High Air Pollution Exposure Research Articles

Informing about the invisible: communicating en route air pollution and noise exposure to cyclists and pedestrians using focus groups

Active mobility and public transport are considered beneficial for health and wellbeing and valuable for climate change mitigation. However, cyclists and pedestrians have high air pollution and noise exposure alongside traffic, which adversely impact health and wellbeing. The measured exposure can differ from the perceived exposure, hence, communicating en route exposure is crucial. Therefore, this study investigates how to communicate route-based exposure to cyclists and pedestrians and explores if exposure communication, e.g. via smartphones, is worthwhile for healthy and pleasant commute. It is investigated how exposure feedback influences the motivation to protect oneself and how exposure information should be designed. Three focus groups with 20 cyclists/pedestrians living in Berlin, Germany, were conducted. Based on Protection Motivation Theory and Environmental Health Literacy concept, (1) experiences and practices after recognizing exposure were discussed and (2) information needs and communication strategies were developed. The results reveal a feeling of helplessness regarding the ubiquity and uncertainty of pollution and a heightened threat appraisal. Anger, anxiety and rejection were stated. Making sense of pollution levels and protective alternatives were central. A healthy routing app, including also pleasant route factors, was desired. However, information provision was also denied. Participants argued the responsibility should not be left to the commuters and planning for exposed road users would be crucial. Information provision may not be worthwhile if planning authorities do not provide healthy alternatives. People-centered approaches for tackling air pollution and noise exposure en route should be investigated further.

A population-based cohort study of traffic congestion and infant growth using connected vehicle data.

More than 11 million Americans reside within 150 meters of a highway, an area of high air pollution exposure. Traffic congestion further contributes to environmental pollution (e.g., air and noise), but its unique importance for population health is unclear. We hypothesized that degraded environmental quality specifically from traffic congestion has harmful impacts on fetal growth. Using a population-based cohort of births in Texas (2015-2016), we leveraged connected vehicle data to calculate traffic congestion metrics around each maternal address at delivery. Among 579,122 births, we found consistent adverse associations between traffic congestion and reduced term birth weight (8.9 grams), even after accounting for sociodemographic characteristics, typical traffic volume, and diverse environmental coexposures. We estimated that up to 1.2 million pregnancies annually may be exposed to traffic congestion (27% of births in the United States), with ~256,000 in the highest congestion zones. Therefore, improvements to traffic congestion may yield positive cobenefits for infant health.

Air pollution exposure during pregnancy and childhood, APOE ε4 status and Alzheimer polygenic risk score, and brain structural morphology in preadolescents

BackgroundAir pollution exposure is associated with impaired neurodevelopment, altered structural brain morphology in children, and neurodegenerative disorders. Differential susceptibility to air pollution may be influenced by genetic features. ObjectivesTo evaluate whether the apolipoprotein E (APOE) genotype or the polygenic risk score (PRS) for Alzheimer's Disease (AD) modify the association between air pollution exposure during pregnancy and childhood and structural brain morphology in preadolescents. MethodsWe included 1186 children from the Generation R Study. Concentrations of fourteen air pollutants were calculated at participants’ home addresses during pregnancy and childhood using land-use-regression models. Structural brain images were collected at age 9–12 years to assess cortical and subcortical brain volumes. APOE status and PRS for AD were examined as genetic modifiers. Linear regression models were used to conduct single-pollutant and multi-pollutant (using the Deletion/Substitution/Addition algorithm) analyses with a two-way interaction between air pollution and each genetic modifier. ResultsHigher pregnancy coarse particulate matter (PMcoarse) and childhood polycyclic aromatic hydrocarbons exposure was differentially associated with larger cerebral white matter volume in APOE ε4 carriers compared to non-carriers (29,485 mm3 (95% CI 6,189; 52,781) and 18,663 mm3 (469; 36,856), respectively). Higher pregnancy PMcoarse exposure was differentially associated with larger cortical grey matter volume in children with higher compared to lower PRS for AD (19436 mm3 (825, 38,046)). DiscussionAPOE status and PRS for AD possibly modify the association between air pollution exposure and brain structural morphology in preadolescents. Higher air pollution exposure is associated with larger cortical volumes in APOE ε4 carriers and children with a high PRS for AD. This is in line with typical brain development, suggesting an antagonistic pleiotropic effect of these genetic features (i.e., protective effect in early-life, but neurodegenerative effect in adulthood). However, we cannot discard chance findings. Future studies should evaluate trajectorial brain development using a longitudinal design.

Ambient air pollution, bone mineral density and osteoporosis: Results from a national population-based cohort study

Evidence concerning the associations of ambient air pollution exposure with bone mineral density and osteoporosis has been mixed. We conducted cross-sectional and prospective analysis of the associations between air pollution exposure and osteoporosis using data from UK Biobank study. Estimated bone mineral density (eBMD) of each participant at baseline survey was calculated using quantitative ultrasound data, and incident osteoporosis cases were identified during the follow-up period according to health-related records. Air pollution concentrations were assessed using land use regression models. We fitted multivariable linear and logistic regression models to estimate the associations of air pollution with eBMD and osteoporosis prevalence at baseline. We applied cox proportional hazard regression models to assess the relationships between air pollution and osteoporosis incidence. Among the 341,311 participants at baseline, higher air pollution exposure was associated with lower eBMD levels and increased odds of osteoporosis prevalence. For example, an IQR increase in PM2.5, PM2.5 absorbance, PM10, NO2 and NOx levels were associated with 0.0018 (95% CI: 0.0012, 0.0023) to 0.0052 (95% CI: 0.0046, 0.0058) g/cm2 decrease in eBMD. A total of 330,988 participants without osteoporosis were followed up for an average of 12.0 years. We identified 8105 incident osteoporosis cases (456 cases with pathological fracture and 7634 cases without pathological fracture) during the follow-up. The hazard ratios for an interquartile range increase in PM2.5, PM2.5 absorbance, PM10, NO2 and NOx were 1.09 (95% CI: 1.06, 1.12), 1.04 (95% CI: 1.02, 1.07), 1.04 (95% CI: 1.01, 1.07), 1.07 (95% CI: 1.04, 1.10), and 1.06 (95% CI: 1.03, 1.09), respectively. Our study suggests that ambient air pollution might be a risk factor of decreased bone mineral density and osteoporosis incidence.

Road traffic noise and incidence of primary hypertension: a prospective analysis in UK Biobank

BACKGROUND AND AIM The quality of evidence regarding the associations between road traffic noise and hypertension is low due to the limitations of cross-sectional study design, with the role of air pollution remains to be further clarified. To evaluate associations of long-term road traffic noise and air pollution exposure with incident primary hypertension, we conducted a prospective population-based analysis in UK Biobank. METHODS Road traffic noise was estimated at baseline residential address using the Common Noise Assessment Method model. Incident primary hypertension (ICD 10: I10) was ascertained through linkage with medical records for ~250 000 participants. Cox proportional hazard models were used to estimate hazard ratios (HRs) for association between road traffic noise and incident primary hypertension, adjusting for covariates determined via directed acyclic graph. RESULTS During a median of 8.1 years follow up, 21 185 incident primary hypertension cases were ascertained. The HR for a 10 dB[A] increase in mean weighted average 24-h road traffic noise level (Lden) exposure was 1.08 [95% confidence interval (CI) 1.02, 1.14]. A dose-response relationship was found, with HRs of 1.14 (95% CI: 1.04, 1.26) for Lden > 65dB[A] vs. ≤ 55dB[A] (P trend <0.05), and HRs of 1.15 (95% CI: 1.04, 1.26) for night-time road traffic noise (Lnight)>55 dB[A] vs. ≤ 45dB[A] (P trend <0.05). The associations were all robust to adjustment for fine particulate matter (PM2.5) and nitrogen dioxide (NO2). Furthermore, the highest incident hypertension risk was seen in the group who were exposed to the highest level of both road traffic noise and air pollution. CONCLUSIONS Long-term exposure to road traffic noise was associated with increased incidence of primary hypertension, and the effect estimates were greater in those with higher air pollution exposure. KEYWORDS road traffic noise; air pollution; primary hypertension; prospective analysis

Residential greenness, air pollution, and incident ischemic heart disease: A prospective cohort study in China

Background and aim: Green living environments are associated with beneficial health outcomes, whereas higher air pollution exposure might increase the risk of chronic diseases. Moreover, few studies have explored the interaction between residential greenness and air pollution on the risk of ischemic heart disease (IHD). Therefore we aimed to estimate the associations of residential greenness and air pollution with IHD and their interaction. Methods: We performed a prospective cohort study that included 29,141 adult participants recruited from Yinzhou District, Ningbo, China. Normalized Difference Vegetation Index (NDVI) around each participant’s residence was calculated to measure residential greenness exposure. Land-use regression models were conducted to estimate long-term individual exposure to air pollutants, including nitrogen dioxide (NO2) and particulate matter with aerodynamic diameters ≤ 2.5 μm (PM2.5) and ≤10 μm (PM10). Cox proportional hazard models were used to calculate the hazard ratios (HRs) and 95% confidence intervals (95% CIs) for the association of residential greenness and air pollutants with the risk of incident IHD. Results: During 101,172.5 person-years of follow-up, 1,392 incident IHD cases were reported in the study population. Residential greenness, expressed as an interquartile range (IQR) increase in NDVI within 300m, was inversely associated with incident IHD. However, long-term air pollution exposures were associated with higher IHD incidence. Mediation analyses suggested that the beneficial effect of residential greenness on incident IHD could be partly mediated by reducing the exposure to PM2.5. Conclusion: Higher greenness was associated with decreased risk of IHD, while air pollutants were positively associated with incident IHD. Meanwhile, residential greenness may decrease the risk of IHD by reducing PM2.5 exposure. Keywords: Residential greenness; Air pollution; Ischemic heart disease; Cohort study; Effect mediation

Outdoor residential air pollution exposure and the development of brain morphology across childhood: a longitudinal study

Background and aim: Emerging evidence suggests a relationship between exposure to air pollution and brain morphology in children, but little is known about how air pollution exposure influences the development of brain structures throughout childhood. We aim to study the association of air pollution exposure during pregnancy and childhood with the development of brain morphology from age 6-16 years. Methods: We used data from 4,243 children of the Generation R study, a birth cohort in Rotterdam, the Netherlands. We estimated the concentrations of fourteen air pollutants at participant´s home addresses during pregnancy and childhood, using land use regression models. We included structural brain images at three time points, namely at age 6-10 years, 9-12 years, and 13-16 years. We assessed the association between the air pollutants and brain volumes with linear mixed models, fitting an interaction term for age and each pollutant. Models were adjusted for socioeconomic status and lifestyle characteristics. Results: Higher air pollution exposure during pregnancy was associated with a slower decrease of cortical grey matter volume starting at around age 10 and a slower increase of corpus callosum volume (e.g. -12.7 mm3 increase in corpus callosum volume [95%CI -22.0; -3.3] with each year of age per 10 μg/m3 increase in nitrogen dioxide exposure). Childhood exposure was associated with a faster decrease of putamen and caudate nucleus volume, and a slower increase of hippocampus volume. Higher exposure to air pollution during pregnancy and childhood was associated with a slower increase of thalamus volume. Air pollution exposure was not associated with cerebellum, amygdala, nucleus accumbens or globus pallidus volume. Conclusions: Air pollution exposure was associated with region-specific differences in age-related growth trajectories. Air pollution exposure during childhood might affect different brain regions than exposure during pregnancy. Keywords: air pollution, neurodevelopment, children, traffic

A population-based cohort study of traffic congestion and term birth weight using vehicle telematics data

Background and Aim: Over 11 million Americans reside within 150 m of a major highway, an area of high air pollution exposure. Traffic congestion further contributes to this problem but has not been evaluated in epidemiological studies to-date. We hypothesize that degraded air quality due to traffic congestion will have an adverse impact on infant birth weight. Methods: Using a population-based birth cohort in 2015-2016 for the State of Texas, we limited our study population to addresses within 1,000 m of a road in this database. We calculated traffic congestion around each geocoded maternal address at delivery for 100 m, 300 m, and 500 m buffer distances. We leveraged novel congestion and vehicle volume measurement data from the Texas Most Congested Roads database, which contains measurements of traffic volume, delay, and emissions from connected vehicle and device data. We used linear regressions to evaluate the association between traffic congestion and term birth weight, adjusting for sociodemographic characteristics and vehicle volume. Results: Among 580,992 births, we find consistent negative associations between traffic congestion and term birth weight. We observed a 15.8 g reduction in term birth weight (95% CI: -20.5, -11.1) among the highest quintile of delay exposure at 500 m compared to births with no delay exposure in this buffer distance. Results are similar, though attenuated, for truck-specific congestion. When we calculate excess vehicle emissions from congestion, we observe a -17.6 g reduction in term birth weight (95% CI: -21.4, -13.9) when comparing the highest and lowest quintiles. Conclusion: Our study provides important new evidence that traffic congestion is associated with adverse infant health outcomes, in addition to total traffic volumes on nearby roads. Therefore, programs to reduce traffic congestion may have positive co-benefits for infant health with respect to birth weight. Keywords: traffic-related air pollution, infant health, birth weight

Residential greenness, air pollution, and incident ischemic heart disease: A prospective cohort study in China.

Greener residential surroundings are associated with beneficial health outcomes, whereas higher air pollution exposure is linked with elevated risks of chronic diseases. To date, limited studies have explored the interaction between residential greenness and air pollution on the risk of ischemic heart disease (IHD). We performed a prospective cohort study that included 29,141 adult participants recruited from Yinzhou District, Ningbo, China. Normalized Difference Vegetation Index (NDVI) around each participant's residence was calculated to measure residential greenness exposure. Land-use regression models were conducted to estimate long-term individual exposure to air pollutants, including nitrogen dioxide (NO2) and particulate matter with aerodynamic diameters ≤ 2.5 μm (PM2.5) and ≤10 μm (PM10). Cox proportional hazard models were used to calculate the hazard ratios (HRs) and 95% confidence intervals (95% CIs) for the associations of residential greenness and air pollutants with the risk of incident IHD. During 101,172.5 person-years of follow-up, 1392 incident IHD cases were reported in the study population. Residential greenness, expressed as an interquartile range (IQR) increase in NDVI within 250 m, was inversely associated with incident IHD (HR = 0.89, 95%CI: 0.81,0.98). However, long-term exposures to air pollution were associated with higher IHD incidence (HR = 1.21, 95%CI:1.10,1.33 per IQR increase for PM2.5; HR = 1.12, 95%CI:1.03,1.22 per IQR increase for PM10; HR = 1.09, 95%CI:1.02,1.16 per IQR increase for NO2). Mediation analyses suggested that the beneficial effect of residential greenness on incident IHD could be partly mediated by reducing the exposure to PM2.5. These findings suggested that higher greenness was associated with decreased risk of IHD, while air pollutants were positively associated with incident IHD. Meanwhile, residential greenness may decrease the risk of IHD by reducing exposure to PM2.5.

Air pollution and risk of chronic obstructed pulmonary disease: The modifying effect of genetic susceptibility and lifestyle.

SummaryBackgroundThe effect of long-term exposure to air pollution on the development of chronic obstructive pulmonary disease (COPD) is still controversial, and the role of the interactions of air pollution with genetic risk and lifestyle in COPD risk is unclear.MethodsWe included 452762 participants derived from the UK Biobank. Annual concentrations of air pollutions, including particle matter (PM2.5, PM10), nitrogen oxides (NOx), and nitrogen dioxide (NO2), were assessed using land-use regression model. We applied Cox proportional hazard model to evaluate the associations between air pollution and COPD risk. In addition, we constructed a polygenic risk score and a lifestyle score, and assessed whether genetic susceptibility and lifestyle modified the effect of air pollution on the COPD risk.FindingsEach interquartile range (IQR) increase in annual concentrations of PM2.5, PM10, NOx, and NO2 was associated with 1.17 (95% CI: 1.15,1.19), 1.05 (95% CI: 1.03,1.06), 1.13 (95% CI: 1.11,1.14), and 1.19 (95% CI: 1.16,1.21) times the risk of COPD, respectively. We observed an additive interaction between PM2.5 and genetic risk (P-interact=0.095), and a negative interaction between PM2.5 and lifestyle (P-interact=0.062). The HRs for each IQR increase in PM2.5 were 1.21, (95% CI: 1.16-1.25) and 1.24, (95% CI: 1.21-1.26) in individuals with healthy and unfavourable lifestyle, respectively; and 1.16, (95% CI: 1.13-1.19) and 1.19, (95% CI: 1.16-1.22) in those with low genetic risk and high genetic risk, respectively. Participants with high air pollution exposure, high genetic risk and unfavourable lifestyle showed the highest risk of COPD.InterpretationLong-term exposure to air pollution was associated with increased risk of COPD, especially in those with high genetic risk and unfavourable lifestyle.FundingNone.

Green space, air pollution, traffic noise and mental wellbeing throughout adolescence: Findings from the PIAMA study

BackgroundGreen 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. MethodsWe 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. ResultsThe 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. ConclusionsResidential exposure to green space may be associated with a better mental wellbeing in adolescents.

Associations of genetic risk factors and air pollution with incident hypertension among participants in the UK Biobank study

The purposes of this study were to quantify the association of the combination of air pollution and genetic risk factors with hypertension and explore the interactions between air pollution and genetic risk. This study included 391,366 participants of European ancestry initially free from pre-existing hypertension in the UK Biobank. Exposure to ambient air pollutants, including particulate matter (PM2.5 PM2.5-10, and PM10), nitrogen dioxide (NO2) and nitrogen oxides (NOX), was estimated through land use regression modelling, and the associations between air pollutants and the incidence of hypertension were investigated using a Cox proportional hazards model adjusted for covariates. Furthermore, we established a polygenic risk score for hypertension and assessed the combined effect of genetic susceptibility and air pollution on incident hypertension. The results showed significant associations between the risk of hypertension and exposure to PM2.5 (hazard ratio [HR]: 1.41, 95% confidence interval [CI]: 1.29–1.53; per 10 μg/m3), PM10 (1.05, 1.00–1.09; per 10 μg/m3), and NOX (1.01, 1.01–1.02 per 10 μg/m3). Additive effects of PM2.5 and NOX exposure and genetic risk were observed. Compared to individuals with a low genetic risk and low air pollution exposure, participants with high air pollution exposure and a high genetic risk had a significantly increased risk of hypertension (PM2.5: 71% (66%–76%), PM10: 59% (55%–64%), NOX: 65% (60%–70%)). Our results indicate that long-term exposure to air pollution is associated with an increased risk of hypertension, especially in individuals with a high genetic risk.

Neighborhood environmental exposures and incidence of attention deficit/hyperactivity disorder: A population-based cohort study.

Emerging studies have associated low greenspace and high air pollution exposure with risk of child attention deficit/hyperactivity disorder (ADHD). Population-based studies are limited, however, and joint effects are rarely evaluated. We investigated associations of ADHD incidence with greenspace, air pollution, and noise in a population-based birth cohort. We assembled a cohort from administrative data of births from 2000 to 2001 (N∼37,000) in Metro Vancouver, Canada. ADHD was identified by hospital records, physician visits, and prescriptions. Cox proportional hazards models were applied to assess associations between environmental exposures and ADHD incidence adjusting for available covariates. Greenspace was estimated using vegetation percentage derived from linear spectral unmixing of Landsat imagery. Fine particulate matter (PM2.5) and nitrogen dioxide (NO2) were estimated using land use regression models; noise was estimated using a deterministic model. Exposure period was from birth until the age of three. Joint effects of greenspace and PM2.5 were analysed in two-exposure models and by categorizing values into quintiles. During seven-year follow-up, 1217 ADHD cases were diagnosed. Greenspace was associated with lower incidence of ADHD (hazard ratio, HR: 0.90 [0.81-0.99] per interquartile range increment), while PM2.5 was associated with increased incidence (HR: 1.11 [1.06-1.17] per interquartile range increment). NO2 (HR: 1.01 [0.96, 1.07]) and noise (HR: 1.00 [0.95, 1.05]) were not associated with ADHD. There was a 50% decrease in the HR for ADHD in locations with the lowest PM2.5 and highest greenspace exposure, compared to a 62% increase in HR in locations with the highest PM2.5 and lowest greenspace exposure. Effects of PM2.5 were attenuated by greenspace in two-exposure models. We found evidence suggesting environmental inequalities where children living in greener neighborhoods with low air pollution had substantially lower risk of ADHD compared to those with higher air pollution and lower greenspace exposure.

Validity of self-reported air pollution annoyance to assess long-term exposure to air pollutants in Belgium

In epidemiological studies, assessment of long term exposure to air pollution is often estimated using air pollution measurements at fixed monitoring stations, and interpolated to the residence of survey participants through Geographical Information Systems (GIS). However, obtaining georeferenced address data from national registries requires a long and cumbersome administrative procedure, since this kind of personal data is protected by privacy regulations. This paper aims to assess whether information collected in health interview surveys, including air pollution annoyance, could be used to build prediction models for assessing individual long term exposure to air pollution, removing the need for data on personal residence address.Analyses were carried out based on data from the Belgian Health Interview Survey (BHIS) 2013 linked to GIS-modelled air pollution exposure at the residence place of participants older than 15 years (n = 9347). First, univariate linear regressions were performed to assess the relationship between air pollution annoyance and modelled exposure to each air pollutant. Secondly, a multivariable linear regression was performed for each air pollutant based on a set of variables selected with elastic net cross-validation, including variables related to environmental annoyance, socio-economic and health status of participants. Finally, the performance of the models to classify individuals in three levels of exposure was assessed by means of a confusion matrix.Our results suggest a limited validity of self-reported air pollution annoyance as a direct proxy for air pollution exposure and a weak contribution of environmental annoyance variables in prediction models. Models using variables related to the socio-economic status, region, urban level and environmental annoyance allow to predict individual air pollution exposure with a percentage of error ranging from 8% to 18%. Although these models do not provide very accurate predictions in terms of absolute exposure to air pollution, they do allow to classify individuals in groups of relative exposure levels, ranking participants from low over medium to high air pollution exposure. This model represents a rapid assessment tool to identify groups within the BHIS participants undergoing the highest levels of environmental stress.

Effects of the air pollution dynamics on semen quality and sperm DNA methylation in men living in urban industrial agglomeration.

Human populations living in urban industrial regions of developed countries are exposed to high levels of environmental pollutants. The reproductive consequences of the exposure to air pollution can be monitored through semen analysis and molecular methods. In this study, we tested the possible impact of seasonal changes in the level of air pollution on the semen quality and sperm DNA methylation of 24 men living and working in the industrial agglomeration of Ostrava (Czech Republic). The study participants were healthy non-smokers. The study group was homogeneous regarding their profession, moderate alcohol consumption, no drug abuse and no additional exposure to chemical toxicants. We performed targeted methylation next generation sequencing (NGS) using Agilent SureSelect Human Methyl-Seq and Illumina NextSeq 500 platform to analyze semen samples collected repeatedly from the same men following the season of high (winter) and low (summer) air pollution exposure. We did not detect any adverse effects of the increased exposure on the semen quality; neither we found any difference in average sperm DNA methylation between the two sampling periods. Our search for differentially methylated CpG sites did not reveal any specific CpG methylation change. Our data indicate that the seasonal changes in the level of the air pollution probably do not have any substantial effect on sperm DNA methylation of men living in the highly polluted industrial agglomeration for a long period of time.

Allergic and non-allergic asthma phenotypes and exposure to air pollution

Objective Although harmful effects of air pollution on airway diseases are well-established, its effect on allergy still remains unclear. The aim of this study was to examine changes on asthma clinic and oxidant homeostasis due to air pollution between allergic asthma (AA) and non-allergic asthma (NA) phenotypes. Methods This prospective, case-control study included patients with well-controlled asthma under regular treatment (n = 57) and healthy individuals (n = 51). Of asthma patients, 22 had AA and 35 had NA phenotypes. Respiratory symptoms, pulmonary function tests, serum total antioxidant status (TAS) and total oxidant status (TOS), and thiol/disulfide levels were compared between the most (V1) and least (V2) air-polluted times. Results High air pollution exposure resulted to an increase in the frequency of respiratory symptoms and serum inflammation markers in both asthmatic and healthy individuals. Frequency of dyspnea and cough in AA and rhinitis in NA decreased from V1 to V2. Hospitalization due to asthma exacerbation, systemic corticosteroid use, and eosinophil counts were more frequent in NA group than AA in V1. An increase of blood eosinophil counts was observed in AA group at the same visit. Mean TAS and TOS levels were higher in asthma group than control group, and the decline in TAS and TOS levels from V1 to V2 was seen only in NA. All thiols decreased and SH/total SH ratios significantly increased from V1 to V2 in all groups. Conclusion This study demonstrates that air pollution affects both asthma patients and healthy individuals. Through oxidant-antioxidant and thiol pathways, however, it adversely affects respiratory system of asthma patients, at a greater extent, than healthy individuals.

Air Pollution, Genetic Factors, and the Risk of Lung Cancer: A Prospective Study in the UK Biobank.

Rationale: Both genetic and environmental factors contribute to lung cancer, but the degree to which air pollution modifies the impact of genetic susceptibility on lung cancer remains unknown. Objectives: To investigate whether air pollution and genetic factors jointly contribute to incident lung cancer. Methods: We analyzed data from 455,974 participants (53% women) without previous cancer at baseline in the UK Biobank. The concentrations of particulate matter (PM) (PM ⩽2.5 μm in aerodynamic diameter [PM2.5], coarse PM between 2.5 μm and 10 μm in aerodynamic diameter [PMcoarse], and PM ⩽10 μm in aerodynamic diameter [PM10]), nitrogen dioxide (NO2), and nitrogen oxides (NOx) were estimated by using land-use regression models, and the association between air pollutants and incident lung cancer was investigated by using a Cox proportional hazard model. Furthermore, we constructed a polygenic risk score and evaluated whether air pollutants modified the effect of genetic susceptibility on the development of lung cancer. Measurements and Main Results: The results showed significant associations between the risk of lung cancer and PM2.5 (hazard ratio [HR], 1.63; 95% confidence interval [CI], 1.33-2.01; per 5 μg/m3), PM10 (HR, 1.53; 95% CI, 1.20-1.96; per 10 μg/m3), NO2 (HR, 1.10; 95% CI, 1.05-1.15; per 10 μg/m3), and NOx (HR, 1.13; 95% CI, 1.07-1.18; per 20 μg/m3). There were additive interactions between air pollutants and the genetic risk. Compared with participants with low genetic risk and low air pollution exposure, those with high air pollution exposure and high genetic risk had the highest risk of lung cancer (PM2.5: HR, 1.71; 95% CI, 1.45-2.02; PM10: HR, 1.77; 95% CI, 1.50-2.10; NO2: HR, 1.77; 95% CI, 1.42-2.22; NOx: HR, 1.67; 95% CI, 1.43-1.95). Conclusions: Long-term exposure to air pollution may increase the risk of lung cancer, especially in those with high genetic risk.

Development and evaluation of air pollution-linked quality of life (AP-QOL) questionnaire: insight from two different cohorts.

In this study, the air pollution-related quality of life (AP-QOL) questionnaire was carried out in two geographically and economically different groups including New Delhi (Megacity) and Hamirpur, Himachal Pradesh (town), and APE scores were linked with respiratory and cardiovascular illness.The APE-Score was developed by AP-QOL questionnaire responses usingDelphi technique and further analyzed usingprincipal component analysis (PCA). For reliability of APE-Score and AP-QOL questionnaire, α-Cronbach's test and basic statistics were performed. The linear mixed-effect model and odds ratios were used to evaluate air pollution exposure and health outcomes. Overall, 720 academicians and 276 security guards were invited to participate in the questionnaire. Cronbach's α coefficients ranged from 0.70 to 0.84 indicated significant reliability in the AP-QOL questionnaire conducted in this study. Substantial variation in respiratory symptoms and their medical history were found - 76.9% ([95% confidential interval (CI)]: (- 83.8, - 66.9) (p < 0.05)) and - 28.6% (95% CI: (- 37.8, - 18.0) (p < 0.05)), respectively, with interquartile range (IQR) increase of APE score. The odds ratios (ORs) of respiratory medical history (MH Res.) showed a significant increase from 1.01 to 1.35 for low to high air pollution exposure in the academic group of IIT Delhi. Interestingly, for an academic group of NITH, the ORs for medical history of cardiovascular (MH Card.) showed an increase from 1.08 to 1.13 for low to high APE which was not the case for IIT Delhi academicians.

Feasibility of Indonesia Family Life Survey Wave 5 (IFLS5) Data for Air Pollution Exposure–Response Study in Indonesia

Background: Air pollution is an important risk factor for the disease burden; however there is limited evidence in Indonesia on the effect of air pollution on health, due to lack of exposure and health outcome data. The objective of this study is to evaluate the potential use of the IFLS data for response part of urban-scale air pollution exposure–health response studies. Methods: Relevant variables were extracted based on IFLS5 documentation review. Analysis of the spatial distribution of respondent, data completeness, prevalence of relevant health outcomes, and consistency or agreement evaluation between similar variables were performed. Power for ideal sample size was estimated. Results: There were 58,304 respondents across 23 provinces, with the highest density in Jakarta (750/district). Among chronic conditions, hypertension had the highest prevalence (15–25%) with data completeness of 79–83%. Consistency among self-reported health outcome variables was 90–99%, while that with objective measurements was 42–70%. The estimated statistical power for studying air pollution effect on hypertension (prevalence = 17%) in Jakarta was approximately 0.6 (α = 0.1). Conclusions: IFLS5 data has potential use for epidemiological study of air pollution and health outcomes such as hypertension, to be coupled with high quality urban-scale air pollution exposure estimates, particularly in Jakarta.

Associations of adverse pregnancy outcomes with high ambient air pollution exposure: Results from the Project ELEFANT

BackgroundInvestigations on the potential effects of high air pollution exposure before pregnancy on adverse pregnancy outcomes are limited, and it is unknown whether air quality standards looser than that set by World Health Organization (WHO) still can provide sufficient protection pregnant women from adverse pregnancy outcomes. ObjectivesTo evaluate the potential effects of high ambient air pollution around pregnancy on preterm birth (PTB) and low birth weight (LBW), and assess the risk of PTB and LBW associated with air pollutants with reference to different air quality standards of WHO and China. MethodsOur study leveraged 10,960 pregnant women from the Project ELEFANT. Daily average particulate matter with an aerodynamic diameter of ≤2.5 μm (PM2.5) and ≤10 μm (PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO) and ozone (O3) concentrations were collected based on Chinese Air Quality Reanalysis datasets. Hazard ratios (HR) of PTB and LBW were estimated for maternal PM2.5, PM10, NO2, SO2, CO and O3 exposures and related proportions of days with daily average air pollution concentrations exceeding air quality standards of WHO and China around pregnancy using Cox proportional hazards regression models with adjustment for potential confounders. ResultsAmbient PM2.5, PM10, NO2, SO2 and CO exposure during the before pregnancy and pregnancy period were both significantly and positively associated with increased risk of PTB, PTB subtypes and LBW. A 10% increase in proportion of days with daily average PM2.5 exceeding 25 μg/m3 over the entire pregnancy was most apparently associated with risk of PTB (HR, 12.66; 95% CI, 8.20–19.53) and LBW (HR, 17.42; 95% CI, 6.88–44.10) among all PM2.5 proportion variables based on different air quality standards. ConclusionAir quality standards of WHO are necessary to be implemented to control for risks of adverse pregnancy outcomes associated with ambient air pollution in areas with high air pollution levels.