A geographic regression model for medical statistics

Abstract

A method for modeling geographic processes using cencus-type data is introduced in an analysis of male and female lung cancer mortality rates. The study area comprises the counties in those states which abut the Gulf of Mexico and the southeast Atlantic Coast of the United States. A spatially autoregressive model is used to estimate the strength of the univariate relationship between both the male and female lung cancer mortality rate in a county and in the respective lung cancer rates in the first to fifth order adjacent counties. The results show that the male lung cancer exhibits spatial autocorrelation while female lung cancer does not, and that the female data exhibit a spatial trend while the male data do not. These findings suggest that factors which vary at the regional scale play a greater role in the etiology of female lung cancer and that factors that vary at the neighborhood scale play a greater role in the etiology of male lung cancer.