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Objectives To explore the associations of long-term exposure to air pollution with onset of all human health conditions.Design Prospective phenome-wide association study.Setting Denmark.Participants All Danish residents aged ≥30 years on 1 January 2000 were included (N=3 323 612). After exclusion of individuals with missing geocoded residential addresses, 3 111 988 participants were available for the statistical analyses.Main outcome measure First registered diagnosis of every health condition according to the International Classification of Diseases, 10th revision, from 2000 to 2017.Results Long-term exposure to fine particulate matter (PM2.5) and nitrogen dioxide (NO2) were both positively associated with the onset of more than 700 health conditions (ie, >80% of the registered health conditions) after correction for multiple testing, while the remaining associations were inverse or insignificant. As regards the most common health conditions, PM2.5 and NO2 were strongest positively associated with chronic obstructive pulmonary disease (PM2.5: HR 1.06 (95% CI 1.05 to 1.07) per 1 IQR increase in exposure level; NO2: 1.14 (95% CI 1.12 to 1.15)), type 2 diabetes (PM2.5: 1.06 (95% CI 1.05 to 1.06); NO2: 1.12 (95% CI 1.10 to 1.13)) and ischaemic heart disease (PM2.5: 1.05 (95% CI 1.04 to 1.05); NO2: 1.11 (95% CI 1.09 to 1.12)). Furthermore, PM2.5 and NO2 were both positively associated with so far unexplored, but highly prevalent outcomes relevant to public health, including senile cataract, hearing loss and urinary tract infection.Conclusions The findings of this study suggest that air pollution has a more extensive impact on human health than previously known. However, as this study is the first of its kind to investigate the associations of long-term exposure to air pollution with onset of all human health conditions, further research is needed to replicate the study findings.

Abstract Background Long-term exposure to air pollution and noise is detrimental to health; but studies that evaluated both remain limited. This study explores associations with natural and cause-specific mortality for a range of air pollutants and transportation noise. Methods Over 4 million adults in Switzerland were followed from 2000 to 2014. Exposure to PM2.5, PM2.5 components (Cu, Fe, S and Zn), NO2, black carbon (BC) and ozone (O3) from European models, and transportation noise from source-specific Swiss models, were assigned at baseline home addresses. Cox proportional hazards models, adjusted for individual and area-level covariates, were used to evaluate associations with each exposure and death from natural, cardiovascular (CVD) or non-malignant respiratory disease. Analyses included single and two exposure models, and subset analysis to study lower exposure ranges. Results During follow-up, 661,534 individuals died of natural causes (36.6% CVD, 6.6% respiratory). All exposures including the PM2.5 components were associated with natural mortality, with hazard ratios (95% confidence intervals) of 1.026 (1.015, 1.038) per 5 µg/m3 PM2.5, 1.050 (1.041, 1.059) per 10 µg/m3 NO2, 1.057 (1.048, 1.067) per 0.5 × 10–5/m BC and 1.045 (1.040, 1.049) per 10 dB Lden total transportation noise. NO2, BC, Cu, Fe and noise were consistently associated with CVD and respiratory mortality, whereas PM2.5 was only associated with CVD mortality. Natural mortality associations persisted

Abstract 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.

Background: Few comparisons between causal inference and traditional approaches have been performed. We applied “causal” and “traditional” methods to investigate the association between long-term air pollution exposure (PM2.5 and NO2) and mortality. Methods: We analyzed pooled data from eight well-characterized cohorts and one administrative cohort. We defined the generalized propensity score (GPS) as the conditional likelihood of exposure given confounders, and derived corresponding inverse-probability weights (IPW). We applied Cox-proportional hazard models weighted by IPW, adjusted for GPS, and directly adjusting for all confounders. Results: In IPW models, PM2.5 5 µg/m3 increases were associated with hazard ratios (HR) = 1.141 (95% confidence interval (CI): 1.107, 1.176) and 1.050 (1.014, 1.088) in the pooled and administrative cohorts. Corresponding estimates for traditional Cox models were 1.132 (1.107, 1.158) and 1.057 (1.025, 1.089). Almost identical results were found for all approaches and both pollutants, when unbalanced covariates were adjusted for in causal models. Conclusions: Traditional and causal approaches provided consistent associations between long-term exposure to air pollution and mortality.

Objective: Evidence on potential cardiovascular benefits of personal-level intervention among the elderly exposed to high levels of particulate matter (PM) remains limited. We aimed to assess improvements in surrogate markers of cardiovascular injury in vulnerable populations at risks by using indoor air filtration units. Methods: We conducted a randomized crossover trial for 2 separate 2-week air filtration interventions in 20 households of patients with stable chronic obstructive pulmonary disease and their partners in the winter of 2013, with concurrent measurements of indoor PM. The changes in biomarkers indicative of cardiac injury, atherosclerosis progression and systemic inflammation following intervention were evaluated using linear mixed-effect models. Results: In the analysis, average levels of indoor PM with aerodynamic diameters

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.

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.

Background: The association between long-term exposure to air pollution and mortality from cardiorespiratory diseases is well established, yet the evidence for other diseases remains limited. Objectives: To examine the associations of long-term exposure to air pollution with mortality from diabetes, dementia, psychiatric disorders, chronic kidney disease (CKD), asthma, acute lower respiratory infection (ALRI), as well as mortality from all-natural and cardiorespiratory causes in the Danish nationwide administrative cohort. Methods: We followed all residents aged ≥ 30 years (3,083,227) in Denmark from 1 January 2000 until 31 December 2017. Annual mean concentrations of fine particulate matter (PM2.5), nitrogen dioxide (NO2), black carbon (BC), and ozone (warm season) were estimated using European-wide hybrid land-use regression models (100 m × 100 m) and assigned to baseline residential addresses. We used Cox proportional hazard models to evaluate the association between air pollution and mortality, accounting for demographic and socioeconomic factors. We additionally applied indirect adjustment for smoking and body mass index (BMI). Results: During 47,023,454 person-years of follow-up, 803,881 people died from natural causes. Long-term exposure to PM2.5 (mean: 12.4 µg/m3), NO2 (20.3 µg/m3), and/or BC (1.0 × 10-5/m) was statistically significantly associated with all studied mortality outcomes except CKD. A 5 µg/m3 increase in PM2.5 was associated with higher mortality from all-natural causes (hazard ratio 1.11; 95% confidence interval 1.09–1.13), cardiovascular disease (1.09; 1.07–1.12), respiratory disease (1.11; 1.07–1.15), lung cancer (1.19; 1.15–1.24), diabetes (1.10; 1.04–1.16), dementia (1.05; 1.00–1.10), psychiatric disorders (1.38; 1.27–1.50), asthma (1.13; 0.94–1.36), and ALRI (1.14; 1.09–1.20). Associations with long-term exposure to ozone (mean: 80.2 µg/m3) were generally negative but became significantly positive for several endpoints in two-pollutant models. Generally, associations were attenuated but remained significant after indirect adjustment for smoking and BMI. Conclusion: Long-term exposure to PM2.5, NO2, and/or BC in Denmark were associated with mortality beyond cardiorespiratory diseases, including diabetes, dementia, psychiatric disorders, asthma, and ALRI.

Background: Green space, air pollution and traffic noise exposure may be associated with mental health in adolescents. We assessed the associations of long-term exposure to residential green space, ambient air pollution and traffic noise with mental wellbeing from age 11 to 20 years. Methods: We included 3059 participants of the Dutch PIAMA birth cohort who completed the five-item Mental Health Inventory (MHI-5) at ages 11, 14, 17 and/or 20 years. We estimated exposure to green space (the average Normalized Difference Vegetation Index (NDVI) and percentages of green space in circular buffers of 300 m, 1000 m and 3000 m), ambient air pollution (particulate matter (PM10 and PM2.5), nitrogen dioxide, PM2.5 absorbance and the oxidative potential of PM2.5) and road traffic and railway noise (Lden) at the adolescents’ home addresses at the times of completing the MHI-5. Associations with poor mental wellbeing (MHI-5 score ≤ 60) were assessed by generalized linear mixed models with a logit link, adjusting for covariates. Results: The odds of poor mental wellbeing at age 11 to 20 years decreased with increasing exposure to green space in a 3000 m buffer (adjusted odds ratio (OR) 0.78 [95% CI 0.68–0.88] per IQR increase in the average NDVI; adjusted OR 0.77 [95% CI 0.67–0.88] per IQR increase in the total percentage of green space). These associations persisted after adjustment for air pollution and road traffic noise. Relationships between mental wellbeing and green space in buffers of 300 m and 1000 m were less consistent. Higher air pollution exposure was associated with higher odds of poor mental wellbeing, but these associations were strongly attenuated after adjustment for green space in a buffer of 3000 m, traffic noise and degree of urbanization. Traffic noise was not related to mental wellbeing throughout adolescence. Conclusions: Residential exposure to green space may be associated with a better mental wellbeing in adolescents.

Abstract Background It is well known that maternal smoking during pregnancy and maternal pre-pregnancy overweight have opposite effects on the infants’ birth weight. We report on the association of the combination between both risk factors and the infants’ birth weight. Methods We studied 3241 infants born at term in the PIAMA birth cohort. Maternal smoking during pregnancy and pre-pregnancy height and weight were self-reported. Multivariable regression analysis was performed to assess the associations between infants of mothers who only smoked during pregnancy, who only had pre-pregnancy overweight and who had both risk factors simultaneously, on term birth weight and the risk of being SGA or LGA. Results Of 3241 infants, 421 infants (13%) were born to smoking, non-overweight mothers, 514 (15.8%) to non-smoking, overweight mothers, 129 (4%) to smoking and overweight mothers and 2177 (67%) to non-smoking, non-overweight mothers (reference group). Infants of mothers who smoked and also had pre-pregnancy overweight had similar term birth weight (− 26.6 g, 95%CI: − 113.0, 59.8), SGA risk (OR = 1.06, 95%CI: 0.56, 2.04), and LGA risk (OR = 1.09, 95%CI: 0.61, 1.96) as the reference group. Conclusions Our findings suggested that the effects of maternal smoking during pregnancy and maternal pre-pregnancy overweight on infants’ birth weight cancel each other out. Therefore, birth weight may not be a good indicator of an infant’s health status in perinatal practice because it may mask potential health risks due to these maternal risk factors when both present together.

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.

Abstract Background Evidences that oxidative stress plays a role in the associations between outdoor air pollution and asthma are growing. We aimed to study the role of plasma fluorescent oxidation products levels (FlOPs; an oxidative stress-related biomarker), as potential mediators, in the associations between outdoor air pollution and persistent asthma. Methods Analyses were conducted in 204 adult asthmatics followed up in the French case-control and family study on asthma (EGEA; the Epidemiological study of the Genetic and Environmental factors of Asthma). Persistent asthma was defined as having current asthma at EGEA2 (baseline, 2003–2007) and EGEA3 (follow-up, 2011–2013). Exposures to nitrogen dioxide, nitrogen oxides, road traffic, particulate matter with a diameter ≤ 10 μm (PM10) and ≤ 2.5 μm were estimated by ESCAPE models (2009–2010), and ozone (O3) by IFEN models (2004). We used a mediation analysis to assess the mediated effect by FlOPs levels and the interaction between FlOPs levels and air pollution. Results FlOPs levels increased with PM10 and O3 (adjusted β = 0.04 (95%CI 0.001–0.08), aβ = 0.04 (95%CI 0.009–0.07) per 10 μg/m3, respectively), and the risk of persistent asthma increased with FlOPs levels (aOR = 1.81 (95%CI 1.08–3.02)). The risk of persistent asthma decreased with exposures to NO2, NOx and PM2.5 (aOR ranging from 0.62 to 0.94), and increased with exposures to PM10, O3, O3-summer and road traffic, the greater effect being observed for O3 (aOR = 1.78, 95% CI 0.73–4.37, per 10 μg/m3). Using mediation analysis, we observed a positive total effect (aOR = 2.16, 95%CI 0.70–11.9), a positive direct effect of O3 on persistent asthma (OR = 1.68, 95%CI 0.57–7.25), and a positive indirect effect mediated by FIOPs levels (aOR = 1.28 (95%CI 1.01–2.29)) accounting for 41% of the total effect. Conclusions Our results add insights on the role of oxidative stress in the association between air pollution and persistent asthma.

Background: Evidence is emerging that poor mental health is associated with the environmental exposures of surrounding green, air pollution and traffic noise. Most studies have evaluated only associations of single exposures with poor mental health. Objectives: To evaluate associations of combined exposure to surrounding green, air pollution and traffic noise with poor mental health. Methods: In this cross-sectional study, we linked data from a Dutch national health survey among 387,195 adults including questions about psychological distress, based on the Kessler 10 scale, to an external database on registered prescriptions of anxiolytics, hypnotics & sedatives and antidepressants. We added data on residential surrounding green in a 300 m and a 1000 m buffer based on the Normalized Difference Vegetation Index (NDVI) and a land-use database (TOP10NL), modeled annual average air pollutant concentrations (including particulate matter (PM10, PM2.5), and nitrogen dioxide (NO2)) and modeled road- and rail-traffic noise (Lden and Lnight) to the survey. We used logistic regression to analyze associations of surrounding green, air pollution and traffic noise exposure with poor mental health. Results: In single exposure models, surrounding green was inversely associated with poor mental health. Air pollution was positively associated with poor mental health. Road-traffic noise was only positively associated with prescription of anxiolytics, while rail-traffic noise was only positively associated with psychological distress. For prescription of anxiolytics, we found an odds ratio [OR] of 0.88 (95% CI: 0.85, 0.92) per interquartile range [IQR] increase in NDVI within 300 m, an OR of 1.14 (95% CI: 1.10, 1.19) per IQR increase in NO2 and an OR of 1.07 (95% CI: 1.03, 1.11) per IQR increase in road-traffic noise. In multi exposure analyses, associations with surrounding green and air pollution generally remained but attenuated. Joint odds ratios [JOR], based on the Cumulative Risk Index (CRI) method, of combined exposure to air pollution, traffic noise and decreased surrounding green were higher than the ORs of single exposure models. Associations of environmental exposures with poor mental health differed somewhat by age. Conclusions: Studies including only one of these three correlated exposures may overestimate the influence of poor mental health attributed to the studied exposure, while underestimating the influence of combined environmental exposures. Keywords: NDVI, NO2, PM2.5, Joint odds ratio, Anxiolytics, Hypnotics & sedatives, Antidepressants

Background: It has been suggested that adults who use cleaning agents in their homes have a higher risk of asthma and allergic symptoms. The associations of asthma and allergic symptoms with household use of cleaning agents in adolescents have not been investigated yet. Objectives: To examine the associations of household cleaning agents use with the prevalence of asthma, rhinitis and eczema in adolescents. Methods: In this cross-sectional analysis, we included participants of the PIAMA birth cohort study with data on household use of 10 types of cleaning agents and information on asthma, rhinitis and/or eczema from parent-completed questionnaires at age 14 (N = 2333). For the cleaning agents, we developed a composite score ranging from 0 (no exposure) to 30 points (household use on 4–7 days per week for all 10 types of cleaning agents). Logistic regression was used to analyse associations between household cleaning agents use (composite score and specific cleaning agents) and outcomes, adjusting for potential confounders. Results: Seven, 13 and 11% of the participants had asthma, rhinitis and eczema, respectively, at age 14. The composite score for household use of cleaning agents was not associated with asthma, rhinitis and eczema. For instance, adjusted odds ratios (95% confidence interval) for the prevalence of asthma, rhinitis and eczema comparing those with the highest use of cleaning agents (≥10 points) to those with never/seldom use (0–4 points) were 0.95 (0.56, 1.63), 1.23 (0.82, 1.82) and 0.95 (0.56, 1.63), respectively. For individual cleaning agents, we only found the use of ammonia to be significantly associated with a lower risk of rhinitis [0.60, (0.44, 0.82)]. Conclusions: There was no indication of an increased prevalence of asthma, rhinitis or eczema among adolescents living in households within the highest category of cleaning agents use. Keywords: Cleaning agents, Asthma, Rhinitis, Eczema, Birth cohort, Adolescence

Abstract Background Spirometric lung function measurements have been proven to be excellent objective markers of respiratory morbidity. The use of different types of spirometers in epidemiological and clinical studies may present systematically different results affecting interpretation and implication of results. We aimed to explore considerations in the use of different spirometers in epidemiological studies by comparing forced expiratory volume in 1 s (FEV1) and forced vital capacity (FVC) measurements between the Masterscreen pneumotachograph and EasyOne spirometers. We also provide a correction equation for correcting systematic differences using regression calibration. Methods Forty-nine volunteers had lung function measured on two different spirometers in random order with at least three attempts on each spirometer. Data were analysed using correlation plots, Bland and Altman plots and formal paired t-tests. We used regression calibration to provide a correction equation. Results The mean (SD) FEV1 and FVC was 3.78 (0.63) L and 4.78 (0.63) L for the Masterscreen pneumotachograph and 3.54 (0.60) L and 4.41 (0.83) L for the EasyOne spirometer. The mean FEV1 difference of 0.24 L and mean FVC difference of 0.37 L between the spirometers (corresponding to 6.3 and 8.4% difference, respectively) were statistically significant and consistent between younger ( 30 years) and between males and females. Regression calibration indicated that an increase of 1 L in the EasyOne measurements corresponded to an average increase of 1.032 L in FEV1 and 1.005 L in FVC in the Masterscreen measurements. Conclusion Use of different types of spirometers may result in significant systematic differences in lung function values. Epidemiological researchers need to be aware of these potential systematic differences and correct for them in analyses using methods such as regression calibration.

Background: It has been suggested that children who are exposed to agricultural pesticides have an increased risk of asthma, but evidence for associations betweeen residential pesticide exposure and childhood asthma is inconsistent. Objectives: To investigate the associations of residential pesticide exposure with the prevalence of asthma and related symptoms within a Dutch birth cohort study. Methods: In this cross-sectional analysis, we included participants of the PIAMA birth cohort study with data on residential pesticide exposure and asthma from parent-completed questionnaires at age 14, collected in 2012 (N = 1473). We used spatial data on the presence of individual crops (cereals, open field vegetables, commercial crops, open field floriculture/bulbs, corn and potatoes) and pesticide application on these crops to estimate residential exposure to pesticides with known irritant properties for the respiratory system within distances of 100, 500, and 1000 m of the participants' homes. Logistic regression was used to estimate associations between exposure and outcomes, adjusting for potential confounders. Results: No associations were found between living within 100, 500 and 1000 m of agricultural fields likely treated with pesticides and symptoms of asthma. For instance, for participants living within 100 m of fields with any crops likely treated with pesticides, the adjusted odds ratios (95% confidence interval) for the prevalence of asthma, shortness of breath and dry night cough at age 14 were 0.31 (0.07, 1.32), 0.61 (0.23, 1.57) and 1.26 (0.56, 2.80), respectively. No associations were found between estimated exposure to pesticides with known irritant properties for the respiratory system and asthma or related symptoms. Conclusions: There was no association between living near agricultural fields likely treated with pesticides and asthma and related respiratory symptoms, among our study participants. Keywords: Agricultural pesticides, Respiratory outcomes, Asthma, Birth cohort, Adolescents

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.

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

Introduction: To characterize air pollution exposure at a fine spatial scale, different exposure assessment methods have been applied. Comparison of associations with health from different exposure methods are scarce. The aim of this study was to evaluate associations of air pollution based on hybrid, land-use regression (LUR) and dispersion models with natural cause and cause-specific mortality. Methods: We followed a Dutch national cohort of approximately 10.5 million adults aged 29+ years from 2008 until 2012. We used Cox proportional hazard models with age as underlying time scale and adjusted for several potential individual and area-level socio-economic status confounders to evaluate associations of annual average residential NO2, PM2.5 and BC exposure estimates based on two stochastic models (Dutch LUR, European-wide hybrid) and deterministic Dutch dispersion models. Results: Spatial variability of PM2.5 and BC exposure was smaller for LUR compared to hybrid and dispersion models. NO2 exposure variability was similar for the three methods. Pearson correlations between hybrid, LUR and dispersion modeled NO2 and BC ranged from 0.72 to 0.83; correlations for PM2.5 were slightly lower (0.61–0.72). In general, all three models showed stronger associations of air pollutants with respiratory disease and lung cancer mortality than with natural cause and cardiovascular disease mortality. The strength of the associations differed between the three exposure models. Associations of air pollutants estimated by LUR were generally weaker compared to associations of air pollutants estimated by hybrid and dispersion models. For natural cause mortality, we found a hazard ratio (HR) of 1.030 (95% confidence interval (CI): 1.019, 1.041) per 10 µg/m3 for hybrid modeled NO2, a HR of 1.003 (95% CI: 0.993, 1.013) per 10 µg/m3 for LUR modeled NO2 and a HR of 1.015 (95% CI: 1.005, 1.024) per 10 µg/m3 for dispersion modeled NO2. Conclusion: Air pollution was positively associated with natural cause and cause-specific mortality, but the strength of the associations differed between the three exposure models. Our study documents that the selected exposure model may contribute to heterogeneity in effect estimates of associations between air pollution and health.

While there is clear evidence that high levels of pollution are associated with increased all-cause mortality and cardiovascular mortality and morbidity, the biological mechanisms that would explain this association are less understood. We examined the association between long-term exposure to air pollutants and risk factors associated with cardiovascular disease. Air pollutant concentrations were estimated at place of residence for cohort members in the Western Australian Centre for Health and Ageing Health in Men Study. Blood samples and blood pressure measures were taken for a cohort of 4249 men aged 70 years and above between 2001 and 2004. We examined the association between 1-year average pollutant concentrations with blood pressure, cholesterol, triglycerides, C-reactive protein, and total homocysteine. Linear regression analyses were carried out, with adjustment for confounding, as well as an assessment of potential effect modification. The four pollutants examined were fine particulate matter, black carbon (BC), nitrogen dioxide, and nitrogen oxides. We found that a 2.25 μg/m3 higher exposure to fine particulate matter was associated with a 1.1 percent lower high-density cholesterol (95% confidence interval: -2.4 to 0.1) and 4.0 percent higher serum triglycerides (95% confidence interval: 1.5 to 6.6). Effect modification of these associations by diabetes history was apparent. We found no evidence of an association between any of the remaining risk factors or biomarkers with measures of outdoor air pollution. These findings indicate that long-term PM2.5 exposure is associated with elevated serum triglycerides and decreased HDL cholesterol. This requires further investigation to determine the reasons for this association.

Background: Most previous studies that investigated associations of surrounding green, air pollution or traffic noise with mortality focused on single exposures. Objectives: The aim of this study was to evaluate combined associations of long-term residential exposure to surrounding green, air pollution and traffic noise with total non-accidental and cause-specific mortality. Methods: We linked a national health survey (Public Health Monitor, PHM) conducted in 2012 to the Dutch longitudinal mortality database. Subjects of the survey who were 30 years or older on 1 January 2013 (n = 339,633) were followed from 1 January 2013 till 31 December 2017. We used Cox proportional hazard models to evaluate associations of residential surrounding green (including the average Normalized Difference Vegetation Index (NDVI) in buffers of 300 m and 1000 m), annual average air pollutant concentrations (including particulate matter (PM10, PM2.5), nitrogen dioxide (NO2)) and traffic noise with non-accidental, circulatory disease, respiratory disease, lung cancer and neurodegenerative disease mortality. Results: We observed 26,886 non-accidental deaths over 1.627.365 person-years of follow-up. Surrounding green, air pollution and traffic noise exposure were not significantly associated with non-accidental or cause-specific mortality. For non-accidental mortality, we found a hazard ratio (HR) of 0.99 (0.98, 1.01) per IQR increase in NDVI 300 m, a HR of 0.99 (95% CI: 0.97, 1.01) per IQR increase in NO2, a HR of 0.98 (0.97, 1.00) per IQR increase in PM2.5 and a HR of 0.99 (95% CI: 0.97, 1.01) per IQR increase in road-traffic noise. Analyses restricted to non-movers or excluding subjects aged 85+ years did not change the findings. Conclusion: We found no evidence for associations of long-term residential exposures to surrounding green, air pollution and traffic noise with non-accidental or cause-specific mortality in a large population based survey in the Netherlands, possibly related to the relatively short follow-up period. Keywords: NDVI, NO2, PM2.5, Traffic noise, Mortality

Abstract Background Air pollution has been found to adversely affect children’s lung function. Forced expiratory volume in 1 s and forced vital capacity from spirometry have been studied most frequently, but measurements of airway resistance may provide additional information. We assessed associations of long-term air pollution exposure with airway resistance. Methods We measured airway resistance at age 8 with the interrupter resistance technique (Rint) in participants of the Dutch PIAMA birth cohort study. We linked Rint with estimated annual average air pollution concentrations [nitrogen oxides (NO2, NOx), PM2.5 absorbance (“soot”), and particulate matter

Abstract Background Heavy industry emits many potentially hazardous pollutants into the air which can affect health. However, the effects of air pollution from heavy industry on lung function and respiratory symptoms have been investigated scarcely. Our aim was to investigate the associations of long-term air pollution from heavy industry with lung function and respiratory symptoms in school children. Methods A cross-sectional lung function study was conducted among school children (7–13 years) in the vicinity of an area with heavy industry. Lung function measurements were conducted during school hours. Parents of the children were asked to complete a questionnaire about the health of their children. A dispersion model was used to characterize the additional individual-level exposures to air pollutants from the industry in the area. Associations between PM2.5 and NOX exposure with lung function and presence of respiratory symptoms were investigated by linear and/or logistic regression analysis. Results Participation in the lung function measurements and questionnaires was 84% (665/787) and 77% (603/787), respectively. The range of the elevated PM2.5 and NOX five years average concentrations (2008–2012) due to heavy industry were 0.04–1.59 μg/m3 and 0.74–11.33 μg/m3 respectively. After adjustment for confounders higher exposure to PM2.5 and NOX (per interquartile range of 0.56 and 7.43 μg/m3 respectively) was associated with lower percent predicted peak expiratory flow (PEF) (B -2.80%, 95%CI -5.05% to − 0.55% and B -3.67%, 95%CI -6.93% to − 0.42% respectively). Higher exposure to NOX (per interquartile range of 7.43 μg/m3) was also associated with lower percent forced vital capacity (FVC) and percent predicted forced expiration volume in 1 s (FEV1) (B -2.30, 95% CI -4.55 to − 0.05 and B -2.73, 95%CI -5.21 to − 0.25 respectively). No significant associations were found between the additional exposure to PM2.5 or NOX and respiratory symptoms except for PM2.5 and dry cough (OR 1.40, 95%CI 1.00 to 1.94). Conclusion Exposure to PM2.5 and NOX from industry was associated with decreased lung function. Exposure to PM2.5 was also associated with parents’ reports of dry cough among their children.

Background: The evidence from observational epidemiological studies of a link between long-term air pollution exposure and diabetes prevalence and incidence is currently mixed. Some studies found the strongest associations of diabetes with fine particles, other studies with nitrogen dioxide and some studies found no associations. Objectives: Our aim was to investigate associations between long-term exposure to multiple air pollutants and diabetes prevalence in a large national survey in the Netherlands. Methods: We performed a cross-sectional analysis using the 2012 Dutch national health survey to investigate the associations between the 2009 annual average concentrations of multiple air pollutants (PM10, PM2.5, PM10−2.5, PM2.5 absorbance, OPDTT, OPESR and NO2) and diabetes prevalence, among 289,703 adults. Air pollution exposure was assessed by land use regression models. Diabetes was defined based on a combined measure of self-reported physician diagnosis and medication prescription from an external database. Using logistic regression, we adjusted for potential confounders, including neighborhood- and individual socio-economic status and lifestyle-related risk factors such as smoking habits, alcohol consumption, physical activity and BMI. Results: After adjustment for potential confounders, all pollutants (except PM2.5) were associated with diabetes prevalence. In two-pollutant models, NO2 and OPDTT remained associated with increased diabetes prevalence. For NO2 and OPDTT, single-pollutant ORs per interquartile range were 1.07 (95% CI: 1.05, 1.09) and 1.08 (95% CI: 1.05, 1.10), respectively. Stratified analysis showed no consistent effect modification by any of the included known diabetes risk factors. Conclusions: Long-term residential air pollution exposure was associated with diabetes prevalence in a large health survey in the Netherlands, strengthening the evidence of air pollution being an important diabetes risk factor. Most consistent associations were observed for NO2 and oxidative potential of PM2.5 measured by the DTT assay. The finding of an association with the oxidative potential of fine particles but not with PM2.5, suggests that particle composition may be important for a potential effect on diabetes.

Background: Green space has been hypothesized to improve cardiometabolic health of adolescents, whereas air pollution and traffic noise may negatively impact cardiometabolic health. Objectives: To examine the associations of green space, air pollution and traffic noise with cardiometabolic health in adolescents aged 12 and 16 years. Methods: Waist circumference, blood pressure, cholesterol and glycated hemoglobin (HbA1c) were measured in subsets of participants of the Dutch PIAMA birth cohort, who participated in medical examinations at ages 12 (n = 1505) and/or 16 years (n = 797). We calculated a combined cardiometabolic risk score for each participant, with a higher score indicating a higher cardiometabolic risk. We estimated exposure to green space (i.e. the average Normalized Difference Vegetation Index (NDVI) and percentages of green space in circular buffers of 300 m and 3000 m), air pollution (by land-use regression models) and traffic noise (using the Standard Model Instrumentation for Noise Assessments (STAMINA) model) at the adolescents' home addresses at the time of the medical examinations. We assessed associations of these exposures with cardiometabolic health outcomes at ages 12 and 16 by multiple linear regression, adjusting for potential confounders. Results: We did not observe consistent patterns of associations of green space, air pollution and traffic noise with the cardiometabolic risk score, blood pressure, total cholesterol levels, the total/HDL cholesterol ratio and HbA1c. We found inverse associations of air pollution with waist circumference at both age 12 and 16. These associations weakened after adjustment for region, except for particulate matter with a diameter of

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

Adolescents with high educational attainment generally have better outcomes across the lifespan than adolescents with lower educational attainment. This study investigated how three measures of socioeconomic status (SES)-maternal education, paternal education, and neighbourhood SES-combined to predict adolescent educational attainment (track level at age 17). We proposed three mechanisms for this pathway: cognitive ability (at age 11), primary school teacher assessment (stating the secondary education level suitable for a child at age 11), and educational expectations (at age 14). Using the data of 2,814 Dutch adolescents from the Prevention and Incidence of Asthma and Mite Allergy (PIAMA) study, logistic regressions tested associations between SES and educational attainment. Structural equation modelling (SEM) tested mediational pathways between SES and educational attainment. In models with three SES measures, having a medium-educated mother was associated with higher educational attainment relative to having a low-educated mother (OR; 95% CI: 1.83; 1.41-2.38), and having a high-educated mother was associated with higher educational attainment relative to having a low-educated mother (OR; 95% CI: 3.44; 2.59-4.55). The odds ratios for paternal education showed a similar pattern. We found no association between neighbourhood SES and adolescent educational attainment, so neighbourhood SES was removed from further analyses. Mediational analyses revealed that cognitive ability (30.0%), teacher assessment (28.5%), and educational expectations (1.2%) explained 59.8% of the total association between parental SES and educational attainment. The results showed that mother education and father education were both important for understanding the strong association between parental SES and adolescent educational attainment. In the Netherlands, the association between parental SES and educational attainment can be largely explained by cognitive ability and teacher assessments.

Heavy industry emits many potentially hazardous pollutants into the air which can affect health. Awareness about the potential health impacts of air pollution from industry can influence people's risk perception. This in turn can affect (self-reported) symptoms. Our aims were to investigate the associations of air pollution from heavy industry with health symptoms and to evaluate whether these associations are mediated by people's risk perception about local industry.A cross-sectional questionnaire study was conducted among children (2-18 years) and adults (19 years and above) living in the direct vicinity of an area with heavy industry. A dispersion model was used to characterize individual-level exposures to air pollution emitted from the industry in the area. Associations between PM2.5 and NOX with presence of chronic diseases (adults) and respiratory symptoms (adults and children) were investigated by logistic regression analysis. Risk perception was indirectly measured by worries about local industry (0-10 scale). Mediation analyses were performed to investigate the role of mediation by these worries.The response was 54% (2,627/4,877). In adults exposure to modelled PM2.5 from industry (per μg/m3) was related with reported high blood pressure (OR 1.56, 95% CI 1.13-2.15) and exposure to modelled NOX (per μg/m3) was inversely related with cardiovascular diseases (OR 0.91, 95% CI 0.84-0.98). In children higher PM2.5 and NOX concentrations (per μg/m3) were related with wheezing (OR 2.00, 95% CI 1.24-3.24 and OR 1.13, 95% CI 1.06-1.21 respectively) and dry cough (OR 2.33, 95% CI 1.55-3.52 and OR 1.16, 95% CI 1.10-1.22 respectively). Parental worry about local industry was an important mediator in exposure-health relations in children (indirect effect between 19-28%).Exposure from industry was associated with self-reported reported high blood pressure among adults and respiratory symptoms among their children. Risk perception was found to mediate these associations for children.

Background: Land-use regression (LUR) and dispersion models (DM) are commonly used for estimating individual air pollution exposure in population studies. Few comparisons have however been made of the performance of these methods. Objectives: Within the European Study of Cohorts for Air Pollution Effects (ESCAPE) we explored the differences between LUR and DM estimates for NO2, PM10 and PM2.5. Methods: The ESCAPE study developed LUR models for outdoor air pollution levels based on a harmonised monitoring campaign. In thirteen ESCAPE study areas we further applied dispersion models. We compared LUR and DM estimates at the residential addresses of participants in 13 cohorts for NO2; 7 for PM10 and 4 for PM2.5. Additionally, we compared the DM estimates with measured concentrations at the 20–40 ESCAPE monitoring sites in each area. Results: The median Pearson R (range) correlation coefficients between LUR and DM estimates for the annual average concentrations of NO2, PM10 and PM2.5 were 0.75 (0.19–0.89), 0.39 (0.23–0.66) and 0.29 (0.22–0.81) for 112,971 (13 study areas), 69,591 (7) and 28,519 (4) addresses respectively. The median Pearson R correlation coefficients (range) between DM estimates and ESCAPE measurements were of 0.74 (0.09–0.86) for NO2; 0.58 (0.36–0.88) for PM10 and 0.58 (0.39–0.66) for PM2.5. Conclusions: LUR and dispersion model estimates correlated on average well for NO2 but only moderately for PM10 and PM2.5, with large variability across areas. DM predicted a moderate to large proportion of the measured variation for NO2 but less for PM10 and PM2.5. Keywords: Land use regression, Dispersion modelling, Air pollution, Exposure, Cohort

PURPOSE:To investigate the association between exposure to traffic-related air pollution and use of spectacles (as a surrogate measure for myopia) in schoolchildren. METHODS:We analyzed the impact of exposure to NO2 and PM2.5 light absorbance at home (predicted by land-use regression models) and exposure to NO2 and black carbon (BC) at school (measured by monitoring campaigns) on the use of spectacles in a cohort of 2727 schoolchildren (7-10 years old) in Barcelona (2012-2015). We conducted cross-sectional analyses based on lifelong exposure to air pollution and prevalent cases of spectacles at baseline data collection campaign as well as longitudinal analyses based on incident cases of spectacles use and exposure to air pollution during the three-year period between the baseline and last data collection campaigns. Logistic regression models were developed to quantify the association between spectacles use and each of air pollutants adjusted for relevant covariates. RESULTS:An interquartile range increase in exposure to NO2 and PM2.5 absorbance at home was respectively associated with odds ratios (95% confidence intervals (CIs)) for spectacles use of 1.16 (1.03, 1.29) and 1.13 (0.99, 1.28) in cross-sectional analyses and 1.15 (1.00, 1.33) and 1.23 (1.03, 1.46) in longitudinal analyses. Similarly, odds ratio (95% CIs) of spectacles use associated with an interquartile range increase in exposures to NO2 and black carbon at school was respectively 1.32 (1.09, 1.59) and 1.13 (0.97, 1.32) in cross-sectional analyses and 1.12 (0.84, 1.50) and 1.27 (1.03, 1.56) in longitudinal analyses. These findings were robust to a range of sensitivity analyses that we conducted. CONCLUSION:We observed increased risk of spectacles use associated with exposure to traffic-related air pollution. These findings require further confirmation by future studies applying more refined outcome measures such as quantified visual acuity and separating different types of refractive errors.

Objectives. To evaluate sensitization and acute respiratory health effects in inhabitants living in the vicinity of a factory producing soy oil. Methods. Two panels of potential responders were created on the basis of a response to a short screening questionnaire sent to random samples of 1,000 exposed and 1,000 non-exposed individuals living around the factory and a control area. Individuals responding to the questionnaire were invited for a medical evaluation, including a respiratory symptom questionnaire and skin prick testing, for a panel of common allergens and a soy allergen extract. This resulted in 53 atopic and/or asthmatic inhabitants from the area surrounding the factory and 30 comparable control subjects. In these subjects, morning and evening Peak Expiratory Flow (PEF), respiratory symptoms and medication use were recorded daily during a 10-week period in the autumn. At the same time, soy allergen and endotoxin concentrations were determined in airborne dust in the exposed and the control area. The wind direction relative to the location of a subjects’ house and the factory was used to determine whether an individual was exposed on a particular day. Results. Only few of the atopic subjects were sensitized to soy. PEF showed a decrease, respiratory symptoms and bronchodilator use, an increase among soy sensitized subjects after having been downwind from the factory. Airborne soy allergen was found more frequently in the area surrounding the factory and levels were higher than in the control area. Highest levels were found on the factory premises. Only a weak association was found with wind direction. Airborne endotoxin concentrations did not show a consistent pattern with distance, but levels were clearly higher on the factory premises. Conclusion. Sensitization to soy allergen was not increased among the population sample living in the vicinity of the factory. Soy sensitized individuals living in the surroundings of the factory reported more respiratory symptoms, used bronchodilators more often and had a lower PEF after having been downwind of the factory.

HbA1c is associated with cardiovascular risk in persons without diabetes and cardiovascular risk accumulates over the life course. Therefore, insight in factors determining HbA1c from childhood onwards is important. We investigated (lifestyle) determinants of HbA1c at age 12 years and the effects of growth on change in HbA1c and the tracking of HbA1c between the age of 8 and 12 years.Anthropometric measurements were taken and HbA1c levels were assessed in 955 children without diabetes aged around 12 years participating in the PIAMA birth cohort study. In 363 of these children HbA1c was also measured at age 8 years. Data on parents and children were collected prospectively by questionnaires.We found no significant association between known risk factors for diabetes and HbA1c at age 12 years. Mean(SD) change in HbA1c between ages 8 and 12 years was 0.6(0.7) mmol/mol per year (or 0.1(0.1) %/yr). Anthropometric measures at age 8 and their change between age 8 and 12 years were not associated with the change in HbA1c. 68.9% of the children remained in the same quintile or had an HbA1c one quintile higher or lower at age 8 years compared to age 12 years.The lack of association between known risk factors for diabetes and HbA1c suggest that HbA1c in children without diabetes is relatively unaffected by factors associated with glycaemia. HbA1c at age 8 years is by far the most important predictor of HbA1c at age 12. Therefore, the ranking of HbA1c levels appear to be fairly stable over time.

An inhibition enzyme immunoassay was developed for quantitation of (1→3)-β-D-glucans in the indoor environment. Immunospecific rabbit antibodies were produced by immunization with bovine serum albuminconjugated laminarin.The laminarin calibration curve ranged from 40 to 3000 ng/ml.Another (1→3)-β-D-glucan (curdlan) showed a similar inhibition curve, but was less reactive on a weight basis. Pustulan, presumed to be (1→3)-β-D-glucan, also showed immunoreactivity in the assay. Control experiments indicated that this was due to (1→3)-β-D-glucan structures. Other non-(1→3)-β-D-glucan polysaccharides did not react. (1→3)-β-Dglucan was detectable in dust from a variety of occupational and environmental settings. We conclude that the new assay offers a useful method for indoor (1→3)-β-Dglucan exposure assessment.

Exposure to ambient particulate matter (PM) has been associated with adverse cardiovascular effects in epidemiological studies. Current knowledge of independent effects of individual PM characteristics remains limited.Using a semi-experimental design we investigated which PM characteristics were consistently associated with blood biomarkers believed to be predictive of the risk of cardiovascular events. We exposed healthy adult volunteers at 5 different locations chosen to provide PM exposure contrasts with reduced correlations among PM characteristics. Each of the 31 volunteers was exposed for 5 h, exercising intermittently, 3-7 times at different sites from March to October 2009. Extensive on-site exposure characterization included measurements of PM mass and number concentration, elemental- (EC) and organic carbon (OC), trace metals, sulfate, nitrate, and PM oxidative potential (OP). Before and 2 h and 18 h after exposure we measured acute vascular blood biomarkers - C-reactive protein, fibrinogen, platelet counts, von Willebrand Factor, and tissue plasminogen activator/plasminogen activator inhibitor-1 complex. We used two-pollutant models to assess which PM characteristics were most consistently associated with the measured biomarkers.We found OC, nitrate and sulfate to be most consistently associated with different biomarkers of acute cardiovascular risk. Associations with PM mass concentrations and OP were less consistent, whereas other measured components of the air pollution mixture, including PNC, EC, trace metals and NO2, were not associated with the biomarkers after adjusting for other pollutants.

ObjectiveTo examine the associations between pet keeping in early childhood and asthma and allergies in children aged 6-10 years.DesignPooled analysis of individual participant data of 11 prospective European birth cohorts that recruited a total of over 22,000 children in the 1990s. EXPOSURE DEFINITION: Ownership of only cats, dogs, birds, rodents, or cats/dogs combined during the first 2 years of life. OUTCOME DEFINITION: Current asthma (primary outcome), allergic asthma, allergic rhinitis and allergic sensitization during 6-10 years of age.Data synthesisThree-step approach: (i) Common definition of outcome and exposure variables across cohorts; (ii) calculation of adjusted effect estimates for each cohort; (iii) pooling of effect estimates by using random effects meta-analysis models.ResultsWe found no association between furry and feathered pet keeping early in life and asthma in school age. For example, the odds ratio for asthma comparing cat ownership with "no pets" (10 studies, 11489 participants) was 1.00 (95% confidence interval 0.78 to 1.28) (I(2) = 9%; p = 0.36). The odds ratio for asthma comparing dog ownership with "no pets" (9 studies, 11433 participants) was 0.77 (0.58 to 1.03) (I(2) = 0%, p = 0.89). Owning both cat(s) and dog(s) compared to "no pets" resulted in an odds ratio of 1.04 (0.59 to 1.84) (I(2) = 33%, p = 0.18). Similarly, for allergic asthma and for allergic rhinitis we did not find associations regarding any type of pet ownership early in life. However, we found some evidence for an association between ownership of furry pets during the first 2 years of life and reduced likelihood of becoming sensitized to aero-allergens.ConclusionsPet ownership in early life did not appear to either increase or reduce the risk of asthma or allergic rhinitis symptoms in children aged 6-10. Advice from health care practitioners to avoid or to specifically acquire pets for primary prevention of asthma or allergic rhinitis in children should not be given.

BACKGROUND: There is evidence that rapid weight gain during the first year of life is associated with overweight later in life. However, results from studies exploring other critical periods for the development of overweight are inconsistent. OBJECTIVE: The objective was to investigate BMI development to assess at what ages essential differences between normal weight and overweight children occur, and to assess which age intervals the most strongly influence the risk of overweight at 8 years of age. METHODS: Longitudinal weight and height data were collected by annual questionnaires in a population of 3963 children participating in the PIAMA birth cohort study. BMI and BMI standard deviation scores (SDS) were calculated for every year from birth until 8 years of age. BMI, BMI SDS and BMI SDS change in each 1-year-age interval were compared between children with and without overweight at 8 years of age, using t-tests, logistic regression analysis and the analysis of response profiles method. RESULTS: At 8 years of age, 10.5% of the children were overweight. Already at the age of 1 year, these children had a significantly higher mean BMI SDS than normal weight 8-year-olds, (0.53 vs 0.04). In each 1-year-age interval the change in BMI SDS was significantly associated with overweight at 8 years with odds ratios increasing from 1.14 (95% CI 1.04-1.24) per 1 SDS increase at 0-1 year to 2.40 (95% CI 2.09-2.76) at 7-8 years. CONCLUSION: At every age, starting already in the first year of life, a rapid increase in BMI SDS was significantly associated with overweight risk at the age of 8 years. There was no evidence for a specific critical period for the development of overweight. Prevention of overweight should start early in life and be continued with age-specific interventions throughout childhood.

OBJECTIVE: Childhood and adolescent overweight, defined by body mass index (BMI) are associated with an increased risk of cardiovascular disease in later life. Abdominal adiposity may be more important in associations with cardiovascular diseases but waist circumference (WC) has been rarely studied in children. We studied associations between BMI and WC and blood pressure (BP) and cholesterol in 12-year-old children and prospectively changes in BMI or WC status between age 8 and 12 years and BP and cholesterol at age 12. STUDY DESIGN: Weight, height, WC, BP and cholesterol concentrations were measured in 1432 children at age 12 years. Linear regression was used to study the associations between high BMI and large WC (>90(th) percentile) and BP and cholesterol. RESULTS: Systolic BP was 4.9 mmHg higher (95% (CI 2.5, 7.2) in girls and 4.2 mmHg (95%CI 1.9, 6.5) in boys with a high BMI. Large WC was also associated with higher systolic BP in girls (3.7 mmHg (95%CI 1.3, 6.1)) and boys (3.5 mmHg (95%CI 1.2, 5.8)). Diastolic BP and cholesterol concentrations were significantly positively (HDL cholesterol negatively) associated with high BMI and large WC, too. Normal weight children with a history of overweight did not have higher blood pressure levels or adverse cholesterol concentrations than children that were normal weight at both ages. CONCLUSION: A high BMI and large WC were associated with higher BP levels and adverse cholesterol concentrations. WC should be taken into account when examining cardiovascular risk factors in children.

BACKGROUND: Adult cholesterol concentrations might be influenced by early-life factors, such as breastfeeding and birth weight, referred to as "early programming". How such early factors exert their influence over the life course is still poorly understood. Evidence from studies in children and adolescents is scarce and conflicting. We investigated the influence of 6 different perinatal risk factors on childhood total and HDL cholesterol concentrations and total-to-HDL cholesterol ratio measured at 8 years of age, and additionally we studied the role of the child's current Body Mass Index (BMI). METHODS: Anthropometric measures and blood plasma samples were collected during a medical examination in 751 8-year-old children participating in the prospective Prevention and Incidence of Asthma and Mite Allergy (PIAMA) birth cohort study. Linear and logistic regression were performed to estimate associations of total and HDL cholesterol concentrations with breastfeeding, birth weight, infant weight gain, maternal overweight before pregnancy, gestational diabetes and maternal smoking during pregnancy, taking into account the child's current BMI. RESULTS: Linear regressions showed an association between total-to-HDL cholesterol ratio and maternal pre-pregnancy overweight (β = 0.15, Confidence Interval 95% (CI): 0.02, 0.28), rapid infant weight gain (β = 0.13, 95%CI: 0.01, 0.26), and maternal smoking during pregnancy (β = 0.14, 95%CI: 0.00, 0.29). These associations were partly mediated by the child's BMI. CONCLUSION: Total-to-HDL cholesterol ratio in 8-year-old children was positively associated with maternal pre-pregnancy overweight, maternal smoking during pregnancy and rapid infant weight gain.

Objective. To prospectively identify behavioral risk factors for childhood overweight and to assess their relevance in high risk sub groups (children of mothers with overweight or low education). Methods. In the PIAMA birth cohort (𝑛=3963), questionnaire data were obtained at ages 5 and 7 on “screen time”, walking or cycling to school, playing outside, sports club membership, fast food consumption, snack consumption and soft drink consumption. Weight and height were measured at age 8 years. Results. Screen time, but none of the other hypothesized behavioral factors, was associated with overweight (aOR 1.4 (CI: 1.2–1.6)). The adjusted population attributable risk fraction for screen time > 1 hr/day was 10% in the high risk and 17% in the low risk sub groups. Conclusion. Reduction of screen time to < 1 hr/day could result in a reduction of overweight prevalence in the order of 2 percentage points in both high and low risks sub groups.