Understanding the role of biofilms and estimation of life-span of a tire derived aggregates-based underground stormwater treatment system.

The importance of biofilm in tire derived aggregates (TDA) based underground systems has been investigated in this paper, to assess the utilization of tire waste as a cost-effective and sustainable resource for stormwater treatment. The primary objective of this study is to look into the role of biofilms in preventing metal leaching from a TDA based stormwater treatment system and to estimate the life span of a TDA based stormwater treatment system. TDA subjected to different influents to promote or limit the growth of biofilms were analyzed for their leaching and adsorption potential for fifteen different metals through 72 flushes, which is representative of roughly 9 years of TDA exposure to storm events in the upper Midwest USA. Biofilm growth on a manufacturing byproduct (wire exposed-TDA) was higher than on the traditional TDA. The presence of biofilm on TDA had a minor impact on orthophosphate adsorption as observed in a previous study conducted by the authors. However, metals such as iron, zinc and copper, which were previously a concern, had substantially lower leaching into the stored runoff. In addition, the orthophosphate removal from runoff by TDA with a biofilm through 72 flushes indicates that TDA based underground systems can have orthophosphate removal life span beyond 8-9 years. Thus, TDA with biofilms in an underground storage/infiltration chamber has the potential to establish itself as a sustainable, cost-effective, and long life-span alternative for stormwater remediation of orthophosphate pollution without leaching of metals.

Short-Term Nitrogen Dioxide Exposure and Emergency Hospital Admissions for Asthma in Children: A Case-Crossover Analysis in England.

Background: There is an increasing body of evidence associating short-term ambient nitrogen dioxide (NO2) exposure with asthma-related hospital admissions in children. However, most studies have relied on temporally resolved exposure information, potentially ignoring the spatial variability of NO2. We aimed to investigate how daily NO2 estimates from a highly resolved spatio-temporal model are associated with the risk of emergency hospital admission for asthma in children in England. Methods: We conducted a time-stratified case-crossover study including 111,766 emergency hospital admissions for asthma in children (aged 0-14 years) between 1st January 2011 and 31st December 2015 in England. Daily NO2 levels were predicted at the patients' place of residence using spatio-temporal models by combining land use data and chemical transport model estimates. Conditional logistic regression models were used to obtain the odds ratios (OR) and confidence intervals (CI) after adjusting for temperature, relative humidity, bank holidays, and influenza rates. The effect modifications by age, sex, season, area-level income deprivation, and region were explored in stratified analyses. Results: For each 10 µg/m³ increase in NO2 exposure, we observed an 8% increase in asthma-related emergency admissions using a five-day moving NO2 average (mean lag 0-4) (OR 1.08, 95% CI 1.06-1.10). In the stratified analysis, we found larger effect sizes for male (OR 1.10, 95% CI 1.07-1.12) and during the cold season (OR 1.10, 95% CI 1.08-1.12). The effect estimates varied slightly by age group, area-level income deprivation, and region. Significance: Short-term exposure to NO2 was significantly associated with an increased risk of asthma emergency admissions among children in England. Future guidance and policies need to consider reflecting certain proven modifications, such as using season-specific countermeasures for air pollution control, to protect the at-risk population.

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

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

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

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

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

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

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

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

Adopting a child perspective for exposome research on mental health and cognitive development - Conceptualisation and opportunities.

Mental disorders among children and adolescents pose a significant global challenge. The exposome framework covering the totality of internal, social and physical exposures over a lifetime provides opportunities to better understand the causes of and processes related to mental health, and cognitive functioning. The paper presents a conceptual framework on exposome, mental health, and cognitive development in children and adolescents, with potential mediating pathways, providing a possibility for interventions along the life course. The paper underscores the significance of adopting a child perspective to the exposome, acknowledging children's specific vulnerability, including differential exposures, susceptibility of effects and capacity to respond; their susceptibility during development and growth, highlighting neurodevelopmental processes from conception to young adulthood that are highly sensitive to external exposures. Further, critical periods when exposures may have significant effects on a child's development and future health are addressed. The paper stresses that children's behaviour, physiology, activity pattern and place for activities make them differently vulnerable to environmental pollutants, and calls for child-specific assessment methods, currently lacking within today's health frameworks. The importance of understanding the interplay between structure and agency is emphasized, where agency is guided by social structures and practices and vice-versa. An intersectional approach that acknowledges the interplay of social and physical exposures as well as a global and rural perspective on exposome is further pointed out. To advance the exposome field, interdisciplinary efforts that involve multiple scientific disciplines are crucial. By adopting a child perspective and incorporating an exposome approach, we can gain a comprehensive understanding of how exposures impact children's mental health and cognitive development leading to better outcomes.

Variability of the Human Serum Metabolome over 3 Months in the EXPOsOMICS Personal Exposure Monitoring Study.

Liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS) and untargeted metabolomics are increasingly used in exposome studies to study the interactions between nongenetic factors and the blood metabolome. To reliably and efficiently link detected compounds to exposures and health phenotypes in such studies, it is important to understand the variability in metabolome measures. We assessed the within- and between-subject variability of untargeted LC-HRMS measurements in 298 nonfasting human serum samples collected on two occasions from 157 subjects. Samples were collected ca. 107 (IQR: 34) days apart as part of the multicenter EXPOsOMICS Personal Exposure Monitoring study. In total, 4294 metabolic features were detected, and 184 unique compounds could be identified with high confidence. The median intraclass correlation coefficient (ICC) across all metabolic features was 0.51 (IQR: 0.29) and 0.64 (IQR: 0.25) for the 184 uniquely identified compounds. For this group, the median ICC marginally changed (0.63) when we included common confounders (age, sex, and body mass index) in the regression model. When grouping compounds by compound class, the ICC was largest among glycerophospholipids (median ICC 0.70) and steroids (0.67), and lowest for amino acids (0.61) and the O-acylcarnitine class (0.44). ICCs varied substantially within chemical classes. Our results suggest that the metabolome as measured with untargeted LC-HRMS is fairly stable (ICC > 0.5) over 100 days for more than half of the features monitored in our study, to reflect average levels across this time period. Variance across the metabolome will result in differential measurement error across the metabolome, which needs to be considered in the interpretation of metabolome results.

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

BACKGROUND: Risk factors for malignant tumours of the central nervous system (CNS) are largely unknown. METHODS: We pooled six European cohorts (N = 302,493) and assessed the association between residential exposure to nitrogen dioxide (NO2), fine particles (PM2.5), black carbon (BC), ozone (O3) and eight elemental components of PM2.5 (copper, iron, potassium, nickel, sulfur, silicon, vanadium, and zinc) and malignant intracranial CNS tumours defined according to the International Classification of Diseases ICD-9/ICD-10 codes 192.1/C70.0, 191.0-191.9/C71.0-C71.9, 192.0/C72.2-C72.5. We applied Cox proportional hazards models adjusting for potential confounders at the individual and area-level. RESULTS: During 5,497,514 person-years of follow-up (average 18.2 years), we observed 623 malignant CNS tumours. The results of the fully adjusted linear analyses showed a hazard ratio (95% confidence interval) of 1.07 (0.95, 1.21) per 10 µg/m³ NO2, 1.17 (0.96, 1.41) per 5 µg/m³ PM2.5, 1.10 (0.97, 1.25) per 0.5 10-5m-1 BC, and 0.99 (0.84, 1.17) per 10 µg/m³ O3. CONCLUSIONS: We observed indications of an association between exposure to NO2, PM2.5, and BC and tumours of the CNS. The PM elements were not consistently associated with CNS tumour incidence.

Spatial assessment of the attributable burden of disease due to transportation noise in England.

BACKGROUND: Noise pollution from transportation is one of the leading contributors to the environmental disease burden in Europe. We provide a novel assessment of spatial variations of these health impacts within a country, using England as an example. METHODS: We estimated the burden of annoyance (highly annoyed), sleep disturbance (highly sleep disturbed), ischemic heart disease (IHD), stroke, and diabetes attributable to long-term transportation noise exposures in England for the adult population in 2018 down to local authority level (average adult population: 136,000). To derive estimates, we combined literature-informed exposure-response relationships, with population data on noise exposures, disease, and mortalities. Long-term average noise exposures from road, rail and aircraft were sourced from strategic noise mapping, with a lower exposure threshold of 50 dB (decibels) Lden and Lnight. RESULTS: 40 %, 4.5 % and 4.8 % of adults in England were exposed to road, rail, and aircraft noise exceeding 50 dB Lden. We estimated close to a hundred thousand (∼97,000) disability adjusted life years (DALY) lost due to road-traffic, ∼13,000 from railway, and âˆ¼ 17,000 from aircraft noise. This excludes some noise-outcome pairs as there were too few studies available to provide robust exposure-response estimates. Annoyance and sleep disturbance accounted for the majority of the DALYs, followed by strokes, IHD, and diabetes. London, the South East, and North West regions had the greatest number of road-traffic DALYs lost, while 63 % of all aircraft noise DALYs were found in London. The strategic noise mapping did not include all roads, which may still have significant traffic flows. In sensitivity analyses using modelled noise from all roads in London, the DALYs were 1.1x to 2.2x higher. CONCLUSION: Transportation noise exposures contribute to a significant and unequal environmental disease burden in England. Omitting minor roads from the noise exposure modelling leads to underestimation of the disease burden.

Aircraft noise and cardiovascular morbidity and mortality near Heathrow Airport: A case-crossover study.

Aircraft noise causes annoyance and sleep disturbance and there is some evidence of associations between long-term exposures and cardiovascular disease (CVD). We investigated short-term associations between previous day aircraft noise and cardiovascular events in a population of 6.3 million residing near Heathrow Airport using a case-crossover design and exposure data for different times of day and night. We included all recorded hospitalisations (n = 442,442) and deaths (n = 49,443) in 2014-2018 due to CVD. Conditional logistic regression was used to estimate the ORs and adjusted for NO2 concentration, temperature, and holidays. We estimated an increase in risk for 10 dB increment in noise during the previous evening (Leve OR = 1.007, 95% CI 0.999-1.015), particularly from 22:00-23:00 h (OR = 1.007, 95% CI 1.000-1.013), and the early morning hours 04:30-06:00 h (OR = 1.012, 95% CI 1.002-1.021) for all CVD admissions, but no significant associations with day-time noise. There was effect modification by age-sex, ethnicity, deprivation, and season, and some suggestion that high noise variability at night was associated with higher risks. Our findings are consistent with proposed mechanisms for short-term impacts of aircraft noise at night on CVD from experimental studies, including sleep disturbance, increases in blood pressure and stress hormone levels and impaired endothelial function.

Does air pollution confound associations between environmental noise and cardiovascular outcomes? - A systematic review.

BACKGROUND: Exposure to environmental noise is associated with adverse health effects, but there is potential for confounding and interaction with air pollution, particularly where both exposures arise from the same source, such as transport. OBJECTIVES: To review evidence on confounding and interaction of air pollution in relation to associations between environmental noise and cardiovascular outcomes. METHODS: Papers were identified from similar reviews published in 2013 and 2015, from the systematic reviews supporting the WHO 2018 noise guidelines, and from a literature search covering the period 2016-2022 using Medline and PubMed databases. Additional papers were identified from colleagues. Study selection was according to PECO inclusion criteria. Studies were evaluated against the WHO checklist for risk of bias. RESULTS: 52 publications, 36 published after 2015, were identified that assessed associations between transportation noise and cardiovascular outcomes, that also considered potential confounding (49 studies) or interaction (23 studies) by air pollution. Most, but not all studies, suggested that the associations between traffic noise and cardiovascular outcomes are independent of air pollution. NO2 or PM2.5 were the most commonly included air pollutants and we observed no clear differences across air pollutants in terms of the potential confounding role. Most papers did not appear to suggest an interaction between noise and air pollution. Eight studies found the largest noise effect estimates occurring within the higher noise and air pollution exposure categories, but were not often statistically significant. CONCLUSION: Whilst air pollution does not appear to confound associations of noise and cardiovascular health, more studies on potential interactions are needed. Current methods to assess quality of evidence are not optimal when evaluating evidence on confounding or interaction.

Road Traffic Noise and Incidence of Primary Hypertension: A Prospective Analysis in UK Biobank.

Background: The quality of evidence regarding the associations between road traffic noise and hypertension is low due to the limitations of cross-sectional study design, and the role of air pollution remains to be further clarified. Objectives: The purpose of this study was to evaluate the associations of long-term road traffic noise exposure with incident primary hypertension; we conducted a prospective population-based analysis in UK Biobank. Methods: Road traffic noise was estimated at baseline residential address using the common noise assessment method model. Incident hypertension was ascertained through linkage with medical records. Cox proportional hazard models were used to estimate hazard ratios (HRs) for association in an analytical sample size of over 240,000 participants free of hypertension at baseline, adjusting for covariates determined via directed acyclic graph. Results: During a median of 8.1 years follow-up, 21,140 incident primary hypertension (International Classification of Diseases-10th Revision [ICD-10]: I10) were ascertained. The HR for a 10 dB[A] increment in mean weighted average 24-hour road traffic noise level (L den ) exposure was 1.07 (95% CI: 1.02-1.13). A dose-response relationship was found, with HR of 1.13 (95% CI: 1.03-1.25) for L den >65 dB[A] vs ≤55 dB[A] (P for trend <0.05). The associations were all robust to adjustment for fine particles (PM2.5) and nitrogen dioxide (NO2). Furthermore, high exposure to both road traffic noise and air pollution was associated with the highest hypertension risk. Conclusions: Long-term exposure to road traffic noise was associated with increased incidence of primary hypertension, and the effect estimates were stronger in presence of higher air pollution.

Does It Measure Up? A Comparison of Pollution Exposure Assessment Techniques Applied across Hospitals in England.

Weighted averages of air pollution measurements from monitoring stations are commonly assigned as air pollution exposures to specific locations. However, monitoring networks are spatially sparse and fail to adequately capture the spatial variability. This may introduce bias and exposure misclassification. Advanced methods of exposure assessment are rarely practicable in estimating daily concentrations over large geographical areas. We propose an accessible method using temporally adjusted land use regression models (daily LUR). We applied this to produce daily concentration estimates for nitrogen dioxide, ozone, and particulate matter in a healthcare setting across England and compared them against geographically extrapolated measurements (inverse distance weighting) from air pollution monitors. The daily LUR estimates outperformed IDW. The precision gains varied across air pollutants, suggesting that, for nitrogen dioxide and particulate matter, the health effects may be underestimated. The results emphasised the importance of spatial heterogeneity in investigating the societal impacts of air pollution, illustrating improvements achievable at a lower computational cost.

Associations between greenness and predicted COVID-19-like illness incidence in the United States and the United Kingdom.

Green spaces may be protective against COVID-19 incidence. They may provide outdoor, ventilated, settings for physical and social activities and therefore decrease transmission risk. We examined the association between neighborhood greenness and COVID-19-like illness incidence using individual-level data. Methods: The study population includes participants enrolled in the COVID Symptom Study smartphone application in the United Kingdom and the United States (March-November 2020). All participants were encouraged to report their current health condition and suspected risk factors for COVID-19. We used a validated symptom-based classifier that predicts COVID-19-like illness. We estimated the Normalized Difference Vegetation Index (NDVI), for each participant's reported neighborhood of residence for each month, using images from Landsat 8 (30 m2). We used time-varying Cox proportional hazards models stratified by age, country, and calendar month at study entry and adjusted for the individual- and neighborhood-level risk factors. Results: We observed 143,340 cases of predicted COVID-19-like illness among 2,794,029 participants. Neighborhood NDVI was associated with a decreased risk of predicted COVID-19-like illness incidence in the fully adjusted model (hazard ratio = 0.965, 95% confidence interval = 0.960, 0.970, per 0.1 NDVI increase). Stratified analyses showed protective associations among U.K. participants but not among U.S. participants. Associations were slightly stronger for White individuals, for individuals living in rural neighborhoods, and for individuals living in high-income neighborhoods compared to individuals living in low-income neighborhoods. Conclusions: Higher levels of greenness may reduce the risk of predicted COVID-19-like illness incidence, but these associations were not observed in all populations.

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

BACKGROUND: The link between exposure to ambient air pollution and mortality from cardiorespiratory diseases is well established, while evidence on neurodegenerative disorders including Parkinson's Disease (PD) remains limited. OBJECTIVE: We examined the association between long-term exposure to ambient air pollution and PD mortality in seven European cohorts. METHODS: Within the project 'Effects of Low-Level Air Pollution: A Study in Europe' (ELAPSE), we pooled data from seven cohorts among six European countries. Annual mean residential concentrations of fine particulate matter (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.

Long-term exposure to nitrogen dioxide air pollution and breast cancer risk: A nested case-control within the French E3N cohort study.

Nitrogen dioxide (NO2) is an important air pollutant due to its adverse effects on human health. Yet, current evidence on the association between NO2 and the risk of breast cancer lacks consistency. In this study, we investigated the association between long-term exposure to NO2 and breast cancer risk in the French E3N cohort study. Association of breast cancer risk with NO2 exposure was assessed in a nested case-control study within the French E3N cohort including 5222 breast cancer cases identified over the 1990-2011 follow-up period and 5222 matched controls. Annual mean concentrations of NO2 at participants' residential addresses for each year from recruitment 1990 through 2011, were estimated using a land use regression (LUR) model. Multivariable conditional logistic regression models were used to compute odds ratios (ORs) and their 95% confidence intervals (CIs). Additional analyses were performed using NO2 concentrations estimated by CHIMERE, a chemistry transport model. Overall, the mean NO2 exposure was associated with an increased risk of breast cancer. In all women, for each interquartile range (IQR) increase in NO2 levels (LUR: 17.8 µg/m3), the OR of the model adjusted for confounders was 1.09 (95% CI: 1.01-1.18). The corresponding OR in the fully adjusted model (additionally adjusted for established breast cancer risk factors) was 1.07 (95% CI: 0.98-1.15). By menopausal status, results for postmenopausal women were comparable to those for all women, while no association was observed among premenopausal women. By hormone receptor status, the OR of estrogen receptor positive breast cancer = 1.07 (95% CI: 0.97-1.19) in the fully adjusted model. Additional analyses using the CHIMERE model showed slight differences in ORs estimates. The results of this study indicate an increased risk of breast cancer associated with long-term exposure to NO2 air pollution. Observing comparable effects of NO2 exposure estimated by two different models, reinforces these findings.

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

BACKGROUND: Established risk factors for breast cancer include genetic disposition, reproductive factors, hormone therapy, and lifestyle-related factors such as alcohol consumption, physical inactivity, smoking, and obesity. More recently a role of environmental exposures, including air pollution, has also been suggested. The aim of this study, was to investigate the relationship between long-term air pollution exposure and breast cancer incidence. METHODS: We conducted a pooled analysis among six European cohorts (n = 199,719) on the association between long-term residential levels of ambient nitrogen dioxide (NO2), fine particles (PM2.5), black carbon (BC), and ozone in the warm season (O3) and breast cancer incidence in women. The selected cohorts represented the lower range of air pollutant concentrations in Europe. We applied Cox proportional hazards models adjusting for potential confounders at the individual and area-level. RESULTS: During 3,592,885 person-years of follow-up, we observed a total of 9,659 incident breast cancer cases. The results of the fully adjusted linear analyses showed a HR (95% confidence interval) of 1.03 (1.00-1.06) per 10 µg/m³ NO2, 1.06 (1.01-1.11) per 5 µg/m³ PM2.5, 1.03 (0.99-1.06) per 0.5 10-5 m-1 BC, and 0.98 (0.94-1.01) per 10 µg/m³ O3. The effect estimates were most pronounced in the group of middle-aged women (50-54 years) and among never smokers. CONCLUSIONS: The results were in support of an association between especially PM2.5 and breast cancer. IMPACT: The findings of this study suggest a role of exposure to NO2, PM2.5, and BC in development of breast cancer.

The relationship between hair metabolites, air pollution exposure and gestational diabetes mellitus: A longitudinal study from pre-conception to third trimester.

Background: Gestational diabetes mellitus (GDM) is a metabolic condition defined as glucose intolerance with first presentation during pregnancy. Many studies suggest that environmental exposures, including air pollution, contribute to the pathogenesis of GDM. Although hair metabolite profiles have been shown to reflect pollution exposure, few studies have examined the link between environmental exposures, the maternal hair metabolome and GDM. The aim of this study was to investigate the longitudinal relationship (from pre-conception through to the third trimester) between air pollution exposure, the hair metabolome and GDM in a Chinese cohort. Methods: A total of 1020 women enrolled in the Complex Lipids in Mothers and Babies (CLIMB) birth cohort were included in our study. Metabolites from maternal hair segments collected pre-conception, and in the first, second, and third trimesters were analysed using gas chromatography-mass spectrometry (GC-MS). Maternal exposure to air pollution was estimated by two methods, namely proximal and land use regression (LUR) models, using air quality data from the air quality monitoring station nearest to the participant's home. Logistic regression and mixed models were applied to investigate associations between the air pollution exposure data and the GDM associated metabolites. Results: Of the 276 hair metabolites identified, the concentrations of fourteen were significantly different between GDM cases and non-GDM controls, including some amino acids and their derivatives, fatty acids, organic acids, and exogenous compounds. Three of the metabolites found in significantly lower concentrations in the hair of women with GDM (2-hydroxybutyric acid, citramalic acid, and myristic acid) were also negatively associated with daily average concentrations of PM2.5, PM10, SO2, NO2, CO and the exposure estimates of PM2.5 and NO2, and positively associated with O3. Conclusions: This study demonstrated that the maternal hair metabolome reflects the longitudinal metabolic changes that occur in response to environmental exposures and the development of GDM.

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

Ambient air pollution is an established risk factor for premature mortality from chronic cardiovascular, respiratory and metabolic diseases, while evidence on neurodegenerative diseases and psychiatric disorders remains limited. We examined the association between long-term exposure to air pollution and mortality from dementia, psychiatric disorders, and suicide in seven European cohorts. Within the multicenter project 'Effects of Low-Level Air Pollution: A Study in Europe' (ELAPSE), we pooled data from seven European cohorts from six countries. Based on the residential addresses, annual mean levels of fine particulate matter (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.