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•First LUR models for UFP on a national scale.•Combining targeted mobile monitoring with long-term regional background monitoring.•Different algorithms predicted external measurements ...well and correlated highly.•Deconvolution can improve large-area exposure assessment.•Models will be applied in Dutch nation-wide health studies.
Large nation- and region-wide epidemiological studies have provided important insights into the health effects of long-term exposure to outdoor air pollution. Evidence from these studies for the long-term effects of ultrafine particles (UFP), however is lacking. Reason for this is the shortage of empirical UFP land use regression models spanning large geographical areas including cities with varying topographies, peri-urban and rural areas. The aim of this paper is to combine targeted mobile monitoring and long-term regional background monitoring to develop national UFP models.
We used an electric car to monitor UFP concentrations in selected cities and towns across the Netherlands over a 14-month period in 2016–2017. Routes were monitored 3 times and concentrations were averaged per road segment. In addition, we used kriging maps based on regional background monitoring (20 sites; 3 × 2 weeks) over the same period to assess annual average regional background concentrations. All road segments were used to model spatial variation of UFP with three different land-use (regression) approaches: supervised stepwise regression, LASSO and random forest. For each approach, we also tested a deconvolution method, which segregates the average concentration at each road segment into a local and background signal. Model performance was evaluated with short-term (400 sites across the Netherlands; 3 × 30 minutes) and external longer-term measurements (42 sites in two major cities; 3 × 24 hours). We also compared predictions of all six models at 1000 random addresses spread over the country.
We found similar predictive performance for the six models, with validation R2 values from 0.25 to 0.35 for short-term measurements and 0.52 to 0.60 for longer-term external measurements. Models with and without deconvolution had similar predictive performance. All models based on the deconvolution method included a regional background kriging map as important predictor. Correlations between predictions at random addresses were high with Pearson correlations from 0.84 to 0.99. Models overestimated exposure at the short-term and long-term sites by about 20–30% in all cases, with small differences between regions and road types.
We developed robust nation-wide models for long-term UFP exposure combining mobile monitoring with long-term regional background monitoring. Minor differences in predictive performance between different algorithms were found, but the deconvolution approach is considered more physically realistic. The models will be applied in Dutch nation-wide health studies.
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.
To evaluate associations of combined exposure to surrounding green, air pollution and traffic noise with poor mental health.
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.
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.
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.
•Surrounding green was inversely associated with poor mental health.•Air pollution and to a limited extent traffic noise were positively associated with poor mental health.•In multi exposure models, associations with surrounding green and air pollution attenuated, but remained significant.•The most consistent associations were observed with prescription of anxiolytics and prescription of hypnotics & sedatives.•Joint odds ratios of combined exposure were higher than the ORs of single exposure models.
Half the world's population lives in urban areas. It is therefore important to identify characteristics of the built environment that are beneficial to human health. Urban greenness has been ...associated with improvements in a diverse range of health conditions, including birth outcomes; however, few studies have attempted to distinguish potential effects of greenness from those of other spatially correlated exposures related to the built environment.
We aimed to investigate associations between residential greenness and birth outcomes and evaluate the influence of spatially correlated built environment factors on these associations.
We examined associations between residential greenness measured using satellite-derived Normalized Difference Vegetation Index (NDVI) within 100 m of study participants' homes and birth outcomes in a cohort of 64,705 singleton births (from 1999-2002) in Vancouver, British Columbia, Canada. We also evaluated associations after adjusting for spatially correlated built environmental factors that may influence birth outcomes, including exposure to air pollution and noise, neighborhood walkability, and distance to the nearest park.
An interquartile increase in greenness (0.1 in residential NDVI) was associated with higher term birth weight (20.6 g; 95% CI: 16.5, 24.7) and decreases in the likelihood of small for gestational age, very preterm (< 30 weeks), and moderately preterm (30-36 weeks) birth. Associations were robust to adjustment for air pollution and noise exposures, neighborhood walkability, and park proximity.
Increased residential greenness was associated with beneficial birth outcomes in this population-based cohort. These associations did not change after adjusting for other spatially correlated built environment factors, suggesting that alternative pathways (e.g., psychosocial and psychological mechanisms) may underlie associations between residential greenness and birth outcomes.
Ambient air pollution is controllable, and it is one of the greatest environmental threats to human health. Studies conducted worldwide have provided evidence that maternal exposure to ambient air ...pollution during pregnancy enhances the risk of low birth weight at term (TLBW, <2500g among infants born ≥37 completed weeks of gestation), a maker of intrauterine growth restriction (IUGR), and suggest that some subgroups of pregnant women who are smoking, of low or high body-mass index (BMI), low socioeconomic status (SES) or asthma are more vulnerable towards the effect of ambient air pollution. The aim of this commentary is to review the published literature on the association between ambient air pollution and TLBW regarding increased vulnerability for the above-mentioned subgroups.
Although more than fifty epidemiological studies have examined the associations between ambient air pollution and TLBW to date, we only identified six studies that examined the potential effect modification of the association between ambient air pollution and TLBW by the above listed maternal risk factors. Two studies assessed effect modification caused by smoking on the association between ambient air pollution and TLBW. The adjusted odds ratio (OR) for TLBW associated with exposure to ambient air pollution were in one study higher among women who smoked during pregnancy, as compared to the OR of non-smoking women, while in the other study the association was in the opposite direction. The association of ambient air pollution and TLBW were higher among women characterized by extreme BMI (two studies) and low SES compared to non-obese women or women of higher SES (four studies), respectively. Only one study reported the estimated effects among asthmatic and non-asthmatic women and no statistically significant effect modification was evident for the risk of TLBW associated with ambient air pollution.
The current epidemiologic evidence is scarce, but suggests that pregnant women who are smoking, being underweight, overweight/obese or having lower SES are a vulnerable subpopulation when exposed to ambient air pollution, with and increased risk of having a child with TLBW. The limited evidence precludes for definitive conclusions and further studies are recommended.
•Ambient air pollution increases the risk of intrauterine growth restriction (IUGR).•Smokers and women of under/overweight or low SES may be more vulnerable.•Further studies are recommended as the epidemiological evidence is limited.
IntroductionThe oxidative potential (OP) of particulate matter (PM) has been proposed as a health-relevant metric, but currently few epidemiological studies investigated associations of OP with ...health. Our main aim was to assess associations of long-term exposure to OP with respiratory health in children. Our second aim was to evaluate whether OP is more consistently associated with respiratory health than PM mass, PM composition or nitrogen dioxide (NO2).MethodsFor 3701 participants of a prospective birth cohort, annual average concentrations of OP (assessed by spin resonance (OPESR) and dithiothreitol assay (OPDTT)), PM with an aerodynamic diameter of less than 2.5 µm (PM2.5) mass, NO2, and PM2.5 constituents at the home addresses at birth and at all follow-up addresses were estimated by land-use regression. Repeated questionnaire reports of asthma and hay fever until age 14 years, and measurements of allergic sensitisation, lung function and fractional exhaled nitric oxide at age 12 years were linked with air pollution concentrations.ResultsAsthma incidence, prevalence of asthma symptoms and rhinitis were positively associated with OPDTT (adjusted OR (95% CI) per IQR increase in exposure 1.10 (1.01 to 1.20), 1.08 (1.02 to 1.16), 1.15 (1.05 to 1.26), respectively). These associations persisted after adjustment for most co-pollutants. Forced expiratory volume in 1s and forced vital capacity were negatively associated with OPDTT. These associations were sensitive to adjustment for NO2. Respiratory health was not significantly associated with PM2.5 mass and OPESR.ConclusionsRespiratory health was more strongly associated with OPDTT than with PM2.5 mass; OPDTT associations with lung function, but not symptoms, were sensitive to adjustment for NO2.
Background: Motorized traffic is an important source of both air pollution and community noise. While there is growing evidence for an adverse effect of ambient air pollution on reproductive health, ...little is known about the association between traffic noise and pregnancy outcomes. Methods: We evaluated the impact of residential noise exposure on small size for gestational age, preterm birth, term birth weight, and low birth weight at term in a population-based cohort study, for which we previously reported associations between air pollution and pregnancy outcomes. We also evaluated potential confounding of air pollution effects by noise and vice versa. Linked administrative health data sets were used to identify 68,238 singleton births (1999–2002) in Vancouver, British Columbia, Canada, with complete covariate data (sex, ethnicity, parity, birth month and year, income, and education) and maternal residential history. We estimated exposure to noise with a deterministic model (CadnaA) and exposure to air pollution using temporally adjusted land-use regression models and inverse distance weighting of stationary monitors for the entire pregnancy. Results: Noise exposure was negatively associated with term birth weight (mean difference = −19 95% confidence interval = −23 to −15 g per 6 dB(A)). Injoint air pollution-noise models, associations between noise and term birth weight remained largely unchanged, whereas associations decreased for all air pollutants. Conclusion: Traffic may affect birth weight through exposure to both air pollution and noise.
Green space has been hypothesized to improve cardiometabolic health of adolescents, whereas air pollution and traffic noise may negatively impact cardiometabolic health.
To examine the associations ...of green space, air pollution and traffic noise with cardiometabolic health in adolescents aged 12 and 16 years.
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.
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 <2.5 μm (PM2.5) at age 12. The association of PM2.5 with waist circumference at age 12 remained after adjustment for green space and road traffic noise (adjusted difference − 1.42 cm 95% CI −2.50, −0.35 cm per 1.16 μg/m3 increase in PM2.5).
This study does not provide evidence for beneficial effects of green space or adverse effects of air pollution and traffic noise on cardiometabolic health in adolescents.
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•Green space, air pollution and traffic noise may influence children's health.•We studied associations of these exposures with cardiometabolic health in adolescents.•We found no associations with cardiometabolic health at either age 12 or 16 years.
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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.
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.
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.
Residential exposure to green space may be associated with a better mental wellbeing in adolescents.
•Surrounding green, air pollution and traffic noise were moderately correlated.•Surrounding green was not significantly associated with non-accidental mortality.•Analyses restricted to non-movers did ...not change the findings.•Air pollution was not significantly associated with non-accidental mortality.
Most previous studies that investigated associations of surrounding green, air pollution or traffic noise with mortality focused on single exposures.
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.
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.
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.
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.
Evidence for the effects of air pollution exposure on lung function growth into adolescence is scarce. We investigated associations of air pollution exposure with lung function and lung function ...growth until age 16.We conducted both longitudinal (n=915) and cross-sectional (n=721) analyses of associations of air pollution exposure with forced expiratory volume in 1 s (FEV
) and forced vital capacity (FVC) growth from ages eight to 16 and FEV
and FVC at age 16. We estimated residential concentrations of nitrogen dioxide (NO
), "soot" and particulate matter (PM
, where x is the 50% cut-off aerodynamic diameter in µm) with diameters of <2.5 µm (PM
), <10 µm (PM
) and 2.5-10 µm (PM
) during the preschool, primary school and secondary school time windows by land use regression models. Associations with (growth in) FEV
and FVC were analysed by linear (mixed effects) regression.Higher air pollution exposure was associated with reduced FEV
growth (
adjusted difference -0.26% (95% CI -0.49 to -0.03%) per interquartile range increase in secondary school PM
) and lower FEV
(adjusted difference -2.36% (95% CI -3.76 to -0.94%)), but was not adversely associated with FVC. Associations with FEV
were stronger in boys than girls and were not modified by asthma status.Higher air pollution exposure may lead to increased airway obstruction, but not reduced lung volume in adolescence.