Traffic-related Air Pollution Exposure Research Articles

Determining the Effectiveness of Interventions for the Reduction of Child Exposure to Traffic-Related Air Pollution at Schools in England

Traffic-related air pollution (TRAP) is a significant risk to human health and is particularly damaging to children as a vulnerable group. TRAP exposure near schools and on the school commute is linked to a growing number of adverse health effects, including respiratory and cardiovascular disease and can lead to (and exacerbate existing) respiratory conditions. The current study aimed to assess the effectiveness of interventions for the reduction of potential child exposure to TRAP at the school gates and on the school commute. This study employed dispersion modelling to assess the effects of interventions for reducing TRAP concentrations in the vicinity of five schools in England. The results revealed that all interventions led to reductions in nitrogen dioxide (NO2) concentrations. Improved travel routes were the most effective intervention for reducing concentrations along travel routes, while the introduction of low-emission zones (LEZs) proved most effective in reducing NO2 concentrations at schools, with greater effectiveness observed at shorter distances. Active travel also demonstrated effectiveness, particularly in areas with heavy traffic. When considering all receptors, LEZ implementation, active travel, and rideshare interventions exhibited effectiveness, with greater distance providing greater reductions in NO2 concentrations. Anti-idling was found to be more effective in sparsely populated areas. Combined with improved travel routes, anti-idling showed the greatest percentage difference in concentrations, followed by active travel, and rideshare.

Development of a metabolomic risk score for exposure to traffic-related air pollution: A multi-cohort study

To synthesize vast amounts of high-throughput biological information, omics-fields like epigenetics have applied risk scores to develop biomarkers for environmental exposures. Extending the risk score analytic tool to the metabolomic data would be highly beneficial. This research aimed to develop and evaluate metabolomic risk score (metRS) approaches reflecting the biological response to traffic-related air pollution (TRAP) exposure (fine particulate matter, black carbon, and nitrogen dioxide). A simulation study compared three metRS methodologies: elastic net regression, which uses penalized regression to select metabolites, and two variations of thresholding, where a p-value cutoff is used to select metabolites. The methods performance was compared to assess 1) ability to correctly select metabolites associated with daily TRAP and 2) ability of the risk score to predict daily TRAP exposure. Power calculations and false discovery rates (FDR) were calculated for each approach. This metRS was applied to two real cohorts, the Center for Health Discovery and Wellbeing (CHDWB, n = 180) and Environment and Reproductive Health (EARTH, n = 200). In simulations, elastic net regression consistently presented inflated FDR for both high and low effect sizes and across all three sample sizes (n = 200; 500; 1000). Power to detect correct metabolites exceeded 0.8 for all three sample sizes in all three methods. In the real data application assessing associations of metabolomics risk scores and TRAP, associations were largely null. While we did not identify strong associations between the risk scores and TRAP in the real data application, metabolites selected by the risk score approaches were enriched in pathways that are well-known for their association with TRAP. These results demonstrate that certain methodologies to construct metabolomics risk scores are statistically robust and valid; however, standardized metabolic profiling and large sample sizes are required.

Exposure to air pollution and cardiovascular risk in young children - a pilot project.

To examine relationships between traffic-related air pollution (TRAP) and markers of pre-clinical cardiovascular risk in young children. We studied a cohort of healthy children ages 2-5 recruited from pediatric primary care sites (n = 122). We obtained child weight, height, blood pressure and hair nicotine levels. A blood sample was obtained for biomarkers of systemic inflammation, oxidation, and prevalence of circulating endothelial progenitor cells. This manuscript represents a secondary analysis. TRAP exposure (particulate levels, nitrogen dioxide, nitrogen oxides, and proximity to major roadways) was assessed using national air pollution data based on child's census tract of residence. TRAP exposure had significant positive associations with prevalence of two of the three EPC subtypes (CD34 + /CD133 + /CD45- and CD133 + /CD45-) in unadjusted correlations. In a linear regression model, adjusting for sex, age, race, ethnicity, body mass index, parental education, child insurance, and secondhand smoke exposure, one EPC subtype (CD133 + /CD45-) had a positive significant correlation to every TRAP measure. No significant relationships between air pollution and measures of inflammation and oxidation was found. Our findings of the upregulation of EPCs may signal a response to early vascular damage during early childhood due to air pollution exposure. Traffic-related air pollution (TRAP) - known cardiovascular risk factor during adulthood Current pilot study in very young children shows upregulation of cells which protect the endothelial lining of blood vessels (endothelial progenitor cells, EPCs) Upregulation of EPCs aligns with other cardiovascular risks during childhood (obesity, prematurity, type 1 diabetes) Demonstrated with TRAP exposure lower than EPA threshold Response to air pollution may be protective of cardiovascular damage during early childhood.

Associations of air pollution exposures in preconception and pregnancy with birth outcomes and infant neurocognitive development: analysis of the Complex Lipids in Mothers and Babies (CLIMB) prospective cohort in Chongqing, China

ObjectivesTo investigate the associations of traffic-related air pollution exposures in early pregnancy with birth outcomes and infant neurocognitive development.DesignCohort study.SettingEligible women attended six visits in the maternity clinics of two...

Association of ischemic placental disease in a Southern California Birth Cohort and PM2.5 chemical species and oxidative potential markers

Road traffic is a significant source of particulate matter pollution, whose exposure is a significant risk factor in pregnancy-related health outcomes. The exact mechanisms behind the relationship between traffic-related air pollution (TRAP) exposure and adverse pregnancy outcomes remain unclear. We aim to assess the relationship between exposure to brake and tire wear-associated metals and oxidative potential and ischemic placental disease (IPD). Data were assembled from a final population of 178 women who sought specialized prenatal care at UCLA between 2016 and 2019 in Los Angeles, CA. Modeled first trimester exposures to chemical constituents and oxidative stress potential of PM2.5, black carbon, and PM2.5 mass concentration. Speciated measurements included tracers of brake wear (barium), tire wear (zinc), and oxidative potential markers based on metal concentrations (KM-SUB-ELF ROS) or laboratory assays (DTT loss, OH radical formation). Exposures were modeled by integrating data from filter samples, a low-cost PM2.5 sensor network, and land-use data. We used logistic regression to estimate the associations between air pollution exposures and IPD, adjusting for covariates assessed through medical records and interviews. Scaled to the interquartile range, odds ratios (95% CI) were as follows: barium OR: 1.7 (1.1, 2.7), zinc OR: 1.4 (.86, 2.4), and oxidative potential markers, both modeled as well as measured through DTT loss and OH formation assays (ORs ranging from 1.1-2.0). Point estimates of effect sizes for PM2.5 and black carbon were lower than most measurements (ORs: 1.3-1.4). mass and black carbon. Our findings suggest two key points: (i) metals associated with brake and tire wear, currently unregulated, may play a role in the relationship between TRAP and adverse pregnancy outcomes, and (ii) reducing tailpipe emissions may not be sufficient to protect pregnant women from TRAP.

Multiomic Signatures of Traffic-Related Air Pollution in London Reveal Potential Short-Term Perturbations in Gut Microbiome-Related Pathways.

This randomized crossover study investigated the metabolic and mRNA alterations associated with exposure to high and low traffic-related air pollution (TRAP) in 50 participants who were either healthy or were diagnosed with chronic pulmonary obstructive disease (COPD) or ischemic heart disease (IHD). For the first time, this study combined transcriptomics and serum metabolomics measured in the same participants over multiple time points (2 h before, and 2 and 24 h after exposure) and over two contrasted exposure regimes to identify potential multiomic modifications linked to TRAP exposure. With a multivariate normal model, we identified 78 metabolic features and 53 mRNA features associated with at least one TRAP exposure. Nitrogen dioxide (NO2) emerged as the dominant pollutant, with 67 unique associated metabolomic features. Pathway analysis and annotation of metabolic features consistently indicated perturbations in the tryptophan metabolism associated with NO2 exposure, particularly in the gut-microbiome-associated indole pathway. Conditional multiomics networks revealed complex and intricate mechanisms associated with TRAP exposure, with some effects persisting 24 h after exposure. Our findings indicate that exposure to TRAP can alter important physiological mechanisms even after a short-term exposure of a 2 h walk. We describe for the first time a potential link between NO2 exposure and perturbation of the microbiome-related pathways.

EAACI guidelines on environmental science for allergy and asthma: The impact of short-term exposure to outdoor air pollutants on asthma-related outcomes and recommendations for mitigation measures.

The EAACI Guidelines on the impact of short-term exposure to outdoor pollutants on asthma-related outcomes provide recommendations for prevention, patient care and mitigation in a framework supporting rational decisions for healthcare professionals and patients to individualize and improve asthma management and for policymakers and regulators as an evidence-informed reference to help setting legally binding standards and goals for outdoor air quality at international, national and local levels. The Guideline was developed using the GRADE approach and evaluated outdoor pollutants referenced in the current Air Quality Guideline of the World Health Organization as single or mixed pollutants and outdoor pesticides. Short-term exposure to all pollutants evaluated increases the risk of asthma-related adverse outcomes, especially hospital admissions and emergency department visits (moderate certainty of evidence at specific lag days). There is limited evidence for the impact of traffic-related air pollution and outdoor pesticides exposure as well as for the interventions to reduce emissions. Due to the quality of evidence, conditional recommendations were formulated for all pollutants and for the interventions reducing outdoor air pollution. Asthma management counselled by the current EAACI guidelines can improve asthma-related outcomes but global measures for clean air are needed to achieve significant impact.

Nitrogen dioxide exposure, attentional function, and working memory in children from 4 to 8 years: Periods of susceptibility from pregnancy to childhood

BackgroundAir pollution exposure during pregnancy and childhood has been linked to executive function impairment in children, however, very few studies have assessed these two exposure periods jointly to identify susceptible periods of exposure. We sought to identify potential periods of susceptibility of nitrogen dioxide (NO2) exposure from conception to childhood on attentional function and working memory in school-aged children. MethodsWithin the Spanish INMA Project, we estimated residential daily NO2 exposures during pregnancy and up to 6 years of childhood using land use regression models (n = 1,703). We assessed attentional function at 4–6 years and 6–8 years, using the Conners Kiddie Continuous Performance Test and the Attention Network Test, respectively, and working memory at 6–8 years, using the N-back task. We used distributed lag non-linear models to assess the periods of susceptibility of each outcome, adjusting for potential confounders and correcting for multiple testing. We also stratified all models by sex. ResultsHigher exposure to NO2 between 1.3 and 1.6 years of age was associated with higher hit reaction time standard error (HRT-SE) (0.14 ms (95 % CI 0.05; 0.22) per 10 μg/m3 increase in NO2) and between 1.5 and 2.2 years of age with more omission errors (1.02 (95 % CI 1.01; 1.03) of the attentional function test at 4–6 years. Higher exposure to NO2 between 0.3 and 2.2 years was associated with higher HRT-SE (10.61 ms (95 % CI 3.46; 17.75) at 6–8 years only in boys. We found no associations between exposure to NO2 and working memory at 6–8 years. ConclusionOur findings suggest that NO2 exposure during the first two years of life is associated with poorer attentional function in children from 4 to 8 years of age, especially in boys. These findings highlight the importance of exploring long-term effects of traffic-related air pollution exposure in older age groups.

Traffic-related air pollution and dementia incidence in the Adult Changes in Thought Study

BackgroundWhile epidemiologic evidence links higher levels of exposure to fine particulate matter (PM2.5) to decreased cognitive function, fewer studies have investigated links with traffic-related air pollution (TRAP), and none have examined ultrafine particles (UFP, ≤100 nm) and late-life dementia incidence. ObjectiveTo evaluate associations between TRAP exposures (UFP, black carbon [BC], and nitrogen dioxide [NO2]) and late-life dementia incidence. MethodsWe ascertained dementia incidence in the Seattle-based Adult Changes in Thought (ACT) prospective cohort study (beginning in 1994) and assessed ten-year average TRAP exposures for each participant based on prediction models derived from an extensive mobile monitoring campaign. We applied Cox proportional hazards models to investigate TRAP exposure and dementia incidence using age as the time axis and further adjusting for sex, self-reported race, calendar year, education, socioeconomic status, PM2.5, and APOE genotype. We ran sensitivity analyses where we did not adjust for PM2.5 and other sensitivity and secondary analyses where we adjusted for multiple pollutants, applied alternative exposure models (including total and size-specific UFP), modified the adjustment covariates, used calendar year as the time axis, assessed different exposure periods, dementia subtypes, and others. ResultsWe identified 1,041 incident all-cause dementia cases in 4,283 participants over 37,102 person-years of follow-up. We did not find evidence of a greater hazard of late-life dementia incidence with elevated levels of long-term TRAP exposures. The estimated hazard ratio of all-cause dementia was 0.98 (95 % CI: 0.92–1.05) for every 2000 pt/cm3 increment in UFP, 0.95 (0.89–1.01) for every 100 ng/m3 increment in BC, and 0.96 (0.91–1.02) for every 2 ppb increment in NO2. These findings were consistent across sensitivity and secondary analyses. DiscussionWe did not find evidence of a greater hazard of late-life dementia risk with elevated long-term TRAP exposures in this population-based prospective cohort study.

Methylomic, Proteomic, and Metabolomic Correlates of Traffic-Related Air Pollution in the Context of Cardiorespiratory Health: A Systematic Review, Pathway Analysis, and Network Analysis.

A growing body of literature has attempted to characterize how traffic-related air pollution (TRAP) affects molecular and subclinical biological processes in ways that could lead to cardiorespiratory disease. To provide a streamlined synthesis of what is known about the multiple mechanisms through which TRAP could lead to cardiorespiratory pathology, we conducted a systematic review of the epidemiological literature relating TRAP exposure to methylomic, proteomic, and metabolomic biomarkers in adult populations. Using the 139 papers that met our inclusion criteria, we identified the omic biomarkers significantly associated with short- or long-term TRAP and used these biomarkers to conduct pathway and network analyses. We considered the evidence for TRAP-related associations with biological pathways involving lipid metabolism, cellular energy production, amino acid metabolism, inflammation and immunity, coagulation, endothelial function, and oxidative stress. Our analysis suggests that an integrated multi-omics approach may provide critical new insights into the ways TRAP could lead to adverse clinical outcomes. We advocate for efforts to build a more unified approach for characterizing the dynamic and complex biological processes linking TRAP exposure and subclinical and clinical disease and highlight contemporary challenges and opportunities associated with such efforts.

Concentration-dependent alterations in the human plasma proteome following controlled exposure to diesel exhaust

Traffic-related air pollution (TRAP) exposure is associated with systemic health effects, which can be studied using blood-based markers. Although we have previously shown that high TRAP concentrations alter the plasma proteome, the concentration-response relationship between blood proteins and TRAP is unexplored in controlled human exposure studies. We aimed to identify concentration-dependent plasma markers of diesel exhaust (DE), a model of TRAP. Fifteen healthy non-smokers were enrolled into a double-blinded, crossover study where they were exposed to filtered air (FA) and DE at 20, 50 and 150 μg/m3 PM2.5 for 4h, separated by ≥ 4-week washouts. We collected blood at 24h post-exposure and used label-free mass spectrometry to quantify proteins in plasma. Proteins exhibiting a concentration-response, as determined by linear mixed effects models (LMEMs), were assessed for pathway enrichment using WebGestalt. Top candidates, identified by sparse partial least squares discriminant analysis and LMEMs, were confirmed using enzyme-linked immunoassays. Thereafter, we assessed correlations between proteins that showed a DE concentration-response and acute inflammatory endpoints, forced expiratory volume in 1 s (FEV1) and methacholine provocation concentration causing a 20% drop in FEV1 (PC20). DE exposure was associated with concentration-dependent alterations in 45 proteins, which were enriched in complement pathways. Of the 9 proteins selected for confirmatory immunoassays, based on complementary bioinformatic approaches to narrow targets and availability of high-quality assays, complement factor I (CFI) exhibited a significant concentration-dependent decrease (−0.02 μg/mL per μg/m3 of PM2.5, p = 0.04). Comparing to FA at discrete concentrations, CFI trended downward at 50 (−2.14 ± 1.18, p = 0.08) and significantly decreased at 150 μg/m3 PM2.5 (−2.93 ± 1.18, p = 0.02). CFI levels were correlated with FEV1, PC20 and nasal interleukin (IL)-6 and IL-1β. This study details concentration-dependent alterations in the plasma proteome following DE exposure at concentrations relevant to occupational and community settings. CFI shows a robust concentration-response and association with established measures of airway function and inflammation.

2020 Near-roadway population census, traffic exposure and equity in the United States

We present an updated analysis of the size and demographic composition of the United States (U.S.) population living near high traffic volume roadways where the risk of negative health outcomes from traffic-related air pollution exposure is elevated using traffic data from 2018 and 2020 census data. We also evaluate disparities in traffic exposure by race, ethnicity, and income using refined equity analysis methods and break down our analysis by light-, medium-, and heavy-duty vehicle traffic. We find that 24 % of the U.S. population now lives near high-volume roadways, a larger share than 10 years ago. We also find statistically significant associations between higher levels of traffic exposure and greater proportions of people of color and lower household incomes in 89 % of U.S. counties. The increasing size of the near-roadway population, persistent and widespread inequities, and rapidly growing truck traffic raise significant public health and environmental justice concerns.

Climate change as a threat multiplier to environmental reproductive justice

Legacies of racial capitalism and colonialism drive present day racial disparities in perinatal health outcomes. Climate change amplifies existing social inequalities associated with environmental exposures and reproductive health, of which BIPOC (Black, Indigenous, and people of color) communities bear a disproportionate burden. Through case studies, this article summarizes three examples of climate justice issues with reproductive healthcare outcomes: traffic related air pollution exposure, chemical exposures in personal care products and plastics, and natural disaster frequency. We advocate for incorporation of climate justice and environmental health impact into medical school curriculum, increased prenatal screening for environmental toxins, and physician engagement with local environmental issues.

Improving traffic-related air pollution estimates by modelling minor road traffic volumes

Accurately estimating annual average daily traffic (AADT) on minor roads is essential for assessing traffic-related air pollution (TRAP) exposure, particularly in areas where most people live. Our study assessed the direct and indirect external validity of three methods used to estimate AADT on minor roads in Melbourne, Australia.We estimated the minor road AADT using a fixed-value approach (assuming 600 vehicles/day) and linear and negative binomial (NB) models. The models were generated using road type, road importance index, AADT and distance of the nearest major road, population density, workplace density, and weighted road density. External measurements of traffic counts, as well as black carbon (BC) and ultrafine particles (UFP), were conducted at 201 sites for direct and indirect validation, respectively. Statistical tests included Akaike information criterion (AIC) to compare models' performance, the concordance correlation coefficient (CCC) for direct validation, and Spearman's correlation coefficient for indirect validation. Results show that 88.5% of the roads in Melbourne are minor, yet only 18.9% have AADT. The performance assessment of minor road models indicated comparable performance for both models (AIC of 1,023,686 vs. 1,058,502). In the direct validation with external traffic measurements, there was no difference between the three methods for overall minor roads. However, for minor roads within residential areas, CCC (95% confidence interval [CI]) values were −0.001 (−0.17; 0.18), 0.47 (0.32; 0.60), and 0.29 (0.18; 0.39) for the fixed-value approach, the linear model, and the NB model, respectively. In the indirect validation, we found differences only on UFP where the Spearman's correlation (95% CI) for both models and fixed-value approach were 0.50 (0.37; 0.62) and 0.34 (0.19; 0.48), respectively. In conclusion, our linear model outperformed the fixed-value approach when compared against traffic and TRAP measurements. The methodology followed in this study is relevant to locations with incomplete minor road AADT data.

Changes in Socioeconomic Disparities for Traffic-Related Air Pollution Exposure During Pregnancy Over a 20-Year Period in Texas

Air pollution presents clear environmental justice issues. However, few studies have specifically examined traffic-related air pollution (TRAP), a source driven by historically racist infrastructure policies, among pregnant individuals, a population susceptible to air pollution effects. How these disparities have changed over time is also unclear but has important policy implications. To examine changes in TRAP exposure by sociodemographic characteristics among recorded pregnancies over a 20-year period. This population-based birth cohort study used descriptive analysis among pregnant individuals in Texas from 1996 to 2016. All pregnant individuals with valid residential address, socioeconomic, and demographic data were included. Individual-level race and ethnicity, education, and maternal birthplace data were extracted from birth certificates and neighborhood-level household income and historical neighborhood disinvestment (ie, redlining) data were assessed via residential addresses. Data analysis occurred between June 2022 and June 2023. The main outcome, TRAP exposure at residential addresses, was assessed via traffic levels, represented by total and truck-specific vehicle miles traveled (VMT) within 500 m; nitrogen dioxide (no2) concentrations from a spatial-temporal land use regression model (ie, vehicle tailpipe emissions); and National Air Toxic Agency cancer risk index from on-road vehicle emissions. TRAP exposure differences were assessed by sociodemographic indicators over the 1996 to 2016 period. Among 7 043 598 pregnant people (mean [SD] maternal age, 26.8 [6.1] years) in Texas from 1996 to 2016, 48% identified as Hispanic or Latinx, 4% identified as non-Hispanic Asian or Pacific Islander, 12% identified as non-Hispanic Black, and 36% identified as non-Hispanic White. There were differences in TRAP for pregnant people by all sociodemographic variables examined. The absolute level of these disparities decreased from 1996 to 2016, but the relative level of these disparities increased: for example, in 1996, non-Hispanic Black pregnant individuals were exposed to a mean (SD) 15.3 (4.1) ppb of no2 vs 13.5 (4.4) ppb of no2 for non-Hispanic White pregnant individuals, compared with 2016 levels of 6.7 (2.4) ppb no2 for Black pregnant individuals and 5.2 (2.4) ppb of no2 for White pregnant individuals. Large absolute and relative differences in traffic levels were observed for all sociodemographic characteristics, increasing over time. For example, non-Hispanic Black pregnant individuals were exposed to a mean (SD) of 22 836 (32 844) VMT within 500 m of their homes, compared with 12 478 (22 870) VMT within 500 m of the homes of non-Hispanic White pregnant individuals in 2016, a difference of 83%. This birth cohort study found that while levels of air pollution disparities decreased in absolute terms over the 20 years of the study, relative disparities persisted and large differences in traffic levels remained, requiring renewed policy attention.

A study on air pollution exposure of “first and last mile” urban commuters under space-behavior dual verification based on big data, land-use regression model and space syntax

Urban traffic-related air pollution (TRAP) exposure is a serious problem during daily commutes. Previous studies assess the TRAP exposure of commuters mainly based on fastest and lowest-dose routes. In addition, the first and last parts of the commutes (“first and last mile”) are often overlooked, wherein the commuters tend to choose active transport (walking, jogging and cycling) and are highly exposed to air pollution. This study uses a space syntax model to simulate the most likely actual commuting routes (behavior-based routes) of “first and last mile” in Changsha, China, and combine it with a land-use regression (LUR) model to assess the TRAP exposure. Furthermore, the air pollution exposure doses of commuters across the behavior-based routes are compared with those across the fastest and lowest-dose routes. The results indicate that only 5.9%–13% of lowest-dose routes do not overlap the fastest routes, and the differences in both average fine particulate matter (PM2.5) and nitrogen dioxide (NO2) exposure are below 1%. However, up to 53.1%–68% of the behavior-based routes do not overlap with the fastest and lowest-dose routes, and the average accumulated exposure of the behavior-based routes exceeds those of the other routes by 7.8%–12.9%. These findings suggest an underestimation of TRAP exposure and the potential benefits of choosing cleaner routes. The results also indicate that commuters living in sub-central areas are linked with relatively larger commuting time costs and higher accumulated exposure doses. This highlights the need to focus on the environmental issues suffered by the commuters in these areas. In addition, our study suggests that behavioral science methods, such as space syntax, can shed new light on air pollution exposure research and develop targeted interventions to address related environmental problems.

Long-Term Exposure to Traffic-Related Air Pollution and Diabetes: A Systematic Review and Meta-Analysis.

Objectives: We report results of a systematic review on the health effects of long-term traffic-related air pollution (TRAP) and diabetes in the adult population. Methods: An expert Panel appointed by the Health Effects Institute conducted this systematic review. We searched the PubMed and LUDOK databases for epidemiological studies from 1980 to July 2019. TRAP was defined based on a comprehensive protocol. Random-effects meta-analyses were performed. Confidence assessments were based on a modified Office for Health Assessment and Translation (OHAT) approach, complemented with a broader narrative synthesis. We extended our interpretation to include evidence published up to May 2022. Results: We considered 21 studies on diabetes. All meta-analytic estimates indicated higher diabetes risks with higher exposure. Exposure to NO2 was associated with higher diabetes prevalence (RR 1.09; 95% CI: 1.02; 1.17 per 10μg/m3), but less pronounced for diabetes incidence (RR 1.04; 95% CI: 0.96; 1.13 per 10μg/m3). The overall confidence in the evidence was rated moderate, strengthened by the addition of 5 recently published studies. Conclusion: There was moderate evidence for an association of long-term TRAP exposure with diabetes.

Traffic-Related Air Pollution (TRAP) in relation to respiratory symptoms and lung function of school-aged children in Kuala Lumpur

ABSTRACT Traffic-Related Air Pollution (TRAP) exposure has been connected to significant health impacts among children. A cross-sectional comparative study was conducted among school children in Malaysia to determine the relationship between their exposure to TRAP and respiratory health effects. Air monitoring was conducted in schools and residences, while the children’s routines were investigated using a diary of daily activities. Respondents’ background and respiratory symptoms were obtained from a validated questionnaire, while a spirometry test was performed to determine their lung function status. The distances between schools and residences from the had contributed to the higher concentration of air pollutants in this study, which had associations with the children’s respiratory symptoms and lung function status. PM2.5 was the main predictor influencing the respondents’ respiratory symptoms and lung function abnormalities. In conclusion, exposure of school children to a high TRAP level might increase their risk of getting respiratory symptoms and lung function reduction.

Association between traffic-related air pollution exposure and fertility-assisted births

Previous studies have suggested that traffic-related air pollution is associated with adverse fertility outcomes, such as reduced fecundability and subfertility. The purpose of this research is to investigate if PM2.5 exposure prior to conception or traffic-related exposures (traffic density and distance to nearest major roadway) at birth address is associated with fertility-assisted births. We obtained all live and still births from the Massachusetts state birth registry with an estimated conception date between January 2002 through December 2008. All births requiring fertility drugs or assisted reproductive technology were identified as cases. We randomly selected 2000 infants conceived each year to serve as a common control group. PM2.5 exposure was assessed using 4 km spatial satellite remote sensing, meteorological and land use spatiotemporal models at geocoded birth addresses for the year prior to conception. The mean PM2.5 level was 9.81 µg m−3 (standard deviation = 1.70 µg m−3), with a maximum of 14.27 µg m−3. We calculated crude and adjusted fertility treatment odds ratios (ORs) and 95% confidence intervals (CI) per interquartile range of 1.72 µg m−3 increase in PM2.5 exposure. Our final analyses included 10 748 fertility-assisted births and 12 225 controls. After adjusting for parental age, marital status, race, maternal education, insurance status, parity, and year of birth, average PM2.5 exposure during the year prior to conception was weakly associated with fertility treatment (OR: 1.01; 95% CI: 0.97, 1.05). Fertility-assisted births were inversely associated with traffic density (highest quartile compared to lowest quartile, OR: 0.92; 95% CI: 0.83, 1.02) and positively associated with distance from major roadway (OR per 100 m: 1.01; 95% CI: 1.00, 1.02) in adjusted analyses. We did not find strong evidence to support an adverse relationship between traffic-related air pollution exposure and fertility-assisted births.

Residential green space improves cognitive performances in primary schoolchildren independent of traffic-related air pollution exposure

BackgroundCognitive performances of schoolchildren have been adversely associated with both recent and chronic exposure to ambient air pollution at the residence. In addition, growing evidence indicates that exposure to green space is associated with a wide range of health benefits. Therefore, we aimed to investigate if surrounding green space at the residence improves cognitive performance of primary schoolchildren while taking into account air pollution exposure.MethodsCognitive performance tests were administered repeatedly to a total of 307 primary schoolchildren aged 9-12y, living in Flanders, Belgium (2012–2014). These tests covered three cognitive domains: attention (Stroop and Continuous Performance Tests), short-term memory (Digit Span Forward and Backward Tests), and visual information processing speed (Digit-Symbol and Pattern Comparison Tests). Green space exposure was estimated within several radii around their current residence (50 m to 2000 m), using a aerial photo-derived high-resolution (1 m2) land cover map. Furthermore, air pollution exposure to PM2.5 and NO2 during the year before examination was modelled for the child’s residence using a spatial–temporal interpolation method.ResultsAn improvement of the children’s attention was found with more residential green space exposure independent of traffic-related air pollution. For an interquartile range increment (21%) of green space within 100 m of the residence, a significantly lower mean reaction time was observed independent of NO2 for both the sustained-selective (-9.74 ms, 95% CI: -16.6 to -2.9 ms, p = 0.006) and the selective attention outcomes (-65.90 ms, 95% CI: -117.0 to -14.8 ms, p = 0.01). Moreover, green space exposure within a large radius (2000 m) around the residence was significantly associated with a better performance in short-term memory (Digit-Span Forward Test) and a higher visual information processing speed (Pattern Comparison Test), taking into account traffic-related exposure. However, all associations were attenuated after taking into account long-term residential PM2.5 exposure.ConclusionsOur panel study showed that exposure to residential surrounding green space was associated with better cognitive performances at 9–12 years of age, taking into account traffic-related air pollution exposure. These findings support the necessity to build attractive green spaces in the residential environment to promote healthy cognitive development in children.