Table 7.

Linear models with infection and mortality rates as response variables for NHB.

Linear regression models with infection rate in NHB population as a response variable
	Preliminary model			Final model
	β(95%CI)	Pr(> t)	VIF	β(95%CI)	Pr(> |t|)	VIF
(Intercept)	1.10 (0.42, 1.79)	0.002**		2.12 (1.42, 2.84)	<0.01***
BMI30+	0.04 (−0.04, 0.13)	0.309	97.03	0.05 (0.04, 0.06)	<0.01***	1.00
Poverty	0.02 (−0.01, 0.05)	0.169	1.10	−0.01 (−0.04, 0.02)	0.39	1.00
Diabetes	0.02 (−0.06, 0.10)	0.695	101.10
Age60+	−0.20 (−0.34, −0.05)	0.009***	164.01
HBP	0.16 (0.06, 0.26)	0.003***	127.51
CVD	−0.02 (−0.09, 0.05)	0.514	58.27
	$R^2=0.81,R_{adj}^2=0.77,n=38$			$R^2=0.66,R_{adj}^2=0.64,n=40$
	F(6, 31) = 17.51, p <0.01***			F(2, 37) = 37.89, p <0.01***
Linear regression models with mortality rate in NHB population as a response variable
	Preliminary model			Final model
	β (95%CI)	Pr (> t)	VIF	β (95%CI)	Pr (> |t|)	VIF
(Intercept)	1.26 (0.36, 2.17)	0.008***		2.16 (1.32, 3.01)	<0.01***
BMI30+	0.10 (−0.01, 0.22)	0.073*	97.03	0.06 (0.04, 0.07)	<0.01***	1.00
Poverty	0.00 (−0.04, 0.04)	0.921	1.10	−0.02 (−0.05, 0.12)	0.191	1.00
Diabetes	−0.04 (−0.15, 0.06)	439	101.10
Age60+	−0.25 (−0.45, −0.06)	0.011**	164.01
HBP	0.17 (−0.03, 0.30)	0.017**	127.51
CVD	0.03 (−0.06, 0.12)	0.521	58.27
	$R^2=0.77,R_{adj}^2=0.73,n=38$			$R^2=0.67,R_{adj}^2=0.65,n=40$
	F(6, 31) = 17.51, p <0.01***			F(2, 37) = 199.9, p <0.01***

The first column shows preliminary model along with the VIFs for each explanatory variable. The second column indicates the model obtained using maximum VIF elimination algorithm.

^“*”significance at p < 0.1,

^“**” significance at p < 0.05, and

^“***”significance at p < 0.01.