A co-created citizen science project on the short term effects of outdoor residential woodsmoke on the respiratory health of adults in the Netherlands.

BACKGROUND AND AIM: Woodsmoke from household fireplaces contributes significantly to outdoor air pollution in the Netherlands. The current understanding of the respiratory health effects of exposure to smoke from residential wood burning is limited. This study investigated the association between short-term changes in outdoor woodsmoke exposure and lung function, respiratory symptoms, and medication use in adults in the Netherlands. METHODS: This study was co-created with citizen scientists and other relevant stakeholders. A panel study was conducted with repeated observations in 46 adults between February and May 2021 in four Dutch towns. Participants recorded their symptoms and medication use in daily diaries, and conducted morning and evening home spirometry measurements. Woodsmoke exposure was characterized by measuring levoglucosan (most specific marker for woodsmoke exposure), black/brown carbon, fine and ultrafine particulate matter at central monitoring sites. Individual woodsmoke perception (smell) was recorded in daily diaries. Linear and logistic regression models were used to investigate the association between respiratory health and woodsmoke exposure. Models were adjusted for time-varying confounders and accounted for repeated observations within participants. RESULTS: Consistent positive associations were found between levoglucosan and shortness of breath (SOB) during rest and extra respiratory medication use. Odds ratios for current day exposure to levoglucosan were 1.12 (95% CI: 0.97, 1.30) for SOB during rest and 1.19 (95% CI: 1.07, 1.33) for extra medication use, expressed per interquartile range of levoglucosan concentrations (69.16 ng/m3). Positive non-significant associations were found between levoglucosan and nasal symptoms, cough and waking up with SOB. No consistent association was found between levoglucosan and lung function. Associations found between woodsmoke markers, SOB during rest and extra medication use remained after the inclusion of PM2.5 and UFP in two-pollutant models. CONCLUSIONS: Adults experienced more SOB during rest, nasal symptoms and used more medication to treat respiratory symptoms on days with higher levels of outdoor woodsmoke concentrations.

Perinatal exposure to traffic related air pollutants and the risk of infection in the first six months of life: a cohort study from a low-middle income country.

OBJECTIVE: There is limited study from low-and-middle income countries on the effect of perinatal exposure to air pollution and the risk of infection in infant. We assessed the association between perinatal exposure to traffic related air pollution and the risk of infection in infant during their first six months of life. METHODS: A prospective cohort study was performed in Jakarta, March 2016-September 2020 among 298 mother-infant pairs. PM2.5, soot, NOx, and NO2 concentrations were assessed using land use regression models (LUR) at individual level. Repeated interviewer-administered questionnaires were used to obtain data on infection at 1, 2, 4 and 6 months of age. The infections were categorized as upper respiratory tract (runny nose, cough, wheezing or shortness of breath), lower respiratory tract (pneumonia, bronchiolitis) or gastrointestinal tract infection. Logistic regression models adjusted for covariates were used to assess the association between perinatal exposure to air pollution and the risk of infection in the first six months of life. RESULTS: The average concentrations of PM2.5 and NO2 were much higher than the WHO recommended levels. Upper respiratory tract infections (URTI) were much more common in the first six months of life than diagnosed lower respiratory tract or gastro-intestinal infections (35.6%, 3.5% and 5.8% respectively). Perinatal exposure to PM2.5 and soot suggested increase cumulative risk of upper respiratory tract infection (URTI) in the first 6 months of life per IQR increase with adjusted OR of 1.50 (95% CI 0.91; 2.47) and 1.14 (95% CI 0.79; 1.64), respectively. Soot was significantly associated with the risk of URTI at 4-6 months age interval (aOR of 1.45, 95%CI 1.02; 2.09). All air pollutants were also positively associated with lower respiratory tract infection, but all CIs include unity because of relatively small samples. Adjusted odds ratios for gastrointestinal infections were close to unity. CONCLUSION: Our study adds to the evidence that perinatal exposure to fine particles is associated with respiratory tract infection in infants in a low-middle income country.

Alterations to biomarkers related to long-term exposure to diesel exhaust at concentrations below occupational exposure limits in the European Union and the USA.

BACKGROUND: We previously found that occupational exposure to diesel engine exhaust (DEE) was associated with alterations to 19 biomarkers that potentially reflect the mechanisms of carcinogenesis. Whether DEE is associated with biological alterations at concentrations under existing or recommended occupational exposure limits (OELs) is unclear. METHODS: In a cross-sectional study of 54 factory workers exposed long-term to DEE and 55 unexposed controls, we reanalysed the 19 previously identified biomarkers. Multivariable linear regression was used to compare biomarker levels between DEE-exposed versus unexposed subjects and to assess elemental carbon (EC) exposure-response relationships, adjusted for age and smoking status. We analysed each biomarker at EC concentrations below the US Mine Safety and Health Administration (MSHA) OEL (<106 µg/m3), below the European Union (EU) OEL (<50 µg/m3) and below the American Conference of Governmental Industrial Hygienists (ACGIH) recommendation (<20 µg/m3). RESULTS: Below the MSHA OEL, 17 biomarkers were altered between DEE-exposed workers and unexposed controls. Below the EU OEL, DEE-exposed workers had elevated lymphocytes (p=9E-03, false discovery rate (FDR)=0.04), CD4+ count (p=0.02, FDR=0.05), CD8+ count (p=5E-03, FDR=0.03) and miR-92a-3p (p=0.02, FDR=0.05), and nasal turbinate gene expression (first principal component: p=1E-06, FDR=2E-05), as well as decreased C-reactive protein (p=0.02, FDR=0.05), macrophage inflammatory protein-1ß (p=0.04, FDR=0.09), miR-423-3p (p=0.04, FDR=0.09) and miR-122-5p (p=2E-03, FDR=0.02). Even at EC concentrations under the ACGIH recommendation, we found some evidence of exposure-response relationships for miR-423-3p (ptrend=0.01, FDR=0.19) and gene expression (ptrend=0.02, FDR=0.19). CONCLUSIONS: DEE exposure under existing or recommended OELs may be associated with biomarkers reflective of cancer-related processes, including inflammatory/immune response.

The effect of exposure to traffic related air pollutants in pregnancy on birth anthropometry: a cohort study in a heavily polluted low-middle income country.

BACKGROUND: Ambient air pollution has been recognized as one of the most important environmental health threats. Exposure in early life may affect pregnancy outcomes and the health of the offspring. The main objective of our study was to assess the association between prenatal exposure to traffic related air pollutants during pregnancy on birth weight and length. Second, to evaluate the association between prenatal exposure to traffic related air pollutants and the risk of low birth weight (LBW). METHODS: Three hundred forty mother-infant pairs were included in this prospective cohort study performed in Jakarta, March 2016-September 2020. Exposure to outdoor PM2.5, soot, NOx, and NO2 was assessed by land use regression (LUR) models at individual level. Multiple linear regression models were built to evaluate the association between air pollutants with birth weight (BW) and birth length (BL). Logistic regression was used to assess the risk of low birth weight (LBW) associated with all air pollutants. RESULTS: The average PM2.5 concentration was almost eight times higher than the current WHO guideline and the NO2 level was three times higher. Soot and NOx were significantly associated with reduced birth length. Birth length was reduced by - 3.83 mm (95% CI -6.91; - 0.75) for every IQR (0.74 × 10- 5 per m) increase of soot, and reduced by - 2.82 mm (95% CI -5.33;-0.30) for every IQR (4.68 µg/m3) increase of NOx. Outdoor air pollutants were not significantly associated with reduced birth weight nor the risk of LBW. CONCLUSION: Exposure to soot and NOx during pregnancy was associated with reduced birth length. Associations between exposure to all air pollutants with birth weight and the risk of LBW were less convincing.

Association between diesel exhaust exposure and mitochondrial DNA methylation.

OBJECTIVES: Diesel exhaust is an established human carcinogen, however the mechanisms by which it leads to cancer development are not fully understood. Mitochondrial dysfunction is an established contributor to carcinogenesis. Recent studies have improved our understanding of the role played by epigenetic modifications in the mitochondrial genome on tumorigenesis. In this study, we aim to evaluate the association between diesel engine exhaust (DEE) exposure with mitochondrial DNA (mtDNA) methylation levels in workers exposed to DEE. METHODS: The study population consisted of 53 male workers employed at a diesel engine manufacturing facility in Northern China who were routinely exposed to diesel exhaust in their occupational setting, as well as 55 unexposed male control workers from other unrelated factories in the same geographic area. Exposure to DEE, elemental carbon, organic carbon, and particulate matter (PM2.5) were assessed. mtDNA methylation for CpG sites (CpGs) from seven mitochondrial genes (D-Loop, MT-RNR1, MT-CO2, MT-CO3, MT-ATP6, MT-ATP8, MT-ND5) was measured in blood samples. Linear regression models were used to estimate the associations between DEE, elemental carbon, organic carbon and PM2.5 exposures with mtDNA methylation levels, adjusting for potential confounders. RESULTS: DEE exposure was associated with decreased MT-ATP6 (difference = -35.6%, P-value = 0.019) and MT-ATP8 methylation (difference = -30%, P-value = 0.029) compared to unexposed controls. Exposures to elemental carbon, organic carbon, and PM2.5 were also significantly and inversely associated with methylation in MT-ATP6 and MT-ATP8 genes (all P-values < 0.05). CONCLUSIONS: Our findings suggest that DEE exposure perturbs mtDNA methylation, which may be of importance for tumorigenesis.

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

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

Short-term associations between barbecue fumes and respiratory health in young adults.

BACKGROUND: Epidemiological studies have associated biomass combustion with (respiratory) morbidity and mortality, primarily in indoor settings. Barbecuing results in high outdoor air pollution exposures, but the health effects are unknown. OBJECTIVE: The objective was to investigate short-term changes in respiratory health in healthy adults, associated with exposure to barbecue fumes. METHODS: 16 healthy, adult volunteers were exposed to barbecue smoke in outdoor air in rest during 1.5 h, using a repeated-measures design. Major air pollutants were monitored on-site, including particulate matter <2.5 µm (PM2.5), particle number concentrations (PNC) and black- and brown carbon. At the same place and time-of-day, subjects participated in a control session, during which they were not exposed to barbecue smoke. Before and immediately after all sessions lung function was measured. Before, immediately after, 4- and 18 h post-sessions nasal expression levels of interleukin (IL)-8, IL6 and Tumor Necrosis Factor alpha (TNFα) were determined in nasal swabs, using quantitative polymerase chain reaction. Associations between major air pollutants, lung function and inflammatory markers were assessed using mixed linear regression models. RESULTS: High PM2.5 levels and PNCs were observed during barbecue sessions, with averages ranging from 553 to 1062 µg/m3 and 109,000-463,000 pt/cm3, respectively. Average black- and brown carbon levels ranged between 4.1-13.0 and 5.0-16.2 µg/m3. A 1000 µg/m3 increase in PM2.5 was associated with 2.37 (0.97, 4.67) and 2.21 (0.98, 5.00) times higher expression of IL8, immediately- and 18 h after exposure. No associations were found between air pollutants and lung function, or the expression of IL6 or TNFα. DISCUSSION: Short-term exposure to air pollutants emitted from barbecuing was associated with a mild respiratory response in healthy young adults, including prolonged increase in nasal IL8 without a change in lung function and other measured inflammatory markers. The results might indicate prolonged respiratory inflammation, due to short-term exposure to barbecue fumes.

Spatial and Spatiotemporal Variability of Regional Background Ultrafine Particle Concentrations in the Netherlands.

Studies of the health effects of ultrafine particles (UFPs) in large nationwide cohorts are currently hampered by a lack of knowledge about spatial and spatiotemporal variations in regional background UFPs. We measured the UFP (10-300 nm) at 20 regional background locations (3 × 2 weeks) across the Netherlands and a reference site continuously over a total period of 14 months in 2016-2017. We compared the overall averages for each site and used kriging to create a regional background spatial map of the Netherlands. Spatiotemporal variability was analyzed by correlating time-series of 2 and 24 h average concentrations. The overall average measured UFP concentrations at the 20 locations ranged from 3814 to 7070 particles/cm3. We found the spatial correlation in the UFP concentrations up to 180 km and clear differences between the north and the more populated southern parts of the country. The average temporal correlation between 2 and 24 h average UFP concentrations was 0.50 (IQR: 0.36-0.61) and 0.58 (IQR: 0.44-0.75), respectively. Temporal correlation declined weakly with a distance between sites, from 0.58 for sites within 80 km of each other to 0.47 for sites farther away. The substantial spatial variation in the regional background UFP concentrations suggests that regional variation may contribute importantly to exposure contrast in nationwide health studies of UFP.

Occupational and environmental exposure to SARS-CoV-2 in and around infected mink farms.

OBJECTIVE: Unprecedented SARS-CoV-2 infections in farmed minks raised immediate concerns regarding transmission to humans and initiated intensive environmental investigations to assess occupational and environmental exposure. METHODS: Air sampling was performed at infected Dutch mink farms, at farm premises and at nearby residential sites. A range of other environmental samples were collected from minks' housing units, including bedding materials. SARS-CoV-2 RNA was analysed in all samples by quantitative PCR. RESULTS: Inside the farms, considerable levels of SARS-CoV-2 RNA were found in airborne dust, especially in personal inhalable dust samples (approximately 1000-10 000 copies/m3). Most of the settling dust samples tested positive for SARS-CoV-2 RNA (82%, 75 of 92). SARS-CoV-2 RNA was not detected in outdoor air samples, except for those collected near the entrance of the most recently infected farm. Many samples of minks' housing units and surfaces contained SARS-CoV-2 RNA. CONCLUSIONS: Infected mink farms can be highly contaminated with SARS-CoV-2 RNA. This warns of occupational exposure, which was substantiated by considerable SARS-CoV-2 RNA concentrations in personal air samples. Dispersion of SARS-CoV-2 to outdoor air was found to be limited and SARS-CoV-2 RNA was not detected in air samples collected beyond farm premises, implying a negligible risk of environmental exposure to nearby communities. Our occupational and environmental risk assessment is in line with whole genome sequencing analyses showing mink-to-human transmission among farm workers, but no indications of direct zoonotic transmission events to nearby communities.

Elevated Alu retroelement copy number among workers exposed to diesel engine exhaust.

BACKGROUND: Millions of workers worldwide are exposed to diesel engine exhaust (DEE), a known genotoxic carcinogen. Alu retroelements are repetitive DNA sequences that can multiply and compromise genomic stability. There is some evidence linking altered Alu repeats to cancer and elevated mortality risks. However, whether Alu repeats are influenced by environmental pollutants is unexplored. In an occupational setting with high DEE exposure levels, we investigated associations with Alu repeat copy number. METHODS: A cross-sectional study of 54 male DEE-exposed workers from an engine testing facility and a comparison group of 55 male unexposed controls was conducted in China. Personal air samples were assessed for elemental carbon, a DEE surrogate, using NIOSH Method 5040. Quantitative PCR (qPCR) was used to measure Alu repeat copy number relative to albumin (Alb) single-gene copy number in leucocyte DNA. The unitless Alu/Alb ratio reflects the average quantity of Alu repeats per cell. Linear regression models adjusted for age and smoking status were used to estimate relations between DEE-exposed workers versus unexposed controls, DEE tertiles (6.1-39.0, 39.1-54.5 and 54.6-107.7 µg/m3) and Alu/Alb ratio. RESULTS: DEE-exposed workers had a higher average Alu/Alb ratio than the unexposed controls (p=0.03). Further, we found a positive exposure-response relationship (p=0.02). The Alu/Alb ratio was highest among workers exposed to the top tertile of DEE versus the unexposed controls (1.12±0.08 SD vs 1.06±0.07 SD, p=0.01). CONCLUSION: Our findings suggest that DEE exposure may contribute to genomic instability. Further investigations of environmental pollutants, Alu copy number and carcinogenesis are warranted.

Cardiovascular benefits of short-term indoor air filtration intervention in elderly living in Beijing: An extended analysis of BIAPSY study.

BACKGROUND: Adverse cardiovascular effects associated with air pollution exposure have been widely demonstrated. However, inconsistent cardiovascular responses were observed from reducing indoor air pollution exposure. We aimed to assess whether short-term air filtration intervention could benefit cardiovascular health in elderly living in high pollution area. METHODS: A randomized crossover intervention study of short-term indoor air filtration intervention on cardiovascular health was conducted among 35 non-smoking elderly participants living in Beijing in the winter of 2013, as part of Beijing Indoor Air Purifier StudY (BIAPSY). Portable air filtration units were randomly allocated to active filtration for 2 weeks and sham filtration for 2 weeks in the households. Twelve-hour daytime ambulatory heart rate variability (HRV) and blood pressure (ABP) were measured during active and sham filtration. Concurrently, real-time indoor and outdoor particulate matter with diameter less than 2.5 µm (PM2.5) and indoor black carbon (BC) concentrations were measured. We applied generalized additive mixed models to evaluate the associations of 1- to 10-h moving average (MA) exposures of indoor PM2.5 and BC with HRV and ABP indices, and to explore whether these associations could be modified by air filtration. RESULTS: We observed decreases of 34.8% in indoor PM2.5 and 35.3% in indoor BC concentrations during active filtration. Indoor PM2.5 and BC exposures were significantly associated with reduced HRV and increased ABP indices, and greater changes were observed during sham filtration. In specific, each 10 µg/m3 increase in indoor PM2.5 at MA8-h was associated with a significant reduction of 1.34% (95% CI: -2.42, -0.26) in SDNN during sham filtration, compared with a non-significant reduction of 0.81% (95% CI: -6.00, 4.68) during active filtration (Pinter< 0.001). Each 1 µg/m3 increase in indoor BC at MA8-h was associated with a significant increase of 2.41% (95% CI: 0.38, 4.47) in SBP during sham filtration, compared with a non-significant increase of -1.09% (95% CI: -4.06, 1.96) during active filtration (Pinter = 0.135). Nonlinear inverse exposure-response relationships of indoor air pollution exposures with predicted HRV and ABP indices also confirmed some cardiovascular benefits of short-term air filtration intervention. CONCLUSIONS: Our results suggested that short-term indoor air filtration intervention can be of some cardiovascular benefits in elderly living with high pollution episodes.

Occupational exposure to diesel engine exhaust and alterations in immune/inflammatory markers: a cross-sectional molecular epidemiology study in China.

The relationship between diesel engine exhaust (DEE), a known lung carcinogen, and immune/inflammatory markers that have been prospectively associated with lung cancer risk is not well understood. To provide insight into these associations, we conducted a cross-sectional molecular epidemiology study of 54 males highly occupationally exposed to DEE and 55 unexposed male controls from representative workplaces in China. We measured plasma levels of 64 immune/inflammatory markers in all subjects using Luminex bead-based assays, and compared our findings to those from a nested case-control study of these markers and lung cancer risk, which had been conducted among never-smoking women in Shanghai using the same multiplex panels. Levels of nine markers that were associated with lung cancer risk in the Shanghai study were altered in DEE-exposed workers in the same direction as the lung cancer associations. Among these, associations with the levels of CRP (ß= -0.53; P = 0.01) and CCL15/MIP-1D (ß = 0.20; P = 0.02) were observed in workers exposed to DEE and with increasing elemental carbon exposure levels (Ptrends <0.05) in multivariable linear regression models. Levels of a third marker positively associated with an increased lung cancer risk, CCL2/MCP-1, were higher among DEE-exposed workers compared with controls in never and former smokers, but not in current smokers (Pinteraction = 0.01). The immunological differences in these markers in DEE-exposed workers are consistent with associations observed for lung cancer risk in a prospective study of Chinese women and may provide some insight into the mechanistic processes by which DEE causes lung cancer.

Land Use Regression Models for Ultrafine Particles in Six European Areas.

Long-term ultrafine particle (UFP) exposure estimates at a fine spatial scale are needed for epidemiological studies. Land use regression (LUR) models were developed and evaluated for six European areas based on repeated 30 min monitoring following standardized protocols. In each area; Basel (Switzerland), Heraklion (Greece), Amsterdam, Maastricht, and Utrecht ("The Netherlands"), Norwich (United Kingdom), Sabadell (Spain), and Turin (Italy), 160-240 sites were monitored to develop LUR models by supervised stepwise selection of GIS predictors. For each area and all areas combined, 10 models were developed in stratified random selections of 90% of sites. UFP prediction robustness was evaluated with the intraclass correlation coefficient (ICC) at 31-50 external sites per area. Models from Basel and The Netherlands were validated against repeated 24 h outdoor measurements. Structure and model R2 of local models were similar within, but varied between areas (e.g., 38-43% Turin; 25-31% Sabadell). Robustness of predictions within areas was high (ICC 0.73-0.98). External validation R2 was 53% in Basel and 50% in The Netherlands. Combined area models were robust (ICC 0.93-1.00) and explained UFP variation almost equally well as local models. In conclusion, robust UFP LUR models could be developed on short-term monitoring, explaining around 50% of spatial variance in longer-term measurements.

Comparison of Ultrafine Particle and Black Carbon Concentration Predictions from a Mobile and Short-Term Stationary Land-Use Regression Model.

Mobile and short-term monitoring campaigns are increasingly used to develop land-use regression (LUR) models for ultrafine particles (UFP) and black carbon (BC). It is not yet established whether LUR models based on mobile or short-term stationary measurements result in comparable models and concentration predictions. The goal of this paper is to compare LUR models based on stationary (30 min) and mobile UFP and BC measurements from a single campaign. An electric car collected both repeated stationary and mobile measurements in Amsterdam and Rotterdam, The Netherlands. A total of 2964 road segments and 161 stationary sites were sampled over two seasons. Our main comparison was based on predicted concentrations of the mobile and stationary monitoring LUR models at 12 682 residential addresses in Amsterdam. Predictor variables in the mobile and stationary LUR model were comparable, resulting in highly correlated predictions at external residential addresses (R2 of 0.89 for UFP and 0.88 for BC). Mobile model predictions were, on average, 1.41 and 1.91 times higher than stationary model predictions for UFP and BC, respectively. LUR models based upon mobile and stationary monitoring predicted highly correlated UFP and BC concentration surfaces, but predicted concentrations based on mobile measurements were systematically higher.

Effects of long-term exposure to air pollution on natural-cause mortality: an analysis of 22 European cohorts within the multicentre ESCAPE project.

BACKGROUND: Few studies on long-term exposure to air pollution and mortality have been reported from Europe. Within the multicentre European Study of Cohorts for Air Pollution Effects (ESCAPE), we aimed to investigate the association between natural-cause mortality and long-term exposure to several air pollutants. METHODS: We used data from 22 European cohort studies, which created a total study population of 367,251 participants. All cohorts were general population samples, although some were restricted to one sex only. With a strictly standardised protocol, we assessed residential exposure to air pollutants as annual average concentrations of particulate matter (PM) with diameters of less than 2.5 µm (PM2.5), less than 10 µm (PM10), and between 10 µm and 2.5 µm (PMcoarse), PM2.5 absorbance, and annual average concentrations of nitrogen oxides (NO2 and NOx), with land use regression models. We also investigated two traffic intensity variables-traffic intensity on the nearest road (vehicles per day) and total traffic load on all major roads within a 100 m buffer. We did cohort-specific statistical analyses using confounder models with increasing adjustment for confounder variables, and Cox proportional hazards models with a common protocol. We obtained pooled effect estimates through a random-effects meta-analysis. FINDINGS: The total study population consisted of 367,251 participants who contributed 5,118,039 person-years at risk (average follow-up 13.9 years), of whom 29,076 died from a natural cause during follow-up. A significantly increased hazard ratio (HR) for PM2.5 of 1.07 (95% CI 1.02-1.13) per 5 µg/m(3) was recorded. No heterogeneity was noted between individual cohort effect estimates (I(2) p value=0.95). HRs for PM2.5 remained significantly raised even when we included only participants exposed to pollutant concentrations lower than the European annual mean limit value of 25 µg/m(3) (HR 1.06, 95% CI 1.00-1.12) or below 20 µg/m(3) (1.07, 1.01-1.13). INTERPRETATION: Long-term exposure to fine particulate air pollution was associated with natural-cause mortality, even within concentration ranges well below the present European annual mean limit value. FUNDING: European Community's Seventh Framework Program (FP7/2007-2011).

Particulate matter composition and respiratory health: the PIAMA Birth Cohort study.

BACKGROUND: Ambient particulate matter (PM) exposure is associated with children's respiratory health. Little is known about the importance of different PM constituents. We investigated the effects of PM constituents on asthma, allergy, and lung function until the age of 11-12 years. METHODS: For 3,702 participants of a prospective birth cohort study, questionnaire-reported asthma and hay fever and measurements of allergic sensitization and lung function were linked with annual average concentrations of copper, iron, potassium, nickel, sulfur, silicon, vanadium, and zinc in particles with diameters of less than 2.5 and 10 µm (PM2.5 and PM10) at birth addresses and current addresses from land-use regression models. Exposure-health relations were analyzed by multiple (repeated measures) logistic and linear regressions. RESULTS: Asthma incidence and prevalence of asthma symptoms and rhinitis were positively associated with zinc in PM10 at the birth address (odds ratio [95% confidence interval] per interquartile range increase in exposure 1.13 [1.02, 1.25], 1.08 [1.00, 1.17], and 1.16 [1.04, 1.30], respectively). Moreover, asthma symptoms were positively associated with copper in PM10 at the current address (1.06 [1.00, 1.12]). Allergic sensitization was positively associated with copper and iron in PM10 at the birth address (relative risk [95% confidence interval] 1.07 [1.01, 1.14] and 1.10 [1.03, 1.18]) and current address. Forced expiratory volume in 1 second was negatively associated with copper and iron in PM2.5 (change [95% confidence interval] -2.1% [-1.1, -0.1%] and -1.0% [-2.0, -0.0%]) and FEF75-50 with copper in PM10 at the current address (-2.3% [-4.3, -0.3%]). CONCLUSION: PM constituents, in particular iron, copper, and zinc, reflecting poorly regulated non-tailpipe road traffic emissions, may increase the risk of asthma and allergy in schoolchildren.

Land Use Regression Models for Ultrafine Particles and Black Carbon Based on Short-Term Monitoring Predict Past Spatial Variation.

Health effects of long-term exposure to ultrafine particles (UFP) have not been investigated in epidemiological studies because of the lack of spatially resolved UFP exposure data. Short-term monitoring campaigns used to develop land use regression (LUR) models for UFP typically had moderate performance. The aim of this study was to develop and evaluate spatial and spatiotemporal LUR models for UFP and Black Carbon (BC), including their ability to predict past spatial contrasts. We measured 30 min at each of 81 sites in Amsterdam and 80 in Rotterdam, The Netherlands in three different seasons. Models were developed using traffic, land use, reference site measurements, routinely measured pollutants and weather data. The percentage explained variation (R(2)) was 0.35-0.40 for BC and 0.33-0.42 for UFP spatial models. Traffic variables were present in every model. The coefficients for the spatial predictors were similar in spatial and spatiotemporal models. The BC LUR model explained 61% of the spatial variation in a previous campaign with longer sampling duration, better than the model R(2). The UFP LUR model explained 36% of UFP spatial variation measured 10 years earlier, similar to the model R(2). Short-term monitoring campaigns may be an efficient tool to develop LUR models.

Occupational exposure to diesel engine exhaust and alterations in lymphocyte subsets.

BACKGROUND: The International Agency for Research on Cancer recently classified diesel engine exhaust (DEE) as a Group I carcinogen based largely on its association with lung cancer. However, the exposure-response relationship is still a subject of debate and the underlying mechanism by which DEE causes lung cancer in humans is not well understood. METHODS: We conducted a cross-sectional molecular epidemiology study in a diesel engine truck testing facility of 54 workers exposed to a wide range of DEE (ie, elemental carbon air levels, median range: 49.7, 6.1-107.7 µg/m(3)) and 55 unexposed comparable controls. RESULTS: The total lymphocyte count (p=0.00044) and three of the four major lymphocyte subsets (ie, CD4+ T cells (p=0.00019), CD8+ T cells (p=0.0058) and B cells (p=0.017)) were higher in exposed versus control workers and findings were highly consistent when stratified by smoking status. In addition, there was evidence of an exposure-response relationship between elemental carbon and these end points (ptrends<0.05), and CD4+ T cell levels were significantly higher in the lowest tertile of DEE exposed workers compared to controls (p=0.012). CONCLUSIONS: Our results suggest that DEE exposure is associated with higher levels of cells that play a key role in the inflammatory process, which is increasingly being recognised as contributing to the aetiology of lung cancer. IMPACT: This study provides new insights into the underlying mechanism of DEE carcinogenicity.

A national fine spatial scale land-use regression model for ozone.

Uncertainty about health effects of long-term ozone exposure remains. Land use regression (LUR) models have been used successfully for modeling fine scale spatial variation of primary pollutants but very limited for ozone. Our objective was to assess the feasibility of developing a national LUR model for ozone at a fine spatial scale. Ozone concentrations were measured with passive samplers at 90 locations across the Netherlands (19 regional background, 36 urban background, 35 traffic). All sites were measured simultaneously during four 2-weekly campaigns spread over the seasons. LUR models were developed for the summer average as the primary exposure and annual average using predictor variables obtained with Geographic Information Systems. Summer average ozone concentrations varied between 32 and 61 µg/m(3). Ozone concentrations at traffic sites were on average 9 µg/m(3) lower compared to regional background sites. Ozone correlated highly negatively with nitrogen dioxide and moderately with fine particles. A LUR model including small-scale traffic, large-scale address density, urban green and a region indicator explained 71% of the spatial variation in summer average ozone concentrations. Land use regression modeling is a promising method to assess ozone spatial variation, but the high correlation with NO2 limits application in epidemiology.

Air pollution and nonmalignant respiratory mortality in 16 cohorts within the ESCAPE project.

RATIONALE: Prospective cohort studies have shown that chronic exposure to particulate matter and traffic-related air pollution is associated with reduced survival. However, the effects on nonmalignant respiratory mortality are less studied, and the data reported are less consistent. OBJECTIVES: We have investigated the relationship of long-term exposure to air pollution and nonmalignant respiratory mortality in 16 cohorts with individual level data within the multicenter European Study of Cohorts for Air Pollution Effects (ESCAPE). METHODS: Data from 16 ongoing cohort studies from Europe were used. The total number of subjects was 307,553. There were 1,559 respiratory deaths during follow-up. MEASUREMENTS AND MAIN RESULTS: Air pollution exposure was estimated by land use regression models at the baseline residential addresses of study participants and traffic-proximity variables were derived from geographical databases following a standardized procedure within the ESCAPE study. Cohort-specific hazard ratios obtained by Cox proportional hazard models from standardized individual cohort analyses were combined using metaanalyses. We found no significant associations between air pollution exposure and nonmalignant respiratory mortality. Most hazard ratios were slightly below unity, with the exception of the traffic-proximity indicators. CONCLUSIONS: In this study of 16 cohorts, there was no association between air pollution exposure and nonmalignant respiratory mortality.