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Table 1 Results of the global OLS regression model

From: Do the risk factors for type 2 diabetes mellitus vary by location? A spatial analysis of health insurance claims in Northeastern Germany using kernel density estimation and geographically weighted regression

Variable

Coefficient

VIF

Intercept

2.259540***

 

Persons aged 65–79 (%)

0.027251***

1.656689

Persons aged 80 and older (%)

0.010704**

1.650654

Unemployed persons aged 55–65 (%)

0.013354***

2.593295

Employed persons (%)

−0.006181**

1.602619

Mean income tax

0.000780**

2.272369

Non-married couples (%)

0.014524*

1.452730

Adjusted R2

0.44

 

AICc

−313

 

Global Moran’s I of residuals

I = 0.264 (p < 0.001)

 
  1. Significance levels: * ≤ 0.05; ** ≤ 0.01; *** ≤ 0.001
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International Journal of Health Geographics

ISSN: 1476-072X