Early-life exposure to traffic-related air pollution and child anthropometry.
ABSTRACT: Background:Early-life exposure to traffic-related air pollution may decrease fetal growth and increase childhood obesity risk. Our objective was to evaluate the relationship of early-life exposure to traffic-related air pollution with birthweight in term newborns and obesity at age 7-8 years in two prospective birth cohorts in Cincinnati, OH (the Health Outcomes and Measures of the Environment (HOME) Study and Cincinnati Childhood Allergy and Air Pollution Study (CCAAPS)). Methods:We estimated elemental carbon attributable to traffic (ECAT) exposure at residential addresses during pregnancy with a validated land use regression model. We assessed birthweight among term infants using birth records or parent report (HOME Study n= 333 and CCAAPS n=590). We measured children's weight and height at 7-8 years, and calculated age- and sex-specific BMI z-scores (HOME Study n= 198 and CCAAPS n=459). Using multivariable linear regression, we estimated the difference in term birthweight and BMI z-score per interquartile range (IQR) increase in ECAT concentrations in each cohort separately and in the pooled sample. Results:In adjusted models, ECAT exposure was not associated with lower birthweight (pooled sample ?: 30g; 95% CI: -6, 66), or with higher BMI z-score (pooled sample ?: -0.04; 95% CI: -0.15, 0.08). Infant sex modified the association between ECAT and birthweight (p=0.05). Among male newborns, higher ECAT concentrations were associated with higher birthweight (?: 61g; 95% CI: 9, 113), but we observed no association among female newborns (?: -9g; 95% CI: -58, 41). Conclusions:In contrast to some prior studies, early-life traffic-related air pollution exposure was not associated with lower birthweight or increased childhood adiposity in these two cohorts.
Project description:Traffic-related air and noise pollution may increase the risk for cardiovascular disorders, especially among susceptible populations like pregnant women. The objective of this study was to evaluate the association of exposure to traffic-related air pollution and traffic noise with blood pressure in pregnant women. We extracted systolic blood pressure (SBP) and diastolic blood pressure (DBP) at ?20?weeks gestation, as well as hypertensive disorders of pregnancy from medical records in the HOME Study, a prospective pregnancy and birth cohort from Cincinnati, OH (n?=?370). We estimated exposure to elemental carbon attributable to traffic (ECAT),1 a marker of traffic-related air pollution, at women's residences at ~20?weeks gestation using a validated land use regression model and traffic noise using a publicly available transportation noise model. We used linear mixed models and modified Poisson regression adjusted for covariates to examine associations of ECAT and traffic noise with blood pressure and hypertensive disorders of pregnancy risk, respectively. In adjusted models, we found a 1.6 (95% CI?=?0.02, 3.3; p?=?0.048) mm?Hg increase in SBP associated with an interquartile range increase in ECAT concentration; the association was stronger after adjusting for traffic noise (1.9?mm?Hg, 95%?=?0.1, 3.7; p?=?0.035). ECAT concentrations were not significantly associated with DBP or hypertensive disorders of pregnancy, and traffic noise was not associated with SBP, DBP, or hypertensive disorders of pregnancy. There was no evidence of a joint effect of traffic noise and ECAT on any outcome. In this cohort, higher residential traffic-related air pollution exposure at ~20?weeks gestation was associated with higher SBP in late pregnancy. It is important for future studies of traffic-related air or noise pollution to jointly consider both exposures and neighborhood characteristics given their correlation and potential cumulative impact on cardiovascular health.
Project description:BACKGROUND:While air pollution has been associated with depression and anxiety in adults, its impact on childhood mental health is understudied. OBJECTIVE:We examined lifetime exposure to traffic-related air pollution (TRAP) and symptoms of depression and anxiety at age 12 years in the Cincinnati Childhood Allergy and Air Pollution Study cohort. METHODS:We estimated exposure to elemental carbon attributable to traffic (ECAT), a surrogate of diesel exhaust, at birth, age 12 years, and average exposure throughout childhood, using a validated land use regression model. We assessed depression and anxiety at age 12 years by parent report with the Behavior Assessment System for Children-2, and by child report with the Child Depression Inventory-2 (CDI-2) and the Spence Children's Anxiety Scale (SCAS). Associations between TRAP at birth, age 12 years, and childhood average and mental health outcomes were estimated using linear regression models adjusting for covariates including parent depression, secondhand smoke exposure, race, household income, and others. RESULTS:Exposure to ECAT was not significantly associated with parent-reported depression or anxiety. However, exposure to ECAT at birth was associated with increased child-reported depression and anxiety. Each 0.25?µg/m3 increase in ECAT was associated with a 3.5 point increase (95% CI 1.6-5.5) in CDI-2 scores and 2.3 point increase (95% CI 0.8-3.9) in SCAS total anxiety scores. We observed similar associations between average childhood ECAT exposures but not for concurrent exposures at age 12. CONCLUSIONS:TRAP exposure during early life and across childhood was significantly associated with self-reported depression and anxiety symptoms in children. The negative impact of air pollution on mental health previously reported among adults may also be present during childhood.
Project description:BACKGROUND:Exposure to traffic-related air pollution (TRAP) has been linked to childhood anxiety symptoms. Neuroimaging in patients with anxiety disorders indicate altered neurochemistry. OBJECTIVES:Evaluate the impact of TRAP on brain metabolism and its relation to childhood anxiety symptoms in the Cincinnati Childhood Allergy and Air Pollution Study (CCAAPS). METHODS:Adolescents (n?=?145) underwent magnetic resonance spectroscopy. Brain metabolites, including myo-inositol, N-acetylaspartate, creatine, choline, glutamate, glutamate plus glutamine, and glutathione were measured in the anterior cingulate cortex. Anxiety symptoms were assessed using the Spence Children's Anxiety Scale. TRAP exposure in early-life, averaged over childhood, and during the 12 months prior to imaging was estimated using a validated land use regression model. Associations between TRAP exposure, brain metabolism, and anxiety symptoms were estimated using linear regression and a bootstrapping approach for testing mediation by brain metabolite levels. RESULTS:Recent exposure to high levels of TRAP was associated with significant increases in myo-inositol (??=?0.26; 95%CI 0.01, 0.51) compared to low TRAP exposure. Recent elevated TRAP exposure (??=?4.71; 95% CI 0.95, 8.45) and increased myo-inositol levels (??=?2.98; 95% CI 0.43, 5.52) were also significantly associated with increased generalized anxiety symptoms with 12% of the total effect between TRAP and generalized anxiety symptoms being mediated by myo-inositol levels. CONCLUSIONS:This is the first study of children to utilize neuroimaging to link TRAP exposure, metabolite dysregulation in the brain, and generalized anxiety symptoms among otherwise healthy children. TRAP may elicit atypical excitatory neurotransmission and glial inflammatory responses leading to increased metabolite levels and subsequent anxiety symptoms.
Project description:Exposure assessment for elemental components of particulate matter (PM) using land use modeling is a complex problem due to the high spatial and temporal variations in pollutant concentrations at the local scale. Land use regression (LUR) models may fail to capture complex interactions and non-linear relationships between pollutant concentrations and land use variables. The increasing availability of big spatial data and machine learning methods present an opportunity for improvement in PM exposure assessment models. In this manuscript, our objective was to develop a novel land use random forest (LURF) model and compare its accuracy and precision to a LUR model for elemental components of PM in the urban city of Cincinnati, Ohio. PM smaller than 2.5 ?m (PM2.5) and eleven elemental components were measured at 24 sampling stations from the Cincinnati Childhood Allergy and Air Pollution Study (CCAAPS). Over 50 different predictors associated with transportation, physical features, community socioeconomic characteristics, greenspace, land cover, and emission point sources were used to construct LUR and LURF models. Cross validation was used to quantify and compare model performance. LURF and LUR models were created for aluminum (Al), copper (Cu), iron (Fe), potassium (K), manganese (Mn), nickel (Ni), lead (Pb), sulfur (S), silicon (Si), vanadium (V), zinc (Zn), and total PM2.5 in the CCAAPS study area. LURF utilized a more diverse and greater number of predictors than LUR and LURF models for Al, K, Mn, Pb, Si, Zn, TRAP, and PM2.5 all showed a decrease in fractional predictive error of at least 5% compared to their LUR models. LURF models for Al, Cu, Fe, K, Mn, Pb, Si, Zn, TRAP, and PM2.5 all had a cross validated fractional predictive error less than 30%. Furthermore, LUR models showed a differential exposure assessment bias and had a higher prediction error variance. Random forest and other machine learning methods may provide more accurate exposure assessment.
Project description:BACKGROUND: Air pollution may promote type 2 diabetes by increasing adipose inflammation and insulin resistance. This study examined the relation between long-term exposure to traffic-related air pollution and type 2 diabetes prevalence among 50- to 75-year-old subjects living in Westfriesland, the Netherlands. METHODS: Participants were recruited in a cross-sectional diabetes screening-study conducted between 1998 and 2000. Exposure to traffic-related air pollution was characterized at the participants' home-address. Indicators of exposure were land use regression modeled nitrogen dioxide (NO2) concentration, distance to the nearest main road, traffic flow at the nearest main road and traffic in a 250 m circular buffer. Crude and age-, gender- and neighborhood income adjusted associations were examined by logistic regression. RESULTS: 8,018 participants were included, of whom 619 (8%) subjects had type 2 diabetes. Smoothed plots of exposure versus type 2 diabetes supported some association with traffic in a 250 m buffer (the highest three quartiles compared to the lowest also showed increased prevalence, though non-significant and not increasing with increasing quartile), but not with the other exposure metrics. Modeled NO2-concentration, distance to the nearest main road and traffic flow at the nearest main road were not associated with diabetes. Exposure-response relations seemed somewhat more pronounced for women than for men (non-significant). CONCLUSIONS: We did not find consistent associations between type 2 diabetes prevalence and exposure to traffic-related air pollution, though there were some indications for a relation with traffic in a 250 m buffer.
Project description:Small proline rich protein 2B (SPRR2B) is a skin and lung epithelial protein associated with allergic inflammation in mice that has not been evaluated in human atopic diseases.To determine whether single-nucleotide polymorphisms (SNPs) in SPRR2B are associated with childhood eczema and with the phenotype of childhood eczema combined with asthma.Genotyping for SPRR2B and filaggrin (FLG) was performed in 2 independent populations: the Cincinnati Childhood Allergy & Air Pollution Study (CCAAPS; N = 762; birth-age, 4 years) and the Greater Cincinnati Pediatric Clinical Repository (GCPCR; N = 1152; ages 5-10 years). Eczema and eczema plus asthma were clinical outcomes based on parental report and clinician's diagnosis. Genetic analyses were restricted to whites and adjusted for sex in both cohorts and adjusted for environmental covariates in CCAAPS.Variants in SPRR2B were not significantly associated with eczema in either cohort after Bonferroni adjustment. Children from both cohorts with the CC genotype of the SPRR2B rs6693927 SNP were at 4 times the risk for eczema plus asthma (adjusted odds ratio, 4.1; 95% confidence interval, 1.5-10.9; P = .005 in CCAAPS; and adjusted odds ratio, 4.0; 95% confidence interval, 1.8-9.1; P < .001 in the GCPCR), however. SNPs in SPRR2B were not in strong linkage disequilibrium with the R501X and del2282 FLG mutations, and these findings were independent of FLG.An SNP in SPRR2B was predictive of asthma among white children with eczema from 2 independent populations. SPRR2B polymorphisms may serve as important predictive markers for the combined eczema plus asthma phenotype.
Project description:Environmental and host predictors of asthma control in older asthmatic patients (>65 years old) are poorly understood.To examine the effects of residential exposure to traffic exhaust and other environmental and host predictors on asthma control in older adults.One hundred four asthmatic patients 65 years of age or older from allergy and pulmonary clinics in greater Cincinnati, Ohio, completed the validated Asthma Control Questionnaire (ACQ), pulmonary function testing, and skin prick testing to 10 common aeroallergens. Patients had a physician's diagnosis of asthma, had significant reversibility in forced expiratory volume in 1 second or a positive methacholine challenge test result, and did not have chronic obstructive pulmonary disease. The mean daily residential exposure to elemental carbon attributable to traffic (ECAT) was estimated using a land-use regression model. Regression models were used to evaluate associations among independent variables, ACQ scores, and the number of asthma exacerbations, defined as acute worsening of asthma symptoms requiring prednisone use, in the past year.In the adjusted model, mean daily residential exposure to ECAT greater than 0.39 ?g/m(3) was significantly associated with poorer asthma control based on ACQ scores (adjusted ? = 2.85; 95% confidence interval [CI], 0.58-5.12; P = .02). High ECAT levels were also significantly associated with increased risk of asthma exacerbations (adjusted odds ratio, 3.24; 95% CI, 1.01-10.37; P = .05). A significant association was found between higher body mass index and worse ACQ scores (adjusted ? = 1.15; 95% CI, 0.53-1.76; P < .001). Atopic patients (skin prick test positive) had significantly better ACQ scores than nonatopic patients (adjusted ? = -0.39; 95% CI, -0.67 to -0.11; P < .01).Higher mean daily residential exposure to traffic exhaust, obesity, and nonatopic status are associated with poorer asthma control among older asthmatic patients.
Project description:BACKGROUND:Atmospheric pollution is a major public health concern. It can affect placental function and restricts fetal growth. However, scientific knowledge remains too limited to make inferences regarding causal associations between maternal exposure to air pollution and adverse effects on pregnancy. This study evaluated the association between low birth weight (LBW) and maternal exposure during pregnancy to traffic related air pollutants (TRAP) in São Paulo, Brazil. METHODS AND FINDINGS:Analysis included 5,772 cases of term-LBW (<2,500 g) and 5,814 controls matched by sex and month of birth selected from the birth registration system. Mothers' addresses were geocoded to estimate exposure according to 3 indicators: distance from home to heavy traffic roads, distance-weighted traffic density (DWTD) and levels of particulate matter ?10 µg/m3 estimated through land use regression (LUR-PM10). Final models were evaluated using multiple logistic regression adjusting for birth, maternal and pregnancy characteristics. We found decreased odds in the risk of LBW associated with DWTD and LUR-PM10 in the highest quartiles of exposure with a significant linear trend of decrease in risk. The analysis with distance from heavy traffic roads was less consistent. It was also observed that mothers with higher education and neighborhood-level income were potentially more exposed to TRAP. CONCLUSIONS:This study found an unexpected decreased risk of LBW associated with traffic related air pollution. Mothers with advantaged socioeconomic position (SEP) although residing in areas of higher vehicular traffic might not in fact be more expose to air pollution. It can also be that the protection against LBW arising from a better SEP is stronger than the effect of exposure to air pollution, and this exposure may not be sufficient to increase the risk of LBW for these mothers.
Project description:Exposure to ambient air pollution, particularly from traffic, has been associated with adverse cognitive outcomes, but the association with depressive symptoms remains unclear.We investigated the association between exposure to ambient air and traffic pollution and the presence of depressive symptoms among 732 Boston-area adults ? 65 years of age (78.1 ± 5.5 years, mean ± SD).We assessed depressive symptoms during home interviews using the Revised Center for Epidemiological Studies Depression Scale (CESD-R). We estimated residential distance to the nearest major roadway as a marker of long-term exposure to traffic pollution and assessed short-term exposure to ambient fine particulate matter (PM2.5), sulfates, black carbon (BC), ultrafine particles, and gaseous pollutants, averaged over the 2 weeks preceding each assessment. We used generalized estimating equations to estimate the odds ratio (OR) of a CESD-R score ? 16 associated with exposure, adjusting for potential confounders. In sensitivity analyses, we considered CESD-R score as a continuous outcome and mean annual residential BC as an alternate marker of long-term exposure to traffic pollution.We found no evidence of a positive association between depressive symptoms and long-term exposure to traffic pollution or short-term changes in pollutant levels. For example, we found an OR of CESD-R score ? 16 of 0.67 (95% CI: 0.46, 0.98) per interquartile range (3.4 ?g/m(3)) increase in PM2.5 over the 2 weeks preceding assessment.We found no evidence suggesting that ambient air pollution is associated with depressive symptoms among older adults living in a metropolitan area in attainment of current U.S. regulatory standards.
Project description:Exposure to traffic pollution particulate matter, predominantly diesel exhaust particles (DEPs), increases the risk of asthma and asthma exacerbation; however, the underlying mechanisms remain poorly understood.We sought to examine the effect of DEP exposure on the generation and persistence of allergen-specific memory T cells in asthmatic patients and translate these findings by determining the effect of early DEP exposure on the prevalence of allergic asthma in children.The effect of DEPs on house dust mite (HDM)-specific memory responses was determined by using an asthma model. Data from children enrolled in the Cincinnati Childhood Allergy and Air Pollution Study birth cohort were analyzed to determine the effect of DEP exposure on asthma outcomes.DEP coexposure with HDM resulted in persistent TH2/TH17 CD127(+) effector/memory cells in the lungs, spleen, and lymph nodes of adult and neonatal mice. After 7 weeks of rest, a single exposure to HDM resulted in airway hyperresponsiveness and increased TH2 cytokine levels in mice that had been previously exposed to both HDM and DEPs versus those exposed to HDM alone. On the basis of these data, we examined whether DEP exposure was similarly associated with increased asthma prevalence in children in the presence or absence of allergen exposure/sensitization in the Cincinnati Childhood Allergy and Air Pollution Study birth cohort. Early-life exposure to high DEP levels was associated with significantly increased asthma prevalence among allergic children but not among nonallergic children.These findings suggest that DEP exposure results in accumulation of allergen-specific TH2/TH17 cells in the lungs, potentiating secondary allergen recall responses and promoting the development of allergic asthma.