Correlations between meteorological parameters and prostate cancer

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

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

*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.

ISSN: 1476-072X