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Geographic risk modeling of childhood cancer relative to county-level crops, hazardous air pollutants and population density characteristics in Texas.

Thompson JA, Carozza SE, Zhu L - Environ Health (2008)

Bottom Line: The risk for Hodgkin lymphoma appeared to be reduced in areas of rapidly growing population.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.

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Affiliation: Department of Large Animal Clinical Science, Texas A&M University, College Station, Texas 77843-4475, USA. jthompson@cvm.tamu.edu

ABSTRACT

Background: 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. 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.

Methods: A 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.

Results: There 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.

Conclusion: The 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.

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Study-specific temporal effects. 4a. Leukemias and lymphomas. 4b. Nervous tissue tumors. 4c. Other tumors. International Classification of Childhood Cancer (ICCC3) Classification Key. Ia. Acute Lymphoid leukemias (ALL). Ib. Acute myeloid leukemias (AML). Ic, d, e, Other leukemias. IIa. Hodgkin lymphoma. IIb, c, d, e. Non-Hodgkin lymphoma. IIIa. Ependymoma and choroid plexus tumor. IIIb. Astrocytomas. IIIc. Intracranial and intraspinal embryonal tumors. IIId. Other gliomas. IIIe, f Other CNS tumors. IV. Neuroblastoma and other peripheral nervous cell tumors. V Retinoblastoma. VI. Renal tumors. VII. Hepatic tumors. VIII. Malignant bone tumors. IX. Soft tissue and other extraosseous sarcomas. X. Germ cell tumors, trophoblastic tumors, and neoplasms of gonads. XI. Other malignant epithelial neoplasms and malignant melanomas. XII. Other and unspecified malignant neoplasms (including uncoded).
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Figure 4: Study-specific temporal effects. 4a. Leukemias and lymphomas. 4b. Nervous tissue tumors. 4c. Other tumors. International Classification of Childhood Cancer (ICCC3) Classification Key. Ia. Acute Lymphoid leukemias (ALL). Ib. Acute myeloid leukemias (AML). Ic, d, e, Other leukemias. IIa. Hodgkin lymphoma. IIb, c, d, e. Non-Hodgkin lymphoma. IIIa. Ependymoma and choroid plexus tumor. IIIb. Astrocytomas. IIIc. Intracranial and intraspinal embryonal tumors. IIId. Other gliomas. IIIe, f Other CNS tumors. IV. Neuroblastoma and other peripheral nervous cell tumors. V Retinoblastoma. VI. Renal tumors. VII. Hepatic tumors. VIII. Malignant bone tumors. IX. Soft tissue and other extraosseous sarcomas. X. Germ cell tumors, trophoblastic tumors, and neoplasms of gonads. XI. Other malignant epithelial neoplasms and malignant melanomas. XII. Other and unspecified malignant neoplasms (including uncoded).

Mentions: Children born January 1, 1990 were followed for 13 years and children born January 1, 2002 for one year. The counts of incident cases by histotype and year are listed in Table 1. Independent random walk priors were used to allow autoregressive temporal smoothing for each histotype. Temporal trends were readily identifiable and they varied considerably among histotypes. Two cancers with the greatest decrease in risk over the period of study were malignant bone tumors (e.g. osteosarcoma) and Hodgkin lymphoma. Two cancers with relatively steady risk over the study period were AML and "other leukemias." The temporal smoothing parameters used in the study are presented in Figure 4.


Geographic risk modeling of childhood cancer relative to county-level crops, hazardous air pollutants and population density characteristics in Texas.

Thompson JA, Carozza SE, Zhu L - Environ Health (2008)

Study-specific temporal effects. 4a. Leukemias and lymphomas. 4b. Nervous tissue tumors. 4c. Other tumors. International Classification of Childhood Cancer (ICCC3) Classification Key. Ia. Acute Lymphoid leukemias (ALL). Ib. Acute myeloid leukemias (AML). Ic, d, e, Other leukemias. IIa. Hodgkin lymphoma. IIb, c, d, e. Non-Hodgkin lymphoma. IIIa. Ependymoma and choroid plexus tumor. IIIb. Astrocytomas. IIIc. Intracranial and intraspinal embryonal tumors. IIId. Other gliomas. IIIe, f Other CNS tumors. IV. Neuroblastoma and other peripheral nervous cell tumors. V Retinoblastoma. VI. Renal tumors. VII. Hepatic tumors. VIII. Malignant bone tumors. IX. Soft tissue and other extraosseous sarcomas. X. Germ cell tumors, trophoblastic tumors, and neoplasms of gonads. XI. Other malignant epithelial neoplasms and malignant melanomas. XII. Other and unspecified malignant neoplasms (including uncoded).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2572154&req=5

Figure 4: Study-specific temporal effects. 4a. Leukemias and lymphomas. 4b. Nervous tissue tumors. 4c. Other tumors. International Classification of Childhood Cancer (ICCC3) Classification Key. Ia. Acute Lymphoid leukemias (ALL). Ib. Acute myeloid leukemias (AML). Ic, d, e, Other leukemias. IIa. Hodgkin lymphoma. IIb, c, d, e. Non-Hodgkin lymphoma. IIIa. Ependymoma and choroid plexus tumor. IIIb. Astrocytomas. IIIc. Intracranial and intraspinal embryonal tumors. IIId. Other gliomas. IIIe, f Other CNS tumors. IV. Neuroblastoma and other peripheral nervous cell tumors. V Retinoblastoma. VI. Renal tumors. VII. Hepatic tumors. VIII. Malignant bone tumors. IX. Soft tissue and other extraosseous sarcomas. X. Germ cell tumors, trophoblastic tumors, and neoplasms of gonads. XI. Other malignant epithelial neoplasms and malignant melanomas. XII. Other and unspecified malignant neoplasms (including uncoded).
Mentions: Children born January 1, 1990 were followed for 13 years and children born January 1, 2002 for one year. The counts of incident cases by histotype and year are listed in Table 1. Independent random walk priors were used to allow autoregressive temporal smoothing for each histotype. Temporal trends were readily identifiable and they varied considerably among histotypes. Two cancers with the greatest decrease in risk over the period of study were malignant bone tumors (e.g. osteosarcoma) and Hodgkin lymphoma. Two cancers with relatively steady risk over the study period were AML and "other leukemias." The temporal smoothing parameters used in the study are presented in Figure 4.

Bottom Line: The risk for Hodgkin lymphoma appeared to be reduced in areas of rapidly growing population.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.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Large Animal Clinical Science, Texas A&M University, College Station, Texas 77843-4475, USA. jthompson@cvm.tamu.edu

ABSTRACT

Background: 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. 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.

Methods: A 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.

Results: There 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.

Conclusion: The 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.

Show MeSH
Related in: MedlinePlus