Implementing a weighted spatial smoothing algorithm to identify a lung cancer belt in the United States.
Lung cancer is the leading cause of cancer death in the United States, but a large fraction of cases is preventable. We use a spatial smoothing algorithm to identify a geographic pattern of high lung cancer mortality, primarily in the Southeast, which we call a lung cancer belt. Disease belts are an effective mode for conveying patterns of high incidence or mortality; formally defining this lung cancer belt may encourage increased public dialogue and more focused research. Public health officials could complement existing population lung cancer data with this information to help inform resource allocation decisions.
Department of Biostatistics and Epidemiology, College of Public Health, East Tennessee State University, Johnson City, TN 37614, USA. blackley@goldmail.etsu.edu
David
D
Blackley
Shimin
S
Zheng
Winn
W
Ketchum
D000465:Algorithms; D006801:Humans; D015994:Incidence; D008175:Lung Neoplasms / Q000453:epidemiology*; D040841:Resource Allocation / Q000458:organization & administration; D015144:Southeastern United States / Q000453:epidemiology; D015996:Survival Rate