Table 5 Multivariable regression analysis on the proportion of malignant tumors occurrence in prefecture-level regions.

From: Geographical analysis of malignant tumor incidence and treatment in China

Variable

Respiratory system malignant tumor

Digestive system malignant tumor

Breast system malignant tumor

Reproductive system malignant tumor

Urinary system malignant tumor

Endocrine system malignant tumor

Constant

0.150***

(0.003)

0.158***

(0.003)

0.107***

(0.002)

0.074***

(0.004)

0.100***

(0.004)

0.030***

(0.001)

Average elevation

    

0.020*

(0.009)

− 0.007***

(0.002)

Topographic variation

      

Average temperature in January

− 0.016***

(0.003)

− 0.009*

(0.004)

   

− 0.005**

(0.002)

Average temperature in July

      

Annual precipitation

− 0.026***

(0.004)

   

− 0.024**

(0.008)

0.012***

(0.003)

Average annual relative humidity

 

0.019***

(0.004)

  

0.005

(0.004)

− 0.003

(0.002)

Annual sunshine hours

 

0.014***

(0.003)

  

0.011*

(0.005)

0.006**

(0.002)

Average annual wind speed

  

0.005***

(0.001)

0.005*

(0.002)

  

Income level

0.013***

(0.003)

 

0.004

(0.002)

 

− 0.001

(0.004)

0.006***

(0.001)

Urbanization rate

  

0.016**

(0.003)

− 0.012

(0.007)

− 0.008

(0.005)

 

Education level

0.004

(0.002)

  

− 0.003

(0.002)

− 0.006**

(0.002)

0.003***

(0.001)

Public health Resources

 

− 0.006***

(0.001)

− 0.008***

(0.001)

− 0.008***

(0.002)

0.011*

(0.005)

 

Water pollution

 

0.003*

(0.002)

    

Air pollution

  

0.005**

(0.002)

 

− 0.004

(0.003)

 

Goodness of fit (R2)

0.36

0.14

0.36

0.19

0.55

0.41

Sample size

294

294

294

294

294

294

  1. Gender and age factors were removed, and stepwise regression analysis was performed. In each step, the least significant influencing factor was removed until all influencing factors had a p value less than 0.1. ***, **, and * represent the significance of the influencing factors at the 0.1%, 1%, and 5% levels, respectively.