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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