Traffic-Related Air Pollution and Ultrasound Parameters of Fetal Growth in Eastern Massachusetts

Previous studies have examined the association between prenatal nitrogen dioxide (NO2)-a traffic emissions tracer-and fetal growth based on ultrasound measures. Yet, most have used exposure assessment methods with low temporal resolution, which limits the identification of critical exposure windows given that pregnancy is relatively short. Here, we used NO2 data from an ensemble model linked to residential addresses at birth to fit distributed lag models that estimated the association between NO2 exposure (resolved weekly) and ultrasound biometric parameters in a Massachusetts-based cohort of 9,446 singleton births from 2011-2016. Ultrasound biometric parameters examined included biparietal diameter (BPD), head circumference, femur length, and abdominal circumference. All models adjusted for sociodemographic characteristics, time trends, and temperature. We found that higher NO2 was negatively associated with all ultrasound parameters. The critical window differed depending on the parameter and when it was assessed. For example, for BPD measured after week 31, the critical exposure window appeared to be weeks 15-25; 10-parts-per-billion higher NO2 sustained from conception to the time of measurement was associated with a lower mean z score of -0.11 (95% CI: -0.17, -0.05). Our findings indicate that reducing traffic emissions is one potential avenue to improving fetal and offspring health.

Baseline risk and marginal willingness to pay for health risk reduction

Empirical results presented in this paper suggest that parents' marginal willingness to pay (MWTP) for a reduction in morbidity risk from heart disease is inversely related to baseline risk (i.e., the amount of risk initially faced) both for themselves and for their children. For instance, a 40% reduction from the mean of baseline risk results in an increase in MWTP by 70% or more. Thus, estimates of monetary benefits of public programs to reduce heart disease risk would be understated if the standard practice is followed of evaluating MWTP at initial risk levels and then multiplying this value by the number of cases avoided. Estimates are supported by: (1) unique quantitative information on perceptions of the risk of getting heart disease that allow baseline risk to be defined at an individual level and (2) improved econometric procedures to control for well-known difficulties associated with stated preference data.