The Association Between Exposure to Traffic-Related Air Pollution During Pregnancy and Children's Health Outcomes in the San Joaquin Valley of California: An Example of Causal Inference Methods

Ambient air pollution and traffic exposure are widely recognized as an important public health concern. This research aims to investigate the association between traffic-related air pollution exposure during pregnancy and two important public health outcomes: pulmonary function in asthmatic children and term low birth weight. Asthma is the leading cause of childhood morbidity and term low birth weight is an important predictor of infant mortality. The period of pregnancy may be a critical time during which exposures may affect these health outcomes. Two study populations are used in this dissertation: the Fresno Asthmatic Children and Environment Study - Lifetime Exposure (FACES-LITE) and the Study of Air pollution, Genetics and the Early life events (SAGE). FACES-LITE is a longitudinal cohort of asthmatic children, aged 6-11 at baseline, with periodic pulmonary function tests and exposure assessment of ambient air pollutants during pregnancy in Fresno, California. SAGE is a study of birth records from four counties in the San Joaquin Valley of California from 2000-2006 linked to traffic density metrics based on the geo-coded residences of the mother at birth. For both studies, causal inference methods were used to estimate the association between exposure to traffic-related air pollution during pregnancy and these child health outcomes. Specifically, targeted maximum likelihood estimation (TMLE) was used to obtain the counterfactual marginal effect of traffic-related air pollution exposure during pregnancy on pulmonary function and term low birth weight. In other words, the predicted outcomes were compared had everyone been exposed to specific levels of air pollution during pregnancy. The results of the TMLE for FACES-LITE found that above-median levels of ambient NO2 exposure during the first and second trimesters were associated with deficits in pulmonary function for all age groups. The SAGE analysis showed the highest quartile of traffic density exposure was associated with significantly higher term low birth weight compared to the lowest quartile; however, there was no evidence of a monotonic exposure-response relation. In general, the studies presented in this dissertation suggest that traffic-related air pollution exposure during pregnancy may be associated with pulmonary function deficits in children with asthma, as well as with an increased risk for term low birth weight. These analyses represent the first application of TMLE to the study of air pollution and child health outcomes. In addition to their novelty, these causal inference methods are unique in that they offer easily interpretable parameters with important public health implications and unlike traditional regression methods, they do not assume arbitrary models. The analysis of the FACES-LITE study contributes to the subject-matter and supports earlier work on the association of ambient air pollution exposure during pregnancy and lung function in children by using the repeated measures of lung function. In contrast, the SAGE analysis focused on a methodological approach using causal methods and contextual variables. For that reason, I included only one exposure metric and one birth outcome for a demonstration of these methods. This subject-matter analysis will be extended in future analyses to further characterize the complexity of the exposure and any additional potential confounders and effect modifiers