Dataset Information

Bayesian Spatial-temporal Model for Cardiac Congenital Anomalies and Ambient Air Pollution Risk Assessment.

ABSTRACT: We introduce a Bayesian spatial-temporal hierarchical multivariate probit regression model that identifies weeks during the first trimester of pregnancy which are impactful in terms of cardiac congenital anomaly development. The model is able to consider multiple pollutants and a multivariate cardiac anomaly grouping outcome jointly while allowing the critical windows to vary in a continuous manner across time and space. We utilize a dataset of numerical chemical model output which contains information regarding multiple species of PM2.5. Our introduction of an innovative spatial-temporal semiparametric prior distribution for the pollution risk effects allows for greater flexibility to identify critical weeks during pregnancy which are missed when more standard models are applied. The multivariate kernel stick-breaking prior is extended to include space and time simultaneously in both the locations and the masses in order to accommodate complex data settings. Simulation study results suggest that our prior distribution has the flexibility to outperform competitor models in a number of data settings. When applied to the geo-coded Texas birth data, weeks 3, 7 and 8 of the pregnancy are identified as being impactful in terms of cardiac defect development for multiple pollutants across the spatial domain.

SUBMITTER: Warren J

PROVIDER: S-EPMC3589577 | biostudies-literature | 2012 Dec

REPOSITORIES: biostudies-literature

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Bayesian Spatial-temporal Model for Cardiac Congenital Anomalies and Ambient Air Pollution Risk Assessment.

Warren Joshua J Fuentes Montserrat M Herring Amy A Langlois Peter P

Environmetrics 20121011 8

We introduce a Bayesian spatial-temporal hierarchical multivariate probit regression model that identifies weeks during the first trimester of pregnancy which are impactful in terms of cardiac congenital anomaly development. The model is able to consider multiple pollutants and a multivariate cardiac anomaly grouping outcome jointly while allowing the critical windows to vary in a continuous manner across time and space. We utilize a dataset of numerical chemical model output which contains info ...[more]

PMID: 23482298

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Project description:BackgroundA recent meta-analysis suggested evidence for an effect of exposure to ambient air pollutants on risk of certain congenital heart defects. However, few studies have investigated the effects of traffic-related air pollutants with sufficient spatial accuracy.ObjectivesWe estimated associations between congenital anomalies and exposure to traffic-related air pollution in Barcelona, Spain.MethodCases with nonchromosomal anomalies (n = 2,247) and controls (n = 2,991) were selected from the Barcelona congenital anomaly register during 1994-2006. Land use regression models from the European Study of Cohorts for Air Pollution Effects (ESCAPE), were applied to residential addresses at birth to estimate spatial exposure to nitrogen oxides and dioxide (NOx, NO2), particulate matter with diameter ? 10 ?m (PM10), 10-2.5 ?m (PMcoarse), ? 2.5 ?m (PM2.5), and PM2.5 absorbance. Spatial estimates were adjusted for temporal trends using data from routine monitoring stations for weeks 3-8 of each pregnancy. Logistic regression models were used to calculate odds ratios (ORs) for 18 congenital anomaly groups associated with an interquartile-range (IQR) increase in exposure estimates.ResultsIn spatial and spatiotemporal exposure models, we estimated statistically significant associations between an IQR increase in NO2 (12.2 ?g/m3) and coarctation of the aorta (ORspatiotemporal = 1.15; 95% CI: 1.01, 1.31) and digestive system defects (ORspatiotemporal = 1.11; 95% CI: 1.00, 1.23), and between an IQR increase in PMcoarse (3.6 ?g/m3) and abdominal wall defects (ORspatiotemporal = 1.93; 95% CI: 1.37, 2.73). Other statistically significant increased and decreased ORs were estimated based on the spatial model only or the spatiotemporal model only, but not both.ConclusionsOur results overall do not indicate an association between traffic-related air pollution and most groups of congenital anomalies. Findings for coarctation of the aorta are consistent with those of the previous meta-analysis.CitationSchembari A, Nieuwenhuijsen MJ, Salvador J, de Nazelle A, Cirach M, Dadvand P, Beelen R, Hoek G, Basagaña X, Vrijheid M. 2014. Traffic-related air pollution and congenital anomalies in Barcelona. Environ Health Perspect 122:317-323;?http://dx.doi.org/10.1289/ehp.1306802.

Dataset Information

Bayesian Spatial-temporal Model for Cardiac Congenital Anomalies and Ambient Air Pollution Risk Assessment.

Publications

Bayesian Spatial-temporal Model for Cardiac Congenital Anomalies and Ambient Air Pollution Risk Assessment.

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