Abstract
BackgroundChildhood cancer has been linked to a variety of environmental factors, including agricultural activities, industrial pollutants and population mixing, but etiologic studies have often been inconclusive or inconsistent when considering specific cancer types. More specific exposure assessments are needed. It would be helpful to optimize future studies to incorporate knowledge of high-risk locations or geographic risk patterns. The objective of this study was to evaluate potential geographic risk patterns in Texas accounting for the possibility that multiple cancers may have similar geographic risks patterns.MethodsA spatio-temporal risk modeling approach was used, whereby 19 childhood cancer types were modeled as potentially correlated within county-years. The standard morbidity ratios were modeled as functions of intensive crop production, intensive release of hazardous air pollutants, population density, and rapid population growth.ResultsThere was supportive evidence for elevated risks for germ cell tumors and "other" gliomas in areas of intense cropping and for hepatic tumors in areas of intense release of hazardous air pollutants. The risk for Hodgkin lymphoma appeared to be reduced in areas of rapidly growing population. Elevated spatial risks included four cancer histotypes, "other" leukemias, Central Nervous System (CNS) embryonal tumors, CNS other gliomas and hepatic tumors with greater than 95% likelihood of elevated risks in at least one county.ConclusionThe Bayesian implementation of the Multivariate Conditional Autoregressive model provided a flexible approach to the spatial modeling of multiple childhood cancer histotypes. The current study identified geographic factors supporting more focused studies of germ cell tumors and "other" gliomas in areas of intense cropping, hepatic cancer near Hazardous Air Pollutant (HAP) release facilities and specific locations with increased risks for CNS embryonal tumors and for "other" leukemias. Further study should be performed to evaluate potentially lower risk for Hodgkin lymphoma and malignant bone tumors in counties with rapidly growing population.
Highlights
Childhood cancer has been linked to a variety of environmental factors, including agricultural activities, industrial pollutants and population mixing, but etiologic studies have often been inconclusive or inconsistent when considering specific cancer types
The Texas Cancer Registry (TCR) is an active member of the North American Association of Central Cancer Registries (NAACCR) and follows the quality control guidelines and standards established by NAACCR
Some pooling of very rare cancer types was performed as follows: childhood cancer subgroups Ic, Id and Ie were pooled and assigned the name "other leukemias"; subgroups IIb, IIc, IId and IIe were pooled into a single group and were labeled "non-Hodgkin lymphoma"; and subtypes IIIe, and IIIf were pooled into a group called "other Central Nervous System (CNS) tumors." The database provided records for 3718 cancer cases distributed among 19 histotype groups and 3,805,745 total births
Summary
Childhood cancer has been linked to a variety of environmental factors, including agricultural activities, industrial pollutants and population mixing, but etiologic studies have often been inconclusive or inconsistent when considering specific cancer types. Bayesian methods have begun to predominate disease mapping applications[1]. This emergence has been largely attributed to advances in computer hardware that have enabled Markov Chain Monte Carlo implementations of relatively complex Bayesian models[2] and recently developed software has made these techniques readily available to health researchers[3]. One of the potential advantages for performing the risk estimation in a Bayesian approach is that the inference is based on parameter or risk certainty and the risk can apply to the lower organizational unit, such as individuals, in a hierarchal Bayes approach [1]. The risk estimate would apply to an individual considering alternative living locations
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