Objective-To determine an accurate estimate of the prevalence of congenital heart defects (CHD) using current standard diagnostic modalities.Study design-We obtained data on infants with CHD delivered during 1998-2005 identified by the Metropolitan Atlanta Congenital Defects Program, an active, population-based birth defects surveillance system. Physiologic shunts in infancy and shunts associated with prematurity were excluded. Selected infant and maternal characteristics of the cases were compared with those of the overall birth cohort.Results-From 1998-2005 there were 398 140 births, of which 3240 infants had CHD, for an overall prevalence of 81.4/10 000 births. The most common CHD were muscular ventricular septal defect, perimembranous ventricular septal defect, and secundum atrial septal defect, with prevalence of 27.5, 10.6, and 10.3/10 000 births, respectively. The prevalence of tetralogy of Fallot, the most common cyanotic CHD, was twice that of transposition of the great arteries (4.7 vs. 2.3/10 000 births). Many common CHD were associated with older maternal age and multiple-gestation pregnancy; several were found to vary by sex.Conclusion-This study, using a standardized cardiac nomenclature and classification, provides current prevalence estimates of the various CHD subtypes. These estimates can be used to assess variations in prevalence across populations, time or space. Keywordscongenital heart defects; cardiovascular malformations; surveillance; prevalence Congenital heart defects (CHD) are the leading cause of infant mortality associated with birth defects (1) and can result in chronic disability, morbidity, and increased health-care costs (2, 3). It is therefore important to derive population-based estimates of the prevalence of CHD.Correspondence: Mark Reller MD, Division of Pediatric Cardiology, CDRC-P, Oregon Health & Science University, 707 SW Gaines Rd, Portland, Oregon, 97239, rellerm@ohsu.edu, Office: (503) 494-2192, Fax: (503) 494-2824. Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. NIH Public Access NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author ManuscriptMost CHD prevalence estimates are based on data from population-based birth defects surveillance systems; a review by Hoffman and Kaplan (4) reported the inter-quartile range of prevalence estimates across 44 international studies for the common forms of CHD. For all types of CHD combined, the inter-quartile range was 60 to 105 CHD per 10 000 births (4). Routine utilization of echocardiography has significantly enhanced the ability to diagnose CHD, including minor abnorm...

Abstract. The ability of certain components of particulate matter to induce oxidative stress through the generation of reactive oxygen species (ROS) in vivo may be one mechanism accounting for observed linkages between ambient aerosols and adverse health outcomes. A variety of assays have been used to measure this so-called aerosol oxidative potential. We developed a semi-automated system to quantify oxidative potential of filter aqueous extracts utilizing the dithiothreitol (DTT) assay and report here the development of a similar semi-automated system for the ascorbic acid (AA) assay. Approximately 500 PM2.5 filter samples collected in contrasting locations in the southeastern US were analyzed for a host of aerosol species, along with AA and DTT activities. We present a detailed contrast in findings from these two assays. Water-soluble AA activity was higher in summer and fall than in winter, with highest levels near heavily trafficked highways, whereas DTT activity was higher in winter compared to summer and fall and more spatially homogeneous. AA activity was nearly exclusively correlated with water-soluble Cu (r  =  0.70–0.94 at most sites), whereas DTT activity was correlated with organic and metal species. Source apportionment models, positive matrix factorization (PMF) and a chemical mass balance method with ensemble-averaged source impact profiles (CMB-E), suggest a strong contribution from traffic emissions and secondary processes (e.g., organic aerosol oxidation or metals mobilization by secondary acids) to both AA and DTT activities in urban Atlanta. In contrast, biomass burning was a large source for DTT activity, but insignificant for AA. AA activity was not correlated with PM2.5 mass, while DTT activity co-varied strongly with mass (r  =  0.49–0.86 across sites and seasons). Various linear models were developed to estimate AA and DTT activities for the central Atlanta Jefferson Street site, based on the CMB-E sources. The models were then used to estimate daily oxidative potential at this site over the 1998–2009 period. Time series epidemiological analyses were conducted to assess daily emergency department (ED) visits data for the five-county Atlanta metropolitan area based on the estimated 10-year backcast oxidative potential. Estimated AA activity was not statistically associated with any tested health outcome, while DTT activity was associated with ED visits for both asthma or wheeze and congestive heart failure. The findings point to the importance of both organic components and transition metals from biomass burning and mobile sources to adverse health outcomes in this region.

Exposure to atmospheric fine particulate matter (PM2.5) is associated with cardiorespiratory morbidity and mortality, but the mechanisms are not well understood. We assess the hypothesis that PM2.5 induces oxidative stress in the body via catalytic generation of reactive oxygen species (ROS). A dithiothreitol (DTT) assay was used to measure the ROS-generation potential of water-soluble PM2.5. Source apportionment on ambient (Atlanta, GA) PM2.5 was performed using the chemical mass balance method with ensemble-averaged source impact profiles. Linear regression analysis was used to relate PM2.5 emission sources to ROS-generation potential and to estimate historical levels of DTT activity for use in an epidemiologic analysis for the period of 1998-2009. Light-duty gasoline vehicles (LDGV) exhibited the highest intrinsic DTT activity, followed by biomass burning (BURN) and heavy-duty diesel vehicles (HDDV) (0.11 ± 0.02, 0.069 ± 0.02, and 0.052 ± 0.01 nmol min(-1) μg(-1)source, respectively). BURN contributed the largest fraction to total DTT activity over the study period, followed by LDGV and HDDV (45, 20, and 14%, respectively). DTT activity was more strongly associated with emergency department visits for asthma/wheezing and congestive heart failure than PM2.5. This work provides further epidemiologic evidence of a biologically plausible mechanism, that of oxidative stress, for associations of adverse health outcomes with PM2.5 mass and supports continued assessment of the utility of the DTT activity assay as a measure of ROS-generating potential of particles.

Background: A growing body of evidence has associated maternal exposure to air pollution with adverse effects on fetal growth; however, the existing literature is inconsistent.Objectives: We aimed to quantify the association between maternal exposure to particulate air pollution and term birth weight and low birth weight (LBW) across 14 centers from 9 countries, and to explore the influence of site characteristics and exposure assessment methods on between-center heterogeneity in this association.Methods: Using a common analytical protocol, International Collaboration on Air Pollution and Pregnancy Outcomes (ICAPPO) centers generated effect estimates for term LBW and continuous birth weight associated with PM10 and PM2.5 (particulate matter ≤ 10 and 2.5 µm). We used meta-analysis to combine the estimates of effect across centers (~ 3 million births) and used meta-regression to evaluate the influence of center characteristics and exposure assessment methods on between-center heterogeneity in reported effect estimates.Results: In random-effects meta-analyses, term LBW was positively associated with a 10-μg/m3 increase in PM10 [odds ratio (OR) = 1.03; 95% CI: 1.01, 1.05] and PM2.5 (OR = 1.10; 95% CI: 1.03, 1.18) exposure during the entire pregnancy, adjusted for maternal socioeconomic status. A 10-μg/m3 increase in PM10 exposure was also negatively associated with term birth weight as a continuous outcome in the fully adjusted random-effects meta-analyses (–8.9 g; 95% CI: –13.2, –4.6 g). Meta-regressions revealed that centers with higher median PM2.5 levels and PM2.5:PM10 ratios, and centers that used a temporal exposure assessment (compared with spatiotemporal), tended to report stronger associations.Conclusion: Maternal exposure to particulate pollution was associated with LBW at term across study populations. We detected three site characteristics and aspects of exposure assessment methodology that appeared to contribute to the variation in associations reported by centers.

Rationale: Certain outdoor air pollutants cause asthma exacerbations in children. To advance understanding of these relationships, further characterization of the dose-response and pollutant lag effects are needed, as are investigations of pollutant species beyond the commonly measured criteria pollutants. Objectives: Investigate short-term associations between ambient air pollutant concentrations and emergency department visits for pediatric asthma. Methods: Daily counts of emergency department visits for asthma or wheeze among children aged 5 to 17 years were collected from 41 Metropolitan Atlanta hospitals during 1993-2004 (n 5 91,386 visits). Ambient concentrations of gaseous pollutants and speciated particulate matter were available from stationary monitors during this time period. Rate ratios for the warm season (May to October) and cold season (November to April) were estimated using Poisson generalized linear models in the framework of a case-crossover analysis. Measurements and Main Results: Both ozone and primary pollutants from traffic sources were associated with emergency department visits for asthma or wheeze; evidence for independent effects of ozone and primary pollutants from traffic sources were observed in multipollutant models. These associations tended to be of the highest magnitude for concentrations on the day of the emergency department visit and were present at relatively low ambient concentrations. Conclusions: Even at relatively low ambient concentrations, ozone and primary pollutants from traffic sources independently contributed to the burden of emergency department visits for pediatric asthma.Keywords: ambient particulate matter; asthma; minors; ozone A broad literature supports associations between ambient air pollutant concentrations and asthma exacerbations (1-3). Children are thought to be particularly susceptible to ambient air pollutants, because their lungs and immune systems are not fully developed, they breathe more air per unit body weight and are typically more active than adults, and their peripheral airways are anatomically smaller than adults so that inflammation results in proportionally greater airway obstruction (4-6). To help advance understanding of the relationships between ambient air pollutant concentrations and asthma exacerbations in children, further characterization of the dose-response and pollutant lag effects are needed, as are investigations of pollutant species beyond the commonly measured urban air pollutants (3, 7). Further investigation of pollutant mixtures and effect modification may also provide insights (8, 9); for example, there have been reports of stronger pollution effects during the warm season (10-15) even though pediatric asthma rates peak during the cold season (16). To lessen concerns about uncontrolled confounding, aggressive control for variables, such as meteorology and seasonal asthma trends, is required.In the present study, we analyzed data from the Study of Particles and Health in Atlanta (SOPHIA) (14,(17)(18)(19)(20)(21), one of...

To estimate PM concentrations, many parametric regression models have been developed, while nonparametric machine learning algorithms are used less often and national-scale models are rare. In this paper, we develop a random forest model incorporating aerosol optical depth (AOD) data, meteorological fields, and land use variables to estimate daily 24 h averaged ground-level PM concentrations over the conterminous United States in 2011. Random forests are an ensemble learning method that provides predictions with high accuracy and interpretability. Our results achieve an overall cross-validation (CV) R value of 0.80. Mean prediction error (MPE) and root mean squared prediction error (RMSPE) for daily predictions are 1.78 and 2.83 μg/m, respectively, indicating a good agreement between CV predictions and observations. The prediction accuracy of our model is similar to those reported in previous studies using neural networks or regression models on both national and regional scales. In addition, the incorporation of convolutional layers for land use terms and nearby PM measurements increase CV R by ∼0.02 and ∼0.06, respectively, indicating their significant contributions to prediction accuracy. A pair of different variable importance measures both indicate that the convolutional layer for nearby PM measurements and AOD values are among the most-important predictor variables for the training process.

BackgroundThere is a growing body of epidemiologic literature reporting associations between atmospheric pollutants and reproductive outcomes, particularly birth weight and gestational duration.ObjectivesThe objectives of our international workshop were to discuss the current evidence, to identify the strengths and weaknesses of published epidemiologic studies, and to suggest future directions for research.DiscussionParticipants identified promising exposure assessment tools, including exposure models with fine spatial and temporal resolution that take into account time–activity patterns. More knowledge on factors correlated with exposure to air pollution, such as other environmental pollutants with similar temporal variations, and assessment of nutritional factors possibly influencing birth outcomes would help evaluate importance of residual confounding. Participants proposed a list of points to report in future publications on this topic to facilitate research syntheses. Nested case–control studies analyzed using two-phase statistical techniques and development of cohorts with extensive information on pregnancy behaviors and biological samples are promising study designs. Issues related to the identification of critical exposure windows and potential biological mechanisms through which air pollutants may lead to intrauterine growth restriction and premature birth were reviewed.ConclusionsTo make progress, this research field needs input from toxicology, exposure assessment, and clinical research, especially to aid in the identification and exposure assessment of feto-toxic agents in ambient air, in the development of early markers of adverse reproductive outcomes, and of relevant biological pathways. In particular, additional research using animal models would help better delineate the biological mechanisms underpinning the associations reported in human studies.

Upper and lower respiratory infections are common in early childhood and may be exacerbated by air pollution. We investigated short-term changes in ambient air pollutant concentrations, including speciated particulate matter less than 2.5 μm in diameter (PM2.5), in relation to emergency department (ED) visits for respiratory infections in young children. Daily counts of ED visits for bronchitis and bronchiolitis (n = 80,399), pneumonia (n = 63,359), and upper respiratory infection (URI) (n = 359,246) among children 0-4 years of age were collected from hospitals in the Atlanta, Georgia, area for the period 1993-2010. Daily pollutant measurements were combined across monitoring stations using population weighting. In Poisson generalized linear models, 3-day moving average concentrations of ozone, nitrogen dioxide, and the organic carbon fraction of particulate matter less than 2.5 μm in diameter (PM2.5) were associated with ED visits for pneumonia and URI. Ozone associations were strongest and were observed at low (cold-season) concentrations; a 1-interquartile range increase predicted a 4% increase (95% confidence interval: 2%, 6%) in visits for URI and an 8% increase (95% confidence interval: 4%, 13%) in visits for pneumonia. Rate ratios tended to be higher in the 1- to 4-year age group compared with infants. Results suggest that primary traffic pollutants, ozone, and the organic carbon fraction of PM2.5 exacerbate upper and lower respiratory infections in early life, and that the carbon fraction of PM2.5 is a particularly harmful component of the ambient particulate matter mixture.