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. 2022 Jun 28;10(4):200–206. doi: 10.1016/j.prnil.2022.06.004

Table 4.

Binomial logistic regression analysis between BPH marker drugs and climate variables

Categorical climate variables BPH marker drugs McFadden R2 Likelihood ratio B with 95% CI Wald tatistics Constant term with 95% CI Odds ratio with 95% CI
Temperature (0 or 1) Uroselective α1 receptor blockers 0.1549 10.0925 −0.0005 6.9404 7.1405 0.9995
p = 0.0015∗∗ (−0.0008 ∼−0.0001) p = 0.0084∗∗ (1.8307 ∼ 12.4503) (0.9992 ∼ 0.9999)
Precipitation (0 or 1) 0.0006 0.0379 0.00002 0.0379 −0.3021 1.0000
p = 0.8457 (−0.0002 ∼0.0002) p = 0.8457 (−3.8239 ∼ 3.2196) (0.9998 ∼ 1.0002)
Relative humidity (0 or 1) 0.0585 3.8007 0.0002 3.8007 −3.6524 1.0002
p = 0.0512 (−0.00002 ∼0.0005) p = 0.0512 (−7.8103 ∼ 0.5055) (1.0000 ∼ 1.0005)
Temperature (0 or 1) Dutasteride 0.0541 3.5233 −0.0010 3.0943 2.4367 0.9990
p = 0.0605 (−0.0022 ∼0.0001) p = 0.0786 (−0.2746 ∼ 5.1481) (0.9978 ∼ 1.0001)
Precipitation (0 or 1) 0.0081 0.5259 −0.0004 0.5159 0.9191 0.9996
p = 0.4684 (−0.0014 ∼0.0007) p = 0.4726 (−1.5383 ∼ 3.3764) (0.9986 ∼ 1.0007)
Relative humidity (0 or 1) 0.0866 5.6262 0.0014 4.5293 −3.0598 1.0014
p = 0.0177∗ (0.0001 ∼ 0.0027) p = 0.0333∗ (−6.0078 ∼ −0.1119) (1.0001 ∼ 1.0027)

CI, confidence interval; B, regression coefficient; The median in the sorted climate values of 47 prefectures was used as cut-off value to categorize climate data into low (0) and high (1) categories (16.8°C for temperature, 1,760 mm for precipitation, and 71% for relative humidity).