We propose to study how cumulative environmental pollution during pregnancy can affect whether the baby is born prematurely. We will also find out if the potential effects of this pollution on preterm birth are stronger for women of different race/ethnicity or women of different socioeconomic status and whether pollution contributes to disparities in preterm birth.
Researchers and policy makers are concerned about the persistence of preterm birth disparities in the US, particularly since conditions at birth influence health throughout the life course. These disparities remain largely unexplained by genetics, access to prenatal care, or education, and thus point to the importance of environmental and social factors. Yet, there are data gaps in the assessment of environmental exposure in diverse populations and how they affect preterm birth. This project will examine how exposures to cumulative and independent pollutants affect preterm birth, and whether these adverse effects are different by race/ethnicity and socioeconomic status at the individual and neighborhood level. We propose to take advantage of a unique and new California state-wide database based on merged birth certificates/vital statistics from the State of California, mother and child patient discharge medical records from the Office of Statewide Health Planning and Development in California, the CalEnviroScreen from the Department of Public Health of the State of California, and demographic and socioeconomic data from the U.S. Census Bureau. Several studies have examined environmental exposure and social factors with regard to preterm birth, though never on this scale and never with so many cumulative exposures. We hypothesize that exposure to cumulative pollution burden may have an association with preterm birth and that these associations may differ by race and socioeconomic status. Our research proposal will use maternal and infant birth data for all births in CA, with a study size of 2.5 million, giving us more than sufficient power and geographic coverage to investigate multiple and important individual- level and place-based risk factors (environmental and social) and determine how they modify one another and contribute to both PTB overall and disparities in PTB. We will use a novel statistical technique, quantile regression, which allows for different effect estimates at different gestational ages and does not assume a uniform relationship only on the mean of the distribution. This could also illuminate a population-level intervention (e.g., lowering pollution burden) that could shift both the mean and have a greater effect on those at highest risk. The ethnic and economic diversity of our study population provides a unique opportunity to examine the range of prenatal exposures to pollution burden and their effects on preterm birth and how the associations may differ by race/ethnicity and SES. This study will provide a comprehensive and cumulative investigation of environmental pollution and preterm birth in a large and diverse study population and the contribution of environmental contaminants to disparities in preterm birth.