UCLA

The etiology of childhood cancer remains unexplained in a majority of cases. Cancer is the leading cause of death by disease in children in the US. Ionizing radiation and certain genetic abnormalities have been well-established as risk factors for childhood cancers. In addition, several environmental factors including pesticides and air toxics have been implicated in previous studies. Utilizing a statewide population-based case-control study in California, we examined the effects of ambient agricultural pesticides and industrial dichloromethane releases on childhood cancers. Cases less than age six were obtained from the California Cancer Registry diagnosed between 1988-2012 and linked to birth certificates. Controls were then randomly selected from birth certificates and frequency matched by year of birth. Pesticide exposure estimates were obtained using a sophisticated geographic information system (GIS) based program. The GIS-based Residential Ambient Pesticide Estimation System (GRAPES) combined agricultural Pesticide Use Reports (PUR), Land Use Surveys (LUR), and the Public Land Survey System (PLSS) to create estimates based on distance to the child’s residence at birth. We analyzed the effects of individual pesticides on childhood acute lymphoblastic leukemia (ALL) using semi-Bayesian hierarchical logistic modeling. Our findings suggest an increased risk of childhood ALL among those exposed to any carcinogenic pesticides, or 2,6-dinitroanilines, anilides, ureas classes of pesticides, and specifically diuron, phosmet, kresoxim-methyl, and propanil.

Additionally, we investigated the effects of dichloromethane exposure among children born to mothers living in proximity to industrial facilities. Using the Environmental Protection Agency’s (EPA) Toxics Release Inventory (TRI), we estimated exposure to dichloromethane based on distance from the residence to the facility using three exposure modeling methods. We observed elevated risks in germ cell tumors, particularly teratomas, and a possible increase in risk for ALL and acute myeloid leukemias (AML).

Lastly, we explored a possible explanation for the null and often inverse associations seen in maternal smoking and childhood ALL. We simulated populations based on priors obtained from the Danish National Registries and estimated the effect of a possible survivor bias, also known as ‘live-birth bias,’ to determine the strength of the bias. Based on our results, it is unlikely that this survivor bias can solely explain the inconsistent associations seen with maternal smoking.