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Table 3 β-Coefficients for final ordinary least squares regression model including meteorological parameters, confounders, pollution indices, and the significant interaction term*.

From: Correlations between meteorological parameters and prostate cancer

Predictor Coefficient P
Constant 460.30 <0.001
Heart disease mortality -0.19781 <0.001
Average annual unemployment rate - 1.5025 <0.001
Acres of land used to grow crops -0.00001040 0.188
Shortwave radiation - 33.10 0.011
Heating degree days - 0.008341 <0.001
Average annual snowfall 0.00789 0.636
Average annual rainfall -0.11708 <0.001
Heating degree days squared 0.00000157 <0.001
Shortwave radiation squared 0.9851 0.021
Interaction term (Crop)(Snow) 0.00000046 <0.001
  1. *This model explained approximately 18.5% of the variation in the county level average annual incidence rate of prostate cancer (R2 = 0.185) and had the lowest AIC in the GWR analysis.