Table 1.

Summary results of ordinary least square (OLS) and geographically weighted ordinary least squares regression (GW-OLS) models.

	OLS		GW-OLS
	Estimate	Pr( >|t|)	Min	1st Qu	Median	3rd Qu	Max
Intercept	10.02	< 2e−16***	8.40	9.46	10.02	10.82	11.57
Obesity	0.82	< 2e−16***	0.12	0.67	0.87	1.05	1.65
Physical inactivity	0.85	< 2e−16***	− 0.12	0.28	0.58	0.85	1.22
Access to exercise	0.20	5.36e−11***	− 0.56	− 0.09	0.02	0.16	0.60
Food environment index	− 0.02	0.662NS	− 1.02	− 0.29	− 0.14	0.03	0.50
Poverty	0.18	1.66e−06***	− 0.58	− 0.11	0.02	0.16	0.58
Education	0.65	2e−16***	− 0.40	0.14	0.35	0.58	1.21
R2		0.665					0.791
Adjusted-R2		0.665					0.770
AIC		11,035.6					9978.4

OLS: ordinary least squares, GW-OLS, geographically weighted OLS regression, AIC: Akaike's information criterion.

***p < 0.001, NS: not significant.