Search

Background: Long-term exposure to road traffic noise is associated with cardiovascular disease, but the evidence on respiratory diseases is just emerging. We aimed to examine the association between long-term exposure to road traffic noise and the incidence of acute lower respiratory infections (ALRIs) in adults. Methods: We followed 23,141 female nurses (age ≥ 44 years) from the Danish Nurse Cohort from baseline (1993 or 1999) to their first hospital contact (inpatient, outpatient, or emergency room) for ALRI, death, emigration or the end of 2015. The residential annual mean levels of road traffic noise (Lden) during the follow-up were estimated using the Nord2000 model. We applied time-varying Cox models to estimate the association of 3-year mean exposure to Lden with ALRIs incidence and piecewise analysis to estimate the threshold of Lden. We examined the robustness of the results by adjusting for residential exposure to air pollution, and the effect modification by attained age, socioeconomic status (SES), comorbidity, and lifestyle. Results: During 18.5 years of follow-up, 2,004 nurses developed ALRIs. In a linear model, we detected a statistically significant positive association between Lden and ALRI, with a hazard ratio (HR) of 1.11 (95 % confidence interval (CI): 1.04, 1.17) per 9.2 dB (interquartile range, IQR). We observed non-linear association with a threshold at 57 dB, above which the HR was 1.25 (95 % CI: 1.09, 1.43) per IQR. Further adjustment for PM2.5 reduced the HRs slightly to 1.21 (95 % CI: 1.04, 1.40). The associations were stronger for nurses with asthma, and in those with lowest SES. Conclusion: We present novel findings in support of the association between long-term exposure to road traffic noise and ALRIs, independent of air pollution, suggesting noise as a risk factor for infectious respiratory diseases.

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

Background: Environmental noise is an important environmental exposure that can affect health. An association between transportation noise and breast cancer incidence has been suggested, although current evidence is limited. We investigated the pooled association between long-term exposure to transportation noise and breast cancer incidence. Methods: Pooled data from eight Nordic cohorts provided a study population of 111,492 women. Road, railway, and aircraft noise were modelled at residential addresses. Breast cancer incidence (all, estrogen receptor (ER) positive, and ER negative) was derived from cancer registries. Hazard ratios (HR) were estimated using Cox Proportional Hazards Models, adjusting main models for sociodemographic and lifestyle variables together with long-term exposure to air pollution. Results: A total of 93,859 women were included in the analyses, of whom 5,875 developed breast cancer. The median (5th–95th percentile) 5-year residential road traffic noise was 54.8 (40.0–67.8) dB Lden, and among those exposed, the median railway noise was 51.0 (41.2–65.8) dB Lden. We observed a pooled HR for breast cancer (95 % confidence interval (CI)) of 1.03 (0.99–1.06) per 10 dB increase in 5-year mean exposure to road traffic noise, and 1.03 (95 % CI: 0.96–1.11) for railway noise, after adjustment for lifestyle and sociodemographic covariates. HRs remained unchanged in analyses with further adjustment for PM2.5 and attenuated when adjusted for NO2 (HRs from 1.02 to 1.01), in analyses using the same sample. For aircraft noise, no association was observed. The associations did not vary by ER status for any noise source. In analyses using

Background: The link between exposure to ambient air pollution and mortality from cardiorespiratory diseases is well established, while evidence on neurodegenerative disorders including Parkinson’s Disease (PD) remains limited. Objective: We examined the association between long-term exposure to ambient air pollution and PD mortality in seven European cohorts. Methods: Within the project ‘Effects of Low-Level Air Pollution: A Study in Europe’ (ELAPSE), we pooled data from seven cohorts among six European countries. Annual mean residential concentrations of fine particulate matter (PM2.5), nitrogen dioxide (NO2), black carbon (BC), and ozone (O3), as well as 8 PM2.5 components (copper, iron, potassium, nickel, sulphur, silicon, vanadium, zinc), for 2010 were estimated using Europe-wide hybrid land use regression models. PD mortality was defined as underlying cause of death being either PD, secondary Parkinsonism, or dementia in PD. We applied Cox proportional hazard models to investigate the associations between air pollution and PD mortality, adjusting for potential confounders. Results: Of 271,720 cohort participants, 381 died from PD during 19.7 years of follow-up. In single-pollutant analyses, we observed positive associations between PD mortality and PM2.5 (hazard ratio per 5 µg/m3: 1.25; 95% confidence interval: 1.01–1.55), NO2 (1.13; 0.95–1.34 per 10 µg/m3), and BC (1.12; 0.94–1.34 per 0.5 × 10-5m-1), and a negative association with O3 (0.74; 0.58–0.94 per 10 µg/m3). Associations of PM2.5, NO2, and BC with PD mortality were linear without apparent lower thresholds. In two-pollutant models, associations with PM2.5 remained robust when adjusted for NO2 (1.24; 0.95–1.62) or BC (1.28; 0.96–1.71), whereas associations with NO2 or BC attenuated to null. O3 associations remained negative, but no longer statistically significant in models with PM2.5. We detected suggestive positive associations with the potassium component of PM2.5. Conclusion: Long-term exposure to PM2.5, at levels well below current EU air pollution limit values, may contribute to PD mortality.

Abstract 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 (Lden [dB]) and air pollutants (particulate matter with diameter

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 (PM2.5), 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.

Hyperlocal air quality maps are becoming increasingly common, as they provide useful insights into the spatial variation and sources of air pollutants. In this study, we produced several high-resolution concentration maps to assess the spatial differences of three traffic-related pollutants, Nitrogen dioxide (NO2), Black Carbon (BC) and Ultrafine Particles (UFP), in Amsterdam, the Netherlands, and Copenhagen, Denmark. All maps were based on a mixed-effect model approach by using state-of-the-art mobile measurements conducted by Google Street View (GSV) cars, during October 2018 – March 2020, and Land-use Regression (LUR) models based on several land-use and traffic predictor variables.We then explored the concentration ratio between the different normalised pollutants to understand possible contributing sources to the observed hyperlocal variations. The maps developed in this work reflect, (i) expected elevated pollution concentrations along busy roads, and (ii) similar concentration patterns on specific road types, e.g., motorways, for both cities. In the ratio maps, we observed a clear pattern of elevated concentrations of UFP near the airport in both cities, compared to BC and NO2.This is the first study to produce hyperlocal maps for BC and UFP using high-quality mobile measurements. These maps are important for policymakers and health-effect studies, trying to disentangle individual effects of key air pollutants of interest (e.g., UFP).

Ambient air pollution is an established risk factor for premature mortality from chronic cardiovascular, respiratory and metabolic diseases, while evidence on neurodegenerative diseases and psychiatric disorders remains limited. We examined the association between long-term exposure to air pollution and mortality from dementia, psychiatric disorders, and suicide in seven European cohorts. Within the multicenter project ‘Effects of Low-Level Air Pollution: A Study in Europe’ (ELAPSE), we pooled data from seven European cohorts from six countries. Based on the residential addresses, annual mean levels of fine particulate matter (PM2.5), nitrogen dioxide (NO2), black carbon (BC), ozone (O3), and 8 PM2.5 components were estimated using Europe-wide hybrid land-use regression models. We applied stratified Cox proportional hazard models to investigate the associations between air pollution and mortality from dementia, psychiatric disorders, and suicide. Of 271,720 participants, 900 died from dementia, 241 from psychiatric disorders, and 164 from suicide, during a mean follow-up of 19.7 years. In fully adjusted models, we observed positive associations of NO2 (hazard ratio [HR] = 1.38; 95 % confidence interval [CI]: 1.13, 1.70 per 10 µg/m3), PM2.5 (HR = 1.29; 95 % CI: 0.98, 1.71 per 5 µg/m3), and BC (HR = 1.37; 95 % CI: 1.11, 1.69 per 0.5 × 10−5/m) with psychiatric disorders mortality, as well as with suicide (NO2: HR = 1.13 [95 % CI: 0.92, 1.38]; PM2.5: HR = 1.19 [95 % CI: 0.76, 1.87]; BC: HR = 1.08 [95 % CI: 0.87, 1.35]), and no association with dementia mortality. We did not detect any positive associations of O3 and 8 PM2.5 components with any of the three mortality outcomes. Long-term exposure to NO2, PM2.5, and BC may lead to premature mortality from psychiatric disorders and suicide.

Background: The majority of studies have shown higher greenness exposure associated with reduced mortality risks, but few controlled for spatially correlated air pollution and traffic noise exposures. We aim to address this research gap in the ELAPSE pooled cohort. Methods: Mean Normalized Difference Vegetation Index (NDVI) in a 300-m grid cell and 1-km radius were assigned to participants’ baseline home addresses as a measure of surrounding greenness exposure. We used Cox proportional hazards models to estimate the association of NDVI exposure with natural-cause and cause-specific mortality, adjusting for a number of potential confounders including socioeconomic status and lifestyle factors at individual and area-levels. We further assessed the associations between greenness exposure and mortality after adjusting for fine particulate matter (PM2.5), nitrogen dioxide (NO2) and road traffic noise. Results: The pooled study population comprised 327,388 individuals who experienced 47,179 natural-cause deaths during 6,374,370 person-years of follow-up. The mean NDVI in the pooled cohort was 0.33 (SD 0.1) and 0.34 (SD 0.1) in the 300-m grid and 1-km buffer. In the main fully adjusted model, 0.1 unit increment of NDVI inside 300-m grid was associated with 5% lower risk of natural-cause mortality (Hazard Ratio (HR) 0.95 (95% CI: 0.94, 0.96)). The associations attenuated after adjustment for air pollution [HR (95% CI): 0.97 (0.96, 0.98) adjusted for PM2.5; 0.98 (0.96, 0.99) adjusted for NO2]. Additional adjustment for traffic noise hardly affected the associations. Consistent results were observed for NDVI within 1-km buffer. After adjustment for air pollution, NDVI was inversely associated with diabetes, respiratory and lung cancer mortality, yet with wider 95% confidence intervals. No association with cardiovascular mortality was found. Conclusions: We found a significant inverse association between surrounding greenness and natural-cause mortality, which remained after adjusting for spatially correlated air pollution and traffic noise.

Poor ventilation and polluting cooking fuels in low-income homes cause high exposure, yet relevant global studies are limited. We assessed exposure to in-kitchen particulate matter (PM2.5 and PM10) employing similar instrumentation in 60 low-income homes across 12 cities: Dhaka (Bangladesh); Chennai (India); Nanjing (China); Medellín (Colombia); São Paulo (Brazil); Cairo (Egypt); Sulaymaniyah (Iraq); Addis Ababa (Ethiopia); Akure (Nigeria); Blantyre (Malawi); Dar-es-Salaam (Tanzania) and Nairobi (Kenya). Exposure profiles of kitchen occupants showed that fuel, kitchen volume, cooking type and ventilation were the most prominent factors affecting in-kitchen exposure. Different cuisines resulted in varying cooking durations and disproportional exposures. Occupants in Dhaka, Nanjing, Dar-es-Salaam and Nairobi spent > 40% of their cooking time frying (the highest particle emitting cooking activity) compared with ∼ 68% of time spent boiling/stewing in Cairo, Sulaymaniyah and Akure. The highest average PM2.5 (PM10) concentrations were in Dhaka 185 ± 48 (220 ± 58) μg m−3 owing to small kitchen volume, extensive frying and prolonged cooking compared with the lowest in Medellín 10 ± 3 (14 ± 2) μg m−3. Dual ventilation (mechanical and natural) in Chennai, Cairo and Sulaymaniyah reduced average in-kitchen PM2.5 and PM10 by 2.3- and 1.8-times compared with natural ventilation (open doors) in Addis Ababa, Dar-es-Salam and Nairobi. Using charcoal during cooking (Addis Ababa, Blantyre and Nairobi) increased PM2.5 levels by 1.3- and 3.1-times compared with using natural gas (Nanjing, Medellin and Cairo) and LPG (Chennai, Sao Paulo and Sulaymaniyah), respectively. Smaller-volume kitchens (

Abstract Background Inconclusive evidence has suggested a possible link between air pollution and central nervous system (CNS) tumors. We investigated a range of air pollutants in relation to types of CNS tumors. Methods We identified all (n = 21,057) intracranial tumors in brain, meninges and cranial nerves diagnosed in Denmark between 1989 and 2014 and matched controls on age, sex and year of birth. We established personal 10-year mean residential outdoor exposure to particulate matter

Summary: Background: Long-term exposure to ambient air pollution has been associated with premature mortality, but associations at concentrations lower than current annual limit values are uncertain. We analysed associations between low-level air pollution and mortality within the multicentre study Effects of Low-Level Air Pollution: A Study in Europe (ELAPSE). Methods: In this multicentre longitudinal study, we analysed seven population-based cohorts of adults (age ≥30 years) within ELAPSE, from Belgium, Denmark, England, the Netherlands, Norway, Rome (Italy), and Switzerland (enrolled in 2000–11; follow-up until 2011–17). Mortality registries were used to extract the underlying cause of death for deceased individuals. Annual average concentrations of fine particulate matter (PM2·5), nitrogen dioxide (NO2), black carbon, and tropospheric warm-season ozone (O3) from Europe-wide land use regression models at 100 m spatial resolution were assigned to baseline residential addresses. We applied cohort-specific Cox proportional hazard models with adjustment for area-level and individual-level covariates to evaluate associations with non-accidental mortality, as the main outcome, and with cardiovascular, non-malignant respiratory, and lung cancer mortality. Subset analyses of participants living at low pollutant concentrations (as per predefined values) and natural splines were used to investigate the concentration-response function. Cohort-specific effect estimates were pooled in a random-effects meta-analysis. Findings: We analysed 28 153 138 participants contributing 257 859 621 person-years of observation, during which 3 593 741 deaths from non-accidental causes occurred. We found significant positive associations between non-accidental mortality and PM2·5, NO2, and black carbon, with a hazard ratio (HR) of 1·053 (95% CI 1·021–1·085) per 5 μg/m3 increment in PM2·5, 1·044 (1·019–1·069) per 10 μg/m3 NO2, and 1·039 (1·018–1·059) per 0·5 × 10−5/m black carbon. Associations with PM2·5, NO2, and black carbon were slightly weaker for cardiovascular mortality, similar for non-malignant respiratory mortality, and stronger for lung cancer mortality. Warm-season O3 was negatively associated with both non-accidental and cause-specific mortality. Associations were stronger at low concentrations: HRs for non-accidental mortality at concentrations lower than the WHO 2005 air quality guideline values for PM2·5 (10 μg/m3) and NO2 (40 μg/m3) were 1·078 (1·046–1·111) per 5 μg/m3 PM2·5 and 1·049 (1·024–1·075) per 10 μg/m3 NO2. Similarly, the association between black carbon and non-accidental mortality was highest at low concentrations, with a HR of 1·061 (1·032–1·092) for exposure lower than 1·5× 10−5/m, and 1·081 (0·966–1·210) for exposure lower than 1·0× 10−5/m. Interpretation: Long-term exposure to concentrations of PM2·5 and NO2 lower than current annual limit values was associated with non-accidental, cardiovascular, non-malignant respiratory, and lung cancer mortality in seven large European cohorts. Continuing research on the effects of low concentrations of air pollutants is expected to further inform the process of setting air quality standards in Europe and other global regions. Funding: Health Effects Institute.

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

Air pollutants such as NO2 and PM2.5 have consistently been linked to mortality, but only few previous studies have addressed associations with long-term exposure to black carbon (BC) and ozone (O3).We investigated the association between PM2.5, PM10, BC, NO2, and O3 and mortality in a Danish cohort of 49,564 individuals who were followed up from enrollment in 1993–1997 through 2015. Residential address history from 1979 onwards was combined with air pollution exposure obtained by the state-of-the-art, validated, THOR/AirGIS air pollution modelling system, and information on residential traffic noise exposure, lifestyle and socio-demography.We observed higher risks of all-cause as well as cardiovascular disease (CVD) mortality with higher long-term exposure to PM2.5, PM10, BC, and NO2. For PM2.5 and CVD mortality, a hazard ratio (HR) of 1.29 (95% CI: 1.13–1.47) per 5 μg/m3 was observed, and correspondingly HRs of 1.16 (95% CI: 1.05–1.27) and 1.11 (95% CI: 1.04–1.17) were observed for BC (per 1 μg/m3) and NO2 (per 10 μg/m3), respectively. Adjustment for noise gave slightly lower estimates for the air pollutants and CVD mortality. Inverse relationships were observed for O3. None of the investigated air pollutants were related to risk of respiratory mortality. Stratified analyses suggested that the elevated risks of CVD and all-cause mortality in relation to long-term PM, NO2 and BC exposure were restricted to males.This study supports a role of PM, BC, and NO2 in all-cause and CVD mortality independent of road traffic noise exposure. Keywords: Particulate matter, NO2, Black carbon, Ozone, CVD, Mortality, Epidemiology

Background: We evaluated methods for the analysis of multi-level survival data using a pooled dataset of 14 cohorts participating in the ELAPSE project investigating associations between residential exposure to low levels of air pollution (PM2.5 and NO2) and health (natural-cause mortality and cerebrovascular, coronary and lung cancer incidence). Methods: We applied five approaches in a multivariable Cox model to account for the first level of clustering corresponding to cohort specification: (1) not accounting for the cohort or using (2) indicator variables, (3) strata, (4) a frailty term in frailty Cox models, (5) a random intercept under a mixed Cox, for cohort identification. We accounted for the second level of clustering due to common characteristics in the residential area by (1) a random intercept per small area or (2) applying variance correction. We assessed the stratified, frailty and mixed Cox approach through simulations under different scenarios for heterogeneity in the underlying hazards and the air pollution effects. Results: Effect estimates were stable under approaches used to adjust for cohort but substantially differed when no adjustment was applied. Further adjustment for the small area grouping increased the effect estimates’ standard errors. Simulations confirmed identical results between the stratified and frailty models. In ELAPSE we selected a stratified multivariable Cox model to account for between-cohort heterogeneity without adjustment for small area level, due to the small number of subjects and events in the latter. Conclusions: Our study supports the need to account for between-cohort heterogeneity in multi-center collaborations using pooled individual level data.

Telomere length (TL) is a biomarker of biological aging that may be affected by prenatal exposure to air pollution. The aim of this study was to assess the association between prenatal exposure to air pollution and TL in maternal blood cells (leukocytes), placenta and umbilical cord blood cells, sampled immediately after birth in 296 Danish mother-child pairs from a birth cohort. Exposure data was obtained using the high-resolution and spatial–temporal air pollution modeling system DEHM-UBM-AirGIS for PM2.5, PM10, SO2, NH4+, black carbon (BC), organic carbon (OC), CO, O3, NO2, and NOx at residential and occupational addresses of the participating women for the full duration of the pregnancy. The association between prenatal exposure to air pollutants and TL was investigated using distributed lag models. There were significant and positive associations between TL in umbilical cord blood cells and prenatal exposure to BC, OC, NO2, NOx, CO, and O3 during the second trimester. TL in umbilical cord blood was significantly and inversely associated with prenatal exposure to PM2.5, BC, OC, SO2, NH4+, CO and NO2 during the third trimester. There were similar inverse associations between TL from umbilical cord blood cells and air pollution exposure at the residential and occupational addresses. There were weaker or no associations between air pollution exposure and TL in placenta tissue and maternal blood cells. In conclusion, both the second and third trimesters of pregnancy are shown to be sensitive windows of exposure to air pollution affecting fetal TL.

Background/aim: Ambient air pollution has been associated with lung cancer, but the shape of the exposure-response function - especially at low exposure levels - is not well described. The aim of this study was to address the relationship between long-term low-level air pollution exposure and lung cancer incidence. Methods: The “Effects of Low-level Air Pollution: a Study in Europe” (ELAPSE) collaboration pools seven cohorts from across Europe. We developed hybrid models combining air pollution monitoring, land use data, satellite observations, and dispersion model estimates for nitrogen dioxide (NO2), fine particulate matter (PM2.5), black carbon (BC), and ozone (O3) to assign exposure to cohort participants’ residential addresses in 100 m by 100 m grids. We applied stratified Cox proportional hazards models, adjusting for potential confounders (age, sex, calendar year, marital status, smoking, body mass index, employment status, and neighborhood-level socio-economic status). We fitted linear models, linear models in subsets, Shape-Constrained Health Impact Functions (SCHIF), and natural cubic spline models to assess the shape of the association between air pollution and lung cancer at concentrations below existing standards and guidelines. Results: The analyses included 307,550 cohort participants. During a mean follow-up of 18.1 years, 3956 incident lung cancer cases occurred. Median (Q1, Q3) annual (2010) exposure levels of NO2, PM2.5, BC and O3 (warm season) were 24.2 µg/m3 (19.5, 29.7), 15.4 µg/m3 (12.8, 17.3), 1.6 10−5m−1 (1.3, 1.8), and 86.6 µg/m3 (78.5, 92.9), respectively. We observed a higher risk for lung cancer with higher exposure to PM2.5 (HR: 1.13, 95% CI: 1.05, 1.23 per 5 µg/m3). This association was robust to adjustment for other pollutants. The SCHIF, spline and subset analyses suggested a linear or supra-linear association with no evidence of a threshold. In subset analyses, risk estimates were clearly elevated for the subset of subjects with exposure below the EU limit value of 25 µg/m3. We did not observe associations between NO2, BC or O3 and lung cancer incidence. Conclusions: Long-term ambient PM2.5 exposure is associated with lung cancer incidence even at concentrations below current EU limit values and possibly WHO Air Quality Guidelines.

Background: Air pollution has been suggested as a risk factor for chronic obstructive pulmonary disease (COPD), but evidence is sparse and inconsistent. Objectives: We examined the association between long-term exposure to low-level air pollution and COPD incidence. Methods: Within the ‘Effects of Low-Level Air Pollution: A Study in Europe’ (ELAPSE) study, we pooled data from three cohorts, from Denmark and Sweden, with information on COPD hospital discharge diagnoses. Hybrid land use regression models were used to estimate annual mean concentrations of particulate matter with a diameter

Background: Air pollution is an established carcinogen. Evidence for an association with brain tumors is, however, inconclusive. We investigated if individual particulate matter constituents were associated with brain tumor risk. Methods: From comprehensive national registers, we identified all (n = 12 928) brain tumor cases, diagnosed in Denmark in the period 1989–2014, and selected 22 961 controls, matched on age, sex and year of birth. We established address histories and estimated 10-year mean residential outdoor concentrations of particulate matter

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 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 PM2.5, PM10, 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 (Lden) were estimated using the Nord2000 model. We examined associations between the three-year running mean of PM2.5, 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 PM2.5 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 PM2.5

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

Noise from wind turbines (WTs) has been reported more annoying than traffic noise at similar levels, and concerns have been raised about whether WT noise (WTN) can increase risk for cardiovascular disease. We aimed to investigate if long-term exposure to WTN increases risk for hypertension, estimated as redemption of prescriptions for antihypertensive drugs. We identified all Danish dwellings within a radius of 20 WT heights from a WT and 25% randomly selected dwellings within 20–40 WT heights radius. Using data on WT type and hourly wind conditions at each WT, we estimated hourly outdoor (10–10,000 Hz) and low frequency (LF: 10–160 Hz) indoor WTN for all dwellings, and aggregated it as long-term nighttime running means. From nationwide registries, we identified 535,675 persons age 25–85 years living in these dwellings for >1 year from 1996 to 2013, of whom 83,729 fulfilled our case definition of redeeming ≥2 prescriptions and ≥180 defined daily doses of antihypertensive drugs within a year. Data were analyzed using Poisson regression according to categories of WTN exposure and adjustment for individual and area-level covariates. We found no associations between 5-year mean exposure to WTN during night and redemption of antihypertensives, with hazard ratios (HR) of 0.91 (95% confidence intervals (CI): 0.78–1.06) for outdoor WTN ≥ 42 dB(A) and of 1.06 (CI: 0.83–1.35) for indoor LF WTN ≥ 15 dB(A) when compared to the reference WTN levels (

OBJECTIVES: Exposure to traffic noise and air pollution is suspected to increase susceptibility to viral infections – the main triggering factor for febrile seizures. No studies have examined these two exposures in relation to febrile seizures. We aimed to investigate whether exposure to road traffic noise and air pollution are associated with risk of febrile seizures in childhood. METHODS: From our study base of 51 465 singletons from a national birth cohort, we identified 2175 cases with febrile seizures using a nationwide registry. Residential address history from conception to six years of age were found in national registers, and road traffic noise (L_den) and air pollution (NO_2) were modeled for all addresses. Analyses were done using Cox proportional hazard model with adjustment for potential confounders, including mutual exposure adjustment. RESULTS: An interquartile range (IQR) increase in childhood exposure to road traffic noise and air pollution was associated with an 11% [incidence rate ratio (IRR) 1.11, 95% confidence interval (CI) 1.04–1.19) and 5% (IRR 1.05, 95% CI 1.02–1.07) higher risk for febrile seizures, respectively, after adjustment for potential confounders. Weaker tendencies were seen for pregnancy exposure. In models with mutual exposure adjustment, the estimates were slightly lower, with IRR of 1.08 (95% CI 1.00–1.16) and 1.03 (95% CI 0.99–1.06) per IQR increase in childhood exposure to road traffic noise and air pollution, respectively. CONCLUSIONS: This study suggests that residential exposure to road traffic noise and air pollution is associated with higher risk for febrile seizures.

Studies on health effects of long-term exposure to specific PM2.5 constituents are few. Previous studies have reported an association between black carbon (BC) exposure and cardiovascular diseases (CVD) and a few studies have found an association between sulfate exposure and mortality. These studies, however, relied mainly on exposure data from centrally located air-monitoring stations, which is a crude approximation of personal exposure.We focused on specific chemical constituents of PM2.5, i.e. elemental and primary organic carbonaceous particles (BC/OC), sea salt, secondary inorganic aerosols (SIA, i.e. NO3–, NH4+, and SO42-), and secondary organic aerosols (SOA), in relation to all-cause, CVD and respiratory disease mortality.We followed a Danish cohort of 49,564 individuals from enrollment in 1993–1997 through 2015. We combined residential address history from 1979 onwards with mean annual air pollution concentrations obtained by the AirGIS air pollution modelling system, lifestyle information from baseline questionnaires and socio-demography obtained by register linkage.During 895,897 person-years of follow-up, 10,193 deaths from all causes occurred – of which 2319 were CVD-related and 870 were related to respiratory disease. The 15-year time-weighted average concentrations of PM2.5, BC/OC, sea salt, SIA and SOA were 13.8, 2.8, 3.4, 4.9, and 0.3 µg/m3, respectively. For all-cause mortality, a higher risk was observed with higher exposure to PM2.5, BC/OC and SOA with adjusted hazard ratios of 1.03 (95% confidence intervals: 1.01, 1.05), 1.06 (1.03, 1.09), and 1.08 (1.03, 1.13) per interquartile range, respectively. The associations for BC/OC and SOA remained after adjustment for PM2.5 in two-pollutant models. For CVD mortality, we observed elevated risks with higher exposure to PM2.5, BC/OC and SIA. The results showed no clear relationship between sea salt and mortality.In this study, we observed a relationship between long-term exposure to PM2.5, BC/OC, and SOA and all-cause mortality and between PM2.5, BC/OC, and SIA and CVD mortality. Keywords: Particulate matter chemical constituents, Carbonaceous particles, Secondary inorganic aerosols, Secondary organic aerosols, Sea salt, Mortality

Empirical spatial air pollution models have been applied extensively to assess exposure in epidemiological studies with increasingly sophisticated and complex statistical algorithms beyond ordinary linear regression. However, different algorithms have rarely been compared in terms of their predictive ability.This study compared 16 algorithms to predict annual average fine particle (PM2.5) and nitrogen dioxide (NO2) concentrations across Europe. The evaluated algorithms included linear stepwise regression, regularization techniques and machine learning methods. Air pollution models were developed based on the 2010 routine monitoring data from the AIRBASE dataset maintained by the European Environmental Agency (543 sites for PM2.5 and 2399 sites for NO2), using satellite observations, dispersion model estimates and land use variables as predictors. We compared the models by performing five-fold cross-validation (CV) and by external validation (EV) using annual average concentrations measured at 416 (PM2.5) and 1396 sites (NO2) from the ESCAPE study. We further assessed the correlations between predictions by each pair of algorithms at the ESCAPE sites.For PM2.5, the models performed similarly across algorithms with a mean CV R2 of 0.59 and a mean EV R2 of 0.53. Generalized boosted machine, random forest and bagging performed best (CV R2~0.63; EV R2 0.58–0.61), while backward stepwise linear regression, support vector regression and artificial neural network performed less well (CV R2 0.48–0.57; EV R2 0.39–0.46). Most of the PM2.5 model predictions at ESCAPE sites were highly correlated (R2 > 0.85, with the exception of predictions from the artificial neural network). For NO2, the models performed even more similarly across different algorithms, with CV R2s ranging from 0.57 to 0.62, and EV R2s ranging from 0.49 to 0.51. The predicted concentrations from all algorithms at ESCAPE sites were highly correlated (R2 > 0.9). For both pollutants, biases were low for all models except the artificial neural network. Dispersion model estimates and satellite observations were two of the most important predictors for PM2.5 models whilst dispersion model estimates and traffic variables were most important for NO2 models in all algorithms that allow assessment of the importance of variables.Different statistical algorithms performed similarly when modelling spatial variation in annual average air pollution concentrations using a large number of training sites. Keywords: Land use regression, Fine particles, Nitrogen dioxide, Machine learning

Aims/hypothesis: It has been suggested that air pollution may increase the risk of type 2 diabetes but data on particulate matter with diameter

This cross-sectional study investigated the relationship between exposure to airborne indoor and outdoor particulate matter (PM) and cardiovascular and respiratory health in a population-based sample of 58 residences in Copenhagen, Denmark. Over a 2-day period indoor particle number concentrations (PNC, 10–300 nm) and PM2.5 (aerodynamic diameter

The major emission source of primary PM2.5 in many Nordic countries is wood burning for domestic heating. Though direct measurements of wood burning emissions are possible under controlled conditions, emission inventories for urban scale domestic heating are difficult to calculate and remain uncertain. As an alternative method for estimating these emissions, this paper makes use of ambient air measurements, chemical analysis of filter samples, receptor models, dispersion models, and simple inverse modelling methods to infer the emission strengths. A comparison of dispersion models with receptor models indicates that the dispersion models tend to overestimate the contribution from wood burning. The inverse modelling results are found to agree with those from the receptor modelling. Though both the receptor and inverse modelling point to an overestimation of the wood burning emissions of PM2.5, it is not possible to assign this solely to errors in the emissions inventory as a dispersion model error can be significant. It is recommended to improve plume rise and urban canopy meteorological descriptions in the dispersion models before these models are of sufficient quality to allow quantitative assessments of emission inventories.

Few studies have investigated the association between objectively measured traffic noise and health-related quality of life. However, as traffic noise has been associated with both cardiovascular disease and diabetes, and health-issues including sleeping problems, annoyance, and stress, it seems plausible that traffic noise is associated with health-related quality of life.Between 1999 and 2002, a cohort of 38,964 Danes filled in the short form-36 (SF-36) questionnaire. Residential exposure to road traffic and railway noise was calculated for all historical addresses for 10 years preceding the SF-36, using the Nordic prediction method. Associations between noise exposure and SF-36 summary scales and the eight sub-scales were calculated using general linear models, adjusted for age, sex, socioeconomic status, and lifestyle.Models adjusted for age, sex and socioeconomic factors showed that a 10 dB higher road traffic noise 1 year preceding SF-36 assessment was associated with a 0.14 lower mental component summary (MCS) score (95% confidence interval (CI) -0.26, -0.01). However, further adjustment for lifestyle factors (smoking, alcohol, and waist circumference) attenuated the association: (-0.08 (95% CI: -0.20, 0.04)). Exposure to more than 55 dB of railway noise in the same time period was borderline significantly associated with lower MCS. The physical component summary was not associated with traffic noise.The present study suggests a weak association between traffic noise exposure and the mental health component score of SF-36, which may operate through lifestyle. The magnitude of effect was, however, not clinically relevant.

Cardiovascular disease is the number one cause of death globally and air pollution can be a contributing cause. Acute myocardial infarction and cardiac arrest are frequent manifestations of coronary heart disease. The objectives of the study were to investigate the association between 4 657 out-of-hospital cardiac arrests (OHCA) and hourly and daily outdoor levels of PM(10), PM(2.5), coarse fraction of PM (PM(10-2.5)), ultrafine particle proxies, NO(x), NO(2), O(3) and CO in Copenhagen, Denmark, for the period 2000-2010. Susceptible groups by age and sex was also investigated. A case-crossover design was applied. None of the hourly lags of any of the pollutants were significantly associated with OHCA events. The strongest association with OHCA events was observed for the daily lag4 of PM(2.5), lag3 of PM(10), lag3 of PM(10-2.5), lag3 of NO(x) and lag4 of CO. An IQR increase of PM(2.5) and PM(10) was associated with a significant increase of 4% (95% CI: 0%; 9%) and 5% (95% CI: 1%; 9%) in OHCA events with 3 days lag, respectively. None of the other daily lags or other pollutants was significantly associated with OHCA events. Adjustment for O(3) slightly increased the association between OHCA and PM(2.5) and PM(10). No susceptible groups were identified.

One of the key climate change factors, temperature, has potentially grave implications for human health. We report the first attempt to investigate the association between the daily 3-hour maximum apparent temperature (Tapp(max)) and respiratory (RD), cardiovascular (CVD), and cerebrovascular (CBD) emergency hospital admissions in Copenhagen, controlling for air pollution. The study period covered 1 January 2002-31 December 2006, stratified in warm and cold periods. A case-crossover design was applied. Susceptibility (effect modification) by age, sex, and socio-economic status was investigated. For an IQR (8°C) increase in the 5-day cumulative average of Tapp(max), a 7% (95% CI: 1%, 13%) increase in the RD admission rate was observed in the warm period whereas an inverse association was found with CVD (-8%, 95% CI: -13%, -4%), and none with CBD. There was no association between the 5-day cumulative average of Tapp(max) during the cold period and any of the cause-specific admissions, except in some susceptible groups: a negative association for RD in the oldest age group and a positive association for CVD in men and the second highest SES group. In conclusion, an increase in Tapp(max) is associated with a slight increase in RD and decrease in CVD admissions during the warmer months.