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Geographic boundaries in breast, lung and colorectal cancers in relation to exposure to air toxics in Long Island, New York.

Jacquez GM, Greiling DA - Int J Health Geogr (2003)

Bottom Line: In this second paper, we compare patterns in standardized morbidity ratios (SMR values), calculated from New York State Department of Health (NYSDOH) data, to geographic patterns in overall predicted risk (OPR) from air toxics using exposures estimated in the USEPA National Air Toxics Assessment database.RESULTS: We identified significant geographic boundaries in SMR and OPR.We found little or no association between the SMR of colorectal and breast cancers and the OPR for each cancer from exposure to the air toxics.

View Article: PubMed Central - HTML - PubMed

Affiliation: TerraSeer, Inc, Ann Arbor, MI, USA. dunrie@biomedware.com

ABSTRACT
BACKGROUND: This two-part study employs several statistical techniques to evaluate the geographic distribution of breast cancer in females and colorectal and lung cancers in males and females in Nassau, Queens, and Suffolk counties, New York, USA. In this second paper, we compare patterns in standardized morbidity ratios (SMR values), calculated from New York State Department of Health (NYSDOH) data, to geographic patterns in overall predicted risk (OPR) from air toxics using exposures estimated in the USEPA National Air Toxics Assessment database. RESULTS: We identified significant geographic boundaries in SMR and OPR. We found little or no association between the SMR of colorectal and breast cancers and the OPR for each cancer from exposure to the air toxics. We did find boundaries in male and female lung cancer SMR and boundaries in lung cancer OPR to be closer to one another than expected. CONCLUSION: While consistent with a causal relationship between air toxics and lung cancer incidence, the boundary analysis does not demonstrate the existence of a causal relationship. However, now that the areas of overlap between boundaries in lung cancer incidence and potential airborne exposures have been identified, we can begin to evaluate local- as well as large-scale determinants of lung cancer.

No MeSH data available.


Related in: MedlinePlus

Male lung cancer incidence showing local boundaries (orange). The blue outlines are the ZIP code edges. The fill in the ZIP code areas indicates the SMR for male lung cancer, with darker purple regions having higher SMR, white regions having SMR near 1, and darker green regions having lower SMR. The boundaries shown in orange indicate those ZIP code edges with large changes in cancer incidence.
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Figure 11: Male lung cancer incidence showing local boundaries (orange). The blue outlines are the ZIP code edges. The fill in the ZIP code areas indicates the SMR for male lung cancer, with darker purple regions having higher SMR, white regions having SMR near 1, and darker green regions having lower SMR. The boundaries shown in orange indicate those ZIP code edges with large changes in cancer incidence.

Mentions: Boundaries in male lung cancer incidence are shown in Figure 11. These are expected to indicate not only the margins of the clusters identified under the local Moran test [1], but also the margins of singleton ZIP codes with SMR values that differ substantially from their neighbors. It is interesting to observe the high singleton ZIP codes (Rockaways, Brightwaters and Roosevelt) are along the southern shore.


Geographic boundaries in breast, lung and colorectal cancers in relation to exposure to air toxics in Long Island, New York.

Jacquez GM, Greiling DA - Int J Health Geogr (2003)

Male lung cancer incidence showing local boundaries (orange). The blue outlines are the ZIP code edges. The fill in the ZIP code areas indicates the SMR for male lung cancer, with darker purple regions having higher SMR, white regions having SMR near 1, and darker green regions having lower SMR. The boundaries shown in orange indicate those ZIP code edges with large changes in cancer incidence.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC151677&req=5

Figure 11: Male lung cancer incidence showing local boundaries (orange). The blue outlines are the ZIP code edges. The fill in the ZIP code areas indicates the SMR for male lung cancer, with darker purple regions having higher SMR, white regions having SMR near 1, and darker green regions having lower SMR. The boundaries shown in orange indicate those ZIP code edges with large changes in cancer incidence.
Mentions: Boundaries in male lung cancer incidence are shown in Figure 11. These are expected to indicate not only the margins of the clusters identified under the local Moran test [1], but also the margins of singleton ZIP codes with SMR values that differ substantially from their neighbors. It is interesting to observe the high singleton ZIP codes (Rockaways, Brightwaters and Roosevelt) are along the southern shore.

Bottom Line: In this second paper, we compare patterns in standardized morbidity ratios (SMR values), calculated from New York State Department of Health (NYSDOH) data, to geographic patterns in overall predicted risk (OPR) from air toxics using exposures estimated in the USEPA National Air Toxics Assessment database.RESULTS: We identified significant geographic boundaries in SMR and OPR.We found little or no association between the SMR of colorectal and breast cancers and the OPR for each cancer from exposure to the air toxics.

View Article: PubMed Central - HTML - PubMed

Affiliation: TerraSeer, Inc, Ann Arbor, MI, USA. dunrie@biomedware.com

ABSTRACT
BACKGROUND: This two-part study employs several statistical techniques to evaluate the geographic distribution of breast cancer in females and colorectal and lung cancers in males and females in Nassau, Queens, and Suffolk counties, New York, USA. In this second paper, we compare patterns in standardized morbidity ratios (SMR values), calculated from New York State Department of Health (NYSDOH) data, to geographic patterns in overall predicted risk (OPR) from air toxics using exposures estimated in the USEPA National Air Toxics Assessment database. RESULTS: We identified significant geographic boundaries in SMR and OPR. We found little or no association between the SMR of colorectal and breast cancers and the OPR for each cancer from exposure to the air toxics. We did find boundaries in male and female lung cancer SMR and boundaries in lung cancer OPR to be closer to one another than expected. CONCLUSION: While consistent with a causal relationship between air toxics and lung cancer incidence, the boundary analysis does not demonstrate the existence of a causal relationship. However, now that the areas of overlap between boundaries in lung cancer incidence and potential airborne exposures have been identified, we can begin to evaluate local- as well as large-scale determinants of lung cancer.

No MeSH data available.


Related in: MedlinePlus