Studies in a number of countries have reported associations between exposure to ambient air pollutants and adverse birth outcomes, including low birth weight, preterm birth (PTB) and, less commonly, small for gestational age (SGA). Despite their growing number, the available studies have significant limitations, e.g., incomplete control of temporal trends in exposure, modest sample sizes, and a lack of information regarding individual risk factors such as smoking. No study has yet examined large numbers of susceptible individuals. We investigated the association between ambient air pollutant concentrations and term SGA and PTB outcomes among 164,905 singleton births in Detroit, Michigan occurring between 1990 and 2001. SO2, CO, NO2, O3 and PM10 exposures were used in single and multiple pollutant logistic regression models to estimate odds ratios (OR) for these outcomes, adjusted for the infant’s sex and gestational age, the mother’s race, age group, education level, smoking status and prenatal care, birth season, site of residence, and long-term exposure trends. Term SGA was associated with CO levels exceeding 0.75 ppm (OR=1.14, 95% confidence interval=1.02–1.27) and NO2 exceeding 6.8 ppb (1.11, 1.03–1.21) exposures in the first month, and with PM10 exceeding 35 μg/m3 (1.22, 1.03–1.46) and O3 (1.11, 1.02–1.20) exposure in the third trimester. PTB was associated with SO2 (1.07, 1.01–1.14) exposure in the last month, and with (hourly) O3 exceeding 92 ppb (1.08, 1.02–1.14) exposure in the first month. Exposure to several air pollutants at modest concentrations was associated with adverse birth outcomes. This study, which included a large Black population, suggests the importance of the early period of pregnancy for associations between term SGA with CO and NO2, and between O3 with PTB; and the late pregnancy period for associations between term SGA and O3 and PM10, and between SO2 with PTB. It also highlights the importance of accounting for individual risk factors such as maternal smoking, maternal race, and long-term trends in air pollutant levels and adverse birth outcomes in evaluating relationships between pollutant exposures and adverse birth outcomes.

ObjectivesPreterm births (PTBs) represent significant health risks, and several studies have found associations between high outdoor temperatures and PTB. We estimated both the total and natural direct effects (independent of particulate matter, ozone and nitrogen dioxide air pollutants) of the prior 2-day mean apparent temperature (AT) on PTB. We evaluated effect modification by maternal age, race, education, smoking status and prenatal care.Design and settingWe obtained birth records and meteorological data for the Detroit, Michigan, USA area, for the warm months (May to September), 1991 to 2001. We used a time series Poisson regression with splines of AT, wind speed, solar radiation and citywide average precipitation to estimate total effects. To accommodate multiple mediators and exposure-mediator interactions, AT inverse odds weights, predicted by meteorological and air pollutant covariates, were added in a subsequent model to estimate direct effects.ResultsAt 24.9°C relative to 18.6°C, 10.6% (95% CI: 3.8% to 17.2%) of PTBs were attributable to the total effects of AT, and 10.4% (95% CI: 2.2% to 17.5%) to direct effects. Relative excess risks of interaction indicated that the risk of PTB with increasing temperature above 18.6°C was significantly lower among black mothers and higher among mothers less than 19, older than 30, with late or no prenatal care and who smoked.ConclusionThis additional evidence of a direct association between high temperature and PTB may motivate public health interventions to reduce extreme heat exposures among pregnant women, particularly among those who may have enhanced vulnerability.

Consistent with other published qualitative reviews, there is no clear evidence of an association between occupational exposure to TiO2 and lung cancer.

Ambient air quality datasets include missing data, values below method detection limits and outliers, and the precision and accuracy of the measurements themselves are often unknown. At the same time, many analyses require continuous data sequences and assume that measurements are error-free. While a variety of data imputation and cleaning techniques are available, the evaluation of such techniques remains limited. This study evaluates the performance of these techniques for ambient air toxics measurements, a particularly challenging application, and includes the analysis of intra- and inter-laboratory precision. The analysis uses an unusually complete-dataset, consisting of daily measurements of over 70 species of carbonyls and volatile organic compounds (VOCs) collected over a one year period in Dearborn, Michigan, including 122 pairs of replicates. Analysis was restricted to compounds found above detection limits in > or =20% of the samples. Outliers were detected using the Gumbell extreme value distribution. Error models for inter- and intra-laboratory reproducibility were derived from replicate samples. Imputation variables were selected using a generalized additive model, and the performance of two techniques, multiple imputation and optimal linear estimation, was evaluated for three missingness patterns. Many species were rarely detected or had very poor reproducibility. Error models developed for seven carbonyls showed median intra- and inter-laboratory errors of 22% and 25%, respectively. Better reproducibility was seen for the 16 VOCs meeting detection and reproducibility criteria. Imputation performance depended on the compound and missingness pattern. Data missing at random could be adequately imputed, but imputations for row-wise deletions, the most common type of missingness pattern encountered, were not informative. The analysis shows that air toxics data require significant efforts to identify and mitigate errors, outliers and missing observations, and that these steps are essential and should be performed prior to using these data in receptor, exposure, health and other applications.

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