportation noise may increase risk for breast cancer, but existing literature is scarce and inconclusive. We aimed to investigate associations between road traffic and railway noise and risk for breast cancer across the entire Danish female population. METHODS: For all 2.8 million residential addresses across Denmark, we modelled road and railway noise at the most and least exposed façades for the period 1990-2017. We calculated 10-year time-weighted mean noise exposure for 1.8 million women aged >35 years, of whom 66,006 developed breast cancer during follow-up from 2000 to 2017. We analysed data using Cox proportional hazards models with noise exposure included as 10-year running means and adjusted for a number of individual and area-level socioeconomic co-variates and air pollution with fine particles estimated for all addresses. RESULTS: For exposures at the least exposed façade, we found that a 10 dB increase in 10-year time-weighted noise was associated with incidence rate ratios (IRRs) and 95% confidence intervals (CI) for breast cancer of 1.032 (1.019-1.046) for road noise and 1.023 (0.993-1.053) for railway noise. For exposures at the most exposed façade, the IRRs (95% CIs) were 1.012 (1.002-1.022) for road noise and 1.020 (1.001-1.039) for railway noise. Associations were strongest among women with human epidermal growth factor receptor 2 negative breast cancer. CONCLUSIONS: Road traffic and railway noise were associated with higher risk for breast cancer, especially noise at the least exposed façade, which is a proxy for noise exposure during sleep.

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.

'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.

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.

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, PM2.5, 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 PM2.5 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.

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.

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.

External costs of atmospheric Pb emissions: valuation of neurotoxic impacts due to inhalation.

BACKGROUND: The Impact Pathway Approach (IPA) is an innovative methodology to establish links between emissions, related impacts and monetary estimates. Only few attempts have so far been presented regarding emissions of metals; in this study the external costs of airborne lead (Pb) emissions are assessed using the IPA. Exposure to Pb is known to provoke impacts especially on children's cognition. As cognitive abilities (measured as IQ, intelligence quotient) are known to have implications for lifetime income, a pathway can be established leading from figures for Pb emissions to the implied loss in earnings, and on this basis damage costs per unit of Pb emission can be assessed. METHODS: Different types of models are here linked. It is relatively straightforward to establish the relationship between Pb emissions and consequent increase in air-Pb concentration, by means of a Gaussian plume dispersion model (OML). The exposed population can then be modelled by linking the OML-output to population data nested in geo-referenced grid cells. Less straightforward is to establish the relationship between exposure to air-Pb concentrations and the resulting blood-Pb concentration. Here an Age-Dependent Biokinetic Model (ADBM) for Pb is applied. On basis of previous research which established links between increases in blood-Pb concentrations during childhood and resulting IQ-loss we arrive at our results. RESULTS: External costs of Pb airborne emissions, even at low doses, in our site are in the range of 41-83 euro/kg emitted Pb, depending on the considered meteorological year. This estimate applies only to the initial effects of air-Pb, as our study does not address the effects due to the Pb environmental-accumulation and to the subsequent Pb re-exposure. These are likely to be between one and two orders of magnitude higher. CONCLUSIONS: Biokinetic modelling is a novel tool not previously included when applying the IPA to explore impacts of Pb emissions and related external costs; it allows for more fine-tuned, age-dependent figures for the external costs from low-dose exposure. Valuation of additional health effects and impacts e.g. due to exposure via ingestion appear to be feasible when extending the insights from the present pilot study.

The effect of nitrogen deposition on the species richness of acid grasslands in Denmark: a comparison with a study performed on a European scale.

The effect of atmospheric nitrogen deposition on the species richness of acid grasslands was investigated by combining data from a large Danish monitoring program with a large European data set, where a significant non-linear negative effect of nitrogen deposition had been demonstrated (Stevens et al., 2010). The nitrogen deposition range in Denmark is relatively small and when only considering the Danish data a non-significant decrease in the species richness with nitrogen deposition was observed. However, when both data sets were combined, then the conclusion of the European survey was further corroborated by the results of the Danish monitoring. Furthermore, by combining the two data sets a more comprehensive picture of the threats to the biodiversity of acid grasslands emerge; i.e., species richness in remnant patches of acid grassland in intensively cultivated agricultural landscapes is under influence not only from nitrogen deposition, but also from current and historical land use.